Using uncertainty and sensitivity analysisfor finding the best rainfall-runoff model in mountainous watersheds (Case study: the Navrood watershed in Iran) Using uncertainty and sensitivity analysisfor finding the best rainfall-runoff model in mountainous watersheds (Case study: the Navrood watershed in Iran)

最小化 最大化

Vol16 No.3: 529-541

Title】Using uncertainty and sensitivity analysisfor finding the best rainfall-runoff model in mountainous watersheds (Case study: the Navrood watershed in Iran)

Author】Arash ADIB*; Morteza LOTFIRAD; Ali HAGHIGHI

Addresses】Civil Engineering Department, Engineering Faculty, Shahid Chamran University of Ahvaz, Ahvaz, Iran

Corresponding author】Arash ADIB

Citation】Adib A, Lotfirad M, Haghighi A (2019) Using uncertainty and sensitivity analysisfor finding the best rainfall-runoff model in mountainous watersheds (Case study: the Navrood watershed in Iran). Journal of Mountain Science 16(3). https://doi.org/10.1007/s11629-018-5010-6

DOI】https://doi.org/10.1007/s11629-018-5010-6

Abstract】In watersheds that have not sufficient meteorological and hydrometric data for simulating rainfall-runoff events, using geomorphologic and geomorphoclimatic characteristics of watershed is a conventional method for the simulation. A number of rainfall-runoff models utilize these characteristics such as Nash-IUH, Clark-IUH, Geomorphologic Instantaneous Unit Hydrograph (GIUH), Geomorphoclimatic Instantaneous Unit Hydrograph (GcIUH), GIUH-based Nash (GIUH-Nash) and GcIUH-based Clark (GcIUH-Clark). But all these models are not appropriate for mountainous watersheds. Therefore, the objective of this study is to select the best of them for the simulation. The procedure of this study is:a) selecting appropriate rainfall- runoff events for calibration and validation of six hybrid models, b) distinguishingthe best model based on different performance criteria (Percentage Error in Volume(PEV); Percentage Error in Peak (PEP); Percentage Error in Time to Peak (PETP); Root Mean Square Error (RMSE)and Nash-Sutcliffe model efficiency coefficient (ENS)), c) Sensitivity analysis for determination of the most effective parameter at each model, d) Uncertaintydetermination of different parameters in  each model and confirmation of the obtained results by application of the performance criteria. For application of this procedure, the Navrood watershed in the north of Iran as a mountainous watershed has been considered.  The results showed that the Clark-IUH and GcIUH-Clark are suitable models for simulation of flood hydrographs, while other models cannot simulate flood hydrographs appropriately. The sensitivity analysis shows that the most sensitive parameters are the infiltration constant rate and time of concentration in the Clark-IUH model. Also, the most sensitive parameters include the infiltration constant rate and storage coefficient in the GcIUH-Clark model. The Clark-IUH and GcIUH-Clark models are more sensitive to their parameters. The Latin Hypercube Sampling (LHS) on Monte Carlo (MC)simulation method was used for evaluation of uncertainty of data in rainfall-runoff models. In this method 500 setsof data values are produced and then the peak discharge of flood hydrographs for each produced data set is simulated with rainfall-runoff models. The uncertainty of data changes the value of simulated peak discharge of flood hydrograph. The uncertainty analysis shows that the observed peak discharges of different rainfall-runoff events are within the range of values of simulated by the six hybrid rainfall-runoff models and IUH that inputs of these models were the produced data sets. The range of the produced peak discharge of flood hydrographs by the Clark-IUH and GcIUH-Clark models is wider than those of other models.

Keywords】Sensitivity analysis; Uncertainty analysis; Clark-IUH; GcIUH-Clark; GIUH-Nash; Monte Carlo simulation method