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Senegalese cities are experiencing very rapid growth in terms of both spatial and demographic development, which has an impact on the management of runoff water, which is increasingly a major concern of authorities and urban populations. In these cities, public sanitation infrastructure is insufficient and unevenly distributed in urban space. The objective of this study is to characterize the problem of rainwater management in the city of Ziguinchor (southern Senegal). The methodology is based on an administration, a questionnaire submitted to 288 heads of households, and an interview guide with 13 actors who stand out in the environmental management component at the local level. The results obtained attest to a real problem of sanitation of rainwater managed in precarious conditions due to the lack of infrastructure and water management methods used by households. The infrastructural problem is a factor in the poor management of rainwater in Ziguinchor, while rainwater drainage practices do not protect the living environment of the populations. In the city of Ziguinchor, the main strategies adopted in the face of the sanitation network deficit are based on backfilling, the laying of sandbags and stones, evacuation through buckets.

Within the framework of water resources management, numerous research works and methods were led in world. In this trail, we noted a fast development of time series data mining (TSDM) which supplies a new method for water resources management. This article examines the trend of discharge during the high water period (from July till November) in the basin of Gambia measured at the Mako station for 1970-2013 period. Methodology consisted at first in calculation and in standardization of data by the method of z-score of some statistical parameters (mean, maximum, minimum, range and standard deviation). Obtained series were afterward submitted to classifications techniques such as k-means clustering and Agglomerative Hierarchical Clustering (AHC) of TSDM to cluster and discover the discharge patterns in terms of the autoregressive model. Based on these methods, a discharge forecast model has been developed. For the validation of the indicated model, and with respect to the maximum discharge, the coefficients of discharge growth and decay, respectively on the phase of rise and the phases of rise and descent waters, were calculated. This study presents basin discharge dynamics in high water period based on TSDM.