Linking satellite derived LAI patterns with subsoil heterogeneity using large-scale ground-based electromagnetic induction measurements

摘要

Patterns in crop development and yield are often directly related to lateral and vertical changes in soil textureudcausing changes in available water and resource supply for plant growth, especially under dry conditions. Relictudgeomorphologic features, such as old river channels covered by shallow sediments can challenge assumptions ofuduniformity in precision agriculture, subsurface hydrology, and crop modeling. Hence a better detection of theseudsubsurface structures is of great interest. In this study, the origins of narrow and undulating leaf area indexud(LAI) patterns showing better crop performance in large scale multi-temporal satellite imagery were for theudfirst time interpreted by proximal soil sensor data. A multi-receiver electromagnetic induction (EMI) sensor measuringudsoil apparent electrical conductivity (ECa) for six depths of exploration (DOE) ranging from 0–0.25 toud0–1.9 m was used as reconnaissance soil survey tool in combination with selected electrical resistivity tomographyud(ERT) transects, and ground truth texture data to investigate lateral and vertical changes of soil properties atudten arable fields. The moderate to excellent spatial consistency (R2 0.19–0.82) of ECa patterns and LAI crop marks that indicate a higher water storage capacity as well as the increased correlations between large-offset ECa dataudand the subsoil clay content and soil profile depth, implies that along this buried paleo-river structure the subsoil is mainly responsible for better crop development in drought periods. Furthermore, observed stagnant water inudthe subsoil indicates that this paleo-river structure still plays an important role in subsurface hydrology. Theseudinsights should be considered and implemented in local hydrological as well as crop models.