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A New Fuzzy Model for Predicting Runoff Coefficient Rate Based on Soil Properties and Land Use Information: A Case Study of Antalya Sub-basin

Journal Intelligent and fuzzy systems

publisher İnas rifat

DOI https://doi.org/10.1007/978-3-031-98304-7_69

Accurate determination of the river runoff coefficient and its variations is required for various crucial activities, such as efficiently utilizing available water resources, planning the construction of water structures, and preventing catastrophes. Without a thorough understanding of the hydrology and climate of the river basin, it is impossible to make accurate predictions of the runoff coefficient. The Simple Membership Functions and Fuzzy Rules Generation Technique (SMRGT) were implemented in this study. The Aksu River Basin in Turkey, bordering the Mediterranean Sea, was chosen as the study area, and data from this region was utilized. The annual precipitation data (P), land use (LU), and soil permeability (Sp) were input variables, while the runoff coefficient was the output variable. After evaluation, it was concluded that the study examined the outcomes using several performance metrics of the model, such as mean absolute error (MAE), Nash–Sutcliffe efficiency coefficient (NSE), root mean square error (RMSE), and correlation coefficient (R2). The outcomes demonstrated that the SMRGT method magnificently predicts runoff coefficients and effectively creates membership functions and fuzzy rules, as demonstrated with the minimal RMSE (7.7) and MAE (0.06) values and high correlation coefficient value (0.98). This work confirms that the SMRGT method can be used to improve the hydrological analysis to estimate runoff coefficient and that the good blocking results in the hydrological analysis contribute to efficient flood prediction, optimized water resource management, and more proper flood mitigation strategies.

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Certificate of presentation

Country Turkey

Location İstanbul