| Title: |
High-resolution frequency-domain electromagnetic mapping for the hydrological modeling of an orange orchard |
| Authors: |
Peruzzo, Luca; Werban, Ulrike; Pohle, Marco; Pavoni, Mirko; Mary, Benjamin; Cassiani, Giorgio; Consoli, Simona; Vanella, Daniela |
| Contributors: |
Peruzzo, Luca; Werban, Ulrike; Pohle, Marco; Pavoni, Mirko; Mary, Benjamin; Cassiani, Giorgio; Consoli, Simona; Vanella, Daniela |
| Publisher Information: |
Copernicus Publications |
| Publication Year: |
2025 |
| Collection: |
Padua Research Archive (IRIS - Università degli Studi di Padova) |
| Description: |
While aboveground precision agriculture technologies provide spatial and temporal datasets that are ever increasing in terms of density and precision, belowground information lags behind and has been typically limited to time series. As recognized in agrogeophysics, geophysical methods can address the lack of subsurface spatial information. This study focuses on high-resolution frequency-domain electromagnetic induction (FDEM) mapping as an ideal complement to aboveground and belowground time series that are commonly available in precision agriculture. Focused on a Sicilian orange orchard, this study first investigates some methodological challenges behind seemingly simple FDEM survey choices and processing steps, as well as their interplay with the spatial heterogeneity of agricultural sites. Second, this study shows how the detailed FDEM-based spatial information can underpin a surface/subsurface hydrological model that integrates time series from soil moisture sensors and micro-meteorological sensors. While FDEM has long been recognized as a promising solution in agrogeophysics, this study demonstrates how the approach can be successfully applied in an orchard, whose 3D subsurface variability is a complex combination of root water uptake, irrigation, evapotranspiration, and row-interrow dynamics. The resulting hydrological model reproduces the observed spatiotemporal water dynamics with parameters that agree with the results from soil laboratory analysis, supporting gamma-ray and electrical resistivity tomography datasets. The implementation of a hydrological model positively aligns with the increasing number and variety of methods in precision agriculture, as well as with the need for better predictive capability. |
| Document Type: |
article in journal/newspaper |
| Language: |
English |
| Relation: |
info:eu-repo/semantics/altIdentifier/wos/WOS:001593251200001; volume:11; issue:2; firstpage:811; lastpage:831; numberofpages:21; journal:SOIL; https://hdl.handle.net/11577/3581638 |
| DOI: |
10.5194/soil-11-811-2025 |
| Availability: |
https://hdl.handle.net/11577/3581638; https://doi.org/10.5194/soil-11-811-2025 |
| Rights: |
info:eu-repo/semantics/openAccess ; license:Creative commons ; license uri:http://creativecommons.org/licenses/by/4.0/ |
| Accession Number: |
edsbas.FA69A3EB |
| Database: |
BASE |