Skip to main content
ARS Home » Plains Area » Fort Collins, Colorado » Center for Agricultural Resources Research » Water Management and Systems Research » Research » Publications at this Location » Publication #330359
Title: Global sensitivity and uncertainty analysis of the nitrate leaching and crop yield simulation under different water and nitrogen management practices

Author
item LIANG, HAO - China Agricultural University
item QI, ZHIMING - McGill University - Canada
item DeJonge, Kendall
item HU, KELIN - China Agricultural University
item LI, BAOGUO - China Agricultural University

Submitted to: Journal of Environmental Quality
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/9/2017
Publication Date: 9/15/2017
Citation: Liang, H., Qi, Z., Dejonge, K.C., Hu, K., Li, B. 2017. Global sensitivity and uncertainty analysis of the nitrate leaching and crop yield simulation under different water and nitrogen management practices. Journal of Environmental Quality. 142(A):201–210, 2017.

Interpretive Summary: Complexity in input parameters of agricultural system models often leads to significant uncertainty when simulating dynamic processes such as nitrate leaching or crop yield. In order to assess the sensitivity and uncertainty of the modeling nitrate leaching and crop yield under different water and N management for a newly integrated WHCNS model (soil Water Heat Carbon Nitrogen Simulator), both the Morris screening method and Sobol’ variance-based method were employed in this study. The field experiment conducted in a desert oasis of Inner Mongolia, China, a factorial combination of standard and conservation levels of irrigation and N fertilization. Sensitivity analysis (SA) showed that nitrate leaching showed strong sensitivity to soil hydraulic and crop parameters, but generally low sensitivity to N transformation parameters. Based on Sobol’ SA, crop parameters accounted for up to 64% of nitrate leaching variability in some treatments. Overall, irrigation practice was the main factor influencing the sensitivity and uncertainty of nitrate leaching.

Technical Abstract: Agricultural system models have become important tools in studying water and nitrogen (N) dynamics, as well as crop growth, under different management practices. Complexity in input parameters often leads to significant uncertainty when simulating dynamic processes such as nitrate leaching or crop yield. In order to assess the sensitivity and uncertainty of the modeling nitrate leaching and crop yield under different water and N management for a newly integrated WHCNS model (Soil Water Heat Carbon Nitrogen Simulator), both the Morris screening method and Sobol’ variance-based method were employed in this study. The field experiment conducted in a desert oasis of Inner Mongolia, China, a factorial combination of standard (Istd, standard, 750 mm per season; Nstd, standard, 138 kg ha-118 ) and conservation (Icsv, conservation, 570 mm per season; Ncsv, conservation, 92 kg ha-119 ) levels of irrigation and N fertilization: IstdNstd, IstdNcsv, IcsvNstd and IcsvNcsv. Sensitivity analysis (SA) showed that nitrate leaching showed strong sensitivity to soil hydraulic and crop parameters, but generally low sensitivity to N transformation parameters. Based on Sobol’ SA, crop parameters accounted for 64.3%, 63.2%, 39.2% and 39.2% of nitrate leaching variability for the IstdNstd, IstdNcsv, IcsvNstd and IcsvNcsv treatments, 23 respectively. A greater interaction occurred between irrigation and N fertilization levels under Icsv than under Istd. Uncertainty analysis showed the average amount of nitrate leaching under Istd (135.3 N kg ha-125 ) to be 2.3-fold greater than under Icsv (58.0 N kg ha-126 ); however, the distributions of yield between the four treatment combinations did not show significant differences. Overall, irrigation practice was the main factor influencing the sensitivity and uncertainty of nitrate leaching. This knowledge can be used to guide model calibration. Model simulations of hypothetical irrigation/N fertilization regimes for the Alxa region suggest that there exists a great potential to improve water and N management in the area.