Utah Water Research Laboratory转发了
?? New publication from the NSF I-GUIDE team! "Toward Reproducible and Interoperable Environmental Modeling: Integration of HydroShare with Server-side Methods for Exposing Large-Extent Spatial Datasets to Models" published in Environmental Modelling and Software By authors: Young-Don Choi of K-water (Korea Water Resources Corporation) and the University of Virginia Iman Maghami of the University of Virginia and Brigham Young University Jonathan Goodall of the University of Virginia Larry Band of the University of Virginia Ayman Nassar of the Utah State University YuJu (Laurence) LIN of the University of Virginia Linnea Saby, Ph.D. of the University of Virginia ZHIYU (Drew) LI of the University of Utah Shaowen Wang of the University of Illinois Urbana-Champaign Chris Calloway of the University of North Carolina at Chapel Hill Hong Yi of the University of North Carolina at Chapel Hill Martin Seul of the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) Dan Ames of Brigham Young University David Tarboton of the Utah Water Research Laboratory at the University of Utah Read the full paper here ?? https://lnkd.in/gvTJcRhG This study presents a method for automating the distribution of state-scale spatial datasets for GIS-based environmental modeling, using GeoServer and THREDDS Data Server connected to HydroShare. By applying this approach with the RHESSys model across three U.S. watersheds, the study demonstrates minimal errors compared to traditional methods, enhancing reproducibility. This method can be adapted for various scales and other online data repositories, streamlining the process for researchers. Read the full paper here ?? https://lnkd.in/gvTJcRhG Abstract 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.