Parallel multi-objective calibration of a component-based river temperature model. (June 2019)

• Record Type: Journal Article
• Authors: Buahin, Caleb A.; Horsburgh, Jeffery S.; Neilson, Bethany T.
• Is Part Of: Environmental modelling & software. Volume 116(2019)
• Page Start: 57
• Page End: 71
• Publication Date: 2019-06
• Subjects: Component-based modeling -- Model calibration -- High performance computing -- River temperature modeling -- OpenMI -- HydroCouple; 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.2019.02.012
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Many recent modeling efforts have employed component-based modeling frameworks to take advantage of the flexibility they provide in representing systems more holistically. Despite the benefits that are driving this adoption, conducting model parameter estimation, uncertainty analysis, sensitivity assessment, and other simulations of this nature within component-based modeling frameworks has remained unexplored. Using a multi-objective calibration of a component-based river temperature model, we illustrate how the component cloning and parallel model execution interfaces we have implemented in the HydroCouple framework support such simulations. The river temperature model calibration application we present involves a heavily human mediated 13.6 km section of the Logan River in Utah, USA with limited information regarding variable inflows. Due to the flexibility in the modeling and calibration framework, results from the calibration effort were successful with root mean square errors of 0.4–0.7 °C and provided insights on mechanisms controlling river temperatures. Highlights: The calibration of a component-based river temperature model is presented. Simulations are aided by component cloning and a parallel execution framework. Computational efficiency is improved as more computing cores are used. Approach presented offers a path for component-based model sensitivity analysis.