RETRACTED ARTICLE: Uncertainty Analysis of a Continuous Hydrological Model Using DREAM-ZS Algorithm
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RESEARCH PAPER
Uncertainty Analysis of a Continuous Hydrological Model Using DREAM‑ZS Algorithm Amirhosein Aghakhani Afshar1 · Yousef Hassanzadeh1 · Mohsen Pourreza‑Bilondi2 · Hadi Memarian3 Received: 17 April 2018 / Accepted: 12 June 2019 © Shiraz University 2019
Abstract Although hydrological models play an essential role in managing water resources, quantifying different sources of uncertainties is a challenging task. In this study, the application of parameter uncertainty quantification methods and their performance for predicting runoff were investigated in Kashafrood River, as a large-scale basin, located in the northeast of Iran. Differential Evolution Adaptive Metropolis (DREAM-ZS) algorithm was employed to explore the output uncertainty of Soil and Water Assessment Tool (SWAT) model at flow gauging stations. To optimize the model and quantify the parameters uncertainty, S1 and S2 scenarios, which belong to the DREAM-ZS algorithm, were defined. The prior ranges of the S1 scenario were selected by the final calibration of parameters’ ranges in the SWAT-Calibration and Uncertainty Program (SWAT-CUP) software and Sequential Uncertainty Fitting version 2 procedure, and the prior ranges of the S2 scenario were selected using a compromising approach between the prior ranges of the SWAT-CUP and posterior ranges from S1 scenario. P-factor, d-factor, Nash–Sutcliffe (NS), Total Uncertainty Index (TUI) and Average Deviation Amplitude (ADA) showed that the S2 scenario performed better than the S1 in the reduction of prediction uncertainties. Based on S1 simulation, the NS coefficient ranged from 0.54 to 0.72, while for S2 simulation, it ranged from 0.63 to 0.78. The TUI for total uncertainty was in a range of 0.2–0.6 and 0.22–0.66 for S1 and S2 scenarios, respectively. The S1 and S2 simulations led to the TUI of 0.63–0.94 and 0.74–1.22 for parameter uncertainty, respectively. Finally, ADA index for total uncertainty was 0.098 and 0.445 for S1 and S2 scenarios, while according to S1 and S2 simulations, the ADA index was 0.098 and 0.451 for parameter uncertainty, respectively. The DREAM-ZS algorithm improved the model calibration efficiency and led to more realistic values of the parameters for runoff simulation by SWAT model in the Kashafrood River Basin. Keywords Uncertainty analysis · Multisite calibration · DREAM-ZS · SWAT
1 Introduction * Amirhosein Aghakhani Afshar [email protected]; [email protected] Yousef Hassanzadeh [email protected] Mohsen Pourreza‑Bilondi [email protected] Hadi Memarian [email protected] 1
Department of Water Engineering, Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran
2
Department of Water Engineering, College of Agriculture, University of Birjand, Birjand, Iran
3
Department of Watershed Management, Faculty of Natural Resources and Environment, University of Birjand, Birjand, Iran
Most of the rivers, located in the large-scale mountainous watersheds, are demonstrated as the important sources of water availab
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