We evaluated different management alternatives to enhance potential water availability for agriculture under climate change scenarios. The management goal involved maximizing potential water availability, understood as the maximum volume of water supplied at a certain point of the river network that satisfies a defined demand, and taking into account specified reliability requirements. We focused on potential water availability for agriculture and assumed two types of demands: urban supply and irrigation. If potential water availability was not enough to satisfy all irrigation demands, management measures were applied aiming at achieving a compromise solution between resources and demands. The methodological approach consisted of estimation and comparison of runoff for current and future period under climate change effects, calculation of water availability changes due to changes in runoff, and evaluation of the adaptation choices that can modify the distribution of water availability, under climate change. Adaptation choices include modifying water allocation to agriculture, increasing the reservoir storage capacity, improving the efficiency of urban water use, and modifying water allocation to environmental flows. These management measures were evaluated at the desired points of the river network by applying the Water Availability and Adaptation Policy Analysis (WAAPA) model. We simulated the behavior of a set of reservoirs that supply water for a set of prioritized demands, complying with specified ecological flows and accounting for evaporation losses. We applied the methodology in six representative basins of southern Europe: Duero-Douro, Ebro, Guadalquivir, Po, Maritsa-Evros, and Struma-Strymon. While in some basins, such as the Ebro or Struma-Strymon, measures can significantly increase water availability and compensate for a fraction of water scarcity due to climate change, in other basins, like the Guadalquivir, water availability cannot be enhanced by applying the management measures analyzed, and irrigation water use will have to be reduced.

Recent trends suggest that streamflow discharge is diminishing in many rivers of Southern Europe and that interannual variability is increasing. This threatens to aggravate water scarcity problems that periodically arise in this region, because both effects will deteriorate the performance of reservoirs, decreasing their reliable yield. Reservoir storage is the key infrastructure to overcome variability and to enhance water availability in semiarid climates. This paper presents an analysis of the role of reservoir storage in preserving water availability under climate change scenarios. The study is focused on 16 major Southern European basins. Potential water availability was calculated in these basins under current condition and for 35 different climatic projections for the period 2070–2100. The results show that the expected reduction of water availability is comparable to the decrease of the mean annual flow in basins with large storage capacity. For basins with small storage, the expected reduction of water availability is larger than the reduction of mean annual flow. Additionally, a sensitivity analysis was carried out by replicating the analysis assuming variable reservoir volumes from 25% to 175% of current storage. The results show that increasing storage capacity attenuates the reduction of water availability and reduces its uncertainty under climate change projections. This feature would allow water managers to develop suitable policies to mitigate the impacts of climate change, thus enhancing the resilience of the system.

This study addresses the question of how to select the minimum set of storms that should be simulated each year in order to estimate an accurate flood frequency curve for return periods ranging between 1 and 1000 years. The Manzanares basin (Spain) was used as a study case. A continuous 100,000-year hourly rainfall series was generated using the stochastic spatial–temporal model RanSimV3. Individual storms were extracted from the series by applying the exponential method. For each year, the extracted storms were transformed into hydrographs by applying an hourly time-step semi-distributed event-based rainfall–runoff model, and the maximum peak flow per year was determined to generate the reference flood frequency curve. Then, different flood frequency curves were obtained considering the N storms with maximum rainfall depth per year, with 1 ≤ N ≤ total number of storms. Main results show that: (a) the degree of alignment between the calculated flood frequency curves and the reference flood frequency curve depends on the return period considered, increasing the accuracy for higher return periods; (b) for the analyzed case studies, the flood frequency curve for medium and high return period (50 ≤ return period ≤ 1000 years) can be estimated with a difference lower than 3% (compared to the reference flood frequency curve) by considering the three storms with the maximum total rainfall depth each year; (c) when considering only the greatest storm of the year, for return periods higher than 10 years, the difference for the estimation of the flood frequency curve is lower than 10%; and (d) when considering the three greatest storms each year, for return periods higher than 100 years, the probability of achieving simultaneously a hydrograph with the annual maximum peak flow and the maximum volume is 94%.

Adaptation of irrigation networks to climate change: Linking robust design and stakeholder contribution