Journal of Applied Geophysics 98 (2013) 90–99

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Journal of Applied Geophysics

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Geoelectrical, strain and tilt investigations of hydrological processes atthe broadband Geodynamical Observatory Moxa, Germany

Tobias Hermann ⁎, Corinna Kroner 1, Thomas JahrFriedrich Schiller University Jena, Institute of Geosciences, Burgweg 11, 07749 Jena, Germany

⁎ Corresponding author at: Now at: Alfred-Wegener-IPolar- und Meeresforschung, Am alten Hafen 26, 27568+49 47148311948.

E-mail address: THermann22@gmx.de (T. Hermann).1 Now at: Physikalisch-Technische Bundesanstalt, Fach

38116 Braunschweig, Germany.

0926-9851/$ – see front matter © 2013 Elsevier B.V. All rihttp://dx.doi.org/10.1016/j.jappgeo.2013.07.007

a b s t r a c t

a r t i c l e i n f o

Article history:Received 6 May 2013Accepted 27 July 2013Available online 6 August 2013

Keywords:Electrical resistivity tomographyStrain and tilt measurementsGeodynamical Observatory MoxaHydrological induced deformations

The Geodynamic Observatory Moxa, located in Thuringia/Germany, is dedicated to studies of temporal deforma-tions of the earth's crust and of variations of the gravity field. One of the essential issueswith respect to these inves-tigations is the reduction of the hydrological impact on the data of the gravimeters, strainmeters and tiltmeters. Inorder to optimise the reductions, we investigated the changes in the hydrological conditions in the woody moun-tain slope above the observatory with time-lapse electrical resistivity tomography (ERT), and analysed the strainand tilt measurements for prominent signatures of pore pressure induced subsurface deformations.Herewepresent the results for two profiles – parallel and perpendicular to the slope –measuredwith ERT during33 campaigns between June 2007 and April 2010. Resistivity changes and variations of apparent soil moisture,inferred from ERT sections, were found to primarily occur in the first two metres of the subsurface. These varia-tions can be related to subsurface flow in the upper two metres induced by precipitation events and snowmelts.Trees close to the profiles only show a minimum impact on the resistivity and soil moisture changes.Furthermore, systematic hydrologically induced deformations can be observed in hodographs of strain and tilt mea-surements for large precipitation events (N80 mm) and snowmelts. In the strain data a short-term (b3 days) dilata-tional signal is found with an amplitude of 20 nstrain to 60 nstrain and a long-term (N7 days) compressional signalbetween 40 nstrain and 180 nstrain. The preferential N–S direction of long-term deformational signals (N1 week) isalso observed in the tilt data. Thedirectionof tilt changes (25 nrad–120 nrad) is nearlyparallel to thedrainagedirectionof the nearby Silberleite creek indicating variations of pore pressure gradients during hydrological events.The results of these hydrological studies at the GeodynamicObservatoryMoxa can be used for removing the timedependent hydrological signal in strain and tilt data and, thus, better correction algorithms for hydrological im-pacts can be developed to enhance the value of the data for geodynamic studies.

© 2013 Elsevier B.V. All rights reserved.

1. Introduction

Investigations on deformations of the earth's shape require correc-tions of different environmental influences on the data. Currently, ad-justments on correction algorithms of hydrological impacts in strainand tilt data are discussed (e.g. Agnew, 1986; Braitenberg, 1999; DalMoro and Zadro, 1998; Grillo et al., 2011; Jacob et al., 2010; Jahr et al.,2006, 2009; Kroner and Jahr, 2006; Kümpel, 1982; Longuevergneet al., 2009; Naujoks et al., 2010; Tenze et al., 2012; Zadro andBraitenberg, 1999). At some stations linear relations between deforma-tion andhydrology have been found, at leastwhenwater intake is abovea certain threshold. The linear relationswere to some extent successful-ly used for elimination of hydrological impacts. These reductions are im-portant for the analysis of small geodynamic signals in strain and tilt

nstitut Helmholtz-Zentrum fürBremerhaven, Germany. Tel.:

bereich PSt 1, Bundesallee 100,

ghts reserved.

data such as oscillations of the earth's core, the “Nearly diurnal FreeWobble” (NDFW; Zürn, 1997) or tectonically induced crustal deforma-tions due to the same order of magnitude of the variations of interestand the hydrologically induced signals.

From experiments and first estimates the influence of the hill flankabove the observatory building with regard to hydrologically inducedsignals in the geodynamic observations became evident. In order to ob-tain an improved understanding of hydrological variations in the hillflank time-lapse electrical resistivity tomography (ERT) measurementswere carried out. This method is widely used for hydrological investiga-tions like detection of groundwater flow paths and their variationswithtime as well as creating of underground models derived from ERT data.Generally, for time-lapse ERT the variation of resistivity is dependent onwater content, soil temperature and salinity variations within the sub-surface (e.g. Amidu and Dunbar, 2007; Cassiani et al., 2009; Rayneret al., 2007;Uhlenbrook andWenninger, 2006;White, 1994) and, there-fore, this method is used for the investigations.

The aim of the repeated ERT at Moxawas twofold: the identificationof zones in which predominantly hydrological variations occur and thedetermination of variations of the moisture content and their

91T. Hermann et al. / Journal of Applied Geophysics 98 (2013) 90–99

homogeneity in the eastern hill slope above theGeodynamicObservato-ryMoxa (Fig. 1A). For this, also comparisonswith local soil moisture ob-servationsweremade. The strain and tilt datawere analysedwith regardto systematic hydrologically induced signals caused by extreme precipi-tation events (N80 mm) and snowmelts. These hydrological eventscaused pronounced pore pressure gradients and hydrologically induceddeformations. The resulting deformations were recorded by strain- andtiltmeters (Biot, 1941; Rice and Cleary, 1976).

2. Geology and hydrology

The investigations are carried out at the Geodynamic ObservatoryMoxa, Thuringia/Germany. The observatory is located in aNNW–SSE run-ning valley of the creek Silberleite with a steep eastern slope and a flatwestern slope (Fig. 1A). In the south, the valley opens to meadows. Theobservatory building at the base of the steep eastern slope has a galleryinside the hill with a 45 m long E–W part followed by a 35 m long N–Ssection (Fig. 1B). The mountain coverage reaches up to 35 m. Inside thegallery two quartz tube strainmeters of 26 m length each, in N–S andE–W direction, are installed. The N–S strainmeter is aligned with the to-pography and the E–W strainmeter runs perpendicular to the topogra-phy. In the northern part of the observatory an ASKANIA tiltmeter isinstalled in a 100 m deep borehole (Jahr et al., 2009; Fig. 1B). Next tothis borehole, the water level is monitored (Fig. 1B). Two profiles forERT were set up approximately 35 m above the observatory on thewoody eastern slope (Fig. 1A). Each profile, parallel and perpendicularto the slope, consists of 24 electrodes within a distance of one metre.Thus, the downhill directed groundwater flowpaths and their lateral var-iations along the slope can be detected. The measurements wereperformedwith themulti-electrode resistivitymeter Syscal Junior Switch24 by Iris Instruments. At the western end of the downhill oriented pro-file soilmoisture variations aremonitoredwith two horizontally installedTDRprobes in depths of 8 cmand93 cm (Fig. 1B). Additionally,meteoro-logical parameters such as barometric pressure and precipitation are ob-served at the meteorological station of the observatory.

Geologically the observatory is located at the border of the Thurin-gian SlateMountains. The bedrock in the surroundings consists ofmain-ly greywacke-shale-stratification and pure shale. During the Variscanorogenesis, with the main direction of compression in NW–SE, folds ofWSW–ENE strikewere formed. The fracturing generally varies betweenNNW–SSE and NW–SE (Kasch et al., 2013). In the shale the fracturing isless and mainly closed compared to the greywacke. The unweathered

BA

tiltmbor100

tiltmeboreh50 m

400 km

1 km0.5

Fig. 1. TheGeodynamicObservatoryMoxa. (A) Overview of the location ofMoxa in Central Eurolines of altitude are orange, roads and the observatory aremarkedwith red. (B) Footprint of the(after Naujoks, 2008; Schulze, 1998).

bedrock is highly consolidated and therefore, it has less permeabilityfor water. Hence, the water conductivity consequently is restricted tofractures, cracks and faults (Dlugosch, 2006). Furthermore, the valleyis filled with 2 m to 4 m thick quaternary sediments consisting ofloam gravel conglomeration (Drobe, 2005; Kasch et al., 2013). The east-ern slope is coveredwith a 1.1 m to 1.7 m thickweathered layer (Drobe,2005; Kasch et al., 2013; Vermue and van de Voorde, 2005). This weath-ered layer encompasses a 5 cm to 10 cm thick humus rich layer above aloamy gravel layer and the weathering horizon of the shale.

The general hydrological situation in the surroundings of the obser-vatory can be described as headwater catchment of the creek Silberleitewith an area of nearly 2 km2 and drainage in southern to south-easterndirection (Naujoks et al., 2010). Due to hydrological processes and theirinfluences on gravity observations (e.g. Krause et al., 2009; Kroner,2001, 2002; Kroner and Jahr, 2006; Naujoks et al., 2010) several inves-tigations on water movements at the eastern slope above the observa-tory were carried out. It emerged that the water movements aremainly concentrated on the opened fissures and cracks, whereas theunweathered bedrock does not contribute to the water movements.The porosities of the subsurface range between 20 vol.% and 30 vol.%decreasing downwards (Dlugosch, 2006). But detailed time variant re-sults of hydrological processes at the slope remained unresolved.

The vegetation of the surroundings is characterised by grassland tothe south and the remaining area is characterised by spruce forestswith less ground vegetation.

3. Data processing

A number of environmental parameters are recorded continuouslyat the Geodynamic Observatory Moxa (Fig. 1B) which can be used forcorrections of the ERT data and geodynamic measurements. The soiltemperature and the soil moisture next to the ERT profiles are recordedwith a sample rate of 30 min and 15 min, respectively. Precipitation,barometric pressure, air temperature inside and outside the gallery,and water level in the valley are measured with a sample rate of 10 s.

3.1. ERT

The Wenner–Schlumberger configuration was used for the ERT be-cause of its high vertical resolution as well as its high signal to noiseratio compared to other electrode configurations (after Ward, 1990).For each electrode configuration three measurements were stacked to

N

0 4 8 12 mmeteorologicalstation

eterehole m

tiltmeterborehole50 m

terole

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mountain coverageca. 35 m

north buildingsouth building

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observation point at eastern slope aboveobservatory with soil moisture andtemperature probe

centralbuilding

Silberleite

N-S strainmeter

E-W strainmeter

water levelborehole50 m

measurement of gallerytemperature

ERT profiles (electrodes) at eastern slope aboveobservatory

pe (insetmap) and the surrounding area of the observatory.Water ismarked blue, contourGeodynamical ObservatoryMoxa. The locations of the instruments are indicated in colours

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Fig. 2. Reference models for the resistivity and soil moisture variations in Fig. 3.

92 T. Hermann et al. / Journal of Applied Geophysics 98 (2013) 90–99

increase the signal to noise ratio. The measurements have an investiga-tion depth of approximately 4 m (Ward, 1990). The two ERT profileswere measured during field campaigns in irregular intervals. The sur-veys were mostly conducted close to prominent hydrological eventslike precipitation, snowmelt or long dry phases of more than 10 days.In the period from June 2007 to April 2010 altogether 33 field cam-paigns were performed. The repeatability of the measurements at com-parable conditions was checked with twofold measurements duringone field campaign. Furthermore, ERT measurements were performedalong profiles which were shifted by 5 m in profile direction in orderto check for the independency of the obtained apparent resistivity dis-tribution from the Wenner–Schlumberger configuration.

The processing of the ERT data was done with the softwareSensInv2D (Fechner, 2003). A standard inversion was used and a cellgrid size of 30 cm × 30 cmwas chosen because of high spatial near sur-face resistivity variations which were observed during the first surveys.For all inversion processes the same parameters were applied. The re-sult of the first field campaign (apparent resistivity distribution whilewater saturated conditions) was used as start model for the inversionand as reference model for the ERT data of the following field cam-paigns. The obtained apparent resistivities were temperature correctedto a reference temperature of 25 °C. For this temperature correction therelation of Keller and Frischknecht (1966) was used:

ρ25 �C ¼ ρT � 1þ 0:025 � T−25 �C� �� � ð1Þ

with standard temperature coefficient 0.025, apparent resistivitiesρ25 °C and ρT at a temperature of 25 °C and T, respectively. The variationof temperaturewith increasing depthwas also corrected after Campbelland Norman (1998):

T zð Þ ¼ Ta þ Tamp � exp −zD

� �� sin ϖ t−8ð Þ−z

D

h ið2Þ

Fig. 3. Examples of ERT measurements. (Top) Examples of differences of field campaigns (redvariation (example 2, right). The location of the ERT profiles is shown in Fig. 1.

with the following parameters: Ta — mean daily soil surface tempera-ture, ϖ ¼ π

12, Tamp — amplitude of the temperature fluctuations at thesurface (b1 °C), t — time in hours, D ¼ 2k

ϖ — damping depth with thethermal diffusivity k of the soil, and z— depth inmetres. For the thermaldiffusivity k of the soil values of shale were taken according to Schön(2004). The corrected apparent resistivity distribution was convertedto soil moisture with the modified Archie equation from Shah andSingh (2005),

σ s ¼ c � σw � Θm; ð3Þ

with the empirical relations:

c ¼ i � clayj;

m ¼ k � clayl:ð4Þ

The used parameters are: σ s ¼ 1ρs

— conductivity of the soil(=reciprocity of resistivity of the soil), σw — conductivity of the porefluid, Θ — soil moisture, clay — clay content, and the empirical valuesc, m, i, j, k, and l. The modification of Archie's equation is necessary be-cause of the non-negligible clay content (Shah and Singh, 2005) of75% in the greywacke-shale-mixture (Kasch et al., 2013; Pettijohnet al., 1987). Themeasured conductivity of the creek Silberleite alloweda reasonable estimation for the conductivity of the pore fluid (Vermueand van de Voorde, 2005) and the empirical values of Shah and Singh(2005)were used for calculating the soil moisture.Moreover, the calcu-lated soil moisture was calibratedwith themeasured soil moisture nextto the ERT profiles to obtain the more reliable absolute values. Finally,the data were smoothed to decrease unreasonable strong and abruptsoil moisture changes (Fechner, 2003; Zhou et al., 2001). The processeddata are given relative to the reference model (Fig. 2).

bars) including a major precipitation event (example 1, left) and the maximal seasonal

Example 1 Example 2E

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300027502500225020001750150012501000750500

-500-750-1000-1250-1500-1750-2000-2250-2500-2750-3000

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-500-750-1000-1250-1500-1750-2000-2250-2500-2750-3000

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7065605550454035302520151050-5-10-15-20-25-30-35-40-45-50-55-60-65-70

7065605550454035302520151050-5-10-15-20-25-30-35-40-45-50-55-60-65-70

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precipitation event seasonal variation

W EW E

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01.09.2007 01.10.2007 01.11.2007 01.12.2007 01.01.2008 01.04.2008 01.05.2008 01.06.2008 01.07.2008 01.08.2008 01.09.2008date date

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93T. Hermann et al. / Journal of Applied Geophysics 98 (2013) 90–99

94 T. Hermann et al. / Journal of Applied Geophysics 98 (2013) 90–99

3.2. Deformation measurements

The investigations of near surface deformations with strain- and tilt-meters caused by hydrological processes focused onprominent hydrolog-ical events between January 2005 and July 2009. Based on accumulatedprecipitation, soil moisture and water level, prominent hydrologicalevents and their time windows were selected (Fig. 3; Table 1). Thetime windows analysed, covered the period three days before the hy-drological events started and until seven days after the hydrologicalevents ceased. Thus, the clear detection of the complete hydrologicalsignals was ensured.

The 10 s strain and tilt data were processed (de-spiked, eliminationof earthquakes and instrument-related offsets) and filtered to one hoursampling rate. In addition, the tilt data were calibrated and transformedin a north–south and an east–west component for later directional in-vestigations (Jahr et al., 2009). For the elimination of the tidal signalwithin the strain and tilt data, the software package ETERNA 3.40(Wenzel, 1996) and local tidal parameters were used (Jahr et al.,2006; Schindler et al., in press). A linear instrumental drift (Jahr et al.,2006, 2009) was removed from all data sections using the first threeand last three days of an investigation period to calculate the lineardrift without any hydrological induced signals. The influence of baro-metric pressure on the observationswas corrected using a linear regres-sion coefficient (α) between the approximated gradients of barometricpressure (p˙ ) and the strain and tilt data (D˙ ):

D¼ α �p: ð5Þ

The gradients were approximated by difference quotients. Numeri-cal integration of Eq. (5) yields the approximated pressure induced de-formation. It cannot be fully excluded, that also hydrologically inducedsignals are reduced by this processing step because barometric pressurevariations are often combined with hydrological events. But this pro-cessing step minimises the barometric pressure induced deformationand is needed because of the large influence of barometric pressure gra-dients on deformation data (Gebauer et al., 2009; Herbst, 1976; Kroneret al., 2005; Kümpel, 1982; Weise, 1992).

4. Results and interpretation

4.1. ERT

Repeated measurements of the apparent resistivity during onefield campaign confirm the reproducibility of the previously obtainedresistivity distribution. The measurements were repeated within twohours and the locally observed maximum discrepancy has a non-significant magnitude of several tens of Ωm. Measurements alongthe shifted profiles illustrated the independency of the obtainedresistivity distribution from the used Wenner–Schlumberger configu-ration. Both shifted and original profiles show resistivity variationsat the same absolute position independent of the Wenner–Schlumberger configuration. These findings prove the reliability ofthe results.

The referencemodel of the time-lapse ERT is shown in Fig. 2. The re-sistivity distributions of the E–WandN–S profile showmainly elliptical-ly shaped anomalies with high resisitivity values of 4000 Ωm to7000 Ωm centred in the uppermost two metres (Fig. 2). The remainingarea of the uppermost two metres has resistivity values of 1000 Ωm to2000 Ωm. In greater depth resistivity values of less than 500 Ωm arefound. The basic distribution of the apparent soil moisture is obviouslyinverse to the corresponding principle resistivity distribution describedabove. Areas with high resistivity are characterised by small apparentsoilmoisture values and vice versa. The values of soilmoisture range be-tween 10 vol.% and 80 vol.% (Fig. 2). In depths greater than two metresthe soilmoisture content amounts to 20 vol.% to 35 vol.%. In general, ob-served apparent soil moisture values N40 vol.% are unrealistic because

there are no recorded soil moisture contents above 40 vol.% by the cal-ibrated TDR probes at the downhill location above the observatory(Fig. 1B). Locally soil moisture contents N40 vol.% can be completely ex-cluded, based on hydrological gravitymodelling approaches and furthersoil moisture measurements in the vicinity of the observatory (Krauseet al., 2009; Naujoks et al., 2010). In addition, maximumporosity valuesof 40 vol.% give the framewhere soil moisture can range. One reason forcalculated high soil moisture content N40 vol.% are different chemicalproperties of the subsurface which results in a reduced validity of theapplied conversion (Shah and Singh, 2005). Thus, the soil moisture con-tent above 40 vol.% can be related to areaswith clay content higher than75% (Shah and Singh, 2005). Therefore, the areas with apparent soilmoistures above 40 vol.% are not included in the interpretation. Typicalapparent soil moisture values are between 10 vol.% and 17 vol.% inthe uppermost two metres as well as distinct punctual structuresin the E–W profile with values greater than 25 vol.% (Fig. 2) FollowingZhou et al. (2001) and Fechner (2003), these punctual structures are re-lated to old tree roots.

Focusing on our results, the resistivity differences of the time-lapse ERT are illustrated by two representative examples (Fig. 3):(1) during a strong precipitation event with more than 80 mm accu-mulated precipitation within three to five days and (2) for the max-imal seasonal resistivity variation. Example (1) of resistivity and soilmoisture variations shows a clear bisection of the subsurface, in par-ticular in the profile parallel to the slope (Fig. 3, left). In this examplethe differences between the two field campaigns before and after theprecipitation event are considered. The resistivity decreases in theupper two metres by 0 Ωm to 300 Ωm. Below this layer the resistiv-ity increases slightly by 0 Ωm to 125 Ωm (Fig. 3, left). The soil mois-ture increases in the upper two metres by 2% to 3% and decreases inthe deeper regions by 0% to 3%.

Example (2) covers the maximal seasonal variation between twofield campaigns in spring and summer 2008 (Fig. 3, right). The resistivityincreases by up to 2500 Ωm in the upper twometres. The highest varia-tions occur in areas of the maximum resistivity values (Figs. 2 & 3,right). Below the upper two metres the resistivity remains constant.These resistivity observations apply to both profiles. The variation ofsoil moisture is homogeneous for the whole subsurface and decreasesby 15% to 25%. Trees next to the profiles are marked in Fig. 3 for verifi-cation of their influence on resistivity and soil moisture variations. Thesoil moisture and resistivity variations caused by trees are only ob-served in the maximal seasonal resistivity and soil moisture variations(Fig. 3, right). The absolute resistivity values near to the surface(depth b1 m) are 200 Ωm to 1000 Ωm smaller in regions with treesthan in regions without trees (Fig. 2). In addition, close to the treesthe soil moisture decreases more significantly by 2% to 5% than in re-gions without trees (Fig. 3, right). Variations between separate fieldcampaigns are not detectable. Therefore, it is concluded that the treeshave only minor influences on the resistivity and soil moisturevariations.

Summarising our results, the resistivity varies in the upper twometresby −1000 Ωm to +700 Ωm between the separate field campaigns. Theresulting soilmoisture variations are−10 vol.% to+20 vol.%. The largestvariations occur as expected in the spring and autumn. In the spring thesmallest resistivities and the biggest soil moisture are found— in the au-tumn it is vice versa.

However, the resistivity along the N–S profile (parallel to slope) isgenerally smaller than along the E–W profile (perpendicular to slope)of up to 400 Ωmdue to the anisotropy of the subsurface (Fig. 2). The re-sistance parallel to striking geological structures is smaller than perpen-dicular to it (Watson and Barker, 1999). Therefore, the NNW–SSEstriking of fissures, foliation and lamination (Kasch et al., 2013) causesthe different resistivity levels at the intersection point of both profiles.Because we consider the variations of resistivity differences betweendifferent field campaigns, the anisotropy effects need to be taken intoaccount.

Table 1Number of time windows and the corresponding types of hydrological events.

Prominent precipiation events Snowmelts

Strainmeter data 8 2Tiltmeter data 5 2

95T. Hermann et al. / Journal of Applied Geophysics 98 (2013) 90–99

4.2. Deformation measurements

The tiltmeter data are presented in hodographs as movement of thependulum tip over ground illustrating the directions of the recorded tilt(Kümpel, 1982; Weise et al., 1999). Furthermore, the tiltmeter data ofthe N–S- and E–W-component are displayed aswell as the hydrologicalparameters water level and accumulated precipitation (Fig. 4B).

The tiltmeter data contain systematic changes. In the investigatedtimewindows typically ellipses and small deflectionswith thepreferen-tial direction NW–SE occur (Fig. 4B). The preferential direction NW–SEis visible before and after the hydrologically induced signals in most ofthe hodographs (Fig. 4B, left). The amplitude of deflections, alternative-ly the semimajor axis of the ellipses, is in the range of 2.5 nrad to

B

A

Fig. 4. Examples of typical strain (A) and tilt measurements (B) of hydrological induced deformtiltmeter measurements represents the movement of the pendulum tip over ground. An increaresponds to dilatation in E–W-andN–S-direction. (Right) E–W-(black) andN–S-component (re(light blue) and accumulated precipitation (dark blue) are given.

10 nrad. For comparison, the tidal deformations have magnitudessmaller than 100 nrad (Jahr et al., 2009). During and after hydrologicalevents, tilt signals with a preferential direction exist in 6 of 8 time win-dows. In 50% of the time windows a tilt to NE is observed with ampli-tudes between 20 nrad to 25 nrad within 1 day to 3 days. In the other50% of the cases the movement runs in southern direction with ampli-tudes between 78 nrad to 122 nrad within 8 days to 10 days (Fig. 4B).The huge southernly directed tilt signals do not reverse within the in-vestigated time windows. Thus, a long-term process is presumed assource. Additionally, if a long-term tilt signal is observed in the data,then simultaneously a big long-term (compressional) signal in thestrain measurements is recorded (Fig. 4).

In general, noticeable variations of the pendulum tip over groundoccur with the beginning of strong precipitation events (N30 mmwith-in 3–5 days) and strongwater level jumps (N150 mm rise, Fig. 4B). Thehydrologically induced deformations are produced by pore pressure gra-dients but these are not identical with water level changes (e.g. Kümpel,1982). The water level changes are only used as indicators for existingpore pressure gradients. Based on our investigations, this assumption isvalid for about 80% of the investigated hydrological events. Furthermore,

ation signals. (Left) Hodographs of the strain and tilt measurements. The hodograph of these corresponds to dips in east and north direction, respectively. An increase of strain cor-d) of the strain and tiltmeasurements. In addition, thehydrological parameterswater level

96 T. Hermann et al. / Journal of Applied Geophysics 98 (2013) 90–99

the lengths of the semimajor axis of the ellipses show nonlinear correla-tions with observed precipitation intensities.

The strainmeter data are also presented in the form of hodographs(Fig. 4A). In the data set no preferential direction is discernible. The rec-ognized directions vary between NW–SE and N–S (Figs. 4A & 5). Thelength of the semimajor axis of the ellipses and the amplitudes rangebetween 3 nstrain and 15 nstrain. In 7 of 11 cases similar strain signalscan be seen in the hodographs (Figs. 4A & 5). In the hodographs a strongcompression occurs in N–S direction parallel to the topography, whichdoes not reverse in the investigated timewindows (Figs. 4A&5). Duringthe hydrological events this N–S compression begins and typically endsseveral days (2–10 days) after the end of the hydrological events. Theamplitude of compression in N–S direction ranges between 40 nstrainand 180 nstrain (Fig. 4A). Before this long-period compression, ashort-period dilatation is observed in N–S direction of 12 nstrain to 23nstrain. In the E–W direction a short-term dilatational signal with am-plitudes of 20 nstrain to 60 nstrain is recorded (Figs. 4A & 5). It shouldalso be mentioned that the long-term compression signal exists simul-taneously to long-term signals in the tiltmeter data (Fig. 4). This isfurther evidence for a common process effecting NS-deformations. Fur-thermore, an increased pore pressure rise, indicating existing pore pres-sure gradients, is necessary to produce the hydrologically induced strainsignals.

The comparison of the observed hydrologically induced strain andtilt signals with hydrological parameters such as amplitude of waterlevel rise, precipitation amount and the duration of water level risesor precipitation events show no obvious correlation. As expected, nosimple linear relations between strain or tilt signals and hydrologicalparameters exist. However, the pore pressure gradient, that is responsi-ble for hydrological deformations, is not measured and only indicatedbywater levelmeasurements (Kümpel, 1982). Therefore, no correlationbetween hydrological deformations and the pore pressure gradient canbe established. Otherwise, qualitative correlations between hydrologi-cally induced deformations and hydrological parameters can be made.The larger the values of hydrological parameters, the bigger thedeformations.

elon

gatio

n in

NS

-dire

ctio

n

elongation in EW-

W

rainfall

W E

Fig. 5. Schematic drift of strain during hydrological events (upper panel) and possible mechaniThemost typical drift is indicatedwith a continuous line and dashed lines showmodifications. Tdue to infiltration of rain in fissures and the following extension of the fissures (left). Dilatatio

5. Discussion

5.1. ERT

The time-lapse ERT measurements show resistivity changes in theupper two metres with 2000 Ωm of variations (Fig. 3). Disregardingvariations in salinity, flow processes are predominantly within theweathering layer in the upper two metres. Spatial soil moisture varia-tions show different characteristics. The soil moisture variations showalso a defined bisection of the subsurface like in the resistivity varia-tions, but significant changes occur in depths greater than two metres(Fig. 3). This apparent contradiction to resistivity changes may becaused by the empirical relation (3) used for the conversion of resistiv-ity data to soil moisture values. This relation produces larger soil mois-ture variations at low resistivity values than at high resistivity values forthe same resistivity changes. In particular, in depths greater than twometres, the resistivity is lower than 2000 Ωm, resulting in soil moisturevariations N20 vol.% for resistivity changes b50 Ωm (Fig. 3). The maxi-mum soil moisture variation in the upper two metres is ca. 20 vol.%,which is in a similar order of magnitude as that observed with a TDRprobe rod in this area (Fig. 3). Below two metres depth the soilmoisture varies stronger than in lesser depths. Former time-lapseelectromagnetical investigations of Dlugosch (2006) suggest that(1) variations of the resistivity near the surface are affected bymoisturevariations and (2) deeper resistivity variations are dominantly based onsalinity variations (McNeill, 1980; Pozdnyakov et al., 2006). This obser-vation is also confirmed by conductivity measurements of the creekSilberleite which is fed by water coming from the surrounding hillflanks.

Following McNeill (1980), salinity variations can be explained bybiological (e.g. formation of organic acids) and geological processes(e.g. weathering). During dry periods a near surface accumulation ofproducts from these processes takes place. In the undissolved statethese final products have no impact on the resistivity of the subsurface.Smaller precipitation events lead to dissolution and to a mainly verticaltransportation of these products to deeper soil layers. Therefore, usually

direction

E

sms for hydrological induced signals (lower panels; after Yamauchi, 1993). (Upper panel)he arrow shows the direction of the drift. (Lower panels) Compression of the strainmetersn of the strainmeters due to increased loading effects in the valley (right).

97T. Hermann et al. / Journal of Applied Geophysics 98 (2013) 90–99

dry conditions result in higher resistivities and wet conditions in lowerresistivities (Archie, 1942). Repeated desiccation of the subsurfacecauses a high ionic concentration of the pore fluid. This enrichment ofions might reduce the resistivity of the deep soil during dry periods(Fig. 3, right). Long (N2 days) or strong precipitation events (N80 mm)wet the whole subsurface, which dilute the saline pore fluids. Then, anincreased vertical flow exists and, therefore, the ions are removedfrom the area, in particular in depths larger than twometres. The lattercase may result in a resistivity increase caused by strong moisture pen-etration of the subsurface (Fig. 3). These resistivity variations in thedeep subsurface, caused by strong precipitation events, long precipita-tion periods or long dry periods, are found for 80% of the ERT. In addi-tion, the border between the near surface and the deep regions can bedelineated in twometres depth (Fig. 3). The low soil moisture contentin the upper two metres of the subsurface, compared to the highsoil moisture in deep regions, confirms former investigations ofDlugosch (2006) in the vicinity of the Moxa observatory. Accordingto Pozdnyakov et al. (2006), in regions with low soil moisture con-tent (b25%, Fig. 2), the soil moisture reflects itself in the resistivity var-iations and in regions with high soil moisture content (N25%, Fig. 2)mostly chemical and physical characteristics of the soil are reflectedby the resistivity variations. Although the salinity variations of thepore water are not measured directly, this interpretation is reasonable(e.g. Dlugosch, 2006; Krause et al., 2009; Vermue and van de Voorde,2005). Based on our results, the apparent soil moisture variations indepths greater than two metres likely result from salinity variations.This result supports the occurrence ofmoisture content variationswith-in the upper two metres.

5.2. Deformation measurements

In only 20% of the investigated timewindows no or only small hydro-logically induced signals are observed in the strain and tilt data. Other-wise significant hydrologically induced signals are found. This findingleads to the assumption that only a certain minimumwater level rise in-dicates emerging pore pressure variations or gradients, respectively. Fur-thermore, pore pressure gradients result in simultaneously recordedsignals in the strain and tilt data. Similar observations were also madeby Dal Moro and Zadro (1998). These authors found that a minimal pre-cipitation amount per day was sufficient for obtaining hydrologicallyinduced deformations in near surface earth crust in strain and tilt mea-surements. This result supports the assumption that hydrological in-duced deformations are controlled by nonlinear processes (Dal Moroand Zadro, 1998). However, to some extent linear relations can befound, depending on the rock fabric and hydrology (e.g. Braitenberg,1999; Tenze et al., 2012).

Possible explanations for the deformations are shown for exampleby Yamauchi (1993) (Fig. 5, lower panels). The compression of thestrainmeter is caused by infiltration of rainwater in fissures and the fol-lowing extensionof thefissures (Fig. 5, lower panel left). This type of de-formation is not valid for the quartztube-strainmeter in Moxa due toNNW–SSE and N–S trending fissures. Furthermore, no short-term com-pression signal (20 nstrain–60 nstrain) of the E–W strainmeter is ob-served (Fig. 4A). Because of mainly parallel to fissure orientatedcompression, the N–S compression cannot be explained by this type ofdeformation. The second model of Yamauchi (1993) leads to increasedloading effects in the valley (Fig. 5, lower panel right). This may be apossible explanation for the recorded extension signals in E–W direc-tion at Moxa observatory. The loading effect can be caused by variedloadings of the valley infill between dry and wet conditions. The long-term compression signal in N–S direction cannot be caused by a lakelevel rise of the Hohenwarte reservoir 4 km south of the observatoryand the following loading effect due to expected extensions in N–S di-rection (Steffen and Kaufmann, 2006).

The observed tilt changes by hydrological events are induced bypore pressure variations (Jahr et al., 2009). The observed tilt changes

in S to S–E direction (20 nrad–122 nrad, Fig. 4B) are consistent withthe drainage direction near the observatory building (Fig. 1A). Fromthis observation it can be inferred that precipitation events and snow-melts increase the pore pressure in the north of the local catchmentarea resulting in a pore pressure gradient with decreasing values tothe south parallel to the drainage direction. This N–S toNW–SE trendingpore pressure gradient with higher values in the north causes tiltchanges in S to S–E direction. Thismechanismmay also be a possible ex-planation for the long-term compression in the N–S component of thestrain data (40 nstrain–180 nstrain, Fig. 4A). The resulting pore pressuregradient causes a compression in N–S direction. After the hydrologicalevents, the pore pressure gradient disappears and an equilibrium statedevelopswithout anyhydrologically induced compression and extension.This process is reflected in the N–S-component of the quartztube-strainmeter (Fig. 4A). The subsequent inversion of this process is not al-ways seen in the data because of the lengths of the selected time win-dows. Therefore, the duration of this process is likely longer than 7 days.

These time constants depend on the local rock fracturing, which canbe finding out by comparing hydrological induced strain and tiltresponse at different stations (Braitenberg, 1999; Grillo et al., 2011;Longuevergne et al., 2009; Tenze et al., 2012). However, the duration ofthese hydrological induced deformations still vary according to the hy-draulic response of the subsurface to hydrological events. The hydraulicresponse mainly depends on soil conditions, water infiltration rate,water runoff, and conductive fractures (Grillo et al., 2011; Jacob et al.,2010; Longuevergne et al., 2009; Tenze et al., 2012; Zadro andBraitenberg, 1999). Again, these parameters depend mainly on the rocktype housing the station. For example, other stations in the Alps orKarst (Italy and France) show a high percentage of fracturing and highconductive fracturing as well. Thus, a minimum intake of water into therocks is necessary for emerging of a linear relation for both strain andtilt with typical directionalities. The observed linear relations evolve pre-dominantly perpendicular to fractures and faults as well as along thewater runoff (Grillo et al., 2011; Jacob et al., 2010; Longuevergne et al.,2009; Tenze et al., 2012). For Moxa observatory, located in the Variscanbelt, the surrounding hills are much older and, therefore, more compact.Consequently, lesser well defined flow patterns as well as aligned cracksand faults exist, resulting in no typical directionalities of hydrological in-duced deformations and linear relations between deformations and hy-drological parameters. However, maybe the hydrological induceddeformation signals can be used for characterising the fracturing ofrocks housing the station. Emerging linear relations might indicate welldefinedwater runoff and conductive fractures. On the other hand, the ab-sence of such linear relations, like at Moxa observatory, characterises re-duced subsurface water flow paths and compact bedrock.

6. Conclusions

6.1. ERT

The resistivity and soil moisture distributions show a bisection of thesubsurface with a distinct transition in two metres depth. In the upperpart the resistivity values are larger than 1000 Ωm and in the deeperpart the resistivity values are smaller than 200 Ωm. The observed bisec-tion can be interpreted as soil or weathering layer and transitional layerto the subjacent jointed basement.

The time-lapse ERT shows resistivity values which are varying in theupper two metres by up to 2000 Ωm. This results in soil moisturecontent variations predominantly in depths up to two metres and themaximum soil moisture variation is 25 vol.%. In deeper parts of the sub-surface the soil moisture apparently varies stronger than above (up to30 vol.%). This apparent contradiction between electrical resistivity andsoil moisture variations is a result of the empirical relationship used forthe conversion of electrical resistivity into soil moisture values. Improve-ments of the empirical relationship require additional investigations likefurther comparisons between ERT and soil moisture measurements in

98 T. Hermann et al. / Journal of Applied Geophysics 98 (2013) 90–99

particular for depths greater than two metres with clay contents above75%. However, the apparent soil moisture variations indicate significantsalinity variations in depths greater than twometres and real soil mois-ture variations within the upper twometres. Thus, hydrological modelsat Moxa observatory can be improved, in particular at the eastern hillflank above the observatory building. Consequently, the hydrologicalimpact on the data of gravimeters will be reduced.

6.2. Deformation measurements

In about 20% of the investigated time windows no or only small hy-drologically induced signals in the strainmeter and tiltmeter data areobserved. That means only a certain minimum change in the amountof stored water is sufficient for pore pressure variations or gradientsand for recording of simultaneously hydrologically induced signals indeformation measurements. This supports the hypothesis that hydro-logically induced deformations are controlled by nonlinear processesas expected.

The short-term dilatational signal in the E–W-component of thequartztube-strainmeters (20 nstrain–60 nstrain) with durations shorterthan three days can be explained by a temporarily increased load of thevalley area. A similar mechanism with loads caused by the Hohenwartereservoir 4 km south of the observatory is not applicable due to observedcompression in the NS-component of the quartztube-strainmeter andnot of dilatation which should be expected.

During hydrological events the recorded tilt variations in S–SE direc-tion (20 nrad–122 nrad) are produced by pore pressure gradients. Thedirection of the observed tilt variations is nearly the same as the drain-age direction near the observatory building. Therefore, a pore pressuregradient parallel to the drainage direction obviously produces the tiltvariations. This mechanism may also be a possible explanation forthe compression signal in the N–S-component of the quartztube-strainmeter (40 nstrain–180 nstrain).

For the hydrological correction algorithms in strain and tilt data, hy-drological models with detailed information about local groundwaterflow processes and resulting pore pressure gradients are necessary.Thus, the nonlinear processes at the Geodynamic ObservatoryMoxa, in-cluding the phase shift between the beginning of precipitation eventand deformation, can be modelled properly. Otherwise, corrections onhydrological induced deformations can be minimised by observationpoints in areas with no topography, resulting in reduced horizontalpore pressure variations.

Acknowledgements

The technical support of the Geodynamical Observatory Moxa andduring the ERT measurements by Wernfrid Kühnel and MatthiasMeininger is greatfully acknowledged. The authors also thank RebekkaSteffen, David Markwart and Peter Schindler for their support ofthe ERT measurements. The meticulous review of the manuscript byC. Braitenberg and an anonymous reviewer greatly improved the man-uscript, which is also acknowledged.

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