Richards equation at the hillslope scale: Can we resolve the heterogeneity of soil hydraulic material properties?
• +2
• Hannes H Bauser,
• Minseok Kim,
• Wei-Ren Ng,
• Aaron Bugaj,
• Peter A. Troch
Hannes H Bauser
University of Arizona

Corresponding Author:hannes.bauser@gmail.com

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Minseok Kim
University of Arizona
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Wei-Ren Ng
University of Arizona
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Aaron Bugaj
University of Arizona
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Peter A. Troch
University of Arizona
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## Abstract

Process-based modeling of soil water movement with the Richards equation requires the description of soil hydraulic material properties, which are highly uncertain and heterogeneous at all scales. This limits the applicability of Richards equation at larger scales beyond the patch scale. The experimental capabilities of the three hillslopes of the Landscape Evolution Observatory (LEO) at Biosphere 2 provide a unique opportunity to observe the heterogeneity of hydraulic material properties at the hillslope scale. We performed a gravity flow experiment where through constant irrigation the water content increases until the hydraulic conductivity matches the irrigation flux above. The dense water content sensor network at LEO then allows to map the heterogeneity of hydraulic conductivity at a meter scale resolution. The experiment revealed spatial structures within the hillslopes, mainly a vertical trend with the lowest hydraulic conductivity close to the surface. However, the variation between neighbouring sensors is high, showing that the heterogeneity cannot be fully resolved even at LEO. By representing the heterogeneity in models through Miller scaling we showed the impact on hillslope discharge. For the hillslope with the smallest heterogeneity, representing the dominant structures was sufficient. However, for the two hillslopes with the larger overall heterogeneity, adding further details of the local heterogeneity did impact the discharge further. This highlights the limitations of Richards equation, which requires the heterogeneous field of material properties, at the hillslope scale and shows the relevance to improve our understanding of effective parameters to be able to apply the process-based model to larger scales.