The identification of debris torrent basins using morphometric measures derived within a GIS

David Rowbotham, Fes De Scally, John Louis

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

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.
Original languageEnglish
Pages (from-to)527-537
Number of pages11
JournalGeografiska Annaler, Series A: Physical Geography
Volume87
Issue number4
DOIs
Publication statusPublished - 2005

Fingerprint

torrent
information system
frequency distribution
descriptive statistics
basin
curvature
digital elevation model
logistics
regression
skewness
drainage basin
geographic information system
relief

Cite this

Rowbotham, David ; De Scally, Fes ; Louis, John. / The identification of debris torrent basins using morphometric measures derived within a GIS. In: Geografiska Annaler, Series A: Physical Geography. 2005 ; Vol. 87, No. 4. pp. 527-537.
@article{8d989f8637254663ac8e34399fb3e67f,
title = "The identification of debris torrent basins using morphometric measures derived within a GIS",
abstract = "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.",
author = "David Rowbotham and {De Scally}, Fes and John Louis",
note = "Imported on 12 Apr 2017 - DigiTool details were: Journal title (773t) = Geografiska Annaler. Series A. Physical Geography. ISSNs: 0435-3676;",
year = "2005",
doi = "10.1111/j.0435-3676.2005.00276.x",
language = "English",
volume = "87",
pages = "527--537",
journal = "Geografiska Annaler, Series A: Physical Geography",
issn = "0435-3676",
publisher = "Wiley-Blackwell",
number = "4",

}

The identification of debris torrent basins using morphometric measures derived within a GIS. / Rowbotham, David; De Scally, Fes; Louis, John.

In: Geografiska Annaler, Series A: Physical Geography, Vol. 87, No. 4, 2005, p. 527-537.

Research output: Contribution to journalArticle

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

VL - 87

SP - 527

EP - 537

JO - Geografiska Annaler, Series A: Physical Geography

JF - Geografiska Annaler, Series A: Physical Geography

SN - 0435-3676

IS - 4

ER -