This study analyses how indicators of water quality (thirteen physico-chemical variables) and drivers of change (i.e., monthly aggregated air temperature and streamflow, population density, and percentage of agricultural land use) coevolve in three large European river basins (i.e., Adige, Ebro, Sava) with different climatic, soil and water use conditions. Spearman rank correlation, Principal Component Analysis, and Mann-Kendall trend tests were applied to long-term time series of water quality data during the period 1990-2015 in order to investigate the relationships between water quality parameters and the main factors controlling them. Results show that air temperature, considered as a proxy of climatic change, has a significant impact, in particular in the Adige and Ebro: positive trends of water temperature and negative of dissolved oxygen are correlated with upward trends of air temperatures. The aquatic ecosystems of these rivers are, therefore, experiencing a reduction in oxygen, which may exacerbate in the future given the projected further increase in temperature. Furthermore, monthly streamflow has been shown to reduce in the Ebro, thereby reducing the beneficial effect of dilution, which appears evident from the observed upward patterns of chloride concentrations and electrical conductivity. Upward trends of chloride and biological oxygen demand in the Adige and Sava, and of phosphate in the Adige appears to be related to increasing human population density, whereas phosphates in the Sava and biological oxygen demand in the Ebro are highly correlated with agricultural land use, considered as a proxy of the impact of agricultural practises. The present study shows the complex relationships between drivers and observed changes in water quality parameters. Such analysis can represent, complementary to a deep knowledge of the investigated systems, a reliable tool for decision makers in river basin planning by providing an overview of the potential impacts on the aquatic ecosystem of the three basins.
Quantifying the effects of multiple stressors on Alpine freshwater ecosystems is challenging, due to the lack of tailored field campaigns for the contemporaneous measurement of hydrological, chemical and ecological parameters. Conducting exhaustive field campaigns is costly and hence most of the activities so far have been performed addressing specific environmental issues. An accurate analysis of existing information is therefore useful and necessary, to identify stressors that may act in synergy and to design new field campaigns. We present an extended review of available studies and datasets concerning the hydrological, chemical and ecological status of the Adige, which is the second longest river and the third largest river basin in Italy. The most relevant stressors are discussed in the light of the information extracted from a large number of studies. The detailed analysis of these studies identified that hydrological alterations caused by hydropower production are the main source of stress for the freshwater ecosystems in the Adige catchment. However, concurrent effects with other stressors, such as the release of pollutants from waste water treatment plants or from agricultural and industrial activities, have not been explored at depth, so far. A wealth of available studies address a single stressor separately without exploring their concurrent effect. It is concluded that a combination of extended experimental field campaigns, focusing on the coupled effects of multiple stressors, and modeling activities is highly needed in order to quantify the impact of the multifaceted human pressures on freshwater ecosystems in the Adige river.
Water resources are under pressure from multiple anthropogenic stressors such as changing climate, agriculture and water abstraction. This holds, in particular, for the Mediterranean region, where substantial changes in climate are expected throughout the 21st century. Nonetheless, little attention has been paid to linkages between long-term trends in climate, streamflow and water quality in Mediterranean river basins. In the present study, we perform a comparative analysis of recent trends in hydroclimatic parameters and nitrate pollution in three climatologically different Mediterranean watersheds (i.e., the Adige, Ebro and Sava River Basins). Mann-Kendall trend analyses of annual mean temperature, precipitation and streamflow (period 1971 to 2010) and monthly nitrate concentrations, mass fluxes and flow-adjusted concentrations (period 1996 to 2012) were performed in these river basins. Temperature is shown to have increased the most in the Ebro followed by the Sava, whereas minor increases are observed in the Adige. Precipitation presents, overall, a negative trend in the Ebro and a positive trend in both the Adige and Sava. These climatic trends thus suggest the highest risk of increasing water scarcity for the Ebro and the lowest risk for the Adige. This is confirmed by trend analyses of streamflow time series, which indicate a severe decline in streamflow for the Ebro and a substantial decline in the Sava, as opposed to the Adige showing no prevailing trend. Concerning surface water quality, nitrate pollution appears to have decreased in all study basins. Overall, these findings emphasize progressive reduction of water resources availability in river basins characterized by continental climate (i.e., Ebro and Sava). This study thus underlines the need for adapted river management in the Mediterranean region, particularly considering strong feedbacks between hydroclimatic trends, freshwater ecosystem services and water resources availability for agriculture, water supply and hydropower generation.
Assessing the accuracy of gridded climate data sets is highly relevant to climate change impact studies, since evaluation, bias correction, and statistical downscaling of climate models commonly use these products as reference. Among all impact studies those addressing hydrological fluxes are the most affected by errors and biases plaguing these data. This paper introduces a framework, coined Hydrological Coherence Test (HyCoT), for assessing the hydrological coherence of gridded data sets with hydrological observations. HyCoT provides a framework for excluding meteorological forcing data sets not complying with observations, as function of the particular goal at hand. The proposed methodology allows falsifying the hypothesis that a given data set is coherent with hydrological observations on the basis of the performance of hydrological modeling measured by a metric selected by the modeler. HyCoT is demonstrated in the Adige catchment (southeastern Alps, Italy) for streamflow analysis, using a distributed hydrological model. The comparison covers the period 1989–2008 and includes five gridded daily meteorological data sets: E‐OBS, MSWEP, MESAN, APGD, and ADIGE. The analysis highlights that APGD and ADIGE, the data sets with highest effective resolution, display similar spatiotemporal precipitation patterns and produce the largest hydrological efficiency indices. Lower performances are observed for E‐OBS, MESAN, and MSWEP, especially in small catchments. HyCoT reveals deficiencies in the representation of spatiotemporal patterns of gridded climate data sets, which cannot be corrected by simply rescaling the meteorological forcing fields, as often done in bias correction of climate model outputs. We recommend this framework to assess the hydrological coherence of gridded data sets to be used in large‐scale hydroclimatic studies.
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