Data from: Topographic Wetness Index as a proxy for soil moisture: the importance of flow-routing algorithm and grid resolution

• Main Authors: Riihimäki, Henri, Kemppinen, Julia, Kopecký, Martin, Luoto, Miska
• Other Authors: Lammi, Panu, Määttänen, Aino-Maija, Niittynen, Pekka, Niskanen, Annina, Toikka, Akseli
• Format: Other/Unknown Material
• Language: unknown
• Published: Zenodo 2021
• Subjects: Soil moisture; Topographic Wetness Index; Digital Elevation Model; Light Detection and Ranging; Flow-routing algorithm; Grid resolution; Arctic; Riihimäki
• Online Access: https://doi.org/10.5281/zenodo.4590184

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 modelling methods and 5200 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. Riihimäki, Kemppinen, Kopecký & Luoto (Preprint). Topographic Wetness Index as a proxy for soil moisture: the importance of flow-routing algorithm and grid resolution. Zenodo. These are the data from Riihimäki & Kemppinen et al. (Preprint). HR and JK were funded by the Doctoral Programme in Geosciences at the University of Helsinki. JK was also funded by the Arctic Interactions at the University of Oulu and Academy of Finland (project 318930, Profi 4). MK was funded by the Czech Academy of Sciences (project RVO 67985939). The field research was funded by the Academy of Finland (project 286950).