Estimating Evapotranspiration for Dryland Cropping Systems in the Semiarid Texas High Plains Using <scp>SWAT</scp>

Marek, Gary W.; Gowda, Prasanna H.; Evett, Steven R.; Baumhardt, R. Louis; Bräuer, David; Howell, Terry A.; Marek, Thomas H.; Srinivasan, Raghavan

doi:10.1111/1752-1688.12383

Cited by 33 publications

(38 citation statements)

References 28 publications

(41 reference statements)

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“…This argument concurs with the results by Marek et al. (2016b) that used the Soil and Water Assessment Tool model for the same site. They attributed overestimation of ET earlier in the growing season to increased available water content due to occurrence of rainfall events in some years.…”

Section: Resultssupporting

confidence: 92%

Simulating Soil Water Content, Evapotranspiration, and Yield of Variably Irrigated Grain Sorghum Using AquaCrop

Masasi

Taghvaeian

Gowda

et al. 2019

J American Water Resour Assoc

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Use of models to simulate crop production has become important in optimizing irrigation management in arid and semiarid regions. However, applicability and performance of these models differ across regions, due to differences in environmental and management factors. The AquaCrop model was used to simulate soil water content (SWC), evapotranspiration (ET), and yield for grain sorghum under different irrigation regimes and dryland conditions at two sites in Central and Southern High Plains. Prediction error (Pe), estimated as the difference between simulated and measured divided by measured, for SWC ranged from −17% to 4% in fully irrigated, −3% to −10% in limited irrigated, and −16% to 25% in dryland treatments. The Pe within ±4%, −5%, and −17% to 24% were attained for seasonal ET under fully irrigated, limited irrigated, and dryland conditions, respectively. Pe values for grain yield were within those previously reported and ranged from −10% to 12%, −12% to 7%, and 9% to 17% for fully irrigated, limited irrigated and dryland conditions, respectively. Overall performance of the AquaCrop model showed it could be used as an effective tool for evaluating the impacts of variable crop and irrigation managements on the production of grain sorghum in the study area. Finally, the application of the model in the study area revealed planting date has a significant impact on sorghum yield and irrigation requirements, but the impact of planting density was negligible. Editor's note: This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.

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Section: Resultssupporting

confidence: 92%

Simulating Soil Water Content, Evapotranspiration, and Yield of Variably Irrigated Grain Sorghum Using AquaCrop

Masasi

Taghvaeian

Gowda

et al. 2019

J American Water Resour Assoc

Self Cite

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“…In most studies, hydrologic models were calibrated for streamflow using measured data at the watershed outlet [4]. A limited number of studies have used measured evapotranspiration (ET) for calibrating hydrologic models [5][6][7]. According to an assessment of 257 process-based, watershed modeling papers published between 1992 and 2010, auto-irrigation functions for simulations of irrigation, ET, and crop responses using quality, long-term field observations.…”

Section: Introductionmentioning

confidence: 99%

Assessing the Efficacy of the SWAT Auto-Irrigation Function to Simulate Irrigation, Evapotranspiration, and Crop Response to Management Strategies of the Texas High Plains

Chen

Marek

Marek³

et al. 2017

Water

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Abstract:In the semi-arid Texas High Plains, the underlying Ogallala Aquifer is experiencing continuing decline due to long-term pumping for irrigation with limited recharge. Accurate simulation of irrigation and other associated water balance components are critical for meaningful evaluation of the effects of irrigation management strategies. Modelers often employ auto-irrigation functions within models such as the Soil and Water Assessment Tool (SWAT). However, some studies have raised concerns as to whether the function is able to adequately simulate representative irrigation practices. In this study, observations of climate, irrigation, evapotranspiration (ET), leaf area index (LAI), and crop yield derived from an irrigated lysimeter field at the USDA-ARS Conservation and Production Research Laboratory at Bushland, Texas were used to evaluate the efficacy of the SWAT auto-irrigation functions. Results indicated good agreement between simulated and observed daily ET during both model calibration (2001-2005) and validation (2006-2010) periods for the baseline scenario (Nash-Sutcliffe efficiency; NSE ≥ 0.80). The auto-irrigation scenarios resulted in reasonable ET simulations under all the thresholds of soil water deficit (SWD) triggers as indicated by NSE values > 0.5. However, the auto-irrigation function did not adequately represent field practices, due to the continuation of irrigation after crop maturity and excessive irrigation when SWD triggers were less than the static irrigation amount.

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“…These patterns of poor model performance that coincided with the crop growing seasons (i.e., mainly from June until end of October) highlight the importance of proper plant growth simulations in predicting ET as the crop characteristics impact ET (Marek et al. ; Talebizadeh, Moriasi, Gowda, et al. ).…”

Section: Resultsmentioning

confidence: 99%

A Parallel Computation Tool to Enable Dynamic Sensitivity and Model Performance Analysis of APEX: Evapotranspiration Modeling

Talebizadeh

Moriasi

Steiner

et al. 2019

J American Water Resour Assoc

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Global sensitivity analysis can be used for assessing the relative importance of model parameters on model outputs. The sensitivity of parameters usually indicates a temporal variation due to variation in the environmental conditions (e.g., variation in weather or plant growth). In addition, the size of averaging window by which the outputs of a model are aggregated or averaged may impact parameter sensitivities. In this study, temporal variation of parameters sensitives, model performance, as well as the impact of the size of time‐averaging window on evapotranspiration (ET) prediction using the Agricultural Policy/Environmental eXtender (APEX) model are investigated. To achieve these goals, an open‐source package named PARAPEX was developed in R and used to perform dynamic sensitivity and model performance analysis of APEX using parallel computation. PARAPEX reduced the computation time from 5,939 to 379 s (using 20 and 1 computation nodes, respectively). The sensitivity analysis results indicated the parameters accounting for the reducing effect of plant cover on evaporation from the soil surface, the effect of soil on the plant root growth, and the effect of cycling and transformation dynamics of organic matter at the top soil layer as the top sensitive parameters based on the mean daily simulated ET and the Nash–Sutcliffe model performance measure. The dynamic performance analysis indicated poor ET predictions by APEX during the growing seasons. Editor's note: This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.

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Estimating Evapotranspiration for Dryland Cropping Systems in the Semiarid Texas High Plains Using SWAT

Cited by 33 publications

References 28 publications

Simulating Soil Water Content, Evapotranspiration, and Yield of Variably Irrigated Grain Sorghum Using AquaCrop

Simulating Soil Water Content, Evapotranspiration, and Yield of Variably Irrigated Grain Sorghum Using AquaCrop

Assessing the Efficacy of the SWAT Auto-Irrigation Function to Simulate Irrigation, Evapotranspiration, and Crop Response to Management Strategies of the Texas High Plains

A Parallel Computation Tool to Enable Dynamic Sensitivity and Model Performance Analysis of APEX: Evapotranspiration Modeling

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