Optimizing cocoa biomass density through integrated irrigation and drainage management under water stress: A linear programming approach

Abstract

This study presents a novel linear programming model that combines crop growth and hydrological dynamics to optimize irrigation and drainage schedules, enhancing cocoa biomass density under variable water stress conditions. Using data from the NASA POWER database and incorporating detailed climate, soil, and crop management variables specific to San Vicente del Chucurí, Colombia, the model evaluated 19,980 environmental and policy scenarios to test its effectiveness. The results indicate that targeted management of irrigation and drainage frequencies can substantially improve cocoa yield by adapting to fluctuating environmental conditions. This model provides key insights into the optimal timing and frequency of water applications, critical for sustaining crop health and productivity in the face of climate variability. These findings hold significant implications for sustainable agricultural practices, offering a practical tool for farmers and policymakers to increase yield while conserving water resources. Future research will focus on enhancing this model through real-time climate data integration and exploring its potential application to diverse crops, further advancing sustainable resource management in agriculture.