Author Topic: HydroDS: Data Services in Support of Physically Based, Distributed Hydrological  (Read 234 times)

Pankaj Dey

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  • Institute : Indian Institute of Science
  • Programming language : MATLAB, R
Physically based distributed hydrologic models require geospatial and time-series data that take considerable time and effort in processing them into model inputs. Tools that automate and speed up input processing facilitate the application of these models. In this study, we developed a set of web-based data services called HydroDS to provide hydrologic data processing ‘software as a service.’ HydroDS provides functions for processing watershed, terrain, canopy, climate, and soil data. The services are accessed through a Python client library that facilitates developing simple but effective data processing workflows with Python. Evaluations of HydroDS by setting up the Utah Energy Balance and TOPNET models for multiple headwater watersheds in the Colorado River basin show that HydroDS reduces the input preparation time compared to manual processing. It also removes the requirements for software installation and maintenance by the user, and the Python workflows enhance reproducibility of hydrologic data processing and tracking of provenance.

Highlights

•Web-based data services developed for preparation of input data to selected distributed hydrologic models.
•Services are accessed through a Python client library and facilitate development of simple and effective Python workflow scripts.
•Services reduce time for hydrologic model input preparation, enhance reproducibility of hydrologic data processing, and enable tracking of data provenance.

Paper: https://www.sciencedirect.com/science/article/pii/S1364815217308009

Github: https://github.com/CI-WATER/Hydro-DS/
Pankaj