Assessment and Prediction of Rainfall-Runoff Models Using GR4J in the Klela Basin in Mali

Autor: Souleymane Keita, Adama Toure, Zakari Mahamadou Mounir, Ibrahima Daou, Oumou Diancoumba
Rok vydání: 2022
Předmět:
Zdroj: Modern Applied Science. 16:52
ISSN: 1913-1852
1913-1844
DOI: 10.5539/mas.v16n4p52
Popis: The study on water resources is very important for a country like Mali Republic. This is because the climate of the Sahel is projected by many climate scenarios that contribute to a premature dry season. So, the Klela basin being one of the affected areas by the phenomenon is selected for this study. Hence, it is interesting to evaluate this vital resource for a better planning in order to facilitate the decision making from the concerned authorities. For this research, the hydrological model, GR4J, is used to evaluate the dynamics of the surface water flow. The main objective of this study is to assess and predict (using scenarios RCP4.5 and RCP8.5) the correlation between rainfall and runoff in the Klela basin. In tandem with on this objective, the water flow and climate data were used as input data into the GR4J model. The model was calibrated and evaluated using the time series data 2000-2007 and 2008-2013, respectively. The performance of the model was evaluated mainly based on the Nash-Sutcliffe efficiency. The overall outputs display that the surface water flow is declining over time and this is more significant in the worst scenario RCP8.5.
Databáze: OpenAIRE