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Hydrological modeling using the SWAT model based on two types of data from the watershed of Beni Haroun dam, Algeria

Authors
  • Kateb, Zakaria1
  • Bouchelkia, Hamid2
  • Benmansour, Abdelhalim1
  • Belarbi, Fadila1
  • 1 URMER Laboratory, Algeria , (Algeria)
  • 2 URMER Laboratory, 13000 , (Algeria)
Type
Published Article
Journal
Journal of Water and Land Development
Publisher
Walter de Gruyter GmbH
Publication Date
Dec 01, 2019
Volume
43
Issue
1
Pages
76–89
Identifiers
DOI: 10.2478/jwld-2019-0065
Source
De Gruyter
Keywords
License
Green

Abstract

The dam of Beni Haroun is the largest in Algeria, and its transfer structures feed seven provinces (wilayas) in the eastern part of Algeria. Due to its importance in the region, it has now become urgent to study its watershed as well as all the parameters that can influence the water and solid intakes that come into the dam. The Soil and Water Assessment Tool (SWAT) model is used to quantify the water yields and identify the vulnerable spots using two scenarios. The first one uses worldwide data (GlobCover and HWSD), and the second one employs remote sensing and digital soil mapping in order to determine the most suitable data to obtain the best results. The SWAT model can be used to reproduce the hydrological cycle within the watershed. Concerning the first scenario, during the calibration period, R2 was found between 0.45 and 0.69, and the Nash–Sutcliffe efficiency (NSE) coefficient was within the interval from 0.63 to 0.80; in the validation period, R2 lied between 0.47 and 0.59, and the NSE coefficient ranged from 0.58 to 0.64. As for the second scenario, during the calibration period, R2 was between 0.60 and 0.66, and the NSE coefficient was between 0.55 and 0.75; however, during the validation period, R2 was in the interval from 0.56 to 0.70, and the NSE coefficient within the range 0.64–0.70. These findings indicate that the data obtained using remote sensing and digital soil mapping provide a better representation of the watershed and give a better hydrological modelling.

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