4.7 Article Proceedings Paper

Evaluation of potential evapotranspiration assessment methods for hydrological modelling with SWAT-Application in data-scarce rural Tunisia

期刊

AGRICULTURAL WATER MANAGEMENT
卷 174, 期 -, 页码 39-51

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ELSEVIER
DOI: 10.1016/j.agwat.2016.03.004

关键词

Potential evapotranspiration; Actual evapotranspiration; Weather generator; Penman-Monteith; SWAT model

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Potential evapotranspiration (PET) is an important factor used in hydrological models as well as in management of irrigation projects and water-balance estimations. At the catchment level, hydrological models first calculate PET and then actual evapotranspiration (ET) by considering soil moisture and land use. In this study, we used the SWAT model to estimate PET, actual ET and streamflow. SWAT provides three methods for computing PET: (i) Penman-Monteith (PM), (ii) Hargreaves (HA) and (iii) Priestly-Taylor (PT). Due to missing weather parameters for the PM method, a statistical weather generator embedded in SWAT, WXGEN was used in several studies to generate missing weather data and to fill in gaps in measured records. The goals of this work were to evaluate the PM method's accuracy in calculating PET using generated and measured meteorological data and further to compare the three embedded methods in SWAT to predict PET. The model was applied to the Joumine basin, covering an area of 418 km(2), located in northern Tunisia. For each run, simulated streamflow was compared with measured data by calculating Nash-Sutcliffe efficiency, root mean square error and coefficient of determination. The PM method predicted PET well with generated data. The method used to calculate PET did not considerably affect stream flow predictions; however, significant differences were found among them. Model predictions of streamflow were close to observed values, with a Nash-Sutcliffe efficiency of 0.90 and R-2 value of 0.92 after monthly calibration using HA method. During the validation period, SWAT predictions were nearly as accurate, with Nash-Sutcliffe efficiency and R-2 values of 0.89 and 0.92, respectively. (C) 2016 Elsevier B.V. All rights reserved.

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