An approach for global sensitivity analysis of a complex environmental model to spatial inputs and parameters: A case study of an agro-hydrological model

A methodology is presented to assess the sensitivity of a complex model involved in integrated assessment and modeling approaches to spatial factors. The application considers the spatially-distributed agro-hydrological model TNT2, and its sensitivity to soil characteristics and their spatial distribution (soil pattern). The final goal is to identify soil input data that require more accurate description (measurement) and the relevant spatial resolution for soil information. Based on methods commonly used for non-spatially-distributed models (Morris method and a fractional factorial design with ANOVA), the proposed approach is innovative in the way that spatial input factors are considered in the global sensitivity analysis. The global sensitivity analysis is performed in three steps (i) screening among soil input data to identify those that most affect model outputs, (ii) quantifying the sensitivity of TNT2 to the dominant soil input factors and their interactions when considering a single soil and (iii) incorporating the soil pattern into the global sensitivity as an explicit input factor. The results indicate differences in the hierarchy of influential input factors between the screening and quantitative methods. The model's low sensitivity to spatial patterns provides recommendations for further field sampling campaigns. The hierarchical approach developed in this paper is based on sensitivity analysis methods with relatively low computational demand. The approach is generic and applicable to any complex spatial model.