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Plant Science Today (PST)

Research Articles

Vol. 12 No. 3 (2025)

Application of simulation-optimization techniques for Rabi crop planning in the Bargarh canal command of eastern India

DOI
https://doi.org/10.14719/pst.8843
Submitted
12 April 2025
Published
24-07-2025 — Updated on 31-07-2025
Versions

Abstract

The nation’s economic growth relies heavily on agriculture, which in turn depends on water resources, land and crops. Effective optimization and management of these water resources have become essential for sustainable agricultural practices, particularly in irrigated command areas. This study aims to develop a linear programming model for optimizing water resource allocation and crop selection in the Bargarh Canal Command Area (BCCA) to maximize farmers’ net returns. We analyzed the existing cropping patterns adopted by farmers and calculated the optimal areas for crop cultivation. Water requirements were assessed using the FAO’s CROPWAT model, while groundwater availability was modeled using the Groundwater Modeling System (GMS) with MODFLOW software. Linear programming was employed to optimize both water allocation and crop selection, considering constraints such as available cropland and water resources. Considering the prevailing cropping pattern, the net profit obtained in the Rabi season was 4673.18 million rupees and using linear optimization, the net profit was 4837.14 million rupees from the current cropping pattern. This indicates a significant increase in farmers’ income. The study examined water availability, crop water requirements and optimal cropping patterns within the BCCA, which covers approximately 130235 hectares irrigated by the Bargarh canal system. The temporal scope included analyzing Canal water availability over the approximately 100-day cropping period during Rabi 2023, as well as assessing groundwater conditions. The developed model serves as a valuable tool for policymakers and farmers, enabling them to make informed decisions that could lead to more sustainable and profitable agricultural practices in irrigated command areas.

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