From daf8522ee120378229d5df2fa7b6c0db007316e4 Mon Sep 17 00:00:00 2001
From: Tadd Bindas <taddbindas@gmail.com>
Date: Tue, 8 Sep 2026 22:47:43 -0400
Subject: [PATCH 1/6] =?UTF-8?q?spec:=20gridded=20(ISIMIP=20DDM30)=20routin?=
 =?UTF-8?q?g=20as=20a=20data=20source=20=E2=80=94=20design?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EqnrtmU91yzuVpGnADnXLP
---
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 create mode 100644 docs/superpowers/specs/2026-09-08-ddrs-gridded-routing-design.md

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+# Gridded (ISIMIP DDM30) routing in ddrs — design
+
+**Date:** 2026-09-08
+**Source:** DeepGroundwater/ddr PR #194 ("Gridded (ISIMIP DDM30) routing:
+network, attributes, forcing, and training", merged to DDR master).
+**Status:** designed autonomously from the user's directive; assumptions are
+listed in §7 for review.
+
+## 1. What DDR #194 actually is
+
+DDR #194 is a **data-preparation** feature, not a solver change. Its PR body
+says so: "The routing engine, `mmc.py`, `merit.py` and the MERIT/Lynker paths
+are untouched. Everything here is additive." It adds:
+
+- `ddr_engine.gridded` — builds a river network from the ISIMIP DDM30 0.5°
+  D8 grid, aggregates 25 attributes from native rasters onto cells, regrids
+  per-catchment Q′ onto cells (mass-conserving area weights), splits cells
+  into Courant≈1 sub-reaches, and validates the products.
+- Data products keyed on the **cell id** (`row·720 + col`, row 0 at 55.75°S):
+  an attributes NetCDF in the `merit_global_attributes_v2` layout (`COMID` =
+  cell id), a Q′ icechunk store (`Qr(divide_id, time)`, `divide_id` = cell id),
+  and a **sub-reach adjacency zarr** carrying `order` (node id =
+  `cell·1000 + sub`), `parent_cell`, `indices_0/1`, `values`, `length_m`,
+  `slope`, `lat`, `lon`.
+- Two trainers (`examples/juniata_gridded/train_gridded.py`, `train_conus.py`)
+  that feed those products to the unchanged `dmc` router, plus a 1.6 MB
+  self-contained Juniata bundle.
+
+ddrs has no `engine/` module and the user asked to keep it that way: **ddrs
+consumes DDR's gridded products as another data source; it does not port the
+raster/regridding engine.**
+
+## 2. The key observation: ddrs already has the abstraction
+
+ddrs's reach subdivision (`params.subdivision`, `.claude/REACH-SUBDIVISION.md`)
+already models exactly the structure the gridded sub-reach network has:
+
+| Gridded sub-reach zarr (DDR) | ddrs subdivided store |
+|---|---|
+| `parent_cell` per row (contiguous, upstream-first) | `order` (parent COMID repeated per piece), `parent_order`, `parent_offset` |
+| attributes looked up by parent cell | `AttributesStore::open(…, &conus.parent_order)` |
+| Q′ per cell ÷ `k_per_node` | `pieces_per_row_divisor` in `MuskingumCunge::setup_inputs` |
+| gauge outlet = cell's last sub-reach | `position_lookup` = COMID → **last** row; `outlet(p) = parent_offset[p+1]−1` |
+| `length_m`, `slope` in the adjacency zarr | `length_m`, `slope` in the adjacency zarr |
+| summed-Q′ baseline sums each cell once | `upstream_comids` dedups via `parent_order` |
+
+So the whole routing/training/eval/baseline path is untouched. What is new is
+**one builder input**: a reader that turns the DDM30 sub-reach zarr into a
+`SubdividedAdjacency`, and the plumbing that lets `ddrs plan` build the managed
+stores from it.
+
+```
+  data_sources.gridded_network            data_sources.gages (CSV, `cell` col)
+  (DDM30 sub-reach zarr from DDR)                     │
+            │                                         │
+            ▼                                         │
+  adjacency::gridded::GriddedNetwork::open            │
+    order/parent_cell/indices/length_m/slope          │
+    validate: lower-tri, contiguous parents           │
+            │                                         │
+            ▼ to_subdivided()                         │
+  SubdividedAdjacency { order = parent_cell,          │
+     parent_order, parent_offset, rows, cols,         │
+     length_m, slope }                                │
+            │                                         │
+            ├──► write_conus_store_subdivided ──► <stem>_adjacency.zarr
+            │                                         │
+            └──► build_gauge_subgraphs(expanded_view, csv) ◄──┘
+                       │  (BFS upstream from the cell's OUTLET piece)
+                       ▼
+                 write_gauges_store ──► <stem>_gages_adjacency.zarr
+
+  .ddrs/adjacency/<key>/ … then MeritGagesDataset, baseline, train, eval
+  run exactly as they do for a subdivided MERIT network.
+```
+
+## 3. Changes (blast radius)
+
+| Area | Change | Tier |
+|---|---|---|
+| `src/config.rs` | `data_sources.gridded_network: Option<PathBuf>`; guards (§4) | C |
+| `src/data/store/gage_csv.rs` | `COMID` column accepts `cell` as a serde alias | C |
+| `src/adjacency/gridded.rs` (new) | `GriddedNetwork::open`, validation, `to_subdivided` | C |
+| `src/adjacency/cache.rs` | `resolve_or_build_gridded`; zarr-dir fingerprint; manifest `network_kind` | C |
+| `src/adjacency/zarr_write.rs` | writers take a `geodataset` attr value (`"ddm30"`) | C |
+| `src/cli/plan.rs`, `src/cli/sources.rs` | third `resolve_adjacency` branch; lock `gridded_network` | C |
+| `examples/juniata_gridded/` | DDR's bundle byte-identical + `ddrs.yaml` + statistics JSON + README | — |
+| `scripts/build_attribute_statistics.py` | writes the statistics sidecar for any attributes NetCDF (DDR venv) | — |
+| `scripts/snap_gridded_gauges.py` | CONUS gauge→cell snapping (DDR venv) → gauge CSV with `COMID` = cell | — |
+| `config/sources/conus-gridded.yaml` | source group for the on-disk CONUS gridded stores | D |
+| `tests/gridded_bundle.rs`, `tests/gridded_acceptance.rs` | contract + end-to-end floors | — |
+
+Not touched: `src/routing/`, `src/sparse/`, `src/nn/`, `src/training/`,
+`src/data/dataset.rs`, `src/baseline/`. Invariants 1–7 are unaffected; the
+Tier A gates still run because `cargo test` includes `ddr_sandbox_match`.
+
+## 4. Config contract
+
+```yaml
+data_sources:
+  gridded_network: examples/juniata_gridded/data/juniata_subreach_adjacency.zarr
+  attributes:      examples/juniata_gridded/data/ddm30_conus_attributes.nc
+  streamflow:      examples/juniata_gridded/data/juniata_qprime.ic
+  observations:    examples/juniata_gridded/data/juniata_obs.ic
+  gages:           examples/juniata_gridded/data/juniata_gage.csv
+```
+
+Load-time guards (all in `validate_data_sources` / `validate_subdivision`):
+
+- `gridded_network` is a **third mutually-exclusive adjacency source**:
+  with `geospatial_fabric` → error; with `conus_adjacency`/`gages_adjacency`
+  → error; with neither of the other two → managed build.
+- `geospatial_fabric_layer` with `gridded_network` → error (existing rule:
+  the layer key needs a `.gpkg` fabric).
+- `params.subdivision.enabled: true` with `gridded_network` → error. The
+  gridded graph is already subdivided upstream (DDR sizes sub-reaches from
+  celerity at mean flow); ddrs's MERIT subdivision does not apply to it and
+  the flag would be silently inert.
+
+The gauge CSV column that names the outlet is `COMID` **or** `cell` (DDR's
+gridded CSVs write `cell`). Its value is the DDM30 cell id; the gauge is read
+at that cell's most downstream sub-reach.
+
+## 5. Cache key and manifest
+
+`key = blake3(gridded_fp ∥ gages_fp ∥ "gridded" ∥ BUILDER_VERSION)[..16]`
+where `gridded_fp` hashes every file under the zarr store directory in sorted
+relative-path order (name ∥ NUL ∥ bytes). `params.subdivision` does not enter
+the key because it is rejected with `gridded_network`. The manifest reuses
+`CacheManifest` with `fabric_path`/`fabric_resolved_path` = the store dir and a
+new `network_kind: "ddm30"` field (`#[serde(default)]`, so MERIT manifests
+stay readable). Store names use the zarr stem
+(`juniata_subreach_adjacency_adjacency.zarr` is ugly; the stem's trailing
+`_adjacency` is stripped first → `juniata_subreach_adjacency.zarr` /
+`juniata_subreach_gages_adjacency.zarr`).
+
+## 6. Example bundle and tests
+
+`examples/juniata_gridded/data/` is DDR's bundle **byte-identical** (same
+readers on both sides is the point, as with `examples/juniata`), plus
+`statistics/merit_attribute_statistics_ddm30_conus_attributes.nc.json`
+generated by `scripts/build_attribute_statistics.py` (same six statistics DDR's
+`set_statistics` writes; `merit_` prefix kept because ddrs derives the sidecar
+name from a fixed template). `ddrs.yaml` mirrors `train_gridded.py`:
+`n ∈ [0.02, 0.2]`, `q ∈ [0, 1]`, `p ∈ [1, 200]` log-space, `p` default 21,
+lr 1e-3 constant, 30 epochs, rho 90, warmup 5, seed 42, CPU solver.
+
+Tests:
+
+- `tests/gridded_bundle.rs` (never skips): bundle opens through
+  `GriddedNetwork`; 27 rows / 26 edges / 4 parents with pieces 9,6,6,6; the
+  managed build into a tempdir yields a gauges store whose `01567000` subgraph
+  covers all 27 rows with `gage_idx` = the last row of cell 138445; the
+  statistics cover the ten KAN inputs; `MeritGagesDataset::open` succeeds.
+- `tests/gridded_acceptance.rs` (release-only, like `juniata_acceptance`):
+  full `train-and-test`, summed-Q′ baseline in a tight band around DDR's
+  0.594 NSE (deterministic, a cross-implementation reader check), routed NSE/KGE
+  above floors set from a measured ddrs run, routed beats baseline.
+- Unit tests in `gridded.rs` (synthetic store), `config.rs` (guards),
+  `gage_csv.rs` (`cell` alias), `cache.rs` (key sensitivity).
+
+## 7. Assumptions and known deviations from DDR
+
+1. **KAN head runs in parent (cell) space.** ddrs's subdivision design feeds
+   the head `(n_parent, F)` attributes and gathers its outputs onto the pieces.
+   DDR's gridded trainer runs the head per sub-reach with `log10_uparea`
+   recomputed per piece by accumulating `cell_area/k`. In ddrs every piece of
+   a cell shares the cell's parameters and the cell's `log10_uparea`.
+   *Why accepted:* mirroring it would change `training/forward.rs` and the
+   attribute path for every network (Tier C on the training core) to add
+   within-cell variation that DDR's own README calls minor ("with only four
+   cells the KAN has four distinct attribute rows"). Revisit only if a CONUS
+   comparison shows a material gap.
+2. **No `da_ratio` output correction.** `train_conus.py` divides predictions
+   by the cell/gauge drainage-area ratio; `train_gridded.py` (the Juniata
+   reference) does not. ddrs's `FLOW_SCALE` scales the gauge reach's own
+   lateral inflow, a different quantity, so it is *not* used to emulate it.
+   The CONUS gauge CSV carries `da_ratio` as an informational column only.
+3. **Normalisation statistics are CONUS-wide** (all 5,198 cells), matching
+   DDR's `conus.describe()`; the script uses `nanstd` (ddof 0) like DDR's
+   MERIT sidecar rather than pandas' ddof 1 — a 1e-4 relative difference.
+4. **Cells with no Q′** (21 % of CONUS sub-reach parents) get the icechunk
+   reader's 0.001 m³/s fill, DDR's gridded trainer uses 0. Irrelevant for the
+   Juniata bundle (all four cells present).
+5. **The sub-reach zarr is trusted as topologically ordered and
+   lower-triangular**; `GriddedNetwork::open` verifies `rows > cols` and
+   parent contiguity and refuses otherwise, rather than re-sorting.
+6. **The `gridded_network` key is the dispatch**, not `geodataset:`. The
+   example config sets `geodataset: ddm30` for documentation; the field is
+   still unread (as it is today for `merit`).
+
+## 8. Concerns
+
+- **Routed skill will not reproduce DDR's 0.795/0.737 exactly**: different
+  RNG windows (as with `examples/juniata`) plus deviation 1. The acceptance
+  floors are set from ddrs's own measured run, and the baseline band is the
+  DDR cross-check.
+- **Only the sub-reach form is supported.** DDR also ships an unsplit cell
+  adjacency (`ddm30_adjacency.zarr`, no `parent_cell`). It is out of scope:
+  DDR's trainers use the sub-reach store, and its README calls the cell
+  network "available for cheap iteration" only. A store without
+  `parent_cell` is rejected with a message saying so.
+- **`ddrs sources use conus-gridded` needs a gauge CSV that does not exist in
+  DDR's references yet**; `scripts/snap_gridded_gauges.py` produces it under
+  DDR's venv, following the `build_gages_2000_area_balanced.py` precedent.

From c83d4bcc13ee019f1d60c15435998024ee7fba89 Mon Sep 17 00:00:00 2001
From: Tadd Bindas <taddbindas@gmail.com>
Date: Wed, 9 Sep 2026 00:48:07 -0400
Subject: [PATCH 2/6] gridded: route DDR's ISIMIP DDM30 sub-reach network as a
 data source (mirrors ddr #194)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

`data_sources.gridded_network` names DDR's sub-reach adjacency zarr
(order, parent_cell, indices_0/1, length_m, slope). `ddrs plan` relabels it
into the existing subdivided store layout (parent = 0.5° cell, pieces = the
cell's contiguous sub-reaches, gauge read at the last piece) and cuts gauge
subgraphs from it — adjacency::gridded::GriddedNetwork +
cache::resolve_or_build_gridded. Attributes (COMID = cell) and Q'
(divide_id = cell, split across pieces by pieces_per_row_divisor) need no
change; the gauge CSV's `cell` column is a serde alias of COMID. Exclusive
with geospatial_fabric / explicit adjacency; params.subdivision.enabled is
rejected with it. No engine port: DDR's raster/regridding products are
consumed as-is.

Two bugs the gridded path exposed, both fixed:
- GageSubgraph::upstream_comids was per-piece on subdivided stores, so the
  summed-Q' baseline counted each divide m times (also MERIT subdivision).
- DDR's gridded Q' stores are Qr(time, divide_id); zarrs returns fill values
  for an out-of-range subset, so the fixed-axis reader silently read NaN.
  StreamflowStore now sniffs the axis order (dimension_names, shape fallback,
  refuses neither); fixture tests/fixtures/qr_daily_time_major.ic.

examples/juniata_gridded/: DDR's bundle byte-identical + statistics sidecar
+ ddrs.yaml + README. Baseline NSE 0.594 / KGE 0.672 (DDR 0.594 / 0.671);
routed 0.751 / 0.730 at seed 42 (seeds {42,7,123}: 0.744–0.758 / 0.728–0.732;
DDR 0.795 / 0.737 — RNG windows + ddrs's per-cell KAN head). CONUS:
config/sources/conus-gridded.yaml, config/experiments/gridded_conus.yaml,
scripts/snap_gridded_gauges.py (620 gauges, DDR's population); plan builds
5,198 cells → 91,867 sub-reaches in 0.6 s, baseline median NSE 0.354.

Tests: gridded_bundle (never skips), gridded_acceptance (release floors),
unit tests for the reader, config guards, CSV alias, upstream_comids dedup,
time-major fixture. Gates: cargo test 607/0, compare_ddr_sandbox ABSOLUTE
MATCH, juniata_acceptance unchanged (0.7903 / 0.8810 / 0.6947).

Docs: spec (with outcome), CLAUDE.md, ddrs-dev skill (change→gate row,
config guards, traps T11 time-major Qr / T12 CUDA 13.3 vs cudarc),
docs/usage/inputs-reading.md, nh-qprime-store-contract.md.

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EqnrtmU91yzuVpGnADnXLP
---
 .claude/skills/ddrs-dev/SKILL.md              |  39 ++
 .../ddrs-dev/references/build-and-env.md      |   7 +
 .claude/skills/ddrs-dev/references/config.md  |  15 +-
 .claude/skills/ddrs-dev/references/testing.md |  12 +-
 .claude/skills/ddrs-dev/references/traps.md   |  27 ++
 .gitignore                                    |   2 +
 CLAUDE.md                                     |  23 ++
 config/experiments/gridded_conus.yaml         |  94 +++++
 config/sources/conus-gridded.yaml             |  17 +
 docs/nh-qprime-store-contract.md              |   9 +-
 .../2026-09-08-ddrs-gridded-routing-design.md |  35 ++
 docs/usage/inputs-reading.md                  |  14 +-
 examples/juniata_gridded/README.md            |  87 +++++
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 ..._statistics_ddm30_conus_attributes.nc.json | 202 ++++++++++
 examples/juniata_gridded/ddrs.yaml            | 119 ++++++
 scripts/build_attribute_statistics.py         |  56 +++
 scripts/make_streamflow_fixtures.py           |  20 +-
 scripts/snap_gridded_gauges.py                | 103 +++++
 src/adjacency/cache.rs                        | 232 +++++++++++-
 src/adjacency/gridded.rs                      | 358 ++++++++++++++++++
 src/adjacency/mod.rs                          |   1 +
 src/adjacency/zarr_write.rs                   |  31 +-
 src/baseline/cache.rs                         |   2 +
 src/cli/plan.rs                               |  27 +-
 src/cli/sources.rs                            |   3 +
 src/config.rs                                 | 132 ++++++-
 src/data/store/gage_csv.rs                    |  20 +-
 src/data/store/icechunk.rs                    |  76 +++-
 src/data/store/zarr.rs                        |  28 ++
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 tests/gridded_acceptance.rs                   | 105 +++++
 tests/gridded_bundle.rs                       | 157 ++++++++
 tests/hourly_streamflow.rs                    |  34 ++
 108 files changed, 2423 insertions(+), 42 deletions(-)
 create mode 100644 config/experiments/gridded_conus.yaml
 create mode 100644 config/sources/conus-gridded.yaml
 create mode 100644 examples/juniata_gridded/README.md
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 create mode 100644 examples/juniata_gridded/data/juniata_subreach_adjacency.zarr/slope/c/0
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 create mode 100644 examples/juniata_gridded/data/juniata_subreach_adjacency.zarr/zarr.json
 create mode 100644 examples/juniata_gridded/data/statistics/merit_attribute_statistics_ddm30_conus_attributes.nc.json
 create mode 100644 examples/juniata_gridded/ddrs.yaml
 create mode 100644 scripts/build_attribute_statistics.py
 create mode 100644 scripts/snap_gridded_gauges.py
 create mode 100644 src/adjacency/gridded.rs
 create mode 100644 tests/fixtures/qr_daily_time_major.ic/manifests/1ZQAR89FZ5DSH6AJMKEG
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 create mode 100644 tests/gridded_acceptance.rs
 create mode 100644 tests/gridded_bundle.rs

diff --git a/.claude/skills/ddrs-dev/SKILL.md b/.claude/skills/ddrs-dev/SKILL.md
index 4ec04610..7f4f370c 100644
--- a/.claude/skills/ddrs-dev/SKILL.md
+++ b/.claude/skills/ddrs-dev/SKILL.md
@@ -114,6 +114,7 @@ Full commands and rationale in `references/testing.md`.
 | `config/**/*.yaml` only | **D** | `ddrs plan --config … --workspace …` exits 0, no drift |
 | `.github/workflows/ci.yml`, `.githooks/**` | — | push to a branch and let the PR run vet it; there is no local gate for workflow changes |
 | `examples/juniata/**` (bundle, config, README) | — | `cargo test --test juniata_bundle` (never skips — bundle is committed), `cargo test --release --test juniata_acceptance` (end-to-end metric floors), and `ddrs --config examples/juniata/ddrs.yaml plan` exits 0 from the repo root |
+| `src/adjacency/gridded.rs`, `resolve_or_build_gridded`, `examples/juniata_gridded/**`, the `Qr` axis-order sniff in `src/data/store/icechunk.rs` | **C** | `cargo test --test gridded_bundle` (never skips), `cargo test --test hourly_streamflow` (time-major fixture), `cargo test --release --test gridded_acceptance`, then Tier C |
 | Plotting / analysis scripts only | — | no gate |
 | `epochs`, `learning_rate`, `batch_size`, loss weights within documented ranges | — | no gate |
 
@@ -183,6 +184,44 @@ Two deviations from DDR's bundle: `data/statistics/*.json` is **committed**
 `ddrs.yaml` ignore. Regenerate the bundle in the ddr repo
 (`extract_bundle.py`), then re-copy `data/` plus the generated statistics JSON.
 
+## Gridded (ISIMIP DDM30) routing — `examples/juniata_gridded/` (2026-09-09)
+
+ddrs consumes DDR PR #194's gridded products as a **data source**; it ports
+none of the raster/regridding engine. `data_sources.gridded_network` points at
+DDR's sub-reach adjacency zarr (`order`, `parent_cell`, `indices_0/1`,
+`length_m`, `slope`) and `ddrs plan` relabels it into the existing subdivided
+store layout (parent = cell, pieces = the cell's contiguous sub-reaches, gauge
+read at the last piece) via `adjacency::gridded::GriddedNetwork` +
+`cache::resolve_or_build_gridded`. Attributes and Q′ are keyed on the cell id,
+so `parent_order` lookups and `pieces_per_row_divisor` (Q′/k) need no change.
+The gauge CSV's `cell` column is a serde alias of `COMID`. Guards: exclusive
+with `geospatial_fabric` and the explicit zarr pair; `params.subdivision.enabled`
+is rejected with it. Spec:
+`docs/superpowers/specs/2026-09-08-ddrs-gridded-routing-design.md`.
+
+```bash
+target/release/ddrs --config examples/juniata_gridded/ddrs.yaml plan
+target/release/ddrs --config examples/juniata_gridded/ddrs.yaml run --workflow train-and-test --backend cpu
+```
+
+Verified 2026-09-09 (4 cells / 27 sub-reaches, 30 epochs, CPU, ~15 s): baseline
+NSE 0.594 / KGE 0.672 (DDR 0.594 / 0.671); routed NSE 0.751 / KGE 0.730 at seed
+42, seeds {42, 7, 123} span 0.744–0.758 / 0.728–0.732 (DDR 0.795 / 0.737 — RNG
+windows plus ddrs's per-cell KAN head vs DDR's per-sub-reach `log10_uparea`).
+CONUS: `config/sources/conus-gridded.yaml` + `config/experiments/gridded_conus.yaml`
+(620 gauges from `scripts/snap_gridded_gauges.py`, DDR's population); `plan`
+builds 5,198 cells → 91,867 sub-reaches in 0.6 s, baseline median NSE 0.354 /
+KGE 0.505 over 1995-10-01..1997-09-30 (DDR's 0.390 includes its `da_ratio`
+output correction, which ddrs does not apply).
+
+Two things this work found, both fixed: (1) `GageSubgraph::upstream_comids`
+returned one entry per piece on subdivided stores, so the summed-Q′ baseline
+counted each divide `m` times — now deduplicated by id (also affected MERIT
+`params.subdivision` baselines); (2) DDR's gridded Q′ stores are
+`Qr(time, divide_id)`, and zarrs returns fill values for an out-of-range subset
+instead of erroring, so the old fixed-axis reader silently read NaN — the
+reader now sniffs the axis order (traps.md T11).
+
 ## Maintenance
 
 This skill and `ddrs-eval-plots` are the only two skills in this repo. When a run,
diff --git a/.claude/skills/ddrs-dev/references/build-and-env.md b/.claude/skills/ddrs-dev/references/build-and-env.md
index 84e3f3f3..a69351a6 100644
--- a/.claude/skills/ddrs-dev/references/build-and-env.md
+++ b/.claude/skills/ddrs-dev/references/build-and-env.md
@@ -17,6 +17,13 @@ Verified against `Cargo.toml` and source on 2026-07-30.
 
 If a system HDF5 leaks into the static build: `unset HDF5_DIR; unset NETCDF_DIR`.
 
+- **CUDA newer than `cudarc`'s table** (13.3.1 on this host since 2026-09 vs
+  cudarc 0.19.7's max 13.2): the build script panics with `Unsupported cuda
+  toolkit version`. Set `CUDARC_CUDA_VERSION=13020` — a gitignored
+  `.cargo/config.toml` with `[env] CUDARC_CUDA_VERSION = "13020"` is the
+  per-checkout fix (traps.md T12). Cached `target/` dirs mask it until the
+  build script reruns.
+
 ## Fork pins
 
 All **13** `burn-*` crates must resolve from `github.com/taddyb/burn` branch
diff --git a/.claude/skills/ddrs-dev/references/config.md b/.claude/skills/ddrs-dev/references/config.md
index 44f344a0..38de5710 100644
--- a/.claude/skills/ddrs-dev/references/config.md
+++ b/.claude/skills/ddrs-dev/references/config.md
@@ -37,10 +37,14 @@ to §`params:` if you are looking for `tau` (it is not a routing sub-step count)
 (feature-concatenated on COMID, NaN-filled, `deserialize_one_or_many_paths`).
 An empty list is a hard error.
 
-Adjacency rule: provide **either** both `conus_adjacency` + `gages_adjacency`,
-**or** `geospatial_fabric` (managed build into `.ddrs/adjacency/<key>/`).
-Exactly one of the pair ⇒ error; neither source ⇒ `"adjacency sources are missing"`.
-For multi-layer gpkg set `geospatial_fabric_layer` (participates in the cache key).
+Adjacency rule: provide **exactly one** of (a) both `conus_adjacency` +
+`gages_adjacency`, (b) `geospatial_fabric` (MERIT managed build into
+`.ddrs/adjacency/<key>/`), (c) `gridded_network` (DDR's DDM30 sub-reach
+adjacency zarr, managed build via `resolve_or_build_gridded`; added 2026-09-09).
+Exactly one of the pair ⇒ error; neither source ⇒ `"adjacency sources are missing"`;
+`gridded_network` with (a) or (b) ⇒ error. For multi-layer gpkg set
+`geospatial_fabric_layer` (participates in the cache key). `params.subdivision.enabled`
+is rejected alongside `gridded_network` (the store is already split by DDR).
 
 `aorc_precip` is required whenever `kan_head.disaggregation:` is present — see below.
 
@@ -177,6 +181,9 @@ Four validators run at `Config::from_yaml_file`, plus one at dataset open.
 | `validate_data_sources` | one of the adjacency pair | `` "`gages_adjacency` is missing" `` |
 | | neither adjacency nor fabric | `"adjacency sources are missing"` |
 | | `geospatial_fabric_layer` on a non-gpkg | `"geospatial_fabric_layer"` + `".gpkg"` |
+| | `gridded_network` + `geospatial_fabric` | `"gridded_network"` + `"geospatial_fabric"` |
+| | `gridded_network` + explicit adjacency pair | `"gridded_network"` + `"conus_adjacency"` |
+| `validate_subdivision` | `subdivision.enabled: true` + `gridded_network` | `"params.subdivision"` + `"gridded_network"` |
 | `validate_leakance` | `use_leakance` + `use_cuda_graphs` | both key names |
 | `validate_ddr_match` | `use_cuda_graphs: true` without the deprecated `ddr_match: true` | `"use_cuda_graphs: true` requires the DEPRECATED `ddr_match: true"` |
 | `validate_disagg_pretrained` | `freeze: true` without `pretrained_checkpoint` | `"freeze: true requires pretrained_checkpoint"` |
diff --git a/.claude/skills/ddrs-dev/references/testing.md b/.claude/skills/ddrs-dev/references/testing.md
index 5226a6f5..15e865b6 100644
--- a/.claude/skills/ddrs-dev/references/testing.md
+++ b/.claude/skills/ddrs-dev/references/testing.md
@@ -48,6 +48,15 @@ debug_assertions** (a debug train takes minutes), so it only runs with
 readers when you want end-to-end confirmation. Verified 2026-09-02:
 NSE 0.7903 / KGE 0.8810 / baseline 0.6947 in 18.3 s.
 
+```bash
+cargo test --release --test gridded_acceptance -- --nocapture   # ~30 s after build
+```
+
+The gridded (DDM30) twin on `examples/juniata_gridded/`: floors NSE ≥ 0.70 /
+KGE ≥ 0.69 (seed-42 reference 0.751 / 0.730; seeds {42, 7, 123} span
+0.744–0.758 / 0.728–0.732), baseline NSE ∈ [0.57, 0.62] (deterministic 0.594,
+matches DDR). The baseline band is the one that catches a wrong `Qr` axis order.
+
 ### Tier B — KAN head
 `src/nn/`, `Cargo.toml` rskan tag
 
@@ -103,7 +112,8 @@ enables `.githooks/pre-push` (runs `ddr_sandbox_match`; bypass with
 |---|---|
 | Routing | `mmc`, `routing_utils`, `geometry` |
 | DDR parity (invariant 1) | `ddr_sandbox_match` (in-process, plain `cargo test`) + `compare_ddr_sandbox` example (diagnostics, exits 1 on mismatch) |
-| End-to-end acceptance | `juniata_acceptance` (release-only; metric floors + beats-baseline on the committed bundle) |
+| End-to-end acceptance | `juniata_acceptance`, `gridded_acceptance` (release-only; metric floors + beats-baseline on the committed bundles) |
+| Gridded (DDM30) ingestion | `gridded_bundle` (sub-reach store → subdivided layout, gauge at the cell's last piece, cache hit, dataset opens), `cargo test --lib adjacency::gridded` (synthetic-store validation), `hourly_streamflow::time_major_store_reads_identically_to_divide_major`, `cargo test --lib zarr::tests::upstream_comids_names_each_subdivided_parent_once` |
 | Sparse / autograd | `sparse_gradcheck`, `sp8_gradcheck` |
 | KAN head | the 4 `kan_head_*` fixture tests (need `--features fixtures`) |
 | Leakance | `leakance_gradcheck`, `leakance_off_parity`, `zeta_accum` |
diff --git a/.claude/skills/ddrs-dev/references/traps.md b/.claude/skills/ddrs-dev/references/traps.md
index 13fb7f9c..8a836415 100644
--- a/.claude/skills/ddrs-dev/references/traps.md
+++ b/.claude/skills/ddrs-dev/references/traps.md
@@ -18,6 +18,8 @@ is what a future session needs, not the narrative.
 | Mid-eval `object not found` from icechunk | T8 |
 | `.ddrs/` appeared somewhere unexpected | T9 |
 | Resumed run trains zero batches | T10 |
+| Baseline predicts ~0 (FHV −100 %) on a new Q′ store, no error | T11 |
+| Fresh checkout/worktree fails in `cudarc`'s build script: `Unsupported cuda toolkit version` | T12 |
 
 ---
 
@@ -195,6 +197,31 @@ Resume additionally requires `experiment.epochs > E` or the resumed run trains z
 batches. Stored weights are f16, so a resumed trajectory drifts slowly — expected,
 not a bug.
 
+## T11 — Time-major `Qr(time, divide_id)` read as fill values (fixed 2026-09-09)
+
+DDR's gridded (DDM30) `build_gridded_qprime.py` writes `Qr(time, divide_id)`;
+the MERIT stores and the contract are `Qr(divide_id, time)`. zarrs answers an
+out-of-range `retrieve_array_subset` with **fill values, not an error**, so the
+old fixed-axis `read_slab` returned NaN for every cell and the summed-Q′
+baseline scored NSE −0.655 with FHV −100 % — no message anywhere. `open` now
+decides the axis order from the array's `dimension_names`, falling back to its
+shape against the coordinate lengths, and refuses a shape matching neither
+(`detect_time_major`, `src/data/store/icechunk.rs`). Fixture:
+`tests/fixtures/qr_daily_time_major.ic`. A baseline that is *deterministic and
+matches DDR* is the check that catches this class of bug; that is why both
+acceptance tests band the baseline tightly.
+
+## T12 — CUDA toolkit newer than `cudarc` knows (2026-09-09)
+
+`cudarc 0.19.7` (via `cuda-version-from-build-system`) parses `nvcc --version`
+and panics on a version outside its table (max 13.2). This host moved to CUDA
+13.3.1 in 2026-09; the main tree's `target/` still carried the 13.2 build-script
+output, so only a fresh worktree/checkout hit it. Fix: `CUDARC_CUDA_VERSION=13020`
+(gitignored `.cargo/config.toml` `[env]` block, or export it). 13.3 is
+driver/ABI-compatible with 13.2 for the dynamic-loading path ddrs uses. The
+main tree will hit the same panic the next time its cudarc build script reruns
+(any `CUDA_*` env change or a `cargo clean`).
+
 ## Exit codes
 
 `src/cli/types.rs`: 0 Success · 1 Generic · 2 ConfigInvalid · 3 DataSourceMissing ·
diff --git a/.gitignore b/.gitignore
index f146e2a1..cd40a704 100644
--- a/.gitignore
+++ b/.gitignore
@@ -59,6 +59,8 @@ ddrs.yaml
 # …but the Juniata sample's config is a committed example, not a personal
 # workspace config (its .ddrs/ workspace is still ignored by the rule above).
 !examples/juniata/ddrs.yaml
+# …same exception for the gridded Juniata example's committed config.
+!examples/juniata_gridded/ddrs.yaml
 
 # Personal research journal (local only)
 JOURNAL.md
diff --git a/CLAUDE.md b/CLAUDE.md
index ad7ccf29..3514ab31 100644
--- a/CLAUDE.md
+++ b/CLAUDE.md
@@ -72,6 +72,8 @@ cargo test --test ddr_sandbox_match
 # assert routed NSE/KGE floors + beats the summed-Q' baseline. Release-only
 # (silently skips in debug builds — a debug train takes minutes):
 cargo test --release --test juniata_acceptance
+# Same, on the gridded (ISIMIP DDM30) Juniata bundle (examples/juniata_gridded/):
+cargo test --release --test gridded_acceptance
 
 # Hydrograph plot for visual sanity-check:
 cargo run --release --example benchmark_hydrograph
@@ -315,6 +317,27 @@ math. Read it before touching `src/routing/` or `src/sparse/`.
 | Global streamflow forcing | `/gpfs/hjj5218/data/dmc_forcing/streamflow/zarr/8km/merit_global_v2.7` (multi-zone zarr v2, `(time, COMID)` f64 per pfaf-2 zone) | `zarrs` |
 | Global gage metadata | `/gpfs/hjj5218/data/dmc_forcing/gage_information/formatted_gage_csvs/v3.1/8km/` (57 per-zone `<zone>_all.csv`) | `csv` |
 
+**Gridded (ISIMIP DDM30, 0.5°) routing** (2026-09-09, mirrors DDR PR #194):
+ddrs has no `engine/` module and ports none of DDR's raster aggregation or Q′
+regridding — it consumes DDR's products as a data source. `data_sources.
+gridded_network` names DDR's **sub-reach** adjacency zarr (`order`,
+`parent_cell`, `indices_0/1`, `length_m`, `slope`); `ddrs plan` relabels it into
+the existing subdivided store layout (parent = cell, pieces = sub-reaches, gauge
+read at the cell's last piece) and cuts gauge subgraphs from it
+(`src/adjacency/gridded.rs`, `cache::resolve_or_build_gridded`). Attributes
+(`COMID` = cell id) and Q′ (`divide_id` = cell id, split across pieces by
+`pieces_per_row_divisor`) need no changes; the gauge CSV's `cell` column is an
+alias of `COMID`. It is exclusive with `geospatial_fabric` and the explicit
+zarr pair, and `params.subdivision.enabled` is rejected with it. Committed
+sample: `examples/juniata_gridded/` (routed NSE 0.751 / KGE 0.730 vs baseline
+0.594 / 0.672, which matches DDR's baseline to rounding); CONUS:
+`config/sources/conus-gridded.yaml` (620 gauges via
+`scripts/snap_gridded_gauges.py`). Known deviations from DDR (per-cell KAN head,
+no `da_ratio` output correction) are in
+`docs/superpowers/specs/2026-09-08-ddrs-gridded-routing-design.md` §7.
+DDR's gridded Q′ stores are `Qr(time, divide_id)`; the icechunk reader sniffs
+the axis order (`detect_time_major`) — see the ddrs-dev skill's trap T11.
+
 The `observations` and `streamflow` data sources auto-detect their format
 (`ObservationsStore::open` / `StreamflowSource::open`,
 `src/data/store/mod.rs`); the icechunk CONUS path is the fallback when the
diff --git a/config/experiments/gridded_conus.yaml b/config/experiments/gridded_conus.yaml
new file mode 100644
index 00000000..5f70179c
--- /dev/null
+++ b/config/experiments/gridded_conus.yaml
@@ -0,0 +1,94 @@
+# Gridded (ISIMIP DDM30, 0.5°) CONUS training — the ddrs counterpart of DDR's
+# examples/juniata_gridded/train_conus.py (DeepGroundwater/ddr PR #194).
+#
+# Data: config/sources/conus-gridded.yaml (inlined below). 620 gages_3000
+# gauges above 2,000 km² snapped to cells (scripts/snap_gridded_gauges.py),
+# routed over DDR's 91,867-sub-reach Courant≈1 network.
+#
+# Run from the repo root — pass --workspace, or .ddrs lands beside this file:
+#
+#   ddrs --config config/experiments/gridded_conus.yaml --workspace .ddrs plan
+#   ddrs --config config/experiments/gridded_conus.yaml --workspace .ddrs run --workflow train-and-test
+#
+# Deviations from train_conus.py (see the 2026-09-08 gridded design spec §7):
+# the KAN runs per cell (not per sub-reach), and predictions are NOT divided
+# by the gauge's drainage-area ratio (`da_ratio` in the gauge CSV is
+# informational). DDR's reference: 45 epochs, median NSE 0.542 vs summed 0.390.
+
+mode: training
+workflow: train-and-test
+geodataset: ddm30
+device: 0
+seed: 42
+np_seed: 42
+
+data_sources:
+  gridded_network: /home/tbindas/projects/ddr/data/ddm30/ddm30_subreach_adjacency.zarr
+  attributes: /mnt/ssd1/data/icechunk/ddm30_conus_attributes.nc
+  streamflow: /mnt/ssd1/data/icechunk/ddm30_conus_uh_retrospective_regridded.ic
+  observations: /mnt/ssd1/data/icechunk/usgs_daily_observations
+  gages: /home/tbindas/projects/ddr/references/gage_info/ddm30_conus_gauges.csv
+
+experiment:
+  # train_conus.py defaults: batch 16 gauges, rho 90, warmup 5, lr 1e-3
+  # halved at epoch max(2, epochs // 2).
+  batch_size: 16
+  start_time: 1981/10/01
+  end_time: 1995/09/30
+  epochs: 10
+  rho: 90
+  shuffle: true
+  warmup: 5
+  learning_rate:
+    1: 0.001
+    5: 0.0005
+  grad_clip_max_norm: 1.0
+
+kan_head:
+  hidden_size: 21
+  num_hidden_layers: 2
+  grid: 50
+  k: 2
+  input_var_names:
+    - SoilGrids1km_clay
+    - aridity
+    - meanelevation
+    - meanP
+    - NDVI
+    - meanslope
+    - log10_uparea
+    - SoilGrids1km_sand
+    - ETPOT_Hargr
+    - Porosity
+  learnable_parameters:
+    - n
+    - q_spatial
+    - p_spatial
+
+params:
+  parameter_ranges:
+    n: [0.02, 0.2]
+    q_spatial: [0.0, 1.0]
+    p_spatial: [1.0, 200.0]
+  attribute_minimums:
+    discharge: 1.0e-4
+    slope: 1.0e-3
+    velocity: 0.01
+    depth: 0.01
+    bottom_width: 0.01
+  defaults:
+    p_spatial: 21.0
+  log_space_parameters:
+    - p_spatial
+  tau: 9
+  subdivision:
+    enabled: false
+  sparse_solver: cuda
+  use_cuda_graphs: false
+
+# train_conus.py's default test window (two water years).
+testing:
+  start_time: 1995/10/01
+  end_time: 1997/09/30
+  batch_size: 15
+  rho: null
diff --git a/config/sources/conus-gridded.yaml b/config/sources/conus-gridded.yaml
new file mode 100644
index 00000000..3a7060fd
--- /dev/null
+++ b/config/sources/conus-gridded.yaml
@@ -0,0 +1,17 @@
+data_sources:
+  # Gridded (ISIMIP DDM30, 0.5°) CONUS routing on DDR PR #194's products.
+  # The sub-reach adjacency is DDR's `scripts/build_subdivided_adjacency.py`
+  # output (91,867 Courant≈1 sub-reaches over 5,198 cells); ddrs relabels it
+  # into its subdivided store layout on the first `ddrs plan`.
+  gridded_network: /home/tbindas/projects/ddr/data/ddm30/ddm30_subreach_adjacency.zarr
+  # 25 cell attributes, `COMID` = cell id (statistics sidecar:
+  # scripts/build_attribute_statistics.py writes it beside the file).
+  attributes: /mnt/ssd1/data/icechunk/ddm30_conus_attributes.nc
+  # dHBV2 UH retrospective Q' area-weighted onto cells (`Qr(divide_id, time)`,
+  # 4,085 of 5,198 cells; the rest read as the 0.001 m³/s floor).
+  streamflow: /mnt/ssd1/data/icechunk/ddm30_conus_uh_retrospective_regridded.ic
+  observations: /mnt/ssd1/data/icechunk/usgs_daily_observations
+  # gages_3000 gauges above 2,000 km² snapped to cells by drainage-area match
+  # (scripts/snap_gridded_gauges.py; `COMID` = snapped cell, 620 gauges as in
+  # DDR's train_conus.py).
+  gages: /home/tbindas/projects/ddr/references/gage_info/ddm30_conus_gauges.csv
diff --git a/docs/nh-qprime-store-contract.md b/docs/nh-qprime-store-contract.md
index abdf40eb..58dea1e5 100644
--- a/docs/nh-qprime-store-contract.md
+++ b/docs/nh-qprime-store-contract.md
@@ -15,7 +15,14 @@ lives here.
 
 - An **icechunk repository** (`main` branch, local filesystem), root group.
 - One data variable **`Qr(divide_id, time)`**, dtype **float32**, attr
-  `units: m^3/s`. The dtype is not checked at `open` — `open` only
+  `units: m^3/s`. The transposed layout **`Qr(time, divide_id)`** — what
+  DDR's gridded (DDM30) `build_gridded_qprime.py` writes — is also read:
+  `open` decides the axis order from the array's dimension names, falling
+  back to matching its shape against the coordinate lengths, and refuses a
+  shape that fits neither (`detect_time_major`). The check exists because
+  zarrs answers an out-of-range subset with fill values rather than an
+  error, so a wrong axis guess would read NaN silently (2026-09-08).
+  The dtype is not checked at `open` — `open` only
   resolves the array handle (`src/data/store/icechunk.rs:239-241`). It is
   enforced at the first *read*, where `retrieve_array_subset::<Vec<f32>>`
   errors on a non-f32 array. `ddrs import` triggers that read itself via
diff --git a/docs/superpowers/specs/2026-09-08-ddrs-gridded-routing-design.md b/docs/superpowers/specs/2026-09-08-ddrs-gridded-routing-design.md
index 3860a6db..cb763977 100644
--- a/docs/superpowers/specs/2026-09-08-ddrs-gridded-routing-design.md
+++ b/docs/superpowers/specs/2026-09-08-ddrs-gridded-routing-design.md
@@ -203,3 +203,38 @@ Tests:
 - **`ddrs sources use conus-gridded` needs a gauge CSV that does not exist in
   DDR's references yet**; `scripts/snap_gridded_gauges.py` produces it under
   DDR's venv, following the `build_gages_2000_area_balanced.py` precedent.
+
+## 9. Outcome (2026-09-09)
+
+Implemented on branch `worktree-gridded-routing` as designed, with two
+findings the design did not anticipate:
+
+1. **`GageSubgraph::upstream_comids` was per-piece on subdivided stores.** It
+   deduplicated on row position, so a cell with `k` sub-reaches appeared `k`
+   times and the summed-Q′ baseline counted its Q′ `k` times. Fixed to
+   deduplicate on the id (a no-op for un-subdivided stores). The same bug
+   applied to MERIT `params.subdivision` baselines.
+2. **DDR's gridded Q′ stores are `Qr(time, divide_id)`**, the transpose of the
+   contract, and zarrs returns fill values for an out-of-range subset rather
+   than an error — the fixed-axis reader produced an all-NaN baseline with no
+   message. `StreamflowStore::open` now detects the axis order from
+   `dimension_names` (shape fallback, refuses neither) and `read_slab` addresses
+   the raw buffer accordingly; `tests/fixtures/qr_daily_time_major.ic` pins it.
+
+Results on the Juniata bundle (CPU, 30 epochs):
+
+| | NSE | KGE |
+|---|---|---|
+| summed-Q′ baseline, ddrs / DDR | 0.594 / 0.594 | 0.672 / 0.671 |
+| routed, seed 42 | 0.751 | 0.730 |
+| routed, seeds {42, 7, 123} | 0.744–0.758 | 0.728–0.732 |
+| routed, DDR Python | 0.795 | 0.737 |
+
+CONUS (`config/experiments/gridded_conus.yaml`, 620 gauges, test window
+1995-10-01..1997-09-30): `plan` builds 5,198 cells → 91,867 sub-reaches in
+0.6 s; baseline median NSE 0.354 / KGE 0.505. DDR reports 0.390 for its summed
+baseline, which includes the `da_ratio` output correction ddrs omits
+(deviation 2 in §7). Training beyond a mechanics smoke was not run.
+
+Environment note: the worktree build needed `CUDARC_CUDA_VERSION=13020`
+(host CUDA 13.3.1 vs cudarc 0.19.7's table); recorded as trap T12.
diff --git a/docs/usage/inputs-reading.md b/docs/usage/inputs-reading.md
index d176bb43..9d236ff9 100644
--- a/docs/usage/inputs-reading.md
+++ b/docs/usage/inputs-reading.md
@@ -73,7 +73,19 @@ Adjacency is an either/or, enforced at config load by
   `.ddrs/adjacency/<key>/{conus,gages}`. Subsequent plans are cache hits.
 - **Pre-built zarr** — set *both* `conus_adjacency` and `gages_adjacency`
   and omit `geospatial_fabric`.
-- Exactly one adjacency key, or neither key and no fabric, is a load-time
+- **Gridded (ISIMIP DDM30) network** — set `gridded_network` to DDR's
+  sub-reach adjacency zarr (DeepGroundwater/ddr PR #194,
+  `scripts/build_subdivided_adjacency.py`: `order`, `parent_cell`,
+  `indices_0/1`, `length_m`, `slope`) and omit the other two. `ddrs plan`
+  relabels it into the subdivided store layout below — parent = grid cell,
+  pieces = the cell's contiguous sub-reaches, gauge read at the last piece —
+  and cuts per-gauge subgraphs from it
+  (`adjacency::gridded::GriddedNetwork`, `cache::resolve_or_build_gridded`).
+  Attributes and Q′ stay keyed on the cell id, so nothing downstream changes;
+  the gauge CSV may name the outlet under `cell` (DDR's column) instead of
+  `COMID`. See `examples/juniata_gridded/` and the 2026-09-08 design spec.
+- Exactly one adjacency key, neither key and no fabric or gridded network,
+  or `gridded_network` combined with either of the others, is a load-time
   error.
 
 The cache key is `blake3(fabric_fingerprint ∥ gages_fingerprint ∥
diff --git a/examples/juniata_gridded/README.md b/examples/juniata_gridded/README.md
new file mode 100644
index 00000000..3f421ad7
--- /dev/null
+++ b/examples/juniata_gridded/README.md
@@ -0,0 +1,87 @@
+# Gridded (ISIMIP DDM30) Juniata sample
+
+The gridded counterpart of [`examples/juniata`](../juniata/README.md), and
+the ddrs mirror of DDR's `examples/juniata_gridded` (DeepGroundwater/ddr
+PR #194). Same basin and gauge (USGS 01567000, 8,657 km²), but the river
+network is the ISIMIP DDM30 0.5° drainage-direction grid instead of MERIT
+flowlines: four grid cells, split by DDR into 27 sub-reaches of about 7 km.
+
+Everything needed is in `data/` (1.6 MB, byte-identical to DDR's bundle plus
+the statistics sidecar). No HPC, S3, CUDA, or external stores.
+
+## Quickstart
+
+From the **repo root** (the config's data paths are repo-root-relative):
+
+    cargo build --release --bin ddrs
+    target/release/ddrs --config examples/juniata_gridded/ddrs.yaml plan
+    target/release/ddrs --config examples/juniata_gridded/ddrs.yaml run --workflow train-and-test --backend cpu
+
+`plan` relabels DDR's sub-reach store into ddrs's subdivided adjacency
+layout, cuts the gauge's upstream subgraph, caches both under
+`examples/juniata_gridded/.ddrs/adjacency/<key>/` (gitignored), and prints
+the summed-Q' baseline. `run` trains the KAN head for 30 optimizer steps
+(one random 90-day window per epoch on a single gauge), then evaluates over
+water years 1996–2010. The whole workflow takes well under a minute on CPU.
+
+Reference results (CPU, 30 epochs, test 1995-10-01 – 2010-09-30):
+
+| | NSE | KGE |
+|---|---|---|
+| ddrs routed (seed 42) | 0.751 | 0.730 |
+| ddrs routed, seeds {42, 7, 123} | 0.744–0.758 | 0.728–0.732 |
+| DDR (Python) routed | 0.795 | 0.737 |
+| summed-Q' baseline (ddrs) | 0.594 | 0.672 |
+| summed-Q' baseline (DDR) | 0.594 | 0.671 |
+
+The baseline is deterministic and matches DDR to rounding: the two
+implementations read the same bundle through independent readers, so it is
+a live cross-implementation check (it is what exposed that DDR's gridded Q'
+store is written `Qr(time, divide_id)`, the transpose of the MERIT layout;
+ddrs now detects both). The routed gap to DDR has two known sources: the 30
+random training windows come from different RNG streams (as in
+`examples/juniata`), and ddrs's KAN head runs **per cell** — every
+sub-reach of a cell shares the cell's parameters and the cell's
+`log10_uparea` — where DDR's gridded trainer runs it per sub-reach with an
+accumulated `log10_uparea`. With four cells the field is nearly uniform
+either way; DDR's own README calls the sample a demonstration that the
+gridded network trains and routes, not a converged model.
+
+## How the gridded inputs map onto ddrs
+
+ddrs has no `engine/` module and ports none of DDR's raster aggregation or
+Q' regridding. It consumes DDR's products as a data source: the new
+`data_sources.gridded_network` key points at DDR's sub-reach adjacency
+zarr, and everything downstream is the existing subdivided-network path:
+
+| DDR gridded product | ddrs reads it as |
+|---|---|
+| `juniata_subreach_adjacency.zarr` — `order` (node id = cell·1000 + sub), `parent_cell`, `indices_0/1`, `length_m`, `slope` | a subdivided CONUS store: parent = cell, pieces = the cell's contiguous sub-reaches, outlet = last piece |
+| `ddm30_conus_attributes.nc` — 25 attributes, `COMID` = cell id (all 5,198 CONUS cells, so normalisation matches a CONUS run) | the attributes table, looked up per cell; sidecar `data/statistics/merit_attribute_statistics_ddm30_conus_attributes.nc.json` from `scripts/build_attribute_statistics.py` |
+| `juniata_qprime.ic` — `Qr(time, divide_id)` daily m³/s per cell, 1980–2010 | daily Q' per cell, split evenly across the cell's sub-reaches at routing time (`pieces_per_row_divisor`) |
+| `juniata_obs.ic` — `streamflow(gage_id, time)`, USGS 01567000 | observations, unchanged |
+| `juniata_gage.csv` — one row with the snapped `cell` and `da_ratio` | the gauge table; `cell` is read as the outlet id, routed at that cell's last sub-reach. `da_ratio` is informational (no output correction, as in DDR's `train_gridded.py`) |
+
+Design and the full list of deviations:
+`docs/superpowers/specs/2026-09-08-ddrs-gridded-routing-design.md`.
+
+## Tests
+
+    cargo test --test gridded_bundle                 # bundle contract, never skips
+    cargo test --release --test gridded_acceptance   # end-to-end metric floors
+
+## CONUS
+
+`config/sources/conus-gridded.yaml` names the on-disk CONUS products
+(91,867 sub-reaches, 620 gauges from `scripts/snap_gridded_gauges.py`), and
+`config/experiments/gridded_conus.yaml` mirrors DDR's `train_conus.py`
+defaults. Both need the workstation stores under `/mnt/ssd1` and
+`~/projects/ddr/data/ddm30`.
+
+## Regenerating the bundle
+
+Maintainer only. Regenerate in the ddr repo
+(`examples/juniata_gridded/extract_bundle.py`), copy `data/` here, then
+
+    ~/projects/ddr/.venv/bin/python scripts/build_attribute_statistics.py \
+        examples/juniata_gridded/data/ddm30_conus_attributes.nc
diff --git a/examples/juniata_gridded/data/ddm30_conus_attributes.nc b/examples/juniata_gridded/data/ddm30_conus_attributes.nc
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diff --git a/examples/juniata_gridded/data/juniata_gage.csv b/examples/juniata_gridded/data/juniata_gage.csv
new file mode 100644
index 00000000..fac7774b
--- /dev/null
+++ b/examples/juniata_gridded/data/juniata_gage.csv
@@ -0,0 +1,2 @@
+STAID,STANAME,DRAIN_SQKM,LAT_GAGE,LNG_GAGE,cell,da_ratio
+01567000,"JUNIATA RIVER AT NEWPORT, PA",8657.0,40.4785,-77.1294,138445,1.0880212544761465
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new file mode 100644
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diff --git a/examples/juniata_gridded/data/juniata_obs.ic/chunks/2MGHGS8R7AN9RNHYFAS0 b/examples/juniata_gridded/data/juniata_obs.ic/chunks/2MGHGS8R7AN9RNHYFAS0
new file mode 100644
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diff --git a/examples/juniata_gridded/data/juniata_obs.ic/chunks/4R696W5CMNH287T1N560 b/examples/juniata_gridded/data/juniata_obs.ic/chunks/4R696W5CMNH287T1N560
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diff --git a/examples/juniata_gridded/data/juniata_obs.ic/chunks/D8V36GXME8HHBW236MZG b/examples/juniata_gridded/data/juniata_obs.ic/chunks/D8V36GXME8HHBW236MZG
new file mode 100644
index 0000000000000000000000000000000000000000..26d7b13901cec8f9a5011fbb81b97e32ae659262
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diff --git a/examples/juniata_gridded/data/juniata_obs.ic/chunks/PHM8GS06CPVYYQ5XEQTG b/examples/juniata_gridded/data/juniata_obs.ic/chunks/PHM8GS06CPVYYQ5XEQTG
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diff --git a/examples/juniata_gridded/data/juniata_obs.ic/chunks/PWE693HB7A0MC7TTDJ1G b/examples/juniata_gridded/data/juniata_obs.ic/chunks/PWE693HB7A0MC7TTDJ1G
new file mode 100644
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diff --git a/examples/juniata_gridded/data/juniata_qprime.ic/chunks/08PA56AQTKRSGG58PFTG b/examples/juniata_gridded/data/juniata_qprime.ic/chunks/08PA56AQTKRSGG58PFTG
new file mode 100644
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diff --git a/examples/juniata_gridded/data/juniata_qprime.ic/chunks/6YZMPPEHXRRYRYBM02P0 b/examples/juniata_gridded/data/juniata_qprime.ic/chunks/6YZMPPEHXRRYRYBM02P0
new file mode 100644
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diff --git a/examples/juniata_gridded/data/juniata_qprime.ic/chunks/935T0S2BG6F1GPR03AC0 b/examples/juniata_gridded/data/juniata_qprime.ic/chunks/935T0S2BG6F1GPR03AC0
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diff --git a/examples/juniata_gridded/data/juniata_qprime.ic/chunks/D4RJKVDD0VZ29MTAKKY0 b/examples/juniata_gridded/data/juniata_qprime.ic/chunks/D4RJKVDD0VZ29MTAKKY0
new file mode 100644
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diff --git a/examples/juniata_gridded/data/juniata_qprime.ic/chunks/E9Y90M6R0V6Q9VE67BC0 b/examples/juniata_gridded/data/juniata_qprime.ic/chunks/E9Y90M6R0V6Q9VE67BC0
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diff --git a/examples/juniata_gridded/data/juniata_qprime.ic/chunks/ERDTKF1N4QMKCMEFF53G b/examples/juniata_gridded/data/juniata_qprime.ic/chunks/ERDTKF1N4QMKCMEFF53G
new file mode 100644
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diff --git a/examples/juniata_gridded/data/juniata_qprime.ic/chunks/FXDT100W5GJN994AX400 b/examples/juniata_gridded/data/juniata_qprime.ic/chunks/FXDT100W5GJN994AX400
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diff --git a/examples/juniata_gridded/data/juniata_qprime.ic/chunks/MK2Z5AJ49K7ZFNJMB74G b/examples/juniata_gridded/data/juniata_qprime.ic/chunks/MK2Z5AJ49K7ZFNJMB74G
new file mode 100644
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diff --git a/examples/juniata_gridded/data/juniata_qprime.ic/chunks/ZQBR3098145BTY3TSGMG b/examples/juniata_gridded/data/juniata_qprime.ic/chunks/ZQBR3098145BTY3TSGMG
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+      "separator": "/"
+    }
+  },
+  "fill_value": 0.0,
+  "codecs": [
+    {
+      "name": "bytes",
+      "configuration": {
+        "endian": "little"
+      }
+    },
+    {
+      "name": "zstd",
+      "configuration": {
+        "level": 0,
+        "checksum": false
+      }
+    }
+  ],
+  "attributes": {},
+  "zarr_format": 3,
+  "node_type": "array",
+  "storage_transformers": []
+}
diff --git a/examples/juniata_gridded/data/juniata_subreach_adjacency.zarr/order/c/0 b/examples/juniata_gridded/data/juniata_subreach_adjacency.zarr/order/c/0
new file mode 100644
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diff --git a/examples/juniata_gridded/data/juniata_subreach_adjacency.zarr/order/zarr.json b/examples/juniata_gridded/data/juniata_subreach_adjacency.zarr/order/zarr.json
new file mode 100644
index 00000000..c63fe6b6
--- /dev/null
+++ b/examples/juniata_gridded/data/juniata_subreach_adjacency.zarr/order/zarr.json
@@ -0,0 +1,40 @@
+{
+  "shape": [
+    27
+  ],
+  "data_type": "int64",
+  "chunk_grid": {
+    "name": "regular",
+    "configuration": {
+      "chunk_shape": [
+        27
+      ]
+    }
+  },
+  "chunk_key_encoding": {
+    "name": "default",
+    "configuration": {
+      "separator": "/"
+    }
+  },
+  "fill_value": 0,
+  "codecs": [
+    {
+      "name": "bytes",
+      "configuration": {
+        "endian": "little"
+      }
+    },
+    {
+      "name": "zstd",
+      "configuration": {
+        "level": 0,
+        "checksum": false
+      }
+    }
+  ],
+  "attributes": {},
+  "zarr_format": 3,
+  "node_type": "array",
+  "storage_transformers": []
+}
diff --git a/examples/juniata_gridded/data/juniata_subreach_adjacency.zarr/parent_cell/c/0 b/examples/juniata_gridded/data/juniata_subreach_adjacency.zarr/parent_cell/c/0
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diff --git a/examples/juniata_gridded/data/juniata_subreach_adjacency.zarr/parent_cell/zarr.json b/examples/juniata_gridded/data/juniata_subreach_adjacency.zarr/parent_cell/zarr.json
new file mode 100644
index 00000000..10303bd3
--- /dev/null
+++ b/examples/juniata_gridded/data/juniata_subreach_adjacency.zarr/parent_cell/zarr.json
@@ -0,0 +1,40 @@
+{
+  "shape": [
+    27
+  ],
+  "data_type": "int32",
+  "chunk_grid": {
+    "name": "regular",
+    "configuration": {
+      "chunk_shape": [
+        27
+      ]
+    }
+  },
+  "chunk_key_encoding": {
+    "name": "default",
+    "configuration": {
+      "separator": "/"
+    }
+  },
+  "fill_value": 0,
+  "codecs": [
+    {
+      "name": "bytes",
+      "configuration": {
+        "endian": "little"
+      }
+    },
+    {
+      "name": "zstd",
+      "configuration": {
+        "level": 0,
+        "checksum": false
+      }
+    }
+  ],
+  "attributes": {},
+  "zarr_format": 3,
+  "node_type": "array",
+  "storage_transformers": []
+}
diff --git a/examples/juniata_gridded/data/juniata_subreach_adjacency.zarr/slope/c/0 b/examples/juniata_gridded/data/juniata_subreach_adjacency.zarr/slope/c/0
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diff --git a/examples/juniata_gridded/data/juniata_subreach_adjacency.zarr/slope/zarr.json b/examples/juniata_gridded/data/juniata_subreach_adjacency.zarr/slope/zarr.json
new file mode 100644
index 00000000..0455e05a
--- /dev/null
+++ b/examples/juniata_gridded/data/juniata_subreach_adjacency.zarr/slope/zarr.json
@@ -0,0 +1,40 @@
+{
+  "shape": [
+    27
+  ],
+  "data_type": "float32",
+  "chunk_grid": {
+    "name": "regular",
+    "configuration": {
+      "chunk_shape": [
+        27
+      ]
+    }
+  },
+  "chunk_key_encoding": {
+    "name": "default",
+    "configuration": {
+      "separator": "/"
+    }
+  },
+  "fill_value": 0.0,
+  "codecs": [
+    {
+      "name": "bytes",
+      "configuration": {
+        "endian": "little"
+      }
+    },
+    {
+      "name": "zstd",
+      "configuration": {
+        "level": 0,
+        "checksum": false
+      }
+    }
+  ],
+  "attributes": {},
+  "zarr_format": 3,
+  "node_type": "array",
+  "storage_transformers": []
+}
diff --git a/examples/juniata_gridded/data/juniata_subreach_adjacency.zarr/values/c/0 b/examples/juniata_gridded/data/juniata_subreach_adjacency.zarr/values/c/0
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diff --git a/examples/juniata_gridded/data/juniata_subreach_adjacency.zarr/values/zarr.json b/examples/juniata_gridded/data/juniata_subreach_adjacency.zarr/values/zarr.json
new file mode 100644
index 00000000..4074697f
--- /dev/null
+++ b/examples/juniata_gridded/data/juniata_subreach_adjacency.zarr/values/zarr.json
@@ -0,0 +1,37 @@
+{
+  "shape": [
+    26
+  ],
+  "data_type": "uint8",
+  "chunk_grid": {
+    "name": "regular",
+    "configuration": {
+      "chunk_shape": [
+        26
+      ]
+    }
+  },
+  "chunk_key_encoding": {
+    "name": "default",
+    "configuration": {
+      "separator": "/"
+    }
+  },
+  "fill_value": 0,
+  "codecs": [
+    {
+      "name": "bytes"
+    },
+    {
+      "name": "zstd",
+      "configuration": {
+        "level": 0,
+        "checksum": false
+      }
+    }
+  ],
+  "attributes": {},
+  "zarr_format": 3,
+  "node_type": "array",
+  "storage_transformers": []
+}
diff --git a/examples/juniata_gridded/data/juniata_subreach_adjacency.zarr/zarr.json b/examples/juniata_gridded/data/juniata_subreach_adjacency.zarr/zarr.json
new file mode 100644
index 00000000..a7acf16b
--- /dev/null
+++ b/examples/juniata_gridded/data/juniata_subreach_adjacency.zarr/zarr.json
@@ -0,0 +1,19 @@
+{
+  "attributes": {
+    "format": "COO",
+    "shape": [
+      27,
+      27
+    ],
+    "geodataset": "ddm30",
+    "subdivided": true,
+    "cell_id_scheme": "node id = cell id * 1000 + sub index (upstream-most first)",
+    "data_types": {
+      "indices_0": "int32",
+      "indices_1": "int32",
+      "values": "uint8"
+    }
+  },
+  "zarr_format": 3,
+  "node_type": "group"
+}
diff --git a/examples/juniata_gridded/data/statistics/merit_attribute_statistics_ddm30_conus_attributes.nc.json b/examples/juniata_gridded/data/statistics/merit_attribute_statistics_ddm30_conus_attributes.nc.json
new file mode 100644
index 00000000..a97e3c71
--- /dev/null
+++ b/examples/juniata_gridded/data/statistics/merit_attribute_statistics_ddm30_conus_attributes.nc.json
@@ -0,0 +1,202 @@
+{
+  "meanelevation": {
+    "min": 0.004861295323337654,
+    "max": 3369.19688318091,
+    "mean": 703.9322811238138,
+    "std": 660.8384435790672,
+    "p10": 69.40527726837776,
+    "p90": 1759.9149382594505
+  },
+  "NDVI": {
+    "min": -0.07139881334372336,
+    "max": 0.8012113621976084,
+    "mean": 0.39212428904603336,
+    "std": 0.16051253610065513,
+    "p10": 0.18850096432721256,
+    "p90": 0.6226797447717318
+  },
+  "snow_fraction": {
+    "min": 7.450250524098686e-05,
+    "max": 0.6698027268301546,
+    "mean": 0.09175650361244392,
+    "std": 0.09728262891609547,
+    "p10": 0.0013670597900336228,
+    "p90": 0.23224604059529871
+  },
+  "FW": {
+    "min": 0.0,
+    "max": 1.0,
+    "mean": 0.058816597108576625,
+    "std": 0.14434725529012868,
+    "p10": 0.000209455598065324,
+    "p90": 0.13832576788124348
+  },
+  "Ksat": {
+    "min": 1.630860676223944,
+    "max": 360.32950299120023,
+    "mean": 29.965475362872624,
+    "std": 36.42079478433762,
+    "p10": 6.477697036109817,
+    "p90": 71.25291135094982
+  },
+  "ALPHA": {
+    "min": 0.0016555487306490662,
+    "max": 0.10123577553330375,
+    "mean": 0.020262717081631222,
+    "std": 0.012544429442543381,
+    "p10": 0.007331282362348112,
+    "p90": 0.03696019671172372
+  },
+  "N": {
+    "min": 1.1986454776628077,
+    "max": 1.6693176918692725,
+    "mean": 1.3249985062017362,
+    "std": 0.06297205116060489,
+    "p10": 1.247119541409867,
+    "p90": 1.4068147898142649
+  },
+  "ORMC": {
+    "min": 0.4428205578327663,
+    "max": 52.20994461155595,
+    "mean": 8.741051363357073,
+    "std": 6.635191044133652,
+    "p10": 2.4944028294625813,
+    "p90": 16.503845225470094
+  },
+  "WCpF2": {
+    "min": 0.16847541756909717,
+    "max": 0.6116269056806527,
+    "mean": 0.37807038847617563,
+    "std": 0.06387835873786013,
+    "p10": 0.2910144102103489,
+    "p90": 0.45110854385255456
+  },
+  "WCsat": {
+    "min": 0.3936480963612873,
+    "max": 0.7172914560492192,
+    "mean": 0.49274685483597847,
+    "std": 0.05074944293515737,
+    "p10": 0.43361513124774137,
+    "p90": 0.5675219682404052
+  },
+  "SoilGrids1km_clay": {
+    "min": 2.0618805485446328,
+    "max": 53.02753344037019,
+    "mean": 22.060060387691486,
+    "std": 7.029637572972272,
+    "p10": 13.18350418518392,
+    "p90": 31.155411883878447
+  },
+  "SoilGrids1km_sand": {
+    "min": 4.115237064847427,
+    "max": 94.81344250065135,
+    "mean": 40.129230147520076,
+    "std": 14.779979045583923,
+    "p10": 20.56785571370896,
+    "p90": 57.42126506346657
+  },
+  "SoilGrids1km_silt": {
+    "min": 2.8477707313651184,
+    "max": 70.83410231479239,
+    "mean": 37.810677628739946,
+    "std": 10.427255627718067,
+    "p10": 24.797150150008086,
+    "p90": 51.42990197184438
+  },
+  "meanslope": {
+    "min": 0.0,
+    "max": 27.263860282239285,
+    "mean": 3.397809137240753,
+    "std": 4.139947075799843,
+    "p10": 0.4088235262148592,
+    "p90": 8.639461607208487
+  },
+  "meanP": {
+    "min": 57.27565084232705,
+    "max": 3139.0101362051923,
+    "mean": 744.2556414051538,
+    "std": 396.6552667548469,
+    "p10": 293.9332777773968,
+    "p90": 1259.2973333326408
+  },
+  "meanTa": {
+    "min": -4.214311336403693,
+    "max": 25.418786005990317,
+    "mean": 9.397976360355777,
+    "std": 6.757331808995632,
+    "p10": 0.6839523293738895,
+    "p90": 18.991226844959154
+  },
+  "ETPOT_Hargr": {
+    "min": 506.3604392672467,
+    "max": 1979.1649480526967,
+    "mean": 1082.352619034022,
+    "std": 328.609970222106,
+    "p10": 678.405916454727,
+    "p90": 1554.4528788758657
+  },
+  "seasonality_P": {
+    "min": 0.045816066321010616,
+    "max": 1.018944280140316,
+    "mean": 0.36544183968232397,
+    "std": 0.2032374264509107,
+    "p10": 0.13108854272027207,
+    "p90": 0.6138264486008584
+  },
+  "seasonality_PET": {
+    "min": 0.17664974526005303,
+    "max": 0.9025561776057203,
+    "mean": 0.5753634587230027,
+    "std": 0.16810704414639588,
+    "p10": 0.33392438075236064,
+    "p90": 0.8013925131806772
+  },
+  "snowfall_fraction": {
+    "min": 0.0,
+    "max": 0.7009380043020851,
+    "mean": 0.1738869544314959,
+    "std": 0.15691078415008627,
+    "p10": 0.0,
+    "p90": 0.38890798297778867
+  },
+  "aridity": {
+    "min": 0.24188227366112164,
+    "max": 28.526506740792904,
+    "mean": 2.2754431321907855,
+    "std": 2.543380125305846,
+    "p10": 0.7385919473552908,
+    "p90": 4.607038839728651
+  },
+  "Porosity": {
+    "min": 0.00999999977648258,
+    "max": 0.2793158438904144,
+    "mean": 0.13425318477349144,
+    "std": 0.06511777897495456,
+    "p10": 0.027224847045667213,
+    "p90": 0.21367892881640052
+  },
+  "permeability": {
+    "min": -16.500000000000004,
+    "max": -10.916314141407062,
+    "mean": -13.783503510211885,
+    "std": 1.0981717690721766,
+    "p10": -15.275190199691304,
+    "p90": -12.515690630734188
+  },
+  "catchsize": {
+    "min": 1871.0049494176442,
+    "max": 2818.3185855515253,
+    "mean": 2311.363148928616,
+    "std": 260.79175193002754,
+    "p10": 1955.7352702129808,
+    "p90": 2670.174390705445
+  },
+  "log10_uparea": {
+    "min": 3.2720749363519226,
+    "max": 6.509329060049167,
+    "mean": 3.8717224718970327,
+    "std": 0.6399331225807444,
+    "p10": 3.3218508865933143,
+    "p90": 4.795751524059255
+  }
+}
\ No newline at end of file
diff --git a/examples/juniata_gridded/ddrs.yaml b/examples/juniata_gridded/ddrs.yaml
new file mode 100644
index 00000000..e16b88fa
--- /dev/null
+++ b/examples/juniata_gridded/ddrs.yaml
@@ -0,0 +1,119 @@
+# Gridded (ISIMIP DDM30) Juniata sample — the ddrs mirror of DDR's
+# examples/juniata_gridded (DeepGroundwater/ddr PR #194).
+#
+# Same gauge as examples/juniata (USGS 01567000, 8,657 km²) but the river
+# network is the 0.5° DDM30 grid: four cells split into 27 Courant≈1
+# sub-reaches of ~7 km. The 1.6 MB bundle under examples/juniata_gridded/data/
+# is byte-identical to DDR's; nothing external is needed.
+#
+# Run FROM THE REPO ROOT (data paths below are repo-root-relative):
+#
+#   ddrs --config examples/juniata_gridded/ddrs.yaml plan
+#   ddrs --config examples/juniata_gridded/ddrs.yaml run --workflow train-and-test --backend cpu
+#
+# The workspace (.ddrs/) is created beside this file. `plan` relabels the
+# sub-reach store into ddrs's subdivided layout and cuts the gauge subgraph
+# into .ddrs/adjacency/<key>/ (parent = grid cell, pieces = sub-reaches).
+#
+# Hyperparameters mirror DDR's examples/juniata_gridded/train_gridded.py —
+# keep them in sync when comparing against the Python implementation.
+
+mode: training
+workflow: train-and-test
+geodataset: ddm30
+device: 0
+seed: 42
+np_seed: 42
+
+data_sources:
+  # DDR's sub-reach adjacency zarr (`order`, `parent_cell`, `indices_0/1`,
+  # `length_m`, `slope`, `lat`, `lon`), 27 rows over 4 cells. This is the
+  # gridded counterpart of `geospatial_fabric`: ddrs builds the managed
+  # stores from it on first `plan`.
+  gridded_network: examples/juniata_gridded/data/juniata_subreach_adjacency.zarr
+  # 25 attributes for all 5,198 CONUS cells (`COMID` = cell id), so the
+  # normalisation statistics match a CONUS run. Sidecar:
+  # data/statistics/merit_attribute_statistics_ddm30_conus_attributes.nc.json
+  # (generated by scripts/build_attribute_statistics.py; ddrs never recomputes).
+  attributes: examples/juniata_gridded/data/ddm30_conus_attributes.nc
+  # Daily lateral inflow per CELL (`Qr(divide_id, time)`, divide_id = cell
+  # id): dHBV2 UH retrospective area-weighted onto the four cells. Each cell's
+  # Q' is split evenly across its sub-reaches at routing time.
+  streamflow: examples/juniata_gridded/data/juniata_qprime.ic
+  # USGS daily observed discharge at 01567000 (icechunk store).
+  observations: examples/juniata_gridded/data/juniata_obs.ic
+  # One-row gauge table. The `cell` column (DDR's name) is the snapped DDM30
+  # cell; ddrs reads it as the outlet id and routes to that cell's most
+  # downstream sub-reach.
+  gages: examples/juniata_gridded/data/juniata_gage.csv
+
+experiment:
+  # Single gauge → one mini-batch (one random rho-day window) per epoch, so
+  # `epochs` is the optimizer-step count. 30 steps demonstrates that the
+  # gridded network trains and routes; it is not a converged model.
+  batch_size: 1
+  start_time: 1981/10/01
+  end_time: 1995/09/30
+  epochs: 30
+  rho: 90
+  shuffle: true
+  warmup: 5
+  # train_gridded.py uses a constant Adam lr of 1e-3 (no halving).
+  learning_rate:
+    1: 0.001
+  grad_clip_max_norm: 1.0
+
+kan_head:
+  hidden_size: 21
+  num_hidden_layers: 2
+  grid: 50
+  k: 2
+  input_var_names:
+    - SoilGrids1km_clay
+    - aridity
+    - meanelevation
+    - meanP
+    - NDVI
+    - meanslope
+    - log10_uparea
+    - SoilGrids1km_sand
+    - ETPOT_Hargr
+    - Porosity
+  learnable_parameters:
+    - n
+    - q_spatial
+    - p_spatial
+
+params:
+  # train_gridded.py::make_config bounds (n is narrower than the MERIT
+  # Juniata example's [0.015, 0.25]).
+  parameter_ranges:
+    n: [0.02, 0.2]
+    q_spatial: [0.0, 1.0]
+    p_spatial: [1.0, 200.0]
+  attribute_minimums:
+    discharge: 1.0e-4
+    slope: 1.0e-3
+    velocity: 0.01
+    depth: 0.01
+    bottom_width: 0.01
+  defaults:
+    p_spatial: 21.0
+  log_space_parameters:
+    - p_spatial
+  tau: 9
+  # The sub-reach store is already split by DDR; ddrs's MERIT reach plan
+  # must stay off (config load rejects `enabled: true` with gridded_network).
+  subdivision:
+    enabled: false
+  # CPU-friendly: no CUDA requirement anywhere in the sample.
+  sparse_solver: cpu
+  use_cuda_graphs: false
+
+# Evaluation overlay (water years 1996–2010, as train_gridded.py).
+# CAUTION — batch_size changes meaning: GAUGES in training, DAYS here.
+testing:
+  start_time: 1995/10/01
+  end_time: 2010/09/30
+  batch_size: 15
+  rho: null
diff --git a/scripts/build_attribute_statistics.py b/scripts/build_attribute_statistics.py
new file mode 100644
index 00000000..81fe0e23
--- /dev/null
+++ b/scripts/build_attribute_statistics.py
@@ -0,0 +1,56 @@
+"""Build the attribute-statistics sidecar JSON that ddrs reads at data-load time.
+
+ddrs never recomputes normalization statistics itself (see
+`src/data/dataset.rs::stats_path_from_attrs`): it expects a
+`<attrs_dir>/statistics/merit_attribute_statistics_<attrs_filename>.json`
+file to already exist next to any attributes NetCDF it opens, MERIT or
+DDM30-gridded alike (the `merit_` prefix is a fixed template, not a claim
+about the network type). This script produces that sidecar, mirroring DDR's
+`src/ddr/io/statistics.py::set_statistics` but without needing a DDR `Config`
+object, so it can run standalone under DDR's venv against any attributes file.
+
+Usage:
+    python build_attribute_statistics.py <attributes.nc> [--out-dir <dir>]
+
+Default `--out-dir` is `<attributes dir>/statistics`.
+"""
+
+import argparse
+import json
+from pathlib import Path
+
+import numpy as np
+import xarray as xr
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser()
+    parser.add_argument("attributes", type=Path)
+    parser.add_argument("--out-dir", type=Path, default=None)
+    args = parser.parse_args()
+
+    out_dir = args.out_dir or (args.attributes.parent / "statistics")
+    out_dir.mkdir(exist_ok=True, parents=True)
+    out_file = out_dir / f"merit_attribute_statistics_{args.attributes.name}.json"
+
+    ds = xr.open_dataset(args.attributes)
+    stats = {}
+    for attr in list(ds.data_vars.keys()):
+        data = ds[attr].values
+        stats[attr] = {
+            "min": float(np.nanmin(data, axis=0)),
+            "max": float(np.nanmax(data, axis=0)),
+            "mean": float(np.nanmean(data, axis=0)),
+            "std": float(np.nanstd(data, axis=0)),
+            "p10": float(np.nanpercentile(data, 10, axis=0)),
+            "p90": float(np.nanpercentile(data, 90, axis=0)),
+        }
+
+    with open(out_file, "w") as f:
+        json.dump(stats, f, indent=2)
+
+    print(f"Wrote {out_file}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/scripts/make_streamflow_fixtures.py b/scripts/make_streamflow_fixtures.py
index 4687a808..01a26271 100644
--- a/scripts/make_streamflow_fixtures.py
+++ b/scripts/make_streamflow_fixtures.py
@@ -11,13 +11,18 @@
   qr_daily.ic   : 4 divides x 10 days,   Qr[j, t] = (j+1)*100  + t
   qr_hourly.ic  : 4 divides x 240 hours, Qr[j, h] = (j+1)*1000 + h
   qr_minutes.ic : sniff-rejection fixture (units "minutes since ...")
+  qr_daily_time_major.ic : qr_daily's values stored TIME-MAJOR, Qr(time, divide_id)
+                  -- the layout DDR's gridded (DDM30) Q' stores use; the reader
+                  must return identical values from both.
+
+Stores that already exist are left alone (icechunk snapshot ids are not
+deterministic, so rewriting would churn tracked bytes); delete one to regenerate.
 
 Note: xarray normalises "hours since 1981-01-01 00:00:00" to drop the time
 component on write.  We patch the zarr attr back to the full string after
 to_zarr() so the on-disk CF units string is exactly as documented above.
 """
 from pathlib import Path
-import shutil
 
 import icechunk
 import numpy as np
@@ -35,14 +40,19 @@ def write_store(
     time_units: str,
     *,
     time_units_on_disk: str | None = None,
+    time_major: bool = False,
 ) -> None:
-    shutil.rmtree(path, ignore_errors=True)
+    if path.exists():
+        print(f"exists, skipping: {path} (delete it to regenerate)")
+        return
+    dims = ["time", "divide_id"] if time_major else ["divide_id", "time"]
+    data = qr.T if time_major else qr
     storage = icechunk.local_filesystem_storage(str(path))
     repo = icechunk.Repository.create(storage)
     session = repo.writable_session("main")
     ds = xr.Dataset(
         data_vars={
-            "Qr": (["divide_id", "time"], qr.astype(np.float32), {"units": "m^3/s"}),
+            "Qr": (dims, data.astype(np.float32), {"units": "m^3/s"}),
         },
         coords={
             "divide_id": ("divide_id", DIVIDES),
@@ -70,6 +80,10 @@ def main() -> None:
     daily_times = np.datetime64("1981-01-01") + np.arange(n_days).astype("timedelta64[D]")
     daily = (np.arange(4)[:, None] + 1) * 100 + np.arange(n_days)[None, :]
     write_store(FIXTURES / "qr_daily.ic", daily_times, daily, "days since 1981-01-01")
+    write_store(
+        FIXTURES / "qr_daily_time_major.ic", daily_times, daily, "days since 1981-01-01",
+        time_major=True,
+    )
 
     n_hours = n_days * 24
     hourly_times = np.datetime64("1981-01-01T00") + np.arange(n_hours).astype("timedelta64[h]")
diff --git a/scripts/snap_gridded_gauges.py b/scripts/snap_gridded_gauges.py
new file mode 100644
index 00000000..10409a84
--- /dev/null
+++ b/scripts/snap_gridded_gauges.py
@@ -0,0 +1,103 @@
+"""Build the CONUS gauge CSV for ddrs's gridded (ISIMIP DDM30) routing path.
+
+Gridded counterpart of the gages_3000 gauge selection used by the MERIT-fabric
+path: takes `gages_3000.csv`, keeps gauges with DRAIN_SQKM above a minimum
+(default 2,000 km2 -- a 0.5 degree DDM30 cell is ~2,350 km2, so 2,416 of the
+3,211 gages_3000 gauges are sub-cell and cannot be represented by a single
+routing element), snaps each surviving gauge to a DDM30 cell via
+`ddr_benchmarks.gridded.snap_gauges` (drainage-area-matched 3x3 neighborhood
+search against per-cell upstream area from the sub-reach adjacency zarr), then
+keeps gauges present in the USGS observation store with daily coverage above a
+minimum (default 0.9) over 1981-10-01..1997-09-30 (train_conus.py measures coverage
+from `--train-start` to its `--test-end` default), which yields DDR's 620 gauges.
+Mirrors `~/projects/ddr/examples/juniata_gridded/train_conus.py::build_network`
+(lines 51-91) exactly, including its default thresholds.
+
+Output columns: STAID,STANAME,DRAIN_SQKM,LAT_GAGE,LNG_GAGE,COMID,da_ratio
+`COMID` is the snapped DDM30 cell id (ddrs's gauge reader joins on `COMID`);
+`da_ratio` is snap_gauges's cell-upstream-area / gauge-DA ratio, informational.
+
+Run under DDR's venv (needs `ddr_benchmarks` and `ddr` importable):
+    cd ~/projects/ddr && \
+    ~/projects/ddr/.venv/bin/python ~/projects/ddrs/scripts/snap_gridded_gauges.py
+"""
+
+import argparse
+import logging
+from pathlib import Path
+
+import numpy as np
+import pandas as pd
+import zarr
+
+SUBREACH = Path("/home/tbindas/projects/ddr/data/ddm30/ddm30_subreach_adjacency.zarr")
+OBS = Path("/mnt/ssd1/data/icechunk/usgs_daily_observations")
+GAGES = Path("/home/tbindas/projects/ddr/references/gage_info/gages_3000.csv")
+OUT_DEFAULT = "/home/tbindas/projects/ddr/references/gage_info/ddm30_conus_gauges.csv"
+
+MIN_DA_KM2 = 2000.0
+MIN_COVERAGE = 0.9
+START = "1981-10-01"
+END = "1997-09-30"  # train_conus.py measures coverage over train_start..test_end (default 1997-09-30)
+
+log = logging.getLogger("snap_gridded_gauges")
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument("--out", default=OUT_DEFAULT)
+    parser.add_argument("--min-da-km2", type=float, default=MIN_DA_KM2)
+    parser.add_argument("--min-coverage", type=float, default=MIN_COVERAGE)
+    args = parser.parse_args()
+
+    logging.basicConfig(level=logging.INFO, format="%(message)s")
+
+    from ddr_benchmarks.gridded import cell_areas_km2, snap_gauges, topo_accumulate
+
+    from ddr.io.readers import read_ic
+
+    g = zarr.open_group(str(SUBREACH), mode="r")
+    parent = g["parent_cell"][:]
+    node_ids = g["order"][:]
+    rows, cols = g["indices_0"][:], g["indices_1"][:]
+    n_all = len(node_ids)
+    dn = np.full(n_all, -1, dtype=np.int64)
+    dn[cols] = rows
+
+    _, inv, cnt = np.unique(parent, return_inverse=True, return_counts=True)
+    k_per_node = cnt[inv]
+    uparea = topo_accumulate(cell_areas_km2(g["lat"][:]) / k_per_node, dn)
+
+    # the cell's outlet is its most downstream sub-reach
+    sub_idx = node_ids % 1000
+    outlet_of_cell: dict[int, int] = {}
+    for i in range(n_all):
+        c = int(parent[i])
+        if c not in outlet_of_cell or sub_idx[i] > sub_idx[outlet_of_cell[c]]:
+            outlet_of_cell[c] = i
+    ua_cell = {c: float(uparea[i]) for c, i in outlet_of_cell.items()}
+
+    gauges = pd.read_csv(GAGES, dtype={"STAID": str})
+    gauges["STAID"] = gauges.STAID.str.zfill(8)
+    gauges = snap_gauges(gauges[gauges.DRAIN_SQKM > args.min_da_km2], ua_cell)
+    obs_ds = read_ic(str(OBS))
+    gauges = gauges[gauges.STAID.isin(set(obs_ds.gage_id.values.astype(str)))]
+    cov = (
+        obs_ds["streamflow"]
+        .sel(gage_id=gauges.STAID.tolist(), time=slice(START, END))
+        .notnull()
+        .mean("time")
+        .values
+    )
+    gauges = gauges[cov > args.min_coverage].reset_index(drop=True)
+    log.info("%d gauges after DA match and observation coverage", len(gauges))
+
+    out = gauges[["STAID", "STANAME", "DRAIN_SQKM", "LAT_GAGE", "LNG_GAGE", "cell", "da_ratio"]].rename(
+        columns={"cell": "COMID"}
+    )
+    out.to_csv(args.out, index=False, quoting=1)  # quoting=1 == csv.QUOTE_ALL, keeps STAID's leading zeros
+    log.info("wrote %d gauges to %s", len(out), args.out)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/src/adjacency/cache.rs b/src/adjacency/cache.rs
index 487a8bf8..17bdd3ca 100644
--- a/src/adjacency/cache.rs
+++ b/src/adjacency/cache.rs
@@ -37,8 +37,12 @@ use serde::{Deserialize, Serialize};
 use crate::adjacency::build::{build_conus_adjacency, BuildError, ConusAdjacency};
 use crate::adjacency::fabric::{read_fabric_records, resolve_fabric};
 use crate::adjacency::gauges::build_gauge_subgraphs;
+use crate::adjacency::gridded::GriddedNetwork;
 use crate::adjacency::subdivide::{plan_reaches, subdivide, ReachPlan, SubdividedAdjacency};
-use crate::adjacency::zarr_write::{write_conus_store_subdivided, write_gauges_store};
+use crate::adjacency::zarr_write::{
+    write_conus_store_subdivided, write_conus_store_subdivided_as, write_gauges_store,
+    write_gauges_store_as,
+};
 use crate::adjacency::BUILDER_VERSION;
 use crate::config::Subdivision;
 use crate::data::error::DataError;
@@ -117,6 +121,14 @@ struct CacheManifest {
     build_duration_secs: f64,
     /// `git rev-parse HEAD` at build time, empty string if not available.
     ddrs_git_sha: String,
+    /// `"merit"` (fabric builder) or `"ddm30"` (`gridded_network`). Defaulted
+    /// for manifests written before the gridded path existed.
+    #[serde(default = "default_network_kind")]
+    network_kind: String,
+}
+
+fn default_network_kind() -> String {
+    "merit".to_string()
 }
 
 // ── public API ───────────────────────────────────────────────────────────────
@@ -268,21 +280,12 @@ pub fn resolve_or_build(
         dropped_comids,
         build_duration_secs,
         ddrs_git_sha: capture_git_sha(),
+        network_kind: "merit".to_string(),
     };
     let json = serde_json::to_string_pretty(&manifest)?;
     fs::write(tmp_dir.join("manifest.json"), json)?;
 
-    // Atomic rename into place.  If the target already exists (lost race
-    // between two concurrent builds) treat it as a hit and discard the tmp.
-    match fs::rename(&tmp_dir, &cache_dir) {
-        Ok(()) => {}
-        Err(_) if is_cache_hit(&cache_dir)
-            && store_paths(&cache_dir, &fabric_stem).conus.is_dir() => {
-            // Another process won the race; discard our tmp.
-            let _ = fs::remove_dir_all(&tmp_dir);
-        }
-        Err(e) => return Err(AdjacencyCacheError::Io(e)),
-    }
+    commit_build(&tmp_dir, &cache_dir, &fabric_stem)?;
 
     println!(
         "  adjacency cache written to {} ({:.1}s)",
@@ -297,6 +300,148 @@ pub fn resolve_or_build(
     })
 }
 
+/// Resolve the adjacency cache for a **gridded** (DDM30 sub-reach) network,
+/// building if necessary — the `data_sources.gridded_network` counterpart of
+/// [`resolve_or_build`].
+///
+/// The store is DDR's sub-reach adjacency zarr (`gridded::GriddedNetwork`).
+/// It is already a subdivided graph, so there is no fabric read and no reach
+/// plan: the build relabels it into ddrs's parent/piece layout, writes it as
+/// `<stem>_adjacency.zarr`, and cuts the per-gauge subgraphs from the sub-reach
+/// rows — `position_lookup` maps a cell id to its **last** row, which is the
+/// cell's outlet piece, so a gauge snapped to a cell is read where DDR's
+/// trainers read it (`outlet_of_cell`). `<stem>` is the store's file stem with
+/// a trailing `_adjacency` dropped (`juniata_subreach_adjacency.zarr` →
+/// `juniata_subreach_{,gages_}adjacency.zarr`).
+///
+/// Key: blake3(store fingerprint ∥ gages fingerprint ∥ "gridded" ∥
+/// BUILDER_VERSION). The store fingerprint hashes every file under the zarr
+/// directory (sorted relative path ∥ NUL ∥ bytes), so any array edit rebuilds.
+pub fn resolve_or_build_gridded(
+    workspace_root: &Path,
+    gridded: &Path,
+    gages_csv: &Path,
+) -> Result<AdjacencyCacheOutcome, AdjacencyCacheError> {
+    let stem = gridded
+        .file_stem()
+        .map(|s| s.to_string_lossy().into_owned())
+        .unwrap_or_else(|| "ddm30".into());
+    let stem = stem.strip_suffix("_adjacency").unwrap_or(&stem).to_string();
+
+    let store_fp = dir_fingerprint(gridded)?;
+    let gages_fp = gages_fingerprint(gages_csv)?;
+    let key = content_key_gridded(&store_fp, &gages_fp);
+
+    let cache_dir = adjacency_cache_dir(workspace_root, &key);
+    if is_cache_hit(&cache_dir) {
+        let paths = store_paths(&cache_dir, &stem);
+        if paths.conus.is_dir() && paths.gages.is_dir() {
+            return Ok(AdjacencyCacheOutcome { paths, key, cache_hit: true });
+        }
+        eprintln!(
+            "  adjacency cache {} is incomplete (manifest without stores) — rebuilding",
+            cache_dir.display()
+        );
+        fs::remove_dir_all(&cache_dir)?;
+    }
+
+    println!(
+        "  building DDM30 sub-reach adjacency from {}",
+        gridded.display()
+    );
+    let tmp_dir = workspace_root
+        .join("adjacency")
+        .join(format!(".tmp-{}", key));
+    let _ = fs::remove_dir_all(&tmp_dir);
+    fs::create_dir_all(&tmp_dir)?;
+    let t0 = Instant::now();
+
+    let network = GriddedNetwork::open(gridded).map_err(AdjacencyCacheError::Data)?;
+    let expanded = network.to_subdivided();
+    let n = expanded.order.len();
+    let n_parent = expanded.parent_order.len();
+    let nnz = expanded.rows.len();
+    println!(
+        "  gridded network: {n_parent} cells → {n} sub-reaches ({:.2}x), {nnz} edges",
+        n as f64 / n_parent as f64
+    );
+
+    let conus_dest = tmp_dir.join(format!("{stem}_adjacency.zarr"));
+    write_conus_store_subdivided_as(&expanded, &conus_dest, GRIDDED_GEODATASET)
+        .map_err(AdjacencyCacheError::Data)?;
+
+    // Same sub-reach-space view as the fabric path: a gauge's cell resolves to
+    // that cell's outlet piece (last row).
+    let expanded_view = ConusAdjacency {
+        order: expanded.order.clone(),
+        rows: expanded.rows.clone(),
+        cols: expanded.cols.clone(),
+        length_m: expanded.length_m.clone(),
+        slope: expanded.slope.clone(),
+        dropped_comids: Vec::new(),
+    };
+    let subgraphs = build_gauge_subgraphs(&expanded_view, gages_csv)
+        .map_err(AdjacencyCacheError::Data)?;
+    let n_gauges = subgraphs.len();
+    let gages_dest = tmp_dir.join(format!("{stem}_gages_adjacency.zarr"));
+    write_gauges_store_as(&subgraphs, n, &gages_dest, GRIDDED_GEODATASET)
+        .map_err(AdjacencyCacheError::Data)?;
+
+    let build_duration_secs = t0.elapsed().as_secs_f64();
+    let manifest = CacheManifest {
+        key: key.clone(),
+        builder_version: BUILDER_VERSION,
+        fabric_path: gridded.to_path_buf(),
+        fabric_resolved_path: gridded.to_path_buf(),
+        fabric_layer: None,
+        fabric_fingerprint: store_fp,
+        gages_path: gages_csv.to_path_buf(),
+        gages_fingerprint: gages_fp,
+        n,
+        n_parent,
+        nnz,
+        n_gauges,
+        dropped_comids: Vec::new(),
+        build_duration_secs,
+        ddrs_git_sha: capture_git_sha(),
+        network_kind: GRIDDED_GEODATASET.to_string(),
+    };
+    fs::write(
+        tmp_dir.join("manifest.json"),
+        serde_json::to_string_pretty(&manifest)?,
+    )?;
+
+    commit_build(&tmp_dir, &cache_dir, &stem)?;
+
+    println!(
+        "  adjacency cache written to {} ({:.1}s)",
+        cache_dir.display(),
+        build_duration_secs
+    );
+    Ok(AdjacencyCacheOutcome {
+        paths: store_paths(&cache_dir, &stem),
+        key,
+        cache_hit: false,
+    })
+}
+
+/// `geodataset` attr / manifest `network_kind` for the gridded path.
+const GRIDDED_GEODATASET: &str = "ddm30";
+
+/// Atomically move a finished build into place. If the target already exists
+/// (lost race between two concurrent builds) treat it as a hit and discard the
+/// temp dir.
+fn commit_build(tmp_dir: &Path, cache_dir: &Path, stem: &str) -> Result<(), AdjacencyCacheError> {
+    match fs::rename(tmp_dir, cache_dir) {
+        Ok(()) => Ok(()),
+        Err(_) if is_cache_hit(cache_dir) && store_paths(cache_dir, stem).conus.is_dir() => {
+            let _ = fs::remove_dir_all(tmp_dir);
+            Ok(())
+        }
+        Err(e) => Err(AdjacencyCacheError::Io(e)),
+    }
+}
+
 /// Resolve `<workspace_root>/adjacency/<key>/` for a given key.
 pub fn adjacency_cache_dir(workspace_root: &Path, key: &str) -> PathBuf {
     workspace_root.join("adjacency").join(key)
@@ -495,6 +640,69 @@ fn content_key(
     hex.as_str()[..16].to_string()
 }
 
+/// Content key for [`resolve_or_build_gridded`]: blake3(store_fp ∥ gages_fp ∥
+/// "gridded" ∥ BUILDER_VERSION)[..16]. The literal separates the namespace
+/// from fabric keys; `params.subdivision` is absent because config validation
+/// rejects it with `gridded_network`.
+fn content_key_gridded(store_fp: &str, gages_fp: &str) -> String {
+    let mut h = blake3::Hasher::new();
+    h.update(store_fp.as_bytes());
+    h.update(b"\n");
+    h.update(gages_fp.as_bytes());
+    h.update(b"\ngridded\n");
+    h.update(BUILDER_VERSION.to_le_bytes().as_ref());
+    let hex = h.finalize().to_hex();
+    hex.as_str()[..16].to_string()
+}
+
+#[doc(hidden)]
+pub fn content_key_gridded_for_test(store_fp: &str, gages_fp: &str) -> String {
+    content_key_gridded(store_fp, gages_fp)
+}
+
+/// blake3 over every regular file under `dir`, recursively, in sorted
+/// relative-path order (path ∥ NUL ∥ bytes). The fingerprint of a zarr store:
+/// metadata and chunks alike, so editing any array — or a store attribute —
+/// changes the key.
+pub fn dir_fingerprint(dir: &Path) -> Result<String, AdjacencyCacheError> {
+    fn walk(root: &Path, dir: &Path, out: &mut Vec<PathBuf>) -> std::io::Result<()> {
+        for entry in fs::read_dir(dir)? {
+            let p = entry?.path();
+            if p.is_dir() {
+                walk(root, &p, out)?;
+            } else if p.is_file() {
+                out.push(p);
+            }
+        }
+        Ok(())
+    }
+    if !dir.is_dir() {
+        return Err(AdjacencyCacheError::Io(std::io::Error::new(
+            std::io::ErrorKind::NotFound,
+            format!("gridded_network store is not a directory: {}", dir.display()),
+        )));
+    }
+    let mut files = Vec::new();
+    walk(dir, dir, &mut files).map_err(AdjacencyCacheError::Io)?;
+    files.sort();
+    let mut hasher = blake3::Hasher::new();
+    let mut buf = vec![0u8; 65536];
+    for f in &files {
+        let rel = f.strip_prefix(dir).unwrap_or(f);
+        hasher.update(rel.to_string_lossy().as_bytes());
+        hasher.update(&[0]);
+        let mut reader = BufReader::new(fs::File::open(f).map_err(AdjacencyCacheError::Io)?);
+        loop {
+            let n = reader.read(&mut buf).map_err(AdjacencyCacheError::Io)?;
+            if n == 0 {
+                break;
+            }
+            hasher.update(&buf[..n]);
+        }
+    }
+    Ok(hasher.finalize().to_hex().to_string())
+}
+
 /// Test hook for [`content_key`]. Integration tests live in their own crate and
 /// cannot reach a private fn; exposing the real function (rather than
 /// reimplementing the hash in the test) is what makes
diff --git a/src/adjacency/gridded.rs b/src/adjacency/gridded.rs
new file mode 100644
index 00000000..4c3f9a22
--- /dev/null
+++ b/src/adjacency/gridded.rs
@@ -0,0 +1,358 @@
+//! Read a DDR gridded (ISIMIP DDM30) **sub-reach** adjacency zarr and express
+//! it as the [`SubdividedAdjacency`] the managed builder already knows how to
+//! write and the dataset already knows how to route.
+//!
+//! The store is the output of DDR's `scripts/build_subdivided_adjacency.py`
+//! (DeepGroundwater/ddr #194). Per node (sub-reach) it carries:
+//!
+//! ```text
+//!   order        int64   node id = cell_id * 1000 + sub_index (upstream-most first)
+//!   parent_cell  int32   DDM30 cell id = row * 720 + col (row 0 = 55.75°S)
+//!   indices_0/1  int32   COO (downstream row, upstream col), strictly lower-tri
+//!   length_m     float32 piece length (the cell's flow length / pieces)
+//!   slope        float32 inherited from the cell
+//!   lat, lon     float32 cell centre (unused here)
+//! ```
+//!
+//! and the pieces of a cell form a chain that is **contiguous in `order`**,
+//! upstream first. That is exactly ddrs's subdivided layout (`zarr.rs:36-46`):
+//! parent `p` owns rows `parent_offset[p]..parent_offset[p+1]` and its outlet —
+//! the row a gauge is read at — is the last one. So the translation is a
+//! relabelling, not a rebuild:
+//!
+//! ```text
+//!   DDM30 store                         SubdividedAdjacency
+//!   order       [c₀·1000+0, c₀·1000+1, c₁·1000+0, …]
+//!   parent_cell [c₀, c₀, c₁, …]  ──►   order        = [c₀, c₀, c₁, …]
+//!                                       parent_order = [c₀, c₁, …]
+//!                                       parent_offset= [0, 2, 3, …]
+//!   indices_0/1, length_m, slope ──►   rows/cols, length_m, slope  (copied)
+//! ```
+//!
+//! Attributes and Q′ are keyed on the cell id (DDR writes both stores with
+//! `COMID`/`divide_id` = cell id), so `AttributesStore::open(…, parent_order)`
+//! and the streamflow reader need no change, and `pieces_per_row_divisor`
+//! splits each cell's Q′ across its pieces the way DDR's trainers divide by
+//! `k_per_node`.
+//!
+//! **Not supported:** DDR's unsplit cell adjacency (`ddm30_adjacency.zarr`,
+//! no `parent_cell`). DDR's trainers use the sub-reach store; `open` refuses a
+//! store without `parent_cell` with a message saying which script produces one.
+
+use std::path::{Path, PathBuf};
+use std::sync::Arc;
+
+use zarrs::array::Array as ZarrArray;
+use zarrs::filesystem::FilesystemStore;
+use zarrs::group::Group;
+use zarrs::storage::ReadableStorage;
+
+use crate::adjacency::subdivide::SubdividedAdjacency;
+use crate::data::error::{DataError, Result};
+
+/// A DDM30 sub-reach network as read from disk, validated.
+#[derive(Debug, Clone)]
+pub struct GriddedNetwork {
+    pub path: PathBuf,
+    /// `order`: DDR node ids (`cell * 1000 + sub`). Kept for diagnostics only.
+    pub node_ids: Vec<i64>,
+    /// DDM30 cell id per sub-reach row.
+    pub parent_cell: Vec<i32>,
+    /// COO `indices_0` — downstream row.
+    pub rows: Vec<i32>,
+    /// COO `indices_1` — upstream row.
+    pub cols: Vec<i32>,
+    pub length_m: Vec<f32>,
+    pub slope: Vec<f32>,
+    /// Row where each cell's contiguous run starts, plus a final `n`.
+    /// `parent_offset[p]..parent_offset[p+1]` are cell `p`'s rows.
+    parent_offset: Vec<i32>,
+}
+
+impl GriddedNetwork {
+    /// Open and validate a DDM30 sub-reach store.
+    pub fn open(path: impl Into<PathBuf>) -> Result<Self> {
+        let path = path.into();
+        let storage: ReadableStorage =
+            Arc::new(FilesystemStore::new(&path).map_err(|e| zarr_err(&path, e))?);
+        let _root = Group::open(storage.clone(), "/").map_err(|e| zarr_err(&path, e))?;
+
+        let node_ids = read_i64_or_i32(&storage, &path, "/order")?;
+        let n = node_ids.len();
+        let parent_cell = match read_i32(&storage, &path, "/parent_cell") {
+            Ok(v) => v,
+            Err(_) => {
+                return Err(DataError::Malformed {
+                    path,
+                    message: "gridded_network store has no `parent_cell` array — this is \
+                              DDR's unsplit cell adjacency, not a sub-reach store. ddrs \
+                              routes the sub-reach network only; build one with DDR's \
+                              scripts/build_subdivided_adjacency.py"
+                        .to_string(),
+                });
+            }
+        };
+        let rows = read_i32(&storage, &path, "/indices_0")?;
+        let cols = read_i32(&storage, &path, "/indices_1")?;
+        let length_m = read_f32(&storage, &path, "/length_m")?;
+        let slope = read_f32(&storage, &path, "/slope")?;
+
+        let malformed = |message: String| DataError::Malformed {
+            path: path.clone(),
+            message,
+        };
+
+        if parent_cell.len() != n || length_m.len() != n || slope.len() != n {
+            return Err(malformed(format!(
+                "order/parent_cell/length_m/slope lengths disagree: {n} / {} / {} / {}",
+                parent_cell.len(),
+                length_m.len(),
+                slope.len()
+            )));
+        }
+        if rows.len() != cols.len() {
+            return Err(malformed(format!(
+                "indices_0/indices_1 lengths disagree: {} / {}",
+                rows.len(),
+                cols.len()
+            )));
+        }
+        // Routing invariant 3 (forward substitution): every edge must run from
+        // a lower row (upstream) to a strictly higher row (downstream). A
+        // self-edge would also break `subdivide`'s outlet→inlet argument.
+        for (k, (&r, &c)) in rows.iter().zip(cols.iter()).enumerate() {
+            if r < 0 || c < 0 || r as usize >= n || c as usize >= n {
+                return Err(malformed(format!(
+                    "edge {k} ({r} <- {c}) is outside 0..{n}"
+                )));
+            }
+            if r <= c {
+                return Err(malformed(format!(
+                    "edge {k} ({r} <- {c}) is not strictly lower-triangular; the \
+                     sub-reach store must be topologically ordered (downstream row > \
+                     upstream row)"
+                )));
+            }
+        }
+        for (i, (&l, &s)) in length_m.iter().zip(slope.iter()).enumerate() {
+            if !(l.is_finite() && l > 0.0) || !s.is_finite() {
+                return Err(malformed(format!(
+                    "row {i} (node {}) has length_m {l} / slope {s}; both must be finite \
+                     and length positive",
+                    node_ids[i]
+                )));
+            }
+        }
+
+        // Each cell's pieces must be one contiguous run: ddrs reads a gauge at
+        // `parent_offset[p+1] - 1`, and `pieces_per_row_divisor` counts a
+        // parent's rows from the offsets. A cell that appears in two runs
+        // would be split into two "parents" with the same id, and the second
+        // would shadow the first in `IdIndex`.
+        let mut parent_offset = vec![0_i32];
+        let mut seen = std::collections::HashSet::with_capacity(n);
+        for i in 1..=n {
+            if i == n || parent_cell[i] != parent_cell[i - 1] {
+                let cell = parent_cell[i - 1];
+                if !seen.insert(cell) {
+                    return Err(malformed(format!(
+                        "cell {cell} occupies more than one contiguous run of rows; the \
+                         pieces of a cell must be adjacent in `order` (upstream first)"
+                    )));
+                }
+                parent_offset.push(i as i32);
+            }
+        }
+
+        Ok(Self {
+            path,
+            node_ids,
+            parent_cell,
+            rows,
+            cols,
+            length_m,
+            slope,
+            parent_offset,
+        })
+    }
+
+    /// Number of sub-reach rows.
+    pub fn n(&self) -> usize {
+        self.node_ids.len()
+    }
+
+    /// Number of distinct DDM30 cells (parents).
+    pub fn n_cells(&self) -> usize {
+        self.parent_offset.len() - 1
+    }
+
+    /// Relabel into ddrs's subdivided layout (see the module diagram). Pure
+    /// bookkeeping: no edge or length is recomputed.
+    pub fn to_subdivided(&self) -> SubdividedAdjacency {
+        let parent_order: Vec<i32> = self.parent_offset[..self.n_cells()]
+            .iter()
+            .map(|&start| self.parent_cell[start as usize])
+            .collect();
+        SubdividedAdjacency {
+            order: self.parent_cell.clone(),
+            parent_order,
+            parent_offset: self.parent_offset.clone(),
+            rows: self.rows.clone(),
+            cols: self.cols.clone(),
+            length_m: self.length_m.clone(),
+            slope: self.slope.clone(),
+        }
+    }
+}
+
+// ---------- zarr helpers (mirror src/data/store/zarr.rs's private ones) ----------
+
+fn read_i32(storage: &ReadableStorage, store_path: &Path, array_path: &str) -> Result<Vec<i32>> {
+    let arr = ZarrArray::open(storage.clone(), array_path).map_err(|e| zarr_err(store_path, e))?;
+    arr.retrieve_array_subset::<Vec<i32>>(&arr.subset_all())
+        .map_err(|e| zarr_err(store_path, e))
+}
+
+fn read_f32(storage: &ReadableStorage, store_path: &Path, array_path: &str) -> Result<Vec<f32>> {
+    let arr = ZarrArray::open(storage.clone(), array_path).map_err(|e| zarr_err(store_path, e))?;
+    arr.retrieve_array_subset::<Vec<f32>>(&arr.subset_all())
+        .map_err(|e| zarr_err(store_path, e))
+}
+
+/// DDR writes `order` as int64 (`build_subdivided_adjacency.py`); accept int32
+/// too so a hand-rolled store still opens.
+fn read_i64_or_i32(storage: &ReadableStorage, store_path: &Path, array_path: &str) -> Result<Vec<i64>> {
+    let arr = ZarrArray::open(storage.clone(), array_path).map_err(|e| zarr_err(store_path, e))?;
+    match arr.retrieve_array_subset::<Vec<i64>>(&arr.subset_all()) {
+        Ok(v) => Ok(v),
+        Err(_) => arr
+            .retrieve_array_subset::<Vec<i32>>(&arr.subset_all())
+            .map(|v| v.into_iter().map(i64::from).collect())
+            .map_err(|e| zarr_err(store_path, e)),
+    }
+}
+
+fn zarr_err<E: std::error::Error + Send + Sync + 'static>(path: &Path, source: E) -> DataError {
+    DataError::Zarr {
+        path: path.to_path_buf(),
+        source: Box::new(source),
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use zarrs::array::{data_type, ArrayBuilder};
+    use zarrs::group::GroupBuilder;
+
+    /// Two cells, 100 (3 pieces) → 200 (2 pieces): a 5-row chain.
+    ///
+    /// ```text
+    ///   100·0 → 100·1 → 100·2 → 200·0 → 200·1
+    ///   row 0    1       2       3       4
+    /// ```
+    struct Synthetic {
+        order: Vec<i64>,
+        parent: Vec<i32>,
+        rows: Vec<i32>,
+        cols: Vec<i32>,
+        length: Vec<f32>,
+        slope: Vec<f32>,
+    }
+
+    fn chain() -> Synthetic {
+        Synthetic {
+            order: vec![100_000, 100_001, 100_002, 200_000, 200_001],
+            parent: vec![100, 100, 100, 200, 200],
+            rows: vec![1, 2, 3, 4],
+            cols: vec![0, 1, 2, 3],
+            length: vec![3000.0; 5],
+            slope: vec![0.001, 0.001, 0.001, 0.002, 0.002],
+        }
+    }
+
+    fn write_store(dir: &Path, s: &Synthetic, with_parent: bool) {
+        let storage = Arc::new(FilesystemStore::new(dir).unwrap());
+        GroupBuilder::new().build(storage.clone(), "/").unwrap().store_metadata().unwrap();
+        macro_rules! put {
+            ($name:expr, $dt:expr, $fill:expr, $data:expr) => {{
+                let data = $data;
+                let a = ArrayBuilder::new(vec![data.len() as u64], vec![data.len().max(1) as u64], $dt, $fill)
+                    .build(storage.clone(), $name)
+                    .unwrap();
+                a.store_metadata().unwrap();
+                if !data.is_empty() {
+                    a.store_chunk(&[0], &data).unwrap();
+                }
+            }};
+        }
+        put!("/order", data_type::int64(), 0_i64, s.order.clone());
+        if with_parent {
+            put!("/parent_cell", data_type::int32(), 0_i32, s.parent.clone());
+        }
+        put!("/indices_0", data_type::int32(), 0_i32, s.rows.clone());
+        put!("/indices_1", data_type::int32(), 0_i32, s.cols.clone());
+        put!("/length_m", data_type::float32(), 0.0_f32, s.length.clone());
+        put!("/slope", data_type::float32(), 0.0_f32, s.slope.clone());
+    }
+
+    fn open_synthetic(tag: &str, s: &Synthetic, with_parent: bool) -> Result<GriddedNetwork> {
+        let dir = tempfile::tempdir().unwrap();
+        let store = dir.path().join(format!("{tag}_subreach_adjacency.zarr"));
+        write_store(&store, s, with_parent);
+        GriddedNetwork::open(&store)
+    }
+
+    #[test]
+    fn chain_relabels_into_two_parents_with_contiguous_pieces() {
+        let g = open_synthetic("chain", &chain(), true).expect("open");
+        assert_eq!(g.n(), 5);
+        assert_eq!(g.n_cells(), 2);
+        let sub = g.to_subdivided();
+        assert_eq!(sub.order, vec![100, 100, 100, 200, 200]);
+        assert_eq!(sub.parent_order, vec![100, 200]);
+        assert_eq!(sub.parent_offset, vec![0, 3, 5]);
+        assert_eq!(sub.pieces(0), 3);
+        assert_eq!(sub.pieces(1), 2);
+        // The gauge row for a cell is its LAST piece.
+        assert_eq!(sub.outlet(0), 2);
+        assert_eq!(sub.outlet(1), 4);
+        assert_eq!(sub.rows, vec![1, 2, 3, 4]);
+        assert_eq!(sub.cols, vec![0, 1, 2, 3]);
+        assert_eq!(sub.length_m, vec![3000.0; 5]);
+        assert_eq!(sub.slope[3], 0.002);
+    }
+
+    #[test]
+    fn store_without_parent_cell_is_refused_with_the_fix() {
+        let err = open_synthetic("noparent", &chain(), false).unwrap_err();
+        let msg = err.to_string();
+        assert!(msg.contains("parent_cell"), "{msg}");
+        assert!(msg.contains("build_subdivided_adjacency.py"), "{msg}");
+    }
+
+    #[test]
+    fn upper_triangular_edge_is_refused() {
+        let mut s = chain();
+        s.rows[0] = 0;
+        s.cols[0] = 1; // 0 <- 1: downstream row below upstream row
+        let msg = open_synthetic("upper", &s, true).unwrap_err().to_string();
+        assert!(msg.contains("lower-triangular"), "{msg}");
+    }
+
+    #[test]
+    fn non_contiguous_cell_is_refused() {
+        let mut s = chain();
+        s.parent = vec![100, 200, 100, 200, 200]; // cell 100 split in two runs
+        let msg = open_synthetic("split", &s, true).unwrap_err().to_string();
+        assert!(msg.contains("contiguous"), "{msg}");
+    }
+
+    #[test]
+    fn non_positive_length_is_refused() {
+        let mut s = chain();
+        s.length[2] = 0.0;
+        let msg = open_synthetic("zerolen", &s, true).unwrap_err().to_string();
+        assert!(msg.contains("length_m 0"), "{msg}");
+    }
+}
diff --git a/src/adjacency/mod.rs b/src/adjacency/mod.rs
index 1dc92273..0f73d0b4 100644
--- a/src/adjacency/mod.rs
+++ b/src/adjacency/mod.rs
@@ -35,6 +35,7 @@ pub mod cache;
 pub mod dbf;
 pub mod fabric;
 pub mod gauges;
+pub mod gridded;
 pub mod gpkg;
 pub mod subdivide;
 pub mod validate;
diff --git a/src/adjacency/zarr_write.rs b/src/adjacency/zarr_write.rs
index b7c51a28..d70d7919 100644
--- a/src/adjacency/zarr_write.rs
+++ b/src/adjacency/zarr_write.rs
@@ -76,7 +76,7 @@ pub fn write_conus_store(adj: &ConusAdjacency, dest: &Path) -> Result<()> {
 
     // Root group attrs — mirrors coo_to_zarr (zarr_io.py:131-138) and the real
     // store's root zarr.json.
-    let root_attrs = coo_root_attrs(n);
+    let root_attrs = coo_root_attrs(n, "merit");
     let root = GroupBuilder::new()
         .attributes(root_attrs)
         .build(storage.clone(), "/")
@@ -107,13 +107,24 @@ pub fn write_conus_store(adj: &ConusAdjacency, dest: &Path) -> Result<()> {
 /// [`write_conus_store`] plus the two identity arrays, which the reader would
 /// have synthesized anyway — so the disabled path stays a true no-op.
 pub fn write_conus_store_subdivided(sub: &SubdividedAdjacency, dest: &Path) -> Result<()> {
+    write_conus_store_subdivided_as(sub, dest, "merit")
+}
+
+/// [`write_conus_store_subdivided`] with an explicit `geodataset` root attr
+/// (`"merit"` for the fabric builder, `"ddm30"` for `gridded_network`). The
+/// attr is provenance only — no reader dispatches on it.
+pub fn write_conus_store_subdivided_as(
+    sub: &SubdividedAdjacency,
+    dest: &Path,
+    geodataset: &str,
+) -> Result<()> {
     let storage = Arc::new(FilesystemStore::new(dest).map_err(|e| zarr_err(dest, e))?);
 
     let n_sub = sub.order.len();
     let nnz = sub.rows.len();
 
     let root = GroupBuilder::new()
-        .attributes(coo_root_attrs(n_sub))
+        .attributes(coo_root_attrs(n_sub, geodataset))
         .build(storage.clone(), "/")
         .map_err(|e| zarr_err(dest, e))?;
     root.store_metadata().map_err(|e| zarr_err(dest, e))?;
@@ -141,6 +152,16 @@ pub fn write_conus_store_subdivided(sub: &SubdividedAdjacency, dest: &Path) -> R
 ///
 /// Round-trips through [`crate::data::store::zarr::GagesAdjacencyStore::open`].
 pub fn write_gauges_store(subgraphs: &[GaugeSubgraph], conus_n: usize, dest: &Path) -> Result<()> {
+    write_gauges_store_as(subgraphs, conus_n, dest, "merit")
+}
+
+/// [`write_gauges_store`] with an explicit `geodataset` attr on every subgroup.
+pub fn write_gauges_store_as(
+    subgraphs: &[GaugeSubgraph],
+    conus_n: usize,
+    dest: &Path,
+    geodataset: &str,
+) -> Result<()> {
     let storage = Arc::new(FilesystemStore::new(dest).map_err(|e| zarr_err(dest, e))?);
 
     // Empty root group (matches the real merit_gages store's root zarr.json).
@@ -152,7 +173,7 @@ pub fn write_gauges_store(subgraphs: &[GaugeSubgraph], conus_n: usize, dest: &Pa
     for sg in subgraphs {
         let group_path = format!("/{}", sg.staid.as_str());
 
-        let mut attrs = coo_root_attrs(conus_n);
+        let mut attrs = coo_root_attrs(conus_n, geodataset);
         attrs.insert(
             "gage_catchment".into(),
             serde_json::Value::Number(sg.gage_catchment.into()),
@@ -181,7 +202,7 @@ pub fn write_gauges_store(subgraphs: &[GaugeSubgraph], conus_n: usize, dest: &Pa
 
 /// The COO `format`/`shape`/`geodataset`/`data_types` attr block shared by the
 /// CONUS root and every gauge subgroup (zarr_io.py:131-138, 382-392).
-fn coo_root_attrs(dim: usize) -> serde_json::Map<String, serde_json::Value> {
+fn coo_root_attrs(dim: usize, geodataset: &str) -> serde_json::Map<String, serde_json::Value> {
     let mut m = serde_json::Map::new();
     m.insert("format".into(), serde_json::Value::String("COO".into()));
     m.insert(
@@ -193,7 +214,7 @@ fn coo_root_attrs(dim: usize) -> serde_json::Map<String, serde_json::Value> {
     );
     m.insert(
         "geodataset".into(),
-        serde_json::Value::String("merit".into()),
+        serde_json::Value::String(geodataset.into()),
     );
     let mut data_types = serde_json::Map::new();
     data_types.insert("indices_0".into(), serde_json::Value::String("int32".into()));
diff --git a/src/baseline/cache.rs b/src/baseline/cache.rs
index a75400cf..83eb20f5 100644
--- a/src/baseline/cache.rs
+++ b/src/baseline/cache.rs
@@ -369,6 +369,7 @@ mod tests {
             gages_adjacency: Some(PathBuf::from("/dev/null/gages_adj.zarr")),
             geospatial_fabric: None,
             geospatial_fabric_layer: None,
+            gridded_network: None,
             streamflow: PathBuf::from("/dev/null/sf.ic"),
             observations: PathBuf::from("/dev/null/obs.ic"),
             gages: PathBuf::from("/dev/null/gages.csv"),
@@ -496,6 +497,7 @@ mod tests {
             gages_adjacency: None,
             geospatial_fabric: Some(PathBuf::from("/dev/null/fabric.shp")),
             geospatial_fabric_layer: None,
+            gridded_network: None,
             streamflow: PathBuf::from("/dev/null/sf.ic"),
             observations: PathBuf::from("/dev/null/obs.ic"),
             gages: PathBuf::from("/dev/null/gages.csv"),
diff --git a/src/cli/plan.rs b/src/cli/plan.rs
index 6f5754a6..9fefccbf 100644
--- a/src/cli/plan.rs
+++ b/src/cli/plan.rs
@@ -205,6 +205,9 @@ pub fn plan(input: PlanInput, workspace: &Workspace) -> Result<PlanResult, CliEr
     if let Some(p) = &data_sources.geospatial_fabric {
         pairs.push(("geospatial_fabric".into(), p.clone()));
     }
+    if let Some(p) = &data_sources.gridded_network {
+        pairs.push(("gridded_network".into(), p.clone()));
+    }
     let mut sources = BTreeMap::new();
     for (key, path) in pairs {
         let live = match prior_lock.as_ref().and_then(|l| l.sources.get(&key)) {
@@ -323,13 +326,35 @@ pub(crate) fn resolve_adjacency(
                 cache_hit: None,
             })
         }
+        // Gridded (DDM30 sub-reach zarr) managed build. Validation has already
+        // rejected it alongside a fabric or explicit paths.
+        _ if ds.gridded_network.is_some() => {
+            let gridded = ds.gridded_network.as_ref().expect("checked by guard");
+            let outcome = crate::adjacency::cache::resolve_or_build_gridded(
+                workspace.root(),
+                gridded,
+                &ds.gages,
+            )
+            .map_err(|e| CliError::ConfigInvalid {
+                path: config_path.into(),
+                source: Box::new(e),
+            })?;
+            Ok(ResolvedAdjacency {
+                conus: outcome.paths.conus,
+                gages: outcome.paths.gages,
+                cache_key: Some(outcome.key),
+                cache_hit: Some(outcome.cache_hit),
+            })
+        }
         // Fabric-only (managed build). `validate_data_sources` (config.rs) has
         // already rejected the partial-adjacency and neither-source cases at
         // load time, so a missing fabric here is an internal invariant break.
         _ => {
             let fabric = ds.geospatial_fabric.as_ref().ok_or_else(|| CliError::ConfigInvalid {
                 path: config_path.into(),
-                source: "data_sources: no adjacency paths and no geospatial_fabric".into(),
+                source: "data_sources: no adjacency paths and no geospatial_fabric \
+                         or gridded_network"
+                    .into(),
             })?;
             let outcome = crate::adjacency::cache::resolve_or_build(
                 workspace.root(),
diff --git a/src/cli/sources.rs b/src/cli/sources.rs
index 48a4ae9e..90938edd 100644
--- a/src/cli/sources.rs
+++ b/src/cli/sources.rs
@@ -239,6 +239,9 @@ fn lock_sources_from_config(cfg_path: &Path, ws: &Workspace) -> Result<(), CliEr
     if let Some(p) = &ds.geospatial_fabric {
         pairs.push(("geospatial_fabric".into(), p.clone()));
     }
+    if let Some(p) = &ds.gridded_network {
+        pairs.push(("gridded_network".into(), p.clone()));
+    }
 
     // Parallel reachability + fingerprint. std::thread::scope is fine — these
     // are I/O-bound and the count is small.
diff --git a/src/config.rs b/src/config.rs
index f9225e2c..5d2fd78c 100644
--- a/src/config.rs
+++ b/src/config.rs
@@ -127,6 +127,16 @@ pub struct DataSources {
     /// `.shp`/`.dbf` fabrics.
     #[serde(default)]
     pub geospatial_fabric_layer: Option<String>,
+    /// Path to a DDR gridded (ISIMIP DDM30) **sub-reach** adjacency zarr —
+    /// the output of DDR's `scripts/build_subdivided_adjacency.py` (`order`,
+    /// `parent_cell`, `indices_0/1`, `length_m`, `slope`). A third,
+    /// mutually-exclusive adjacency source next to `geospatial_fabric` and
+    /// the explicit zarr pair: `ddrs plan` turns it into ddrs's subdivided
+    /// store layout (parent = grid cell, pieces = sub-reaches) plus per-gauge
+    /// subgraphs under `.ddrs/adjacency/<key>/`. See
+    /// `docs/superpowers/specs/2026-09-08-ddrs-gridded-routing-design.md`.
+    #[serde(default)]
+    pub gridded_network: Option<std::path::PathBuf>,
 }
 
 #[derive(Debug, Clone, Deserialize)]
@@ -963,6 +973,26 @@ fn validate_data_sources(cfg: &Config) -> std::result::Result<(), String> {
     let has_conus = ds.conus_adjacency.is_some();
     let has_gages = ds.gages_adjacency.is_some();
     let has_fabric = ds.geospatial_fabric.is_some();
+    let has_gridded = ds.gridded_network.is_some();
+
+    // The gridded network is its own managed-build input; combining it with
+    // either other adjacency source would leave one of them silently unused.
+    if has_gridded && has_fabric {
+        return Err(
+            "data_sources: `gridded_network` and `geospatial_fabric` are both set; \
+             they are alternative adjacency sources — keep exactly one."
+                .to_string(),
+        );
+    }
+    if has_gridded && (has_conus || has_gages) {
+        return Err(
+            "data_sources: `gridded_network` is set alongside explicit \
+             `conus_adjacency`/`gages_adjacency` paths; the gridded store is built \
+             into the managed cache by `ddrs plan` — remove the explicit paths \
+             (or drop `gridded_network` to use them as-is)."
+                .to_string(),
+        );
+    }
 
     // Layer selection is a gpkg-only concept; reject it for dBASE fabrics
     // (or with no fabric at all) at load time rather than silently ignoring.
@@ -982,10 +1012,10 @@ fn validate_data_sources(cfg: &Config) -> std::result::Result<(), String> {
         }
     }
 
-    match (has_conus, has_gages, has_fabric) {
+    match (has_conus, has_gages, has_fabric || has_gridded) {
         // Both explicit zarr paths: valid.
         (true, true, _) => Ok(()),
-        // Managed build: neither zarr, fabric present: valid.
+        // Managed build: neither zarr, fabric or gridded network present: valid.
         (false, false, true) => Ok(()),
         // Partial adjacency: exactly one of the two zarr keys provided.
         (true, false, _) => Err(
@@ -998,11 +1028,11 @@ fn validate_data_sources(cfg: &Config) -> std::result::Result<(), String> {
              provide both adjacency paths or remove both and set `geospatial_fabric`."
             .to_string(),
         ),
-        // Neither zarr and no fabric.
+        // Neither zarr and no fabric / gridded network.
         (false, false, false) => Err(
             "data_sources: adjacency sources are missing — either set both \
              `conus_adjacency` and `gages_adjacency`, or set `geospatial_fabric` \
-             for a managed adjacency build."
+             (MERIT) or `gridded_network` (DDM30) for a managed adjacency build."
             .to_string(),
         ),
     }
@@ -1068,6 +1098,22 @@ fn validate_subdivision(cfg: &Config) -> std::result::Result<(), String> {
         );
     }
     if s.enabled {
+        if cfg
+            .data_sources
+            .as_ref()
+            .is_some_and(|ds| ds.gridded_network.is_some())
+        {
+            // The DDM30 sub-reach store arrives already split (DDR sizes its
+            // pieces from celerity at mean flow); ddrs's MERIT reach plan has
+            // no `catchsize`/fabric to work from and would be silently inert.
+            return Err(
+                "params.subdivision: `enabled: true` does not apply to \
+                 `data_sources.gridded_network` — the DDM30 sub-reach store is \
+                 already subdivided by DDR's build_subdivided_adjacency.py. \
+                 Set `enabled: false` (or resize the sub-reaches in DDR)."
+                    .to_string(),
+            );
+        }
         validate_subdivision_reaches_the_builder(cfg)?;
     }
     Ok(())
@@ -1588,6 +1634,84 @@ data_sources:
         );
     }
 
+    #[test]
+    fn gridded_network_alone_is_a_valid_managed_build() {
+        let ds_block = r#"
+data_sources:
+  attributes: /dev/null/attrs.nc
+  gridded_network: /dev/null/ddm30_subreach_adjacency.zarr
+  streamflow: /dev/null/sf.ic
+  observations: /dev/null/obs.ic
+  gages: /dev/null/gages.csv
+"#;
+        let path = write_yaml_with_data_sources("ddrs_ds_gridded_only.yaml", ds_block);
+        let cfg = Config::from_yaml_file(&path).expect("gridded_network alone must be valid");
+        let ds = cfg.data_sources.as_ref().unwrap();
+        assert!(ds.gridded_network.is_some());
+        assert!(ds.conus_adjacency.is_none() && ds.gages_adjacency.is_none());
+    }
+
+    #[test]
+    fn gridded_network_with_fabric_rejected() {
+        let ds_block = r#"
+data_sources:
+  attributes: /dev/null/attrs.nc
+  gridded_network: /dev/null/ddm30_subreach_adjacency.zarr
+  geospatial_fabric: /dev/null/rivers.shp
+  streamflow: /dev/null/sf.ic
+  observations: /dev/null/obs.ic
+  gages: /dev/null/gages.csv
+"#;
+        let path = write_yaml_with_data_sources("ddrs_ds_gridded_fabric.yaml", ds_block);
+        let msg = format!("{}", Config::from_yaml_file(&path).unwrap_err());
+        assert!(
+            msg.contains("gridded_network") && msg.contains("geospatial_fabric"),
+            "expected the both-sources error, got: {msg}"
+        );
+    }
+
+    #[test]
+    fn gridded_network_with_explicit_adjacency_rejected() {
+        let ds_block = r#"
+data_sources:
+  attributes: /dev/null/attrs.nc
+  gridded_network: /dev/null/ddm30_subreach_adjacency.zarr
+  conus_adjacency: /dev/null/conus.zarr
+  gages_adjacency: /dev/null/gages.zarr
+  streamflow: /dev/null/sf.ic
+  observations: /dev/null/obs.ic
+  gages: /dev/null/gages.csv
+"#;
+        let path = write_yaml_with_data_sources("ddrs_ds_gridded_explicit.yaml", ds_block);
+        let msg = format!("{}", Config::from_yaml_file(&path).unwrap_err());
+        assert!(
+            msg.contains("gridded_network") && msg.contains("conus_adjacency"),
+            "expected the explicit-paths error, got: {msg}"
+        );
+    }
+
+    #[test]
+    fn gridded_network_with_subdivision_enabled_rejected() {
+        let block = r#"
+data_sources:
+  attributes: /dev/null/attrs.nc
+  gridded_network: /dev/null/ddm30_subreach_adjacency.zarr
+  streamflow: /dev/null/sf.ic
+  observations: /dev/null/obs.ic
+  gages: /dev/null/gages.csv
+params:
+  use_cuda_graphs: false
+  subdivision:
+    enabled: true
+"#;
+        let path = write_yaml_with_data_sources("ddrs_ds_gridded_subdiv.yaml", block);
+        let msg = format!("{}", Config::from_yaml_file(&path).unwrap_err());
+        assert!(
+            msg.contains("params.subdivision") && msg.contains("gridded_network"),
+            "expected the subdivision-vs-gridded error, got: {msg}"
+        );
+    }
+
     #[test]
     fn partial_adjacency_conus_only_rejected() {
         // Only conus_adjacency, no gages_adjacency → config error.
diff --git a/src/data/store/gage_csv.rs b/src/data/store/gage_csv.rs
index b2134755..b5167041 100644
--- a/src/data/store/gage_csv.rs
+++ b/src/data/store/gage_csv.rs
@@ -51,7 +51,10 @@ struct RawRow {
     lat_gage: f64,
     #[serde(rename = "LNG_GAGE")]
     lng_gage: f64,
-    #[serde(rename = "COMID", default)]
+    /// Outlet reach id. DDR's gridded (DDM30) gauge CSVs write the snapped
+    /// grid cell under `cell` instead of `COMID`; the value plays the same role
+    /// (the id the adjacency `order` is keyed on), so it is accepted as an alias.
+    #[serde(rename = "COMID", alias = "cell", default)]
     comid: Option<i64>,
     #[serde(rename = "COMID_DRAIN_SQKM", default)]
     comid_drain_sqkm: Option<f64>,
@@ -230,6 +233,21 @@ STAID,STANAME,DRAIN_SQKM,LAT_GAGE,LNG_GAGE,COMID,COMID_DRAIN_SQKM,COMID_UNITAREA
         assert_eq!(r1.da_valid, Some(false));
     }
 
+    /// DDR's gridded gauge CSV (`examples/juniata_gridded/data/juniata_gage.csv`
+    /// layout): the snapped DDM30 cell is under `cell`, and there is no COMID,
+    /// DA_VALID or FLOW_SCALE column.
+    #[test]
+    fn gridded_csv_cell_column_is_read_as_comid() {
+        let csv = "STAID,STANAME,DRAIN_SQKM,LAT_GAGE,LNG_GAGE,cell,da_ratio\n\
+                   01567000,\"JUNIATA RIVER AT NEWPORT, PA\",8657.0,40.4785,-77.1294,138445,1.088\n";
+        let m = GageMetadata::from_reader(csv.as_bytes(), std::path::PathBuf::from("<inline>"))
+            .expect("parse gridded csv");
+        let r = &m.rows[0];
+        assert_eq!(r.comid, Some(138445));
+        assert_eq!(r.da_valid, None);
+        assert_eq!(r.flow_scale, None);
+    }
+
     #[test]
     fn lookup_by_staid_uses_padded_form() {
         let m = GageMetadata::from_reader(
diff --git a/src/data/store/icechunk.rs b/src/data/store/icechunk.rs
index 58dbccc0..5806ad45 100644
--- a/src/data/store/icechunk.rs
+++ b/src/data/store/icechunk.rs
@@ -190,6 +190,53 @@ pub struct StreamflowStore {
     #[allow(dead_code)]
     storage: Arc<IcZarrStorage>,
     qr: ZarrArray<dyn ReadableStorageTraits>,
+    /// `true` when `Qr` is stored `(time, divide_id)` — DDR's gridded (DDM30)
+    /// stores; `false` for the contract's `(divide_id, time)`. Decided at open
+    /// from the array's dimension names, falling back to its shape.
+    pub time_major: bool,
+}
+
+/// Which axis of `Qr` is the divide axis. The contract
+/// (`docs/nh-qprime-store-contract.md`) is `(divide_id, time)`, but DDR's
+/// `build_gridded_qprime.py` writes `(time, divide_id)`, and zarrs answers an
+/// out-of-range subset with fill values rather than an error — so a layout
+/// guess that is wrong reads NaN silently. Dimension names decide when present;
+/// otherwise the shape does, and a shape matching neither is refused.
+fn detect_time_major(
+    qr: &ZarrArray<dyn ReadableStorageTraits>,
+    n_divide: usize,
+    n_time: usize,
+    path: &Path,
+) -> Result<bool> {
+    let shape = qr.shape();
+    if shape.len() != 2 {
+        return Err(DataError::Malformed {
+            path: path.to_path_buf(),
+            message: format!("Qr must be 2-D, got shape {shape:?}"),
+        });
+    }
+    if let Some(names) = qr.dimension_names() {
+        let named: Vec<&str> = names.iter().map(|n| n.as_deref().unwrap_or("")).collect();
+        match named.as_slice() {
+            ["divide_id", "time"] => return Ok(false),
+            ["time", "divide_id"] => return Ok(true),
+            _ => {} // unnamed or unexpected names: fall through to the shape
+        }
+    }
+    let (a, b) = (shape[0] as usize, shape[1] as usize);
+    if a == n_divide && b == n_time {
+        Ok(false)
+    } else if a == n_time && b == n_divide {
+        Ok(true)
+    } else {
+        Err(DataError::Malformed {
+            path: path.to_path_buf(),
+            message: format!(
+                "Qr shape {shape:?} matches neither (divide_id, time) = ({n_divide}, {n_time}) \
+                 nor (time, divide_id)"
+            ),
+        })
+    }
 }
 
 impl StreamflowStore {
@@ -239,8 +286,9 @@ impl StreamflowStore {
         // 3. Open the `/Qr` data var (Task 3 will actually read from it).
         let qr = ZarrArray::open(readable.clone(), "/Qr")
             .map_err(|e| ic_err(&path, e))?;
+        let time_major = detect_time_major(&qr, index.len(), n_time, &path)?;
 
-        Ok(Self { path, index, time_start, n_time, resolution, storage, qr })
+        Ok(Self { path, index, time_start, n_time, resolution, storage, qr, time_major })
     }
 }
 
@@ -508,17 +556,28 @@ impl StreamflowStore {
         let div_range_end = max_pos + 1;
         let div_count = div_range_end - min_pos;
 
-        // Qr is stored as (divide_id, time). Subset: axis 0 = divide, axis 1 = time.
-        let subset = zarrs::array::ArraySubset::new_with_ranges(&[
-            (min_pos as u64)..(div_range_end as u64),
-            (start_step as u64)..(end_step as u64),
-        ]);
+        // Contract layout is (divide_id, time): axis 0 = divide, axis 1 = time.
+        // Time-major stores (DDR's gridded Q') swap the axes; the raw buffer is
+        // then (n_steps, div_count) row-major and is addressed accordingly.
+        let div_axis = (min_pos as u64)..(div_range_end as u64);
+        let time_axis = (start_step as u64)..(end_step as u64);
+        let subset = if self.time_major {
+            zarrs::array::ArraySubset::new_with_ranges(&[time_axis, div_axis])
+        } else {
+            zarrs::array::ArraySubset::new_with_ranges(&[div_axis, time_axis])
+        };
         let raw_f32: Vec<f32> = self
             .qr
             .retrieve_array_subset(&subset)
             .map_err(|e| ic_err(&self.path, e))?;
-        // raw_f32 is row-major: shape (div_count, n_steps).
         debug_assert_eq!(raw_f32.len(), div_count * n_steps);
+        let raw_idx = |local_div: usize, t: usize| -> usize {
+            if self.time_major {
+                t * div_count + local_div
+            } else {
+                local_div * n_steps + t
+            }
+        };
 
         // Scatter into the output. Walk `comids` in order; for each
         // non-missing entry consume the next element of `positions`.
@@ -531,8 +590,7 @@ impl StreamflowStore {
             next_present += 1;
             let local_div = div_pos - min_pos;
             for t in 0..n_steps {
-                let raw_idx = local_div * n_steps + t;
-                out[(t, out_col)] = raw_f32[raw_idx];
+                out[(t, out_col)] = raw_f32[raw_idx(local_div, t)];
             }
         }
 
diff --git a/src/data/store/zarr.rs b/src/data/store/zarr.rs
index 51f3adf8..d9250e07 100644
--- a/src/data/store/zarr.rs
+++ b/src/data/store/zarr.rs
@@ -216,13 +216,21 @@ impl GageSubgraph {
     /// node appears as an edge endpoint. Single-divide catchments have NO
     /// edges, so this returns empty — callers must filter with
     /// [`GageSubgraph::is_headwater`] first, as training does.
+    ///
+    /// On a **subdivided** store `order` repeats a parent's id once per piece,
+    /// so the position set is deduplicated by id: each divide (MERIT reach or
+    /// DDM30 cell) appears once, in the position order of its first piece.
+    /// The baseline sums Q′ per divide, and Q′ is stored per divide, so a
+    /// per-piece list would count every divide `m` times.
     pub fn upstream_comids(&self, conus: &ConusAdjacencyStore) -> Vec<Comid> {
         let mut positions: std::collections::BTreeSet<i32> = std::collections::BTreeSet::new();
         positions.extend(self.indices_0.iter().copied());
         positions.extend(self.indices_1.iter().copied());
+        let mut seen: std::collections::HashSet<Comid> = std::collections::HashSet::new();
         positions
             .into_iter()
             .map(|pos| conus.order[pos as usize])
+            .filter(|c| seen.insert(*c))
             .collect()
     }
 }
@@ -376,6 +384,26 @@ mod tests {
         assert_eq!(comids, vec![Comid(100), Comid(200), Comid(300), Comid(400)]);
     }
 
+    /// Subdivided store: parent 100 owns rows 0..3, parent 200 owns rows 3..5
+    /// (`order` repeats the parent id per piece). The upstream set of a gauge
+    /// on the outlet piece names each parent ONCE — the baseline reads Q′ per
+    /// parent, and a per-piece list would triple-count parent 100.
+    #[test]
+    fn upstream_comids_names_each_subdivided_parent_once() {
+        let mut conus = fake_conus(vec![100, 100, 100, 200, 200]);
+        conus.parent_order = vec![Comid(100), Comid(200)];
+        conus.parent_offset = vec![0, 3, 5];
+        conus.index = IdIndex::new(conus.parent_order.clone());
+        let sg = GageSubgraph {
+            staid: Staid::from("00000004"),
+            gage_idx: 4,
+            gage_catchment: "200".into(),
+            indices_0: vec![1, 2, 3, 4],
+            indices_1: vec![0, 1, 2, 3],
+        };
+        assert_eq!(sg.upstream_comids(&conus), vec![Comid(100), Comid(200)]);
+    }
+
     #[test]
     fn single_divide_subgraph_is_headwater_and_has_empty_upstream() {
         // Single-divide catchments have NO edges in the gages store — only a
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diff --git a/tests/fixtures/qr_daily_time_major.ic/transactions/1CECHNKREP0F1RSTCMT0 b/tests/fixtures/qr_daily_time_major.ic/transactions/1CECHNKREP0F1RSTCMT0
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diff --git a/tests/gridded_acceptance.rs b/tests/gridded_acceptance.rs
new file mode 100644
index 00000000..d890ec0b
--- /dev/null
+++ b/tests/gridded_acceptance.rs
@@ -0,0 +1,105 @@
+//! End-to-end routing acceptance on the committed gridded (ISIMIP DDM30)
+//! Juniata bundle: full `train-and-test` on CPU through the gridded managed
+//! build, then metric floors on the manifest.
+//!
+//! Reference result (2026-09-09, seed 42, 30 epochs): routed NSE 0.751 /
+//! KGE 0.730 vs summed-Q' baseline NSE 0.594 / KGE 0.672. Seeds {42, 7, 123}
+//! spanned NSE 0.744–0.758 / KGE 0.728–0.732. DDR's Python trainer reports
+//! 0.795 / 0.737 on the same bundle: the gap is the different RNG window
+//! stream plus ddrs's parent-space KAN head (one parameter set per cell;
+//! DDR varies `log10_uparea` per sub-reach) — see
+//! `docs/superpowers/specs/2026-09-08-ddrs-gridded-routing-design.md` §7.
+//! The baseline has no RNG and matches DDR's 0.594 / 0.671 to rounding, so it
+//! gets a tight band and doubles as the cross-implementation reader check —
+//! it is what caught the time-major `Qr(time, divide_id)` layout of DDR's
+//! gridded Q' store.
+//!
+//! Runs only at opt-level 3 (~30 s; a debug build would take minutes):
+//!
+//!     cargo test --release --test gridded_acceptance -- --nocapture
+//!
+//! Must run from the repo root (bundle data paths in
+//! `examples/juniata_gridded/ddrs.yaml` are repo-root-relative). The
+//! workspace goes to a tempdir, so `examples/juniata_gridded/.ddrs/` from
+//! manual runs is untouched.
+
+use std::path::PathBuf;
+
+use ddrs::cli::run::{run, RunInput};
+use ddrs::cli::workspace::Workspace;
+
+/// Routed-metric floors: below the three-seed range (NSE 0.744–0.758 /
+/// KGE 0.728–0.732) by a margin, above the baseline (NSE 0.594 / KGE 0.672).
+const NSE_FLOOR: f64 = 0.70;
+const KGE_FLOOR: f64 = 0.69;
+/// Deterministic summed-Q' NSE (0.594; DDR 0.594).
+const BASELINE_NSE_RANGE: (f64, f64) = (0.57, 0.62);
+
+fn json_f64(v: &serde_json::Value, key: &str) -> f64 {
+    v.get(key)
+        .and_then(|x| x.as_f64())
+        .unwrap_or_else(|| panic!("manifest metrics missing numeric `{key}`: {v}"))
+}
+
+#[test]
+fn gridded_juniata_train_and_test_meets_metric_floors_and_beats_baseline() {
+    if cfg!(debug_assertions) {
+        eprintln!(
+            "skipping: gridded acceptance needs opt-level 3 — \
+             run `cargo test --release --test gridded_acceptance -- --nocapture`"
+        );
+        return;
+    }
+
+    let tmp = tempfile::tempdir().unwrap();
+    let run_dir = run(RunInput {
+        workspace: Workspace::with_root(tmp.path().join(".ddrs")),
+        config_path: PathBuf::from("examples/juniata_gridded/ddrs.yaml"),
+        workflow: None, // config says train-and-test
+        plot: false,
+        strict: false,
+        max_mini_batches: None,
+        batch_order_from: None,
+        backend: "cpu".into(),
+    })
+    .expect("gridded juniata train-and-test run failed");
+
+    let manifest: serde_json::Value = serde_json::from_str(
+        &std::fs::read_to_string(run_dir.join("manifest.json")).expect("read manifest.json"),
+    )
+    .expect("parse manifest.json");
+    let metrics = &manifest["metrics"];
+    assert_eq!(
+        metrics["n_gauges_total"].as_u64(),
+        Some(1),
+        "expected the single Juniata gauge, got: {metrics}"
+    );
+    let nse = json_f64(metrics, "median_nse_finite");
+    let kge = json_f64(metrics, "median_kge_finite");
+
+    let baseline: serde_json::Value = serde_json::from_str(
+        &std::fs::read_to_string(run_dir.join("baseline/manifest.json"))
+            .expect("read baseline/manifest.json"),
+    )
+    .expect("parse baseline/manifest.json");
+    let baseline_nse = baseline["metrics"]["nse"][0]
+        .as_f64()
+        .expect("baseline metrics.nse[0] missing or null");
+
+    eprintln!(
+        "gridded juniata acceptance: routed NSE {nse:.4} / KGE {kge:.4}, baseline NSE {baseline_nse:.4}"
+    );
+
+    assert!(
+        (BASELINE_NSE_RANGE.0..=BASELINE_NSE_RANGE.1).contains(&baseline_nse),
+        "summed-Q' baseline NSE {baseline_nse:.4} outside {BASELINE_NSE_RANGE:?} — \
+         no RNG here, so this is a reader/baseline regression (check the Qr axis \
+         order: DDR's gridded store is (time, divide_id)), not noise"
+    );
+    assert!(nse >= NSE_FLOOR, "routed NSE {nse:.4} < floor {NSE_FLOOR} (seed-42 reference 0.751)");
+    assert!(kge >= KGE_FLOOR, "routed KGE {kge:.4} < floor {KGE_FLOOR} (seed-42 reference 0.730)");
+    assert!(
+        nse > baseline_nse,
+        "routed NSE {nse:.4} does not beat the summed-Q' baseline {baseline_nse:.4}"
+    );
+}
diff --git a/tests/gridded_bundle.rs b/tests/gridded_bundle.rs
new file mode 100644
index 00000000..6996b80d
--- /dev/null
+++ b/tests/gridded_bundle.rs
@@ -0,0 +1,157 @@
+//! Contract test for the committed gridded (ISIMIP DDM30) Juniata bundle
+//! (`examples/juniata_gridded/data/`, byte-identical to DeepGroundwater/ddr
+//! PR #194's `examples/juniata_gridded/data/`).
+//!
+//! Exercises the whole gridded ingestion path through the REAL code:
+//! `GriddedNetwork` reads DDR's sub-reach zarr, the managed build relabels
+//! it into ddrs's subdivided layout and cuts the gauge subgraph, and
+//! `MeritGagesDataset::open` accepts the result. Never skips — the bundle
+//! is committed in-repo.
+
+use ddrs::adjacency::cache::resolve_or_build_gridded;
+use ddrs::adjacency::gridded::GriddedNetwork;
+use ddrs::config::Config;
+use ddrs::data::{
+    AttrStats, ConusAdjacencyStore, GageMetadata, GagesAdjacencyStore, MeritGagesDataset, Staid,
+};
+
+const BUNDLE: &str = "examples/juniata_gridded/data";
+const CONFIG: &str = "examples/juniata_gridded/ddrs.yaml";
+const GAGE: &str = "01567000";
+/// The four DDM30 cells of the Juniata network, upstream first, and the
+/// number of sub-reaches DDR cut each into (`length_m` ≈ 7.1–7.8 km).
+const CELLS: [(i32, usize); 4] = [(139163, 9), (138443, 6), (138444, 6), (138445, 6)];
+/// The gauge's snapped cell (`juniata_gage.csv`'s `cell` column).
+const GAGE_CELL: i64 = 138445;
+
+#[test]
+fn subreach_store_reads_as_27_rows_over_4_cells() {
+    let g = GriddedNetwork::open(format!("{BUNDLE}/juniata_subreach_adjacency.zarr"))
+        .expect("open bundle sub-reach store");
+    assert_eq!(g.n(), 27);
+    assert_eq!(g.n_cells(), 4);
+    assert_eq!(g.rows.len(), 26, "a 27-node tree has 26 edges");
+
+    let sub = g.to_subdivided();
+    let cells: Vec<i32> = CELLS.iter().map(|c| c.0).collect();
+    assert_eq!(sub.parent_order, cells);
+    for (p, &(cell, pieces)) in CELLS.iter().enumerate() {
+        assert_eq!(sub.pieces(p), pieces, "cell {cell} piece count");
+        // Every piece of a cell carries the cell id in `order`.
+        for r in sub.inlet(p)..=sub.outlet(p) {
+            assert_eq!(sub.order[r], cell);
+        }
+    }
+    // DDR's `length_m` is the cell flow length / pieces: all pieces of a cell
+    // are equal, and the cell is ~7 km per piece.
+    for p in 0..4 {
+        let l0 = sub.length_m[sub.inlet(p)];
+        assert!((7000.0..8000.0).contains(&l0), "piece length {l0} m");
+        for r in sub.inlet(p)..=sub.outlet(p) {
+            assert_eq!(sub.length_m[r], l0);
+        }
+    }
+}
+
+#[test]
+fn gauge_csv_cell_column_names_the_outlet_cell() {
+    let meta = GageMetadata::open(format!("{BUNDLE}/juniata_gage.csv")).expect("open gauge csv");
+    assert_eq!(meta.rows.len(), 1);
+    assert_eq!(meta.rows[0].staid, Staid::from(GAGE));
+    assert_eq!(meta.rows[0].comid, Some(GAGE_CELL));
+    // No FLOW_SCALE / COMID_DRAIN_SQKM: the gauge reach's inflow scale stays 1,
+    // matching DDR's train_gridded.py (flow_scale=None).
+    assert!(meta.rows[0].flow_scale.is_none());
+}
+
+/// The managed build into a scratch workspace: the CONUS store round-trips
+/// through `ConusAdjacencyStore` as a subdivided store, and the gauge is read
+/// at cell 138445's most downstream sub-reach (the last row).
+#[test]
+fn managed_build_cuts_the_gauge_at_the_cells_outlet_piece() {
+    let tmp = tempfile::tempdir().unwrap();
+    let out = resolve_or_build_gridded(
+        tmp.path(),
+        std::path::Path::new(&format!("{BUNDLE}/juniata_subreach_adjacency.zarr")),
+        std::path::Path::new(&format!("{BUNDLE}/juniata_gage.csv")),
+    )
+    .expect("gridded managed build");
+    assert!(!out.cache_hit);
+    assert!(out.paths.conus.ends_with("juniata_subreach_adjacency.zarr"));
+    assert!(out.paths.gages.ends_with("juniata_subreach_gages_adjacency.zarr"));
+
+    let conus = ConusAdjacencyStore::open(&out.paths.conus).expect("open built conus store");
+    assert_eq!(conus.n, 27);
+    assert_eq!(conus.nnz, 26);
+    assert_eq!(conus.n_parent(), 4);
+    assert_eq!(conus.parent_offset, vec![0, 9, 15, 21, 27]);
+    let violations = conus
+        .indices_0
+        .iter()
+        .zip(&conus.indices_1)
+        .filter(|(r, c)| r <= c)
+        .count();
+    assert_eq!(violations, 0, "{violations} edges are not strictly lower-triangular");
+
+    let gages = GagesAdjacencyStore::open(&out.paths.gages, &[Staid::from(GAGE)])
+        .expect("open built gages store");
+    let sg = gages.subgraphs.get(&Staid::from(GAGE)).expect("01567000 subgraph present");
+    assert!(!sg.is_headwater());
+    assert_eq!(sg.gage_catchment, GAGE_CELL.to_string());
+    // Outlet piece of the last cell = row 26 (DDR's `outlet_of_cell`).
+    assert_eq!(sg.gage_idx, 26);
+    // Single-gauge bundle: the upstream set is every cell, each once (the
+    // baseline sums a cell's Q' once, not once per piece).
+    let upstream = sg.upstream_comids(&conus);
+    assert_eq!(upstream.len(), 4);
+
+    // Second resolve is a cache hit with the same key.
+    let again = resolve_or_build_gridded(
+        tmp.path(),
+        std::path::Path::new(&format!("{BUNDLE}/juniata_subreach_adjacency.zarr")),
+        std::path::Path::new(&format!("{BUNDLE}/juniata_gage.csv")),
+    )
+    .expect("second resolve");
+    assert!(again.cache_hit);
+    assert_eq!(again.key, out.key);
+}
+
+#[test]
+fn statistics_cover_all_ten_kan_inputs() {
+    let stats = AttrStats::open(format!(
+        "{BUNDLE}/statistics/merit_attribute_statistics_ddm30_conus_attributes.nc.json"
+    ))
+    .expect("open bundle attribute statistics");
+    let cfg = Config::from_yaml_file(CONFIG).expect("load example config");
+    let vars = cfg.kan_head.as_ref().unwrap().input_var_names.clone();
+    assert_eq!(vars.len(), 10);
+    let means = stats.means_f32(&vars);
+    let stds = stats.stds_f32(&vars);
+    for (i, v) in vars.iter().enumerate() {
+        assert!(means[i].is_finite(), "mean for {v} not finite");
+        assert!(stds[i].is_finite() && stds[i] > 0.0, "std for {v} not usable");
+    }
+}
+
+/// End-to-end: the shipped config resolves its adjacency through the gridded
+/// managed build and opens through the full dataset pipeline, exactly as
+/// `ddrs run` would.
+#[test]
+fn example_config_opens_the_dataset() {
+    let mut cfg = Config::from_yaml_file(CONFIG).expect("load example config");
+    let ds = cfg.data_sources.as_mut().unwrap();
+    assert!(ds.gridded_network.is_some());
+    let tmp = tempfile::tempdir().unwrap();
+    let out = resolve_or_build_gridded(
+        tmp.path(),
+        ds.gridded_network.as_ref().unwrap(),
+        &ds.gages,
+    )
+    .expect("gridded managed build");
+    ds.conus_adjacency = Some(out.paths.conus);
+    ds.gages_adjacency = Some(out.paths.gages);
+
+    let dataset = MeritGagesDataset::open(&cfg).expect("open gridded Juniata dataset");
+    assert_eq!(dataset.len(), 1);
+    assert_eq!(dataset.staids(), &[Staid::from(GAGE)]);
+}
diff --git a/tests/hourly_streamflow.rs b/tests/hourly_streamflow.rs
index b4f47fd2..2e50e4a6 100644
--- a/tests/hourly_streamflow.rs
+++ b/tests/hourly_streamflow.rs
@@ -143,6 +143,40 @@ fn streamflow_source_reports_resolution() {
     assert_eq!(hourly.resolution(), Frequency::Hourly);
 }
 
+/// DDR's gridded (DDM30) Q' stores are written `Qr(time, divide_id)`; the
+/// reader must detect the layout and return the same values as the
+/// `(divide_id, time)` contract layout. Before this, the wrong-axis subset
+/// came back as fill values (zarrs does not error on an out-of-range read),
+/// so the summed-Q' baseline on the gridded Juniata bundle summed nothing.
+#[test]
+fn time_major_store_reads_identically_to_divide_major() {
+    let a = StreamflowStore::open(fixture("qr_daily.ic")).expect("open divide-major");
+    let b = StreamflowStore::open(fixture("qr_daily_time_major.ic")).expect("open time-major");
+    assert!(!a.time_major);
+    assert!(b.time_major);
+    assert_eq!(b.resolution, Frequency::Daily);
+    assert_eq!(b.n_time, 10);
+
+    let w = RhoWindow {
+        start_day_idx: 2,
+        rho_days: 4,
+        window_start: d(1981, 1, 3),
+    };
+    // Reversed and partial COMID list, so the divide-axis span is not the
+    // whole array and the scatter order differs from storage order.
+    let comids = [Comid(104), Comid(102), Comid(101)];
+    let qa = a.read_window(&w, &comids).expect("read_window divide-major");
+    let qb = b.read_window(&w, &comids).expect("read_window time-major");
+    assert_eq!(qa, qb);
+    assert_eq!(qb[(0, 0)], 402.0); // divide 104 (j=3), day 2
+    assert_eq!(qb[(71, 2)], 104.0); // divide 101 (j=0), day 4
+
+    let da = a.read_window_daily(d(1981, 1, 2), 5, &COMIDS).expect("daily divide-major");
+    let db = b.read_window_daily(d(1981, 1, 2), 5, &COMIDS).expect("daily time-major");
+    assert_eq!(da, db);
+    assert_eq!(db[(4, 1)], 205.0); // divide 102, day 5
+}
+
 #[test]
 fn daily_fixture_read_window_keeps_repeat24_semantics() {
     // Pins the daily path: values repeat 24x per day with the trailing-day trim.

From 16989ea7f60eaa6125feeb34f9560f5d47f74ab8 Mon Sep 17 00:00:00 2001
From: Tadd Bindas <taddbindas@gmail.com>
Date: Wed, 9 Sep 2026 22:04:57 -0400
Subject: [PATCH 3/6] skills: add ddrs-run (run, track, resume, audit) and fix
 two stale claims
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

New skill `.claude/skills/ddrs-run/`: the runbook for operating ddrs, split
from ddrs-dev (build/code/test) and ddrs-eval-plots (visualize). SKILL.md
carries the judgment calls — a three-step preflight, training recipes,
dataset switching, run tracking, checkpoint resume, and what does not work.
references/commands.md is the flag-by-flag reference for all eight
subcommands, the workspace layout, and exit codes.

Every claim was verified against the binary or the source on 2026-09-09,
which turned up four things the docs had wrong or missing:

- Text-mode `ddrs show` never prints metrics; `--json` is required. The
  ddrs-eval-plots skill recommended `ddrs show <id> | grep -E "nse|kge"`,
  which silently returns nothing on a good run. Corrected there too.
- `<run_dir>/baseline/manifest.json` metrics are per-gauge ARRAYS, not
  reduced medians, so comparing them to the run manifest's
  `median_nse_finite` needs an explicit median. Snippet included and tested
  (gridded Juniata: routed 0.751/0.730 vs baseline 0.594/0.672).
- `src/config.rs` sets `deny_unknown_fields` on TWO structs
  (`DisaggregationSection` and `Subdivision`), not one as ddrs-dev's config
  reference claimed. Corrected there.
- `ddrs sources` resolves groups at `<config dir>/config/sources/`, so
  `--config config/experiments/x.yaml` reports "no groups" and its runs
  never get a data-source segment in the run id.

The stale-binary trap is documented with the misleading error it actually
produces, reproduced here: a pre-gridded `~/.cargo/bin/ddrs` rejects a valid
`gridded_network:` config with "adjacency sources are missing".

ddrs-dev: Route table entry for the new skill; the maintenance note now says
three skills rather than two.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EqnrtmU91yzuVpGnADnXLP
---
 .claude/skills/ddrs-dev/SKILL.md              |   5 +-
 .claude/skills/ddrs-dev/references/config.md  |   4 +-
 .claude/skills/ddrs-eval-plots/SKILL.md       |   5 +-
 .claude/skills/ddrs-run/SKILL.md              | 209 ++++++++++++++++++
 .../skills/ddrs-run/references/commands.md    | 178 +++++++++++++++
 5 files changed, 398 insertions(+), 3 deletions(-)
 create mode 100644 .claude/skills/ddrs-run/SKILL.md
 create mode 100644 .claude/skills/ddrs-run/references/commands.md

diff --git a/.claude/skills/ddrs-dev/SKILL.md b/.claude/skills/ddrs-dev/SKILL.md
index 7f4f370c..8c952084 100644
--- a/.claude/skills/ddrs-dev/SKILL.md
+++ b/.claude/skills/ddrs-dev/SKILL.md
@@ -27,6 +27,7 @@ config reference, test-authoring patterns, and the current research status.
 | Diagnose a failed, hung, or wrong-result run | `references/traps.md` §Symptom → trap |
 | Check whether a question is already settled | `references/research-status.md` |
 | Build or change the training gauge CSV / population | `references/gauge-population.md` |
+| Launch / watch / resume / audit a training run, or use any `ddrs` subcommand | skill `ddrs-run` |
 | Plot or interpret eval output | skill `ddrs-eval-plots` |
 
 ## Contents
@@ -224,7 +225,9 @@ reader now sniffs the axis order (traps.md T11).
 
 ## Maintenance
 
-This skill and `ddrs-eval-plots` are the only two skills in this repo. When a run,
+Three skills live in this repo: this one (build / code / configure / test / debug),
+`ddrs-run` (launch, watch, resume, and audit runs; the full `ddrs` command
+reference), and `ddrs-eval-plots` (visualize and interpret run output). When a run,
 eval, or export completes, update the relevant section here in the same session that
 produced the knowledge — do not leave it only in a findings doc. If a rule here is
 superseded, correct it in place with the new nuance rather than deleting it.
diff --git a/.claude/skills/ddrs-dev/references/config.md b/.claude/skills/ddrs-dev/references/config.md
index 38de5710..b428d39a 100644
--- a/.claude/skills/ddrs-dev/references/config.md
+++ b/.claude/skills/ddrs-dev/references/config.md
@@ -4,7 +4,9 @@ Struct: `src/config.rs::Config`. Loaded via
 `Config::from_yaml_file_with_mode(path, ConfigMode::Training|Testing)`.
 Six top-level sections. Verified against source 2026-07-30.
 
-**No `deny_unknown_fields` except `DisaggregationSection`** (added 2026-08-03) —
+**No `deny_unknown_fields` except `DisaggregationSection`** (added 2026-08-03)
+**and `Subdivision`** (`params.subdivision`; corrected 2026-09-09 — `src/config.rs`
+carries exactly these two) —
 everywhere else a typo'd key silently takes its default instead of erroring. This
 is the single most common cause of "my config change did nothing".
 
diff --git a/.claude/skills/ddrs-eval-plots/SKILL.md b/.claude/skills/ddrs-eval-plots/SKILL.md
index 0a675040..3880f680 100644
--- a/.claude/skills/ddrs-eval-plots/SKILL.md
+++ b/.claude/skills/ddrs-eval-plots/SKILL.md
@@ -197,7 +197,10 @@ L1, run `2026-06-23T02-49-12Z-conus-hourly-train-and-test`) — that is +0.037 N
 −0.007 KGE against the baseline. Full table and the 2026-07-30 KGE qualification:
 `ddrs-dev` → `references/research-status.md`.
 
-`ddrs show <id> | grep -E "nse|kge|loss"` is the cheap pre-plot triage.
+`ddrs show <id> --json | grep -E "nse|kge"` is the cheap pre-plot triage. **The
+`--json` is required** (corrected 2026-09-09): text-mode `ddrs show` prints status,
+workflow, git SHA, drift and adjacency only, never metrics, so the same grep without
+it silently returns nothing on a perfectly good run. See skill `ddrs-run`.
 
 ### Have the parameters converged?
 
diff --git a/.claude/skills/ddrs-run/SKILL.md b/.claude/skills/ddrs-run/SKILL.md
new file mode 100644
index 00000000..4086da35
--- /dev/null
+++ b/.claude/skills/ddrs-run/SKILL.md
@@ -0,0 +1,209 @@
+---
+name: ddrs-run
+description: Use when launching, watching, resuming, or auditing a ddrs training or evaluation job: starting a train / train-and-test run, switching datasets between MERIT and gridded DDM30, finding a past run's metrics or git SHA, resuming after a crash, pruning old runs, or when a run used the wrong code or the wrong data. Trigger on "train a model", "run ddrs", "which run was that", "resume from epoch N", "did it beat the baseline", "ddrs status/show/gc/sources", "my config change did nothing".
+---
+
+# Running and tracking ddrs models
+
+The `ddrs` binary is a terraform-style lifecycle: **`plan`** prepares and validates,
+**`run`** executes a workflow into `.ddrs/runs/<id>/`, **`show`/`status`** audit what
+happened, **`gc`** prunes. Every run writes a self-describing manifest (config
+snapshot, input fingerprints, git SHA), so a finished run can be reproduced without
+guessing what produced it.
+
+This skill is the runbook. For building/testing ddrs itself use `ddrs-dev`; for
+plotting a finished run use `ddrs-eval-plots`.
+
+## Preflight: do these three before EVERY run
+
+Skipping any one of them produces a run that looks fine and is wrong.
+
+**1. Refresh the binary if `src/` changed since the last install.**
+
+```bash
+cargo install --path .          # canonical; updates ~/.cargo/bin/ddrs
+```
+
+`cargo build` does **not** update the `ddrs` on your PATH. A stale binary does not
+say it is stale. It fails as if your *config* were wrong. Reproduced 2026-09-09:
+a pre-gridded `~/.cargo/bin/ddrs` given a valid `gridded_network:` config answered
+
+```
+error: config invalid: data_sources: adjacency sources are missing —
+either set both `conus_adjacency` and `gages_adjacency`, or set `geospatial_fabric`
+```
+
+The key was right there in the file. Alternatives to `cargo install`: run
+`cargo run --release --bin ddrs -- <args>`, or use an **absolute** path to
+`target/release/ddrs` (a relative one resolves to the main tree from a worktree).
+
+**2. Pass `--workspace` whenever you pass `--config`.**
+
+The workspace defaults to `.ddrs/` *beside the config*, so
+`--config config/experiments/x.yaml` silently creates
+`config/experiments/.ddrs/`, a fresh workspace with no run history and a cold
+adjacency/baseline cache. Always:
+
+```bash
+ddrs --config config/experiments/x.yaml --workspace /path/to/repo/.ddrs plan
+```
+
+The one sanctioned exception is `examples/juniata*/ddrs.yaml`, whose workspace is
+meant to land beside it.
+
+**3. `plan` before `run`, and read the baseline it prints.**
+
+`run` re-plans internally, but running `plan` first is where you see the summed-Q'
+baseline, source drift, and the resolved adjacency cache **before** burning hours.
+If the trained median NSE does not beat that baseline number, the routing is not
+earning its keep.
+
+## Launch a training run
+
+```bash
+# from the repo root, with ./ddrs.yaml as the config
+ddrs plan                                        # validate + baseline (cached)
+ddrs run --workflow train-and-test               # train, eval, compare vs baseline
+ddrs run --workflow train                        # train only, no eval
+ddrs run --workflow train --max-mini-batches 2   # mechanics smoke, minutes not hours
+ddrs run --workflow train-and-test --backend cpu # CPU (diagnostics; slower)
+```
+
+Always smoke-test a new config with `--max-mini-batches 2` first. It exercises the
+whole data → forward → backward → checkpoint path in minutes.
+
+`--workflow` must agree with the config's `mode:` (`training` ↔ `train` /
+`train-and-test`, `testing` ↔ `eval`); `plan` rejects a contradiction at load.
+
+## Switch datasets without editing YAML
+
+Data-source groups are named save files under `config/sources/`. Switching is one
+command and re-locks the workspace:
+
+```bash
+ddrs sources list                 # '*' marks the group matching the current config
+ddrs sources use conus-gridded    # gridded ISIMIP DDM30 network
+ddrs sources use conus            # MERIT CONUS
+ddrs sources save my-group        # snapshot the current data_sources block
+```
+
+**`ddrs sources` resolves groups at `<config dir>/config/sources/`.** Run it from
+the repo root against `./ddrs.yaml`. Pointing `--config` at
+`config/experiments/foo.yaml` makes it look in `config/experiments/config/sources/`
+and report *"no groups"*. The groups are fine, the lookup was wrong.
+
+Switching is textual: the whole `data_sources:` block is replaced, so keys that
+belong to only one network (`gridded_network`, `geospatial_fabric`, `aorc_precip`)
+appear and disappear correctly. Everything outside the block is untouched, so
+`geodataset:` and `params.subdivision` do **not** follow the switch. Check them by
+hand when moving between MERIT and gridded.
+
+## Track a run
+
+**While it runs**, every run tees a timestamped log:
+
+`run` prints `run output → <run_dir>` to **stderr as it starts**, before training
+begins, so take the path from there rather than guessing. If you already lost it:
+
+```bash
+tail -f "$(ls -dt .ddrs/runs/*/ | head -1)run.log"
+```
+
+It captures stdout+stderr at fd level (`dup2`), so CUDA driver messages and any
+child process land there too, and it is opened `O_APPEND` and flushed per line, so
+the log survives a crash. That makes `run.log` the first thing to read after a run
+dies. Per-epoch lines carry loss and median `n`; a flat loss across epochs is a real
+signal, not noise (see `ddrs-dev` traps).
+
+**Afterwards:**
+
+```bash
+ddrs status                    # workspace summary: last run, lock state, disk usage
+ddrs show <run-id>             # status, workflow, git SHA, adjacency, drift
+ddrs show <run-id> --json      # the FULL manifest, including metrics
+```
+
+**Text-mode `ddrs show` never prints metrics. `--json` is required for them.**
+Verified 2026-09-09 on a finished train-and-test run: the human view has zero
+NSE/KGE lines, so `ddrs show <id> | grep nse` returns nothing on a perfectly good
+run and reads like a failed one.
+
+`.ddrs/runs/<id>/` holds `manifest.json`, `config.yaml` (the exact config that ran),
+`run.log`, `checkpoints/`, and `Cargo.lock`. The manifest is the audit record:
+`git` (sha, **dirty**, branch), `sources` (blake3 fingerprint per input file),
+`source_lock.drift`, `resolved_adjacency`, and `metrics`.
+
+**`metrics` differs by workflow.** A `train` run reports only
+`epochs_completed`, `final_mini_batch`, `phase1_seconds`. There are no NSE/KGE
+numbers, because nothing was evaluated. Skill numbers
+(`median_nse_finite`, `median_kge_finite`, `n_gauges_total`, `phase2_seconds`) come
+from `train-and-test`. Comparing a `train` run's metrics to a baseline is a category
+error; re-run as `train-and-test`.
+
+**Comparing against the baseline takes one extra step.** `train-and-test` copies the
+baseline to `<run_dir>/baseline/manifest.json`, but its `metrics` are **per-gauge
+arrays** (`nse`, `kge`, `rmse`, `bias`, `fhv`, `flv`, one entry per gauge in
+`gage_ids` order), not pre-reduced medians. The run manifest's
+`median_nse_finite` is already a median, so take the median of the baseline array
+yourself or you will compare a median against a 620-element list:
+
+```bash
+RUN=$(ls -t .ddrs/runs | head -1)
+ddrs show "$RUN" --json | python3 -c 'import json,sys; m=json.load(sys.stdin)["metrics"]; print("routed  NSE", m["median_nse_finite"], "KGE", m["median_kge_finite"])'
+python3 -c 'import json,statistics as s; m=json.load(open(".ddrs/runs/'"$RUN"'/baseline/manifest.json"))["metrics"]; print("baseline NSE", s.median(m["nse"]), "KGE", s.median(m["kge"]))'
+```
+
+`git.dirty: true` means the working tree had uncommitted edits, so the SHA alone
+does not reproduce that run.
+
+## Resume after a crash
+
+A checkpoint is a **directory** `.ddrs/runs/<id>/checkpoints/epoch_E_mb_M/` holding
+`head.mpk`, `optim.mpk`, `state.json` (epoch, next mini-batch, RNG, sampler
+permutation). To resume, set in the config:
+
+```yaml
+experiment:
+  checkpoint: .ddrs/runs/<id>/checkpoints/epoch_6_mb_0
+  epochs: 20        # MUST exceed the checkpoint's epoch or zero batches train
+```
+
+Resume restores all three files, so the run draws the same gauge batches and
+windows the original would have. Weights are stored f16, so a resumed trajectory
+drifts slowly from an uninterrupted one. That is expected, not a bug.
+
+Flat `epoch_E_mb_M.mpk` **files** instead of directories mean a stale pre-resume
+binary wrote them. Go back to preflight step 1.
+
+## Prune
+
+```bash
+ddrs gc --keep 5 --keep-successful --dry-run   # always dry-run first
+ddrs gc --keep 5 --keep-successful
+ddrs gc --older-than 30d
+```
+
+`gc` prunes only `.ddrs/runs/`. Adjacency and baseline caches are kept, because they are
+content-addressed and expensive to rebuild.
+
+## What does not work
+
+| You might try | Reality |
+|---|---|
+| `ddrs run --workflow eval` | Fails: *"standalone --workflow eval needs a --from-run <run-id> flag"*, and `--from-run` is unimplemented. Use `train-and-test`, or the legacy `eval` binary against a checkpoint. |
+| `ddrs init` | Removed. Prints *"ddrs init has been merged into ddrs plan"*. Use `ddrs plan`. |
+| `ddrs experiment <name>` | **Not on master.** The subcommand and `src/experiment/` live on the `experiment-adjoint` branch. On master it exits with *"unrecognized subcommand"*. |
+| `ddrs run --epochs 10` | No such flag. `experiment.epochs` is YAML-only; edit the config. |
+| `ddrs run --checkpoint <dir>` | No such flag. Resume goes through `experiment.checkpoint:` in the config. |
+| A typo'd config key | Silently takes its default almost everywhere. Only `kan_head.disaggregation` and `params.subdivision` set `deny_unknown_fields` (verified 2026-09-09). This is the most common cause of "my config change did nothing". |
+
+## Red flags: stop and re-check preflight
+
+- You edited `src/` and then typed `ddrs …` without `cargo install --path .`
+- You passed `--config` without `--workspace`
+- A config error names a key you did not set, or denies a key you did set
+- `ddrs sources list` reports "no groups"
+- Checkpoints are flat `.mpk` files rather than directories
+- You are comparing a `train` run's metrics against a baseline
+
+Full flag-by-flag reference: `references/commands.md`.
diff --git a/.claude/skills/ddrs-run/references/commands.md b/.claude/skills/ddrs-run/references/commands.md
new file mode 100644
index 00000000..4c983347
--- /dev/null
+++ b/.claude/skills/ddrs-run/references/commands.md
@@ -0,0 +1,178 @@
+# `ddrs` command reference
+
+Every subcommand and flag, captured from `ddrs --help` on master, 2026-09-09.
+Global flags `--config` and `--workspace` are accepted by **every** subcommand.
+
+## Global
+
+| Flag | Default | Notes |
+|---|---|---|
+| `--config <PATH>` | discover `ddrs.yaml` upward from cwd, stopping at the first `.git` ancestor | |
+| `--workspace <DIR>` | `.ddrs/` **beside the config** | Pass it explicitly whenever you pass `--config` |
+
+Config discovery walking up to `.git` means a bare `ddrs plan` from a subdirectory
+finds the repo-root `ddrs.yaml`. It does **not** search sibling directories.
+
+## `ddrs plan`
+
+Prepare + preview. Idempotent, but **not side-effect free**: on first run it opens
+the forcing store to compute the summed-Q' baseline and builds the managed adjacency
+caches. Subsequent plans on the same inputs are cache hits and instant.
+
+| Flag | Notes |
+|---|---|
+| `--workflow <train\|eval\|train-and-test>` | Override the config's `workflow:` for this invocation |
+| `--json` | Plan result as JSON |
+| `--force` | Re-run the GPU smoke test even if a cached verdict exists |
+| `--min-free-gpu-gb <N>` | Warn below this free GPU memory at probe time (default 8) |
+
+What it does, in order: workspace skeleton + GPU probe + cached smoke test →
+locate/bootstrap `ddrs.yaml` → load and validate the config → fingerprint data
+sources and diff against `.ddrs/sources.lock` → resolve adjacency (explicit paths,
+or a managed build from `geospatial_fabric` / `gridded_network`) → summed-Q'
+baseline.
+
+Lock semantics: `plan` reports drift, then **refreshes** the lock ("sources as of my
+last plan"). Use `run --strict` to abort on drift *before* relocking, preserving the
+evidence.
+
+If `ddrs.yaml` is missing, `plan` bootstraps one interactively, offering the last
+successful run's `config.yaml` snapshot or the bundled template. **Non-TTY callers
+must pass `--config`**, otherwise it errors with
+*"no ddrs.yaml found; pass --config or run interactively"*.
+
+## `ddrs run`
+
+Executes a workflow: re-plans internally, then trains and/or evaluates into
+`.ddrs/runs/<id>/`.
+
+| Flag | Notes |
+|---|---|
+| `--workflow <train\|eval\|train-and-test>` | Overrides the config's `workflow:` |
+| `--plot` | After success, dump per-COMID KAN parameters to `plot/kan_parameters.nc` |
+| `--strict` | Exit 4 if sources drifted since the last plan, instead of warning + relocking |
+| `--max-mini-batches <N>` | Stop each epoch after N mini-batches (smoke testing) |
+| `--batch-order-from <PATH>` | Replay a captured mini-batch order from JSON; overrides the per-epoch shuffle. Schema: `[{"epoch": int, "mb": int, "staids": [str, …]}]` |
+| `--backend <cuda\|cpu>` | **Default `cuda`.** `cpu` is NdArray, deterministic, and forces `sparse_solver` to cpu |
+| `--json` | Run result as JSON |
+
+Diagnostics belong on `--backend cpu`: it is deterministic, and the default is
+CUDA, so a diagnostic run that omits the flag is not the run you think you made.
+Never mix backends within one comparison set.
+
+Run id format: `<UTC timestamp>-[<group>-]<workflow>`, where the optional group
+segment is the active data-source group when the config's `data_sources` block
+matches a saved `config/sources/<name>.yaml` (compared structurally, so comments
+and key order do not break the match).
+
+Consequence of the group lookup path: a run launched with
+`--config config/experiments/foo.yaml` **never** gets a group segment, because
+`active_group` looks in `config/experiments/config/sources/`, which does not
+exist. Launch from the repo root against `./ddrs.yaml` if you want the dataset
+named in the run id.
+
+## `ddrs show <RUN_ID>`
+
+Prints a past run's manifest. `--json` for the raw record.
+
+Human output: run id, status, workflow, started/finished, `git <sha> (dirty)`,
+drift, and the resolved adjacency store paths + cache key with hit/built.
+
+Manifest keys: `run_id`, `ddrs_version`, `git` {sha, dirty, branch}, `workflow`,
+`config_path`, `started_at`, `finished_at`, `status`, `exit_reason`, `system`,
+`sources` (per input: path, mtime, size, `fp: blake3:…`), `resolved_adjacency`,
+`source_lock` {lockfile, matched, drift}, `outputs` (checkpoint list),
+`metrics`, `max_mini_batches`.
+
+## `ddrs status`
+
+Workspace summary: workspace path, lockfile present/absent, last run id, and disk
+usage of `.ddrs/runs/` and `.ddrs/adjacency/`. `--json` supported. Use it to list
+run ids for `ddrs show`.
+
+## `ddrs gc`
+
+Deletes run directories under `.ddrs/runs/`.
+
+| Flag | Notes |
+|---|---|
+| `--keep <N>` | Keep the N most recent runs |
+| `--keep-successful` | Never delete successful runs |
+| `--older-than <DUR>` | Only delete runs older than e.g. `30d`, `12h` |
+| `--dry-run` | List what would be deleted, delete nothing |
+
+Prints `note: .ddrs/adjacency/ caches are kept (not pruned by gc in v1)`.
+
+## `ddrs sources`
+
+Named data-source groups stored at `<config dir>/config/sources/<name>.yaml`. For
+the standard repo-root `ddrs.yaml` that is `config/sources/`.
+
+| Subcommand | Notes |
+|---|---|
+| `list` | Lists groups; `*` marks the one matching the current config |
+| `use <name>` | Splice the group into the config's `data_sources:` and refresh `sources.lock` |
+| `save <name>` | Snapshot the current `data_sources` block as a group (`--force` to overwrite) |
+
+`save`/`use` are textual: comments inside the block travel with the group,
+everything outside it is untouched, and `use` validates that the spliced config
+parses before committing.
+
+Groups shipped in-repo: `conus`, `conus-gridded`, `conus-hourly`,
+`conus-experimental`, `conus-hydrodl2`, `global`, `daily-lstm`, `hourly-lstm`,
+`aorc_dhbv_distributed`.
+
+## `ddrs import <STORE>`
+
+Validates a Q' store against the DDR store contract
+(`docs/nh-qprime-store-contract.md`) and registers it as a source group.
+
+| Flag | Notes |
+|---|---|
+| `--name <NAME>` | Group to register under `config/sources/` |
+| `--dry-run` | Validate + report coverage only |
+| `--force` | Overwrite an existing group of that name |
+
+The reader sniffs daily vs hourly-native resolution from the CF time units. Hourly
+stores are sliced natively. An hourly store combined with
+`kan_head.disaggregation` is a config error.
+
+## Workspace layout
+
+| Path | Written by | Holds |
+|---|---|---|
+| `ddrs.yaml` | `plan` (via `$EDITOR`) | Workflow + experiment config (gitignored) |
+| `.ddrs/system.json` | `plan` | GPU/driver/smoke-test record |
+| `.ddrs/sources.lock` | `plan` | Fingerprints of `data_sources` paths |
+| `.ddrs/adjacency/<key>/` | `plan`, first time | Cached adjacency stores, content-addressed |
+| `.ddrs/baselines/<key>/` | `plan`, first time | Cached summed-Q' baseline |
+| `.ddrs/runs/<id>/manifest.json` | `run` | Per-run audit record |
+| `.ddrs/runs/<id>/config.yaml` | `run` | Snapshot of the config that produced the run |
+| `.ddrs/runs/<id>/run.log` | `run` | fd-level timestamped tee of stdout+stderr |
+| `.ddrs/runs/<id>/Cargo.lock` | `run` | Dependency snapshot |
+| `.ddrs/runs/<id>/checkpoints/epoch_E_mb_M/` | `run`, train phase | `head.mpk`, `optim.mpk`, `state.json` |
+| `.ddrs/runs/<id>/baseline/` | `run`, train-and-test | `manifest.json` + raw `predictions.f32` / `observations.f32` |
+| `.ddrs/runs/<id>/eval/predictions.zarr` | `run`, eval phase | Routed predictions over the eval window |
+
+## Exit codes
+
+`src/cli/types.rs`: 0 Success · 1 Generic · 2 ConfigInvalid · 3 DataSourceMissing ·
+4 LockDrift · 5 RuntimeFailure · 6 WorkspaceNotInitialized.
+
+## Legacy binaries (deprecated, removed in 0.4)
+
+`train`, `eval`, `train_and_test` still build and each prints a deprecation warning
+pointing at the `ddrs run` equivalent. The legacy `eval` binary remains the only way
+to evaluate an existing checkpoint without retraining, since
+`ddrs run --workflow eval` is unimplemented:
+
+```bash
+cargo build --release --bin eval
+target/release/eval --config <cfg> \
+  --checkpoint .ddrs/runs/<id>/checkpoints/epoch_E_mb_M \
+  --output /tmp/out.zarr
+```
+
+`--checkpoint` means different things per binary: `eval` and `probe_zeta_gradient`
+take the **directory**; `dump_parameters` takes the **head base**
+(`epoch_E_mb_M/head`, no `.mpk`).

From a90d1dbcb97ef33ba90ebf8c1cf04527015a192f Mon Sep 17 00:00:00 2001
From: Tadd Bindas <taddbindas@gmail.com>
Date: Wed, 9 Sep 2026 22:15:21 -0400
Subject: [PATCH 4/6] skills: close five gaps in ddrs-run found by a with-skill
 verification run

A subagent given only the skill produced a correct runbook but had to leave it
to read source for five things. All now verified and documented:

- The committed starting configs (config/merit_training.yaml,
  config/experiments/gridded_conus.yaml, the two examples/) were never named,
  so the only route to a gridded config looked like hand-building one.
- `ddrs plan`'s bootstrap offers exactly two options and its "clean template"
  is hardcoded to config/merit_training.yaml (plan_bootstrap.rs), so
  bootstrapping while expecting gridded silently yields MERIT.
- `geodataset:` is validated by nothing. It is a provenance label written into
  zarr attrs and the run's config snapshot, so a stale value after
  `sources use` produces a successful run with a mislabelled audit trail.
- A resume mints a NEW run id: run_id is built from the invocation's own start
  timestamp (run.rs), so the interrupted run's manifest, log and checkpoints
  freeze at the crash and one training curve spans two run dirs.
- `run` never re-prints the baseline table that `plan` shows.

Also notes that `cargo install` rewrites the machine-global ~/.cargo/bin/ddrs
shared across worktrees, so with several branches in play an absolute
target/release/ddrs is the safer invocation.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EqnrtmU91yzuVpGnADnXLP
---
 .claude/skills/ddrs-run/SKILL.md | 48 ++++++++++++++++++++++++++++++--
 1 file changed, 45 insertions(+), 3 deletions(-)

diff --git a/.claude/skills/ddrs-run/SKILL.md b/.claude/skills/ddrs-run/SKILL.md
index 4086da35..e1f68e14 100644
--- a/.claude/skills/ddrs-run/SKILL.md
+++ b/.claude/skills/ddrs-run/SKILL.md
@@ -37,6 +37,12 @@ The key was right there in the file. Alternatives to `cargo install`: run
 `cargo run --release --bin ddrs -- <args>`, or use an **absolute** path to
 `target/release/ddrs` (a relative one resolves to the main tree from a worktree).
 
+`cargo install` writes the machine-global `~/.cargo/bin/ddrs`, shared by every
+checkout and worktree on the box. Installing from a worktree silently changes what
+plain `ddrs` means everywhere until someone installs from a different checkout. When
+several branches are in play, prefer the absolute `target/release/ddrs` of the tree
+you mean.
+
 **2. Pass `--workspace` whenever you pass `--config`.**
 
 The workspace defaults to `.ddrs/` *beside the config*, so
@@ -58,6 +64,28 @@ baseline, source drift, and the resolved adjacency cache **before** burning hour
 If the trained median NSE does not beat that baseline number, the routing is not
 earning its keep.
 
+## Start from a ready-made config, not from scratch
+
+`ddrs.yaml` is gitignored and per-workspace; the committed configs are the
+starting points. Copy one in rather than hand-building a config:
+
+| Want | Copy |
+|---|---|
+| MERIT CONUS | `config/merit_training.yaml` |
+| Gridded ISIMIP DDM30 CONUS | `config/experiments/gridded_conus.yaml` |
+| Single-basin MERIT sample | `examples/juniata/ddrs.yaml` (run in place) |
+| Single-basin gridded sample | `examples/juniata_gridded/ddrs.yaml` (run in place) |
+
+```bash
+cp config/experiments/gridded_conus.yaml ddrs.yaml   # gitignored; safe to overwrite
+```
+
+**`ddrs plan`'s interactive bootstrap does not offer these.** With no `ddrs.yaml`
+present it offers exactly two choices: the last successful run's config snapshot,
+or the clean template, and the clean template is hardcoded to
+`config/merit_training.yaml` (`src/cli/plan_bootstrap.rs`). Bootstrapping and then
+expecting a gridded config gets you a MERIT one. Copy the file you want first.
+
 ## Launch a training run
 
 ```bash
@@ -95,8 +123,14 @@ and report *"no groups"*. The groups are fine, the lookup was wrong.
 Switching is textual: the whole `data_sources:` block is replaced, so keys that
 belong to only one network (`gridded_network`, `geospatial_fabric`, `aorc_precip`)
 appear and disappear correctly. Everything outside the block is untouched, so
-`geodataset:` and `params.subdivision` do **not** follow the switch. Check them by
-hand when moving between MERIT and gridded.
+`geodataset:` and `params.subdivision` do **not** follow the switch.
+
+Fix `geodataset:` by hand after switching. **Nothing validates it**: no code path
+compares it against the adjacency keys, so a mismatch does not error. It is a
+provenance label, written into managed-build zarr attrs and copied into the run's
+`config.yaml` snapshot. Leaving `geodataset: ddm30` on a MERIT run produces a
+successful run whose audit trail names the wrong network, which is worse than a
+rejected config because nothing tells you.
 
 ## Track a run
 
@@ -145,7 +179,8 @@ baseline to `<run_dir>/baseline/manifest.json`, but its `metrics` are **per-gaug
 arrays** (`nse`, `kge`, `rmse`, `bias`, `fhv`, `flv`, one entry per gauge in
 `gage_ids` order), not pre-reduced medians. The run manifest's
 `median_nse_finite` is already a median, so take the median of the baseline array
-yourself or you will compare a median against a 620-element list:
+yourself or you will compare a median against a 620-element list. `run` also never
+re-prints the baseline table that `plan` shows, so read it from the file:
 
 ```bash
 RUN=$(ls -t .ddrs/runs | head -1)
@@ -172,6 +207,13 @@ Resume restores all three files, so the run draws the same gauge batches and
 windows the original would have. Weights are stored f16, so a resumed trajectory
 drifts slowly from an uninterrupted one. That is expected, not a bug.
 
+**A resume produces a NEW run id; it does not continue the old directory.** The run
+id is built from the invocation's own start timestamp, so every `ddrs run` mints a
+fresh `.ddrs/runs/<id>/`. The interrupted run's manifest, log, and checkpoints stay
+frozen at the crash, and the resumed run starts an empty log of its own. Expect two
+run ids for one training curve, and keep both: the first holds the epochs the second
+does not.
+
 Flat `epoch_E_mb_M.mpk` **files** instead of directories mean a stale pre-resume
 binary wrote them. Go back to preflight step 1.
 

From 8fa4df906317cb1088a394c6acc77b002d460dec Mon Sep 17 00:00:00 2001
From: Tadd Bindas <taddbindas@gmail.com>
Date: Thu, 10 Sep 2026 02:08:29 -0400
Subject: [PATCH 5/6] config, show: fix three silent-failure bugs found while
 writing the run skill

All three were defects the docs had merely described. Fixed in code, and the
docs that described them updated to match.

1. `ddrs show` printed no metrics in text mode. The numbers were only in
   --json, so `ddrs show <id> | grep nse` came back empty on a healthy
   train-and-test run and read like a failure (ddrs-eval-plots recommended
   exactly that grep). Text mode now prints the metrics block, and for a
   train-and-test run reduces <run_dir>/baseline/manifest.json, whose
   metrics are per-gauge ARRAYS rather than medians, to a median per metric
   shown beside the routed value and the delta, flagging the case where
   routed does not beat baseline. That comparison previously required
   hand-parsing two JSON files and knowing to take the median.

2. `geodataset:` was validated by nothing. It is provenance only (zarr attrs
   plus the run's config.yaml snapshot), which is what made a wrong value
   dangerous: the run succeeds and its audit trail names the wrong network.
   `ddrs sources use` swaps only the data_sources block, so switching
   MERIT to gridded or back left a stale label behind. An absent value is
   now INFERRED from the adjacency source, and a contradicting one is a load
   error. Explicit conus_adjacency/gages_adjacency stay unconstrained: a
   pre-built store can be either network, so the label is undecidable.

3. A typo'd config key silently took its default, the documented single most
   common cause of "my config change did nothing". All seven remaining
   config structs now set deny_unknown_fields (ConfigRaw, DataSources,
   Experiment, KanHeadConfigSection, LossConfig, ParamsRaw,
   TestingOverridesRaw; DisaggregationSection and Subdivision already had
   it), so a misspelling is a load error naming the key.

Tests: typo rejection in each of the five config sections, the mlp: alias
still parsing, geodataset inference/contradiction/undecidable, and
median_finite plus render_scalar units. The shared config test helper no
longer stamps `geodataset: merit`, which would contradict any gridded block.

Gates: cargo test 630 passed / 0 failed (101 binaries), compare_ddr_sandbox
ABSOLUTE MATCH, juniata_acceptance 0.7903/0.8810 and gridded_acceptance
0.7511/0.7299, both identical to pre-fix, so the routing path is untouched.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EqnrtmU91yzuVpGnADnXLP
---
 .claude/skills/ddrs-dev/references/config.md |  13 +-
 .claude/skills/ddrs-eval-plots/SKILL.md      |   9 +-
 .claude/skills/ddrs-run/SKILL.md             |  60 +++---
 src/cli/show.rs                              | 122 ++++++++++-
 src/config.rs                                | 213 ++++++++++++++++++-
 5 files changed, 379 insertions(+), 38 deletions(-)

diff --git a/.claude/skills/ddrs-dev/references/config.md b/.claude/skills/ddrs-dev/references/config.md
index b428d39a..5f0db599 100644
--- a/.claude/skills/ddrs-dev/references/config.md
+++ b/.claude/skills/ddrs-dev/references/config.md
@@ -4,11 +4,13 @@ Struct: `src/config.rs::Config`. Loaded via
 `Config::from_yaml_file_with_mode(path, ConfigMode::Training|Testing)`.
 Six top-level sections. Verified against source 2026-07-30.
 
-**No `deny_unknown_fields` except `DisaggregationSection`** (added 2026-08-03)
-**and `Subdivision`** (`params.subdivision`; corrected 2026-09-09 — `src/config.rs`
-carries exactly these two) —
-everywhere else a typo'd key silently takes its default instead of erroring. This
-is the single most common cause of "my config change did nothing".
+**Every section sets `deny_unknown_fields`** as of 2026-09-09 (`ConfigRaw`,
+`DataSources`, `Experiment`, `KanHeadConfigSection`, `LossConfig`, `ParamsRaw`,
+`TestingOverridesRaw`, plus `DisaggregationSection` and `Subdivision`, which had it
+already), so a typo'd key is a load error naming the key. Historically only the last
+two had it and everywhere else a typo silently took its default, which was the
+single most common cause of "my config change did nothing". On a binary older than
+2026-09-09, that silence is still the first thing to suspect.
 
 ## Contents
 
@@ -186,6 +188,7 @@ Four validators run at `Config::from_yaml_file`, plus one at dataset open.
 | | `gridded_network` + `geospatial_fabric` | `"gridded_network"` + `"geospatial_fabric"` |
 | | `gridded_network` + explicit adjacency pair | `"gridded_network"` + `"conus_adjacency"` |
 | `validate_subdivision` | `subdivision.enabled: true` + `gridded_network` | `"params.subdivision"` + `"gridded_network"` |
+| `validate_geodataset` | `geodataset:` contradicting the adjacency source (`ddm30` with `geospatial_fabric`, `merit` with `gridded_network`) | `"geodataset"` + the source key. Absent ⇒ inferred; explicit adjacency paths ⇒ any label allowed |
 | `validate_leakance` | `use_leakance` + `use_cuda_graphs` | both key names |
 | `validate_ddr_match` | `use_cuda_graphs: true` without the deprecated `ddr_match: true` | `"use_cuda_graphs: true` requires the DEPRECATED `ddr_match: true"` |
 | `validate_disagg_pretrained` | `freeze: true` without `pretrained_checkpoint` | `"freeze: true requires pretrained_checkpoint"` |
diff --git a/.claude/skills/ddrs-eval-plots/SKILL.md b/.claude/skills/ddrs-eval-plots/SKILL.md
index 3880f680..b524d1c2 100644
--- a/.claude/skills/ddrs-eval-plots/SKILL.md
+++ b/.claude/skills/ddrs-eval-plots/SKILL.md
@@ -197,10 +197,11 @@ L1, run `2026-06-23T02-49-12Z-conus-hourly-train-and-test`) — that is +0.037 N
 −0.007 KGE against the baseline. Full table and the 2026-07-30 KGE qualification:
 `ddrs-dev` → `references/research-status.md`.
 
-`ddrs show <id> --json | grep -E "nse|kge"` is the cheap pre-plot triage. **The
-`--json` is required** (corrected 2026-09-09): text-mode `ddrs show` prints status,
-workflow, git SHA, drift and adjacency only, never metrics, so the same grep without
-it silently returns nothing on a perfectly good run. See skill `ddrs-run`.
+`ddrs show <id>` is the cheap pre-plot triage: since 2026-09-09 it prints the
+`metrics` block and, for a `train-and-test` run, the summed-Q' baseline median with
+the routed value and delta beside it, so "did it beat the baseline" is answered
+without opening a notebook. On a binary older than that, text mode printed no
+metrics at all and you need `--json`. See skill `ddrs-run`.
 
 ### Have the parameters converged?
 
diff --git a/.claude/skills/ddrs-run/SKILL.md b/.claude/skills/ddrs-run/SKILL.md
index e1f68e14..f9979138 100644
--- a/.claude/skills/ddrs-run/SKILL.md
+++ b/.claude/skills/ddrs-run/SKILL.md
@@ -125,12 +125,14 @@ belong to only one network (`gridded_network`, `geospatial_fabric`, `aorc_precip
 appear and disappear correctly. Everything outside the block is untouched, so
 `geodataset:` and `params.subdivision` do **not** follow the switch.
 
-Fix `geodataset:` by hand after switching. **Nothing validates it**: no code path
-compares it against the adjacency keys, so a mismatch does not error. It is a
-provenance label, written into managed-build zarr attrs and copied into the run's
-`config.yaml` snapshot. Leaving `geodataset: ddm30` on a MERIT run produces a
-successful run whose audit trail names the wrong network, which is worse than a
-rejected config because nothing tells you.
+Fix `geodataset:` after switching, or just delete the key. It is a provenance label
+(written into managed-build zarr attrs and the run's `config.yaml` snapshot) and
+nothing at runtime reads it, but since 2026-09-09 a value contradicting the
+adjacency source is a **load error**, and an absent one is **inferred** from the
+source. So omitting it is always right, and a stale one now stops the run instead of
+silently mislabelling its audit trail. Only the two managed-build sources are
+decidable; with explicit `conus_adjacency`/`gages_adjacency` any label is accepted,
+because a pre-built store could be either network.
 
 ## Track a run
 
@@ -153,14 +155,26 @@ signal, not noise (see `ddrs-dev` traps).
 
 ```bash
 ddrs status                    # workspace summary: last run, lock state, disk usage
-ddrs show <run-id>             # status, workflow, git SHA, adjacency, drift
-ddrs show <run-id> --json      # the FULL manifest, including metrics
+ddrs show <run-id>             # status, git SHA, adjacency, metrics, baseline delta
+ddrs show <run-id> --json      # the full manifest, machine-readable
 ```
 
-**Text-mode `ddrs show` never prints metrics. `--json` is required for them.**
-Verified 2026-09-09 on a finished train-and-test run: the human view has zero
-NSE/KGE lines, so `ddrs show <id> | grep nse` returns nothing on a perfectly good
-run and reads like a failed one.
+`ddrs show` prints a `metrics` block and, for a `train-and-test` run, the
+summed-Q' baseline reduced to a median per metric with the routed value and the
+delta beside it, flagging the case where routed does not beat baseline:
+
+```
+metrics
+  median_nse_finite      0.7511
+  median_kge_finite      0.7299
+baseline (summed Q', median over gauges)
+  NSE                    0.5943   routed 0.7511   Δ +0.1568
+  KGE                    0.6715   routed 0.7299   Δ +0.0583
+```
+
+(Before 2026-09-09 text mode printed no metrics at all, so `ddrs show <id> | grep
+nse` came back empty on a healthy run. If you are on an older binary and see that,
+it is the binary, not the run.)
 
 `.ddrs/runs/<id>/` holds `manifest.json`, `config.yaml` (the exact config that ran),
 `run.log`, `checkpoints/`, and `Cargo.lock`. The manifest is the audit record:
@@ -174,19 +188,13 @@ numbers, because nothing was evaluated. Skill numbers
 from `train-and-test`. Comparing a `train` run's metrics to a baseline is a category
 error; re-run as `train-and-test`.
 
-**Comparing against the baseline takes one extra step.** `train-and-test` copies the
-baseline to `<run_dir>/baseline/manifest.json`, but its `metrics` are **per-gauge
-arrays** (`nse`, `kge`, `rmse`, `bias`, `fhv`, `flv`, one entry per gauge in
-`gage_ids` order), not pre-reduced medians. The run manifest's
-`median_nse_finite` is already a median, so take the median of the baseline array
-yourself or you will compare a median against a 620-element list. `run` also never
-re-prints the baseline table that `plan` shows, so read it from the file:
-
-```bash
-RUN=$(ls -t .ddrs/runs | head -1)
-ddrs show "$RUN" --json | python3 -c 'import json,sys; m=json.load(sys.stdin)["metrics"]; print("routed  NSE", m["median_nse_finite"], "KGE", m["median_kge_finite"])'
-python3 -c 'import json,statistics as s; m=json.load(open(".ddrs/runs/'"$RUN"'/baseline/manifest.json"))["metrics"]; print("baseline NSE", s.median(m["nse"]), "KGE", s.median(m["kge"]))'
-```
+**If you read the baseline file yourself, reduce it first.** `train-and-test` copies
+the baseline to `<run_dir>/baseline/manifest.json`, and its `metrics` are
+**per-gauge arrays** (`nse`, `kge`, `rmse`, `bias`, `fhv`, `flv`, one entry per
+gauge in `gage_ids` order), not pre-reduced medians. Comparing that raw array to the
+run manifest's `median_nse_finite` compares a scalar against a 620-element list.
+`ddrs show` does the reduction for you; `--json` does not, and `run` never re-prints
+the baseline table that `plan` shows.
 
 `git.dirty: true` means the working tree had uncommitted edits, so the SHA alone
 does not reproduce that run.
@@ -237,7 +245,7 @@ content-addressed and expensive to rebuild.
 | `ddrs experiment <name>` | **Not on master.** The subcommand and `src/experiment/` live on the `experiment-adjoint` branch. On master it exits with *"unrecognized subcommand"*. |
 | `ddrs run --epochs 10` | No such flag. `experiment.epochs` is YAML-only; edit the config. |
 | `ddrs run --checkpoint <dir>` | No such flag. Resume goes through `experiment.checkpoint:` in the config. |
-| A typo'd config key | Silently takes its default almost everywhere. Only `kan_head.disaggregation` and `params.subdivision` set `deny_unknown_fields` (verified 2026-09-09). This is the most common cause of "my config change did nothing". |
+| A typo'd config key | Now a load error naming the key. Every config section sets `deny_unknown_fields` as of 2026-09-09; before that a typo silently took its default, which was the most common cause of "my config change did nothing". On an older binary, that silence is still the first thing to suspect. |
 
 ## Red flags: stop and re-check preflight
 
diff --git a/src/cli/show.rs b/src/cli/show.rs
index 40bf1e79..ed97bcd1 100644
--- a/src/cli/show.rs
+++ b/src/cli/show.rs
@@ -1,8 +1,11 @@
+use std::path::Path;
+
 use crate::cli::{manifest::Manifest, workspace::Workspace};
 use crate::error::CliError;
 
 pub fn run_show(ws: &Workspace, run_id: &str, as_json: bool) -> Result<(), CliError> {
-    let path = ws.runs_dir().join(run_id).join("manifest.json");
+    let run_dir = ws.runs_dir().join(run_id);
+    let path = run_dir.join("manifest.json");
     let m = Manifest::read(&path)?;
     if as_json {
         println!("{}", serde_json::to_string_pretty(&m)
@@ -28,6 +31,123 @@ pub fn run_show(ws: &Workspace, run_id: &str, as_json: bool) -> Result<(), CliEr
             }
         }
         if let Some(p) = &m.outputs.plot { println!("plot     {}", p.display()); }
+        print_metrics(&m.metrics, &run_dir);
     }
     Ok(())
 }
+
+/// Render the manifest's `metrics` map, then the summed-Q' baseline comparison
+/// when the run carries one.
+///
+/// Text mode used to print nothing from `metrics`, so `ddrs show <id> | grep nse`
+/// came back empty on a perfectly good `train-and-test` run and read like a
+/// failure. The numbers were only ever in `--json`.
+fn print_metrics(metrics: &serde_json::Value, run_dir: &Path) {
+    let Some(map) = metrics.as_object() else { return };
+    if map.is_empty() {
+        return;
+    }
+    println!("metrics");
+    // Sorted for a stable, greppable order (serde_json preserves insertion
+    // order only with the preserve_order feature).
+    let mut keys: Vec<&String> = map.keys().collect();
+    keys.sort();
+    for k in keys {
+        println!("  {:<22} {}", k, render_scalar(&map[k]));
+    }
+    print_baseline_comparison(map, run_dir);
+}
+
+fn render_scalar(v: &serde_json::Value) -> String {
+    match v {
+        serde_json::Value::Number(n) => match n.as_f64() {
+            // Integers (epoch counts, gauge counts) shouldn't gain decimals.
+            Some(f) if f.fract() == 0.0 && f.abs() < 1e15 => format!("{}", f as i64),
+            Some(f) => format!("{f:.4}"),
+            None => n.to_string(),
+        },
+        serde_json::Value::String(s) => s.clone(),
+        other => other.to_string(),
+    }
+}
+
+/// `train-and-test` copies the summed-Q' baseline to
+/// `<run_dir>/baseline/manifest.json`, but its metrics are **per-gauge arrays**,
+/// not reduced medians, so a reader comparing them to the run's
+/// `median_nse_finite` was comparing a scalar against a list. Reduce here.
+fn print_baseline_comparison(
+    run_metrics: &serde_json::Map<String, serde_json::Value>,
+    run_dir: &Path,
+) {
+    let text = match std::fs::read_to_string(run_dir.join("baseline/manifest.json")) {
+        Ok(t) => t,
+        Err(_) => return, // train-only run, or baseline copy unavailable
+    };
+    let Ok(b): std::result::Result<serde_json::Value, _> = serde_json::from_str(&text) else {
+        return;
+    };
+    let bm = &b["metrics"];
+    println!("baseline (summed Q', median over gauges)");
+    for (label, key, run_key) in [
+        ("NSE", "nse", "median_nse_finite"),
+        ("KGE", "kge", "median_kge_finite"),
+    ] {
+        let Some(base) = median_finite(&bm[key]) else { continue };
+        match run_metrics.get(run_key).and_then(|v| v.as_f64()) {
+            Some(routed) => println!(
+                "  {:<22} {:.4}   routed {:.4}   Δ {:+.4}{}",
+                label,
+                base,
+                routed,
+                routed - base,
+                if routed > base { "" } else { "  ← routed does NOT beat baseline" },
+            ),
+            None => println!("  {:<22} {:.4}", label, base),
+        }
+    }
+}
+
+/// Median of the finite entries of a JSON array, or `None` if there are none.
+fn median_finite(v: &serde_json::Value) -> Option<f64> {
+    let mut xs: Vec<f64> = v
+        .as_array()?
+        .iter()
+        .filter_map(|x| x.as_f64())
+        .filter(|x| x.is_finite())
+        .collect();
+    if xs.is_empty() {
+        return None;
+    }
+    xs.sort_by(|a, b| a.partial_cmp(b).expect("finite values compare"));
+    let n = xs.len();
+    Some(if n % 2 == 1 {
+        xs[n / 2]
+    } else {
+        (xs[n / 2 - 1] + xs[n / 2]) / 2.0
+    })
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use serde_json::json;
+
+    #[test]
+    fn median_finite_handles_odd_even_and_nonfinite() {
+        assert_eq!(median_finite(&json!([3.0, 1.0, 2.0])), Some(2.0));
+        assert_eq!(median_finite(&json!([1.0, 2.0, 3.0, 4.0])), Some(2.5));
+        // nulls (serde's NaN encoding here) and missing entries are skipped.
+        assert_eq!(median_finite(&json!([1.0, null, 3.0])), Some(2.0));
+        assert_eq!(median_finite(&json!([])), None);
+        assert_eq!(median_finite(&json!([null])), None);
+        assert_eq!(median_finite(&json!("not an array")), None);
+    }
+
+    #[test]
+    fn render_scalar_keeps_counts_integral() {
+        assert_eq!(render_scalar(&json!(30)), "30");
+        assert_eq!(render_scalar(&json!(620.0)), "620");
+        assert_eq!(render_scalar(&json!(0.7510778)), "0.7511");
+        assert_eq!(render_scalar(&json!("ok")), "ok");
+    }
+}
diff --git a/src/config.rs b/src/config.rs
index 5d2fd78c..815028a9 100644
--- a/src/config.rs
+++ b/src/config.rs
@@ -94,6 +94,7 @@ where
 }
 
 #[derive(Debug, Clone, Deserialize)]
+#[serde(deny_unknown_fields)]
 pub struct DataSources {
     #[serde(deserialize_with = "deserialize_one_or_many_paths")]
     pub attributes: Vec<std::path::PathBuf>,
@@ -140,6 +141,7 @@ pub struct DataSources {
 }
 
 #[derive(Debug, Clone, Deserialize)]
+#[serde(deny_unknown_fields)]
 pub struct Experiment {
     pub batch_size: usize,
     pub start_time: String,
@@ -228,6 +230,7 @@ pub enum OptimizerKind {
 /// component weights. See `src/training/loss.rs`.
 #[derive(Debug, Clone, Deserialize)]
 #[serde(default, rename_all = "kebab-case")]
+#[serde(deny_unknown_fields)]
 pub struct LossConfig {
     /// Which objective to optimize.
     pub kind: LossKind,
@@ -299,6 +302,7 @@ pub enum LossKind {
 }
 
 #[derive(Debug, Clone, Deserialize)]
+#[serde(deny_unknown_fields)]
 pub struct KanHeadConfigSection {
     pub hidden_size: usize,
     pub num_hidden_layers: usize,
@@ -687,6 +691,7 @@ impl Default for Params {
 
 #[derive(Debug, Default, Deserialize)]
 #[serde(default)]
+#[serde(deny_unknown_fields)]
 struct ParamsRaw {
     parameter_ranges: HashMap<String, [f32; 2]>,
     attribute_minimums: HashMap<String, f32>,
@@ -823,6 +828,7 @@ pub struct Config {
 /// Fields are all optional so absent keys inherit from `experiment:`.
 #[derive(Debug, Default, Deserialize, Clone)]
 #[serde(default)]
+#[serde(deny_unknown_fields)]
 struct TestingOverridesRaw {
     pub start_time: Option<String>,
     pub end_time: Option<String>,
@@ -849,6 +855,7 @@ where
 /// YAML-shaped intermediate; the public `Config` has nicer types.
 #[derive(Debug, Default, Deserialize)]
 #[serde(default)]
+#[serde(deny_unknown_fields)]
 struct ConfigRaw {
     mode: Option<String>,
     geodataset: Option<String>,
@@ -868,13 +875,25 @@ struct ConfigRaw {
 
 impl From<ConfigRaw> for Config {
     fn from(r: ConfigRaw) -> Self {
+        // Resolved before the struct literal moves `data_sources` out of `r`.
+        let geodataset = r.geodataset.clone().unwrap_or_else(|| {
+            match r.data_sources.as_ref() {
+                Some(ds) if ds.gridded_network.is_some() => "ddm30".to_string(),
+                _ => "merit".to_string(),
+            }
+        });
         Self {
             params: r.params.into(),
             data_sources: r.data_sources,
             experiment: r.experiment,
             kan_head: r.kan_head,
             mode: r.mode.unwrap_or_else(|| "training".to_string()),
-            geodataset: r.geodataset.unwrap_or_else(|| "merit".to_string()),
+            // Absent `geodataset:` is INFERRED from the adjacency source rather
+            // than defaulting blindly to "merit", so a gridded config that
+            // omits the key is labelled `ddm30` instead of being mislabelled.
+            // An explicitly wrong value is then a real disagreement, which
+            // `validate_geodataset` rejects.
+            geodataset,
             seed: r.seed.unwrap_or(42),
             np_seed: r.np_seed.unwrap_or(42),
             workflow: r.workflow,
@@ -925,6 +944,10 @@ impl Config {
             path: path.to_path_buf(),
             source: serde_yaml::Error::custom(msg),
         })?;
+        validate_geodataset(&cfg).map_err(|msg| DataError::Yaml {
+            path: path.to_path_buf(),
+            source: serde_yaml::Error::custom(msg),
+        })?;
         validate_leakance(&cfg).map_err(|msg| DataError::Yaml {
             path: path.to_path_buf(),
             source: serde_yaml::Error::custom(msg),
@@ -1038,6 +1061,49 @@ fn validate_data_sources(cfg: &Config) -> std::result::Result<(), String> {
     }
 }
 
+/// `geodataset:` must agree with the adjacency source it is labelling.
+///
+/// Nothing in the routing path reads `geodataset` — it is provenance, written
+/// into the managed-build zarr attrs and copied into the run's `config.yaml`
+/// snapshot. That is exactly why a wrong value is dangerous: the run succeeds
+/// and its audit trail names the wrong network. `ddrs sources use` replaces the
+/// `data_sources:` block only, so switching MERIT ↔ gridded leaves a stale label
+/// behind unless the user remembers to edit it. This turns that silent
+/// mislabelling into a load-time error.
+///
+/// Only the two managed-build sources are decidable. Explicit
+/// `conus_adjacency`/`gages_adjacency` paths can point at either kind of
+/// pre-built store, so any label is accepted there.
+fn validate_geodataset(cfg: &Config) -> std::result::Result<(), String> {
+    let Some(ds) = cfg.data_sources.as_ref() else {
+        return Ok(());
+    };
+    let label = cfg.geodataset.trim();
+    let expected = if ds.gridded_network.is_some() {
+        "ddm30"
+    } else if ds.geospatial_fabric.is_some() {
+        "merit"
+    } else {
+        return Ok(()); // explicit adjacency paths: undecidable, allow any label
+    };
+    if label.eq_ignore_ascii_case(expected) {
+        return Ok(());
+    }
+    let (source_key, other) = if expected == "ddm30" {
+        ("gridded_network", "merit")
+    } else {
+        ("geospatial_fabric", "ddm30")
+    };
+    Err(format!(
+        "geodataset: `{label}` contradicts `data_sources.{source_key}` — that source \
+         builds a `{expected}` network. Nothing reads `geodataset` at runtime, so this \
+         would not fail the run; it would only mislabel the run's config snapshot and \
+         the adjacency store attrs. Fix: set `geodataset: {expected}` (or omit the key \
+         and it is inferred). If you meant to route the {other} network, change \
+         `data_sources` instead — `ddrs sources use <group>` swaps the block for you."
+    ))
+}
+
 fn validate_leakance(cfg: &Config) -> std::result::Result<(), String> {
     if cfg.params.use_leakance && cfg.params.use_cuda_graphs {
         return Err(
@@ -1567,9 +1633,12 @@ workflow: train
 
     // ── data_sources validation matrix ──────────────────────────────────────
 
+    /// `geodataset:` is deliberately omitted so it is inferred from the block
+    /// under test: stamping `merit` here would contradict any gridded
+    /// `data_sources` and trip `validate_geodataset`.
     fn write_yaml_with_data_sources(name: &str, ds_block: &str) -> std::path::PathBuf {
         let yaml = format!(
-            "mode: training\ngeodataset: merit\nseed: 1\nnp_seed: 1\n{ds_block}"
+            "mode: training\nseed: 1\nnp_seed: 1\n{ds_block}"
         );
         let path = std::env::temp_dir().join(name);
         std::fs::write(&path, yaml).unwrap();
@@ -1651,6 +1720,146 @@ data_sources:
         assert!(ds.conus_adjacency.is_none() && ds.gages_adjacency.is_none());
     }
 
+    /// A misspelled key used to take its default in silence, which the docs
+    /// call the single most common cause of "my config change did nothing".
+    /// Every config section now sets `deny_unknown_fields`, so it is a load
+    /// error naming the key.
+    #[test]
+    fn typod_keys_are_rejected_in_every_section() {
+        let base = |extra: &str| {
+            format!(
+                "mode: training\ngeodataset: merit\nseed: 1\nnp_seed: 1\n\
+                 data_sources:\n  attributes: /dev/null/a.nc\n  \
+                 conus_adjacency: /dev/null/c.zarr\n  gages_adjacency: /dev/null/g.zarr\n  \
+                 streamflow: /dev/null/s.ic\n  observations: /dev/null/o.ic\n  \
+                 gages: /dev/null/g.csv\n{extra}"
+            )
+        };
+        // (label, yaml fragment, the misspelled key that must be named)
+        let cases = [
+            ("top level", "epocs: 5\n", "epocs"),
+            ("experiment", "experiment:\n  epocs: 5\n", "epocs"),
+            ("kan_head", "kan_head:\n  hidden_sizes: 21\n", "hidden_sizes"),
+            ("params", "params:\n  taus: 9\n", "taus"),
+            ("testing", "testing:\n  batchsize: 15\n", "batchsize"),
+        ];
+        for (label, extra, key) in cases {
+            let path = std::env::temp_dir()
+                .join(format!("ddrs_typo_{}.yaml", label.replace(' ', "_")));
+            std::fs::write(&path, base(extra)).unwrap();
+            let err = Config::from_yaml_file(&path)
+                .expect_err(&format!("{label}: typo `{key}` must be rejected"));
+            let msg = format!("{err}");
+            assert!(
+                msg.contains(key),
+                "{label}: error should name the offending key `{key}`, got: {msg}"
+            );
+        }
+    }
+
+    /// The guard must not reject keys that really exist, including the
+    /// `mlp:` backward-compat alias for `kan_head:`.
+    #[test]
+    fn known_keys_and_the_mlp_alias_still_parse() {
+        let yaml = "mode: training\ngeodataset: merit\nseed: 1\nnp_seed: 1\n\
+                    data_sources:\n  attributes: /dev/null/a.nc\n  \
+                    conus_adjacency: /dev/null/c.zarr\n  gages_adjacency: /dev/null/g.zarr\n  \
+                    streamflow: /dev/null/s.ic\n  observations: /dev/null/o.ic\n  \
+                    gages: /dev/null/g.csv\n\
+                    mlp:\n  hidden_size: 21\n  num_hidden_layers: 2\n  grid: 50\n  k: 2\n  \
+                    input_var_names: [meanP]\n  learnable_parameters: [n]\n";
+        let path = std::env::temp_dir().join("ddrs_mlp_alias.yaml");
+        std::fs::write(&path, yaml).unwrap();
+        let cfg = Config::from_yaml_file(&path).expect("mlp alias must still parse");
+        assert_eq!(cfg.kan_head.as_ref().unwrap().hidden_size, 21);
+    }
+
+    #[test]
+    fn absent_geodataset_is_inferred_from_the_adjacency_source() {
+        // Gridded source, no `geodataset:` key → inferred `ddm30`, not the
+        // blind "merit" default that used to mislabel every gridded run.
+        let ds_block = r#"
+data_sources:
+  attributes: /dev/null/attrs.nc
+  gridded_network: /dev/null/ddm30_subreach_adjacency.zarr
+  streamflow: /dev/null/sf.ic
+  observations: /dev/null/obs.ic
+  gages: /dev/null/gages.csv
+"#;
+        let yaml = format!("mode: training\nseed: 1\nnp_seed: 1\n{ds_block}");
+        let path = std::env::temp_dir().join("ddrs_geodataset_infer.yaml");
+        std::fs::write(&path, yaml).unwrap();
+        let cfg = Config::from_yaml_file(&path).expect("infers ddm30");
+        assert_eq!(cfg.geodataset, "ddm30");
+
+        // Fabric source, no key → merit.
+        let ds_block = r#"
+data_sources:
+  attributes: /dev/null/attrs.nc
+  geospatial_fabric: /dev/null/rivers.shp
+  streamflow: /dev/null/sf.ic
+  observations: /dev/null/obs.ic
+  gages: /dev/null/gages.csv
+"#;
+        let yaml = format!("mode: training\nseed: 1\nnp_seed: 1\n{ds_block}");
+        let path = std::env::temp_dir().join("ddrs_geodataset_infer_merit.yaml");
+        std::fs::write(&path, yaml).unwrap();
+        assert_eq!(Config::from_yaml_file(&path).unwrap().geodataset, "merit");
+    }
+
+    #[test]
+    fn geodataset_contradicting_the_source_is_rejected() {
+        // The `ddrs sources use conus` footgun: block swapped to MERIT, stale
+        // `geodataset: ddm30` left behind above it.
+        let yaml = "mode: training\ngeodataset: ddm30\nseed: 1\nnp_seed: 1\n
+data_sources:
+  attributes: /dev/null/attrs.nc
+  geospatial_fabric: /dev/null/rivers.shp
+  streamflow: /dev/null/sf.ic
+  observations: /dev/null/obs.ic
+  gages: /dev/null/gages.csv
+";
+        let path = std::env::temp_dir().join("ddrs_geodataset_stale.yaml");
+        std::fs::write(&path, yaml).unwrap();
+        let msg = format!("{}", Config::from_yaml_file(&path).unwrap_err());
+        assert!(
+            msg.contains("geodataset") && msg.contains("geospatial_fabric"),
+            "expected the mislabel error, got: {msg}"
+        );
+
+        // And the mirror: gridded source labelled merit.
+        let yaml = "mode: training\ngeodataset: merit\nseed: 1\nnp_seed: 1\n
+data_sources:
+  attributes: /dev/null/attrs.nc
+  gridded_network: /dev/null/ddm30.zarr
+  streamflow: /dev/null/sf.ic
+  observations: /dev/null/obs.ic
+  gages: /dev/null/gages.csv
+";
+        let path = std::env::temp_dir().join("ddrs_geodataset_stale2.yaml");
+        std::fs::write(&path, yaml).unwrap();
+        let msg = format!("{}", Config::from_yaml_file(&path).unwrap_err());
+        assert!(msg.contains("ddm30"), "expected the mislabel error, got: {msg}");
+    }
+
+    #[test]
+    fn geodataset_is_unconstrained_with_explicit_adjacency_paths() {
+        // A pre-built store can be either network, so the label is undecidable
+        // and must not be second-guessed.
+        let ds_block = r#"
+data_sources:
+  attributes: /dev/null/attrs.nc
+  conus_adjacency: /dev/null/conus.zarr
+  gages_adjacency: /dev/null/gages.zarr
+  streamflow: /dev/null/sf.ic
+  observations: /dev/null/obs.ic
+  gages: /dev/null/gages.csv
+"#;
+        let path = write_yaml_with_data_sources("ddrs_geodataset_explicit.yaml", ds_block);
+        // write_yaml_with_data_sources stamps `geodataset: merit`.
+        assert!(Config::from_yaml_file(&path).is_ok());
+    }
+
     #[test]
     fn gridded_network_with_fabric_rejected() {
         let ds_block = r#"

From 4082f1a707180d5fdd9e5f4997c15bc088e2846d Mon Sep 17 00:00:00 2001
From: Tadd Bindas <taddbindas@gmail.com>
Date: Thu, 10 Sep 2026 09:28:06 -0400
Subject: [PATCH 6/6] ci: gate the gridded path pre-push and in the acceptance
 job

The gridded (DDM30) tests existed but nothing ran them automatically:
gridded_acceptance self-skips under debug_assertions, so the debug `test`
job never touched it, and the pre-push hook only ran ddr_sandbox_match.

- .githooks/pre-push now runs ddr_sandbox_match + gridded_bundle in one
  cargo invocation, so the build is shared. Both never skip (the sandbox
  fixture and the Juniata gridded bundle are committed), so a broken
  checkout fails locally rather than in CI. Measured 0.43 s warm, which
  keeps the hook cheap enough to leave enabled.
- The release `acceptance` job gains a "Gridded (DDM30) end-to-end
  acceptance" step alongside the Juniata one. It reuses that job's release
  build and the test itself is ~10 s, so the added CI cost is small next to
  the build it shares.

CLAUDE.md and the ddrs-dev testing reference updated to name both jobs and
both hook tests, including why the debug job cannot cover either acceptance
test.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EqnrtmU91yzuVpGnADnXLP
---
 .claude/skills/ddrs-dev/references/testing.md | 11 ++++++++---
 .githooks/pre-push                            |  9 +++++++--
 .github/workflows/ci.yml                      |  5 +++++
 CLAUDE.md                                     |  6 ++++--
 4 files changed, 24 insertions(+), 7 deletions(-)

diff --git a/.claude/skills/ddrs-dev/references/testing.md b/.claude/skills/ddrs-dev/references/testing.md
index 15e865b6..15a21517 100644
--- a/.claude/skills/ddrs-dev/references/testing.md
+++ b/.claude/skills/ddrs-dev/references/testing.md
@@ -88,7 +88,10 @@ Exit 0, no drift warnings.
 required checks must never be skipped): job `test` = debug
 `cargo test --features fixtures --no-fail-fast` (~12–17 min cold; warm is
 shorter); job `acceptance` = release `compare_ddr_sandbox` +
-`juniata_acceptance` (~25 min cold; warm is shorter). The acceptance job
+`juniata_acceptance` + `gridded_acceptance` (~25 min cold; warm is shorter;
+both acceptance tests self-skip under `debug_assertions`, so the debug `test`
+job never runs them — the release job is their only CI coverage). The
+acceptance job
 builds with `CARGO_PROFILE_RELEASE_LTO=false` (env override in the workflow
 only): the thin-LTO link of the test binary was 30 of 40 minutes on the
 2-core runner while the 30 training epochs took ~13 s, so the training is
@@ -103,8 +106,10 @@ local tier gates.
 
 Both jobs install a CUDA toolkit only because compilation requires it
 (build-and-env.md). Local hook: `git config core.hooksPath .githooks`
-enables `.githooks/pre-push` (runs `ddr_sandbox_match`; bypass with
-`git push --no-verify`).
+enables `.githooks/pre-push`, which runs `ddr_sandbox_match` +
+`gridded_bundle` in one cargo invocation (~0.4 s warm; both never skip, so a
+broken checkout fails locally rather than in CI). Bypass with
+`git push --no-verify`.
 
 ## What covers what
 
diff --git a/.githooks/pre-push b/.githooks/pre-push
index ea658bff..1ca888a8 100755
--- a/.githooks/pre-push
+++ b/.githooks/pre-push
@@ -1,7 +1,12 @@
 #!/usr/bin/env bash
-# Fast local gate before any push: the DDR sandbox parity test (invariant 1).
+# Fast local gate before any push:
+#   ddr_sandbox_match  — DDR parity (invariant 1)
+#   gridded_bundle     — gridded (DDM30) ingestion contract against the
+#                        committed examples/juniata_gridded/ bundle
+# Both are debug tests that never skip, so a broken checkout fails here
+# rather than in CI. One cargo invocation, so the build is shared.
 # Enable per-clone:  git config core.hooksPath .githooks
 # Bypass once:       git push --no-verify
 set -euo pipefail
 cd "$(git rev-parse --show-toplevel)"
-cargo test --test ddr_sandbox_match
+cargo test --test ddr_sandbox_match --test gridded_bundle
diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 100e7b6c..0020bab7 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -135,3 +135,8 @@ jobs:
         run: mkdir -p output && cargo run --release --example compare_ddr_sandbox
       - name: Juniata end-to-end acceptance
         run: cargo test --release --test juniata_acceptance -- --nocapture
+      # Same chain on the gridded (ISIMIP DDM30) network: both acceptance
+      # tests self-skip under debug_assertions, so the debug `test` job never
+      # runs them. Shares this job's release build; the test itself is ~10 s.
+      - name: Gridded (DDM30) end-to-end acceptance
+        run: cargo test --release --test gridded_acceptance -- --nocapture
diff --git a/CLAUDE.md b/CLAUDE.md
index 3514ab31..7fc35c62 100644
--- a/CLAUDE.md
+++ b/CLAUDE.md
@@ -87,12 +87,14 @@ cd ~/projects/ddr && uv run python ~/projects/ddrs/scripts/export_ddr_sandbox.py
 
 `.github/workflows/ci.yml` runs on every PR and every master push: job
 `test` (debug `cargo test --features fixtures`) and job `acceptance`
-(release `compare_ddr_sandbox` + `juniata_acceptance`). Branch protection
+(release `compare_ddr_sandbox` + `juniata_acceptance` +
+`gridded_acceptance`). Branch protection
 requires both for PR merges; direct pushes stay possible and are vetted by
 the push-triggered run. CI has no GPU and no real data: green CI does NOT
 cover `--features cuda` tests or the data-dependent suite; run those
 locally per the tier gates. Local pre-push hook (opt-in):
-`git config core.hooksPath .githooks`.
+`git config core.hooksPath .githooks` — runs `ddr_sandbox_match` +
+`gridded_bundle` (both never skip; ~0.4 s warm).
 
 ### `ddrs` CLI (preferred entrypoint)