Streamlining land surface model Initialization: Automated data retrieval for VELMA using HMS REST API and GDAL
Citation:
Venable, Karretta, J. Johnston, AND S. Leduc. Streamlining land surface model Initialization: Automated data retrieval for VELMA using HMS REST API and GDAL. ENVIRONMENTAL MODELLING & SOFTWARE. Elsevier Science, New York, NY, 191:106492, (2025). https://doi.org/10.1016/j.envsoft.2025.106492
Impact/Purpose:
This research focuses on automation for batch collection of the digital elevation model, climate drivers, and surface runoff across the United States to initialize the Visualizing Ecosystem and Land Management Assessment model (VELMA). Using a gridded digital elevation model for any area of interest, acquisition of a single location or gridded network of weather drivers and stream runoff data were developed. This was accomplished using the US EPA's Hydrologic Micro Services (HMS) Representation State Transfer (REST) application programming interface (API) and the Geospatial Data Abstraction Library (GDAL) with Python. This innovation allows VELMA users to initialize simulations more efficiently.
Description:
Continuous monitoring data required for performing environmental model simulations using gridded land surface models (LSMs) are often difficult to obtain and manage, making the modeling process challenging and prone to error. In response, this study focuses on automated retrieval and processing of digital elevation models (DEMs from Google Earth Engine (GEE)), meteorologic drivers of hydrology, and surface runoff time series data, using the Visualizing Ecosystem and Land Management Assessment (VELMA) model as a case study. Our automation methodology is accomplished using the USEPA's Hydrologic Micro Services (HMS) Representation State Transfer (REST) application programming interface (API) and Geospatial Data Abstraction Library (GDAL) with Python. This workflow provides greater efficiency, minimizes data preparation time, reduces manual processing errors, and provides a reusable methodology for use in other modeling studies. With this innovation, users of VELMA and other gridded LSMs will be able to initialize simulations more efficiently, improving their operational capabilities.
URLs/Downloads:
DOI: Streamlining land surface model Initialization: Automated data retrieval for VELMA using HMS REST API and GDAL