Comparison of evapotranspiration methods in the DSSAT Cropping System Model: I. Global sensitivity analysis

• Published in: Computers and electronics in agriculture 2020-10, Vol.177, p.105658, Article 105658
• Main Authors: Thorp, K.R., DeJonge, K.C., Marek, G.W., Evett, S.R.
• Format: Article
• Language: English
• Subjects: Algorithms; Arid lands; Aridity; Cotton; Decision support systems; Evapotranspiration; Irrigation; Mathematical models; Modeling; Order parameters; Parameter identification; Parameter sensitivity; Semi arid environments; Sensitivity; Sensitivity analysis; Simulation; Sobol; Soil conditions; Soil water; Soils; Water; Water management
• ISSN: 0168-1699; 1872-7107
• DOI: 10.1016/j.compag.2020.105658

•A global sensitivity analysis evaluated 24 model outputs with respect to 37 inputs.•Model sensitivity was evaluated among six evapotranspiration (ET) methods.•Nearly half of the tested input parameters did not influence any model output.•Choice of soil water evaporation method led to large sensitivity differences.•The results informed a companion study on ET method performance. Global sensitivity analysis (GSA) is useful for evaluating the responsiveness of agroecosystem models to input parameter adjustments. Evaluations of model sensitivity for diverse water status conditions and evapotranspiration (ET) algorithms will facilitate better use of models to provide water management recommendations. The objective of this study was to conduct a GSA to identify influential parameters in the Decision Support System for Agrotechnology Transfer (DSSAT) Cropping System Model (CSM), specifically using the CROPGRO-Cotton module with data from cotton field studies conducted in 2000, 2001, and 2008 at Bushland, Texas. The field studies tested fully-irrigated, deficit-irrigated, and dryland cotton production in a semi-arid environment. Using high performance computing resources, a GSA was conducted to evaluate the sensitivity of 24 model outputs with respect to 37 model input parameters. The GSA was conducted for six different ET methodologies available in the model. With first-order sensitivity indices 0.05, eleven were cultivar parameters that controlled crop development and growth, and five were soil parameters that specified initial soil water conditions, soil water limits, drainage rate, and root growth characteristics. The influences of another soil parameter and one ET parameter were relevant only for the ET methods that required them. Large differences in sensitivity indices were found based on the choice between two soil water evaporation methods. In addition to providing insights for other applications of this model, the results specifically informed further efforts to evaluate the model using measured data from the Bushland cotton studies to compare performance among the six ET methods, as reported in a companion paper.