TITLE:
Modeling the Hydrological Dynamic of the Breeding Water Bodies in Barkedji’s Zone
AUTHORS:
Mamadou Bop, Angelina Amadou, Ousmane Seidou, Cheikh Mouhamed Fadel Kébé, Jacques André Ndione, Soussou Sambou, Ibrah Seidou Sanda
KEYWORDS:
Breeding Areas, Hydrology, Pond Dynamics, Climate Change
JOURNAL NAME:
Journal of Water Resource and Protection,
Vol.6 No.8,
June
19,
2014
ABSTRACT: Temporary
water bodies’ dynamics play an important role in the epidemiological
chain-borne diseases such as Rift Valley fever as they are the main breeding
habitats for mosquitoes. During the rainy season, hundreds of these temporary
water bodies appear and grow in the Ferlo region (Senegal). The purpose of this
research is to generate historical and future time series water levels and
areas at three temporary ponds located in the environment and health
observatory of Barkedji. A simple lumped hydrological model was developed for
that purpose. It describes each pond watershed as three interconnected
reservoirs: canopy, surface storage and soil storage and uses a linear relation
to describe infiltration, percolation and baseflow (out of the soil reservoir).
Given the depth of the water table in the region, percolation out of the soil
surface is considered lost. Evapotraspiration was calculated using the Penman
equation and withdraws water from the canopy and surface water reservoirs.
Excess runoff from the soil storage is turned into runoff using a triangular
unit hydrograph. The calibration was done using two years of hydrological and
climatic data collected during the 2011 and 2012 rainy seasons. The calibration
was successful and water level in the two ponds was simulated with a Root Mean
Square Error (RMSE) of 11.2 to 15 cm. Because of the short duration of the
observation, no validation could be done. Given the excellent agreement of the
simulated and observed water levels during the calibration phase, the modeling
exercise was considered to be successful. The developed models were used to
generate historical time series of pond areas and correlate these to mosquitoes’
infestation in the region. Future time series of pond areas were also generated
using downscaled outputs of three regional climate models from the AMMA
ENSEMBLES experiment. The generated pond levels and areas are being used to
assess the evolution of the disease in the next 40 years.