Develops a framework for optimizing rainwater harvesting in boreal agriculture, suggesting resource-efficient solutions under drought conditions.
Climate change has intensified summer droughts, threatening crop production and demanding climate-smart solutions for agricultural water management. This study develops a computational framework for optimizing rainwater harvesting (RH) reservoir operations to enhance resource-use efficiency and climate resilience in boreal agriculture. The framework integrates a daily water balance simulation model with RH reservoir operation algorithms to evaluate storage system performance under climate variability. Applied to a Nordic river basin using 43 years of climate data (1981–2023) and crop-specific water demands for potato cultivation, the model simulates reservoir dynamics across capacities ranging from 0 to 550 m 3 /ha. The computational system processes daily inflows from catchment areas, crop evapotranspiration requirements, and storage constraints to quantify three performance metrics: deficit days, deficit volumes, and excess water discharge. Results demonstrate that climate-smart, small-scale reservoirs (50–200 m 3 /ha) reduce average water deficit days by over 90% and mitigate volume shortages by up to 95%, achieving high resource-use efficiency with minimal infrastructure. Mid-range capacities (200–400 m 3 /ha) achieve near-complete drought mitigation with 95–98% deficit reduction, representing optimal resource allocation for climate adaptation. Systems exceeding 400 m 3 /ha show diminishing performance gains, indicating inefficient resource investment. The optimization analysis identifies 200–430 m 3 /ha as the optimal capacity range balancing infrastructure investment and climate resilience. Spatial analysis reveals geographic variation in deficit patterns, with northern regions requiring 15–20% larger storage capacities for equivalent resource-use efficiency. The computational framework provides agricultural planners with a quantitative tool for designing decentralized, resource-efficient water storage infrastructure under climate change, advancing climate-smart reservoir operation modeling for boreal agricultural systems.
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Gohari et al. (2026) studied this question.
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