Modeling daily stream flow using plant evapotranspiration method

In hydrological models, soil conservation services (SCS) are one of the most widely used procedures to calculate the curve number (CN) in rainfall run-off simulation. Recently, another new CN accounting procedure has been mentioned, namely the plant evapotranspiration (ET) method or simply known as...

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Bibliographic Details
Main Authors: Jajarmizadeh, Milad, Harun, Sobri, Ghahraman, Bijan, Mokhtari, M. H.
Format: Article
Published: Academic Journals 2012
Subjects:
Online Access:http://eprints.utm.my/id/eprint/31053/
https://academicjournals.org/journal/IJWREE/article-abstract/D3473E42925
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Institution: Universiti Teknologi Malaysia
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Summary:In hydrological models, soil conservation services (SCS) are one of the most widely used procedures to calculate the curve number (CN) in rainfall run-off simulation. Recently, another new CN accounting procedure has been mentioned, namely the plant evapotranspiration (ET) method or simply known as the plant ET method. This method is embedded in the Soil and Water Assessment Tool (SWAT) model which has been developed for watersheds covered by shallow soils or soils with low storage characteristics. It uses antecedent climate and plant evapotranspiration for calculation of daily curve number. In this study, the same method had been used to simulate the daily stream flow for Roodan watershed located in the southern part of Iran. The watershed covers 10570 km2 and its climate is arid to semi-arid. The modeling process required data from digital elevation model (DEM), land use map, and soil map. It also required daily meteorological data which were collected from weather stations from 1988 to 2008. Other than that, the Sequential Uncertainty Fitting-2 (SUFI-2) algorithm was utilized for calibration and uncertainty analysis of daily stream flow. Criteria of modeling performance were determined through the Nash-Sutcliffe and coefficient of determination for calibration and validation. For calibration, the values were reported at 0.66 and 0.68 respectively and for validation; the values were 0.51 and 0.55. Moreover, percentiles of absolute error between observed and simulated data in calibration and validation period were calculated to be less than 21.78 and 6.37 (m3/s) for 95% of the data. The results were found to be satisfactory under the climatic conditions of the study area.