System for predicting dischearges over the high water period through classification techniques data : case of the Gambia river basin of Mako

Abstract

This article examines the trend of flow during the high water period (from July till November) in the basin of Gambia measured at the Mako station of over 2004-2013 period. Methodology consisted at first in calculation and in standardization of data by the method of z-score of some statistical parameters (average, 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 Time Series Data Mining to cluster and discover the discharge patterns in terms of the autoregressive model.. From these methods, a forecast model has been developed for the discharge process on average over these years. This study presents basin flow dynamics in high water period from Time Series Data Mining technique.

Keywords: data Mining, flow, forecast model, hydrological process, clustering; technics