Probabilistic Trade‐Offs Analysis for Sustainable and Equitable Management of Climate‐Induced Water Risks

Baccour, S., Tilmant, A., Albiac Murillo, J., Espanmanesh, V., & Kahil, T. ORCID: https://orcid.org/0000-0002-7812-5271 (2025). Probabilistic Trade‐Offs Analysis for Sustainable and Equitable Management of Climate‐Induced Water Risks. Water Resources Research 61 (2) e2024WR038514. 10.1029/2024WR038514.

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Abstract

Pressures on water resources are fueling conflicts between sectors. This trend will likely worsen under future climate-induced water stress, jeopardizing food, energy and human water security in most arid and semi-arid regions. Probabilistic analysis using stochastic optimization modeling can characterize multi-sector vulnerabilities and risks associated with future water stress. This study identifies the probabilistic trade-offs between agricultural, urban and energy sectors in the Ebro Basin (Spain). Two intervention policies have been examined and compared: (a) agricultural priority, and (b) energy priority, for two planning horizons 2040–2070 and 2070–2100. Results show that the human water security goal is achieved under both intervention policies. However, the achievement of the food and energy security goals depends on the policy objectives and on the spatial location of irrigation schemes and hydropower plants, which result in different stream flows across the basin. The policy choice results in substantially different benefit gains and losses by sector and therefore by location. None of the sectoral production priority policy provides an equitable sharing of benefits among all sectors and locations under climate change, which is an important issue, because the success or failure of policy interventions would depend on the distribution of the gains and losses of benefits across the basin. Policy uptake by stakeholders would depend on reaching win-win outcomes where losers are compensated, while delivering acceptable levels of food, energy and human water security in large river basins. Information on the probabilistic trade-offs contributes to the design of water management strategies capable of addressing the multi-sector vulnerability.

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