ESRL/PSD Seminar Series

HydroDesktop: An Open Source GIS-Based Platform for Hydologic Data Discovery, Visualization, and Analysis

Dr. Daniel P. Ames
Dept of Geosciences, Idaho State University, Idaho Falls


A growing number of hydrologic information servers are being deployed by government agencies, university networks, and individual researchers using the CUAHSI Hydrologic Information System (HIS), Observations Data Model (ODM) database and Water Data Service web services. Metadata regarding available datasets on these servers is cataloged in HIS Central at the San Diego Supercomputer Center and is searchable through a set of predefined web services based metadata queries. Together, these servers and central catalog service comprise a federated hydrologic information system of a scale and comprehensiveness never previously available.

This presentation will briefly review/introduce the CUAHSI HIS system with special focus on a new HIS software tool called "HydroDesktop" and the open source software development web portal,, which supports community development and maintenance of the software.

HydroDesktop is a client-side desktop software application that acts as a search and discovery tool for exploring the distributed network of HIS servers, downloading specific data series, visualizing and summarizing data series and exporting these to formats needed for analysis by external software. HydroDesktop is based on the open source DotSpatial GIS developer toolkit which provides it with map-based data interaction and visualization, as well as an extensive plug-in interface that can be used by third party developers and researchers to easily extend the software using Microsoft .NET programming languages. HydroDesktop plug-ins that are presently available or currently under development within the project and by third party collaborators include functions for data search and discovery, extensive graphing, data editing and export, HIS server exploration, integration with the OpenMI workflow and modeling system, and an interface for data analysis through the R statistical package.

Friday, September 10

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