DOI: 10.5281/zenodo.14217002
title: Reference Mean and Low Streamflow for all Brazilian Catchments Generated Using Machine Learning Models

description: This dataset provides comprehensive hydrological information for river networks in Brazil, focusing on reference streamflows, specifically long-term mean flows (qm) and low flows exceeded 95% of the time (q95). Covering over 400,000 ungauged river points, the dataset was developed using advanced machine learning models trained on environmental descriptors and validated against data from 1,069 gauging stations spread across the country. The machine learning pipeline evaluated six regression models to achieve high predictive accuracy (R² > 0.8 for qm and > 0.7 for q95). The 62 environmental descriptors - encompassing climate, topography, land cover, lithology, and water storage characteristics - that were used as features for the models are also included.

Key features:



Spatial Coverage: Brazilian territory and the Amazon River basin, based on the BHO 5k dataset of officially adopted river networks.

Outputs: Predicted qm and q95 values for each river stretch, with 90% and 75% confidence intervals to account for prediction uncertainty.

Environmental Descriptors: Aggregated from upstream catchment area.


 
description: Target variables, all by unit area:

"qm": mean flow

"q95": flow exceeded 95% of the time

 

---

 

Files that start with "gauges":

 

- indicate results obtained at the gauged sites

- validation performed using 10-nested folds

- post-processed, where negative values were replaced by zero

 

columns:

'obs'[float]: observed value in l/s per unit area (km2)

'pred'[float]: predicted value in l/s per unit area (km2), i.e. average of best models' ensemble

'ens_std'[float]: standard deviation of best models' ensemble.

'ens_cv'[float]: coefficient of variation (std/avg) of best models' ensemble.

'error_abs'[float]: absolute error in l/s per unit area (km2), i.e. obs - pred

'error_rel'[float]: relative error in l/s per unit area (km2), i.e. (obs - pred)/pred

'lat'[float]: latitude of gauging station (crs=EPSG:4326)

'lon'[float]: longitude of gauging station (crs=EPSG:4326)

 

---

 

Files that start with "bho":

 

- indicate results extrapolated to all data points (gauged and ungauged)

- models trained at gauged points

- post-processed, where negative values were replaced by zero

 

"data": only results with no geometry

"area": the area geometry is included in each data point

"trecho": the trecho geometry is included in each data point

 

columns for all files:

'seg_id' [index]: equivalent to 'cotrecho' in the original bho dataset; unique identifier.

'code_otto'[str]: equivalent to 'cobacia' in the original bho dataset; otto pfaffstatter code.

'area_upst'[float]: equivalent to 'nuareamont' in the original; upstream area.

 

columns for qm and q95:

'pred'[float]: predicted value in l/s per unit area (km2), i.e. average of best models' ensemble.

'ens_std'[float]: standard deviation of best models' ensemble.

'ens_cv'[float]: coefficient of variation (std/avg) of best models' ensemble.

'90_low'[float]: 90% confidence lower value in l/s per unit area (km2).

'90_high'[float]: 90% confidence higher value in l/s per unit area (km2).

'75_low'[float]: 75% confidence lower value in l/s per unit area (km2).

'75_high'[float]: 75% confidence higher value in l/s per unit area (km2).

'gauged'[boolean]: whether data point was used for training (true) or not (false).

 

columns for descriptors:

'p_avg'[float]: Average monthly precipitation in mm/month.

'p_min'[float]: Minimum monthly precipitation in mm/month.

'p_max'[float]: Maximum monthly precipitation in mm/month.

't_avg'[float]: Average monthly temperature in C.

't_min'[float]: Minimum monthly temperature in C.

't_max'[float]: Maximum monthly temperature in C.

'et_avg'[float]: Average monthly evapotranspiration in mm/month.

'et_min'[float]: Minimum monthly evapotranspiration in mm/month.

'et_max'[float]: Maximum monthly evapotranspiration in mm/month.

'pet_avg'[float]: Average monthly potential evapotranspiration in mm/month.

'pet_min'[float]: Minimum monthly potential evapotranspiration in mm/month.

'pet_max'[float]: Maximum monthly potential evapotranspiration in mm/month.

'tc_wtl'[float]: Percentage of catchment covered by wetlands.

'tc_hls'[float]: Percentage of catchment covered by hillslopes.

'tc_plt'[float]: Percentage of catchment covered by plateaus.

'sc_cly'[float]: Soil content percentage of clay.

'sc_org'[float]: Soilcontent percentage of organic matter.

'sc_snd'[float]: Soil content percentage of sand.

'sc_wtr'[float]: Soil content percentage of water.

'tp_elv'[float]: Mean elevation of catchment in m.

'tp_slp'[float]: Average slope of the catchment in degrees.

'tp_hnd'[float]: Mean height above nearest drainage of catchment in m.

'tp_dd'[float]: Drainage density of catchment in km/km2.

'tp_ua'[float]: Catchment upstream area in km2.

'ws_gw'[float]: Groundwater storage variability.

'ws_rs'[float]: Reservoir storage variability.

'ws_sm'[float]: Soil Moisture storage variability.

'ws_sw'[float]: Surface Water storage variability.

'ws_tt'[float]: Total water storage variability.

'lc_fr'[float]: Land cover percentage - forests.

'lc_gr'[float]: Land cover percentage - grasslands.

'lc_ag'[float]: Land cover percentage - agricultural lands.

'lc_pr'[float]: Land cover percentage - prairies.

'lc_wt'[float]: Land cover percentage - wetlands.

'st_cl'[float]: Soil type percentage - clay.

'st_sicl'[float]: Soil type percentage - silty clay.

'st_sacl'[float]: Soil type percentage - sandy clay.

'st_cllo'[float]: Soil type percentage - clay loam.

'st_sicllo'[float]: Soil type percentage - silty clay loam.

'st_sacllo'[float]: Soil type percentage - sandy clay loam.

'st_lo'[float]: Soil type percentage - loam.

'st_silo'[float]: Soil type percentage - silty loam.

'st_salo'[float]: Soil type percentage - sandy loam.

'st_si'[float]: Soil type percentage - silt.

'st_losa'[float]: Soil type percentage - loamy sand.

'st_sa'[float]: Soil type percentage - sand.

'lt_su'[float]: Lithology type percentage - surface units.

'lt_vb'[float]: Lithology type percentage - volcanic and bedrock.

'lt_ss'[float]: Lithology type percentage - sandstone.

'lt_pb'[float]: Lithology type percentage - plutonic bedrock.

'lt_sm'[float]: Lithology type percentage - sedimentary materials.

'lt_sc'[float]: Lithology type percentage - schist.

'lt_va'[float]: Lithology type percentage - volcanic ash.

'lt_mt'[float]: Lithology type percentage - metamorphic terrains.

'lt_pa'[float]: Lithology type percentage - pyroclastic ash.

'lt_vi'[float]: Lithology type percentage - volcanic igneous.

'lt_wb'[float]: Lithology type percentage - weathered bedrock.

'lt_py'[float]: Lithology type percentage - pyroclastics.

'lt_pi'[float]: Lithology type percentage - plutonic igneous.

'lt_ev'[float]: Lithology type percentage - evaporites.

'lt_nd'[float]: Lithology type percentage - no data.

'lt_ig'[float]: Lithology type percentage - igneous rocks.