TY - JOUR
T1 - Energy balance in the DSSAT-CSM-CROPGRO model
AU - Cuadra, Santiago V.
AU - Kimball, Bruce A.
AU - Boote, Kenneth J.
AU - Suyker, Andrew E.
AU - Pickering, Nigel
N1 - Funding Information:
We gratefully acknowledge The Nature Conservancy of Brasil (TNC), the Gordon and Betty Moore Foundation, and the DSSAT Foundation for facilitating and funding support of this work. We also appreciate the help of Cheryl Porter, Patricia Moreno, Willingthon Pavan, Kelly Thorp, and Jeffrey White. We also appreciate access to the comprehensive dataset from Mead, Nebraska, USA, which was collected by the following scientists: Shashi B. Verma, Achim Dobermann, Kenneth G. Cassman, Daniel T. Walters, Johannes M. Knops, Timothy J. Arkebauer, George G. Burba, Brigid Amos, Haishum Yang, Daniel Ginting, Kenneth G. Hubbard, Anatoly A. Gitelson, and Elizabeth A. Walter-Shea. The dataset was collected with support from the DOE-Office of Science (BER: Grant Nos. DE-FG03–00ER62996 and DE-FG02–03ER63639), DOE-EPSCoR (Grant No. DE-FG02–00ER45827), and the Cooperative State Research, Education, and Extension Service, US Department of Agriculture (Agreement No. 2001–38700–11092).
Funding Information:
We gratefully acknowledge The Nature Conservancy of Brasil (TNC), the Gordon and Betty Moore Foundation, and the DSSAT Foundation for facilitating and funding support of this work. We also appreciate the help of Cheryl Porter, Patricia Moreno, Willingthon Pavan, Kelly Thorp, and Jeffrey White. We also appreciate access to the comprehensive dataset from Mead, Nebraska, USA, which was collected by the following scientists: Shashi B. Verma, Achim Dobermann, Kenneth G. Cassman, Daniel T. Walters, Johannes M. Knops, Timothy J. Arkebauer, George G. Burba, Brigid Amos, Haishum Yang, Daniel Ginting, Kenneth G. Hubbard, Anatoly A. Gitelson, and Elizabeth A. Walter-Shea. The dataset was collected with support from the DOE-Office of Science (BER: Grant Nos. DE-FG03?00ER62996 and DE-FG02?03ER63639), DOE-EPSCoR (Grant No. DE-FG02?00ER45827), and the Cooperative State Research, Education, and Extension Service, US Department of Agriculture (Agreement No. 2001?38700?11092).
Publisher Copyright:
© 2020
PY - 2021/2/15
Y1 - 2021/2/15
N2 - One potential way to improve crop growth models is for the models to predict energy balance and evapotranspiration (ET) from first principles, thus serving as a check on “engineered” ET methodology. In this paper, we present new implementations and the results of an energy balance model (EBL) developed by Jagtap and Jones (1989) and then implemented in DSSAT's CROPGRO (CG-EBL) model by Pickering et al. (1995) as a linked energy balance-photosynthesis model that has not been field-tested until now. The energy balance code computes evapotranspiration and other energy balance components, as well as a canopy air temperature, based on three sources (sunlit leaves, shaded leaves, soil surface). Model performance was evaluated with measured biomass and energy fluxes from two sites in Nebraska, namely, the US-Ne2 irrigated maize-soybean rotation field and the US-Ne3 rainfed maize-soybean rotation field, which are part of the Ameriflux eddy covariance network (https://ameriflux.lbl.gov/sites). After implementing new aerodynamic resistances and the stomatal conductance model of the Ball–Berry–Leuning, crop growth, evapotranspiration and soil temperature were simulated well by the EBL model. The EBL improved ET predictions slightly over the often-used FAO56 method [Penman–Monteith (Allen et al., 1998)] for 4 of the 5 years evaluated for both irrigated and rainfed conditions. Further, a significant improvement was achieved using EBL for the simulation of soil temperature at the various depths compared to STEMP, the original subroutine in DSSAT for simulating soil temperature. Compared to the other available DSSAT methods, the EBL explicitly simulates the impacts of crop morphology, physiology and management on the crop's environment and energy and mass exchange, which in turn directly affect the water use and irrigation requirements, phenology, photosynthesis, growth, sterility, and yield of the crop.
AB - One potential way to improve crop growth models is for the models to predict energy balance and evapotranspiration (ET) from first principles, thus serving as a check on “engineered” ET methodology. In this paper, we present new implementations and the results of an energy balance model (EBL) developed by Jagtap and Jones (1989) and then implemented in DSSAT's CROPGRO (CG-EBL) model by Pickering et al. (1995) as a linked energy balance-photosynthesis model that has not been field-tested until now. The energy balance code computes evapotranspiration and other energy balance components, as well as a canopy air temperature, based on three sources (sunlit leaves, shaded leaves, soil surface). Model performance was evaluated with measured biomass and energy fluxes from two sites in Nebraska, namely, the US-Ne2 irrigated maize-soybean rotation field and the US-Ne3 rainfed maize-soybean rotation field, which are part of the Ameriflux eddy covariance network (https://ameriflux.lbl.gov/sites). After implementing new aerodynamic resistances and the stomatal conductance model of the Ball–Berry–Leuning, crop growth, evapotranspiration and soil temperature were simulated well by the EBL model. The EBL improved ET predictions slightly over the often-used FAO56 method [Penman–Monteith (Allen et al., 1998)] for 4 of the 5 years evaluated for both irrigated and rainfed conditions. Further, a significant improvement was achieved using EBL for the simulation of soil temperature at the various depths compared to STEMP, the original subroutine in DSSAT for simulating soil temperature. Compared to the other available DSSAT methods, the EBL explicitly simulates the impacts of crop morphology, physiology and management on the crop's environment and energy and mass exchange, which in turn directly affect the water use and irrigation requirements, phenology, photosynthesis, growth, sterility, and yield of the crop.
KW - CROPGRO
KW - Canopy temperature
KW - DSSAT
KW - Evapotranspiration
KW - Leaf temperature
KW - Soil temperature
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U2 - 10.1016/j.agrformet.2020.108241
DO - 10.1016/j.agrformet.2020.108241
M3 - Article
AN - SCOPUS:85096020624
VL - 297
JO - Agricultural and Forest Meteorology
JF - Agricultural and Forest Meteorology
SN - 0168-1923
M1 - 108241
ER -