Journal
COMMUNICATIONS EARTH & ENVIRONMENT
Volume 2, Issue 1, Pages -Publisher
SPRINGERNATURE
DOI: 10.1038/s43247-021-00180-0
Keywords
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Funding
- ETH Zurich research grant [ETH-18 18-1]
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This study proposes a systematic framework to incorporate soil structure corrections into pedotransfer functions, informed by remote-sensing vegetation metrics and local soil texture, to investigate their effects on infiltration-runoff partitioning. Results show that small scale soil structure features significantly alter hydrologic response at larger scales, and upscaled parameterizations should consider spatial correlations between vegetation and soil texture. The framework allows incorporation of hydrological effects of soil structure into contemporary pedotransfer functions used for land surface parameterization.
Earth system models use soil information to parameterize hard-to-measure soil hydraulic properties based on pedotransfer functions. However, current parameterizations rely on sample-scale information which often does not account for biologically-promoted soil structure and heterogeneities in natural landscapes, which may significantly alter infiltration-runoff and other exchange processes at larger scales. Here we propose a systematic framework to incorporate soil structure corrections into pedotransfer functions, informed by remote-sensing vegetation metrics and local soil texture, and use numerical simulations to investigate their effects on spatially distributed and areal averaged infiltration-runoff partitioning. We demonstrate that small scale soil structure features prominently alter the hydrologic response emerging at larger scales and that upscaled parameterizations must consider spatial correlations between vegetation and soil texture. The proposed framework allows the incorporation of hydrological effects of soil structure with appropriate scale considerations into contemporary pedotransfer functions used for land surface parameterization. Small-scale soil hydraulic properties can be accounted for in large-scale hydrologic and climate models by incorporating vegetation influences on soil structure, informed by global-scale vegetation metrics and soil texture data
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