Toward reproducible and interoperable environmental modeling: Integration of HydroShare with server-side methods for exposing large-extent spatial datasets to models

Young Don Choi, Iman Maghami, Jonathan L. Goodall, Lawrence Band, Ayman Nassar, Laurence Lin, Linnea Saby, Zhiyu Li, Shaowen Wang, Chris Calloway, Hong Yi, Martin Seul, Daniel P. Ames, David G. Tarboton

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Article number106239
JournalEnvironmental Modelling and Software
Volume183
DOIs
StatePublished - Jan 2025

Keywords

  • GeoServer
  • HydroShare
  • Large spatial datasets
  • Reproducible environmental modeling
  • Server-side data access
  • THREDDS data server

ASJC Scopus subject areas

  • Software
  • Environmental Engineering
  • Ecological Modeling

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