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Our study develops and tests a geostatistical technique for locally enhancing macro-scale rainfall–runoff simulations on the basis of observed streamflow data that were not used in calibration. We consider Tyrol (Austria and Italy) and two different types of daily streamflow data: macro-scale rainfall–runoff simulations at 11 prediction nodes and observations at 46 gauged catchments. The technique consists of three main steps: (1) period-of-record flow–duration curves (FDCs) are geostatistically predicted at target ungauged basins, for which macro-scale model runs are available; (2) residuals between geostatistically predicted FDCs and FDCs constructed from simulated streamflow series are computed; (3) the relationship between duration and residuals is used for enhancing simulated time series at target basins. We apply the technique in cross-validation to 11 gauged catchments, for which simulated and observed streamflow series are available over the period 1980–2010. Our results show that (1) the procedure can significantly enhance macro-scale simulations (regional LNSE increases from nearly zero to ≈0.7) and (2) improvements are significant for low gauging network densities (i.e. 1 gauge per 2000 km2).

Streamflow in south-central Chile (SCC, ∼ 37–42∘ S) is vital for agriculture, forestry production, hydroelectricity, and human consumption. Recent drought episodes have generated hydrological deficits with damaging effects on these activities. This region is projected to undergo major reductions in water availability, concomitant with projected increases in water demand. However, the lack of long-term records hampers the development of accurate estimations of natural variability and trends. In order to provide more information on long-term streamflow variability and trends in SCC, here we report findings of an analysis of instrumental records and a tree-ring reconstruction of the summer streamflow of the Río Imperial (∼ 37∘ 40′ S–38∘ 50′ S). This is the first reconstruction in Chile targeted at this season. Results from the instrumental streamflow record (∼ 1940 onwards) indicated that the hydrological regime is fundamentally pluvial with a small snowmelt contribution during spring, and evidenced a decreasing trend, both for the summer and the full annual record. The reconstruction showed that streamflow below the average characterized the post-1980 period, with more frequent, but not more intense, drought episodes. We additionally found that the recent positive phase of the Southern Annular Mode has significantly influenced streamflow. These findings agree with previous studies, suggesting a robust regional signal and a shift to a new hydrological scenario. In this paper, we also discuss implications of these results for water managers and stakeholders; we provide rationale and examples that support the need for the incorporation of tree-ring reconstructions into water resources management.

Drought is one of the most costly natural hazards in Europe. Due to its complexity, drought risk, the combination of the natural hazard and societal vulnerability, is difficult to define and challenging to detect and predict, as the impacts of drought are very diverse, covering the breadth of socioeconomic and environmental systems. Pan- European maps of drought risk could inform the elaboration of guidelines and policies to address its documented severity and impact across borders. This work (1) tests the capability of commonly applied hazard indicators and vulnerability factors to predict annual drought impact occurrence for different sectors and macro regions in Europe and (2) combines information on past drought impacts, drought hazard indicators, and vulnerability factors into estimates of drought risk at the pan-European scale. This “hybrid approach” bridges the gap between traditional vulnerability assessment and probabilistic impact forecast in a statistical modelling framework. Multivariable logistic regression was applied to predict the likelihood of impact occurrence on an annual basis for particular impact categories and European macro regions. The results indicate sector and macro region specific sensitivities of hazard indicators, with the Standardized Precipitation Evapotranspiration Index for a twelve month aggregation period (SPEI-12) as the overall best hazard predictor. Vulnerability factors have only limited ability to predict drought impacts as single predictor, with information about land use and water resources as best vulnerability-based predictors. (3) The application of the “hybrid approach” revealed strong regional (NUTS combo level) and sector specific differences in drought risk across Europe. The majority of best predictor combinations rely on a combination of SPEI for shorter and longer aggregation periods, and a combination of information on land use and water resources. The added value of integrating regional vulnerability information with drought risk prediction could be proven. Thus, the study contributes to the overall understanding of drivers of drought impacts, current practice of drought indicators selection for specific application, and drought risk assessment. JRC.E.1-Disaster Risk Management

The water resources and hydrologic extremes in Mediterranean basins are heavily influenced by climate variability. Modeling these watersheds is difficult due to the complex nature of the hydrologic response as well as the sparseness of hydrometeorological observations. In this work, we present a strategy to calibrate a distributed hydrologic model, known as TIN-based Real-time Integrated Basin Simulator (tRIBS), in the Rio Mannu basin (RMB), a medium-sized watershed (472.5 km2) located in an agricultural area in Sardinia, Italy. In the RMB, precipitation, streamflow and meteorological data were collected within different historical periods and at diverse temporal resolutions. We designed two statistical tools for downscaling precipitation and potential evapotranspiration data to create the hourly, high-resolution forcing for the hydrologic model from daily records. Despite the presence of several sources of uncertainty in the observations and model parameterization, the use of the disaggregated forcing led to good calibration and validation performances for the tRIBS model, when daily discharge observations were available. The methodology proposed here can be also used to disaggregate outputs of climate models and conduct high-resolution hydrologic simulations with the goal of quantifying the impacts of climate change on water resources and the frequency of hydrologic extremes within medium-sized basins.

Managed aquifer recharge (MAR) can be affected by many risks. Those risks are related to different technical and non-technical aspects of recharge, like water availability, water quality, legislation, social issues, etc. Many other works have acknowledged risks of this nature theoretically; however, their quantification and definition has not been developed. In this study, the risk definition and quantification has been performed by means of “fault trees” and probabilistic risk assessment (PRA). We defined a fault tree with 65 basic events applicable to the operation phase. After that, we have applied this methodology to six different managed aquifer recharge sites located in the Mediterranean Basin (Portugal, Spain, Italy, Malta, and Israel). The probabilities of the basic events were defined by expert criteria, based on the knowledge of the different managers of the facilities. From that, we conclude that in all sites, the perception of the expert criteria of the non-technical aspects were as much or even more important than the technical aspects. Regarding the risk results, we observe that the total risk in three of the six sites was equal to or above 0.90. That would mean that the MAR facilities have a risk of failure equal to or higher than 90 % in the period of 2–6 years. The other three sites presented lower risks (75, 29, and 18 % for Malta, Menashe, and Serchio, respectively).

Waters released from wastewater treatment plants (WWTPs) represent a relevant source of pharmaceuticals and personal care products to the aquatic environment, since many of them are not effectively removed by the treatment systems. The consumption of these products increased in the last decades and concerns have consequently risen about their possible adverse effects on the freshwater ecosystem. In this study, we present a simple, yet effective, analytical model of transport of contaminants released in surface waters by WWTPs. Transport of dissolved species is modeled by solving the advection dispersion reaction equation (ADRE) along the river network by using a Lagrangian approach. We applied this model to concentration data of five pharmaceuticals, diclofenac, ketoprofen, clarithromycin, sulfamethoxazole, and irbesartan, collected during two field campaigns, conducted in February and July 2015 in the Adige River, northeastern Italy. The model showed a good agreement with measurements and the successive application at the monthly timescale highlighted significant variations of the load due to the interplay between streamflow seasonality and variation of the anthropogenic pressure, chiefly due to the variability of touristic fluxes. Since the data required by the model are widely available, our model is suitable for large-scale applications.