TY - JOUR
T1 - Comparison of simulated nitrogen management strategies using DRAINMOD-DSSAT and RZWQM2
AU - Singh, Shailendra
AU - Negm, Lamyaa
AU - Jeong, Hanseok
AU - Cooke, Richard
AU - Bhattarai, Rabin
N1 - This work was supported by the National Institute of Food and Agriculture , U.S. Department of Agriculture, Hatch project ( ILLU-741-337 ) and the Dudley Smith Initiative in the College of Agricultural, Consumer, and Environmental Sciences at the University of Illinois at Urbana-Champaign, the Illinois Nutrient Research and Education Council ( NREC 27-16 UI ). The data used in this study was the contribution of Illinois Agricultural Experiment Station, the University of Illinois at Urbana-Champaign as a part of Project 10-309 and Southern Regional Research Project S-273 (formerly S-249). Supported in part with funds from USDA-CSREES under special projects 91-EHUA-1-0040 and 95-34214-2266 (Purdue sub-contract 590-1145-2417-01). Besides, this and related work are supported with funds from the Council on Food and Agricultural Research. The authors have no conflicts of interest to declare.
This work was supported by the National Institute of Food and Agriculture, U.S. Department of Agriculture, Hatch project (ILLU-741-337) and the Dudley Smith Initiative in the College of Agricultural, Consumer, and Environmental Sciences at the University of Illinois at Urbana-Champaign, the Illinois Nutrient Research and Education Council (NREC 27-16 UI). The data used in this study was the contribution of Illinois Agricultural Experiment Station, the University of Illinois at Urbana-Champaign as a part of Project 10-309 and Southern Regional Research Project S-273 (formerly S-249). Supported in part with funds from USDA-CSREES under special projects 91-EHUA-1-0040 and 95-34214-2266 (Purdue sub-contract 590-1145-2417-01). Besides, this and related work are supported with funds from the Council on Food and Agricultural Research. The authors have no conflicts of interest to declare.
PY - 2022/5/31
Y1 - 2022/5/31
N2 - Agroecosystem models provide valuable insights into agricultural management decisions and can serve as a useful tool to quantify the effects of management practices under varying conditions where field experimentations are impractical. We evaluated a newly integrated comprehensive model, DRAINMOD-DSSAT, for hydrology, nitrogen (N) dynamics, and crop yield using eight years (1993–2000) of measured data from a no-tilled subsurface-drained, corn-soybean agricultural system near Danville, Illinois. The model satisfactorily predicted drainage flow and NO3-N losses with Nash-Sutcliffe efficiency (NSE), the ratio of the root mean squared error to the standard deviation (RSR), and percent bias (PBIAS) of 0.68 and 0.60, 0.56 and 0.63, and − 11.6% and − 2.2%, respectively, and crop yield with nRMSE, PBIAS and index of agreement (d) of 8.4%, − 0.6%, and 1, respectively. For the same experimental dataset, the performance comparison of DRAINMOD-DSSAT to Root Zone Water Quality Model (RZWQM2) demonstrated that the two models were most different in their simulation of N loss through seepage and denitrification. Further, we used DRAINMOD-DSSAT to simulate the effects of management practices (N application rates and timings) on NO3-N losses and crop yield and compared them with RZWQM2 simulated results. The results showed that both models provided the same conclusion on the effects of N management strategy on NO3-N losses and crop yield, but they differ in quantity. This study supports being cautious in using only one model to conclude the quantification of the effectiveness of particular agricultural management practices.
AB - Agroecosystem models provide valuable insights into agricultural management decisions and can serve as a useful tool to quantify the effects of management practices under varying conditions where field experimentations are impractical. We evaluated a newly integrated comprehensive model, DRAINMOD-DSSAT, for hydrology, nitrogen (N) dynamics, and crop yield using eight years (1993–2000) of measured data from a no-tilled subsurface-drained, corn-soybean agricultural system near Danville, Illinois. The model satisfactorily predicted drainage flow and NO3-N losses with Nash-Sutcliffe efficiency (NSE), the ratio of the root mean squared error to the standard deviation (RSR), and percent bias (PBIAS) of 0.68 and 0.60, 0.56 and 0.63, and − 11.6% and − 2.2%, respectively, and crop yield with nRMSE, PBIAS and index of agreement (d) of 8.4%, − 0.6%, and 1, respectively. For the same experimental dataset, the performance comparison of DRAINMOD-DSSAT to Root Zone Water Quality Model (RZWQM2) demonstrated that the two models were most different in their simulation of N loss through seepage and denitrification. Further, we used DRAINMOD-DSSAT to simulate the effects of management practices (N application rates and timings) on NO3-N losses and crop yield and compared them with RZWQM2 simulated results. The results showed that both models provided the same conclusion on the effects of N management strategy on NO3-N losses and crop yield, but they differ in quantity. This study supports being cautious in using only one model to conclude the quantification of the effectiveness of particular agricultural management practices.
KW - Crop yield
KW - Management
KW - Modeling
KW - Nitrogen
KW - Subsurface drainage
KW - Water quality
UR - http://www.scopus.com/inward/record.url?scp=85126397151&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85126397151&partnerID=8YFLogxK
U2 - 10.1016/j.agwat.2022.107597
DO - 10.1016/j.agwat.2022.107597
M3 - Article
AN - SCOPUS:85126397151
SN - 0378-3774
VL - 266
JO - Agricultural Water Management
JF - Agricultural Water Management
M1 - 107597
ER -