Evidence Based Estimation of Macrodispersivity for Groundwater Transport Applications.

The scope of this work is to discuss the proper choice of macrodispersion coefficients in modeling contaminant transport through the advection dispersion equation (ADE). It is common to model solute concentrations in transport by groundwater with the aid of the ADE. Spreading is quantified by macrodispersivity coefficients, which are much larger than the laboratory observed pore-scale dispersivities. In the frame of stochastic theory, longitudinal macrodispersivity is related to the hydraulic conductivity spatial variability via its statistical moments (mean, variance, integral scales), which are generally determined by geostatistical analysis of field measurements. In many cases, especially for preliminary assessment of contaminant spreading, these data are not available and ad hoc values are adopted by practitioners. The present study aims at recommending dispersivity values based on a thorough analysis of tens of field experiments. Aquifers are classified as of weak, medium, and high heterogeneity and for each class a range of macrodispersivity values is recommended. Much less data are available for the transverse macrodispersivities, which are significantly smaller than the longitudinal one. Nevertheless, a few realistic values based on field data, are recommended for applications. Transport models using macrodispersivities can predict mean concentrations, different from the local ones. They can be used for estimation of robust measures, like plumes spatial moments, longitudinal mass distribution and breakthrough curves at control planes.

A catchment-scale model of river water quality by Machine Learning.

Water quality is a concern in most river basins worldwide due to the widespread release of pollutants which impacts the freshwater ecosystems. Exploring the relationships between drivers and water quality parameters at the regional scale is key in the identification of appropriate actions for the reduction of water pollution. Regional models are the appropriate tool to achieve this, though their development poses relevant challenges because of the complexity and non-linearity of such relationships. Among the available approaches, Machine Learning (ML) is promising because of its capability to detect complex nonlinear relationships and flexibility in the parameterization, which is learned from data. In this work, we developed regional models of water temperature, dissolved oxygen, arsenic, sulfate and chloride concentrations, as well as electrical conductivity, by using two ML algorithms, Random Forest and Deep feed-forward Neural Network, and compared their performances against the standard Linear Regression model. Our results indicate that the two ML algorithms are much more accurate models for such variables than the classical Linear Regression model, with Deep feed-forward Neural Network being the most effective in identifying the reciprocal importance of the drivers and capturing nonlinear relationships between drivers and water quality variables. Our analysis also revealed that the Julian day and year at which the sample was taken surrogate the air temperature in modeling water temperature and dissolved oxygen, with only a slight performance reduction. Arsenic, sulfate, and chloride show more complex behaviors in which geogenic and anthropogenic sources are intertwined. Dilution exerts a role chiefly for arsenic concentration, which suggests a non-uniform, in space, geogenic origin for this variable.

On the delay between water temperature and invertebrate community response to warming climate.

We evaluated the effect of global warming on invertebrate communities at high altitudes using data from the Careser system. We procured data on air temperature, which was obtained over 50 years at altitudes above 2600 m a.s.l., and data on water temperature, which was available for approximately 30 years. We sampled thrice in the past 20 years (2001, 2014, 2018) at three sampling sites (CR0-metakryal, CR1-hypokryal, CR2-glacio-rhithral) of the Careser glacier-fed stream and its main non-glacial tributary (CR1bis-krenal). Warmer climates were observed in the last decade compared to the 1980s, with a mean maximum summer air temperature (mTmax) increase of 1.7 °C at 2642 m a.s.l. and 1.8 °C at 2858 m a.s.l. Compared to air temperatures, the rise in water temperature was delayed by approximately 20 years; water mTmax started to increase in 2003, reaching 8.1 °C at 2642 m a.s.l. and 2.4 °C at 2858 m a.s.l in the year 2020. The invertebrate community exhibited a delayed response approximately 13 years from the water warming; there was a sequential increase in the number of taxa, Shannon diversity, and after 17 years, functional diversity. In the kryal sites, taxonomical and functional diversity changed more consistently than in the glacio-rhithral site in the same period, due to the arrival of taxa that were previously absent upstream and bearers of entirely new traits. Progressive taxonomical homogenisation was evident with decreasing glacial influence, mainly between glacio-rhithral and krenal sites. The numbers of Diamesa steinboecki, an insect that was adapted to the cold, declined in summer (water mTmax >6 °C and air mTmax >12 °C). This study highlights the mode and time of response of stream invertebrate communities to global warming in alpine streams and provides guidelines for analysing changes in the stream invertebrate communities of other glacial systems in alpine regions.

A Comparison of Six Transport Models of the MADE-1 Experiment Implemented With Different Types of Hydraulic Data.

Six conceptually different transport models were applied to the macrodispersion experiment (MADE)-1 field tracer experiment as a first major attempt for model comparison. The objective was to show that complex mass distributions in heterogeneous aquifers can be predicted without calibration of transport parameters, solely making use of structural and flow data. The models differ in their conceptualization of the heterogeneous aquifer structure, computational complexity, and use of conductivity data obtained from various observation methods (direct push injection logging, DPIL, grain size analysis, pumping tests and flowmeter). They share the same underlying physical transport process of advection by the velocity field solely. Predictive capability is assessed by comparing results to observed longitudinal mass distributions of the MADE-1 experiment. The decreasing mass recovery of the observed plume is attributed to sampling and no physical process like mass transfer is invoked by the models. Measures like peak location and strength are used in comparing the modeled and measured plume mass distribution. Comparison of models reveals that the predictions of the solute plume agree reasonably well with observations, if the models are underlain by a few parameters of close values: mean velocity, a parameter reflecting log-conductivity variability, and a horizontal length scale related to conductivity spatial correlation. The robustness of the results implies that conservative transport models with appropriate conductivity upscaling strategies of various observation data provide reasonable predictions of plumes longitudinal mass distribution, as long as key features are taken into account.

Global riverine nitrous oxide emissions: The role of small streams and large rivers.

Nitrous oxide, N2O, is the leading cause of stratospheric ozone depletion and one of the most potent greenhouse gases (GHG). Its concentration in the atmosphere has been rapidly increasing since the green revolution in the 1950s and 1960s. Riverine systems have been suggested to be an important source of N2O, although their quantitative contribution has been estimated with poor precision, ranging between 32.2 and 2100 GgN2O - N/yr. Here, we quantify reach scale N2O emissions by integrating a data-driven machine learning model with a physically-based upscaling model. The application of this hybrid modeling approach reveals that small streams (those with widths less than 10 m) are the primary sources of riverine N2O emissions to the atmosphere. They contribute nearly 36 GgN2O - N/yr; almost 50% of the entire N2O emissions from riverine systems (72.8 Gg2O - N/yr), although they account for only 13% of the total riverine surface area worldwide. Large rivers (widths wider than 175 m), such as the main stems of the Amazon River (~ 6 GgN2O - N/yr), the Mississippi River (~ 2 GgN2O - N/yr), the Congo River (~ 1 GgN2O - N/yr) and the Yang Tze River (~ 0.7 GgN2O - N/yr), only contribute 26% of global N2O emissions, which primarily originate from their water column. This study identifies, for the first time, near-global N2O emission and NO3 removal hot spots within watersheds and thus can aid the development of local- to global-scale management and mitigation strategies for riverine systems with respect to N2O emissions. The presented framework can be extended to quantified biogeochemical, besides N2O emissions, processes at the global scale.

Priority and emerging organic microcontaminants in three Mediterranean river basins: Occurrence, spatial distribution, and identification of river basin specific pollutants.

There is a worldwide growing use of chemicals by our developed, industrialized, and technological society. More than 100,000 chemical substances are thus commonly used both by industry and households. Depending on the amount produced, physical-chemical properties, and mode of use, many of them may reach the environment and, notably, the aquatic receiving systems. This may result in undesirable and harmful side-effects on both the human and the ecosystem's health. Mediterranean rivers are largely different from Northern and Central European rivers in terms of hydrological regime, climate conditions (e.g. air temperature, solar irradiation, precipitation), and socio-economics (e.g. land use, tourism, crop types, etc.), with all these factors leading to differences in the relative importance of the environmental stressors, in the classes and levels of the pollutants found and their environmental fate. Furthermore, water scarcity might be critical in affecting water pollution because of the lowered dilution capacity of chemicals. This work provides raw chemical data from different families of microcontaminants identified in three selected Mediterranean rivers (the Sava, Evrotas, and Adige) collected during two sampling campaigns conducted in 2014 and 2015 in three different matrices, namely, water, sediments, and biota (fish). More than 200 organic micropollutants were analyzed, including relevant groups like pharmaceuticals, personal care products, perfluorinated compounds, pesticides, pyrethroid insecticides, flame retardants, and persistent organic pollutants. Data obtained were summarized with some basic statistics for all compound families and matrices analyzed. Observed occurrence and spatial patterns were interpreted both in terms of compound physical-chemical properties and local environmental pressures. Finally, their spatial distribution was examined and their ecotoxicological risk in the water phase was assessed. This allowed locating, at each basin, the most polluted sites ("hot spots") and identifying the respective river basin specific pollutants (RBSPs), prioritizing them in terms of the potential ecotoxicological risk posed to the aquatic ecosystems.

Power law scaling model predicts N2O emissions along the Upper Mississippi River basin.

Nitrous oxide (N2O) is widely recognized as one of the most important greenhouse gases, and responsible for stratospheric ozone destruction. A significant fraction of N2O emissions to the atmosphere is from rivers. Reliable catchment-scale estimates of these emissions require both high-resolution field data and suitable models able to capture the main processes controlling nitrogen transformation within surface and subsurface riverine environments. Thus, this investigation tests and validates a recently proposed parsimonious and effective model to predict riverine N2O fluxes with measurements taken along the main stem of the Upper Mississippi River (UMR). The model parameterizes N2O emissions by means of two denitrification Damköhler numbers; one accounting for processes occurring within the hyporheic and benthic zones, and the other one within the water column, as a function of river size. Its performance was assessed with several statistical quantitative indexes such as: Absolute Error (AE), Nash-Sutcliffe efficiency (NSE), percent bias (PBIAS), and ratio of the root mean square error to the standard deviation of measured data (RSR). Comparison of predicted N2O gradients between water and air (ΔN2O) with those quantified from field measurements validates the predictive performance of the model and allow extending previous findings to large river networks including highly regulated rivers with cascade reservoirs and locks. Results show the major role played by the water column processes in contributing to N2O emissions in large rivers. Consequently, N2O productions along the UMR, characterized by regulated flows and large channel size, occur chiefly within this surficial riverine compartment, where the suspended particles may create anoxic microsites, which favor denitrification.

Evaluation of homogenization methods for seasonal snow depth data in the Austrian Alps, 1930-2010.

Despite the importance of snow in alpine regions, little attention has been given to the homogenization of snow depth time series. Snow depth time series are generally characterized by high spatial heterogeneity and low correlation among the time series, and the homogenization thereof is therefore challenging. In this work, we present a comparison between two homogenization methods for mean seasonal snow depth time series available for Austria: the standard normal homogeneity test (SNHT) and HOMOP. The results of the two methods are generally in good agreement for high elevation sites. For low elevation sites, HOMOP often identifies suspicious breakpoints (that cannot be confirmed by metadata and only occur in relation to seasons with particularly low mean snow depth), while the SNHT classifies the time series as homogeneous. We therefore suggest applying both methods to verify the reliability of the detected breakpoints. The number of computed anomalies is more sensitive to inhomogeneities than trend analysis performed with the Mann-Kendall test. Nevertheless, the homogenized dataset shows an increased number of stations with negative snow depth trends and characterized by consecutive negative anomalies starting from the late 1980s and early 1990s, which was in agreement with the observations available for several stations in the Alps. In summary, homogenization of snow depth data is possible, relevant and should be carried out prior to performing climatological analysis.

Convenient use of electrical conductivity measurements to investigate hydrological processes in Alpine headwaters.

Developing effective hydrological models for streamflow generation in Alpine catchments is challenging due to the inherent complexity of the intertwined processes controlling water transfer from hillslopes to streams and along the river network. Over the past decades, studies have proposed complementing traditional hydrological information with environmental tracer data, e.g. stable isotopes or electrical conductivity (EC), for different purposes such as the separation of streamflow components or the estimation of catchment mean residence time. In particular EC has been applied in Alpine environments mainly for hydrograph separation but also, more recently, considered as a possible proxy for streamflow (Q) prediction. The reason is simple: EC data loggers are convenient because of their relative low cost, easiness of installation and low maintenance, unlike traditional water stage gauges. However, EC time series require careful interpretation since electrical conductivity is influenced by a number of geochemical processes not always introduced in the analysis since these can be difficult to parametrize. Likewise, the relationship between EC and Q is very complex because it is characterized by hysteresis loops and often site specific. This study shows how the continuous monitoring of EC in Alpine catchments can be useful specifically for: hydrograph separation, including a proper quantification of uncertainty; process understanding of catchment functioning through the interpretation of hysteresis loops and time lags between EC and Q signals; and finally, water discharge estimation through calibrated functional EC-Q relationships. We discuss advantages and limitations of the use of EC in hydrology and provide information to encourage its use in studies dealing with streamflow generation dynamics in snow-dominated catchments.

A Critical Analysis of Transverse Dispersivity Field Data.

Transverse dispersion, or tracer spreading orthogonal to the mean flow direction, which is relevant e.g, for quantifying bio-degradation of contaminant plumes or mixing of reactive solutes, has been studied in the literature less than the longitudinal one. Inferring transverse dispersion coefficients from field experiments is a difficult and error-prone task, requiring a spatial resolution of solute plumes which is not easily achievable in applications. In absence of field data, it is a questionable common practice to set transverse dispersivities as a fraction of the longitudinal one, with the ratio 1/10 being the most prevalent. We collected estimates of field-scale transverse dispersivities from existing publications and explored possible scale relationships as guidance criteria for applications. Our investigation showed that a large number of estimates available in the literature are of low reliability and should be discarded from further analysis. The remaining reliable estimates are formation-specific, span three orders of magnitude and do not show any clear scale-dependence on the plume traveled distance. The ratios with the longitudinal dispersivity are also site specific and vary widely. The reliability of transverse dispersivities depends significantly on the type of field experiment and method of data analysis. In applications where transverse dispersion plays a significant role, inference of transverse dispersivities should be part of site characterization with the transverse dispersivity estimated as an independent parameter rather than related heuristically to longitudinal dispersivity.

Particle bound pollutants in rivers: Results from suspended sediment sampling in Globaqua River Basins.

Transport of hydrophobic pollutants in rivers such as polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs) and heavy metals is often facilitated by suspended sediment particles, which are typically mobilized during high discharge events. Suspended sediments thus represent a means of transport for particle related pollutants within river reaches and may represent a suitable proxy for average pollutant concentrations estimation in a river reach or catchment. In this study, multiple high discharge/turbidity events were sampled at high temporal resolution in the Globaqua River Basins Sava (Slovenia, Serbia), Adige (Italy), and Evrotas (Greece) and analysed for persistent organic pollutants such as PAHs (polycyclic aromatic hydrocarbons) or PCBs (polychlorinated biphenyls) and heavy metals. For comparison, river bed sediment samples were analysed as well. Further, results are compared to previous studies in contrasting catchments in Germany, Iran, Spain, and beyond. Overall results show that loadings of suspended sediments with pollutants are catchment-specific and relatively stable over time at a given location. For PAHs, loadings on suspended particles mainly correlate to urban pressures (potentially diluted by sediment mass fluxes) in the rivers, whereas metal concentrations mainly display a geogenic origin. By cross-comparison with known urban pressure/sediment yield relationships (e.g. for PAHs) or soil background values (for metals) anthropogenic impact - e.g. caused by industrial activities - may be identified. Sampling of suspended sediments gives much more reliable results compared to sediment grab samples which typically show a more heterogeneous contaminant distribution. Based on mean annual suspended sediment concentrations and distribution coefficients of pollutants the fraction of particle facilitated transport versus dissolved fluxes can be calculated.

Hydrogeophysical characterization and monitoring of the hyporheic and riparian zones: The Vermigliana Creek case study.

The hyporheic and riparian zones are critical domains in a river ecosystem since they mediate the interactions between surface water and groundwater. These domains are generally strongly heterogeneous and difficult to access; yet their characterization and monitoring still rely mostly on hard-to-perform invasive surveys that provide only point information. These well-known issues, however, can be overcome thanks to the application of minimally invasive methods. In this paper, we present the results of the hydrogeophysical characterization of the Vermigliana Creek's hyporheic and riparian zones, performed at an experimental site in the Adige catchment, northern Italy, by means of electrical resistivity tomography (ERT), distributed temperature sensing (DTS), and hydrological modeling. A major advancement is given by the placement of electrodes and of an optical fiber in horizontal boreholes at some depth below the river bed, put in place via directional drilling. The results of this static and dynamic (time-lapse) geophysical characterization identify the presence of two subdomains (the sub-riverbed and the left and right banks) and define the water flow and solute dynamics. The ERT information is then used, together with other hydrological data, to build a 3D subsurface hydrological model (driven mainly by the watercourse stage variations) that is calibrated against local piezometric information. A solute transport model is then developed to reproduce the variations observed in the dynamic geophysical monitoring. The results show good agreement between ERT data and the model outcome. In addition, the transport model is also consistent with the temperature data derived from DTS, even though some slight discrepancies show that the heat capacity of the solid matrix and heat conduction cannot be totally neglected.

High Resolution Assessment of Spatio-Temporal Changes in O2 Concentration in Root-Pathogen Interaction.

Fusarium wilt, caused by the fungus Fusarium oxysporum f. sp. lycopersici (Fol), is one of the most destructive soil-borne diseases of tomatoes. Infection takes place on the roots and the process starts with contact between the fungus and the roots hairs. To date, no detailed studies are available on metabolic activity in the early stages of the Fol and tomato root interaction. Spatial and temporal patterns of oxygen consumption could provide new insights into the dynamics of early colonization. Here, we combined planar optodes and spatial analysis to assess how tomato roots influence the metabolic activity and growth patterns of Fol. The results shows that the fungal metabolism, measured as oxygen consumption, increases within a few hours after the inoculation. Statistical analysis revealed that the fungus tends to growth toward the root, whereas, when the root is not present, the single elements of the fungus move with a Brownian motion (random). The combination of planar optodes and spatial analysis is a powerful new tool for assessing temporal and spatial dynamics in the early stages of root-pathogen interaction.

Uncertainty of modelled flow regime for flow-ecological assessment in Southern Europe.

Sustainable water basin management requires characterization of flow regime in river networks impacted by anthropogenic pressures. Flow regime in ungauged catchments under current, future, or natural conditions can be assessed with hydrological models. Developing hydrological models is, however, resource demanding such that decision makers might revert to models that have been developed for other purposes and are made available to them ('off-the-shelf' models). In this study, the impact of epistemic uncertainty of flow regime indicators on flow-ecological assessment was assessed at selected stations with drainage areas ranging from about 400 to almost 90,000km2 in four South European basins (Adige, Ebro, Evrotas and Sava). For each basin, at least two models were employed. Models differed in structure, data input, spatio-temporal resolution, and calibration strategy, reflecting the variety of conditions and purposes for which they were initially developed. The uncertainty of modelled flow regime was assessed by comparing the modelled hydrologic indicators of magnitude, timing, duration, frequency and rate of change to those obtained from observed flow. The results showed that modelled flow magnitude indicators at medium and high flows were generally reliable, whereas indicators for flow timing, duration, and rate of change were affected by large uncertainties, with correlation coefficients mostly below 0.50. These findings mirror uncertainty in flow regime indicators assessed with other methods, including from measured streamflow. The large indicator uncertainty may significantly affect assessment of ecological status in freshwater systems, particularly in ungauged catchments. Finally, flow-ecological assessments proved very sensitive to reference flow regime (i.e., without anthropogenic pressures). Model simulations could not adequately capture flow regime in the reference sites comprised in this study. The lack of reliable reference conditions may seriously hamper flow-ecological assessments. This study shows the pressing need for improving assessment of natural flow regime at pan-European scale.

Driver detection of water quality trends in three large European river basins.

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.

River ecosystem processes: A synthesis of approaches, criteria of use and sensitivity to environmental stressors.

River ecosystems are subject to multiple stressors that affect their structure and functioning. Ecosystem structure refers to characteristics such as channel form, water quality or the composition of biological communities, whereas ecosystem functioning refers to processes such as metabolism, organic matter decomposition or secondary production. Structure and functioning respond in contrasting and complementary ways to environmental stressors. Moreover, assessing the response of ecosystem functioning to stressors is critical to understand the effects on the ecosystem services that produce direct benefits to humans. Yet, there is more information on structural than on functional parameters, and despite the many approaches available to measure river ecosystem processes, structural approaches are more widely used, especially in management. One reason for this discrepancy is the lack of synthetic studies analyzing river ecosystem functioning in a way that is useful for both scientists and managers. Here, we present a synthesis of key river ecosystem processes, which provides a description of the main characteristics of each process, including criteria guiding their measurement as well as their respective sensitivity to stressors. We also discuss the current limitations, potential improvements and future steps that the use of functional measures in rivers needs to face.

Role of surface and subsurface processes in scaling N2O emissions along riverine networks.

Riverine environments, such as streams and rivers, have been reported as sources of the potent greenhouse gas nitrous oxide ([Formula: see text]) to the atmosphere mainly via microbially mediated denitrification. Our limited understanding of the relative roles of the near-surface streambed sediment (hyporheic zone), benthic, and water column zones in controlling [Formula: see text] production precludes predictions of [Formula: see text] emissions along riverine networks. Here, we analyze [Formula: see text] emissions from streams and rivers worldwide of different sizes, morphology, land cover, biomes, and climatic conditions. We show that the primary source of [Formula: see text] emissions varies with stream and river size and shifts from the hyporheic-benthic zone in headwater streams to the benthic-water column zone in rivers. This analysis reveals that [Formula: see text] production is bounded between two [Formula: see text] emission potentials: the upper [Formula: see text] emission potential results from production within the benthic-hyporheic zone, and the lower [Formula: see text] emission potential reflects the production within the benthic-water column zone. By understanding the scaling nature of [Formula: see text] production along riverine networks, our framework facilitates predictions of riverine [Formula: see text] emissions globally using widely accessible chemical and hydromorphological datasets and thus, quantifies the effect of human activity and natural processes on [Formula: see text] production.

Contamination sources and distribution patterns of pharmaceuticals and personal care products in Alpine rivers strongly affected by tourism.

Knowledge regarding the impact of tourism on the emergence of pharmaceuticals and personal care products (PPCPs) in Alpine river waters is limited and scarce. Therefore, a study on the occurrence patterns and spatiotemporal variability of 105 PPCPs in an Alpine river basin located in the Trentino-Alto Adige region (North-Eastern Italy) has been conducted. We observed that the total concentration of analyzed PPCPs was generally higher in all sampling sites during winter than in the summer. The analysis of tourist data revealed that during both sampling campaigns the number of tourists was lower in the downstream sites in comparison with the upstream area of the basin (Val di Sole). Particularly, sampling sites located near important tourist resorts have shown the highest abundance of the PPCPs during winter, being analgesics/anti-inflammatories, antihypertensives and antibiotics the most abundant pharmaceutically active compounds (PhACs). Diclofenac showed the highest concentration amongst PhACs, reaching concentrations up to 675ngL-1 in the sampling site situated downstream of the Tonale wastewater treatment plant (WWTP). Antihypertensives were found at concentrations >300ngL-1, while antibiotics were quantified up to 196ngL-1, respectively. Amongst personal care products (PCPs), the most abundant compound was octyl-dimethyl-p-aminobenzoic acid (ODPABA) with concentrations reaching up to 748ngL-1 in the sampling site situated within the Rotaliana district. In general, concentrations and detection frequencies were higher in water than in the sediment samples. The most frequently detected PhACs in sediments from both sampling campaigns were antibiotics, while amongst PCPs in sediments, octocrylene (OC) showed the highest concentration in both sampling campaigns. As a result, this study highlights the potential impact of tourism on the water quality of the Alpine aquatic ecosystems.

An alternative smooth particle hydrodynamics formulation to simulate chemotaxis in porous media.

Chemotaxis, the microorganisms autonomous motility along or against the concentration gradients of a chemical species, is an important, yet often neglected factor controlling the transport of bacteria through saturated porous media. For example, chemotactic bacteria could enhance bioremediation by directing their own motion to residual contaminants trapped in low hydraulic conductive zones of contaminated aquifers. The aim of the present work is to develop an accurate numerical scheme to model chemotaxis in saturated porous media and other advective dominating flow systems. We propose to model chemotaxis by using a new class of meshless Lagrangian particle methods we recently developed for applications in fluid mechanics. The method is based on the Smooth Particle Hydrodynamics (SPH) formulation of (Ben Moussa et al., Int Ser Numer Math, 13(1):29-62, 2006), combined with a new Weighted Essentially Non-Oscillatory (WENO) reconstruction technique on moving point clouds in multiple space dimensions. The purpose of this new numerical scheme is to fully exploit the advantages of SPH among traditional mesh-based and mesh-free schemes and to overcome drawbacks related to the use of standard SPH for modeling chemotaxis in porous media. First, we test the new scheme against analytical reference solutions. Then, under the assumption of complete mixing at the Darcy scale, we perform two-dimensional conservative solute transport simulations under steady-state flow conditions, to show the capability of the proposed new scheme to model chemotaxis.

Hydroclimatic and water quality trends across three Mediterranean river basins.

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.