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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

An integrative interdisciplinary approach is currently developed to investigate groundwater systems in alpine and prealpine environments and how they respond to hydrological extremes such as droughts, heavy rain and floods in terms of water quantity, hydrochemical quality, and ecological status. The new approach is aimed at improving the understanding of the interaction between physical, chemical, and biological processes in groundwater responses to extreme events as well as developing indicators suitable for an integrative monitoring and management of the aquifers. For this purpose, observation wells of the existing state hydrographic monitoring net have been selected within the Austrian part of the Mur river basin, stretching from the alpine origin to the national border in the foreland. The investigation area thus comprises diverse hydrogeological settings and land-use types. The selected observation wells have long-term records of groundwater levels and are used for sampling campaigns under different hydrological conditions. Groundwater level fluctuations are evaluated using drought indices and statistical approaches, such as auto-correlation and cross-correlation with precipitation and stream stages. Our hydrochemical analyses of groundwater and surface waters also consider compounds indicative of agricultural sources (e.g., nitrate), wastewater-borne micro-pollutants, and stable isotopes of water. These indicators are used to identify different drivers controlling water origin and quality. The ecological status is characterized using microbiological measures, such as total number of bacteria and microbial activity, groundwater fauna, and the qualitative composition of dissolved organic matter (DOM). First results demonstrate a deterioration of water quality from groundwater to surface water and from the alpine region towards the foreland, corresponding to the more intense agricultural and urban land use in the foreland. Linkages between water quality and hydrological conditions are currently being evaluated and will be further examined using UV-Vis spectrometry for high-resolution in-situ monitoring of water quality changes (DOM and nitrate) at selected observation wells.

In this presentation we provide a brief overview on the strategic selection of representative groundwater wells and lessons learned.The inter-disciplinary project “Integrative Groundwater Assessment”, looks into the effects of extreme hydro-meteorological events on the quantity and the chemical and biological quality of groundwater. Focus is on the Austrian Mur catchment, an area reaching from its alpine spring (~2000 m asl) down to the Slovenian border (~200 m asl). More than 500 state operated groundwater observation wells are available over the 400 km of the river’s course, taking private wells not into account. For state operated wells, time series for water levels are publicly available which allows for simply using all the data i.e. using big data approaches [1, 2, 3] – albeit with some issues [4].However, for water quality, such time series rarely exist and if so, they often do not cover all specific parameters one needs, asking for targeted sampling campaigns. The availability of hundreds of wells seems like a benefit. However, the identification of wells that are representative and suitable for sampling regarding both chemical and biological parameters is a challenging taskIn consequence, we went through a multi-step process of planning a sampling campaign that should fulfill the following requirements: Coverage of the entire stream section from alpine to lowland regions Coverage of different land uses in the river valley Realization of well transects from the river through the complete local aquifer Wells allow sampling of groundwater for the analysis of physical-chemical and biological parameters Historical data of groundwater quantity and quality aspects are available Assessing the available metadata and taking into account the very helpful advice of stakeholders, already reduced the number of representative wells considerably. In order to obtain a consistent data set, another set of wells had to be dismissed, to allow for the same sampling and monitoring procedures at every location. Finally, out in the field, wells that were found damaged or out of order, led to a further reduction. Thus we ended up with only 45 wells suitable for our specific purposes, However, using specific strategies for data analysis as outlined in [3] and [4] and application of a novel groundwater ecological assessment scheme (D-A-C Index [5]) showed that even the substantially reduced number of wells provides a very good coverage of the various regions in the Mur catchment. In a further step, the results from two sampling campaigns and subsequent data analysis will be used to select an even smaller subset of wells where novel multi-parameter spectral dataloggers are going to be installed, enabling us to monitor various quality data in an very high temporal resolution.References:[1] https://doi.org/10.5194/egusphere-egu2020-8148[2] https://doi.org/10.1016/j.ejrh.2019.100597[3] https://doi.org/10.1007/s12665-018-7469-4[4] Haas et al (2020)Tiny steps towards Big Data - Freud und Leid der Arbeit mit großen Grundwasserdatensätzen.Tagungsband 2020. Grundwasser und Flusseinzugsgebiete - Prozesse, Daten und Modelle.[5] https://doi.org/10.1016/j.watres.2019.114902

The assessment and monitoring of the ecological quality and status of groundwater is a timely issue. At present, various assessment tools have been developed that now await application and validation. One of these, the D‑A‑C index, evaluates the microbiological-ecological quality of groundwater based on of prokaryotic cell counts, microbial activity measurements, and the qualitative characterization of dissolved organic carbon (DOM). The purpose of this paper is to illustrate the different ways of application of the D‑A-(C) index making use of a recently collected data set (n = 61) from the river Mur valley, Austria. First, we present an extension of the D‑A-(C) index by including measurements of dissolved organic matter quality (DOM) derived from fluorescence spectroscopy as additional variables to supplement the analysis of microbial cell density and activity levels. Second, we illustrate how the definition of a reference status for a ‘good’ microbiological-ecological state can improve the analysis and allow for a more sensitive and accurate detection of impacts on groundwater ecosystems. Based on our results, we advocate that the analysis be performed by making use of expert knowledge for the definition of reference sites to which target sites are to be compared.

Climate change is mostly associated with the term of “global warming” and thus conjures images of a hotter and dryer future. Indeed, the Alpine region already has seen much higher warming compared to the average of the northern hemisphere [1]. However, because of the impact of other climate variables (e.g. precipitation) and vegetation responses, warming does not necessarily have to mean higher evapotranspiration and dryer conditions [2]. This matter is further complicated as groundwater is closely interlinked with surface water. While surface water is of course related to precipitation, it is also one of the major pathways for humans to have a large and direct impact on the water cycle, e.g. by the construction of run-of-river powerplants. A further direct human impact is the abstraction of groundwater. For this factor, it is generally understood that water use increased with economic activity until the rise of environmentalism in the 1980s and more efficient water use stopped this trend and turned it into a decrease in many industrialized countries. Assessing impacts of climate change on groundwater resources therefore is a challenging task. In order to assess these, as well as direct human impacts on groundwater, we analyzed a large dataset (1017 groundwater level-, 426 stream stage- and 646 precipitation time series) covering Austria from earlier than 1930 until 2015, with the majority of the data from the 1970s on. It is shown that groundwater shows a strong falling trend, followed by a rise, fitting the human water use, whereas precipitation shows a more moderate trend. River stages show a completely deviating behavior before the 1980s but also follow the rising trend afterwards [3]. While this does not yet prove a causal link, it does highlight the possibility that human use could affect groundwater levels more than the climate, especially since Austria almost exclusively uses groundwater for human use and the wells in the dataset are all located in the populated lowlands. Going beyond [3], we take a closer look at the history and future of the human factor, namely water abstraction for public water supply and the effects of humans on rivers. We show that Austria has a very particular form of water supply, mainly due to the special role of the capital, Vienna, whose history could see a repeat in the near future. Under a changing climate, there is also a possibility for further changes in Austria’s rivers. In addition to effects of such changes on groundwater levels, we try to address potential impacts on the chemical quality and ecological status of groundwater. References:[1] Gobiet et al., 2014, 21st century climate change in the European alps-a review. Sci. Total. Environ. 493, 1138 – 1151.[2] Pangle et al., 2014, Rainfall seasonality and an ecohydrological feedback offset the potential impact of climate warming on evapotranspiration and groundwater recharge, Water Resour. Res., 50, 1308–1321[3] Haas & Birk, 2019, Trends in Austrian groundwater – climate or human impact? J. Hydrol.: Reg. Stud. 22, 100597

To improve the understanding of how aquifers in different alluvial settings respond to extreme events in a changing environment, we analyze standardized time series of groundwater levels (Standardized Groundwater level Index – SGI), precipitation (Standardized Precipitation Index – SPI), and river stages of three subregions within the catchment of the river Mur (Austria). Using correlation matrices, differences and similarities between the subregions, ranging from the Alpine upstream part of the catchment to its shallow foreland basin, are identified and visualized. Generally, river stages exhibit the highest correlations with groundwater levels, frequently affecting not only the wells closest to the river, but also more distant parts of the alluvial aquifer. As a result, human impacts on the river are transferred to the aquifer, thus affecting the behavior of groundwater levels. Hence, to avoid misinterpretation of groundwater levels in this type of setting, it is important to account for the river and human impacts on it. While the river is a controlling factor in all of the subregions, an influence of precipitation is evident too. Except for deep wells found in an upstream Alpine basin, groundwater levels show the highest correlation with a precipitation accumulation period of 6 months (SPI6). The correlation in the foreland is generally higher than that in the Alpine subregions, thus corresponding to a trend from deeper wells in the Alpine parts of the catchment towards more shallow wells in the foreland. Extreme events are found to affect the aquifer in different ways. As shown with the well-known European 2003 drought and the local 2009 floods, correlations are reduced under flood conditions, but increased under drought. Thus, precipitation, groundwater levels and river stages tend to exhibit uniform behavior under drought conditions, whereas they may show irregular behavior during floods. Similarly, correlations are found to be weaker in years with little snow as compared with those with much snow. This is in agreement with typical aquifer response times over 1 month, suggesting that short events such as floods will not affect much of the aquifer, whereas a long-term event such as a drought or snow-rich winter will. Splitting the time series into periods of 12 years reveals a tendency towards higher correlations in the most recent time period from 1999 to 2010. This time period also shows the highest number of events with SPI values below −2. The SGI values behave in a similar way only in the foreland aquifer, whereas the investigated Alpine aquifers exhibit a contrasting behavior with the highest number of low SGI events in the time before 1986. This is a result of overlying trends and suggests that the groundwater levels within these subregions are more strongly influenced by direct human impacts, e.g., on the river, than by changes in precipitation. Thus, direct human impacts must not be ignored when assessing climate change impacts on alluvial aquifers situated in populated valleys.

Changing political frameworks in addition to novel and more cost-effective means to investigate the subsurface have led to an increase in the availability of hydrological data. This wealth of data, however, poses new challenges in effectively making use of it. Traditional tools such as spreadsheets or proprietary datalogger software often do not scale easily with a larger amount of available datasets, requiring considerable user interaction. Also, comparing different locations and types of data can be difficult and tedious. Thus, a python script is presented that enables the user to quickly visualize and compare different types of data such as for example groundwater levels or precipitation amounts. This is done by first standardizing the data using different drought indices and, subsequently, visualization of correlation matrices or plots of data on maps. This approach can be used for data quality control (identifying erroneous data, classifying data into different types), data comparison (comparing different types of data, such as groundwater and precipitation; comparing different locations) and to visualize and analyze the development of hydrological data and their correlation patterns over time. Prospects and limitations of the approach are illustrated and discussed using various example applications.