Geophysics in Agriculture
Sustainable Agricultural Intensification aims at reducing the environmental footprint of agricultural production by promoting a sustainable use of limited resources and minimizing the use of agrochemicals, salt accumulation, land degradation and greenhouse gas emissions while increasing productivity and profitability. Such an emphasis requires efficient field-assessments to evaluate continuously the performance of the implemented management strategies and traditional soil sampling methods, which require augering and soil pits for soil sampling and laboratory analysis, cannot provide a comprehensive answer to this problem. This is because they provide only limited spatial coverage and may therefore lack representativeness at the management scales. Furthermore, they are highly time and work consuming, resulting in costly surveys.
Geophysical techniques provide a non-invasive and cost-effective technology for soil survey and monitoring based on innovative sensors, advanced algorithms for 2D and 3D imaging, and new technologies for field surveying allowing assessment of soil properties at the management scale. Measurements obtained using geophysical methods can be related to several soil attributes, such as soil mineral composition, clay content, moisture, salinity, organic carbon, pH, and cation exchange capacity, which are all relevant for agriculture. These techniques provide also a unique opportunity to monitor the processes relevant for agricultural production from the analysis of time-dependent change of water content to the detection of pollutants and from the analysis of soil salinization and fertility to the study of soil–root plant interactions.
My main goal in precision agriculture is to contribute to more efficient field-assessment techniques for soil properties mapping by coupling geophysical observations to limited soil property data using mathematical models. My current research in precision agriculture is a collaboration with international team from University of New South Wales, Australia, University of Lisbon, Portugal, IFAPA, Spain, Italian National Research Council, Italy, National research Institute of rural engineering, Water and Forests, Tunisia and Port Said University, Egypt.
Related publications:
Farzamian, M., Bouksila, F., Paz, Monteiro Santos, F., A., Zemin, N, Salma, F, Ben Slimane, A., Selimi, T., and Triantafilis, J. 2023. Landscape-scale mapping of soil salinity with multi-height electromagnetic induction and quasi-3D inversion (Saharan Oasis, Tunisia), Agric. Water Manag., 284, 108330, https://doi.org/10.1016/j.agwat.2023.108330.
Farzamian, M., Autovino, D., Basile, A., De Mascellis, R., Dragonetti, G., Monteiro Santos, F., Binley, A., and Coppola, A. 2021. Assessing the dynamics of soil salinity with time-lapse inversion of electromagnetic data guided by hydrological modelling, Hydrol. Earth Syst. Sci., 25, 1509–1527, https://doi.org/10.5194/hess-25-1509-2021, 2021.
Farzamian, M., Paz, M.C., Monteiro Santos, F., Gonçalves, M.C., Paz, A.M., Castanheira., N.L., Triantafilis, J. 2019. Mapping soil salinity using electromagnetic conductivity imaging – a comparison of regional and location-specific calibrations. Land Degradation and Development 30, 1393–1406. https://doi.org/10.1002/ldr.3317
Paz, M. C., Farzamian, M., Paz, A. M., Castanheira, N. L., Gonçalves, M. C., and Monteiro Santos, F. 2020. Monitoring soil salinity dynamics using time-lapse electromagnetic conductivity imaging, SOIL, 6, 499–511, https://doi.org/10.5194/soil-6-499-2020,
Paz, A., Castanheira., N., Farzamian, M., Paz, M.C., Gonçalves, M., Monteiro Santos, F., and Triantafilis, J. 2020. Prediction of soil salinity and sodicity using electromagnetic conductivity imaging. Geoderma, 361, 114086, https://doi.org/10.1016/j.geoderma.2019.114086.
Geophysical techniques provide a non-invasive and cost-effective technology for soil survey and monitoring based on innovative sensors, advanced algorithms for 2D and 3D imaging, and new technologies for field surveying allowing assessment of soil properties at the management scale. Measurements obtained using geophysical methods can be related to several soil attributes, such as soil mineral composition, clay content, moisture, salinity, organic carbon, pH, and cation exchange capacity, which are all relevant for agriculture. These techniques provide also a unique opportunity to monitor the processes relevant for agricultural production from the analysis of time-dependent change of water content to the detection of pollutants and from the analysis of soil salinization and fertility to the study of soil–root plant interactions.
My main goal in precision agriculture is to contribute to more efficient field-assessment techniques for soil properties mapping by coupling geophysical observations to limited soil property data using mathematical models. My current research in precision agriculture is a collaboration with international team from University of New South Wales, Australia, University of Lisbon, Portugal, IFAPA, Spain, Italian National Research Council, Italy, National research Institute of rural engineering, Water and Forests, Tunisia and Port Said University, Egypt.
Related publications:
Farzamian, M., Bouksila, F., Paz, Monteiro Santos, F., A., Zemin, N, Salma, F, Ben Slimane, A., Selimi, T., and Triantafilis, J. 2023. Landscape-scale mapping of soil salinity with multi-height electromagnetic induction and quasi-3D inversion (Saharan Oasis, Tunisia), Agric. Water Manag., 284, 108330, https://doi.org/10.1016/j.agwat.2023.108330.
Farzamian, M., Autovino, D., Basile, A., De Mascellis, R., Dragonetti, G., Monteiro Santos, F., Binley, A., and Coppola, A. 2021. Assessing the dynamics of soil salinity with time-lapse inversion of electromagnetic data guided by hydrological modelling, Hydrol. Earth Syst. Sci., 25, 1509–1527, https://doi.org/10.5194/hess-25-1509-2021, 2021.
Farzamian, M., Paz, M.C., Monteiro Santos, F., Gonçalves, M.C., Paz, A.M., Castanheira., N.L., Triantafilis, J. 2019. Mapping soil salinity using electromagnetic conductivity imaging – a comparison of regional and location-specific calibrations. Land Degradation and Development 30, 1393–1406. https://doi.org/10.1002/ldr.3317
Paz, M. C., Farzamian, M., Paz, A. M., Castanheira, N. L., Gonçalves, M. C., and Monteiro Santos, F. 2020. Monitoring soil salinity dynamics using time-lapse electromagnetic conductivity imaging, SOIL, 6, 499–511, https://doi.org/10.5194/soil-6-499-2020,
Paz, A., Castanheira., N., Farzamian, M., Paz, M.C., Gonçalves, M., Monteiro Santos, F., and Triantafilis, J. 2020. Prediction of soil salinity and sodicity using electromagnetic conductivity imaging. Geoderma, 361, 114086, https://doi.org/10.1016/j.geoderma.2019.114086.