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Accessing Hydrology and Climatology Database Using Web Services Through Python

Chegini, Taher

Preparing and processing input data is one the most time consuming parts of hydrological and climate modeling, both physical and data-driven. The required input data are scattered through the web offered in various formats and through several web service protocols. A major barrier for streamlining the use of these web services in the scientific community, is the required technical skills and knowledge. HyRiver is a stack of Python libraries that bridges this gap by providing high-level APIs to these web services. This showcase provides a workflow for carrying out a data analysis across US East, West, and Gulf coasts. We get various datasets such as daily streamflow, river network, and climate data from different sources. Presentation materials are available here.

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