On the calculation of the topographic wetness index: evaluation of different methods based on field observations

TLDR

The topographic wetness index (TWI) quantifies topographic control on hydrological processes by combining upslope contributing area and slope, but its calculation methods vary mainly in how the contributing area is determined. This study compared multiple TWI calculation methods and evaluated them against measured variables such as vascular plant species richness, soil pH, groundwater level, soil moisture, and a constructed wetness degree. The authors computed TWI across all combinations of six parameters affecting accumulated area distribution and slope calculation for two boreal forest sites in northern Sweden. No single calculation method performed best for all variables; instead, the optimal method varied by variable and site, and the study identified general characteristics guiding method selection for species richness, soil pH, groundwater level, and soil moisture. Abstract.

Abstract

Abstract. The topographic wetness index (TWI, ln(a/tanβ)), which combines local upslope contributing area and slope, is commonly used to quantify topographic control on hydrological processes. Methods of computing this index differ primarily in the way the upslope contributing area is calculated. In this study we compared a number of calculation methods for TWI and evaluated them in terms of their correlation with the following measured variables: vascular plant species richness, soil pH, groundwater level, soil moisture, and a constructed wetness degree. The TWI was calculated by varying six parameters affecting the distribution of accumulated area among downslope cells and by varying the way the slope was calculated. All possible combinations of these parameters were calculated for two separate boreal forest sites in northern Sweden. We did not find a calculation method that performed best for all measured variables; rather the best methods seemed to be variable and site specific. However, we were able to identify some general characteristics of the best methods for different groups of measured variables. The results provide guiding principles for choosing the best method for estimating species richness, soil pH, groundwater level, and soil moisture by the TWI derived from digital elevation models.