On the calculation of the topographic wetness index: evaluation of different methods based on field observations
TLDR
In this article, the authors 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.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.read more
Citations
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Soil organic carbon storage as a key function of soils - A review of drivers and indicators at various scales
Martin Wiesmeier,Livia Urbanski,Eleanor Hobley,Birgit Lang,Margit von Lützow,Erika Marin-Spiotta,Bas van Wesemael,Eva Rabot,Mareike Ließ,Noelia Garcia-Franco,Ute Wollschläger,Hans-Jörg Vogel,Ingrid Kögel-Knabner +12 more
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Flood hazard risk assessment model based on random forest
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Height Above the Nearest Drainage – a hydrologically relevant new terrain model
Antonio Donato Nobre,Antonio Donato Nobre,Luz Adriana Cuartas,Martin G. Hodnett,Camilo Daleles Rennó,George Rodrigues,André Luiz Lopes da Silveira,M.J. Waterloo,Scott R. Saleska +8 more
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Digital mapping of soil organic matter stocks using Random Forest modeling in a semi-arid steppe ecosystem
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Effects of DEM resolution on the calculation of topographical indices: TWI and its components
TL;DR: In this paper, a high-resolution digital elevation model (DEM) with a 5m grid size derived from LIDAR (light detection and ranging) data was used to investigate the scale-dependency of TWI values when converting from high resolution elevation data to standard-resolution DEMs.
References
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A physically based, variable contributing area model of basin hydrology
Mike Kirkby,Keith Beven +1 more
TL;DR: In this paper, a hydrological forecasting model is presented that attempts to combine the important distributed effects of channel network topology and dynamic contributing areas with the advantages of simple lumped parameter basin models.
Journal ArticleDOI
Digital terrain modelling: A review of hydrological, geomorphological, and biological applications
TL;DR: In this article, the authors describe elevation data sources, digital elevation model structures, and the analysis of digital elevation data for hydrological, geomorphological, and biological applications.
Journal ArticleDOI
A new method for the determination of flow directions and upslope areas in grid digital elevation models
TL;DR: In this paper, a new procedure for the representation of flow directions and calculation of upslope areas using rectangular grid digital elevation models is presented, based on representing flow direction as a single angle taken as the steepest downward slope on the eight triangular facets centered at each grid point.
Journal ArticleDOI
The prediction of hillslope flow paths for distributed hydrological modelling using digital terrain models
TL;DR: In this paper, the authors examined some of the problems of deriving flow pathways from raster digital terrain data in the context of hydrological predictions using TOPMODEL and proposed a strategy for the case where downslope subsurface flow pathways may deviate from those indicated by the surface topography.
Journal ArticleDOI
The in(a/tan/β) index:how to calculate it and how to use it within the topmodel framework
Paul Quinn,Keith Beven,Rob Lamb +2 more
TL;DR: In this paper, a number of digital terrain analysis (DTA) methods are described for use in calculating the TOPMODEL topographic index, ln(a/tan beta) (a = upslope contributing area per unit contour; tan beta = local slope angle).
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