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In Germany, river monitoring for tritium started in the early 1970s. Today this monitoring network consists of 50 stations and includes stable isotopes. The stable isotope time series to the end of 2021 are at least four years and for some stations up to 30 years long. Daily river water samples were collected during an extraordinary dry season from October 2018 until end of January 2019 from six selected stations of the Rhine and five stations of the Elbe basin. The most dominating stable isotope effects in river water are the seasonal and altitude effects, but also a continental effect is visible. The isotopes indicate snow and ice melt contributions in the Rhine and Danube during the summer months and a consecutive dilution of these signals by mixing with tributary rivers. Close to the coasts in northern Germany, stable isotope patterns reflect influence of seawater and tides. Daily patterns during the dry season 2018/2019 surprisingly do not exhibit extreme changes but rather trends of enhanced groundwater contribution. Long-term continual data across scales are important for comparing and identifying hydrological processes in German river basins of different size and mean catchment altitudes, and highlight the benefits of a co-organized national network.

Bayesian inference has become the most popular approach to uncertainty assessment in vadose zone hydrological modeling. By combining prior information with observations and model predictions, it became popular among hydrologists as it enables them to infer parameter posterior distributions, verify model adequacy, and assess the model's predictive uncertainty. In particular, the posterior distribution is frequently the variable of interest for modelers as it describes the epistemic uncertainty of model parameters conditioned on measurements. Gradient-free Markov-Chain Monte Carlo (MCMC) ensemble samplers based on Differential Evolution (DE) or Affine Invariant (AI) strategies have been used to approximate the posterior distribution, which is frequently anisotropic and correlated in vadose zone-related problems. However, a rigorous benchmark of different MCMC algorithms to provide guidelines for their application in vadose zone hydrological model calibration is still missing. In this study, we elucidate the behavior of MCMC ensemble samplers by performing an in-depth comparison of four samplers that use AI moves or DE-based strategies to approximate the target density. Two Rosenbrock distributions, and one synthetic and one actual case study focusing on the inverse estimation of soil hydraulic parameters using HYDRUS-1D, are used to compare algorithms in different dimensions. The analysis reveals that AI-based samplers are immune to affine transformations of the target density, which instead double the autocorrelation time for DE-based samplers. This behavior is reiterated in the synthetic scenario, for which AI-based algorithms outperform DE-based strategies. However, this performance gain disappears when the number of soil parameters increases from 7 to 16, with both samplers exhibiting poor acceptance rates, which are not improved by increasing the number of chains from 50 to 200 or by mixing different strategies.

The rainfall-runoff process transforms a precipitation input to a catchment into runoff output and is an important indicator for river water quality and quantity. Since runoff events are comprised of precipitation event water and stored pre-event water of the catchment, exploring the event and pre-event components of runoff events using the stable isotopes of water (δ18O, δ2H) and two-component and ensemble isotopic hydrograph separation may further our insights into overall catchment behaviour and the origin of water. The aim of this study is to investigate the origin of water for different streamflow gauges in a small agricultural catchment that represent different runoff generation mechanisms. The analysis is performed at the Hydrological Open Air Laboratory (HOAL) in Austria, which is a 66 ha experimental catchment dominated by agricultural land use. One of the main features of this research catchment is that several tributaries of the catchment representing different runoff generation mechanisms are gauged. Two-component and ensemble isotopic hydrograph separations (for both δ18O and δ2H) are conducted for three streamflow gauges (the catchment’s inlet and outlet and a tile drainage system) for multiple events in the warm periods of 2013-2018. The results of the two methods are compared and discussed for different runoff generation mechanisms.

Groundwater recharge is a key component of the hydrologic cycle, yet its direct measurement is difficult. An alternative is its inverse estimation with a combination of physically based numerical models and soil water observations. However, simulated water fluxes are affected by model predictive uncertainty which are often not considered when simulating and predicting groundwater recharge rates. Therefore, the objective of this study was to use of long-term soil water content measurements at 14 locations from the Austrian soil water monitoring program to quantify and compare local, potential groundwater recharge rates, their temporal variability, and predict future changes in potential groundwater recharge for different climate scenarios. Observations were coupled with a Bayesian probabilistic framework to calibrate the model HYDRUS-1D and assess the effect of model predictive uncertainty on simulated recharge fluxes. Estimated annual potential recharge rates ranged from 44 mm/a to 1319 mm/a with a relative uncertainty (95% interquantile range/median) in the estimation between 1-39%. Recharge rates decreased longitudinally, with high rates and lower seasonality at western sites and low rates with high seasonality and extended periods without recharge at the southeastern and eastern sites of Austria. Higher recharge rates and lower actual evapotranspiration were related to sandy soils. Future recharge predictions at the median remained close to past rates, except for sites in the East, where they increased. In general, predictions varied drastically between different climate models and emission scenarios, especially for the summer months. Across all projections, an increase in winter recharge at the western sites was predicted, due to higher temperatures with less snow accumulation and/or higher amounts of winter precipitation, followed by decreasing recharge rates in spring. Decreasing tendencies in groundwater recharge were stronger at western sites and at higher altitudes, with longer drought periods lasting until later within the calendar year. Uncertainty in recharge prediction was largely dominated by the difference in climate projections, only at the dry sites in the East and for shorter time periods, soil hydraulic parameter uncertainties played a role.

The travel time of precipitation entering a catchment and leaving it as streamflow varies according to the flow paths it takes, with fast travel times posing a high risk to river water quality. However, investigating influences on travel times is challenging due to the complex water flow through heterogeneous landscapes. Recent studies investigated the fraction of streamflow younger than approximately three months (Fyw) using multi-year data (long-term Fyw) or one-year calculation windows to investigate its time-variability (time-variable Fyw). Nonetheless, the influences on time-variable Fyw and the demarcation between long-term and time-variable are not clear yet. Here, we investigated the long-term, the time-variable, and the Fyw derived from an exponential TTD model of nine major catchments in Central Europe and compared them to catchment characteristics and hydrometeorological variables. Additionally, one- to eight-year calculation windows were used and its impact on the variability of time-variable Fyw was investigated. All three methods of estimating Fyw led to similar results, indicating spatial organization of water flow in Central Europe. Spatial analysis further indicated a negative relationship between Fyw and catchment altitude. Contradicting and lacking spatiotemporal relationships to other investigated variables pointed to possibly unknown, region-specific influences on Fyw. With increasing calculation window size, the variability of time-variable Fyw results decreased. Long-term Fyw depended on the method used to define “long-term”, and many time series related factors, beside the actual target of investigation, i.e., catchment water flow, impacted Fyw. This finding points to difficulties in comparability of studies and catchments when using different window sizes, and we thus recommend future studies to calculate long-term Fyw using all data and one- to several-year time-variable Fyw to facilitate comparability.

Determining the processes that drive streamflow generation and catchment-scale transport of nutrients and pollutants by water is one of the challenges of modern hydrology. In the last decades, substantial knowledge has been gained from high-frequency and high-resolution measurements of tracers to track water movements within a hydrological system. For example, the stable isotopes of oxygen (d18O) and hydrogen (d2H) have been widely used to disentangle the contributions of different runoff generation mechanisms by modeling water travel and residence times. However, quantifying the effects of catchment internal factors for similar or different transit time distributions, particularly in characteristically complex and heterogeneous catchments, remains a challenge. Here we test different shapes for age selection functions (StorAge Selection) of individual distinct storage components (e.g., the root zone, groundwater) of the agricultural Hydrological Open Air Laboratory (HOAL) catchment in Petzenkirchen, Austria. The HOAL has a variety of runoff generation mechanisms, including overland flow, wetlands, and tile drains, as well as high-resolution tracer and hydrological data that allows for broad storage-discharge relationship testing. The main goal of this study is to estimate the transit time distributions associated with varying fluxes from these components (e.g., overland flow, groundwater recharge) to learn about catchment internal streamflow generation processes. Water flow is modeled with a water age balance model and are replaced by selecting the appropriate transfer functions. Testing different age selection functions for various storage components of the catchment will provide a better understanding of catchment dynamics under different environmental conditions, allowing for better calibration of catchment-scale water and nutrient transport models.

A few low-frequent but extreme rainfall events generate substantial erosion amounts and, as a result, land degradation negatively affects soil health and agricultural productivity. Determining rainfall erosivity (from small to extreme events) that drive soil erosion will improve our knowledge and understanding of extreme erosion processes and our ability to develop and adapt adequate soil protection strategies. This study aims to analyze rainfall erosivity characteristics across Austria‘s main agricultural production zones using long-term (from 27 to 82 years) with high-resolution (5-minutes) rainfall data from 27 rain gauges. Erosive rainfall characteristics such as rainfall amount, event duration, and the maximum 30-minute intensity were investigated, and typical rainfall types were assessed through a clustering approach based on the k-means algorithm. Results identified three dominant types (clusters) of erosive rainfalls across Austria's agricultural areas. Seasonal distribution analysis showed that the predominant erosive events, characterized by short duration and high intensities, occur during the summer months from June to August. In contrast, the long-duration and low rainfall-intensity events are evenly distributed throughout the year. The spatial distribution of rainfalls related to the largest rainfall erosivities showed a pronounced occurrence in the southeastern pre-alpine areas. Knowledge of the occurrence of erosive rainfall events in space and time eventually supports the implementation of locally adapted Soil Conservation (SC) practices in Austria.

Weather-extreme events are increasingly common due to climate change, with longer periods of drought and periods of strong rainfall. Drought periods are a problem in agriculture with several crops suffering from qualitative and quantitative yield reduction depending on the crop growth stage. Sugar beet (Beta Vulgaris) makes up 20% of sugar production worldwide and is the main source of sugar in temperate regions, with a recent increase in its use for biofuel production. The search for drought-resistant varieties of sugar beet with lower water requirements is expanding, however substantial variability in drought resistance regarding yield and quality has not been found so far. The goal of this study was to develop strategies to improve yield security in sugar beet cultivation under low water availability conditions. Therefore, two field experiments were established at sites representative of Austrian sugar beet production (Oberhausen, Marchfeld; Guntersdorf, Weinviertel) over the course of two years, 2020 and 2021. The experiments involved combining breeding strategies (variety selection) with agronomic approaches (soil management, land cover, irrigation, fertilization) to investigate the sugar beet's response to water stress and assess the performance of different sugar beet varieties, leading to a more climate-resilient sugar beet crop. Direct methods of measuring soil hydraulic properties (e.g. via soil moisture sensors) and plant properties (e.g. stomata density and conductance) with stable isotope analysis for carbon and water were combined. As a result, a significant yield increase was found in irrigated plots. Nitrogen fertilization had a detrimental effect when applied extensively. A yield increase was obtained by soil coverage with wooden chips in both years and sites. Furthermore, the choice of variety also played an essential role, especially regarding the trade-off between drought resistance and yield.

In our ACRP funded project EROS-A we aim at a comprehensive analysis of the erosive energy of rainfall, estimated soil loss, and reported damage using statistical and process-based methods. In this particular study, we evaluate the return periods of erosive rainfall events at 26 meteorological stations in Austria. The main focus is on daily cumulative rainfall and the maximum 30-min rainfall intensity (I30) as these were identified as key parameters for rainfall erosivity assessment. The extreme value series were obtained using both the Annual Maxima Series (AMS) and Peak Over Threshold (POT) approach, in order to assess which of the methods will be most accurate. The assumptions of stationarity and independence of the extreme value series were carefully checked using statistical trend and independence tests and no significant deviations were found.Generalized extreme value (GEV) and generalized Pareto (GPD) probability distributions were fitted using L-moment and maximum likelihood procedures. The GEV distribution is suited for AMS or block maxima data, whereas the GPD is suited for the POT series. For the obtained GEV and GPD models we examined extreme events with return periods of 2, 5, 10, 25, 50, and 100 years. We found that threshold selection is crucial for the POT, with diagnostic tools (such as mean residual life plots) not being fully decisive. Finally sensitivity analysis was performed where convergence of the fitted GPD to the GEV (AMS approach) helped determining robust thresholds for the GPD. The results show that the POT approach for daily cumulative precipitation is the most accurate in 69% of the cases and the AMS approach in 8% of the cases (different return periods and stations), while they have similar performance in 23% of the cases. Similar results are obtained for I30, were the success rates are 80% for the POT, 8% for the AMS and 12% for similar performance. In the next step, we will extend frequency analysis to a regional context, in order to map extreme rainfall erosivity across main agricultural production zones in Austria.

Stable isotopes (δ18O) and tritium (3H) are frequently used as tracers in environmental sciences to estimate age distributions of water. However, it has previously been argued that seasonally variable tracers, such as δ18O, generally and systematically fail to detect the tails of water age distributions and therefore substantially underestimate water ages as compared to radioactive tracers, such as 3H. In this study for the Neckar river basin in central Europe and based on a >20-year record of hydrological, δ18O and 3H data, we systematically scrutinized the above postulate. This was done by comparing water age distributions inferred from δ18O and 3H with a total of 12 different model implementations, including lumped parameter sine-wave (SW) and convolution integral models (CO) as well as integrated hydrological models in combination with SAS-functions (IM-SAS).We found that, indeed, water ages inferred from δ18O with commonly used SW and CO models are with mean transit times (MTT) ~ 1 – 2 years substantially lower than those obtained from 3H with the same models, reaching MTTs ~ 10 years. In contrast, several implementations of IM-SAS models did not only allow simultaneous representations of stream flow as well as δ18O and 3H stream signals, but water ages inferred from δ18O with these models were with MTTs ~ 16 years much higher than those from SW and CO models and similar to those inferred from 3H, which suggested MTTs ~ 15 years. Characterized by similar parameter posterior distributions, in particular for parameters that control water age, IM-SAS model implementations individually constrained with δ18O or 3H observations, exhibited only limited differences in the magnitudes of water ages in different parts of the models as well as in the temporal variability of TTDs in response to changing wetness conditions. This suggests that both tracers lead to comparable descriptions of how water is routed through the system. These findings provide evidence that allowed us to reject the hypothesis that δ18O as a tracer generally and systematically “cannot see water older than about 4 years” and that it truncates the corresponding tails in water age distributions, leading to underestimations of water ages. Instead, our results provide evidence for a broad equivalence of δ18O and 3H as age tracers for systems characterized by MTTs of at least 15 – 20 years.Overall, this study demonstrates that previously reported underestimations of water ages are most likely not a result of the use of δ18O or other seasonally variable tracers per se. Rather, these underestimations can be largely attributed to choices of model approaches and complexity not considering hydrological next to tracer aspects. We therefore advocate to avoid the use of this model type in combination with seasonally variable tracers if possible, and to instead adopt SAS-based or comparable model formulations.

Urban shallow groundwater is highly impacted in terms of hydrogeology and water quality by anthropogenic activities and infrastructure, such as heating and cooling, surface sealing, leaking sewage pipes, and underground buildings. For a sustainable management of urban water resources, a better understanding of biogeochemical processes and its dynamics on a spatial and temporal scale in the urban subsurface is needed. So far, data sets including a critical minimum number of key parameters and an appropriate resolution in space and time have often been missing. Here, we introduce a multi-tracer approach applied to assess the shallow aquifers in Vienna. Water samples were collected twice, in autumn 2021 and spring 2022, respectively, from 150 groundwater wells in the city limits of Vienna. A comprehensive set of parameters (e.g. major ions, nutrients, heavy metals, water and nitrate stable isotopes) were analyzed to evaluate the spatial and seasonal variations in water origin and quality. Statistical analysis revealed that driving factors influencing groundwater quality include aquifer properties, interactions between groundwater-surface water, and redox conditions. A combined interpretation of conservative tracers indicated zones influenced by surface water - groundwater interactions that also influenced the water chemistry. Microbial anaerobic processes govern groundwater quality. In particular, contamination of nitrate from septic water and manure is locally reduced by denitrification, as proven by compound-specific isotope analysis, improving water quality. At the same time, other anaerobic processes, such as iron and manganese reduction, sulfate reduction, and methanogenesis deteriorate water quality. Finally, groundwater temperatures, up to 27°C, were observed close to urban underground infrastructure, hinting at subsurface buildings and surface sealing as stressors in shallow groundwater. In conclusion, our high resolution spatial sampling with the large set of parameters will not only allow a better understanding of groundwater quality dynamics, but also allows to evaluate effects to groundwater biodiversity and develop predictive mathematical models.

Alpine regions are important as “water towers” in regional water supply of clean groundwaters due to their increased precipitation rates and their unspoiled environment. However, they are often characterised by complex geology structures, covered by down-sliding glacio-fluvial sediments. Groundwater recharge conditions and mean transit times (MTTs) are fundamental components of mountain watershed hydrological systems. Here, we used measurements of stable water isotopes of precipitation, pore water, surface and groundwater. In addition, measurements of environmental age tracers (222Rn, CFCs, 3H, 3He, 4He and 14C) were performed to investigate groundwater MTTs from springs in glacio-limnic sediments (20 m) located along a mountainous hillslope (1,400-800 m) within the Subersach watershed near Sibratsgfäll, Bregenzer Wald, Austria. The near surface spring waters contain 3H and CFCs in excess. The deeper artesian well samples contain 3H and CFCs, in addition to elevated terrigenic 4He and low 14C values, suggesting a mixture of waters characterised by residence times that are modern (70 years). We show that binary-mixing MTT models with distinct young and old fractions are needed to explain the full suite of environmental tracers, further supporting the importance of groundwater mixing processes.The vertical unsaturated infiltration in silt/sand dominated glacio-lacustrine sediments were estimated by seasonal variation of 2H/18O-isotopes in pore-water to be 1-4 m/year approximately. Precipitation in the Flysch dominated area at higher altitudes is transported partly as mountain bloc recharge and ascends into the glacial sediments, indicated by temperatures 2-3° C higher than the mean surface temperature. The MTTs of the shallow groundwater (20 m) artesian wells in the western part are dominated by MTT older than 70 years.The research project “Understanding of Extreme Climatological Impacts from Hydrogeological 4D Modelling” (EXTRIG) was funded by the Austrian Academy of Sciences.

Anomalous transport processes are frequently observed in radial flow to wells in highly heterogeneous aquifers. This is generally related to the presence of preferential flow pathways that bypass the sediment matrix, thus leading to the formation of fast flow channels, whose magnitude depends on the geological entropy of the system. Tracer tests can be effectively combined with laboratory or field-scale experimental campaigns to understand better the interlinkage between heterogeneity and preferential flow, and to distinguish hydraulically active and inactive regions. Despite considerable past research efforts, these mechanisms are only partially understood. To advance the current understanding, we study transport processes in a laboratory-built highly heterogeneous aquifer under radial flow conditions. The experimental device (200 x 200 x 100 cm) consists of 2527 randomly distributed cells (10 x 10 x 5 cm) of 12 different porous mixtures assembled in 7 layers to form a 35 cm-deep aquifer. This particularly design is intended to maximize the geological entropy of the aquifer, which is equipped with 37 piezometers placed in a radial configuration at different distances from the central (pumping) well. Multiple conservative tracer tests were conducted by injecting a mixture of deuterated water (D2O) and Potassium Bromide (KBr) into different piezometers, and then by analysing the resulting Breakthrough Curves (BTCs) at the central pumping well. BTCs reveals features peculiar of anomalous transport, such as non-symmetry, early peaks and tailing, which depend on the injecting location. This, jointly with the incomplete mass recovery after 48 hours, suggests the simultaneous presence of fast flow in highly conductive regions, which exchange mass with quasi-immobile portions of the aquifer. By dealing with tests individually, it is seen that curves for the two tracers have a similar trend, with almost perfect overlap in the part before the peaks. Differences in the tailing of the BTCs between the two tracers, that exhibit different molecular diffusion coefficients, indicate the importance of diffusion mechanism taking place in the porous matrix.

High correlations between river stages and groundwater levels are often seen as an indicator of surface water influence on groundwater. However, such a simple correlation does not necessarily provide information about the nature of said influence, i.e. whether the groundwater hydraulic head only follows the changes in river level or if there is also significant inflow of surface water into the aquifer.In two large sampling campaigns (early summer and late autumn) covering 45 groundwater and 11 river sites stretching from the alpine region to the foreland basins of the Mur river, Austria using surface water-borne wastewater indicators, stable isotopes of water and selected microbial indicators [1], we show that the influence of surface water intrusion into the shallow aquifer often can be traced hundreds of meters away from the river. Still, at some wells in close vicinity to the river (< 50m) with high correlation of water levels (R > 0.9), isotope data and wastewater indicators hint at no direct surface water influence.However, one could argue that even at these locations it is plausible that a flood event in the river might reverse flow temporarily, signs of which will not be found by irregular sampling at an inappropriate temporal scale, as the river-borne substances will be quickly flushed out of the shallow aquifer due to the generally effluent conditions. Operating a high-resolution UV-Vis sensor, monitoring nitrate and other key components, we show that direct river influence in the given case still is unlikely. [1] https://doi.org/10.5194/egusphere-egu21-13

The temporal origin of root water uptake and drainage provides insights into the impact of natural and anthropogenic disturbances on plant resilience and aquifer vulnerability. In-situ and virtual tracer experiments provide information on rainfall partitioning and transit times, which help to enhance the understanding of the hydrological response of a soil-plant-atmosphere continuum (SPAC) to climate variability and contaminant transport. A virtual tracer experiment was carried out in a 150-cm-thick soil lysimeter planted with winter rye in Austria. Water flow and tracer transport dynamics were simulated in the SPAC using HYDRUS-1D, previously calibrated with hydrochemical measurements. The root water uptake (τR) and drainage (τD) transit times (τ) were assessed by identifying arrival times when a prescribed percentage of the tracer mass breakthrough curves was reached. The estimates of τR and τD were compared to those derived from a particle tracking algorithm that simulates the particle trajectories subject to convective transport. The tracer-based arrival times were in close agreement with those determined using particle tracking when 50% of the tracer output flux was reached. On average, it took 19 or 234 days for water originating from rainfall in the growing season to be taken up by roots (21%) or exit as drainage (36%), respectively. In contrast, in the dormant season, 10% of rainfall water was taken up by roots after 245 days, while 79% became drainage after 241 days. The results from each daily event can be aggregated at any desired temporal resolution to investigate the effects of climate seasonality on water balance and timing. The temporal origin of water can be explored in other plots using the standard guidelines proposed in this study.

Understanding the reasons why a certain combination of precipitation event and catchment wetness condition causes a particular runoff response serves as the basis for a sustainable water resources management. Runoff responses at the catchment scale are highly variable in space and time due to numerous influencing factors, e.g., topography, land use, geology, and climatic conditions. Yet, despite previous studies having investigated these interdependencies, it remains difficult to differentiate between the various impacts on the runoff response and to determine which driving factors dominate under which conditions. Assuming that similar precipitation and catchment wetness (e.g. in terms of soil water content or groundwater level) lead to similar runoff responses, reoccurring patterns of these hydrological flux and state variables may be useful to assess the causes for similar or different runoff responses. Therefore, we compared precipitation and catchment wetness conditions and classified them as hydrologically similar if they lead to a similar runoff response. In this study, the similarity of runoff responses was assessed for the 38.5 ha, partly forested Wüstebach catchment in Western Germany using the goodness-of-fit (GOF) criteria Nash-Sutcliffe-Efficiency and Volumetric Efficiency. If the GOF exceeded a pre-defined threshold, the runoff responses were classified as similar and grouped together. Subsequently, for similar runoff responses, the corresponding rainfall and wetness conditions were compared calculating the Spearman’s rank correlation coefficient and descriptive statistics. A total of 22 similar out of 73 runoff events were identified for the Wüstebach catchment over a period of nearly 12 years and classified into seven groups with the largest group including in total eight events. Results show that for similar runoff responses in this representative group, soil water content as well as groundwater levels in the riparian zone are well correlated with r = 0.815 and r = 0.840, respectively, indicating a possible dominant control on runoff responses. However, rainfall patterns show overall weak correlations (r = 0.406), implying that the precipitation temporal pattern control on the runoff response might be limited for these types of runoff events in the Wüstebach catchment. In a next step, the here defined hydrologically similar precipitation and wetness conditions will be searched in the data of the Wüstebach catchment to compare the corresponding runoff responses, and hydro-meteorological variables will be used to explain similar or different runoff responses.

Summer periods of warm weather become longer and hotter causing “Urban Heat Islands” in large cities. Rising temperatures do not stop at the surface, but migrate into the underground, where infrastructure – such as sewage and district heating systems, buildings and shallow geothermal energy systems for cooling – amplifies the increase of groundwater temperatures. In order to be able to quantify this ongoing process and predict future temperature developments, a sound data basis is necessary. As of now, only groundwater temperature measurements have been available for different depth (one-point or multiple depth measurements) and time intervals (varying from two weeks to months) at a limited number of wells within the shallow urban aquifers in Vienna. To increase the spatial information content, the goal of this study was to measure groundwater temperature and level within the urban shallow aquifers of Vienna in two extensive field campaigns for more than 800 wells and to analyze those data statisticallyTo document the warmest and coldest conditions, measurements took place in one week each in October (2021) and April (2022). In total, groundwater temperatures in 1 m depth intervals and groundwater level were measured at 812 locations. Out of these ones, at 150 wells, water temperature was measured in pumped water. The average value of the profile equals best the pumped groundwater and thus represents the average aquifer temperature. According to our data analysis, the groundwater temperatures in Vienna vary between 6.9 °C and 30.6 °C. The highest temperatures were detected in close proximity to possible heat sources and a rapid drop in temperature with increasing distance could be demonstrated.Based on the collected data, temperature maps for both measurement dates and for different depth-intervals were derived, and display the underground urban heat islands in Vienna. The temperature maps enable the estimation of the potential for sustainable heating and cooling with groundwater in the capital of Austria.Together with historic long-term temperature data, trend analyses will be performed to allow a prognosis of thermal changes in the groundwater. The results, together with an extensive analysis of the groundwater chemistry and ecology, will feed into the development of a catalogue of measures for authorities and policymakers. Intention of the included recommendations is to counteract further groundwater warming and to ensure an efficient and sustainable use of groundwater for heating and cooling. The guidelines will therefore not only contribute to cooling the groundwater, but also to decarbonize the heating and cooling supply of Vienna.

Tillage is an important management practice that can be necessary to loosen the soil and allow for seeding and aims at enhancing productivity. However, the long-term effects of a particular tillage action on soil health depend on the local soil characteristics and differ amongst soils. The main aim of our study was to evaluate the possible effects of various physical, chemical, and biological soil quality indicators in dependence of three different tillage practices: Conventional Tillage (CT), Mulch Tillage (MT), and No-Till (NT). A long-term tillage experiment that started in 1994 in Mistelbach, Lower Austria, was comprehensively sampled in 2002 and 2021. The research attempts to fill the knowledge gap in the long-term soil health changes due to shifting conventional tillage. To evaluate the soil health changes over time, we assessed the impact of the three tillage practices on selected soil quality indicators in the 0-20 cm layer and below 20 cm, which we determined as being below the plowing depth. The "Soil Management Assessment Framework" (SMAF) procedure was applied to assess and compare the overall soil quality. Twenty-one indicators were selected to compare and evaluate the long-term effects of the three tillage systems (a.); fifteen indicators were used to investigate the temporal changes since the last monitoring (b.); thirteen indicators were selected to assess overall soil quality (c.). The study shows that the tillage practices and temporal conditions significantly affected soil organic carbon (SOC) content. The SOC amount in the 0-20 cm layer was twice as high under no-till (31.2 t/ha) compared to conventional tillage (15.3 t/ha). The SMAF reveals that NT increased SOC content and enhanced soil's physical indicators, such as available soil water, porosity, and coarse pores in the 0-20 cm layer. We found soil quality improvements with MT and NT in the 0-20 cm layer; however, the SMAF also indicates that the soil quality was better below 20 cm in 2021 compared to 2002, independent of the tillage practice. According to our results, conservation tillage practices (such as MT and NT) enhanced overall soil quality, particularly the physical (available soil water, coarse pores) and soil biological indicators, mainly SOC.

Groundwater recharge is a key component of the hydrological cycle, yet its direct measurement is complex and often difficult to achieve. An alternative is its inverse estimation through a combination of numerical models and transient observations from distributed soil water monitoring stations. However, an often neglected aspect of this approach is the effect of model predictive uncertainty on simulated water fluxes. In this study, we made use of long-term soil water content measurements at 14 locations from the Austrian soil water monitoring program to quantify and compare local potential groundwater recharge rates and their temporal variability. Observations were coupled with a Bayesian probabilistic framework to calibrate the HYDRUS-1D model and assess the effect of model predictive uncertainty on long-term simulated recharge fluxes. Estimated annual potential recharge rates ranged from 44 to 1319 mm a−1 with a relative uncertainty (95 % interquantile range/median) in the estimation of between 1 % and 39 %. Recharge rates decreased longitudinally, with high rates and lower seasonality at western sites and low rates with high seasonality and extended periods without recharge at the southeastern and eastern Austrian sites. Higher recharge rates and lower actual evapotranspiration were related to sandy soils; however, climatic factors had a stronger influence on estimated potential groundwater recharge than soil properties, underscoring the vulnerability of groundwater recharge to the effects of climate change.

ZusammenfassungInfiltrationsprozesse spielen eine wichtige Rolle bei der Entstehung von pluvialem Hochwasser. Ob Oberflächenabfluss generiert wird, hängt unter anderem von bodenhydraulischen Eigenschaften ab. Ein zukünftiger verbesserter Schutz vor pluvialem Hochwasser basiert somit auf einem verbesserten Prozessverständnis zu Infiltrationsprozessen in Böden, um Bedingungen und Parameter zu identifizieren, die zu pluvialem Hochwasser führen und die entscheidend für die Vorhersage von Ereignissen sind. Deshalb wurde das Modell KINEROS für eine globale und lokale Sensitivitätsanalyse verwendet, um Parameter zu identifizieren, die den Oberflächenabfluss am stärksten beeinflussen und um den Oberflächenabfluss in Abhängigkeit vom anfänglichen Bodensättigungsgrad für verschiedene Niederschlagsmengen an 14 Standorten in Österreich zu berechnen. Die globale Sensitivitätsanalyse hat gezeigt, dass vor allem die Faktoren gesättigte hydraulische Leitfähigkeit und Oberflächenrauheit sowohl das Gesamtabflussvolumen als auch dessen Spitze maßgeblich beeinflussen. Die Verteilung und Intensität des Niederschlags hat ebenfalls einen großen Einfluss auf den Abflussprozess. Demgegenüber haben die Hangneigung und die anfängliche Bodensättigung einen moderaten Einfluss. Auch wenn der Sättigungsgrad weniger entscheidend war, zeigt die lokale Sensitivitätsanalyse eine nichtlineare Beziehung zwischen dem anfänglichen Sättigungsgrad des Bodens und der Gesamtabflussmenge, besonders bei den mittel- und hochdurchlässigen Böden. Es konnte klar gezeigt werden, dass hydrologische Modelle in Verbindung mit detaillierter, statistischer Analyse ein wichtiges Instrument zur Analyse und Bewertung der hydrologischen Prozesse und deren Unsicherheiten auf der Plotskala sind.

We present field data on the effects of heavy rainfall after drought on the mobility of glyphosate and redox conditions in a clayey floodplain soil. By applying glyphosate together with deuterated water as conservative tracer in combination with time resolved

Sustainable water management in semi-arid agriculture practices requires quantitative knowledge of water fluxes within the soil-vegetation-atmosphere system. Therefore, we used stable-isotope approaches to evaluate evaporation (Ea), transpiration (Ta), and groundwater recharge (R) at sites in Senegal's Groundnut basin and Ferlo Valley pasture region during the pre-monsoon, monsoon, and post-monsoon seasons of 2021. The approaches were based upon (i) the isothermal evaporation model (for quantifyingEa); (ii) water and isotope mass balances (to partitionEaandTafor groundnut and pasture); and (iii) the piston displacement method (for estimating R).Ealosses derived from the isothermal evaporation model corresponded primarily to Stage II evaporation, and ranged from 0.02 to 0.09 mm d−1in the Groundnut basin, versus 0.02–0.11 mm d−1in Ferlo. At the groundnut site,Earates ranged from 0.01 to 0.69 mm d−1;Tawas in the range 0.55–2.29 mm d−1; and theTa/ETaratio was 74%–90%. At the pasture site, the ranges were 0.02–0.39 mm d−1forEa; 0.9–1.69 mm d−1forTa; and 62–90% forTa/ETa. TheETavalue derived for the groundnut site via the isotope approach was similar to those from eddy covariance measurements, and also to the results from the previous validated HYDRUS-1D model. However, the HYDRUS-1D model gave a lowerTa/ETaratio (23.2%). The computed groundwater recharge for the groundnut site amounted to less than 2% of the local annual precipitation. Recommendations are made regarding protocols for preventing changes to isotopic compositions of water in samples that are collected in remote arid regions, but must be analysed days later. The article ends with suggestions for studies to follow up on evidence that local aquifers are being recharged via preferential pathways.

Groundwater is a hidden part of the water cycle due to its subterranean nature but is highly connected to rivers, lakes, and wetlands. In this chapter, we review the physical basis of aquifers (groundwater reservoirs), their hydrodynamics, and hydrogeological parameters (porosity and permeability) that collectively define different types of aquifers. We explore the relationships between groundwater and surface water and define how aquifers function in terms of (1) groundwater flow and transport of solutes and particulate matter; (2) groundwater age, which affects ecosystem processes, physical and biological reactions, and groundwater resources and (3) modeling of the above processes. We also consider the chemical composition of groundwater and the origin of compounds and water-rock interactions that influence water quality. Finally, we discuss chemical and nutrient fluxes in aquifers and biogeochemical reactions, with a focus on oxygen and nitrogen.

Stable isotopes (δ18O) and tritium (3H) are frequently used as tracers in environmental sciences to estimate the age distributions of water. However, it has previously been argued that seasonally variable tracers, such as δ18O, generally and systematically fail to detect the tails of water age distributions and therefore substantially underestimate water ages as compared to radioactive tracers, such as 3H. In this study for the Neckar river basin in central Europe and based on a >20-year record of hydrological, δ18O, and 3H data, we systematically scrutinized the above postulate together with the potential role of spatial aggregation effects to exacerbate the underestimation of water ages. This was done by comparing water age distributions inferred from δ18O and 3H with a total of 12 different model implementations, including lumped parameter sine-wave (SW) and convolution integral models (CO) as well as integrated hydrological models in combination with SAS-functions (IM-SAS). We found that, indeed, water ages inferred from δ18O with commonly used SW and CO models are with mean transit times (MTT) ~ 1–2 years substantially lower than those obtained from 3H with the same models, reaching MTTs ~ 10 years. In contrast, several implementations of IM-SAS models did not only allow simultaneous representations of stream flow as well as δ18O and 3H stream signals, but water ages inferred from δ18O with these models were with MTTs ~ 16 years much higher than those from SW and CO models and similar to those inferred from 3H, which suggested MTTs ~ 15 years. Characterized by similar parameter posterior distributions, in particular for parameters that control water age, IM-SAS model implementations individually constrained with δ18O or 3H observations, exhibited only limited differences in the magnitudes of water ages in different parts of the models as well as in the temporal variability of TTDs in response to changing wetness conditions. This suggests that both tracers lead to comparable descriptions of how water is routed through the system. These findings provide evidence that allowed us to reject the hypothesis that δ18O as a tracer generally and systematically “cannot see water older than about 4 years” and that it truncates the corresponding tails in water age distributions, leading to underestimations of water ages. Instead, our results provide evidence for a broad equivalence of δ18O and 3H as age tracers for systems characterized by MTTs of at least 15–20 years. The question to which degree aggregation of spatial heterogeneity can further adversely affect estimates of water ages remains unresolved as the lumped and distributed implementations of the IM-SAS model provided inconclusive results. Overall, this study demonstrates that previously reported underestimations of water ages are most likely not a result of the use of δ18O or other seasonally variable tracers per se. Rather, these underestimations can be largely attributed to choices of model approaches and complexity not considering hydrological next to tracer aspects. Given the additional vulnerability of SW and CO model approaches in combination with δ18O to substantially underestimate water ages due to spatial aggregation and potentially other, still unknown effects, we, therefore, advocate to avoid the use of this model type in combination with seasonally variable tracers if possible, and to instead adopt SAS-based or comparable model formulations.

Considering three sites under different climate conditions (arid, semiarid, and subhumid), this study aims to use the vadose-zone water stable isotope profiles to estimate the groundwater recharge rate. High-resolution vertical subsurface soil sampling along the vadose zone of the investigated sites was conducted. The collected samples were analysed to determine their stable isotopes ratios (δ2H and δ18O) that were used in the piston displacement method for estimating recharge. Annual recharge rates of 0.2% (±0.1%), 2.5 %, and 18% of the total annual precipitation were obtained for the arid, semiarid, and subhumid sites, respectively. Recharge rates at the semiarid and subhumid sites are comparable to those previously estimated using water balance-based methods. The recharge rate at the arid site is lower than that previously estimated for that site using the water budget-based method, revealing difficulties in applying the piston displacement method under an arid regime.

Groundwater recharge is a key component of the hydrological cycle, yet its direct measurement is complex and often difficult to achieve. An alternative is its inverse estimation through a combination of numerical models and transient observations from distributed soil water monitoring stations. However, an often neglected aspect of this approach is the effect of model predictive uncertainty on simulated water fluxes. In this study, we made use of long-term soil water content measurements at 14 locations from the Austrian soil water monitoring program to quantify and compare local, potential groundwater recharge rates and their temporal variability. Observations were coupled with a Bayesian probabilistic framework to calibrate the model HYDRUS-1D and assess the effect of model predictive uncertainty on long-term simulated recharge fluxes. Estimated annual potential recharge rates ranged from 44 mm a-1 to 1319 mm a-1 with a relative uncertainty (95 % interquantile range/median) in the estimation between 1–39 %. Recharge rates decreased longitudinally, with high rates and lower seasonality at western sites and low rates with high seasonality and extended periods without recharge at the southeastern and eastern sites of Austria. Higher recharge rates and lower actual evapotranspiration were related to sandy soils; however, climatic factors had a stronger influence on estimated potential groundwater recharge than soil properties, underscoring the vulnerability of groundwater recharge to the effects of climate change.

This study focuses on coastal aquifers subject to uncontrolled land use development by investigating the combined effects of seawater intrusion and nitrate contamination. The research is undertaken in a Mediterranean coastal agricultural area (Plain of the El-Nil River, Algeria), where water resources are heavily impacted by anthropogenic activities. A multi-tracer approach, integrating hydrogeochemical and isotopic tracers (δ

Coastal environments around the globe provide services and support to the population. However, they are frequently impacted by human-based activities in addition to seawater intrusion problems. These lowland groundwater resources are exposed to a significant amount and types of pollutants, the most significant of which is nitrate. Tracking and quantifying the sources of nitrate that pollute surface and groundwater systems can be challenging without the use of environmental tracers such as nitrate isotopes. This study explored how changes in regional flow paths impact the nitrogen concentrations and origin of pollution in coastal waters during high tides. Water samples were collected from surface (rivers, lagoon and Atlantic shore) and groundwater (wells and boreholes) systems along the east coast of Côte d'Ivoire during the boreal summer (October). Water samples were analysed for major ions, dissolved nitrogen concentrations, coliforms presence/amount, as well as dual nitrate isotopes (δ15N-NO3- and δ18O-NO3-). Bayesian isotope mixing models were conducted to estimate the contributions of potential main sources (wastewater, seawater, atmospheric deposition, and agrochemicals). In some areas, nitrate inputs were found likely coming from wastewater sources. Nitrate concentration in groundwater was high at several sites. Some groundwater samples (n = 7) exceeded the WHO drinking water limit of nitrate concentrations of 50 mg/l, and most groundwater samples had high levels of total coliforms (>500 cfu/100ml). However, great isotope variation found in both surface and subsurface water samples suggested a spatial differential impact and origin of nitrate pollution, which is in agreement with the modelling. These water resources are the primary source of water for 53% of the local population and an alternative domestic water source for 97%, which highlights the importance of determining the main pollution sources for sustainable development. We expected that groundwater may have been better protected from nitrate pollution than lagoon surface water during wet periods, but this might have not been the case.

Alpine regions are becoming more sensitive to climate change and to understand the hydrogeological processes that follow extreme climatic events (flooding, drought, heavy precipitation and fast snow melt), the hydrologic conditions and geologic realities need to be understood. Our research project “Understanding of Extreme Climatological Impacts from Hydrogeological 4D Modelling” (EXTRIG; funded by the Austrian Academy of Sciences) contributes to this challenge by applying an innovative interdisciplinary approach in an Austrian alpine research area (Sibratsgfäll, Vorarlberg) with a catchment of 5 km² situated at an altitude between 800 and 1.400 m based on a cooperation between hydrogeologists, meteorologists, social scientists and the local population.This poster study emphasizes on preliminary results of applied hydrogeological methods conducted between 2019 and 2021 to understand the local water cycle.To determine surface discharge, radar monitoring stations was installed at each of the four main streams, flowing into the main river beneath the village. Calibration of the results was conducted with several salt dilution measurements. Additional salt dilution measurements helped to estimate diffuse surface and groundwater discharge into the main river. Precipitation was measured in Sibratsgfäll (906m) and compared with precipitation measurements of two nearby weather stations and with past precipitation measurements of the area since 1990. Evapotranspiration was calculated as ET0 with the Hargreaves method in two different approaches, one using the air temperature reconstructed from surrounding weather stations, the other using temperature measurements from the monitoring station in Sibratsgfäll. The resulting data was used to calculate the amount of water infiltrating into the ground via water balance calculation. The yearly precipitation from December 2019 including November 2020 sums up to 2.600 mm/a and approx. 50% discharges via the main streams. Evapotranspiration can be estimated to be 22 to 32% with a large uncertainty leaving 18 to 28% of precipitating water to diffuse discharge and infiltration into the groundwater. Estimating that surface-near discharge is at least 10%, between 8 and 18% of precipitating water may infiltrate into the ground. Diffuse surface near discharge has shown to be higher after snow melt and in summer, but almost absent during colder periods. Furthermore, a complex network of shallow agricultural drainages may only partially dewater to streams but also contribute to surface-near discharge.The monitoring of the stable 2H/18O-isotopes in a meteorological station (906m) and of Flysch-springs close to the mountain ridge of the recharge area allow to differentiate the recharge altitude. The vertical unsaturated infiltration in silt/sand dominated glaciolacustrine sediments were estimated by seasonal variation of 2H/18O-isotopes in soil-water to be 1m/year approximately. Precipitation in the Flysch dominated area at higher altitudes is transported slope-parallel in the upper part of the glacial sediments. The Mean Residence Time (MRT) of the shallow groundwater (2H/18O, 3H/3He, 13C/14C and tracer gases (CFC, SF6) indicate ages between some months and 4 years. Deeper (>40m) artesian wells in the western part are dominated by MRT older than 30 years.

Knowledge about soil water balance and ecosystem water partitioning is crucial for managing soils in semi-arid areas like the Sahel, but hydraulic parameters are hardly available to run either parsimonious or detailed process models. This study aims at bridging this parameterization gap in a typical deep (> 2m) loamy sand soil from the groundnut basin in Senegal[1]. Five approaches of soil hydraulic parameterization with a range of different complexity were compared: (1) the lookup table of Carsel and Parrish (1988) that use only the soil texture class known as “Class PTFs”, (2) Rosetta PTFs from only topsoil characterization, (3) Rosetta PTFs with a detailed multilayer soil characterization, and inverse estimation from soil moisture using Hydrus-1D, considering the soil column either as (4) a single soil material and (5) with three-layered soil material. We compared the predicted (i) soil water content (SWC) with high-frequency measurements from 15 cm down to 200 cm deep and (ii) actual evapotranspiration (ET) with Eddy Covariance (EC) data during four consecutive growing seasons under a rotation of pearl millet and peanut crops. The simplest methods (1 & 2) resulted in a significant bias of the predicted SWC, with, however, some predictive ability of Method 2 to simulate the general trends of Swc, especially under peanut crops. Method 3 behaved reasonably with average RMSE for SWC, varying between 0.029 and 0.023 cm-3 cm-3. Method 4 further improved the predictions with RMSE ranging from 0.013 to 0.020 cm-3 cm-3. The best agreement was found under peanut using Method 5 (RMSE ≤ 0.013 cm3 cm-3). Methods 3, 4 or 5 behaved satisfactorily for predicting ET whatever the crop, e.g. Method 4 (RMSE= 0.05 cm day-1, NSE= 0.9 and R²= 0.93) for pearl millet.We showed that inverse modelling should be preferred over using PTFs when studying water fluxes and evapotranspiration in cultivated Sahelian soils. [1] Faidherbia-Flux (FLUXNET: SN-Nkr): https://lped.info/wikiObsSN/?Faidherbia-Flux

Transit time distributions (TTDs) of water moving through a catchment can be estimated using water isotope data. However, different isotopes are characterized by different information contents, which may affect the estimation of TTDs. Stable isotopes, such as 2H and 18O can provide insights into the part of TTDs that describes water ages of up to a few years. However, they are “blind” to ages older than that. Radioactive isotopes, such as tritium (3H), on the other hand, have been shown to describe old water, and thus the tails of TTDs much better. Direct comparisons of the different information contents and the resulting differences in catchment TTDs estimated from stable and radioactive isotopes are rare, mostly due to very limited data availability. The objectives of this study are therefore to quantify the differences in TTDs together with their temporal variability and sensitivity to climatic variability in multiple components of the hydrological system estimated from both tritium and stable isotopes using a distributed wise-process based model in the Neckar river basin in Germany. More specifically, we test the hypotheses that (1) stable isotope- and tritium-based estimates of TTDs exhibit significant differences for both young and old water ages, (2) they are characterized by distinct sensitivities to climatic variability, and that (3) combined use of stable isotopes and tritium results in more robust estimates of TTDs. The analysis is carried out based on long term hydrological (1958-2016) and isotope data (1990-2016), using a distributed hydrological model coupled with StorAge Selection (SAS) functions, which is simultaneously calibrated (and evaluated) with respect to multiple variables and hydrological signatures including, amongst others, streamflow, tritium, and stable isotope data.