Jupyter Meets the Earth: Hydrological use cases

This Jupyter book presents two projects:

  1. Hydrometeorological data preprocessing

  2. Hydrological model benchmarking

The first project enables interactively aquiring and preprocessing raw hydrometeorological data to deliver a ready to use hydrometeorological data. As such, it involves different data quality control and filling missing value techniques. The project is at the core of the CHOSEN dataset that provides intensively monitored hydrometeorological dataset for 30 watersheds across the CONUS.

The second project focuses on interactively benchmarking hydrological models using both the common statistical and the recent information theoretic based model benchmarking techniques. As a test case, the project focuses on benchmarking the National Hydrological Model (NHM) product of the USGS that covers the CONUS.


This work is supported by the NSF Earth Cube Program under awards 1928406 and 1928374.


Edom Moges
Environmental Systems Dynamics Laboratory (ESDL)
University of California, Berkeley