Uncertainty analysis of model inputs in riverine water temperature simulations

Babak Abdi; Omid Bozorg-Haddad; Xuefeng Chu

doi:10.1038/s41598-021-99371-0

Uncertainty analysis of model inputs in riverine water temperature simulations

Sci Rep. 2021 Oct 7;11(1):19908. doi: 10.1038/s41598-021-99371-0.

Authors

Babak Abdi¹, Omid Bozorg-Haddad², Xuefeng Chu³

Affiliations

¹ Department of Irrigation and Reclamation Engineering, Faculty of Agricultural Engineering and Technology, College of Agriculture and Natural Resources, University of Tehran, Karaj, Tehran, Iran.
² Department of Irrigation and Reclamation Engineering, Faculty of Agricultural Engineering and Technology, College of Agriculture and Natural Resources, University of Tehran, Karaj, Tehran, Iran. obhaddad@ut.ac.ir.
³ Department of Civil and Environmental Engineering, North Dakota State University, Dept 2470, Fargo, ND, 58108-6050, USA.

Abstract

Simulation models are often affected by uncertainties that impress the modeling results. One of the important types of uncertainties is associated with the model input data. The main objective of this study is to investigate the uncertainties of inputs of the Heat-Flux (HFLUX) model. To do so, the Shuffled Complex Evolution Metropolis Uncertainty Algorithm (SCEM-UA), a Monte Carlo Markov Chain (MCMC) based method, is employed for the first time to assess the uncertainties of model inputs in riverine water temperature simulations. The performance of the SCEM-UA algorithm is further evaluated. In the application, the histograms of the selected inputs of the HFLUX model including the stream width, stream depth, percentage of shade, and streamflow were created and their uncertainties were analyzed. Comparison of the observed data and the simulations demonstrated the capability of the SCEM-UA algorithm in the assessment of the uncertainties associated with the model input data (the maximum relative error was 15%).

Publication types

Research Support, Non-U.S. Gov't