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Reproducible environmental modelling often relies on spatial datasets as inputs, typically manually subset for specific areas. Yet, models can benefit from a data distribution approach facilitated by online repositories, and automating processes to foster reproducibility. This study introduces a method leveraging diverse state-scale spatial datasets to create cohesive packages for GIS-based environmental modelling. These datasets were generated and shared via GeoServer and THREDDS Data Server Connected to HydroShare, contrasting with conventional distribution methods. Using the Regional Hydro-Ecologic Simulation System (RHESSys) across three U.S. catchment-scale watersheds, we demonstrate minimal errors in spatial inputs and model streamflow outputs compared to traditional approaches. This spatial data-sharing method facilitates consistent model creation, fostering reproducibility. Its broader impact allows scientists to tailor the method to various use cases, such as exploring different scales beyond state-scale or applying it to other online repositories using existing data distribution systems, eliminating the need to develop their own.more » « lessFree, publicly-accessible full text available January 1, 2026
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null (Ed.)We present the design and development of an open-source web application called Water Data Explorer (WDE), designed to retrieve water resources observation and model data from data catalogs that follow the WaterOneFlow and WaterML Service-Oriented Architecture standards. WDE is a fully customizable web application built using the Tethys Platform development environment. As it is open source, it can be deployed on the web servers of international government agencies, non-governmental organizations, research teams, and others. Water Data Explorer provides uniform access to international data catalogs, such as the Consortium of Universities for the Advancement of Hydrologic Science (CUAHSI) Hydrologic Information System (HIS) and the World Meteorological Organization (WMO) Hydrological Observing System (WHOS), as well as to local data catalogs that support the WaterOneFlow and WaterML standards. WDE supports data discovery, visualization, downloading, and basic data interpolation. It can be customized for different regions by modifying the user interface (i.e., localization), as well as by including pre-defined data catalogs and data sources. Access to WDE functionality is provided by a new open-source Python package called “Pywaterml” which provides programmable access to WDE methods to discover, visualize, download, and interpolate data. We present two case studies that access the CUAHSI HIS and WHOS catalogs and demonstrate regional customization, data discovery from WaterOneFlow web services, data visualization of time series observations, and data downloading.more » « less
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