A new dynamic wetness index (DWI) predicts soil moisture persistence and correlates with key indicators of surface soil geochemistry

Ming Li, Erika J. Foster, Phong V.V. Le, Qina Yan, Andrew Stumpf, Tingyu Hou, A. N.(Thanos) Papanicolaou, Kenneth M. Wacha, Christopher G. Wilson, Jingkuan Wang, Praveen Kumar, Timothy Filley

Research output: Contribution to journalArticle

Abstract

Commonly, the topographic influence on soil hydrology is calculated as a Topographic Wetness Index (TWI), which often correlates with surface soil properties, such as carbon and nitrogen, across broad spatial scales. However, traditional TWI methods can be ineffective at capturing finer scale variations when depression filling approaches are used and they do not incorporate localized soil texture controls on infiltration. We developed a new Dynamic Wetness Index (DWI) that attempts to account for the persistence of soil moisture over time at the microtopographic scale (~1 m2) by including inputs of measured soil texture, and information from the Dhara modeling framework that incorporates canopy process and surface-subsurface hydrologic models. DWI and TWI values were correlated with measured soil geochemical properties across six study sites (four agricultural sites, one restored prairie, and one forest site) within the Upper Sangamon River Basin, in central Illinois, USA. Relative to TWI, DWI improved correlations with certain measured soil surface geochemistry (pH R = −0.53), δ13C R = 0.13, δ15N R = 0.44) and certain lignin phenols (vanillyl, cinnamyl/vanillyl, syringyl-vanillyl-cinnamyl/substituted fatty acids). DWI positively correlated with indicators of lignin oxidation, indicating that wetter soils have higher potential for lignin decomposition. In this small dataset, relative to TWI the data show DWI increased significance and decreased the range of correlations with soil moisture and certain surface soil geochemistry parameters driving plant chemistry decay and nitrogen cycling.

Original languageEnglish (US)
Article number114239
JournalGeoderma
Volume368
DOIs
StatePublished - Jun 1 2020

Keywords

  • LiDAR
  • Microtopographic variability
  • Soil geochemistry
  • Soil moisture

ASJC Scopus subject areas

  • Soil Science

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    Li, M., Foster, E. J., Le, P. V. V., Yan, Q., Stumpf, A., Hou, T., Papanicolaou, A. N. T., Wacha, K. M., Wilson, C. G., Wang, J., Kumar, P., & Filley, T. (2020). A new dynamic wetness index (DWI) predicts soil moisture persistence and correlates with key indicators of surface soil geochemistry. Geoderma, 368, [114239]. https://doi.org/10.1016/j.geoderma.2020.114239