Riihimäki, H., Kemppinen, J., Kopecký, M., & Luoto, M. (2021). Topographic Wetness Index as a proxy for soil moisture: The importance of flow-routing algorithm and grid resolution. Water Resources Research, 57, e2021WR029871. https://doi.org/10.1029/2021WR029871
Topographic wetness index as a proxy for soil moisture : the importance of flow-routing algorithm and grid resolution
|Author:||Riihimäki, H.1; Kemppinen, J.2; Kopecký, M.3,4;|
1Department of Geosciences and Geography, University of Helsinki, Helsinki, Finland
2Geography Research Unit, University of Oulu, Oulu, Finland
3Institute of Botany of the Czech Academy of Sciences, Průhonice, Czech Republic
4Faculty of Forestry and Wood Sciences, Czech University of Life Sciences Prague, Prague, Czech Republic
|Online Access:||PDF Full Text (PDF, 11.7 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2021120258574
American Geophysical Union,
|Publish Date:|| 2022-04-11
The Topographic Wetness Index (TWI) is a commonly used proxy for soil moisture. The predictive capability of TWI is influenced by the flow-routing algorithm and the resolution of the Digital Elevation Model (DEM) that TWI is derived from. Here, we examine the predictive capability of TWI using 11 flow-routing algorithms at DEM resolutions 1–30 m. We analyze the relationship between TWI and field-quantified soil moisture using statistical modeling methods and 5,200 study plots with over 46 000 soil moisture measurements. In addition, we test the sensitivity of the flow-routing algorithms against vertical height errors in DEM at different resolutions. The results reveal that the overall predictive capability of TWI was modest. The highest r² (23.7%) was reached using a multiple-flow-direction algorithm at 2 m resolution. In addition, the test of sensitivity against height errors revealed that the multiple-flow-direction algorithms were also more robust against DEM errors than single-flow-direction algorithms. The results provide field-evidence indicating that at its best TWI is a modest proxy for soil moisture and its predictive capability is influenced by the flow-routing algorithm and DEM resolution. Thus, we encourage careful evaluation of algorithms and resolutions when using TWI as a proxy for soil moisture.
Water resources research
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
H. Riihimäki and J. Kemppinen were funded by the Doctoral Programme in Geosciences at the University of Helsinki. J. Kemppinen was also funded by the Arctic Interactions at the University of Oulu and Academy of Finland (project 318930, Profi 4). M. Kopecký was funded by the Czech Academy of Sciences (project RVO 67985939). The field research was funded by the Academy of Finland (project 286950).
|Academy of Finland Grant Number:||
318930 (Academy of Finland Funding decision)
© 2021. American Geophysical Union.