Open-source Python toolkit for water data, hydrology, and agricultural water management — 15 unified collectors (USGS, FAO, GEMStat, EU WFD…), Bulletin 17C flood frequency, FAO-56 ET₀, and an AI methodology recommender.
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Updated
Aug 13, 2026 - Python
Open-source Python toolkit for water data, hydrology, and agricultural water management — 15 unified collectors (USGS, FAO, GEMStat, EU WFD…), Bulletin 17C flood frequency, FAO-56 ET₀, and an AI methodology recommender.
A distributed hydrology-guided neural network model for streamflow prediction
Pre-delineated MERIT-Hydro watershed boundaries for ~60,000 gauging stations across 16 countries. Zero-config — basins are fetched from a public CDN and cached locally.
Heatmaps of empirical and exceedance probability of many (time-)series.
sondera is a python package providing clients for accessing Swedish hydrology and meteorology related open data. Data sources currently include SMHI open data API and SGU groundwater API.
Home Assistant integration for real-time USGS stream gauge data (flow, gauge height, water temperature)
CLI-based workflow tool for NextGen Water Modeling Framework simulations
LSTM rainfall-runoff forecasting pipeline for streamflow prediction with reproducible metrics and plots.
Synthetic one-step-ahead streamflow forecasting benchmark with statistical and ML baselines
A Python package to conveniently parse Canadian climate and streamflow data to pandas or xarray
Multi-horizon river flow forecasting with upstream hydrologic info (LSTM/ML + HSJ submission pipeline)
Deterministic synthetic-data LSTM demonstration for one-step-ahead discharge forecasting
Lightweight Python scripts for comparing observed and modeled time series, computing standard performance metrics, and generating daily plots.
A lightweight Python toolkit for downloading, processing, and filtering USGS NWIS daily water data. Supports batch downloads, parameter code discovery, and tidy Pandas DataFrames.
HydroTransformer: A Transformer Framework for Generalizable Streamflow Modeling Across Space and Time
Predicting Streamflow in CAMELS Catchments Using LSTM and Transformers
LSTM-GNN routing model for learning streamflow from gridded hydroclimate inputs and Ngen river-network topology.
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