Evaluation of the OhmMapper Instrument for. Measurement of Soil Moisture

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1 Evaluation of the OhmMapper Instrument for Measurement of Soil Moisture 1,2 Jeffrey P. Walker and 1 Paul R. Houser 1. Hydrological Sciences Branch, Laboratory for Hydrospheric Processes NASA s Goddard Space Flight Center, Greenbelt, MD 20771, USA 2. Goddard Earth Sciences and Technology Center Submitted to: Soil Science Society of America Journal 7 th November, 2000 Corresponding Author: Jeffrey P. Walker Rm B309, Building 33 NASA/GSFC Mail Code 974 Greenbelt MD, USA cejpw@land.gsfc.nasa.gov

2 ACKNOWLEDGEMENTS The United States Department of Agriculture is acknowledged for allowing access to the OPE 3 field site at the Agriculture Research Center in Beltsville, MD. Assistance was given in the field by Kristi Arsenault, Brian Cosgrove, Dan Hymer and Melinda Pouss. The loan of an OhmMapper by Geometrics Inc. and analysis of OhmMapper data by Brandy Rutledge is acknowledged.

3 Evaluation of the OhmMapper Instrument for Measurement of Soil Moisture Abstract An instrument for making rapid measurements of the soil moisture content in the top few meters of soil is an essential tool for many applications, including understanding of soil water dynamics, evaluation of agriculture water stress, validation of soil moisture modeling, and assimilation of remotely sensed near-surface soil moisture data. Studies have shown that electrical resistance measurements may be used to measure soil moisture content. In this paper, electrical resistivity resistance multiplied by a geometric factor) measurements of the soil using the OhmMapper instrument of Geometrics Inc. are compared with time domain reflectometry point measurements of soil moisture to a depth of 70 cm. It was found that the OhmMapper could measure soil moisture content with a correlation coefficient of up to 0.6. It is likely that this correlation coefficient would be greater if much deeper measurements of soil moisture were compared with the OhmMapper measurements.

4 1 1. INTRODUCTION Knowledge of the spatial distribution in soil moisture content for the top meter or two of the earth s surface is important for many environmental studies, including meteorology, hydrology and agronomy. However, as a result of the heterogeneity of soil properties, topography, land cover, evapotranspiration, and precipitation, soil moisture is highly variable both spatially and temporally Engman, 1991; Wood et al., 1993). Hence, numerical soil moisture models are prone to error Wood et al., 1993) and spatial coverage by point measurements is limited by logistics Giacomelli et al., 1995). Moreover, soil moisture measurement depth from remote sensing observations is limited to the top few centimeters Schmugge, 1985). As a result, research is being directed toward a combination of these three approaches for estimating the spatial distribution and temporal variation of soil moisture content; assimilation of remote sensing observations into the numerical soil moisture model eg. Houser et al., 1998) and calibration/evaluation of the soil moisture model from point measurements eg. Walker et al., 2000). However, validation of such a system over even moderately sized areas is difficult, due to a lack of knowledge about spatial variability in the soil moisture profile. This necessitates a dependence on sparse point measurements of soil moisture and measurements of surrogate variables, such as surface temperature and evapotranspiration, for validation of the soil moisture estimates. In order to overcome such limitations, there is a demonstrated need for an instrument that allows rapid measurement of the spatial variability in soil moisture for the top meter or two of the earth s surface.

5 2 Studies have shown that soil moisture content can be determined from measurements of the soil electrical resistance eg. Seyfried, 1993; Amer et al., 1994; Hymer et al., 2000) using point measurement techniques. A new instrument on the market for mapping the spatial variability of electrical resistivity resistance multiplied by a geometric factor) over the top several meters of the earth s surface is the OhmMapper by Geometrics Inc. In this paper we evaluate the OhmMapper for its potential to map the soil moisture profile over large areas in a timely fashion. 2. DATA AND METHODOLOGY 2.1 Study Area Evaluation of the OhmMapper was undertaken at the OPE 3 Optimizing Production inputs for Economic and Environmental Enhancement) field site located at the United States Department of Agriculture, Agriculture Research Center, in Beltsville, MD Gish et al., 2001). The OPE 3 field site has a sandy loam soil with terrain slopes from 1% to 3% and is used for growing corn during the spring and summer. This field site consists of four gently sloping 4ha watersheds that feed a wooded riparian wetland and first-order stream. A single 250m transect running from top to bottom of one of the watersheds was monitored using both widely accepted point measurement techniques capacitance and time domain reflectometry) and the OhmMapper. Point measurements were made at 25m spacing to a depth of 70cm. Evaluation was made over a 1-month period immediately following planting in the spring growing season of Soil moisture content and OhmMapper measurements were made on a total of 8 days.

6 3 2.2 Point Measurements The point measurements of soil moisture content were made with the commercially available Theta Probe from Delta-T Devices Ltd. Delta-T Devices Ltd., 1996) and the Trase Connector Time Domain Reflectometry TDR) soil moisture instrument from Soil Moisture Equipment Corp. Soil Moisture Equipment Corp., 1989). The mention of trade and company names is for the benefit of the reader and does not imply an endorsement of the product.) By inserting the probes/waveguides vertically from the soil surface, the Theta Probe provided a soil moisture measurement over the top 6cm of soil, while the TDR instrument provided soil moisture measurements over the top 15, 30, 45, 60 and 70cm of soil. Comparison of Theta Probe and 15cm TDR measurements with thermogravimetric measurements showed that the manufacturers calibration was not satisfactory for this evaluation Figure 1). Hence a correction was applied to the point measurements of soil moisture content. 2.3 OhmMapper The OhmMapper instrument is a capacitively-coupled resistivity system that measures the electrical properties of the ground without the cumbersome galvanic electrodes used in traditional resistivity surveys. A simple coaxial-cable array with transmitter and receiver sections is pulled along the ground either by a single person or a small all-terrain vehicle Figure 2). In conventional resistance surveys, four electrodes are inserted into the soil and a current injected into the ground by connecting a DC power source to two of the electrodes. The voltage is then measured at the remaining two electrodes, and the resistance calculated using Ohm s Law. The resistance measured varies as a function of the distance and geometry between the probes, so it is normalized with the

7 4 addition of a geometric factor that converts the measurement to resistivity Geometrics Inc., 1999). This is the basis for the electrical resistance sensors commercially available for measurement of soil moisture content. Like some configurations of traditional galvanic resistivity, the OhmMapper uses a dipole-dipole array ie. injection of current following measurement of voltage rather than a nested measurement) to measure resistivity, except that contact is made with the ground capacitively. The dipole-dipole array is very sensitive to horizontal changes in resistivity but relatively insensitive to vertical changes, meaning that it is good in mapping vertical structures but relatively poor in mapping horizontal structures Loke, 1991). By increasing the dipole cable length and/or tow-link cable length, and hence the total length of the dipole-dipole array, the depth of the resistivity measurement is increased. For dipoles separated by a dipole length see Figure 2) this measurement depth is approximately 14% of the total length of the dipole-dipole array Loke, 1999). The measurement depth increases to approximately 22% of the total length of the dipole-dipole array for dipoles separated by six dipole lengths Loke, 1999). Hence, by making multiple passes with different configurations of the OhmMapper it is possible to measure the variation of resistivity with depth. In addition, data collection is continuous in time so the resistivity is finely sampled along any given towpath. Nominal dipole cable lengths of 1, 2.5 and 5m, and nominal tow-link cable lengths of 0.25, 0.5, and 4.0m were used in this evaluation.

8 5 2.4 Evaluation Hymer et al. 2000) used a power relationship between volumetric soil moisture content θ) and resistance R) of the form b θ = ar, 1) where a and b are fitted parameters. A relationship of this form is compatible with Archie s Law Archie, 1942), where a is the inverse of soil salinity and b is a soil texture parameter. Similar non-linear relationships have been used by Seyfried 1993) and Amer et al. 1994). In this paper, we take the OhmMapper apparent resistivity measurement to be equivalent to the resistance value in 1). We then solve for the parameters a and b by fitting 1) to OhmMapper measurements of apparent resistivity and TDR/Theta Probe measurements of soil moisture at each 25m interval along the 250m transect. Although the variation of resistivity with depth in the soil profile could be evaluated from an inversion of the multiple OhmMapper measurements with different dipole cable and tow-link cable lengths using a commercially available inversion software package, we have concentrated our efforts on evaluating the single pass resistivity data. Our reasons for this are: i) the TDR measurements used for evaluation give a depth integrated measurement of soil moisture content; and ii) the single pass data must be shown to have information about soil moisture before attempting the measurement of soil moisture variation with depth.

9 6 3. RESULTS AND DISCUSSION The results from fitting the function given in 1) with the measured soil moisture content and resistivity data are summarized in Table 1 for the correlation coefficient. These results show a typically low correlation coefficient, having a value of less than 0.6, for all dipole cable, tow-link and soil moisture depth measurement combinations. However, generally speaking, for a given dipole cable length the soil moisture depth yielding the greatest correlation coefficient increases with tow-link length. The correlation coefficients cease to follow this trend only when soil moisture measurements are too shallow. This trend was expected, as a greater separation between the midpoints of receiver and transmitter dipoles is claimed to yield a deeper measurement Geometrics Inc., 1999). However, using the general rule that resistivity measurement depth is half of this separation, it was expected that the greatest correlation coefficient for the 1m dipole cable length and 0.25m tow-link length would be with the 70cm soil moisture measurement depth. Given that the correlation coefficients are so low for the 1m dipole cable length, the higher correlation coefficient for the 15cm soil moisture measurement depth may be a purely spurious correlation. The scatterplots with fitted function are given in Figures 3 to 5 for each dipole cable and tow-link length for the soil moisture measurement depth having the greatest correlation coefficient. However, it may be seen that there is still as much as 15% v/v variation in soil moisture content for a given resistivity value, with most scatterplots bearing no resemblance to the fitted function, or any other relationship, being simply a cloud of points. The nominal 2.5m dipole cable length with 1m tow-link cable length is the only OhmMapper configuration that yielded a scatterplot that bore a significant resemblance to

10 7 the fitted function, as indicated by its higher correlation coefficient. In fact, this configuration yielded a consistently higher correlation coefficient for all soil moisture measurement depths when compared with the other configurations. It is suggested that the lower correlation coefficients for shorter dipole cables and tow-link lengths are a result of the noisy resistivity measurement yielded by the OhmMapper when the dipole cables were short and/or the dipole cable separation was small relative to the dipole cable length. The lower correlation coefficients for longer dipole cable and/or tow-link lengths are likely a result of the OhmMapper resistivity measurement being for a depth much greater than the deepest TDR measurement of soil moisture. The higher correlation coefficients for all soil moisture measurement depths with the OhmMapper resistivity measurements for 2.5m dipole cables and 1m tow-link cable length are likely a result of high correlation in soil moisture content for the top 70cm of soil. The soil moisture variation along the 250m transect is plotted in Figure 6 for the 60cm TDR measurements, where it is compared with the OhmMapper measurements for 2.5m dipole cables and 1m tow-link lengths using the fitted function from Figure 4c. Most notable in this figure is that TDR point measurements of soil moisture content have a variation of approximately 7% v/v from dry to wet, while the OhmMapper measurements have only approximately 3% v/v variation from dry to wet. However, the day on which TDR measurements indicate the wettest soil moisture coincides with the day on which OhmMapper measurements indicate the wettest soil moisture. Likewise, the TDR and OhmMapper measurements both indicate the driest soil moisture on the same day. Moreover, the OhmMapper measurements exhibit approximately the correct trend of soil moisture content along the transect.

11 8 It is well known that the near-surface soil moisture content responds rapidly to both infiltration and exfiltration events while the soil moisture content for a deep layer of soil has a much slower response time. Moreover, changes in the near-surface soil moisture content have only a minimal impact on the average soil moisture content of a thick soil layer ie. 3m). Hence, an explanation for the OhmMapper having the correct response to soil moisture content but the wrong magnitude may be that the OhmMapper is actually measuring the resistivity, and hence soil moisture, of a much deeper layer than the TDR, being approximately 3m as compared to 60cm. Furthermore, OhmMapper measurements of resistivity are an average measurement made over not only some depth eg 3m), but over the entire length of the instrument ie. 11m for 2.5m dipole cables and 1m tow-link), meaning that interpretation of comparisons with individual point measurement is difficult. 4. CONCLUSIONS This study has shown that there is a correlation coefficient of approximately 0.6 between TDR measurements of soil moisture content and the OhmMapper with 2.5m dipole cables and a 1m tow-link. All other OhmMapper configurations resulted in smaller correlation coefficients for the soil moisture depths measured. Results have indicated that this configuration is optimal for the purpose of measuring soil moisture in the top few meters, with the correlation coefficient likely to be greater if TDR measurements of soil moisture content could be made for a greater depth. Moreover, unless the noise in OhmMapper measurements of resistivity can be reduced for shorter dipole cables and/or shorter dipole cable separations, it is unlikely that the OhmMapper will be applicable for measuring the soil moisture content of shallower soil depths or be used to measure the variation of soil moisture content with depth in the soil profile.

12 9 REFERENCES Amer, S.A., T.O. Keefer, M.A. Weltz, D.C. Goodrich, and L.B. Bach, Soil moisture sensors for continuous monitoring. Water Resources Bulletin, 30: Archie, G.E., The electrical resistivity log as an aid in determining some reservoir characteristics. Transactions of the American Institute of Mineral Engineering, 146: Delta-T Devices Ltd., Theta Probe Soil Moisture Sensor Type ML1 User Manual. Delta-T Devices, Inc., Cambridge, England, 18pp. Engman, E.T., Application of microwave remote sensing of soil moisture for water resources and agriculture. Remote Sensing of the Environment, 35: Geometrics Inc., OhmMapper TR1 Operation Manual. Geometrics Inc., San Jose, USA, 113pp. Giacomelli, A., U. Bacchiega, P.A. Troch, and M. Mancini, Evaluation of surface soil moisture distribution by means of SAR remote sensing techniques and conceptual hydrological modelling. Journal of Hydrology, 166: Gish, T.J., W.P. Dulaney, C.S.T. Daughtry, and K.-J.S. Kung, Influence of preferential flow on surface runoff fluxes. ASAE Preferential Flow Symposium.

13 10 Houser, P.R., W.J. Shuttleworth, J.S. Famiglietti, H.V. Gupta, K.H. Syed, and D.C. Goodrich, Integration of soil moisture remote sensing and hydrologic modeling using data assimilation. Water Resources Research, 34: Hymer, D.C., M.S. Moran, and T.O. Keefer, Soil water evaluation using a hydrologic model and calibrated sensor network. Soil Science Society of America Journal, 64: Loke, M.H., Electrical imaging surveys for environmental and engineering studies: A practical guide to 2D and 3D surveys. Geometrics Inc., San Jose, USA, 57pp. Schmugge, T., Chapter 5: Remote Sensing of Soil Moisture, In: M.G. Anderson, and T.P. Burt, Eds.), Hydrological Forecasting, John Wiley and Sons, New York, Seyfried, M.S., Field calibration and monitoring of soil-water content with fiberglass electrical resistance sensors. Soil Science Society of America Journal, 57: Soil Moisture Equipment Corp., Trase System 1 Operating Instructions. Soil Moisture Equipment Corp., Santa Barbara, USA, 54pp. Walker, J.P., G.R. Willgoose, and J.D. Kalma, Three-dimensional soil moisture profile retrieval by assimilation of near-surface measurements: Simplified Kalman filter covariance forecasting and field application. Water Resources Research, In Preparation.

14 11 Wood, E.F., D.S. Lin, M. Mancini, D.J. Thongs, P.A. Troch, T.J. Jackson, J.S. Famiglietti, and E.T. Engman, Intercomparisons between passive and active microwave remote sensing and hydrological modeling for soil moisture. Advances in Space Research, 13:

15 12 Table 1: Comparison of correlation coefficient between OhmMapper resistivity and soil moisture measurements for nominal dipole cable, tow-link and TDR probe lengths given. Maximum R-value for dipole cable and tow-link length configuration are given in bold. Dipole Cable Length 1.0m 2.5m 5.0m Tow-Link R-Value for Soil Moisture Measurement Depth Length 6cm 15cm 30cm 45cm 60cm 70cm 0.25m m m m m m m m m m m m

16 !! 13 a) ) * +, -. /, , , + : ; 1 < 1 = b)? > ) * +, -. /, , , + : ; 1 < 1 = Figure 1: Calibration of a) Theta Probe and b) 15cm TDR against thermogravimetric soil moisture measurements.

17 14 Fiber optic isolator cable Receiver Non-conductive tow-link cable Dipole Length Transmitter Dipole Cable Dipole Cable Dipole Cable Dipole Cable Resistivity Measurement Figure 2: Schematic of the OhmMapper instrument.

18 !!!! 15 a) C D E F C C A B b) C D E F A B c) D E F G A B d) C D E F G A B Figure 3: Fitted function and scatter plot of apparent resistivity against the soil moisture measurement giving the greatest correlation for the OhmMapper configuration of dipole cable tow-link cable lengths. Nominal 1m dipole cable length with: a) nominal 0.25m towlink length against 15cm TDR measurements; b) nominal 0.5m tow-link length against 30cm TDR measurements; c) nominal 1m tow-link length against 60cm TDR measurements; and d) nominal 2m tow-link length against 70cm TDR measurements.

19 !!!! 16 a) D E F C A N B b) C D E F G A N B c) D E F C G C A N B d) C D E F A N B Figure 4: Fitted function and scatter plot of apparent resistivity against the soil moisture measurement giving the greatest correlation for the OhmMapper configuration of dipole cable tow-link cable lengths. Nominal 2.5m dipole cable length with: a) nominal 0.25m tow-link length against 15cm TDR measurements; b) nominal 0.5m tow-link length against 60cm TDR measurements; c) nominal 1m tow-link length against 60cm TDR measurements; and d) nominal 2m tow-link length against 45cm TDR measurements.

20 !!!! 17 a) C D E F C G A b) C D E F C A c) C D E F A d) D E F C C G A Figure 5: Fitted function and scatter plot of apparent resistivity against the soil moisture measurement giving the greatest correlation for the OhmMapper configuration of dipole cable tow-link cable lengths. Nominal 5m dipole cable length with: a) nominal 0.5m towlink length against 30cm TDR measurements; b) nominal 1m tow-link length against 70cm TDR measurements; c) nominal 2m tow-link length against 70cm TDR measurements; and d) nominal 4m tow-link length against 70cm TDR measurements.

21 b ` a ` _^ ] 18 S R Q P Z [\ V Y X U WV T U Q R O P R P R O R R O P R Q R R Q P R c d e f g h i j k l m Figure 6: Comparison of 60cm TDR soil moisture measurements symbols) with the OhmMapper soil moisture estimate continuous line and symbol); solid circle 7 June, solid triangle 9 June, solid square 12 June, open circle 15 June, open triangle 19 June and open square 23 June.