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2011
DOI: 10.5194/hess-15-3861-2011
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What can we learn from long-term groundwater data to improve climate change impact studies?

Abstract: Abstract. Future risks for groundwater resources, due to global change are usually analyzed by driving hydrological models with the outputs of climate models. However, this model chain is subject to considerable uncertainties. Given the high uncertainties it is essential to identify the processes governing the groundwater dynamics, as these processes are likely to affect groundwater resources in the future, too. Information about the dominant mechanisms can be achieved by the analysis of long-term data, which … Show more

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Cited by 36 publications
(33 citation statements)
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“…This is a further important factor besides other human-induced changes, such as change in land use (surface sealing, afforestation, deforestation, etc.) and pumping activities as for example mentioned by Stoll et al (2011). In small, and heavily human-impacted systems, such as in the Mur valley described herein, those human-induced changes can be among the most important influences, rendering the concept of "natural conditions" almost impossible in shallows wells.…”
Section: Feasibility Of the Indices And Synthesismentioning
confidence: 99%
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“…This is a further important factor besides other human-induced changes, such as change in land use (surface sealing, afforestation, deforestation, etc.) and pumping activities as for example mentioned by Stoll et al (2011). In small, and heavily human-impacted systems, such as in the Mur valley described herein, those human-induced changes can be among the most important influences, rendering the concept of "natural conditions" almost impossible in shallows wells.…”
Section: Feasibility Of the Indices And Synthesismentioning
confidence: 99%
“…In order to facilitate the comparison of standardized groundwater levels, river stages and precipitation within the individual subregions, the abovementioned Pearson correlation coefficients have been plotted as correlation matrix, showing all the SGI time series, all the SRSI time series and SPI1, 3, 6, 9 and 12 for each subregion, similar to the matrices applied in Stoll et al (2011) and Loon and Laaha (2015). For a detailed description on how to read correlation matrices, please refer to Appendix A.…”
Section: Correlation Matrixmentioning
confidence: 99%
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“…While the consequences for groundwater recharge and water availability have been scrutinized by many studies (e.g., Maxwell and Kollet, 2008;Ferguson and Maxwell, 2010;Stoll et al, 2011;Taylor et al, 2013;, there is still a lack of studies regarding the observation and analysis of the effects of recent climate change on shallow groundwater temperatures (Kløve et al, 2013). Groundwater temperature (GWT) is known to be an important driver for water quality (e.g., Green et al, 2011;Sharma et al, 2012;Hähnlein et al, 2013), and therefore it is a crucial parameter for groundwater resource quality management (Figura et al, 2011).…”
Section: Introductionmentioning
confidence: 99%
“…This approach was previously used in several safety assessment studies (Palutikof and Goodess, 1991;Bechtel SAIC Company, 2004). More recently, Stoll et al (2011) studied groundwater recharge and quality using past analogue time series.…”
Section: Published By Copernicus Publications On Behalf Of the Europementioning
confidence: 99%