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Monitoring the transition from preferential to matrix flow in cracking clay soil through changes in electrical anisotropy
Geoderma 179–180 (2012) 46–52
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Monitoring the transition from preferential to matrix flow in cracking clay soil through changes in electrical anisotropy A.K. Greve ⁎, M.S. Andersen, R.I. Acworth Connected Waters Initiative, Water Research Laboratory, University of New South Wales, 110 King Street, 2093 Manly Vale, NSW, Australia Affiliated with the National Centre for Groundwater Research and Training, Australia
a r t i c l e
i n f o
Article history: Received 27 June 2011 Received in revised form 30 January 2012 Accepted 3 February 2012 Available online 19 March 2012 Keywords: Electrical resistivity Square array Soil cracks Preferential flow Stable isotopes
a b s t r a c t Transition from preferential flow to matrix flow in a vertisol was investigated by combined use of square array resistivity measurements and stable water isotopes. Two irrigation events with water of different water isotope composition were carried out on a 0.5 m deep initially dry and cracked soil profile in a weighing lysimeter. Throughout the irrigation events, depth profiles of resistivity square array measurements were collected to calculate profiles of the anisotropy index (AI) and mean resistivity. The stable isotope composition of the drainage water showed that water from the second irrigation bypassed the soil matrix with limited mixing to form the collected drainage. This bypass showed that even though the soil cracks at the surface were visually closed at the onset of the second irrigation, preferential flow paths must have remained open. Changes of the AI with applied irrigation volume were used to detect the dominant flow processes in the soil, with a stable AI indicating matrix flow and an unstable AI indicating preferential flow. The AI showed that over the course of the irrigation events the dominant flow process changed from preferential flow to matrix flow. The use of the AI allowed for the first time to detect the exact timing of this transition. Matrix dominated flow didn't occur until ponding water at the soil surface was observed. The onset of matrix flow started at the top of the profile and progressed downwards. Complete crack closure in terms of water flow occurred long after visual closure of soil cracks and could be detected by monitoring changes in the AI. © 2012 Elsevier B.V. All rights reserved.
1. Introduction Cracking clay soils are common in irrigated areas in many parts of the world. While their high nutrient content and water holding capacity make them highly productive soils, their susceptibility for preferential flow creates challenges for agricultural management of water and solutes. Preferential flow can quickly transport nutrients and pesticides through the unsaturated zone and bypass the soils capacity for storage, adsorption and transformation of potential pollutants before these reach surface or ground waters (Bronswijk et al., 1995; Jaynes et al., 2001). Investigations of flow in cracked soil have reported flow velocities reaching similar levels as overland flow (Beven and Germann, 1982) indicating that soil cracks can play a very significant role in soil water transport. However, it has also been shown that the hydraulic conductivity of initially cracked soil decreased by an order of magnitude during soil swelling (Leeds-Harrison et al., 1986). Due to the shrink and swell characteristics of clay soils, the volume and connectivity of macro-pores decreases with increasing soil moisture content (Lin et al., 1998) and it is assumed that in a fully swollen soil, once
⁎ Corresponding author. Tel.: + 61 280719800; fax: + 61 299494188. E-mail address: [email protected] (A.K. Greve). 0016-7061/$ – see front matter © 2012 Elsevier B.V. All rights reserved. doi:10.1016/j.geoderma.2012.02.003
macro-pores have been entirely closed, water and solutes will be transported through the soil profile by matrix flow (Bouma and Loveday, 1988; Youngs, 1995). However, the timing of complete crack closure varies; cracks between structural peds of drained heavy clay soil may remain open even after extended wetting periods (Beven, 1980) and it is difficult to experimentally determine how long macropores actively contribute to preferential flow (Beven and Germann, 1982). Effective management of the risks associated with preferential flow and transport in irrigation agriculture on cracking soils requires a comprehensive understanding of the temporal variations in hydraulic properties associated with different water applications. Ideally this would allow adjusting the timing of water, nutrient or pesticide application to the expected flow processes in the soil. Reviewing the present state of our understanding of flow in soil macro-pores Jarvis (2007) concluded that further advances in our understanding are expected from new experimental techniques that relate macro-pore structure to flow and transport observations. Further he called for the development of simple indices or descriptors of soil macroporosity and/or resulting flow patterns to assess the likelihood of preferential flow in soil horizons. This study does both. It combines a new in-situ technique to monitor subsurface crack dynamics with stable water isotopes to assess the dominant flow processes in a soil profile. Combining these two
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techniques allows relating the observed flow processes to a simple index of soil heterogeneity, which for the first time allows detection of the transition from preferential flow to matrix flow within a soil profile. Greve et al. (2010a) introduced the use of anisotropy index profiles obtained from square array resistivity measurements to nondestructively monitor in-situ crack dynamics in the subsurface. Here the use of this in-situ technique is extended and combined with profiles of average resistivity to characterise flow dynamics in cracking soil. The change of these two parameters is monitored throughout water applications on an initially dry and cracked soil profile. In conjunction with stable water isotopes this allows investigating the interplay of subsurface crack dynamics and preferential flow in a lysimeter. Further it allows direct detection of the transition from a preferential flow dominated system to a matrix flow dominated system as the water content increases. A better detection of this transition in the field will provide valuable information for optimising the timing of water, nutrient, and pesticide applications. 2. Theory Measuring the flow of electrical current through the subsurface can provide rapid and useful information about physical and chemical properties of the soil. In the electrical resistivity method, a low frequency alternating current (I) is applied to the ground by two current electrodes and the resulting potential difference (Δϕ) is measured with two potential electrodes. Most commonly the four electrodes are arranged in a straight line along the soil surface, but a variety of other arrangements are possible (Bing and Greenhalgh, 1997; Dahlin and Zhou, 2004). In the square array, the electrodes are arranged to form a square on the soil surface (Fig. 1). There are three independent arrangements of the current and potential electrodes within a square, which have been termed the α, β, and γ arrays (Habberjam and Watkins, 1967). As derived in detail by Greve et al. (2010a), the potential differences measured with the α, β, and γ arrays (Δϕα, Δϕβ and Δϕγ) are related as follows: Δϕβ + Δϕγ = Δϕα and in isotropic and homogeneous ground Δϕγ = 0 and Δϕα = Δϕβ. However, if heterogeneities are present, the apparent resistivity (ρa) in the measurement volume that influences the potential at the two potential electrodes varies with the electrode position, so that in most cased Δϕγ ≠ 0 and Δϕα ≠ Δϕβ. In heterogeneous ground, the measured resistances Δϕ Rα ¼ ΔϕI α and Rβ ¼ I β and the apparent resistivities for the total measurement volume influencing the α and β measurements (ρaα and ρaβ) will therefore differ. The ratio of Rα and Rβ, in the following referred to as the anisotropy index (AI), provides a measure of the directional variation of the resistance measurement. Soil cracks generally result in an anisotropic
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alteration of the electric field and hence cause the AI to deviate from unity. Samouelian et al. (2004) related AI variations from unity to surface cracks and Greve et al. (2010a) used depth series of AI measurements on horizontal co-planar square arrays to create AI profiles, which allowed monitoring soil crack dynamics within a soil profile. In addition to the calculation of the AI, the use of the square array also allows the calculation of the average apparent resistivity (ρam), which is the average of ρaα and ρaβ. While the AI is a measure of the heterogeneity in the measurement area, ρam gives an average apparent resistivity value that is relatively independent of the orientation of the electrode array and hence the heterogeneity (Habberjam and Watkins, 1967). 3. Methods 3.1. Lysimeter setup The presented experiment was carried out in a lysimeter. The lysimeter consisted of a fibreglass barrel (inner diameter: 1.3 m, depth: 0.78 m) placed onto a weighing scale, which was logged at 30 min intervals to determine evaporation losses. The barrel was tilted at an angle of 8° and had a 28 mm diameter drainage opening cut into the lowest point of its side wall (Fig. 2). In September 2002 the lower 50 mm of the lysimeter were filled with 195 kg of well flushed river gravel followed by a 500 mm deep layer of mixed vertisol from Breeza in New South Wales, Australia. The vertisol had a CEC of 62 meq/100 g and was made up of a sand, silt, and clay fraction of 16%, 20%, and 64%, respectively. Ca-montmorillonite made up 90% of the clay fraction, with the remaining clay fraction consisting of kaolinite. Before the soil was added to the lysimeter it was thoroughly mixed when dry. Water was added and it was worked into a homogenous soil paste. Once the soil paste was poured into the lysimeter, it was flushed with 500 mm of tap water, which had an electrical conductivity (EC) of 0.2 mS/cm and a sodium adsorption ratio (SAR) of 1.3. The water was applied over a 3 day period. Following the initial set up of the lysimeter, the soil was exposed to a total of ~40 separate irrigation and drying events over a period of 7.5 years, as described in more detail by Greve et al. (2010b). During these repeated drying and wetting periods an aggregate structure was re-established in the soil. 3.2. Electrode installation In December 2008 four electrode strings were vertically installed into the soil profile. The electrode strings consisted of 9 ring-shaped electrodes (38 mm diameter) with 50 mm inter-electrode spacing. Assembly of the electrode strings is described in Greve et al. (2010a). To allow electrode installation, four 450 mm deep vertical holes (40 mm diameter) were hand-augered into the dry soil profile.
Fig. 1. (a–c) Plan view of a square array with α, β, and γ configurations, with C1 and C2 being the current source and sink, P1 and P2 being the potential electrodes, and a being the side length of the square.
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Fig. 2. (a) Cross section of lysimeter setup and (b) sketch of horizontal planes for square array measurements between the four vertical electrode strings in the lysimeter.
During augering, the hand-auger was held in place by a wooden plank with a circular notch to ensure vertical augering. The extracted soil material was worked into a putty-textured soil-water paste, which was used to cover the electrode strings prior to insertion into the augered holes. Once installed, the electrode strings formed a horizontal electrode square with a = 500 mm at each electrode depth (Fig. 2). To avoid disturbance of the crack walls, the electrodes had been installed within stable soil peds. The four electrode strings were therefore not perfectly centred within the lysimeter, instead the centre of the electrode square at the soil surface was offset from the centre of the lysimeter by 0.04 m (Fig. 2). 3.3. Water application and stable water isotope tracing Two irrigation events were carried out on 22 June 2010 and 5 July 2010, with 50 mm (32 mm/h) being applied during the first irrigation and 75 mm (26 mm/h) during the second irrigation. At both events the irrigation water was evenly applied with a watering can. The water that was used for the two irrigation events came from different sources and consequently had different stable water isotope signatures. Tab water was used for the first irrigation (δD = − 16.19 ± 0.35‰, δ 18O = − 2.55 ± 0.02‰) and local dam water from Manly Dam, New South Wales, Australia was used for the second irrigation (δD = − 7.6 ± 0.26‰, δ 18O = − 1.09 ± 0.07‰). Drainage out of the lysimeter was collected and its isotope composition was analysed with a Los Gatos Research Liquid-Water Isotope Analyzer (DLT-100v2) connected to an auto injector from CTC Analytics. A camera was mounted 1.45 m above the soil surface and surface images were taken every 5 min throughout the two irrigation events. 3.4. Square array resistivity measurements A resistivity measurement protocol that measured Rα, Rβ, and Rγ for the horizontal electrode squares at each electrode depth in the lysimeter was created. The protocol, which consisted of 27 measurements, was uploaded to an ABEM SAS4000 terrameter and was run every 5 min throughout each of the two irrigation events. Measurements were made by applying a maximum current of 20 mA. The protocol was run with one stack (no repeat measurements were used), which resulted in a measurement time of ~ 90 s. Rather than assessing the noise through repeat measurements, which would have resulted in an increased measurement
time, the quality of the acquired data was determined based on the tripotential error:
Etp ¼
Rα − Rβ þ Ry Rα
Depth profiles of the AI and the ρam were determined for each protocol run. 3.5. Soil sampling A total of 5 soil cores were taken with a 40 mm diameter push tube and the gravimetric soil moisture content was determined for 50 mm depth intervals of the cores. A core was taken before each of the irrigation events and three cores were taken 2 weeks after the 2nd irrigation event. The first of the three cores taken after the irrigation events was cored on a previous crack location, while the other two were cored on previous soil peds (matrix locations). Soil sampling right after the irrigation events was not carried out as the stickiness of the freshly irrigated soil did not allow depth specific sampling with the coring method applied here. To prevent the creation of artificial preferential flow paths, the first two soil cores were only cored to a depth of 350 mm, while the later three soil cores were cored through the entire depth of the soil profile (500 mm). The holes from the first two soil cores were back filled with dried vertisol powder, which was tightly pressed into the augered hole with a 35 mm diameter wooden staff. In addition, bulk density measurements were made 2 weeks after the 2nd irrigation event. Sampling for bulk density was carried out in 0.05 m depth intervals. A 50 mm deep soil ring with an inner diameter of 25 mm was used to collect 0.098 L of soil. The surrounding soil was dug out with a hand held shovel before a consecutive depth was sampled. The soil was dried at 110 °C to determine its dry weight and dry bulk density. Finally, the porosity was estimated, assuming a grain density of 2650 kg/m 3. 4. Results and discussion 4.1. Water application Prior to the onset of the first irrigation, the soil surface was heavily cracked, with surface cracks of up to 30 mm width (Fig. 3a).
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Fig. 3. Soil surface (a) before irrigation 1, (b) after irrigation 1, (c) 16 mm into irrigation 2 (total of 66 mm applied), and (d) 40 mm into irrigation 2 (total of 90 mm applied).
Throughout the first irrigation surface runoff into the soil cracks was observed. This surface runoff caused erosion and occasionally collapse of the crack walls at the top of the profile, with the eroded and collapsed material being washed into the soil cracks. At the end of irrigation 1, the soil cracks were closed, however due to the erosion and collapse of the crack walls, former soil cracks remained visible as steep surface depressions with a depth of up to 70 mm (Fig. 3b). During irrigation 2 standing water occurred in the surface depressions (Fig. 3c). Once the standing water had infiltrated, the depressions had disappeared (Fig. 3d). The first effluent occurred 2 h 55 min after the start of the second irrigation, when a total of 125 mm had been applied (50 mm in irrigation 1 and 75 mm in irrigation 2). In total 18 mm of drainage occurred over a period of 3 days, with the first 11 mm occurring within the first 3 h of the drainage event. The isotope composition of the drainage water was similar to that of the water applied during irrigation 2 (δD = − 7.6 ± 0.26‰, δ 18O = −1.09 ± 0.07‰), with δD values that varied between −9.49 ± 0.66 and −6.35 ± 0.39‰ and δ 18O values that varied between −1.63 ± 0.09 and − 0.32 ± 0.05‰ (Fig. 4). This strongly indicates that water from irrigation 2 not only bypassed the soil matrix (where presumably irrigation 1 water was residing) but drained out of the column with limited mixing. This direct bypassing of water from irrigation 2 shows that even though at the onset of this irrigation the soil cracks were visually closed at the surface, preferential flow paths must have remained open. This observed preferential flow after visual crack closure is consistent with a similar yet less conclusive breakthrough of a bromide tracer observed by Greve et al. (2010b). The occurrence of preferential flow after visual crack closure, calls for a closer inspection of the dynamics of the crack network and hence the preferential flow paths within the soil profile. Investigation of the changes in the soil water content (SWC) and the square array resistivity measurements will allow doing so.
4.2. Soil parameters and water content The SWC in the entire measured moisture profile increased during both irrigation events (Fig. 5), which highlights that the soil was still below field capacity after irrigation 1. This suggests that capillary suction and/or preferential flow did significantly contribute to the wetting of the soil matrix during irrigation 1, since under piston flow conditions the upper part of the soil would reach field capacity before water continues to propagate deeper into the profile. Except for one soil sample taken at the surface, the soil core that was taken on a previous location of a surface crack shows a higher SWC in the upper 0.3 m of the soil column, than the two cores that were taken on previous soil peds (Fig. 5). This suggests preferential wetting along soil cracks and hence preferential flow through cracks during at least the initial part of the water application. The only exception to the increased soil moisture at the former crack location is one soil sampling point at the top of the profile (0.05 m depth), which shows higher soil moisture on a former soil pad. This higher water content could be explained by the concave shape of the surface of larger soil peds, which results in shallow depressions that directly collect irrigation water that can then infiltrate. The soils bulk density varied randomly over depth and was determined to be 0.81 g/cm 3 with a standard deviation of 0.10 g/cm 3, resulting in an estimated porosity of 70 ± 4%. 4.3. Square array resistivity results The ρam profiles in Fig. 6 show a clear correlation with the water application with a decrease in the resistivity from about 60 Ω m after 15 mm of irrigation to about 18 Ω m after 125 mm. The ρam varies little over depth at any given time apart from the slightly higher ρam-values that can be seen in the upper two measurement depths after the application of 15 mm. The AI profiles increase throughout
Fig. 4. Stable water isotope composition of the two irrigation waters and the collected drainage samples.
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Fig. 5. Gravimetric soil water content determined by soil coring before water application and after irrigations 1 and 2.
the two irrigation events from values that are smaller than 1 towards a profile with AI's of 1 ± 0.2. Greve et al. (2010a) derived a cracking depth range from AI profiles. As an inhomogeneity needs to be present to produce an AI deviation, they concluded that the deepest maximum of the AI deviation indicates the minimum cracking depth. Individual cracks might exceed this depth and end somewhere between this last pronounced maxima and the depth where the AI reaches the stable value that indicates non-cracked conditions. The cracking depth range reaches from the depth of the last pronounced maximum of the AI deviation to the depth where the AI indicates stable, non-cracked soil conditions. At the start of irrigation 1, the last pronounced maximum in the AI deviation was at 0.3 m depth and at the start of irrigation 2, it was at 0.05 m, indicating that cracks extended to at least these depths (Fig. 6). This initial cracking depth of at least 0.3 m is consistent with the depth of preferential wetting of 0.3 m as indicated by the soil cores taken after irrigation 2 (Fig. 5) and the cracking depth of at least 0.05 m at the onset of irrigation 2 is consistent with the 0.07 m deep surface depressions that were observed after irrigation 1. While the AI profiles in Fig. 6 give an indication of the cracking depth and hence the depth of preferential flow paths, they do not give any information about the actual occurrence of preferential flow within the soil profile. In the following it is proposed that detailed plots of the AI against irrigation volume as in Figs. 7 and 8 provide this missing information. Throughout the irrigation process, the ρam-values measured in the soil profile at any one time vary from the mean ρam by 4–8%. The mean ρam per measurement interval shows a continuous decrease in resistivity from 93.7 Ω m at the beginning of irrigation 1, when 12 mm had been applied to 16.7 Ω m at the end of irrigation 2 when a total of 125 mm had been applied. (Note: Square array measurements that were collected in the dry soil before the application
Fig. 7. Development of ρam and of the AI at selected depth intervals throughout irrigations 1 and 2.
of the initial 12 mm of water had a large tripotential error and were removed from the dataset.) The decrease in ρam is stronger in the beginning of the irrigation period and diminishes as more water has been added, which is consistent with the power law relationship that is generally assumed between the bulk resistivity of a porous medium and its saturation (Waxman and Smiths, 1968). Compared to the large depth variation of AI (also Fig. 7), the variation of ρam with depth is low. Particularly at the beginning of irrigation 1, when the soil moisture showed a strong depth gradient (Fig. 5) a larger gradient of ρam with depth could be expected. The low measured variation can be explained by the fact that the median depth of
Fig. 6. Depth profiles of ρam and the AI at selected measurement intervals during irrigations 1 and 2 (Note: AI and ρam at 40 mm depth, could not be determined due to lack of electrode contact).
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Fig. 8. Development of the AI at all depth intervals during the application of the final 79 mm of irrigation water (Note: AI at 40 mm depth, could not be determined due to lack of electrode contact).
investigation (Edwards, 1977) of the square array in the lysimeter (0.23 m) is relatively large compared to the depth increments in which the square array measurements are made (0.05 m). Additionally, current has the tendency to preferably flow through areas of least resistance, resulting in resistivity measurements to be more sensitive to low resistive regions of the subsurface. Furthermore, the effects of heterogeneity are largely eliminated in the ρam (Habberjam and Watkins, 1967), so that differences in heterogeneity, which strongly impact the AI, are not (or only negligibly) expressed in the ρam. Unlike the AI, which is influenced by changes in heterogeneity in depth and time, the ρam is dominated by similar low resistive regions of the soil profile, regardless of the measurement depth. While the ρam-values at all measurement depths continuously decrease throughout the two irrigation events, the AI's show different trends for different measurement depths (Fig. 7). The AI measured at 0.05 m shows a steady increase during the application of the first 66 mm, before it reaches a stable value of 0.82 ± 0.01. The AI's measured at the soil surface show a similar behaviour, but are for visual clarity not displayed in Fig. 7. In the deeper part of the profile, the AI graphs are more complex, with three distinct peaks in AI. To facilitate the discussion of the AI behaviour, the following, three AI states are defined: an AI that remains constant over time is defined as stable state, an AI that fluctuates and shows local minima and maxima is defined as an unstable state, and an AI that steadily moves towards its stable state is defined as a transition state. The majority of AI's measured at the beginning of irrigation 1 were in an unstable state, with a gradual move towards transition or stable states during the course of the irrigation (Fig. 7). As a changes in the AI must be due to the influx of some quantity of irrigation water and potentially the consequent soil swelling or changes in pore water EC within the soil volume that influences the square array measurement. It is proposed that the three AI states indicate different flow regimes. With an unstable AI state indicating preferential flow and hence local changes in both the soil moisture
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and the crack system itself. These local changes can temporarily increase or decrease the electrical heterogeneity of the soil profile, and hence can result in local AI minima and maxima. A stable AI on the other hand is indicating a stable system, which could either be steady state preferential flow with no local change in the soil moisture content or complete crack closure and a change in the flow regime from preferential flow to matrix flow. As the water supply in this study was discontinuous the occurrence of steady state preferential flow can be excluded. In between these two states is the transition state highlighted by an AI that steadily moved towards a stable value. The transition state indicates a soil that through swelling becomes increasingly homogeneous. The proposed interpretation of the three AI states indicates a general move from a preferential flow dominated system to a matrix flow dominated system throughout the irrigation process. While such a transition has been hypothesised for flow in cracking soils (Bouma and Loveday, 1988; Youngs, 1995), this dataset provides unique physical evidence for the hypothesis and further allows the detection of the timing of this transition. Initially the upper part of the profile, which influences the square array measurements at 0.00 and 0.05 m depth, is in transition (Fig. 7). This indicates that the water that infiltrates into the soil peds at the surface causes soil swelling and crack closure in this part of the profile. Deeper parts of the soil that influence the square array measurements from 0.10 to 0.45 m depth, show the unstable state (Fig. 7). Here, preferential flow results in temporal variation of the electrical heterogeneity and hence causes the local minima and maxima in the AI. Throughout irrigation 1 preferential flow eventually gets absorbed by the soil matrix (no effluent occurred) and therefore contributes to wetting and swelling of the soil, resulting in a change into the transition state. During irrigation 1 this change into the transition state is completed for the measurement depth of 0.10 m, which only shows the first of the three local AI maxima in Fig. 7. At greater depth however, the soil still shows unstable conditions during irrigation 2. These initial flow processes during irrigation 1 correspond with the three stage process of macro-pore flow defined by Hoogmoed and Bouma (1980), which consists of vertical infiltration into the soil peds at the surface, downward flow within the macro-pores, and horizontal absorption from soil cracks into the soil matrix. The continuation of change in AI's during irrigation 2 demonstrates that the soil column has not reached its stable state after irrigation 1. This agrees with the stable isotope results (Fig. 4), which show that water from irrigation 2 bypassed the soil matrix and formed the drainage water. Even though surface soil cracks visually appear closed after irrigation 1, further preferential flow and soil swelling occur during irrigation 2, before the AI reaches its stable state at the end of irrigation 2. Fig. 8 shows that the final stable AI's that are measured in the soil profile at the end of irrigation 2 show a consistent increase from 0.82 at 0.05 m depth to 1.06 at 0.45 m depth. This consistent increase with depth is most likely due to the fact that the entire lysimeter is tilted at 8°, while the electrode strings are installed vertically to the soil surface. This setup results into a gradual change in distance to the side walls of the lysimeter with depth. Based on the 0.04 m offset of the electrode square from the centre of the lysimeter at the surface and the 8° inclination of the lysimeter walls, the electrode strings would be at the centre of a horizontal plane through the lysimeter at 0.28 m depth. Under completely homogeneous soil conditions, the AI at 0.28 m would hence be unity, and indeed the final AI's measured at 0.25 and 0.30 m depth are very close to 1, indicating that the stable AI state has indeed been reached for the profile. The stable AI state and hence a transition towards matrix flow is first indicated in the upper part of the profile (Figs. 7 and 8). This occurs after the application of 70 mm at the same measurement interval when standing water is first observed on the soil surface. Considering the constant irrigation rate, the occurrence of standing water suggests
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a decrease in the bulk hydraulic conductivity of the upper soil profile and supports the indicated transition from faster preferential to slower matrix flow. The local AI maxima and minima that are measured at the immediate soil surface (Fig. 8) can be explained by the local filling of the surface depressions, which do not occur at the same time for all depressions and therefore cause small fluctuations in the AI. Once the transition to matrix flow has occurred at the surface, the expression of the unstable state in the lower part of the profile changes as well. Inspection of the three local AI maxima in Fig. 7 shows that the rising, peaking, and decreasing sections of the first two peaks are occurring in the same measurement interval for all depths between 0.15 and 0.45 m. The last peak however, which occurs after transition to matrix flow at the top of the profile, shows an offset of the peak for different measurement depth (Fig. 8). The peak is measured at the same time interval for measurement depth 0.15 and 0.25 m (the peak at 0.2 m is not well pronounced). Starting from a measurement depth of 0.30 m downwards the peak is offset towards later measurement times and the extent of the offset increases with depth. This offset could indicate a slower and in volume diminished preferential flow in the now almost closed soil cracks. Whereas at the beginning of the irrigation process, preferential flow occurred fast and affected the entire unstable part of the profile within one measurement interval, the flow process is now slowed down and takes several measurement intervals to flow through the soil column. 5. Conclusion Combined use of square array resistivity measurements and stable water isotopes allowed unique insight into the flow dynamics in a vertisol. The stable isotope composition of the drainage water that was collected at the bottom of the lysimeter showed that water, which was applied after the surface cracks were visually closed, bypassed the soil matrix with limited mixing to form the collected drainage water. While the water that had been applied at the beginning of the irrigation event, when surface cracks of up to 30 mm width were observed, was entirely taken up by the soil and did not contribute to the effluent at the bottom of the lysimeter. This firstly shows that lateral infiltration from the crack walls was substantial and that preferential flow paths remained open even after visual closure of soil cracks. The variations in the anisotropy index (AI) with applied irrigation volume differ between preferential flow and matrix flow. AI variations can therefore give further insight into the timing of the closure of the preferential flow paths, which allows unique insight into flow processes within a soil profile. Preferential flow is resulting in an unstable AI that shows local minima and maxima, while matrix flow is resulting in a stable AI. Between these two flow regimes and AI states is a transitional state, which is indicated by an AI value that steadily approaches a stable value. The AI states showed that throughout the application of irrigation water the flow regime in the soil profile moved from a preferential flow dominated system to a matrix flow dominated system. While, such a transition has been hypothesised in the literature (Bouma and Loveday, 1988), the exact timing of its occurrence had not yet been detected. Use of electrical resistivity techniques and the AI concept allowed doing so for the first time and showed that preferential flow continues to occur for sometime after visual crack closure. In this experiment the first detection of matrix flow coincided with the first occurrence of ponding water at the top of the profile. The transition to matrix flow first occurred in the
upper 5 cm of the profile, before progressing downwards, indicating that soil swelling and hence closure of preferential flow path was quickest at the top of the profile. This is consistent with the infiltration process in cracked soil as described by Hoogmoed and Bouma (1980), which states that the soil surface is not only wetted via the water that is laterally infiltrating into the crack walls, but also by infiltration from the soil surface. However, as the relative proportions of these two wetting mechanisms vary with application intensity, the transition to matrix flow might not always start at the top of the profile. The three AI stages presented in this study allow in-situ detection of preferential flow as well as of the timing and location of the transition between flow regimes. Accurate determination of dominant flow regimes and of their transition is crucial to better understand, predict, and model flow and transport processes in dynamic soils and to adjust the timing of water, nutrient and pesticide application to the dominant flow processes. Acknowledgements The original setup of the lysimeter was carried out by Dr Justin Bell. References Beven, K., 1980. The Grendon Underwood field drainage experiment. IH Report No.65. Institute of Hydrology, Wallingford, U.K. Beven, K., Germann, P., 1982. Macropores and water-flow in soils. Water Resources Research 18 (5), 1311–1325. Bing, Z., Greenhalgh, S.A., 1997. A synthetic study on cross-hole resistivity imaging with different electrode arrays. Exploration Geophysics 28 (5), 1–5. Bouma, J., Loveday, J., 1988. Characterizing soil water regimes in swelling clay soils. In: Wilding, L.P., Puentes, R. (Eds.), Vertisols: Their Distribution; Properties; Classification and Management. University Printing Center, College Station, TX, pp. 83–96. Bronswijk, J.J.B., Hamminga, W., Oostindie, K., 1995. Rapid nutrient leaching to groundwater and surface water in clay soil areas. European Journal of Agronomy 4 (4), 431–439. Dahlin, T., Zhou, B., 2004. A numerical comparison of 2D resistivity imaging with 10 electrode arrays. Geophysical Prospecting 52 (5), 379–398. Edwards, L.S., 1977. A modified pseudosection for resistivity and IP. Geophysics 42 (5), 1020–1036. Greve, A.K., Acworth, R.I., Kelly, B.F.J., 2010b. Detection of subsurface soil cracks by vertical anisotropy profiles of apparent electrical resistivity. Geophysics 75 (4), WA85–WA93. Greve, A., Andersen, M.S., Acworth, R.I., 2010a. Investigations of soil cracking and preferential flow in a weighing lysimeter filled with cracking clay soil. Journal of Hydrology 393 (1–2), 105–113. Habberjam, G.M., Watkins, G.E., 1967. The use of square configurations in resistivity prospecting. Geophysical Prospecting 15 (3), 445–467. Hoogmoed, W.B., Bouma, J., 1980. A simulation-model for predicting infiltration into cracked clay soil. Soil Science Society of America Journal 44 (3), 458–461. Jarvis, N.J., 2007. A review of non-equilibrium water flow and solute transport in soil macropores: principles, controlling factors and consequences for water quality. European Journal of Soil Science 58 (3), 523–546. Jaynes, D.B., Ahmed, S.I., Kung, K.J.S., Kanwar, R.S., 2001. Temporal dynamics of preferential flow to a subsurface drain. Soil Science Society of America Journal 65 (5), 1368–1376. Leeds-Harrison, P.B., Shipway, C.J.P., Jarvis, N.J., Youngs, E.G., 1986. The influence of soil macroporosity on water retention, transmission and drainage in a clay soil. Soil Use and Management 2 (2), 47–50. Lin, H.S., McInnes, K.J., Wilding, L.P., Hallmark, C.T., 1998. Macroporosity and initial moisture effects on infiltration rates in vertisols and vertic intergrades. Soil Science 163 (1), 2–8. Samouelian, A., et al., 2004. Three-dimensional crack monitoring by electrical resistivity measurement. European Journal of Soil Science 55 (4), 751–762. Waxman, M.H., Smiths, L.J.M., 1968. Electrical Conductivities in Oil-Bearing Shaly Sands. Society of Petroleum Engineers Journal 8, 107–122. Youngs, E.G., 1995. Developments in the physics of infiltration. Soil Science Society of America Journal 59 (2), 307–313.
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Monitoring the transition from preferential to matrix flow in cracking clay soil through changes in electrical anisotropy A.K. Greve ⁎, M.S. Andersen, R.I. Acworth Connected Waters Initiative, Water Research Laboratory, University of New South Wales, 110 King Street, 2093 Manly Vale, NSW, Australia Affiliated with the National Centre for Groundwater Research and Training, Australia
a r t i c l e
i n f o
Article history: Received 27 June 2011 Received in revised form 30 January 2012 Accepted 3 February 2012 Available online 19 March 2012 Keywords: Electrical resistivity Square array Soil cracks Preferential flow Stable isotopes
a b s t r a c t Transition from preferential flow to matrix flow in a vertisol was investigated by combined use of square array resistivity measurements and stable water isotopes. Two irrigation events with water of different water isotope composition were carried out on a 0.5 m deep initially dry and cracked soil profile in a weighing lysimeter. Throughout the irrigation events, depth profiles of resistivity square array measurements were collected to calculate profiles of the anisotropy index (AI) and mean resistivity. The stable isotope composition of the drainage water showed that water from the second irrigation bypassed the soil matrix with limited mixing to form the collected drainage. This bypass showed that even though the soil cracks at the surface were visually closed at the onset of the second irrigation, preferential flow paths must have remained open. Changes of the AI with applied irrigation volume were used to detect the dominant flow processes in the soil, with a stable AI indicating matrix flow and an unstable AI indicating preferential flow. The AI showed that over the course of the irrigation events the dominant flow process changed from preferential flow to matrix flow. The use of the AI allowed for the first time to detect the exact timing of this transition. Matrix dominated flow didn't occur until ponding water at the soil surface was observed. The onset of matrix flow started at the top of the profile and progressed downwards. Complete crack closure in terms of water flow occurred long after visual closure of soil cracks and could be detected by monitoring changes in the AI. © 2012 Elsevier B.V. All rights reserved.
1. Introduction Cracking clay soils are common in irrigated areas in many parts of the world. While their high nutrient content and water holding capacity make them highly productive soils, their susceptibility for preferential flow creates challenges for agricultural management of water and solutes. Preferential flow can quickly transport nutrients and pesticides through the unsaturated zone and bypass the soils capacity for storage, adsorption and transformation of potential pollutants before these reach surface or ground waters (Bronswijk et al., 1995; Jaynes et al., 2001). Investigations of flow in cracked soil have reported flow velocities reaching similar levels as overland flow (Beven and Germann, 1982) indicating that soil cracks can play a very significant role in soil water transport. However, it has also been shown that the hydraulic conductivity of initially cracked soil decreased by an order of magnitude during soil swelling (Leeds-Harrison et al., 1986). Due to the shrink and swell characteristics of clay soils, the volume and connectivity of macro-pores decreases with increasing soil moisture content (Lin et al., 1998) and it is assumed that in a fully swollen soil, once
⁎ Corresponding author. Tel.: + 61 280719800; fax: + 61 299494188. E-mail address: [email protected] (A.K. Greve). 0016-7061/$ – see front matter © 2012 Elsevier B.V. All rights reserved. doi:10.1016/j.geoderma.2012.02.003
macro-pores have been entirely closed, water and solutes will be transported through the soil profile by matrix flow (Bouma and Loveday, 1988; Youngs, 1995). However, the timing of complete crack closure varies; cracks between structural peds of drained heavy clay soil may remain open even after extended wetting periods (Beven, 1980) and it is difficult to experimentally determine how long macropores actively contribute to preferential flow (Beven and Germann, 1982). Effective management of the risks associated with preferential flow and transport in irrigation agriculture on cracking soils requires a comprehensive understanding of the temporal variations in hydraulic properties associated with different water applications. Ideally this would allow adjusting the timing of water, nutrient or pesticide application to the expected flow processes in the soil. Reviewing the present state of our understanding of flow in soil macro-pores Jarvis (2007) concluded that further advances in our understanding are expected from new experimental techniques that relate macro-pore structure to flow and transport observations. Further he called for the development of simple indices or descriptors of soil macroporosity and/or resulting flow patterns to assess the likelihood of preferential flow in soil horizons. This study does both. It combines a new in-situ technique to monitor subsurface crack dynamics with stable water isotopes to assess the dominant flow processes in a soil profile. Combining these two
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techniques allows relating the observed flow processes to a simple index of soil heterogeneity, which for the first time allows detection of the transition from preferential flow to matrix flow within a soil profile. Greve et al. (2010a) introduced the use of anisotropy index profiles obtained from square array resistivity measurements to nondestructively monitor in-situ crack dynamics in the subsurface. Here the use of this in-situ technique is extended and combined with profiles of average resistivity to characterise flow dynamics in cracking soil. The change of these two parameters is monitored throughout water applications on an initially dry and cracked soil profile. In conjunction with stable water isotopes this allows investigating the interplay of subsurface crack dynamics and preferential flow in a lysimeter. Further it allows direct detection of the transition from a preferential flow dominated system to a matrix flow dominated system as the water content increases. A better detection of this transition in the field will provide valuable information for optimising the timing of water, nutrient, and pesticide applications. 2. Theory Measuring the flow of electrical current through the subsurface can provide rapid and useful information about physical and chemical properties of the soil. In the electrical resistivity method, a low frequency alternating current (I) is applied to the ground by two current electrodes and the resulting potential difference (Δϕ) is measured with two potential electrodes. Most commonly the four electrodes are arranged in a straight line along the soil surface, but a variety of other arrangements are possible (Bing and Greenhalgh, 1997; Dahlin and Zhou, 2004). In the square array, the electrodes are arranged to form a square on the soil surface (Fig. 1). There are three independent arrangements of the current and potential electrodes within a square, which have been termed the α, β, and γ arrays (Habberjam and Watkins, 1967). As derived in detail by Greve et al. (2010a), the potential differences measured with the α, β, and γ arrays (Δϕα, Δϕβ and Δϕγ) are related as follows: Δϕβ + Δϕγ = Δϕα and in isotropic and homogeneous ground Δϕγ = 0 and Δϕα = Δϕβ. However, if heterogeneities are present, the apparent resistivity (ρa) in the measurement volume that influences the potential at the two potential electrodes varies with the electrode position, so that in most cased Δϕγ ≠ 0 and Δϕα ≠ Δϕβ. In heterogeneous ground, the measured resistances Δϕ Rα ¼ ΔϕI α and Rβ ¼ I β and the apparent resistivities for the total measurement volume influencing the α and β measurements (ρaα and ρaβ) will therefore differ. The ratio of Rα and Rβ, in the following referred to as the anisotropy index (AI), provides a measure of the directional variation of the resistance measurement. Soil cracks generally result in an anisotropic
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alteration of the electric field and hence cause the AI to deviate from unity. Samouelian et al. (2004) related AI variations from unity to surface cracks and Greve et al. (2010a) used depth series of AI measurements on horizontal co-planar square arrays to create AI profiles, which allowed monitoring soil crack dynamics within a soil profile. In addition to the calculation of the AI, the use of the square array also allows the calculation of the average apparent resistivity (ρam), which is the average of ρaα and ρaβ. While the AI is a measure of the heterogeneity in the measurement area, ρam gives an average apparent resistivity value that is relatively independent of the orientation of the electrode array and hence the heterogeneity (Habberjam and Watkins, 1967). 3. Methods 3.1. Lysimeter setup The presented experiment was carried out in a lysimeter. The lysimeter consisted of a fibreglass barrel (inner diameter: 1.3 m, depth: 0.78 m) placed onto a weighing scale, which was logged at 30 min intervals to determine evaporation losses. The barrel was tilted at an angle of 8° and had a 28 mm diameter drainage opening cut into the lowest point of its side wall (Fig. 2). In September 2002 the lower 50 mm of the lysimeter were filled with 195 kg of well flushed river gravel followed by a 500 mm deep layer of mixed vertisol from Breeza in New South Wales, Australia. The vertisol had a CEC of 62 meq/100 g and was made up of a sand, silt, and clay fraction of 16%, 20%, and 64%, respectively. Ca-montmorillonite made up 90% of the clay fraction, with the remaining clay fraction consisting of kaolinite. Before the soil was added to the lysimeter it was thoroughly mixed when dry. Water was added and it was worked into a homogenous soil paste. Once the soil paste was poured into the lysimeter, it was flushed with 500 mm of tap water, which had an electrical conductivity (EC) of 0.2 mS/cm and a sodium adsorption ratio (SAR) of 1.3. The water was applied over a 3 day period. Following the initial set up of the lysimeter, the soil was exposed to a total of ~40 separate irrigation and drying events over a period of 7.5 years, as described in more detail by Greve et al. (2010b). During these repeated drying and wetting periods an aggregate structure was re-established in the soil. 3.2. Electrode installation In December 2008 four electrode strings were vertically installed into the soil profile. The electrode strings consisted of 9 ring-shaped electrodes (38 mm diameter) with 50 mm inter-electrode spacing. Assembly of the electrode strings is described in Greve et al. (2010a). To allow electrode installation, four 450 mm deep vertical holes (40 mm diameter) were hand-augered into the dry soil profile.
Fig. 1. (a–c) Plan view of a square array with α, β, and γ configurations, with C1 and C2 being the current source and sink, P1 and P2 being the potential electrodes, and a being the side length of the square.
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Fig. 2. (a) Cross section of lysimeter setup and (b) sketch of horizontal planes for square array measurements between the four vertical electrode strings in the lysimeter.
During augering, the hand-auger was held in place by a wooden plank with a circular notch to ensure vertical augering. The extracted soil material was worked into a putty-textured soil-water paste, which was used to cover the electrode strings prior to insertion into the augered holes. Once installed, the electrode strings formed a horizontal electrode square with a = 500 mm at each electrode depth (Fig. 2). To avoid disturbance of the crack walls, the electrodes had been installed within stable soil peds. The four electrode strings were therefore not perfectly centred within the lysimeter, instead the centre of the electrode square at the soil surface was offset from the centre of the lysimeter by 0.04 m (Fig. 2). 3.3. Water application and stable water isotope tracing Two irrigation events were carried out on 22 June 2010 and 5 July 2010, with 50 mm (32 mm/h) being applied during the first irrigation and 75 mm (26 mm/h) during the second irrigation. At both events the irrigation water was evenly applied with a watering can. The water that was used for the two irrigation events came from different sources and consequently had different stable water isotope signatures. Tab water was used for the first irrigation (δD = − 16.19 ± 0.35‰, δ 18O = − 2.55 ± 0.02‰) and local dam water from Manly Dam, New South Wales, Australia was used for the second irrigation (δD = − 7.6 ± 0.26‰, δ 18O = − 1.09 ± 0.07‰). Drainage out of the lysimeter was collected and its isotope composition was analysed with a Los Gatos Research Liquid-Water Isotope Analyzer (DLT-100v2) connected to an auto injector from CTC Analytics. A camera was mounted 1.45 m above the soil surface and surface images were taken every 5 min throughout the two irrigation events. 3.4. Square array resistivity measurements A resistivity measurement protocol that measured Rα, Rβ, and Rγ for the horizontal electrode squares at each electrode depth in the lysimeter was created. The protocol, which consisted of 27 measurements, was uploaded to an ABEM SAS4000 terrameter and was run every 5 min throughout each of the two irrigation events. Measurements were made by applying a maximum current of 20 mA. The protocol was run with one stack (no repeat measurements were used), which resulted in a measurement time of ~ 90 s. Rather than assessing the noise through repeat measurements, which would have resulted in an increased measurement
time, the quality of the acquired data was determined based on the tripotential error:
Etp ¼
Rα − Rβ þ Ry Rα
Depth profiles of the AI and the ρam were determined for each protocol run. 3.5. Soil sampling A total of 5 soil cores were taken with a 40 mm diameter push tube and the gravimetric soil moisture content was determined for 50 mm depth intervals of the cores. A core was taken before each of the irrigation events and three cores were taken 2 weeks after the 2nd irrigation event. The first of the three cores taken after the irrigation events was cored on a previous crack location, while the other two were cored on previous soil peds (matrix locations). Soil sampling right after the irrigation events was not carried out as the stickiness of the freshly irrigated soil did not allow depth specific sampling with the coring method applied here. To prevent the creation of artificial preferential flow paths, the first two soil cores were only cored to a depth of 350 mm, while the later three soil cores were cored through the entire depth of the soil profile (500 mm). The holes from the first two soil cores were back filled with dried vertisol powder, which was tightly pressed into the augered hole with a 35 mm diameter wooden staff. In addition, bulk density measurements were made 2 weeks after the 2nd irrigation event. Sampling for bulk density was carried out in 0.05 m depth intervals. A 50 mm deep soil ring with an inner diameter of 25 mm was used to collect 0.098 L of soil. The surrounding soil was dug out with a hand held shovel before a consecutive depth was sampled. The soil was dried at 110 °C to determine its dry weight and dry bulk density. Finally, the porosity was estimated, assuming a grain density of 2650 kg/m 3. 4. Results and discussion 4.1. Water application Prior to the onset of the first irrigation, the soil surface was heavily cracked, with surface cracks of up to 30 mm width (Fig. 3a).
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Fig. 3. Soil surface (a) before irrigation 1, (b) after irrigation 1, (c) 16 mm into irrigation 2 (total of 66 mm applied), and (d) 40 mm into irrigation 2 (total of 90 mm applied).
Throughout the first irrigation surface runoff into the soil cracks was observed. This surface runoff caused erosion and occasionally collapse of the crack walls at the top of the profile, with the eroded and collapsed material being washed into the soil cracks. At the end of irrigation 1, the soil cracks were closed, however due to the erosion and collapse of the crack walls, former soil cracks remained visible as steep surface depressions with a depth of up to 70 mm (Fig. 3b). During irrigation 2 standing water occurred in the surface depressions (Fig. 3c). Once the standing water had infiltrated, the depressions had disappeared (Fig. 3d). The first effluent occurred 2 h 55 min after the start of the second irrigation, when a total of 125 mm had been applied (50 mm in irrigation 1 and 75 mm in irrigation 2). In total 18 mm of drainage occurred over a period of 3 days, with the first 11 mm occurring within the first 3 h of the drainage event. The isotope composition of the drainage water was similar to that of the water applied during irrigation 2 (δD = − 7.6 ± 0.26‰, δ 18O = −1.09 ± 0.07‰), with δD values that varied between −9.49 ± 0.66 and −6.35 ± 0.39‰ and δ 18O values that varied between −1.63 ± 0.09 and − 0.32 ± 0.05‰ (Fig. 4). This strongly indicates that water from irrigation 2 not only bypassed the soil matrix (where presumably irrigation 1 water was residing) but drained out of the column with limited mixing. This direct bypassing of water from irrigation 2 shows that even though at the onset of this irrigation the soil cracks were visually closed at the surface, preferential flow paths must have remained open. This observed preferential flow after visual crack closure is consistent with a similar yet less conclusive breakthrough of a bromide tracer observed by Greve et al. (2010b). The occurrence of preferential flow after visual crack closure, calls for a closer inspection of the dynamics of the crack network and hence the preferential flow paths within the soil profile. Investigation of the changes in the soil water content (SWC) and the square array resistivity measurements will allow doing so.
4.2. Soil parameters and water content The SWC in the entire measured moisture profile increased during both irrigation events (Fig. 5), which highlights that the soil was still below field capacity after irrigation 1. This suggests that capillary suction and/or preferential flow did significantly contribute to the wetting of the soil matrix during irrigation 1, since under piston flow conditions the upper part of the soil would reach field capacity before water continues to propagate deeper into the profile. Except for one soil sample taken at the surface, the soil core that was taken on a previous location of a surface crack shows a higher SWC in the upper 0.3 m of the soil column, than the two cores that were taken on previous soil peds (Fig. 5). This suggests preferential wetting along soil cracks and hence preferential flow through cracks during at least the initial part of the water application. The only exception to the increased soil moisture at the former crack location is one soil sampling point at the top of the profile (0.05 m depth), which shows higher soil moisture on a former soil pad. This higher water content could be explained by the concave shape of the surface of larger soil peds, which results in shallow depressions that directly collect irrigation water that can then infiltrate. The soils bulk density varied randomly over depth and was determined to be 0.81 g/cm 3 with a standard deviation of 0.10 g/cm 3, resulting in an estimated porosity of 70 ± 4%. 4.3. Square array resistivity results The ρam profiles in Fig. 6 show a clear correlation with the water application with a decrease in the resistivity from about 60 Ω m after 15 mm of irrigation to about 18 Ω m after 125 mm. The ρam varies little over depth at any given time apart from the slightly higher ρam-values that can be seen in the upper two measurement depths after the application of 15 mm. The AI profiles increase throughout
Fig. 4. Stable water isotope composition of the two irrigation waters and the collected drainage samples.
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Fig. 5. Gravimetric soil water content determined by soil coring before water application and after irrigations 1 and 2.
the two irrigation events from values that are smaller than 1 towards a profile with AI's of 1 ± 0.2. Greve et al. (2010a) derived a cracking depth range from AI profiles. As an inhomogeneity needs to be present to produce an AI deviation, they concluded that the deepest maximum of the AI deviation indicates the minimum cracking depth. Individual cracks might exceed this depth and end somewhere between this last pronounced maxima and the depth where the AI reaches the stable value that indicates non-cracked conditions. The cracking depth range reaches from the depth of the last pronounced maximum of the AI deviation to the depth where the AI indicates stable, non-cracked soil conditions. At the start of irrigation 1, the last pronounced maximum in the AI deviation was at 0.3 m depth and at the start of irrigation 2, it was at 0.05 m, indicating that cracks extended to at least these depths (Fig. 6). This initial cracking depth of at least 0.3 m is consistent with the depth of preferential wetting of 0.3 m as indicated by the soil cores taken after irrigation 2 (Fig. 5) and the cracking depth of at least 0.05 m at the onset of irrigation 2 is consistent with the 0.07 m deep surface depressions that were observed after irrigation 1. While the AI profiles in Fig. 6 give an indication of the cracking depth and hence the depth of preferential flow paths, they do not give any information about the actual occurrence of preferential flow within the soil profile. In the following it is proposed that detailed plots of the AI against irrigation volume as in Figs. 7 and 8 provide this missing information. Throughout the irrigation process, the ρam-values measured in the soil profile at any one time vary from the mean ρam by 4–8%. The mean ρam per measurement interval shows a continuous decrease in resistivity from 93.7 Ω m at the beginning of irrigation 1, when 12 mm had been applied to 16.7 Ω m at the end of irrigation 2 when a total of 125 mm had been applied. (Note: Square array measurements that were collected in the dry soil before the application
Fig. 7. Development of ρam and of the AI at selected depth intervals throughout irrigations 1 and 2.
of the initial 12 mm of water had a large tripotential error and were removed from the dataset.) The decrease in ρam is stronger in the beginning of the irrigation period and diminishes as more water has been added, which is consistent with the power law relationship that is generally assumed between the bulk resistivity of a porous medium and its saturation (Waxman and Smiths, 1968). Compared to the large depth variation of AI (also Fig. 7), the variation of ρam with depth is low. Particularly at the beginning of irrigation 1, when the soil moisture showed a strong depth gradient (Fig. 5) a larger gradient of ρam with depth could be expected. The low measured variation can be explained by the fact that the median depth of
Fig. 6. Depth profiles of ρam and the AI at selected measurement intervals during irrigations 1 and 2 (Note: AI and ρam at 40 mm depth, could not be determined due to lack of electrode contact).
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Fig. 8. Development of the AI at all depth intervals during the application of the final 79 mm of irrigation water (Note: AI at 40 mm depth, could not be determined due to lack of electrode contact).
investigation (Edwards, 1977) of the square array in the lysimeter (0.23 m) is relatively large compared to the depth increments in which the square array measurements are made (0.05 m). Additionally, current has the tendency to preferably flow through areas of least resistance, resulting in resistivity measurements to be more sensitive to low resistive regions of the subsurface. Furthermore, the effects of heterogeneity are largely eliminated in the ρam (Habberjam and Watkins, 1967), so that differences in heterogeneity, which strongly impact the AI, are not (or only negligibly) expressed in the ρam. Unlike the AI, which is influenced by changes in heterogeneity in depth and time, the ρam is dominated by similar low resistive regions of the soil profile, regardless of the measurement depth. While the ρam-values at all measurement depths continuously decrease throughout the two irrigation events, the AI's show different trends for different measurement depths (Fig. 7). The AI measured at 0.05 m shows a steady increase during the application of the first 66 mm, before it reaches a stable value of 0.82 ± 0.01. The AI's measured at the soil surface show a similar behaviour, but are for visual clarity not displayed in Fig. 7. In the deeper part of the profile, the AI graphs are more complex, with three distinct peaks in AI. To facilitate the discussion of the AI behaviour, the following, three AI states are defined: an AI that remains constant over time is defined as stable state, an AI that fluctuates and shows local minima and maxima is defined as an unstable state, and an AI that steadily moves towards its stable state is defined as a transition state. The majority of AI's measured at the beginning of irrigation 1 were in an unstable state, with a gradual move towards transition or stable states during the course of the irrigation (Fig. 7). As a changes in the AI must be due to the influx of some quantity of irrigation water and potentially the consequent soil swelling or changes in pore water EC within the soil volume that influences the square array measurement. It is proposed that the three AI states indicate different flow regimes. With an unstable AI state indicating preferential flow and hence local changes in both the soil moisture
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and the crack system itself. These local changes can temporarily increase or decrease the electrical heterogeneity of the soil profile, and hence can result in local AI minima and maxima. A stable AI on the other hand is indicating a stable system, which could either be steady state preferential flow with no local change in the soil moisture content or complete crack closure and a change in the flow regime from preferential flow to matrix flow. As the water supply in this study was discontinuous the occurrence of steady state preferential flow can be excluded. In between these two states is the transition state highlighted by an AI that steadily moved towards a stable value. The transition state indicates a soil that through swelling becomes increasingly homogeneous. The proposed interpretation of the three AI states indicates a general move from a preferential flow dominated system to a matrix flow dominated system throughout the irrigation process. While such a transition has been hypothesised for flow in cracking soils (Bouma and Loveday, 1988; Youngs, 1995), this dataset provides unique physical evidence for the hypothesis and further allows the detection of the timing of this transition. Initially the upper part of the profile, which influences the square array measurements at 0.00 and 0.05 m depth, is in transition (Fig. 7). This indicates that the water that infiltrates into the soil peds at the surface causes soil swelling and crack closure in this part of the profile. Deeper parts of the soil that influence the square array measurements from 0.10 to 0.45 m depth, show the unstable state (Fig. 7). Here, preferential flow results in temporal variation of the electrical heterogeneity and hence causes the local minima and maxima in the AI. Throughout irrigation 1 preferential flow eventually gets absorbed by the soil matrix (no effluent occurred) and therefore contributes to wetting and swelling of the soil, resulting in a change into the transition state. During irrigation 1 this change into the transition state is completed for the measurement depth of 0.10 m, which only shows the first of the three local AI maxima in Fig. 7. At greater depth however, the soil still shows unstable conditions during irrigation 2. These initial flow processes during irrigation 1 correspond with the three stage process of macro-pore flow defined by Hoogmoed and Bouma (1980), which consists of vertical infiltration into the soil peds at the surface, downward flow within the macro-pores, and horizontal absorption from soil cracks into the soil matrix. The continuation of change in AI's during irrigation 2 demonstrates that the soil column has not reached its stable state after irrigation 1. This agrees with the stable isotope results (Fig. 4), which show that water from irrigation 2 bypassed the soil matrix and formed the drainage water. Even though surface soil cracks visually appear closed after irrigation 1, further preferential flow and soil swelling occur during irrigation 2, before the AI reaches its stable state at the end of irrigation 2. Fig. 8 shows that the final stable AI's that are measured in the soil profile at the end of irrigation 2 show a consistent increase from 0.82 at 0.05 m depth to 1.06 at 0.45 m depth. This consistent increase with depth is most likely due to the fact that the entire lysimeter is tilted at 8°, while the electrode strings are installed vertically to the soil surface. This setup results into a gradual change in distance to the side walls of the lysimeter with depth. Based on the 0.04 m offset of the electrode square from the centre of the lysimeter at the surface and the 8° inclination of the lysimeter walls, the electrode strings would be at the centre of a horizontal plane through the lysimeter at 0.28 m depth. Under completely homogeneous soil conditions, the AI at 0.28 m would hence be unity, and indeed the final AI's measured at 0.25 and 0.30 m depth are very close to 1, indicating that the stable AI state has indeed been reached for the profile. The stable AI state and hence a transition towards matrix flow is first indicated in the upper part of the profile (Figs. 7 and 8). This occurs after the application of 70 mm at the same measurement interval when standing water is first observed on the soil surface. Considering the constant irrigation rate, the occurrence of standing water suggests
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a decrease in the bulk hydraulic conductivity of the upper soil profile and supports the indicated transition from faster preferential to slower matrix flow. The local AI maxima and minima that are measured at the immediate soil surface (Fig. 8) can be explained by the local filling of the surface depressions, which do not occur at the same time for all depressions and therefore cause small fluctuations in the AI. Once the transition to matrix flow has occurred at the surface, the expression of the unstable state in the lower part of the profile changes as well. Inspection of the three local AI maxima in Fig. 7 shows that the rising, peaking, and decreasing sections of the first two peaks are occurring in the same measurement interval for all depths between 0.15 and 0.45 m. The last peak however, which occurs after transition to matrix flow at the top of the profile, shows an offset of the peak for different measurement depth (Fig. 8). The peak is measured at the same time interval for measurement depth 0.15 and 0.25 m (the peak at 0.2 m is not well pronounced). Starting from a measurement depth of 0.30 m downwards the peak is offset towards later measurement times and the extent of the offset increases with depth. This offset could indicate a slower and in volume diminished preferential flow in the now almost closed soil cracks. Whereas at the beginning of the irrigation process, preferential flow occurred fast and affected the entire unstable part of the profile within one measurement interval, the flow process is now slowed down and takes several measurement intervals to flow through the soil column. 5. Conclusion Combined use of square array resistivity measurements and stable water isotopes allowed unique insight into the flow dynamics in a vertisol. The stable isotope composition of the drainage water that was collected at the bottom of the lysimeter showed that water, which was applied after the surface cracks were visually closed, bypassed the soil matrix with limited mixing to form the collected drainage water. While the water that had been applied at the beginning of the irrigation event, when surface cracks of up to 30 mm width were observed, was entirely taken up by the soil and did not contribute to the effluent at the bottom of the lysimeter. This firstly shows that lateral infiltration from the crack walls was substantial and that preferential flow paths remained open even after visual closure of soil cracks. The variations in the anisotropy index (AI) with applied irrigation volume differ between preferential flow and matrix flow. AI variations can therefore give further insight into the timing of the closure of the preferential flow paths, which allows unique insight into flow processes within a soil profile. Preferential flow is resulting in an unstable AI that shows local minima and maxima, while matrix flow is resulting in a stable AI. Between these two flow regimes and AI states is a transitional state, which is indicated by an AI value that steadily approaches a stable value. The AI states showed that throughout the application of irrigation water the flow regime in the soil profile moved from a preferential flow dominated system to a matrix flow dominated system. While, such a transition has been hypothesised in the literature (Bouma and Loveday, 1988), the exact timing of its occurrence had not yet been detected. Use of electrical resistivity techniques and the AI concept allowed doing so for the first time and showed that preferential flow continues to occur for sometime after visual crack closure. In this experiment the first detection of matrix flow coincided with the first occurrence of ponding water at the top of the profile. The transition to matrix flow first occurred in the
upper 5 cm of the profile, before progressing downwards, indicating that soil swelling and hence closure of preferential flow path was quickest at the top of the profile. This is consistent with the infiltration process in cracked soil as described by Hoogmoed and Bouma (1980), which states that the soil surface is not only wetted via the water that is laterally infiltrating into the crack walls, but also by infiltration from the soil surface. However, as the relative proportions of these two wetting mechanisms vary with application intensity, the transition to matrix flow might not always start at the top of the profile. The three AI stages presented in this study allow in-situ detection of preferential flow as well as of the timing and location of the transition between flow regimes. Accurate determination of dominant flow regimes and of their transition is crucial to better understand, predict, and model flow and transport processes in dynamic soils and to adjust the timing of water, nutrient and pesticide application to the dominant flow processes. Acknowledgements The original setup of the lysimeter was carried out by Dr Justin Bell. References Beven, K., 1980. The Grendon Underwood field drainage experiment. IH Report No.65. Institute of Hydrology, Wallingford, U.K. Beven, K., Germann, P., 1982. Macropores and water-flow in soils. Water Resources Research 18 (5), 1311–1325. Bing, Z., Greenhalgh, S.A., 1997. A synthetic study on cross-hole resistivity imaging with different electrode arrays. Exploration Geophysics 28 (5), 1–5. Bouma, J., Loveday, J., 1988. Characterizing soil water regimes in swelling clay soils. In: Wilding, L.P., Puentes, R. (Eds.), Vertisols: Their Distribution; Properties; Classification and Management. University Printing Center, College Station, TX, pp. 83–96. Bronswijk, J.J.B., Hamminga, W., Oostindie, K., 1995. Rapid nutrient leaching to groundwater and surface water in clay soil areas. European Journal of Agronomy 4 (4), 431–439. Dahlin, T., Zhou, B., 2004. A numerical comparison of 2D resistivity imaging with 10 electrode arrays. Geophysical Prospecting 52 (5), 379–398. Edwards, L.S., 1977. A modified pseudosection for resistivity and IP. Geophysics 42 (5), 1020–1036. Greve, A.K., Acworth, R.I., Kelly, B.F.J., 2010b. Detection of subsurface soil cracks by vertical anisotropy profiles of apparent electrical resistivity. Geophysics 75 (4), WA85–WA93. Greve, A., Andersen, M.S., Acworth, R.I., 2010a. Investigations of soil cracking and preferential flow in a weighing lysimeter filled with cracking clay soil. Journal of Hydrology 393 (1–2), 105–113. Habberjam, G.M., Watkins, G.E., 1967. The use of square configurations in resistivity prospecting. Geophysical Prospecting 15 (3), 445–467. Hoogmoed, W.B., Bouma, J., 1980. A simulation-model for predicting infiltration into cracked clay soil. Soil Science Society of America Journal 44 (3), 458–461. Jarvis, N.J., 2007. A review of non-equilibrium water flow and solute transport in soil macropores: principles, controlling factors and consequences for water quality. European Journal of Soil Science 58 (3), 523–546. Jaynes, D.B., Ahmed, S.I., Kung, K.J.S., Kanwar, R.S., 2001. Temporal dynamics of preferential flow to a subsurface drain. Soil Science Society of America Journal 65 (5), 1368–1376. Leeds-Harrison, P.B., Shipway, C.J.P., Jarvis, N.J., Youngs, E.G., 1986. The influence of soil macroporosity on water retention, transmission and drainage in a clay soil. Soil Use and Management 2 (2), 47–50. Lin, H.S., McInnes, K.J., Wilding, L.P., Hallmark, C.T., 1998. Macroporosity and initial moisture effects on infiltration rates in vertisols and vertic intergrades. Soil Science 163 (1), 2–8. Samouelian, A., et al., 2004. Three-dimensional crack monitoring by electrical resistivity measurement. European Journal of Soil Science 55 (4), 751–762. Waxman, M.H., Smiths, L.J.M., 1968. Electrical Conductivities in Oil-Bearing Shaly Sands. Society of Petroleum Engineers Journal 8, 107–122. Youngs, E.G., 1995. Developments in the physics of infiltration. Soil Science Society of America Journal 59 (2), 307–313.