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The sedimentological connectivity of agricultural catchments may be affected by anthropogenic structures (land management practices) established to reduce sediment exportation from agricultural plots to water streams. Distributed erosion models may in theory provide information about where and how these structures should be installed in catchments to reduce sediment exportation. The interaction between sediment exportation and land management practices is very complex from both theoretical and experimental points of view. Vegetated fi lters are a widely used land management practice. They interact with water fl ow, change turbulence conditions, and ultimately affect sediment transport and deposition processes. Experimental results have shown that the effi ciency of sediment trapping in vegetated fi lters is infl uenced by fl ow characteristics, sediment size, and vegetation type, as well as by the slope and width of the fi lter in the streamwise direction. At the catchment scale, the spatial organisation of management practices is crucial for the global sedimentological connectivity. Present-day erosion models propose different approaches to simulate the infl uence of management practices on soil loss and sediment export for agricultural catchments. Some of them use the Sediment Delivery Ratio (SDR) or P-factor to describe sediment transport from source to sink areas. Others, such as in the TRAVA and VSFMOD, rely on process-based descriptions involving changes in roughness and infi ltrability along fl ow paths to study the effect of management practices. From the literature review conducted herein, we identifi ed the lack of an approach of intermediate complexity, that would be more physically relevant than SDR and P-factor approaches, but simpler and easier to spatialise than TRAVA and VSFMOD-type models.

Abstract:The objective of this study was to analyze the sensitivity of radar signals in the X-band in irrigated grassland conditions. The backscattered radar signals were analyzed according to soil moisture and vegetation parameters using linear regression models. A time series of radar (TerraSAR-X and COSMO-SkyMed) and optical (SPOT and LANDSAT) images was acquired at a high temporal frequency in 2013 over a small agricultural region in southeastern France. Ground measurements were conducted simultaneously with the satellite data acquisitions during several grassland growing cycles to monitor the evolution of the soil and vegetation characteristics. The comparison between the Normalized Difference Vegetation Index (NDVI) computed from optical images and the in situ Leaf Area Index (LAI) showed a logarithmic relationship with a greater scattering for the dates . Results showed that the radar signal depends on variations in soil moisture, with a higher sensitivity to soil moisture for biomass lower than 1 kg/m². HH and HV polarizations had approximately similar sensitivities to soil moisture. The penetration depth of the radar wave in the X-band was high, even for dense and high vegetation; flooded areas were visible in the images with higher detection potential in HH polarization than in HV polarization, even for vegetation heights reaching 1 m. Lower sensitivity was observed at the X-band between the radar signal and the vegetation parameters with very limited potential of the X-band to monitor grassland growth. These results showed that it is possible to track gravity irrigation and soil moisture variations from SAR X-band images acquired at high spatial resolution (an incidence angle near 30°).

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Abstract. Agrivoltaism is the association of agricultural and photovoltaic energy production on the same land area, coping with the increasing pressure on land use and water resources while delivering clean and renewable energy. However, the solar panels located above the cultivated plots also have a seemingly yes unexplored effect on rain redistribution, sheltering large parts of the plot but redirecting concentrated fluxes on a few locations. The spatial heterogeneity in water amounts observed on the ground is high in the general case; its dynamical patterns are directly attributable to the mobile panels through their geometrical characteristics (dimensions, height, coverage percentage) and the strategies selected to rotate them around their support tube. A coefficient of variation is used to measure this spatial heterogeneity and to compare it with the coefficient of uniformity that classically describes the efficiency of irrigation systems. A rain redistribution model (AVrain) was derived from literature elements and theoretical grounds and then validated from experiments in both field and controlled conditions. AVrain simulates the effective rain amounts on the plot from a few forcing data (rainfall, wind velocity and direction) and thus allows real-time strategies that consist in operating the panels so as to limit the rain interception mainly responsible for the spatial heterogeneities. Such avoidance strategies resulted in a sharp decrease in the coefficient of variation, e.g. 0.22 vs. 2.13 for panels held flat during one of the monitored rain events, which is a fairly good uniformity score for irrigation specialists. Finally, the water amounts predicted by AVrain were used as inputs to Hydrus-2D for a brief exploratory study on the impact of the presence of solar panels on rain redistribution at shallow depths within soils: similar, more diffuse patterns were simulated and were coherent with field measurements.