Economic Optimization of Irrigation Decisions Using Water Productivity for Crop Selection

Despite decades of research, market volatility still hasn't been addressed, creating a gap between agronomic efficiency and economic viability. This study presents a decision-support framework to optimise irrigation water allocation by integrating Crop Water Productivity (CWP) with economic profitability. While traditional CWP focuses on biomass, our model incorporates fluctuating irrigation costs and market prices to calculate Net Profit per Cubic Meter of Water. The present study aims to address the critical gap between biophysical water use and financial viability by introducing a dynamic Economic-Water-Productivity (EWP) framework. In contradistinction to static models, our approach integrates stochastic market volatility with primary farm-level data, thereby enabling the quantification of the specific thresholds at which irrigation transitions from a yield-enhancer to a high-risk financial liability. Model was validated using primary data from 12 commercial farms in Western Transdanubia (2022–2024). The results show that maize exhibited the highest biological water productivity (e.g., 2.23 kg m⁻³) and the highest economic return in 2022 (€ 0.19 m⁻³). However, irrigation was not profitable in 2024 due to lower crop prices and higher costs. The analysis of the data set, which included wheat and soybeans, demonstrated that irrigation was economically non-viable in both years. Sensitivity analysis confirmed the model's robustness under price volatility scenarios of 20% and 40%. The proposed tool facilitates the prioritisation of irrigation based on direct economic efficiency, thereby providing a scalable solution for water-scarce agricultural regions. To reach the break-even point in 2024, a 22% increase in market price (to 0.209 €/kg) or a reduction in irrigation costs to 0.278 € m⁻³ would be required for maize. For soybeans, market prices would need to increase by 150% to reach the break-even threshold.