Issam Nouiri, Ibrahim Boubacar, Harouna Karambiri, and Jean-Emmanuel Paturel
Water Resources Management


An approach based on a real coded Genetic Algorithm (GA) model was used to
optimize water allocation from a coupled reservoir-groundwater system. The GA model
considered five objectives: satisfying irrigation water demand, safeguarding water storage
for the environment and fisheries, maximizing crop water productivity, protecting the down-
stream ecosystem against elevated soil salinity and hydromorphic issues, and reducing the unit
cost of water. The model constraints are based on hydraulic and storage continuity require-
ments. The objectives and constraints were combined into a fitness function using a weighting
factor and the penalty approaches. The decision variable was water allocation for irrigation
demand from reservoir and groundwater. The irrigation water demands around the reservoir
were estimated using the Food and Agriculture Organization (FAO) Penman-Monteith method
in the water evaluation and planning (WEAP) software. The deterministic GA model was
coded using Visual Basic 6 and a new tool for irrigation water management optimization
(OPTIWAM) was developed. To validate the applicability of the deterministic model for the
operation of coupled reservoir-groundwater systems, the Boura reservoir (in the center-west
region of Burkina Faso) and the downstream irrigation area were used as a case study. Results
show that the proposed methodology and the developed tool are effective and useful for
determining optimal allocation of irrigation water. Furthermore, the methodology and tool can
improve water resources management of coupled reservoir-groundwater systems.