owadays there is an increasing need to improve the irrigation and fertilizer efficiency of processing tomatoes in California’s Central Valley, because they represent a major crop in this area. For agronomical and research purposes, agricultural soils are generally monitored and sampled before, during and after the season in order to establish water and fertilizer balances. However, sub-surface drip irrigation and fertigation techniques increase the already heterogeneous water and nutrient distribution in the soil, making representative measurements a challenge. In addition, the crop water status is a proxy that needs to be assessed for evaluating the response of the crop to water management. In this study, we coupled multiple methodologies, including electrical resistivity imaging, 2D Hydrus modeling and proximal sensing techniques, for detecting the soil water redistribution, and characterizing the relative crop water status, in a sub-surface drip irrigated processing tomato field. Specifically, soil electrical resistivity was measured by electrical resistivity tomography (ERT) in two transects during an irrigation event in parallel and perpendicular to the subsurface drip irrigation line. The time-lapse ERT transects were compared to matching 2D-HYDRUS hydrological models and the relative differences were explained by local heterogeneities in electrical resistivity and water content changes. Water contents, measured with neutron probe and TDR techniques, were compared to the changes in resistivity during the irrigation event and the heterogeneity in the different root-zone locations described. In addition, surface temperature measured using infrared thermal thermometer (IRT) showed correlations with the ERT soil resistivity changes. In this study, a combination between multi-dimensional soil modeling and minimally invasive techniques (geophysical and IRT) has provided specific information on local water distribution and its interaction with root water uptake. This analysis will be used to enrich TDR-measured water contents and 2D modeling of root zone soil water dynamics of processing tomatoes during the rest of the season when spatially distributed ERT data is not available.

Detecting soil water distribution in subsurface irrigated tomato crops by coupling electrical resistivity imaging, 2D Hydrus modeling and proximal sensing techniques

Daniela Vanella;Juan Miguel Ramirez Cuesta;
2022-01-01

Abstract

owadays there is an increasing need to improve the irrigation and fertilizer efficiency of processing tomatoes in California’s Central Valley, because they represent a major crop in this area. For agronomical and research purposes, agricultural soils are generally monitored and sampled before, during and after the season in order to establish water and fertilizer balances. However, sub-surface drip irrigation and fertigation techniques increase the already heterogeneous water and nutrient distribution in the soil, making representative measurements a challenge. In addition, the crop water status is a proxy that needs to be assessed for evaluating the response of the crop to water management. In this study, we coupled multiple methodologies, including electrical resistivity imaging, 2D Hydrus modeling and proximal sensing techniques, for detecting the soil water redistribution, and characterizing the relative crop water status, in a sub-surface drip irrigated processing tomato field. Specifically, soil electrical resistivity was measured by electrical resistivity tomography (ERT) in two transects during an irrigation event in parallel and perpendicular to the subsurface drip irrigation line. The time-lapse ERT transects were compared to matching 2D-HYDRUS hydrological models and the relative differences were explained by local heterogeneities in electrical resistivity and water content changes. Water contents, measured with neutron probe and TDR techniques, were compared to the changes in resistivity during the irrigation event and the heterogeneity in the different root-zone locations described. In addition, surface temperature measured using infrared thermal thermometer (IRT) showed correlations with the ERT soil resistivity changes. In this study, a combination between multi-dimensional soil modeling and minimally invasive techniques (geophysical and IRT) has provided specific information on local water distribution and its interaction with root water uptake. This analysis will be used to enrich TDR-measured water contents and 2D modeling of root zone soil water dynamics of processing tomatoes during the rest of the season when spatially distributed ERT data is not available.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/596539
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