Computational reservoir operation framework for climate-smart agricultural water management under summer drought

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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Publication Details

Journal
Environmental Impact Assessment Review
Published
2026-06-25
DOI
https://doi.org/10.1016/j.eiar.2026.108572
Primary Topic
Hydrology and Watershed Management Studies
Type
article
Field-Weighted Citation Impact
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article

Computational reservoir operation framework for climate-smart agricultural water management under summer drought

Alireza Gohari, Anandharuban Panchanathan, Mojtaba Naghdyzadegan Jahromi, Sahand Ghadimi et al.
Environmental Impact Assessment Review
Hydrology and Watershed Management Studies
article

Computational reservoir operation framework for climate-smart agricultural water management under summer drought

Alireza Gohari, Anandharuban Panchanathan, Mojtaba Naghdyzadegan Jahromi, Sahand Ghadimi, Mojtaba Saboori, Ali Torabi Haghighi, Harri Koivusalo, Alireza Sharifi
article en

Abstract

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.

Environmental Impact Assessment ReviewVol. 121
University of Hull (GB), University of Oulu (FI), Aalto University (FI)
Academy of Finland, Maa- ja Vesitekniikan Tuki Ry, HORIZON EUROPE Framework Programme, European Regional Development Fund
Openalex Percentile: Top 13%
Hydrology and Watershed Management Studies
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