Climate change is anticipated to exacerbate the frequency, the intensity, and the duration of droughts, especially in Mediterranean countries. This might lead to more serious water scarcity episodes and fierce competition among water users. Are we really prepared to deal efficiently with droughts and water scarcity events? This paper sheds light on this question by reviewing the evolution of European drought management planning policy, recently developed scientific and technical advances, technical guidance documents, and an extensive number of journal papers. More specifically, Spain presents an ideal context to assess how drought risk has been historically addressed because this country has periodically suffered the impacts of intense droughts and water scarcity episodes, and has developed a long track record in water legislation, hydrological planning, and drought risk management strategies. The most recent Drought Management Plans (DMPs) were approved in December 2018. These include an innovative common diagnosis system that distinguishes droughts and water scarcity situations in terms of indicators, triggers, phases, and actions. We can conclude that DMP should be a live and active document able to integrate updated knowledge. The DMP needs also to set out a clear strategy in terms of water use priorities, drought monitoring systems, and measures in each river basin in order to avoid generalist approaches and possible misinterpretation of the DMP that could lead to increase existing and future conflicts.

Accurately forecasting streamflow values is essential to achieve an efficient, integrated water resources management strategy and to provide consistent support to water decision-makers. We present a simple, low-cost, and robust approach for forecasting monthly and yearly streamflows during the current hydrological year, which is applicable to headwater catchments. The procedure innovatively combines the use of well-known regression analysis techniques, the two-parameter Gamma continuous cumulative probability distribution function and the Monte Carlo method. Several model performance statistics metrics (including the Coefficient of Determination R2; the Root-Mean-Square Error RMSE; the Mean Absolute Error MAE; the Index of Agreement IOA; the Mean Absolute Percent Error MAPE; the Coefficient of Nash-Sutcliffe Efficiency NSE; and the Inclusion Coefficient IC) were used and the results showed good levels of accuracy (improving as the number of observed months increases). The model forecast outputs are the mean monthly and yearly streamflows along with the 10th and 90th percentiles. The methodology has been successfully applied to two headwater reservoirs within the Guadalquivir River Basin in southern Spain, achieving an accuracy of 92% and 80% in March 2017. These risk-based predictions are of great value, especially before the intensive irrigation campaign starts in the middle of the hydrological year, when Water Authorities have to ensure that the right decision is made on how to best allocate the available water volume between the different water users and environmental needs.

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