@article{fdi:010064774,
  title = {{OPTIWAM} : an intelligent tool for optimizing irrigation water management in coupled reservoir-groundwater systems},
  author = {{F}owe, {T}. and {N}ouiri, {I}. and {I}brahim, {B}. and {K}arambiri, {H}. and {P}aturel, {J}ean-{E}mmanuel},
  editor = {},
  language = {{ENG}},
  abstract = {{A}n approach based on a real coded {G}enetic {A}lgorithm ({GA}) model was used to optimize water allocation from a coupled reservoir-groundwater system. {T}he {GA} model considered five objectives: satisfying irrigation water demand, safeguarding water storage for the environment and fisheries, maximizing crop water productivity, protecting the downstream ecosystem against elevated soil salinity and hydromorphic issues, and reducing the unit cost of water. {T}he model constraints are based on hydraulic and storage continuity requirements. {T}he objectives and constraints were combined into a fitness function using a weighting factor and the penalty approaches. {T}he decision variable was water allocation for irrigation demand from reservoir and groundwater. {T}he irrigation water demands around the reservoir were estimated using the {F}ood and {A}griculture {O}rganization ({FAO}) {P}enman-{M}onteith method in the water evaluation and planning ({WEAP}) software. {T}he deterministic {GA} model was coded using {V}isual {B}asic 6 and a new tool for irrigation water management optimization ({OPTIWAM}) was developed. {T}o validate the applicability of the deterministic model for the operation of coupled reservoir-groundwater systems, the {B}oura reservoir (in the center-west region of {B}urkina {F}aso) and the downstream irrigation area were used as a case study. {R}esults show that the proposed methodology and the developed tool are effective and useful for determining optimal allocation of irrigation water. {F}urthermore, the methodology and tool can improve water resources management of coupled reservoir-groundwater systems.},
  keywords = {{I}rrigation ; {W}ater resources ; {A}llocation ; {O}ptimization ; {G}enetic algorithms},
  booktitle = {},
  journal = {{W}ater {R}esources {M}anagement},
  volume = {29},
  numero = {10},
  pages = {3841--3861},
  ISSN = {0920-4741},
  year = {2015},
  DOI = {10.1007/s11269-015-1032-9},
  URL = {https://www.documentation.ird.fr/hor/fdi:010064774},
}