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.
Authors
- Alireza Gohari (ORCID: https://orcid.org/0000-0002-6587-3836)
- Anandharuban Panchanathan (ORCID: https://orcid.org/0000-0003-4670-3257)
- Mojtaba Naghdyzadegan Jahromi (ORCID: https://orcid.org/0000-0002-1027-4318)
- Sahand Ghadimi (ORCID: https://orcid.org/0000-0002-6993-3701)
- Mojtaba Saboori (ORCID: https://orcid.org/0000-0002-9256-3024)
- Ali Torabi Haghighi (ORCID: https://orcid.org/0000-0002-5157-0156)
- Harri Koivusalo
- Alireza Sharifi
Institutions
- University of Hull (GB)
- University of Oulu (FI)
- Aalto University (FI)
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
- 0.00
Funders
- Academy of Finland
- Maa- ja Vesitekniikan Tuki Ry
- HORIZON EUROPE Framework Programme
- European Regional Development Fund