TY - JOUR
T1 - The identification of debris torrent basins using morphometric measures derived within a GIS
AU - Rowbotham, David
AU - De Scally, Fes
AU - Louis, John
N1 - Imported on 12 Apr 2017 - DigiTool details were: Journal title (773t) = Geografiska Annaler. Series A. Physical Geography. ISSNs: 0435-3676;
PY - 2005
Y1 - 2005
N2 - The identification of drainage basins susceptible to debris torrents has advanced in a somewhat ad hoc fashion with a variety of morphometric measures being employed. This study reports on a systematic and automated approach using morphometric measures derived from a digital elevation model (DEM), namely the first and second deravitives of elevation, slope gradient, slope aspect, profile curvature, plan curvature and mean curvature. Descriptive statistics such as the mean, standard deviation, skewness and kurtosis are calculated within a geographic information system (GIS) and used to describe the frequency distribution of the morphometric measures within each basin. For comparison purposes, morphometric measures previously employed to identify debris torrent basins, such as Melton's basin ruggedness R, basin area, and an elevation-relief ratio, are also included in the GIS database. Logistic regression and discriminant analyses indicate that the standard deviations of slope gradient and slope aspect are the strongest predictors of the variables tested. In comparison, Melton's R and basin area, although proving to be significant predictors and thereby supporting previous studies, are shown to be weaker than the two strongest DEM-derived variables. The results suggest that important morphometric indicators of debris torrent activity can be derived from DEMs, thus providing a systematic basis for future research into the identification of debris torrent basins.
AB - The identification of drainage basins susceptible to debris torrents has advanced in a somewhat ad hoc fashion with a variety of morphometric measures being employed. This study reports on a systematic and automated approach using morphometric measures derived from a digital elevation model (DEM), namely the first and second deravitives of elevation, slope gradient, slope aspect, profile curvature, plan curvature and mean curvature. Descriptive statistics such as the mean, standard deviation, skewness and kurtosis are calculated within a geographic information system (GIS) and used to describe the frequency distribution of the morphometric measures within each basin. For comparison purposes, morphometric measures previously employed to identify debris torrent basins, such as Melton's basin ruggedness R, basin area, and an elevation-relief ratio, are also included in the GIS database. Logistic regression and discriminant analyses indicate that the standard deviations of slope gradient and slope aspect are the strongest predictors of the variables tested. In comparison, Melton's R and basin area, although proving to be significant predictors and thereby supporting previous studies, are shown to be weaker than the two strongest DEM-derived variables. The results suggest that important morphometric indicators of debris torrent activity can be derived from DEMs, thus providing a systematic basis for future research into the identification of debris torrent basins.
U2 - 10.1111/j.0435-3676.2005.00276.x
DO - 10.1111/j.0435-3676.2005.00276.x
M3 - Article
SN - 0435-3676
VL - 87
SP - 527
EP - 537
JO - Geografiska Annaler, Series A: Physical Geography
JF - Geografiska Annaler, Series A: Physical Geography
IS - 4
ER -