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

Estimation of Soil Hydraulic Parameters in the Field by Integrated Hydrogeophysical Inversion of Time-Lapse Ground-Penetrating Radar Data

An integrated hydrogeophysical inversion approach was used to remotely infer the unsaturated soil hydraulic parameters from time-lapse ground-penetrating radar (GPR) data collected at a fixed location over a bare agricultural field. The GPR model combines a full-waveform solution of Maxwell’s equations for three-dimensional wave propagation in planar layered media together with global reflection and transmission functions to account for the antenna and its interactions with the medium. The hydrological simulator HYDRUS-1D was used with a two layer single- and dual-porosity model. The radar model was coupled to the hydrodynamic model, such that the soil electrical properties (permitivity and conductivity) that serve as input to the GPR model become a function of the hydrodynamic model output (water content), thereby permiting estimation of the soil hydraulic parameters from the GPR data in an inversion loop. To monitor the soil water content dynamics, time-lapse GPR and time domain reflectometry (TDR) measurements were performed, whereby only GPR data was used in the inversion. Significant effects of water dynamics were observed in the time-lapse GPR data and in particular precipitation and evaporation events were clearly visible. The dual porosity model provided better results compared to the single porosity model for describing the soil water dynamics, which is supported by field observations of macropores. Furthermore, the GPR-derived water content profiles reconstructed from the integrated hydrogeophysical inversion were in good agreement with TDR observations. These results suggest that the proposed method is promising for non-invasive characterization of the shallow subsurface hydraulic properties and monitoring water dynamics at the field scale