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

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... 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. Riihimäki, Kemppinen, Kopecký & Luoto (2021). Data from: Topographic Wetness Index as a proxy for soil moisture: the importance of flow-routing algorithm and grid resolution. Zenodo.