We describe in this paper the implementation of E-Water, an open software Decision Support System (DSS), designed to help local managers assess the Water Energy Food Environment (WEFE) nexus. E-Water aims at providing optimal management solutions to enhance food crop production at river basin level. The DSS was applied in the transboundary Mékrou river basin, shared among Benin, Burkina Faso and Niger. The primary sector for local economy in the region is agriculture, contributing significantly to income generation and job creation. Fostering the productivity of regional agricultural requires the intensification of farming practices, promoting additional inputs (mainly nutrient fertilizers and water irrigation) but, also, a more efficient allocation of cropland.
In order to cope with the heterogeneity of data, and the analyses and issues required by the WEFE nexus approach, our DSS integrates the following modules: (1) the EPIC biophysical agricultural model; (2) a simplified regression metamodel, linking crop production with external inputs; (3) a linear programming and a multiobjective genetic algorithm optimization routines for finding efficient agricultural strategies; and (4) a user-friendly interface for input/output analysis and visualization.
To test the main features of the DSS, we apply it to various real and hypothetical scenarios in the Mékrou river basin. The results obtained show how food unavailability due to insufficient local production could be reduced by, approximately, one third by enhancing the application and optimal distribution of fertilizers and irrigation. That would also affect the total income of the farming sector, eventually doubling it in the best case scenario. Furthermore, the combination of optimal agricultural strategies and modified optimal cropland allocation across the basin would bring additional moderate increases in food self-sufficiency, and more substantial gains in the total agricultural income.
The proposed software framework proves to be effective, enabling decision makers to identify efficient and site-specific agronomic management strategies for nutrients and water. Such practices would augment crop productivity, which, in turn, would allow to cope with increasing future food demands, and find a balanced use of natural resources, also taking other economic sectors—like livestock, urban or energy—into account.
Computers and Electronics in Agriculture, Volume 154, November 2018, Pages 467-481