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

Patterns in crop development and yield are often directly related to lateral and vertical changes in soil texture causing changes in available water and resource supply for plant growth, especially under dry conditions. Relict geomorphologic features, such as old river channels covered by shallow sediments can challenge assumptions of uniformity in precision agriculture, subsurface hydrology, and crop modeling. Hence a better detection of these subsurface structures is of great interest. In this study, the origins of narrow and undulating leaf area index (LAI) patterns showing better crop performance in large scale multi-temporal satellite imagery were for the first time interpreted by proximal soil sensor data. A multi-receiver electromagnetic induction (EMI) sensor measuring soil apparent electrical conductivity (ECa) for six depths of exploration (DOE) ranging from 0–0.25 to 0–1.9 m was used as reconnaissance soil survey tool in combination with selected electrical resistivity tomography (ERT) transects, and ground truth texture data to investigate lateral and vertical changes of soil properties at ten 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 data and 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 in the subsoil indicates that this paleo-river structure still plays an important role in subsurface hydrology. These insights should be considered and implemented in local hydrological as well as crop models

Infiltration from the pedon to global grid scales: an overview and outlook for land surface modelling

Infiltration in soils is a key process that partitions precipitation at the land surface in surface runoff and water that enters the soil profile. We reviewed the basic principles of water infiltration in soils and we analyzed approaches commonly used in Land Surface Models (LSMs) to quantify infiltration as well as its numerical implementation and sensitivity to model parameters. We reviewed methods to upscale infiltration from the point to the field, hill slope, and grid cell scale of LSMs. Despite the progress that has been made, upscaling of local scale infiltration processes to the grid scale used in LSMs is still far from being treated rigorously. We still lack a consistent theoretical framework to predict effective fluxes and parameters that control infiltration in LSMs. Our analysis shows, that there is a large variety in approaches used to estimate soil hydraulic properties. Novel, highly resolved soil information at higher resolutions than the grid scale of LSMs may help in better quantifying subgrid variability of key infiltration parameters. Currently, only a few land surface models consider the impact of soil structure on soil hydraulic properties. Finally, we identified several processes not yet considered in LSMs that are known to strongly influence infiltration. Especially, the impact of soil structure on infiltration requires further research. In order to tackle the above challenges and integrate current knowledge on soil processes affecting infiltration processes on land surface models, we advocate a stronger exchange and scientific interaction between the soil and the land surface modelling communities

Accounting for soil surface roughness in the inversion of ultrawideband off-ground GPR signal for soil moisture retrieval

We combined a full-waveform ground-penetrating radar (GPR) model with a roughness model to retrieve surface soil moisture through signal inversion. The proposed approach was validated under laboratory conditions with measurements performed above a sand layer subjected to seven different water contents and four different surface roughness conditions. The radar measurements were performed in the frequency domain in the range of 1–3 GHz and the roughness amplitude standard deviation was varied from 0 to 1 cm. Two inversion strategies were investigated: (1) Full-waveform inversion using the correct model configuration, and (2) inversion focused on the surface reflection only. The roughness model provided a good description of the frequency-dependent roughness effect. For the fullwaveform analysis, accounting for roughness permitted us to simultaneously retrieve water content and roughness amplitude. However, in this approach, information on soil layering was assumed to be known. For the surface reflection analysis, which is applicable under field conditions, accounting for roughness only enabled water content to be reconstructed, but with a root mean square error (RMS) in terms of water content of 0.034 m3 m−3 compared to an RMS of 0.068 m3 m−3 for an analysis where roughness is neglected. However, this inversion strategy required a priori information on soil surface roughness, estimated, e.g., from laser profiler measurements

Bentonite clay combined with organic amendments to enhance soil fertility in oasis agrosystem

oils in arid and semi-arid lands are vulnerable to climate change, erosion, and mismanagement practices that contribute to organic matter depletion and nutrients imbalances. Oasis agrosystems are considered one of the major farming systems in some parts of these lands in the Middle East and North Africa region. However, oases soils are inherently low in organic carbon due to their sandy texture which retains little water and binds low organic matter contents, and the accelerated decomposition rates of organic matter under high temperature, which makes its accumulation difficult. Traditional farming practices in oasis agrosystems have always integrated organic matter derived from livestock to enhance organic carbon (OC) and total nitrogen (TN) stocks in the soil. This study is aimed to examine the potential effects of a new mixture of organic amendments and bentonite clay on organic carbon and total nitrogen stock accumulation in the soil. Five amendments were applied including sand and compost (SC), sand and manure (SM), sand, bentonite, and compost (SBC), sand, bentonite, and manure (SBM), and sand mixed with bentonite (SB). These treatments were compared to untreated soil (U). The results showed that OC and TN stocks increased significantly (p<0.05) in all three depths of the five treatments compared to the untreated soil. Higher organic carbon stocks (2862±3.4 g m−2) were detected in SBM treatment. The combined organic and mineral amendment retarded OC and TN decomposition. After two years of the amendments’ application, 30% of OC remained in the soil for SBC treatment. In conclusion, the mixed mineral and organic amendment is a better choice to preserve OC and, thus, maintain oasis soil fertility

New improved algorithm for sky calibration of L-band radiometers JÜLBARA and ELBARA II.

peer reviewedWe propose a new algorithm for sky calibration of the L-band radiometers JLBARA and ELBARA II, introducing the effective transmissivities of the instruments. The suggested approach was tested using experimental data obtained at the Selhausen test site, Germany. It was shown that for JLBARA the effective transmissivities depend strongly on the air temperature and decrease with increasing air temperature, while for ELBARA II such strong dependence was not observed. It was also shown that the effective transmissivities account for the antenna and feed cable loss effects, and for the variations of the radiometer gain due to air temperature changes. The new calibration algorithm reduces significantly the bias of brightness temperature estimates for both radiometers, especially for JLBARA. © 2012 IEEE