Global sensitivity analysis of a dynamic agroecosystem model under different irrigation treatments

Authors: DeJonge, Kendall; Ascough Ii, James; AHMADI, MEHDI - Colorado State University; ANDALES, ALLAN - Colorado State University; ARABI, MAZDAK - Colorado State University

Submitted to: Ecological Modeling
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/30/2012
Publication Date: 3/13/2012
Citation: DeJonge, K.C., Ascough II, J.C., Ahmadi, M., Andales, A.A., Arabi, M. 2012. Global sensitivity analysis of a dynamic agroecosystem model under different irrigation treatments. Ecological Modeling. 231(2012):113-125.

Interpretive Summary: Crop models provide a mechanism to evaluate various management methods without performing costly and time-consuming experiments. The CERES-Maize crop model has previously been shown to overestimate evapotranspiration (ET) for limited irrigation treatments (stress during vegetative stage). It is therefore desirable to quantify the effects of CERES-Maize input parameters on model output responses typically used for calibration and/or important in limited irrigation management, including vegetative growth, crop yield, and ET. A sensitivity analysis (SA) utilizing the Morris one-at-time screening and Sobol’ variance-based methods was performed on CERES-Maize v4.5 input parameters affecting water balance and crop growth including soil hydraulic properties, phenological growth properties, and radiation use efficiency. CERES-Maize output responses of interest for the SA included anthesis date, maturity date, leaf number per stem, maximum leaf area index, yield, and cumulative ET. The SA study utilized five years of multi-replicate field management data (both full and limited irrigation treatments) for each combination of random input parameters. The Morris screening SA method was used to eliminate insensitive parameters prior to performing the more computationally intensive Sobol’ method. Results comparing the Morris mean and the Sobol’ total sensitivity index showed very high correlation between the two. For the full irrigation treatment, CERES-Maize output responses were mostly sensitive to crop cultivar parameters. For the limited irrigation treatment, CERES-Maize leaf area index, yield, and ET output responses were highly influenced by soil lower limit and drained upper limit input parameters, which define water holding capacity. A new methodology for systematic calibration of CERES-Maize, based on the Morris and Sobol’ sensitivity indices for the two irrigation treatments, is proposed for future model evaluation as sensitivity differences between treatments indicates that existing CERES-Maize calibration procedures (typically based on non-stressed crops) may need to be reconsidered in cases of water stress.

Technical Abstract: Savings in consumptive use through limited or deficit irrigation in agriculture has become an increasingly viable source of additional water for places with high population growth such as the Colorado Front Range, USA. Crop models provide a mechanism to evaluate various management methods without performing costly and time-consuming experiments, e.g., field studies investigating irrigation scheduling and timing effects on crop growth. The CERES-Maize crop model has previously been shown to overestimate evapotranspiration (ET) for limited irrigation treatments (stress during vegetative stage). It is therefore desirable to quantify the effects of CERES-Maize input parameters on model output responses typically used for calibration and/or important in limited irrigation management, including vegetative growth, crop yield, and ET. A sensitivity analysis (SA) utilizing the Morris one-at-time screening and Sobol’ variance-based methods was performed on CERES-Maize v4.5 input parameters affecting water balance and crop growth including soil hydraulic properties, phenological growth properties, and radiation use efficiency. CERES-Maize output responses of interest for the SA included anthesis date, maturity date, leaf number per stem, maximum leaf area index, yield, and cumulative ET. The SA study utilized five years of multi-replicate field management data (both full and limited irrigation treatments) for each combination of random input parameters. The Morris screening SA method was used to eliminate insensitive parameters prior to performing the more computationally intensive Sobol’ method. Results comparing the Morris mean and the Sobol’ total sensitivity index showed very high correlation between the two, indicating that in this study the computationally cheaper Morris method could have been used as an effective indicator of input parameter sensitivity. For the full irrigation treatment, CERES-Maize output responses were mostly sensitive to crop cultivar parameters. For the limited irrigation treatment, CERES-Maize leaf area index, yield, and ET output responses were highly influenced by soil lower limit and drained upper limit input parameters, which define water holding capacity. There was also a greater amount of interaction between input parameters for the limited irrigation treatment than for full irrigation. There were no differences in sensitivity between treatments for simulated leaf number per stem, a model response that should be altered in future revisions as field observations show that water stress can play a role in leaf count. A new methodology for systematic calibration of CERES-Maize, based on the Morris and Sobol’ sensitivity indices for the two irrigation treatments, is proposed for future model evaluation as sensitivity differences between treatments indicates that existing CERES-Maize calibration procedures (typically based on non-stressed crops) may need to be reconsidered in cases of water stress.