A comparison of wetness indices for the prediction of observed connected saturated areas under contrasting conditions |
| |
| Authors: | Geneviève Ali Christian Birkel Doerthe Tetzlaff Chris Soulsby Jeffrey J McDonnell Paolo Tarolli |
| |
| Institution: | 1. Department of Geological Sciences, University of Manitoba, Manitoba, Canada;2. Northern Rivers Institute, School of Geosciences, University of Aberdeen, Aberdeen, UK;3. Global Institute for Water Security, University of Saskatchewan, Saskatchewan, Canada;4. Department of Land, Environment, Agriculture and Forestry, University of Padova, Padova, Italy |
| |
| Abstract: | For lack of other widely available spatial information, topography is often used to predict water fluxes and water quality in mesoscale watersheds. Such data have however proven to be misleading in many environments where large and flat valley bottoms and/or highly conducive soil covers determine water storage and water transport mechanisms. Also, the focus is generally on the prediction of saturation areas regardless of whether they are connected to the catchment hydrographic network or rather present in isolated topographic depressions. Here soil information was coupled with terrain data towards the targeted prediction of connected saturated areas. The focus was on the 30 km2 Girnock catchment (Cairngorm Mountains, northeast Scotland) and its 3 km2 sub‐catchment, Bruntland Burn in which seven field surveys were done to capture actual maps of connected saturated areas in both dry and humid conditions. The 1 km2 resolution UK Hydrology of Soil Types (HOST) classification was used to extract relevant, spatially variable, soil parameters. Results show that connected saturated areas were fairly well predicted by wetness indices but only in wet conditions when they covered more than 30% of the whole catchment area. Geomorphic indices including information on terrain shape, steepness, aspect, soil texture and soil depth showed potential but generally performed poorly. Indices based on soil and topographic data did not have more predictive power than those based on topographic information only: this was attributed to the coarse resolution of the HOST classification. Nevertheless, analyses provided interesting insights into the scale‐dependent water storage and transport mechanisms in both study catchments. Copyright © 2013 John Wiley & Sons, Ltd. |
| |
| Keywords: | wetness indices observed saturation areas connectivity stream network data resolution |
|
|
