A global sensitivity analysis approach for identifying critical sources of uncertainty in non-identifiable, spatially distributed environmental models: A holistic analysis applied to SWAT for input datasets and model parameters. (May 2020)

• Record Type: Journal Article
• Authors: Koo, Hyeongmo; Chen, Min; Jakeman, Anthony J.; Zhang, Fengyuan
• Is Part Of: Environmental modelling & software. Volume 127(2020)
• Publication Date: 2020-05
• Subjects: Uncertainty -- Sensitivity analysis -- Water quality -- SWAT -- Watershed delineation -- Hydrological response unit -- Identifiability; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2020.104676
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstracts: Environmental models have a key role to play in understanding complex environmental phenomena in space and time. Although their inherent uncertainty and non-identifiability are being increasingly recognized with the development and application of various methods, a more holistic analysis of all sources of model uncertainty is warranted. This paper addresses sources of uncertainty from various types of input datasets and model parameters, including those related to model structure assumptions, using a Soil and Water Assessment Tool (SWAT) application for the Minjiang River watershed, China. The holistic uncertainty sources in the SWAT application are summarized, and a sensitivity analysis (SA) is applied to examine the relative importance of the uncertainty sources influencing average streamflow and the load of nitrate. The analysis reveals that uncertainties related to the stream network precision and certain SWAT parameters are the most critical factors. Furthermore, building upon our SA framework to consider uncertainty sources more holistically would provide a good starting point for subsequent SA of spatially distributed environmental models in general. Highlights: A holistic sensitivity analysis, including model structure uncertainty, is conducted for a spatially distributed model. A sensitivity analysis examines the relative importance of the uncertainty sources using a SWAT application. The uncertainties in the stream network precision and certain SWAT parameters are critical.