Kinematic runoff and erosion model efficiency assessment for hydrological simulation of semi-arid watersheds
Hydrologic modeling of semi-arid watersheds is imperative for the development of appropriate water and soil conservation plans. In the current study, the efficiency of Kinematic Runoff and Erosion model-version 2 (K2) model was used to evaluate water discharge and sediment load simulation of Bar watershed, located in the north-eastern part of Iran. The K2 model relies on the kinematic wave approach to route surface flow. The drainage network and planes are discretized to represent the watershed. In order to evaluate the model, 3 and 2 reported rainfall incidents in various dates were selected for K2 calibration and validation, respectively. The multiplier approach was employed for model calibration. The results of sensitivity investigation revealed that the soil parameters Ks-CH, n and G had the highest impact on flow discharge. Through the calibration process, the Nash-Sutcliff Efficiency and the coefficient of determination as fitting metrics for water discharge simulation (based on event #2, dated 16 March 1992) were estimated to be 0.78 and 0.88, respectively. According to the aggregated measure, the highest K2 efficiency was obtained during the calibration process based on event #2. Other storm events were resulted in a good simulation, as well. During the validation process, K2 simulation (based on event #4, dated 07 March 1991) led to the Nash-Sutcliffe Efficiency and R2 of 0.77 and 0.71, respectively. The K2 calibration for sediment load simulation was performed through the alterations of the Pave and Rainsplash parameters. The bias percentages between simulated and observed total sediment loads based on events #2 and #4 were 5% and 16%, respectively. Conclusively, the K2 model showed an acceptable robustness in the hydrological simulation of Bar watershed as a representative semi-arid watershed in northeast of Iran.
Hydrological processes and their spatial distribution directly are relevant to climate, topography, geology, and land use in the watershed. Therefore, use of a model whit integrity and high performance for simulating the process in deferent watersheds is very important. In this study was assessment performance of semi-distributed SWAT model in simulating hydrology processes in three watersheds ...متن کامل
Using SWAT and SWAT-CUP for hydrological simulation and uncertainty analysis in arid and semi-arid watersheds (Case study: Zoshk Watershed, Shandiz, Iran)
The aims of this project was to assess the capability of SWAT model and SWAT-CUP software in hydrological simulation and to evaluate the uncertainty of SWAT model in estimating runoff in arid and semi-arid watersheds. Model calibration and uncertainty analysis were performed using the Sequential Uncertainty Fitting (SUFI2) algorithm. In the stage of calibration and validation of water flow, per...متن کامل
Modelling runoff and erosion for a semi-arid catchment using a multi-scale approach based on hydrological connectivity
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Prediction of runoff and sediment from agricultural watersheds by a mathematical model 2 mathematical simulation
Study on Applicability of Conceptual Hydrological Models for Flood Forecasting in Humid, Semi-Humid Semi-Arid and Arid Basins in China
Flood simulation and forecasting in various types of watersheds is a hot issue in hydrology. Conceptual hydrological models have been widely applied to flood forecasting for decades. With the development of economy, modern China faces with severe flood disasters in all types of watersheds include humid, semi-humid semi-arid and arid watersheds. However, conceptual model-based flood forecasting ...متن کامل
The efficiency of Artificial Neural Network, Neuro-Fuzzy and Multivariate Regression models for runoff and erosion simulation using rainfall simulator
1- INTRODUCTION According to the complexity of environmental factors related to erosion and runoff, correct simulation of these variables find importance under rain intensity domain of watershed areas. Although modeling of erosion and runoff by Artificial Neural Network and Neuro-Fuzzy based on rainfall-runoff and discharge-sediment models were widely applied by researchers, scrutinizing Arti...متن کامل
دوره 4 شماره 2
صفحات 127- 140
تاریخ انتشار 2018-04-01
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