| dc.description.abstract | 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.
Key words: data mining; discharge; forecast model; hydrological process; clustering; techniques | en_US |
