Assessing soil water content variation in a small mountainous catchment over different time scales and land covers using geographical variables

JOURNAL OF HYDROLOGY

卷:591

Article

Mallet, Florian¹  Marc, Vincent¹  Douvinet, Johnny²  Rossello, Philippe³  Joly, Daniel⁴  Ruy, Stephane⁵ 

[1] Univ Avignon, UMR 1114 EMMAH, Avignon, France

[2] Univ Avignon, UMR 7300, CNRS ESPACE, Avignon, France

[3] GeographR, Avignon, France

[4] Univ Bourgogne Franche Comte, Lab TheMA UMR 6049, CNRS, Besancon, France

[5] INRA, UMR 1114 EMMAH, Avignon, France

关键词: Soil water content;    Headwater catchment;    Flash flood;    Monitoring;   

DOI  :  10.1016/j.jhydrol.2020.125593

来源: Elsevier

【 摘 要 】

Soil Water Content (SWC) plays a key role in hydrological processes at the catchment scale. It is highly dependent on local variables (such as soil properties, vegetation type, and topography) and rainfall, which makes it vary in space and time. To characterize its complexity, scientists need SWC monitoring at short time-steps and at different spatial scales (plot, hillslope, sub-catchment). Today such monitoring is possible due to sensors based on geophysical methods that measure SWC at the plot scale, but assessing the space-time variation of SWC remains a challenge in mountainous catchments. This study focuses on a small headwater catchment (Laval, 0.86 km(2), Draix-Bleone observatory) composed primarily of black marls in which soil water content variations are assumed to occur primarily in the subsurface (0 cm-50 cm). To characterize the catchment inner hydrological response and to identify parameters controlling hydrological processes, 14 capacitance sensors were set up to monitor SWC at a 15 min time-step at depths of 10 cm to 20 cm; this network complements classic measurements (rainfall, outflows, erosion) in various soil-landscape-hydrological units. The model LISDQS (Interpolation of Quantitative and Spatial Data) based on local topographic variables (from a 1 m resolution Digital Elevation Model) (DEM), Normalized Difference Vegetation Index (NDVI), and soil depth made it possible to estimate SWC at the plot scale and at different time scales. Estimated SWC were compared to SWC time-series collected since May 2016. Finally, this method points out how local parameters that control SWC affect this variable according to rainfall and the catchment initial soil hydric status. At the hourly and daily time scales, SWC variations were highly dependent on curvature index and NDVI during wetting period, and primarily on soil depth and NDVI during drying periods. At 15 min time steps, 7 rainfall-runoff events have been investigated. SWC variations were highly dependent on rainfall intensity and initial SWC. At the same time step, matrix flow was characterized as the main subsurface flow type during fall flood events in every monitored environment while preferential flow appeared during summer flood events and mainly in grassland.

【 授权许可】

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