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

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.

Evaluating digital terrain indices for soil wetness mapping – a Swedish case study

“…Here, we used Tarboton's D∞ method (Tarboton, 1997) since Sørensen et al (2006 ) showed that this method gave the best results for predicting soil wetness. Which particular T WI numbers indicate wet soils, however, vary by landscape, climate, and scale (Zinko et al, 2005;Western et al, 1999;Grabs et al, 2009;Günt-ner et al, 2004).…”

“…Some of the more complex multi-directional flow algorithms minimise divergence where unrealistic, and give a more natural representation of flows along ridges, pits, and flats. When used in combination with DEM-derived slope layers, any of the above algorithms can be used to develop soil wetness indices such as the topographic wetness index (T WI ; Tarboton, 1997), the topographic position index (TPI; Weiss, 2001), and the cartographic depth-to-water (D TW , Murphy et al, 2007), with T WI and D TW proving useful for mapping soil (type, drainage, chemical, and physical properties), soil trafficability, and species-or community-based vegetation distributions (Murphy et al, 2011;Zinko et al, 2006;Sørensen et al, 2006;Kuglerova et al, 2014). In this regard, some of the above flow-accumulation algorithms perform better than others.…”

“…In this regard, some of the above flow-accumulation algorithms perform better than others. For example, Kopecky and Cizkova (2010) preferred FD8 for vegetation mapping, while Sørensen et al (2006) concluded that using D∞ improved soil wetness mapping. Murphy et al (2009Murphy et al ( , 2011 found that T WI -based wetness maps improved from D8 to D∞, and these improvements were scale dependent, while D TW maps showed better and fairly scale-independent correlations for various soil properties, including soil and vegetation type and drainage class.…”

A review of the (Revised) Universal Soil Loss Equation (R/USLE): with a view to increasing its global applicability and improving soil loss estimates

“…Topography has a large influence on the spatial aspects watershed hydrology through its effects on soil moisture distribution and flow (Sørensen et al, 2006). In the USLE, the topography is accounted for in the LS-factor which is a function of slope 25 length and steepness, which affects the rate of soil erosion due to water (Wischmeier & Mannering, 1968).…”

Combination of statistical and physically based methods to assess shallow slide susceptibility at the basin scale

“…This index is heavily dependent on the scale (Piacentini et al, 2015), and the neighbourhood radius of 25 m proved to be the most appropriate for the index calculation at the work reference scale. The slope over area ratio was used to express the importance of the topography in hydrological processes through the relationship between the slope and the contribution area (Sørensen et al, 2006), which allows us to infer the areas prone to surface saturation (Fonseca, 2005). The calculation of the SOAR was made using the TauDEM 5.2 (Terrain Analysis Using Digital Elevation Models) tool and the algorithm D8 (O'Callagham and Mark, 1984) to minimize the dispersion of accumulation flow.…”