Soil hydrology in the Earth systemVereecken, H., Amelung, W., Bauke, S. L., Bogena, H., Brüggemann, N., Montzka, C., Vanderborght, J., Bechtold, M., Blöschl, G., Carminati, A., Javaux, M., Konings, A. G., Kusche, J., Neuweiler, I., Or, D., Steele-Dunne, S., Verhoef, A. ORCID: https://orcid.org/0000-0002-9498-6696, Young, M. and Zhang, Y. (2022) Soil hydrology in the Earth system. Nature Reviews Earth & Environment, 3. pp. 573-587. ISSN 2662-138X
It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1038/s43017-022-00324-6 Abstract/SummaryPredicting the impact of land use and climate change on the Earth system hinges on credible representation of soil hydrological processes (SHP), adequate availability of parameters and hydrological states and inclusion of key soil properties. There is increasing evidence that extreme events such as droughts and high intensity precipitation, and land use changes, affect fundamental hydrological processes such as infiltration and runoff generation. In this review, we analyse the influence of soil structure on SHP, critically evaluate the parameterization of soil hydrologic properties and their importance in representing the terrestrial water cycle and highlight the key role of soil hydrology in the functioning of carbon-rich soils and in linking the water and carbon cycles. It emerges that linking soil hydrology and pedology will lead to better understanding critical zone processes, especially in tropical regions. Further, we discuss the role of local scale hydrological processes in understanding root water uptake, vegetation and groundwater dynamics and feedbacks. These processes control and modulate the impact of extreme events such as droughts, floods and heatwaves and they are essential to assess drought and flooding. Finally, new emerging technologies such as wireless and automated sensing approaches, soil moisture observation through novel synthetic aperture radars satellites, big data analysis and machine learning approaches offer unique opportunities to advance soil hydrology.
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