Modeling flood data with mep:Isparta/sutculer flood example

The rainfall-runoff process is one of the fundamental components of the hydrological cycle from an engineering perspective, and estimating runoff resulting from potential precipitation events plays a critical role in water resources planning. In this context, numerous models, both physically based and data-driven, have been developed. While the flow hydrograph reflects the time-dependent runoff response of a watershed, the interpretation and modeling of flood data today constitute a significant aspect of hydrological studies. In this study, the potential of the Multi Expression Programming (MEP) method for flood modeling was investigated using observed flood hydrographs and watershed characteristics. The main focus of the study is the modeling of the 1995 flood event in the Isparta-Sütçüler Watershed using MEP. Various statistical metrics, such as the Coefficient of Determination (R²) and Mean Absolute Error (MAE), were used to evaluate the accuracy and applicability of the developed models. As a result of the study, it was concluded that using shorter time intervals instead of a single continuous time series in MEP-based flood modeling yielded more successful and effective results. The MEP method was found to provide high accuracy and practical applicability in flood modeling studies. It was also emphasized that processing hard-to-obtain data, such as precipitation and runoff, using MEP and similar artificial intelligence techniques is important for improving the accuracy of discharge estimations.