Improving SWAT auto-irrigation functions for simulating agricultural irrigation management using long-term lysimeter field data
Decreasing groundwater availability in the Texas High Plains has resulted in the widespread adoption of management allowed depletion (MAD) irrigation scheduling. Modeling of such practices and their effects on water balance components can be a cost-effective and time-saving alternative to field-base...
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| Published in | Environmental modelling & software : with environment data news Vol. 99; pp. 25 - 38 |
|---|---|
| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
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Oxford
Elsevier Ltd
01.01.2018
Elsevier Science Ltd |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1364-8152 1873-6726 |
| DOI | 10.1016/j.envsoft.2017.09.013 |
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| Abstract | Decreasing groundwater availability in the Texas High Plains has resulted in the widespread adoption of management allowed depletion (MAD) irrigation scheduling. Modeling of such practices and their effects on water balance components can be a cost-effective and time-saving alternative to field-based research. However, studies have identified deficiencies in the auto-irrigation algorithms in the Soil and Water Assessment Tool (SWAT) including the continuation of irrigation during the non-growing season and an inability to simulate growth stage-specific irrigation. Consequently, new and representative auto-irrigation algorithms were developed using 1) a uniform, single season MAD and 2) a growth stage-specific MAD with options for seasonal growth stage partitioning based on scheduled date and accumulated heat units. Comparisons with observed data from an irrigated lysimeter field showed improved model performance for simulations of irrigation amount and frequency and actual evapotranspiration. Minimal differences in leaf area index and yield were observed with the non-water stressed management.
•SWAT default auto-irrigation failed to reproduce the actual irrigation scheduling.•Management allowed depletion (MAD) irrigation algorithm was developed using Fortran.•Growth stage-specific MAD irrigation algorithm was also developed based on FAO.•Ten-year observed irrigation and actual ET data were used to evaluate MAD algorithm.•FAO-MAD auto-irrigation improved representation and simulation of irrigation and ET. |
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| AbstractList | Decreasing groundwater availability in the Texas High Plains has resulted in the widespread adoption of management allowed depletion (MAD) irrigation scheduling. Modeling of such practices and their effects on water balance components can be a cost-effective and time-saving alternative to field-based research. However, studies have identified deficiencies in the auto-irrigation algorithms in the Soil and Water Assessment Tool (SWAT) including the continuation of irrigation during the non-growing season and an inability to simulate growth stage-specific irrigation. Consequently, new and representative auto-irrigation algorithms were developed using 1) a uniform, single season MAD and 2) a growth stage-specific MAD with options for seasonal growth stage partitioning based on scheduled date and accumulated heat units. Comparisons with observed data from an irrigated lysimeter field showed improved model performance for simulations of irrigation amount and frequency and actual evapotranspiration. Minimal differences in leaf area index and yield were observed with the non-water stressed management. Decreasing groundwater availability in the Texas High Plains has resulted in the widespread adoption of management allowed depletion (MAD) irrigation scheduling. Modeling of such practices and their effects on water balance components can be a cost-effective and time-saving alternative to field-based research. However, studies have identified deficiencies in the auto-irrigation algorithms in the Soil and Water Assessment Tool (SWAT) including the continuation of irrigation during the non-growing season and an inability to simulate growth stage-specific irrigation. Consequently, new and representative auto-irrigation algorithms were developed using 1) a uniform, single season MAD and 2) a growth stage-specific MAD with options for seasonal growth stage partitioning based on scheduled date and accumulated heat units. Comparisons with observed data from an irrigated lysimeter field showed improved model performance for simulations of irrigation amount and frequency and actual evapotranspiration. Minimal differences in leaf area index and yield were observed with the non-water stressed management. •SWAT default auto-irrigation failed to reproduce the actual irrigation scheduling.•Management allowed depletion (MAD) irrigation algorithm was developed using Fortran.•Growth stage-specific MAD irrigation algorithm was also developed based on FAO.•Ten-year observed irrigation and actual ET data were used to evaluate MAD algorithm.•FAO-MAD auto-irrigation improved representation and simulation of irrigation and ET. |
| Author | Brauer, D.K. Srinivasan, R. Chen, Y. Marek, G.W. Marek, T.H. |
| Author_xml | – sequence: 1 givenname: Y. surname: Chen fullname: Chen, Y. email: yongchen@neo.tamu.edu organization: Department of Ecosystem Science and Management, Texas A&M University, 2138 TAMU, College Station, TX 77845, USA – sequence: 2 givenname: G.W. surname: Marek fullname: Marek, G.W. organization: USDA-ARS Conservation and Production Research Laboratory, 2300 Experiment Station Rd., P.O. Drawer 10, Bushland, TX 79012, USA – sequence: 3 givenname: T.H. surname: Marek fullname: Marek, T.H. organization: Texas A&M AgriLife Research, Texas A&M AgriLife Research and Extension Center, 6500 Amarillo Blvd W, Amarillo, TX 79106, USA – sequence: 4 givenname: D.K. surname: Brauer fullname: Brauer, D.K. organization: USDA-ARS Conservation and Production Research Laboratory, 2300 Experiment Station Rd., P.O. Drawer 10, Bushland, TX 79012, USA – sequence: 5 givenname: R. orcidid: 0000-0001-8375-6038 surname: Srinivasan fullname: Srinivasan, R. organization: Department of Ecosystem Science and Management, Texas A&M University, 2138 TAMU, College Station, TX 77845, USA |
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| Keywords | Crop leaf area index (LAI) Actual evapotranspiration (ET) Soil water deficit Heat units Auto-irrigation Management allowed depletion (MAD) |
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| SubjectTerms | Actual evapotranspiration (ET) Agricultural management Algorithms Auto-irrigation Computer simulation computer software cost effectiveness Crop leaf area index (LAI) developmental stages Evapotranspiration Groundwater Groundwater availability Groundwater data Growing season Growth stage heat Heat units High plains Hydrologic models irrigated farming Irrigation Irrigation scheduling Leaf area Leaf area index lysimeters Management allowed depletion (MAD) model validation seasonal growth Soil and Water Assessment Tool model Soil water Soil water deficit Texas Water balance Water management |
| Title | Improving SWAT auto-irrigation functions for simulating agricultural irrigation management using long-term lysimeter field data |
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