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4.13 Aquifer vulnerability

Aquifer protection is essential for a sustainable use of the groundwater resources, protection of the dependent ecosystems, and a central part of spatial planning and action plans. Although buried valley aquifers are often covered by thick clayey tills, they can be sensitive to contaminants due to their limited extent and to missing Tertiary clay layers (Sect. 4.11). In some areas they may actually create virtual pollutant highways, where they cut through clayey layers that protect deep lying aquifers. In such areas even the deeper parts of the valleys may be vulnerable, and may also render deep lying Neogene aquifers vulnerable to surface pollution (Sects. 4.11 and 4.12). It is therefore of great importance to be able to locate such high risk areas. The key expression for a quantification of aquifer protection is vulnerability. Vulnerability of an aquifer is defined as the sensitivity of ground-water quality to an imposed contaminant load, which is determined by the intrinsic characteris-tics of the aquifer (Lobo-Ferreira 1999). Hence aquifer vulnerability solely indicates whether the physical and biochemical characteristics of the subsurface prevent or favour the transport of pollutants in and into aquifers. It does not take into account the actual pollutant loading in an area. An area without polluting activities may therefore be very vulnerable to pollution, if for instance the water table is close to the surface and the soil and subsoil is very permeable. Likewise, areas with polluting activities may have low or moderate vulnerability to pollution, if the geological and hydrological settings prevent migration of pollutants. Potentially polluting activities should of course be located in areas with low vulnerability, while areas with high vulnerability should have a higher protection level against pollution. The vulnerability of a “groundwater body” (the term generally used in the European Water Framework Directive for a subsurface water body) is to a large extent controlled by the water flow velocity, which again is controlled by the permeability (“hydraulic conductivity”) of the

unsaturated and saturated zones, the depth to the water table and the groundwater recharge. The vulnerability of a groundwater body can be assessed in three basically different ways: 1. Physical measurements (distribution of high

and low permeability units etc.)

2. Chemical measurements (distribution of environmental tracers)

3. Groundwater/integrated hydrological modelling (numerical modelling)

In this chapter we focus on the physical measurements and we refer to Section 4.11 and 4.12 for a short description of how to use groundwater models and environmental tracers to assess groundwater vulnerability. It should be emphasised that the best and most certain way to assess groundwater vulnerability is to combine results from all three methods (e.g. Broers 2004). If the task is to make a general assessment of the vulnerability of an area, focus may be on the combination of 1) and 3), e.g., Herbst et al. (2005) and Kersebaum et al. (2006), but valuable assessment are also performed by a combination of 2) and 3) (Broers 2004). If the task is to assess the vulnerability at a specific point or interval in an aquifer (e.g. a water supply well or well field), focus will be on 2) and 3). That is, environmental tracer analyses on water pumped from the well(s) preferably combined with simulations from an integrated hydrological model (Sects. 4.11 and 4.12, Zoelmann et al. 2001, Troldborg 2004, Manning et al. 2005, Hinsby et al. 2006, Troldborg et al. 2006). 4.13.1 The influence of protective layers

The protection of groundwater reservoirs is given by the covering layers, also called protective layers (if they consist of soils and sediments of low permeability). Surface water which might be contaminated by fertilizer or pesticides percolates through the protective layers leading to the groundwater recharge. During this percolation process contaminant degradation can occur by mechanical, physicochemical, and microbiological processes (natural attenuation). An effective

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groundwater protection is given by protective layers with sufficient thickness and low hydraulic conductivity leading to high residence time of percolating water (Fig. 4.13.1). An aquifer can be classified as well protected if the percolation time through the unsaturated covering layers exceeds 10 years (Hölting et al. 1995).

Fig. 4.13.1: Percolation time as a result of depth to groundwater table and hydraulic conductivity of the underground material.

In the following, protective layers are for simplicity regarded as homogenous bodies, which can be characterised by the hydraulic conductivity as a bulk property. Inhomogeneities within the protective layers like sandy intrusions or fissures, which can lead to preferred pathways for percolation, are not taken into account, although they are quite common and important for pollution migration (Hinsby et al. 1996, Weatherington-Rice et al. 2006). In a proper vulnerability assessment these should be taken into account as they are, e.g., in the very recent modification (Weatherington-Rice et al. 2006) of the DRASTIC vulnerability index developed in the U.S. environmental protection agency, which is probably the most widely applied vulnerability index globally. Similarly, other parameters may be of importance for vulnerability assessments (e.g. RIVM 1997, LANU 2003). However, in order not to complicate the description too much, we choose to describe the principles of the more simple Aquifer Vulnerability Index (AVI), which describe conditions of the unsaturated zone that is often found to be the most important single parameter (e.g. McLay et al. 2001, Herbst et al. 2005).

Although in the literature vulnerability assessment is mainly restricted to the unsaturated layers above the first groundwater horizon, for deeper aquifers like buried valley aquifers the entire sequence of covering layers should be taken into account, if detailed underground information are available. 4.13.2 How to quantify vulnerability

A classical way to illustrate the lateral distribution of aquifer vulnerability is to use a set of maps showing, e.g., depth to groundwater table, clay content, cation exchange capacity (RIVM 1987, for the Netherlands) or depth to groundwater table and thickness of near surface clayey layers (LANU 2003, for Schleswig-Holstein). However, for practical use, the quantification of vulnerability by a single parameter would be preferred. One approach for vulnerability quantification is the AVI Aquifer Vulnerability Index (Van Stempvoort et al. 1992): This method quantifies vulnerability by hydraulic resistance to vertical flow of water through the protective layers. Hydraulic resistance c is defined by:

∑i i

i

Kd

=c (4.13.1)

di = thickness Ki = hydraulic conductivity of each protective layer (Fig. 4.13.2). The K-values for sandy material (10-5 -10-1 m/s) are several magnitudes higher than those for clayey layers (10-8 -10-6 m/s), so hydraulic resistance as defined above is dominated by clayey layers. As K has the unit length/time (m/s or m/d), the dimension of c is time. Following Van Stempvoort et al. (1992) this can be used as a rough estimate of vertical travel time of water through the unsaturated layers, although important parameter controlling the travel time like hydraulic gradient and diffusion are not considered.

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Fig. 4.13.2: Calculation of hydraulic resistance and aquifer vulnerability index.

The hydraulic conductivity of the groundwater covering layers is a key parameter to the aquifer vulnerability. In the countries of the North Sea area like the Netherlands, Germany and Denmark the covering layers consist mainly of sand, Quaternary till or Tertiary clay. For sandy material, a lot of approaches for the determination of hydraulic conductivity exist. Besides porosity several parameters are used for these approaches: unconformity (d60/d10 from grain size distribution), tortuosity (length of pathways for infiltration), effective porosity (pore space minus irreversible water content), specific inner surface area. Most of these quantities are related: high unconformity → irregular pore space → high specific inner surface area and high tortuosity → high irreversible water content leading to low effective porosity. All this means low hydraulic conductivity. In Figure 4.13.3 the relations between porosity and effective porosity for different grain sizes are shown (after Matthess & Ubell 1981). For clayey material, hydraulic conductivity is controlled by the clay content. The grain size of clay is by far smaller than the grain size of sand. If clay is added to sand, the small clay particles concentrate in the narrow pore connecting channels. This leads to a strong reduction of hydraulic conductivity of the sand clay mixture (Fig. 4.13.4).

Fig. 4.13.3: Top: partly saturated sand (gray: mineral grains, blue: pore water, white: air). Bottom: porosity and effective porosity for different grain sizes, gravel e.g. has a lower porosity than fine grained silt, but a higher effective porosity and so a higher hydraulic conductivity (after Matthess & Ubell 1981).

Fig. 4.13.4: Top: partly saturated sand/clay mixture (gray: mineral grains, black: clay particles, blue: pore water, white: air). Bottom: relation of clay content and hydraulic conductivity for soil samples of depth range 0.8 – 1.2 m (after Scheffer & Schachtschabel 1984).

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The distribution of the hydraulic conductivity (K value) of the saturated zone is also of large importance in the assessment of aquifer vulnerability. A simple and efficient method for obtaining reliable hydraulic conductivities in shallow sandy aquifers was presented by Hinsby et al. (1991). Several hundred of K-values measured by this method demonstrated the variability of the K-values even in a relatively homogeneous sand aquifer and its importance for pollution transport (Bjerg et al. 1991). 4.13.3 Geophysical concepts

The vertical travel time of water through a set of geological layers can be related to the resistivity properties of these layers (Kalinski et al. 1993). Hydraulic resistance of the near surface layers depends on effective porosity (for sandy material) and on clay content (for clayey material). Both parameters are controlling the specific electrical resistivity of the material (Fig. 4.13.5). Specific resistivities of several hundreds to thousand Ωm are typical for dry sand and gravel, while specific resistivities below 60 Ωm are characteristic for clayey material. So, as a first step, sandy and clayey material in the underground can be discriminated by their specific resistivities. Also water saturated sand can be identified by specific resistivities in the range of 60 – 200 Ωm depending on ground water resistivity (mostly 10 – 25 Ωm) and porosity. If we assume a two-dimensional image of electric resistivity of the ground for the cross section shown in Figure 4.13.2, unsaturated sand, saturated sand and till can clearly be discriminated by the electric resistivities. This resistivity image can be obtained by electrical soundings, electrical profiling or electromagnetic mapping. The resistivity information can be used in several manners: for the determination of depth to water table

and thickness of sandy and clayey layers in the unsaturated zone. Standard values for hydraulic conductivities can be attached to the layers, these information are then used to calculate hydraulic resistance and aquifer vulnerability after Equation 4.13.1.

taking the electric resistivity as equivalent to hydraulic conductivity as discussed above, di/Ki can be replaced by the equivalent expression di/ρi or, replacing electric resistivity ρ by the electric conductivity σ, by di x σi. This expression is called integrated conductivity IC (Röttger et al. 2005) and can be used for the quantification of aquifer vulnerability.

i

iid=IC σ∑ (4.13.2)

Using the resistivity results following the first option (determination of layer thickness, discrimination between sandy and clayey material), we obtain a vulnerability index of 7 x 103 s for the sandy region in the left part of Figure 4.13.2 and 4 x 107 s for the right part with the till layer covering the sand. Using the second option as shown in Figure 4.13.6, we obtain integrated conductivities of 9.5 mS for the sandy region (left part of Figures 4.13.2 and 4.13.6) and 87.5 mS for the mixed layering in the right part of the figures. So, the regions with

Fig. 4.13.5: Specific electrical resistivity related to pore water saturation degree (modified Archie law, blue line) and clay content (red line, after Mualem & Friedman 1991 and Rhoades et al. 1989). Pore water saturation for unsaturated sand is related to the irreversible water content and so to effective porosity and hydraulic conductivity. High pore water saturation means low effective porosity and low hydraulic conductivity.

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high and with low protection capability of the covering layers can be identified clearly by the vulnerability index as well as by the integrated conductivity. Vulnerability index or integrated conductivity are calculated for all layers above the groundwater table. The groundwater table is clearly defined by resistivity values ranging from 80 – 200 Ωm. For unconfined aquifers (Fig. 4.13.7 right) covered with dry sands the resistivity contrast is 400 – 1000 Ωm / 80 – 200 Ωm, while for confined aquifers (Fig. 4.13.7 left) covered with clay or till the resistivity contrast is 20 – 60 Ωm / 80 – 200 Ωm.

4.13.4 Application of the concept

For vulnerability mapping all resistivity methods leading to a resistivity-depth image in terms of layer thickness and resistivity can be used (VES, CVES, TEM). Small scale mapping, e.g. in the vicinity of well locations, can be done by ground methods, while for large scale mapping airborn methods or mobile electrode arrays are required. An example for a vulnerability map near to the city of Flensburg is shown in Figure 4.13.8. Here the results of an HEM survey by the BGR were used for the calculation of the integrated conductivity. Moraine areas with high IC and good aquifer protection can clearly be discriminated from sandy outwash plains with low IC and poor aquifer protection.

Fig. 4.13.6: Resistivity cross section for the underground situation shown in Figure 4.13.2 with integrated conductivities IC.

Fig. 4.13.7: Identification of groundwater table (lower boundary of covering layers) by resistivity (blue line).

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Finally, a word of caution: Vulnerability mapping and vulnerability indices are valuable tools for the protection and management of the groundwater resources and the aquatic environment. However, they must not stand alone - several studies have shown that the vulnerability index does not always predict the pollution distribution in the subsurface to a satisfying degree.

Fig. 4.13.8: Example of a vulnerability map based on HEM results (Christensen et al. 2002).

4.13.5 References

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Broers HP (2004): The spatial distribution of groundwater age for different geohydro-logical situations in the Netherlands: implications for groundwater quality monitoring at the regional scale. – Journal of Hydrology 299(1–2): 84–106.

Christensen P-F, Christensen S, Friborg R, Kirsch R, Rabbel W, Röttger B, Scheer W, Thomsen S, Voss W (2002): A geological model of the Danish-German Border Region. – Meyniana 54: 73–88.

Herbst M, Hardelauf H, Harms R, Vanderborght J, Vereecken H (2005): Pesticide fate at regional scale: Development of an integrated model approach and application. – Physics and Chemistry of the Earth 30(8–10): 542–549.

Hinsby K, Purtschert R, Edmunds, M (2006): Groundwater age and water quality vulnerability.– In: Quevauviller P (Ed.) Groundwater Science and Policy. – Chemical Society Reviews, CSR, in prep.

Hinsby K, Mckay LD, Jorgensen PR, Lenczewski M, Gerba CP (1996): Fracture aperture measurements and migration of solutes, viruses, and immiscible creosote in a column of clay-rich till. – Ground Water 34(6): 1065–1075.

Hinsby K, Bjerg PL, Andersen LJ, Skov B, Clausen EV (1992): A Mini Slug Test Method for Determination of A Local Hydraulic Conductivity of An Unconfined Sandy Aquifer. – Journal of Hydrology 136(1–4): 87–106.

Hölting B, Härtlé T, Hohberger K-H, Nachtigall KH, Villinger E, Weinzierl W, Wrobel J-P (1995): Konzept zur Ermittlung der Schutzfunktion der Grundwasserüber-deckung. – Geol. Jb. C 63: 5–24.

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Kalinski RJ, Kelly WE, Bogardi I, Pesti G (1993): Electrical resistivity measurements to estimate travel times through unsaturated ground water protective layers. – Journal of Applied Geophysics 30: 161–173.

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Röttger B, Kirsch R, Scheer W, Thomsen S, Friborg R, Voss W (2005): Multifrequency Airborne EM Surveys – a Tool for Aquifer Vulnerability Mapping. – In: D.K. Butler (ed.): Near surface geophysics, investigations in Geophysics no. 13, Society of Engineering Geophysicists: 643–651.

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Troldborg L (2004): The influence of conceptual geological models on the simulation of flow and transport in Quaternary aquifer systems. – PhD thesis, Technical University of Denmark, published in Geological Survey of Denmark and Greenland, report 2004/107.

Troldborg L, Jensen KH, Engesgaard P, Refsgaard JC, Hinsby K (2006): Simulation of age and environmental tracers in a complex shallow aquifer. In prep.

Weatherington-Rice J, Christy SD, Angle MP, Gehring R, Aller L (2006): Drastic Hydrogeologic Settings Modified for Fractured Tills: Part 1. Theory and Part 2. Field Observations. – The Ohio Journal of Science 106(2): 45–63.

Zoellmann K, Kinzelbach W, Fulda C (2001): Environmental tracer transport (H-3 and SF6) in the saturated and unsaturated zones and its use in nitrate pollution management. -Journal of Hydrology 240(3–4), 187–205.

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