Comparison of Performance between Genetic Algorithm and SCE-UA for Calibration of SCS-CN Surface Runoff Simulation
نویسندگان
چکیده
منابع مشابه
Comparison of Performance between Genetic Algorithm and SCE-UA for Calibration of SCS-CN Surface Runoff Simulation
Global optimization methods linked with simulation models are widely used for automated calibration and serve as useful tools for searching for cost-effective alternatives for environmental management. A genetic algorithm (GA) and shuffled complex evolution (SCE-UA) algorithm were linked with the Long-Term Hydrologic Impact Assessment (L-THIA) model, which employs the curve number (SCS-CN) meth...
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15 صفحه اولAssessment and Calibration of the Curve Number Method (SCS-CN) for Estimating Runoff in the Aras Sub-basins, North West of Iran
The SCS-curve number is one of the common methods to estimate drirect runoff in the watershed scale. There is often an uncertainty in predicting runoff in many areas due to to the model’s assumption on the initial abstraction ratio (l= 0.20). This study was conducted to evaluate the accuracy of SCS-CN method in estimating runoff in some semi-arid subbasins of the Aras river consits of the Livar...
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The aim of this study is to estimate runoff in Wadi Ba Al Arid watershed for a period of ten years 2009-2018 by Soil Conservation Service Curve Number (SCS-CN) method in combination with the GIS techniques using remote sensing data. The used data are the daily rainfall data from NASA Prediction of Worldwide Energy Resource (POWER), digital elevation data (DEM) from ALOS PALSAR RTC , satellite...
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The Soil Conservation Service Curve Number (SCS-CN) approach is widely used as a simple method for predicting direct runoff volume for a given rainfall event. The CN parameter values corresponding to various soil, land cover, and land management conditions can be selected from tables, but it is preferable to estimate the CN value from measured rainfall-runoff data if available. However, previou...
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ژورنال
عنوان ژورنال: Water
سال: 2014
ISSN: 2073-4441
DOI: 10.3390/w6113433