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ameriflux-surgo-grid-extract

Extract dominant-component soil profile variables for EcoSIM grid or template inputs from gSSURGO, with FAO HWSD v2.0 fallback when gSSURGO data are unavailable or incomplete. Use when deriving soil depth, bulk density, field capacity, wilting point, hydraulic conductivity, texture, rock fraction, pH, CEC, or soil organic carbon; or when converting EcoSIM grid NetCDF files to editable Excel workbooks and back.

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含まれるファイル(3)

  • SKILL.md10.3 KB
  • extract_gssurgo_profile.py38.3 KB
  • scripts/grid_netcdf_excel_bridge.py18.9 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

AmeriFlux gSSURGO/FAO Grid Extractor

Use When

  • You need soil profile values for an AmeriFlux or EcoSIM site from a local gSSURGO geodatabase.
  • You need FAO HWSD v2.0 fallback values when gSSURGO is outside coverage, unavailable, or has missing layer values.
  • You need EcoSIM template variables such as CDPTH, BKDSI, FC, WP, SCNV, SCNH, CSAND, CSILT, ROCK, PH, CEC, or CORGC.
  • You need depth-weighted interpolation from source horizons or HWSD2 layers to EcoSIM soil layers.
  • You need to inspect or edit an existing EcoSIM grid NetCDF as an Excel workbook, then rebuild the NetCDF after edits.

Constraints

  • NEVER use it extract climate data.
  • Do not require atmospheric gas scalar variables in EcoSIM grid files. Treat OXYEG (or typo OXYGE), Z2GEG, CO2EIG, CH4EG, Z2OEG, and ZNH3EG as optional legacy/template variables, not derivation gaps.

Workflow

  1. Locate gSSURGO_CONUS.gdb under data/ first, then elsewhere in the repo if needed.
  2. Identify the map unit (MUKEY) by spatial query on MUPOLYGON.
  3. Select the dominant component by comppct_r.
  4. Retrieve horizons and rock fragments from chorizon and chfrags.
  5. Convert units and interpolate vertically to the target template layers.
  6. If gSSURGO fails, generate the profile from FAO HWSD2 under data/FAO_HWSD2.
  7. If gSSURGO succeeds but some layer values are invalid/fill values, replace only those missing values from FAO HWSD2.
  8. Write the derived soil profile JSON under result/<SITE_ID>/.

Overview

This document summarizes which variables in the provided template can be extracted from the CONUS gSSURGO database (directory gSSURGO_CONUS.gdb) and from FAO HWSD v2.0, along with methods for extraction and vertical interpolation.

Extractable Variables from gSSURGO

The following template variables can be derived from standard gSSURGO tables:


Template Variable gSSURGO Source Notes


CDPTH chorizon.hzdepb_r / 100 Depth to bottom of horizon (m)

BKDSI chorizon.dbovendry_r Bulk density (g/cm3)

FC (wthirdbar_r / 100) * Field capacity dbthirdbar_r (volumetric)

WP (wfifteenbar_r / 100) * Wilting point dbfifteenbar_r

SCNV, SCNH ksat_r * 3.6 Convert um/s to mm/h

CSAND sandtotal_r * 10 kg/Mg

CSILT silttotal_r * 10 kg/Mg

ROCK sum(chfrags.fragvol_r) / 100 Volume fraction

PH ph1to1h2o_r Soil pH

CEC cec7_r Cation exchange capacity

CORGC om_r * 0.58 * 10 Soil organic carbon

Fallback Variables from FAO HWSD v2.0

The fallback reads HWSD2_RASTER/HWSD2.bil to identify HWSD2_SMU_ID, then uses the HWSD2_LAYERS attribute table from HWSD2.mdb or an exported HWSD2_LAYERS.csv/SQLite table. Use the dominant soil sequence (SEQUENCE=1) unless a different sequence is explicitly requested.


Template Variable FAO HWSD2 Source Notes


CDPTH template CDPTH Target EcoSIM depths remain template-driven

BKDSI BULK, fallback REF_BULK g/cm3 equals Mg m-3

FC, WP SAND/SILT/CLAY + AWC Texture-class defaults, adjusted by plausible AWC when available

SCNV, SCNH SAND/SILT/CLAY Texture-class Ksat estimate

CSAND SAND * 10 kg/Mg

CSILT SILT * 10 kg/Mg

ROCK COARSE / 100 Volume fraction

PH PH_WATER Soil pH

CEC CEC_SOIL cmolc/kg

CORGC ORG_CARBON g/kg equals kg C/Mg soil

FAO HWSD2 negative miscellaneous/no-data codes (-1 through -9) must be treated as invalid. The fallback should be recorded in the output JSON under sources_by_variable and fallbacks.

Non-Extractable Variables

The following variables are not directly available from gSSURGO and require external datasets or modeling assumptions:

  • Climate variables (e.g., ATCAG)
  • Topography (e.g., ASPX, slope)
  • Hydrologic boundary conditions
  • Nutrient pools (NH4, NO3, PO4)
  • Organic nitrogen/phosphorus pools
  • Exchange coefficients (GKC*) are not measured by gSSURGO. If paired exchange-solution chemistry is unavailable, invoke the gapon-coefficient-estimator ecosystem-template fallback, match the closest ecosystem before climate and management refinements, and remap the selected values to the grid's layer-bottom depths.
  • Water table dynamics

For template-based GKC* values, keep the selector's provenance JSON with the EcoSIM grid and include this reminder in the report or input metadata: "Gapon coefficients are initialized from the closest ecosystem template, not derived from site-specific paired exchange and solution chemistry. They are starting values and are subject to calibration or tuning when needed."

The atmospheric gas scalar variables OXYEG/OXYGE, Z2GEG, CO2EIG, CH4EG, Z2OEG, and ZNH3EG are not part of this soil-grid derivation contract. If they are absent from a generated grid NetCDF, do not flag the file as incomplete for this skill.

Vertical Interpolation

  • Use overlap-weighted averaging for most variables.
  • For soil organic matter (CORGC), apply logarithmic interpolation.
  • Optionally extend deepest horizon or FAO layer downward with --extend-last.

Script

A Python script (extract_gssurgo_profile.py) automates spatial lookup, horizon extraction, variable conversion, vertical interpolation, and FAO HWSD2 fallback.

The companion bridge script (scripts/grid_netcdf_excel_bridge.py) converts an EcoSIM grid NetCDF to an editable .xlsx workbook and back. Use it for file-wide parameter inspection or manual edits to grid parameters.

Example Usage

python .agents/skills/ameriflux-surgo-grid-extract/extract_gssurgo_profile.py \
  --gdb /path/to/gSSURGO_CONUS.gdb \
  --lon -121.85 \
  --lat 39.0 \
  --template template.nc \
  --out result/<SITE_ID>/profile_<SITE_ID>.json \
  --extend-last

The FAO fallback is enabled by default and looks under data/FAO_HWSD2. Use --fao-hwsd2-dir /path/to/FAO_HWSD2 to override the location, or --no-fao-fallback for a strict gSSURGO-only run.

Grid NetCDF Excel Bridge

Use the bundled bridge for grid NetCDF, Excel, and NetCDF round trips:

.venv-cmip6/bin/python .agents/skills/ameriflux-surgo-grid-extract/scripts/grid_netcdf_excel_bridge.py \
  nc-to-xlsx input_grid.nc editable_grid.xlsx

.venv-cmip6/bin/python .agents/skills/ameriflux-surgo-grid-extract/scripts/grid_netcdf_excel_bridge.py \
  xlsx-to-nc editable_grid.xlsx edited_grid.nc --format NETCDF3_CLASSIC

Workbook sheets:

  • dimensions: NetCDF dimension names, lengths, and unlimited flags.
  • global_attrs: global NetCDF attributes.
  • variables: variable names, dtypes, dimensions, and fill values.
  • variable_attrs: per-variable metadata such as long_name, units, and flags.
  • values: flattened variable values with zero-based index tuples.

After editing, run a scratch round trip and compare dimensions, variables, attributes, and data values before using the rebuilt grid file in EcoSIM. Pay special attention to units and mass-balance-sensitive pools; the bridge edits values mechanically and does not make non-derivable parameters scientifically valid.

Notes

  • Bulk density and water retention conversions assume standard pedotransfer interpretations.
  • Ensure gSSURGO geodatabase includes required tables: MUPOLYGON, component, chorizon, chfrags.
  • FAO HWSD2 provides seven layers (D1-D7, 0-200 cm). When --extend-last is used, the deepest FAO layer is extended downward to fill deeper EcoSIM template layers; this should be treated as a gap-fill assumption, not direct observation.
  • Reading HWSD2.mdb requires GDAL/pyogrio with MDB support. If that driver is unavailable, export the Access table as HWSD2_LAYERS.csv in the same FAO_HWSD2 directory.

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