TY - JOUR
T1 - Long-term spatial and temporal maize and soybean evapotranspiration trends derived from ground-based and satellite-based datasets over the great plains
AU - Kukal, Meetpal
AU - Irmak, Suat
AU - Kilic, Ayse
N1 - Publisher Copyright:
©2017 American Society of Civil Engineers.
PY - 2017/9/1
Y1 - 2017/9/1
N2 - Estimation of evapotranspiration (ET) from any given crop is essential for agricultural water consumption analyses, hydrologic modeling, understanding vegetation response to climatic changes, and related studies. Even though it is a simplification of the complex physiological and surface energy balance relationships in accurately estimating ET, crop coefficient (Kc)-based estimation of crop ET is one of the widely used approaches. This study developed and evaluated crop-specific (maize and soybean) Kc versus normalized difference vegetation index (NDVI) relationships using satellite imagery data and observed crop ET fluxes. These models were used to estimate spatiotemporal Kc of maize and soybean using multiplatform satellite imagery to aid in computation of crop ET across these scales. Crop ET was characterized spatially (across the entire Great Plains) and temporally (1982-2013) and direction and magnitudes of trends were quantified. The study area comprises of 9 states and 834 counties, representing a total land area of 2,307,410 km2, which is approximately 30% of the terrestrial area of the United States. The coefficient of determination (R2), Nash-Sutcliffe modeling efficiency (NSE), and root mean square difference (RMSD) for Kc-NDVI models were 0.93, 87.5%, and 0.172, respectively, for maize and 0.76, 75%, and 0.20 for soybean, respectively, which denotes acceptable accuracy. Monthly and growing season maize and soybean ET was computed on a county basis for the study period using the developed monthly Kc values and reference ET, which was determined across 800 sites in the region. Maize ET in the region varied from 242 mm in Park County, Wyoming, to 942 mm in San Jacinto County, Texas. Soybean ET ranged from a minimum of 367 mm in Baca County, Colorado, to a maximum of 753 mm in Creek County, Oklahoma. The regional average magnitude of growing season maize and soybean ET was 651 and 564 mm, respectively. Spatial and temporal variability and trends in county-scale monthly and growing season maize and soybean ET were investigated for the period 1982 to 2013. For the majority of the maize and soybean growing counties, increasing trends in crop ET were detected, despite decreasing trends in reference ET. The significant positive trends in maize ET over the region ranged from 1.48 to 3.86 mm year-1, with an average of 2.65 mmyear-1. For soybean, the significant positive trends varied from 0.88 to 4.13 mmyear-1, with an average of 2.1 mmyear-1. The analyses presented in this study inspire the use of satellite-derived indices to monitor crop development and water use to evaluate regional magnitudes of spatial and temporal ET. Furthermore, the spatial and temporal trend analysis for county-scale crop ET can be instrumental to make informed assessments, decisions, and forecasts about agroecosystem water resources management policy in the Great Plains region by state and federal agencies, producers, and other water resources associated professionals.
AB - Estimation of evapotranspiration (ET) from any given crop is essential for agricultural water consumption analyses, hydrologic modeling, understanding vegetation response to climatic changes, and related studies. Even though it is a simplification of the complex physiological and surface energy balance relationships in accurately estimating ET, crop coefficient (Kc)-based estimation of crop ET is one of the widely used approaches. This study developed and evaluated crop-specific (maize and soybean) Kc versus normalized difference vegetation index (NDVI) relationships using satellite imagery data and observed crop ET fluxes. These models were used to estimate spatiotemporal Kc of maize and soybean using multiplatform satellite imagery to aid in computation of crop ET across these scales. Crop ET was characterized spatially (across the entire Great Plains) and temporally (1982-2013) and direction and magnitudes of trends were quantified. The study area comprises of 9 states and 834 counties, representing a total land area of 2,307,410 km2, which is approximately 30% of the terrestrial area of the United States. The coefficient of determination (R2), Nash-Sutcliffe modeling efficiency (NSE), and root mean square difference (RMSD) for Kc-NDVI models were 0.93, 87.5%, and 0.172, respectively, for maize and 0.76, 75%, and 0.20 for soybean, respectively, which denotes acceptable accuracy. Monthly and growing season maize and soybean ET was computed on a county basis for the study period using the developed monthly Kc values and reference ET, which was determined across 800 sites in the region. Maize ET in the region varied from 242 mm in Park County, Wyoming, to 942 mm in San Jacinto County, Texas. Soybean ET ranged from a minimum of 367 mm in Baca County, Colorado, to a maximum of 753 mm in Creek County, Oklahoma. The regional average magnitude of growing season maize and soybean ET was 651 and 564 mm, respectively. Spatial and temporal variability and trends in county-scale monthly and growing season maize and soybean ET were investigated for the period 1982 to 2013. For the majority of the maize and soybean growing counties, increasing trends in crop ET were detected, despite decreasing trends in reference ET. The significant positive trends in maize ET over the region ranged from 1.48 to 3.86 mm year-1, with an average of 2.65 mmyear-1. For soybean, the significant positive trends varied from 0.88 to 4.13 mmyear-1, with an average of 2.1 mmyear-1. The analyses presented in this study inspire the use of satellite-derived indices to monitor crop development and water use to evaluate regional magnitudes of spatial and temporal ET. Furthermore, the spatial and temporal trend analysis for county-scale crop ET can be instrumental to make informed assessments, decisions, and forecasts about agroecosystem water resources management policy in the Great Plains region by state and federal agencies, producers, and other water resources associated professionals.
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U2 - 10.1061/(ASCE)IR.1943-4774.0001212
DO - 10.1061/(ASCE)IR.1943-4774.0001212
M3 - Article
AN - SCOPUS:85021136881
SN - 0733-9437
VL - 143
JO - Journal of Irrigation and Drainage Engineering
JF - Journal of Irrigation and Drainage Engineering
IS - 9
M1 - 04017031
ER -