SWAT-IRR: A new irrigation algorithm for soil and water Assessment tool to facilitate water management and Conservation in irrigated regions
• SWAT-IRR offers improved control and representation of irrigation simulation. • SWAT-IRR enables the simulation of surface, sprinkler, and drip irrigation systems. • Users can apply the curve number approach to compute irrigation surface runoff. • A Python-based input processing tool facilitates SWAT-IRR application. • The utility of SWAT-IRR is showcased through an application in central Oklahoma. Accurate simulation of irrigation is key for effective water resources planning and management across various scales. This paper presents SWAT-IRR, a new irrigation algorithm for the Soil and Water Assessment Tool (SWAT) model, designed to enhance the simulation of how different irrigation systems and schedules influence hydrologic fluxes in irrigated agricultural areas. SWAT-IRR enables explicit simulation of three irrigation systems (surface, sprinkler, and drip) parameterized using irrigation application efficiency, conveyance efficiency, surface runoff ratio, and an additional area adjustment factor parameter for drip irrigation. SWAT-IRR offers three simulation options to accommodate varying user needs. Option 0 is the original SWAT model irrigation algorithm. Option 1 addresses the original SWAT model’s limitation by improving control of irrigation simulation during growing seasons. Option 2 builds on Option 1 by integrating a new irrigation algorithm to advance the representation of irrigation processes and their associated impacts on hydrologic fluxes. Option 3 further strengthen Option 2 by adopting the U.S. Department of Agriculture (USDA) Natural Resources Conservation Service (NRCS) curve number approach to estimate irrigation surface runoff, as an alternative to the surface runoff ratio. An application of SWAT-IRR at the Fort Cobb Reservoir Experimental Watershed (FCREW) in central Oklahoma illustrates its effectiveness in enhancing irrigation simulation. Comparisons between the original SWAT model and SWAT-IRR, as well as among the various SWAT-IRR options, demonstrates its ability to improve control and representation of irrigation simulation and capture practical aspects of water allocation from various sources and water application using different irrigation systems.
Authors
- Patrick J. Starks (ORCID: https://orcid.org/0000-0003-2844-8993)
- Jean L. Steiner (ORCID: https://orcid.org/0000-0003-3779-8717)
- Ali Mirchi (ORCID: https://orcid.org/0000-0002-9649-2964)
- Maryam Samimi (ORCID: https://orcid.org/0000-0003-0864-4153)
- Daniel N. Moriasi (ORCID: https://orcid.org/0000-0002-3389-3277)
- Zaichen Xiang
- J. Alan Verser
- Saleh Taghvaeian (ORCID: https://orcid.org/0000-0002-9438-6682)
Institutions
- University of Nebraska–Lincoln (US)
- Oklahoma State University (US)
- Kansas State University (US)
- Grazinglands Research Laboratory (US)
- National Laboratory for Agriculture and the Environment (US)
- St. Edward's University (US)
Publication Details
- Journal
- Computers and Electronics in Agriculture
- Published
- 2025-02-20
- DOI
- https://doi.org/10.1016/j.compag.2025.110142
- Citations
- 6
- Primary Topic
- Hydrology and Watershed Management Studies
- Type
- article
- Field-Weighted Citation Impact
- 4.90
Funders
- Agricultural Research Service