Multiscale evaluation of the Standardized Precipitation Index as a groundwater drought indicator

Kumar, Rohini; Musuuza, Jude; Loon, Anne F. Van; Teuling, Adriaan J.; Barthel, Roland; Broek, Jurriaan TenÂ; Mai, Juliane; Samaniego, Luis; Attinger, Sabine

doi:10.5194/hess-20-1117-2016

Cited by 157 publications

(183 citation statements)

References 51 publications

(120 reference statements)

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“…Only recently a corresponding Standardized Groundwater level Index (SGI) (Bloomfield and Marchant, 2013) has been proposed. SGI values computed for observation wells in the UK (Bloomfield and Marchant, 2013) as well as in Germany and the Netherlands (Kumar et al, 2016) show significant correlation with SPI values. However, the maximum correlation and SPI accumulation period are found to differ between the sites.…”

mentioning

confidence: 86%

“…Likewise, Bloomfield and Marchant (2013) as well as Kumar et al (2016) found with few exceptions the highest correlation between SGI and SPI associated with a time lag of 0 months. Our data set follows this expectation, with more than 80 % of SGI-SPI pairings for the shallow part of the Aichfeld, the Murdurchbruchtstal and the Leibnitzer Feld showing the highest Pearson correlation coefficient for a time lag of 0 months.…”

Section: Correlation Matrixmentioning

confidence: 99%

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Characterizing the spatiotemporal variability of groundwater levels of alluvial aquifers in different settings using drought indices

Haas

Birk

2017

Hydrol. Earth Syst. Sci.

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Abstract. 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.

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mentioning

confidence: 86%

Section: Correlation Matrixmentioning

confidence: 99%

Characterizing the spatiotemporal variability of groundwater levels of alluvial aquifers in different settings using drought indices

Haas

Birk

2017

Hydrol. Earth Syst. Sci.

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“…Bloomfield et al, 2015;Kumar et al, 2016) and it is questionable whether the shapes of these distribution functions remain the same when climate or land use change. Physics-based hydrological simulation models that incorporate hydrological processes in a relatively high detail can be considered to potentially provide the most reliable predictions, especially under a changing environment.…”

Section: S Brenner Et Al: Process-based Chalk Groundwater Modellingmentioning

confidence: 99%

“…Groundwater levels were simulated in quite a few studies (Adams et al, 2010;Ladouche et al, 2014;Jimenez-Martinez et al, 2016) but mostly relied on very simple representations of karst hydrological processes and disregarding the scale discrepancy between borehole (point scale) and modelling domain (catchment scale) at which they were applied.…”

Section: S Brenner Et Al: Process-based Chalk Groundwater Modellingmentioning

confidence: 99%

Process-based modelling to evaluate simulated groundwater levels and frequencies in a Chalk catchment in south-western England

Brenner

Coxon

Howden

et al. 2018

Nat. Hazards Earth Syst. Sci.

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Abstract. Chalk aquifers are an important source of drinking water in the UK. Due to their properties, they are particularly vulnerable to groundwater-related hazards like floods and droughts. Understanding and predicting groundwater levels is therefore important for effective and safe water management. Chalk is known for its high porosity and, due to its dissolvability, exposed to karstification and strong subsurface heterogeneity. To cope with the karstic heterogeneity and limited data availability, specialised modelling approaches are required that balance model complexity and data availability. In this study, we present a novel approach to evaluate simulated groundwater level frequencies derived from a semi-distributed karst model that represents subsurface heterogeneity by distribution functions. Simulated groundwater storages are transferred into groundwater levels using evidence from different observations wells. Using a percentile approach we can assess the number of days exceeding or falling below selected groundwater level percentiles. Firstly, we evaluate the performance of the model when simulating groundwater level time series using a spilt sample test and parameter identifiability analysis. Secondly, we apply a split sample test to the simulated groundwater level percentiles to explore the performance in predicting groundwater level exceedances. We show that the model provides robust simulations of discharge and groundwater levels at three observation wells at a test site in a chalk-dominated catchment in south-western England. The second split sample test also indicates that the percentile approach is able to reliably predict groundwater level exceedances across all considered timescales up to their 75th percentile. However, when looking at the 90th percentile, it only provides acceptable predictions for long time periods and it fails when the 95th percentile of groundwater exceedance levels is considered. By modifying the historic forcings of our model according to expected future climate changes, we create simple climate scenarios and we show that the projected climate changes may lead to generally lower groundwater levels and a reduction of exceedances of high groundwater level percentiles.

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“…Climate change and other future developments, such as land use change and population growth, can influence not only the availability of groundwater resources for drinking water, but also the drinking water demand (Kumar et al 2016b). The uncertainty of the impact interferes with the urgency to decide on adaptation measures concerning drinking water supply.…”

Section: Introductionmentioning

confidence: 99%

Impact of Changes in Groundwater Extractions and Climate Change on Groundwater-Dependent Ecosystems in a Complex Hydrogeological Setting

Engelenburg

Hueting

Rijpkema³

et al. 2017

Water Resour Manage

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Climate change and other future developments can influence the availability of groundwater resources for drinking water. The uncertainty of the projected impact is a challenge given the urgency to decide on adaptation measures to secure the drinking water supply. Improved understanding on how climate change affects the groundwater system is necessary to develop adaptation strategies. AZURE is used, a detailed, well-calibrated hydrological model to study the projected impact of climate change scenarios on the large Veluwe aquifer in the Netherlands. The Veluwe area is an important source of drinking water. However, some existing groundwater extractions in the area affect nearby groundwaterdependent ecosystems. Redistribution of the licensed extraction volumes of these sites is considered to reduce the impact on these ecosystems. The projected impact of climate change and redistribution to groundwater levels is studied. The research shows that in a slowly responding large aquifer the projected climate change may cause rising groundwater levels despite the projected increase in summer dryness. The results indicate that this impact may exceed the impact of redistribution of extraction volumes. In addition, it is shown that the combined effect strongly depends on local conditions, thus highlighting the need for highresolution modelling.

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Multiscale evaluation of the Standardized Precipitation Index as a groundwater drought indicator

Cited by 157 publications

References 51 publications

Characterizing the spatiotemporal variability of groundwater levels of alluvial aquifers in different settings using drought indices

Characterizing the spatiotemporal variability of groundwater levels of alluvial aquifers in different settings using drought indices

Process-based modelling to evaluate simulated groundwater levels and frequencies in a Chalk catchment in south-western England

Impact of Changes in Groundwater Extractions and Climate Change on Groundwater-Dependent Ecosystems in a Complex Hydrogeological Setting

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