Enabling dynamic emulation of high-dimensional model outputs: Demonstration for Mexico City groundwater management. (January 2022)

• Record Type: Journal Article
• Authors: Tracy, Jacob; Chang, Won; St George Freeman, Sarah; Brown, Casey; Palma Nava, Adriana; Ray, Patrick
• Is Part Of: Environmental modelling & software. Volume 147(2022)
• Publication Date: 2022-01
• Subjects: Water resources planning -- Process-based models -- Emulation modeling -- Spatiotemporal emulation -- High-dimensional emulation -- Dynamic emulation; 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.2021.105238
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Model emulation has become an integral tool in scenario analysis, risk assessment, and calibration of environmental models. Of particular interest is dynamic emulation – the approximation of model outputs from inputs or processes that vary in time. This paper presents a method for data-driven dynamic emulation of high-dimensional model outputs that overcomes the logistical challenges from assumptions in traditional multivariate statistics concerning output covariance. In this method, outputs are subjected to principal component analysis, and Gaussian random fields are fit along new orthogonal axes to accommodate spatial heterogeneity and serial correlation. The technique is demonstrated on a regional groundwater model of metropolitan Mexico City, where it successfully emulates spatial and temporal dynamics of land subsidence and aquifer level fluctuation resulting from two management scenarios. In doing so, we introduce methodological advances to emulation techniques, which facilitate the use of models with high-dimensional outputs in computationally expensive planning and optimization applications. Highlights: Novel emulation of model outputs overcomes assumptions in traditional multivariate statistics concerning output covariance. Maintains the same spatiotemporal detail of original model. Case study of groundwater management and land subsidence in Mexico City.