Hydrological Modeling Using Chicken Swarm Optimization Algorithm – Oued El Melah Case Study (NE of Algeria)

Abstract

The aim of this article is Hydrological modeling using Chicken Swarm Optimization Algorithm. Interactions between meteorological and hydrometric data been identified as a major conducting factor stationarity in rainfall-runoff relationships. The methodology used in this work is rainfall-runoff modeling is Chicken Swarm Optimization Algorithm. This approach based on randomly selection and chicken society behaivoir. For the efficiency evaluation of Chicken Swarm Optimization Algorithm, a variety of statistical parameters have been used with acceptable values of Nash–Sutclife Efciency (NSE) with 0.38% and Index of Agreement (IA) with 0.91% . The important and new results are the hydrological models (empirical models) adaptation to Algerian conditions especially in ungagged basins. Therefore, the proposal of the present modelling is a technique using the CSO method to model the rainfall-runoff relationship and discharge forecasting in the OUED EL MELAH basin located in GUELMA city. CSO proves to be a valuable model for studies of the rainfall and flood runoff response to protection of agglomerations against flooding risks projections.

Keywords

• water resources management
• rainfall-runoff
• oued el melah basin
• flood forecasting
• machine learning