TITLE:
Estimation of the Impact of Climate Change on Water Resources Using a Deterministic Distributed Hydrological Model in Côte d’Ivoire: Case of the Aghien Lagoon
AUTHORS:
Wa Kouakou Charles N’Dri, Séverin Pistre, Jean Patrice Jourda, Kan Jean Kouamé
KEYWORDS:
Abidjan, Climate Change, Côte d’Ivoire, Aghien Lagoon, SWAT
JOURNAL NAME:
Journal of Geoscience and Environment Protection,
Vol.7 No.7,
July
26,
2019
ABSTRACT:
This work aims to evaluate the
impact of climate change on the quantitative availability of the Aghien lagoon
located in the north of the Abidjan district in Cô
;te d’Ivoire. In the first step, the
semi-distributed SWAT (Soil and Water Assessment Tools) based physical model (Arnold et al., 1998) was calibrated and validated at the monthly time step over the period
1960-1981, in the Me watershed for which data from flow rates are available. SWAT was then applied on the watershed of the lagoon of Aghien which is
ungauged but for which the challenges are considerable for the drinking water
supply of the Abidjanese population. In the second step, the gross outputs (precipitation, temperatures) of six
climate models of the CORDEX-Africa project under the “Representative
Concentration Pathways” (RCP 4.5 and RCP 8.5) scenarios were corrected using
the delta method. These corrected outputs were
used at the SWAT model input to project the impact of climate change on the
flow of the Aghien lagoon to horizons 2040 (2035-2056), 2060 (2057-2078) and
2080 (2079-2100). The projections made on
these different horizons were compared with the simulated flow over the period
1960-1981. The results show a sensible decrease in the annual flow of the Aghien
lagoon compared to the reference period (1960-1981). Under the medium
assumption (RCP 4.5), the models predict a decrease in the annual discharge
almost 10% on average. Under the pessimistic hypothesis (RCP 8.5), the average
annual discharge should decrease by more than 17%. On a monthly basis, flows in
August and September would increase by more than 80% and those in October and November
would increase by more than 20% in both RCP scenarios.