Applications of geophysical methods in agriculture and their potential in Vietnam

Geophysical methods are very popular in Vietnam and have been applied for several decades in deep-earth investigations such as geological mapping, mineral resource searching, and especially oil and gas exploration. In the world, they have proven to be great tools in agriculture as well for soil characterization and monitoring thanks to their notable advantages including rapid data acquisition, large data coverage, high data density, non-destructive and inexpensive survey implementation. However, in Vietnam, the applications of geophysical methods in agriculture have received little attention probably due to the lack of suitable equipment and data processing techniques. This article gives an overview of popular geophysical methods being applied in agriculture in several countries to characterize and monitor soil properties such as moisture, salinity, density, texture, structure, porosity, etc. The main uses of each method are summarized, and relevant publications are given for reading recommendations with the aim of suggesting similar applications in Vietnam. Accordingly, Ground Penetrating Radar (GPR) and Electromagnetic Induction (EMI) are the most versatile with minimum field crew for data acquisition. They should be prioritized to try in Vietnamese agriculture. Since EMI equipment is not currently available in Vietnam, only a GPR test survey was implemented in the Agricultural Academy experimental field by the authors of Hanoi University of Mining and Geology. The preliminary result shows that the biggest challenge is to find reliable techniques to accurately infer soil properties from measured geophysical parameters, which have no explicit relationship with soil properties. Noise suppression is another problem that needs to be addressed to ensure sufficient data quality.

How to Cite

Phan, H.Thien, Vu, D.Hong, Tran, H.Danh and Nguyen, T.Thanh 2024. Applications of geophysical methods in agriculture and their potential in Vietnam. Journal of Mining and Earth Sciences. 65, 2 (Apr, 2024), 86-95. DOI:https://doi.org/10.46326/JMES.2024.65(2).10.

References

Akinsunmade, A.; Tomecka-Suchoń, S.; Pysz, P.,m (2019). Correlation between agrotechnical properties of selected soil types and corresponding GPR response. Acta Geophys., 67, 1913–1919.

Allred, B.J., Freeland, R.S., Farahani, H.J. and Collins, M.E. (2010). Agricultural geophysics: Past, present, and future. In Symposium on the Application of Geophysics to Engineering and Environmental Problems 2010 (pp. 190-202). Society of Exploration Geophysicists.

Ameglio, L. (2018). Review of developments in airborne geophysics and geomatics to map variability of soil properties. In International Conference on Precision Agriculture, Canada. XIV.

Barca, E., De Benedetto, D. and Stellacci, A.M. (2019). Contribution of EMI and GPR proximal sensing data in soil water content assessment by using linear mixed effects models and geostatistical approaches. Geoderma, 343, pp.280-293.

Besson, A.; Séger, M.; Giot, G.; Cousin, I., (2013). Identifying the characteristic scales of soil structural recovery after compaction from three in-field methods of monitoring. Geoderma, 204–205, 130–139.

Blanchy, G.; Watts, C.W.; Richards, J.; Bussell, J.; Huntenburg, K.; Sparkes, D.L.; Stalham, M.; Hawkesford, M.J.; Whalley, W.R.; Binley, A. (2020) Time-lapse geophysical assessment of agricultural practices on soil moisture dynamics. Vadose Zone J. 19, e20080.

Cavallo, G., De Benedetto, D., Castrignanò, A., Quarto, R., Vonella, A.V. and Buttafuoco, G. (2016). Use of geophysical data for assessing 3D soil variation in a durum wheat field and their association with crop yield. Biosystems Engineering, 152, pp.28-40.

Cheng, Q., Tao, M., Chen, X., Binley, A. (2019) Evaluation of electrical resistivity tomography (ERT) for mapping the soil–rock interface in karstic environments. Environ. Earth Sci., 78, 1–14.

Corwin, D.L. (2008). Past, present, and future trends in soil electrical conductivity measurements using geophysical methods. Handbook of agricultural geophysics, pp.17-44.

De Benedetto, D., Castrignano, A., Sollitto, D., Modugno, F., Buttafuoco, G., Papa, G.L. (2012). Integrating geophysical and geostatistical techniques to map the spatial variation of clay. Geoderma , 171–172, 53–63.

De Jong, S.M., Heijenk, R.A., Nijland, W., Van Der Meijde, M. (2020). Monitoring Soil Moisture Dynamics Using Electrical Resistivity Tomography under Homogeneous Field Conditions. Sensors, 20, 5313.

Ditzler, C., Scheffe, K. and Monger, H.C. (2017). Soil Survey Manual (Agriculture Handbook Nº 18). United States Department of Agriculture. Soil Science Division Staff, USA, 638 pages.

Doolittle, J.A. and Brevik, E.C. (2014). The use of electromagnetic induction techniques in soils studies. Geoderma, 223, pp.33-45.

Donohue, S., Forristal., D., and Donohue, L. A. (2013). Detection of soil compaction using seismic surface waves. Soil and Tillage Research, 128, 54–60.

Jadoon, K.Z., Moghadas, D., Jadoon, A., Missimer, T.M., Al-Mashharawi, S.K., McCabe, M.F. (2015). Estimation of soil salinity in a drip irrigation system by using joint inversion of multicoil electromagnetic induction measurements. Water Resour. Res., 51, 3490–3504

Jonard, F., Mahmoudzadeh, M., Roisin, C., Weihermüller, L., André, F., Minet, J., Vereecken, H. and Lambot, S. (2013). Characterization of tillage effects on the spatial variation of soil properties using ground-penetrating radar and electromagnetic induction. Geoderma, 207, pp.310-322.

Galagedara, L.W., Parkin, G.W., Redman, J.D., Von Bertoldi, P. and Endres, A.L. (2005). Field studies of the GPR ground wave method for estimating soil water content during irrigation and drainage. Journal of hydrology, 301(1-4), pp.182-197.

Grote, K., Anger, C., Kelly, B., Hubbard, S. and Rubin, Y. (2010). Characterization of soil water content variability and soil texture using GPR groundwave techniques. Journal of Environmental and Engineering Geophysics, 15(3), pp.93-110.

Gourdol, L., Clément, R., Juilleret, J., Pfister, L., Hissler, C. (2018). Large-scale ERT surveys for investigating shallow regolith properties and architecture. Hydrol. Earth Syst. Sci. Discuss., 1–39.

Heil, K., Schmidhalter, U. (2012). Characterization of soil texture variability using the apparent soil electrical conductivity at a highly variable site. Comput. Geosci., 39, 98–110.

Huang J., Scudiero H., Bagtang M., Corwin D.L., Triantaflis J. (2016). Monitoring scale specific and temporal variation in electromagnetic conductivity images, s. Irrig. Sci., 34, 187–200.

Huisman, J.A., Hubbard, S.S., Redman, J.D. and Annan, A.P. (2003). Measuring soil water content with ground penetrating radar: A review. Vadose zone journal, 2(4), pp.476-491.

Kassim, A.M., Nawar, S. and Mouazen, A.M. (2021). Potential of on-the-go gamma-ray spectrometry for estimation and management of soil potassium site specifically. Sustainability, 13(2), p.661.

Keller, T., Carizzoni, M., Berisso, F.E., Stettler, M. and Lamandé, M. (2013). Measuring the dynamic soil response during repeated wheeling using seismic methods. Vadose Zone Journal, 12(3), pp.vzj2013-01.

Keller, T., Colombi, T., Ruiz, S., Manalili, M.P., Rek, J., Stadelmann, V., Wunderli, H., Breitenstein, D., Reiser, R., Oberholzer, H. (2017). Long-Term Soil Structure Observatory for Monitoring Post-Compaction Evolution of Soil Structure. Vadose Zone J., 16, 1–16.

Klotzsche, A., Jonard, F., Looms, M.C., van der Kruk, J. and Huisman, J.A. (2018). Measuring soil water content with ground penetrating radar: A decade of progress. Vadose Zone Journal, 17(1), pp.1-9.

Lesmes, D.P., Herbstzuber, R.J. and Wertz, D. (1999). Terrain permittivity mapping: GPR measurements of near-surface soil moisture. In Symposium on the Application of Geophysics to Engineering and Environmental Problems 1999 (pp. 575-582). Society of Exploration Geophysicists.

Lu, Y., Song, W., Lu, J., Wang, X., Tan, Y. (2017). An Examination of Soil Moisture Estimation Using Ground Penetrating Radar in Desert Steppe. Water , 9, 521.

Mahmood, H.S., Hoogmoed, W.B. and Van Henten, E.J. (2013). Proximal gamma-ray spectroscopy to predict soil properties using windows and full-spectrum analysis methods. Sensors, 13(12), pp.16263-16280.

Moghadas, D., Jadoon, K.Z., McCabe, M. (2019). Spatiotemporal monitoring of soil moisture from EMI data using DCT-based Bayesian inference and neural network. J. Appl. Geophys., 169, 226–238.

Muñiz, E., Shaw, R.K., Gimenez, D., Williams, C.A., Kenny, L. (2016). Use of Ground-Penetrating

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