Field-scale calibration of crop-yield parameters in the Soil and Water Assessment Tool (SWAT)

Sinnathamby, Sumathy; Douglas-Mankin, Kyle R.; Craige, Collin

doi:10.1016/j.agwat.2016.10.024

Cited by 66 publications

(36 citation statements)

References 41 publications

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“…The SWAT model [11] was used to develop a hydrological model of the Fort Cobb study area, consisting of the Cobb Creek and Five Mile Creek sub-watersheds. SWAT is a hydrological modeling tool widely used to simulate the long-term effects of changes in climate, land use management, and agricultural practices [17,25,32,33]. The 10 m United States Geological Survey (USGS) Digital Elevation Model (DEM) was used to delineate the watershed boundary using the location of the USGS gauge station at Cobb Creek near Eakley (07325800) as the watershed outlet.…”

Section: Hydrological Modelmentioning

confidence: 99%

Projected Climate Could Increase Water Yield and Cotton Yield but Decrease Winter Wheat and Sorghum Yield in an Agricultural Watershed in Oklahoma

Gharibdousti

Kharel

Miller

et al. 2019

Water

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Climate change impacts on agricultural watersheds are highly variable and uncertain across regions. This study estimated the potential impacts of the projected precipitation and temperature based on the downscaled Coupled Model Intercomparison Project 5 (CMIP-5) on hydrology and crop yield of a rural watershed in Oklahoma, USA. The Soil and Water Assessment Tool was used to model the watershed with 43 sub-basins and 15,217 combinations of land use, land cover, soil, and slope. The model was driven by the observed climate in the watershed and was first calibrated and validated against the monthly observed streamflow. Three statistical matrices, coefficient of determination (R 2 ), Nash-Sutcliffe efficiency (NSE), and percentage bias (PB), were used to gauge the model performance with satisfactory values of R 2 = 0.64, NS = 0.61, and PB = +5% in the calibration period, and R 2 = 0.79, NSE = 0.62, and PB = −15% in the validation period for streamflow. The model parameterization for the yields of cotton (PB = −4.5%), grain sorghum (PB = −27.3%), and winter wheat (PB = −6.0%) resulted in an acceptable model performance. The CMIP-5 ensemble of three General Circulation Models under three Representative Concentration Pathways for the 2016-2040 period indicated an increase in both precipitation (+1.5%) and temperature (+1.8 • C) in the study area. This changed climate resulted in decreased evapotranspiration (−3.7%), increased water yield (23.9%), decreased wheat yield (−5.2%), decreased grain sorghum yield (−9.9%), and increased cotton yield (+54.2%) compared to the historical climate. The projected increase in water yield might provide opportunities for groundwater recharge and additional water to meet future water demand in the region. The projected decrease in winter wheat yield-the major crop in the state-due to climate change, may require attention for ways to mitigate these effects.

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Section: Hydrological Modelmentioning

confidence: 99%

Projected Climate Could Increase Water Yield and Cotton Yield but Decrease Winter Wheat and Sorghum Yield in an Agricultural Watershed in Oklahoma

Gharibdousti

Kharel

Miller

et al. 2019

Water

View full text Add to dashboard Cite

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“…; Sinnathamby et al. ). SWAT requires meteorological input data including precipitation, temperature, and solar radiation as well as soils data, land use/management information, and elevation data.…”

Section: Methodsmentioning

confidence: 98%

“…SWAT, jointly developed by USDA-ARS and Texas A&M AgriLife Research, is a watershedscale, physically based model incorporating weather, soil, land cover, and land management data to simulate surface and subsurface hydrology, various chemical and sediment fluxes, and crop development and yields (Arnold et al 1998). SWAT, one of the most commonly used and well supported modeling systems, has been widely used to predict the environmental impact of land use, land management practices, crop management, and climate change (Douglas-Mankin et al 2010;Abbaspour et al 2015;Rocha et al 2015;Wagena et al 2016;Ashraf-Vaghefi et al 2017;Sinnathamby et al 2017). SWAT requires meteorological input data including precipitation, temperature, and solar radiation as well as soils data, land use/management information, and elevation data.…”

Section: Swat-vsa Modelmentioning

confidence: 99%

Meeting Water Quality Goals under Climate Change in Chesapeake Bay Watershed, USA

Bosch

Wagena

Ross

et al. 2018

J American Water Resour Assoc

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Climate change may increase precipitation, temperatures, and pollution loading and necessitate additional measures and costs to achieve water quality goals. We used two climate change models and the mean of the ensemble of seven climate models (Ensemble Mean), a yield prediction model (Soil and Water Assessment Tool‐Variable Source Area), and a farm economic model to estimate how climate change would affect yields and the costs of reducing nitrogen (N) loading in an agricultural subbasin of the Chesapeake Bay. We estimated costs of meeting water quality goals based on the reduction in farm net returns from limits on N loadings under historical and future climate scenarios. Estimated costs of meeting water quality goals increase under future climate for one of the two climate models and for the Ensemble Mean. Major reasons for increased costs are higher predicted N loading from crops and higher N loading reductions to be achieved under future climate. The farm meets N limits by eliminating wheat and reducing corn and soybean production as well as increased use of best management practices (BMPs) including Conservation Reserve Program. Researchers should analyze effects of climate change on the costs of meeting water quality goals using multiple climate change prediction models and considering possible crop substitutions as well as crop and livestock BMPs. Further research should consider how commodity market reactions to producers’ choices under climate change affect costs of meeting water quality goals.

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“…For hydrological models, only the streamflow and the water balance are usually analyzed based on gauging station records and previous studies [8]. For agronomic models, biomass production and crop yield help to calibrate the model [104]. This study combines hydrological and agronomic calibration approaches in order to improve the model estimation thanks to multiple datasets with different scales and time resolutions.…”

Section: Yield and Fertilizationmentioning

confidence: 99%

Hydrological Alteration Index as an Indicator of the Calibration Complexity of Water Quantity and Quality Modeling in the Context of Global Change

Cakir

Raimonet

Sauvage

et al. 2019

Water

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Modeling is a useful way to understand human and climate change impacts on the water resources of agricultural watersheds. Calibration and validation methodologies are crucial in forecasting assessments. This study explores the best calibration methodology depending on the level of hydrological alteration due to human-derived stressors. The Soil and Water Assessment Tool (SWAT) model is used to evaluate hydrology in South-West Europe in a context of intensive agriculture and water scarcity. The Index of Hydrological Alteration (IHA) is calculated using discharge observation data. A comparison of two SWAT calibration methodologies are done; a conventional calibration (CC) based on recorded in-stream water quality and quantity and an additional calibration (AC) adding crop managements practices. Even if the water quality and quantity trends are similar between CC and AC, water balance, irrigation and crop yields are different. In the context of rainfall decrease, water yield decreases in both CC and AC, while crop productions present opposite trends (+33% in CC and −31% in AC). Hydrological performance between CC and AC is correlated to IHA: When the level of IHA is under 80%, AC methodology is necessary. The combination of both calibrations appears essential to better constrain the model and to forecast the impact of climate change or anthropogenic influences on water resources.

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Field-scale calibration of crop-yield parameters in the Soil and Water Assessment Tool (SWAT)

Cited by 66 publications

References 41 publications

Projected Climate Could Increase Water Yield and Cotton Yield but Decrease Winter Wheat and Sorghum Yield in an Agricultural Watershed in Oklahoma

Projected Climate Could Increase Water Yield and Cotton Yield but Decrease Winter Wheat and Sorghum Yield in an Agricultural Watershed in Oklahoma

Meeting Water Quality Goals under Climate Change in Chesapeake Bay Watershed, USA

Hydrological Alteration Index as an Indicator of the Calibration Complexity of Water Quantity and Quality Modeling in the Context of Global Change

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