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Information Journal Paper

Title

Improving runoff prediction using WAPABA model

Pages

  87-94

Abstract

 This paper aims to increase the accuracy of Runoff predictions using WAPABA model and with comparing its efficiency with SALAS model outputs, involving hydrometric Runoff data of North Markazi Province-Iran, for year 2010-2011. The above mentioned models were applied and calibrated using the mentioned historical data. Then the performance of each model were evaluated using different criteria including; CE, RMSE, R2 and MAE. Also, comparison of the models predictions with the measured data were made. Results show that the predicted Runoff data using SALAS model are values more than the measured data, which can be due to the weighting values of this model. In other words in SALAS model the weights which relate to precipitation is more than other parameters. While WAPABA Runoff model with the same weights, which are considered for all parameters, have a better and accurate predictions. However, in this study for the Ghet-e-Char station of the case study WAPABA model had not suitable predictions.

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    • Cite

    APA: Copy

    RASHIDIEH, BEHNAM, ARAGHINEJAD, SHAHAB, & EBRAHIMI, KUMARS. (2017). Improving runoff prediction using WAPABA model. IRANIAN JOURNAL OF SOIL AND WATER RESEARCH, 48(1 ), 87-94. SID. https://sid.ir/paper/225762/en

    Vancouver: Copy

    RASHIDIEH BEHNAM, ARAGHINEJAD SHAHAB, EBRAHIMI KUMARS. Improving runoff prediction using WAPABA model. IRANIAN JOURNAL OF SOIL AND WATER RESEARCH[Internet]. 2017;48(1 ):87-94. Available from: https://sid.ir/paper/225762/en

    IEEE: Copy

    BEHNAM RASHIDIEH, SHAHAB ARAGHINEJAD, and KUMARS EBRAHIMI, “Improving runoff prediction using WAPABA model,” IRANIAN JOURNAL OF SOIL AND WATER RESEARCH, vol. 48, no. 1 , pp. 87–94, 2017, [Online]. Available: https://sid.ir/paper/225762/en

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