Inputs and Outputs

This page summarizes required inputs, expected units/CRS, and outputs by module.

Global assumptions

  • CRS: EPSG:4326 for all rasters and vector inputs unless noted.

  • Area units: number of DEM grid cells; the effective cell area depends on the DEM resolution.

  • Discharge units: m³/s (raw), area-normalized to mm/day for model inputs.

Observed streamflow CSV schema

Lookup CSV (station metadata)

Required columns (default names in parentheses): - station id (id) - latitude (latitude) - longitude (longitude)

Notes: - Coordinates must be in EPSG:4326. - Station IDs are treated as strings.

Per-station CSV (time series)

Required columns (default names in parentheses): - date (date) - discharge (discharge)

Notes: - Dates must be parseable by pandas (e.g., YYYY-MM-DD). - Discharge is expected in m³/s. - One CSV per station; filenames follow {id}.csv by default.

Predicted streamflow units

Model training is performed on linear targets. When area_normalize=True, the target is area-normalized discharge depth (mm/day), and predictions are converted back to volumetric discharge (m³/s) by reversing the area normalization. The CSV outputs written to {working_dir}/predicted_streamflow_data are in m³/s.

When loss_function="asym_laplace_nll", the model predicts 3 values per sample (location + asymmetric scales). The runner/simulator uses the first value (location term) as discharge prediction for plots and CSV outputs.

If area_normalize=False is used, the model trains and predicts in raw m³/s, and no area-based conversion is applied at inference time.

Note: Prediction time series start after a one-year warmup period. The first 365 days of the simulation window are used as model context and are not written to the output CSVs.

Module reference

DEM (bakaano.dem.DEM)

Inputs: - study_area: basin shapefile (EPSG:4326) - local_data_path (optional): local DEM GeoTIFF (EPSG:4326)

Outputs: - {working_dir}/elevation/dem_clipped.tif - {working_dir}/elevation/slope_clipped.tif

Soil (bakaano.soil.Soil)

Inputs: - study_area: basin shapefile (EPSG:4326)

Outputs: - {working_dir}/soil/clipped_AWCh3_M_sl6_1km_ll.tif - {working_dir}/soil/clipped_WWP_M_sl6_1km_ll.tif - {working_dir}/soil/clipped_AWCtS_M_sl6_1km_ll.tif

NDVI (bakaano.ndvi.NDVI)

Inputs: - start_date / end_date: YYYY-MM-DD - study_area: basin shapefile (EPSG:4326)

Outputs: - {working_dir}/ndvi/daily_ndvi_climatology.pkl - Intermediate NDVI GeoTIFFs in {working_dir}/ndvi/

Tree cover (bakaano.tree_cover.TreeCover)

Inputs: - start_date / end_date: YYYY-MM-DD - study_area: basin shapefile (EPSG:4326)

Outputs: - {working_dir}/vcf/mean_tree_cover.tif - {working_dir}/vcf/mean_herb_cover.tif

AlphaEarth (bakaano.alpha_earth.AlphaEarth)

Inputs: - start_date / end_date: YYYY-MM-DD - study_area: basin shapefile (EPSG:4326)

Outputs: - {working_dir}/alpha_earth/band_A00.tif … band_A63.tif

Meteo (bakaano.meteo.Meteo)

Inputs: - start_date / end_date: YYYY-MM-DD - data_source: CHELSA, ERA5, or CHIRPS

Outputs:

  • NetCDFs in {working_dir}/{data_source}/ (pr, tasmax, tasmin, tas)

  • For Earth Engine downloads (ERA5/CHIRPS), intermediate GeoTIFFs are stored in scratch folders before conversion to NetCDF.

VegET + routing (bakaano.veget.VegET)

Inputs: - DEM, soil, NDVI, tree cover, meteo - routing_method: mfd, d8, dinf - climate_data_source: CHELSA, ERA5, or CHIRPS - resume / checkpoint_days (optional): resume interrupted routing runs and

control checkpoint frequency

Outputs: - Routed runoff in {working_dir}/runoff_output/wacc_sparse_arrays.pkl - Resume state during interrupted runs:

{working_dir}/runoff_output/wacc_resume_state.pkl

  • Temporary checkpoint chunks during interrupted runs: {working_dir}/runoff_output/wacc_resume_chunks/*.pkl

  • River grid in {working_dir}/catchment/river_grid.tif (if generated)

Streamflow training (bakaano.streamflow_trainer)

Inputs: - GRDC NetCDF (or CSV lookup + per-station CSVs) - Routed runoff in {working_dir}/runoff_output - AlphaEarth bands in {working_dir}/alpha_earth

Outputs: - Trained model: {working_dir}/models/bakaano_model.keras - AlphaEarth scaler: {working_dir}/models/alpha_earth_scaler.pkl

Streamflow simulation (bakaano.streamflow_simulator)

Inputs: - Trained model - Routed runoff and AlphaEarth bands - GRDC NetCDF or station CSVs (optional)

Outputs: - Predicted streamflow CSVs in {working_dir}/predicted_streamflow_data