Integrated Hydrological Analysis for Water Resource Management and Flood Risk Forecasting in the Diani Watershed

Abstract

The Diani watershed faces increasing pressure on its water resources due to climate variability, population growth, urbanization, and agricultural and pastoral activities. Increasingly frequent episodes of intense rainfall, exacerbated by climate change, cause recurring floods resulting in loss of life, property damage, degradation of agricultural land, and socio-economic disruption. Furthermore, the lack of reliable hydrometeorological data, insufficient flood control infrastructure (retention basins, dikes, drainage canals), uncontrolled development in flood-prone areas, and deforestation further increase the watershed's vulnerability. Poor coordination among institutional stakeholders and the limited integration of modern hydrological modeling tools also hinder the effectiveness of early warning systems. The objective of this study is to estimate return periods and quantiles of extreme rainfall and discharge in order to analyze the relationship between these two variables in the Diani watershed in Guinea's Forest Region. The methodological approach consists of finding a statistical distribution of maximum annual rainfall and discharge from 1995 to 2024 by fitting them to the Gumbel distribution of extreme values. The parameters of the Gumbel extreme value distribution were estimated using the weighted moment method. The results show that the data studied fit the Gumbel extreme value distribution well. Furthermore, the annual maxima of precipitation and stream flow have return periods of 6, 12, 20, and 60 years, respectively. These return periods correspond to abnormal, highly abnormal, and exceptional events. The rainfall and flow quantiles corresponding to these events are 85.8, 99.1, 108.6, and 128.6 mm for the N’Zérékoré station; and 96.1, 113.8, 126.4, and 153.2 mm for the Macenta station, with flow rates of 195.6, 227.3, 249.9, and 297.7 m³/s respectively. Unpredictable extreme rainfall can lead to flooding, which could have serious economic and social consequences in the Diani watershed. The correlation coefficient between rainfall and flow rate is -0.041 at the N’Zérékoré station and 0.013 at the Macenta station. Indeed, these results show that there is no significant relationship between rainfall (N’Zérékoré, Macenta) and flow rates in the Diani River watershed.