Regional debris flow susceptibility analysis in mountainous peri-urban areas through morphometric and land cover indicators

2020 ◽  
pp. 9-40
Author(s):  
María Carolina Rogelis Prada
Keyword(s):  
Land Cover ◽  
Debris Flow ◽  
Urban Areas ◽  
Susceptibility Analysis ◽  
Debris Flow Susceptibility

scholarly journals Regional debris flow susceptibility analysis in mountainous peri-urban areas through morphometric and land cover indicators

2014 ◽  
Vol 14 (11) ◽  
pp. 3043-3064 ◽  
Author(s):  
M. C. Rogelis ◽  
M. Werner
Keyword(s):  
Land Cover ◽  
Debris Flow ◽  
Flood Risk ◽  
Urban Areas ◽  
Debris Flows ◽  
Flood Hazard ◽  
Flow Direction ◽  
Hazard Analysis ◽  
Principal Component ◽  
Debris Flow Susceptibility

Abstract. A method for assessing regional debris flow susceptibility at the watershed scale, based on an index composed of a morphometric indicator and a land cover indicator, is proposed and applied in 106 peri-urban mountainous watersheds in Bogotá, Colombia. The indicator of debris flow susceptibility is obtained from readily available information common to most peri-urban mountainous areas and can be used to prioritise watersheds that can subsequently be subjected to detailed hazard analysis. Susceptibility is considered to increase with flashiness and the possibility of debris flows occurring. Morphological variables recognised in the literature to significantly influence flashiness and occurrence of debris flows are used to construct the morphometric indicator by applying principal component analysis. Subsequently, this indicator is compared with the results of debris flow propagation to assess its capacity in identifying the morphological conditions of a watershed that make it able to transport debris flows. Propagation of debris flows was carried out using the Modified Single Flow Direction algorithm, following identification of source areas by applying thresholds identified in the slope–area curve of the watersheds. Results show that the morphometric variables can be grouped into four indicators: size, shape, hypsometry and (potential) energy, with energy being the component that best explains the capability of a watershed to transport debris flows. However, the morphometric indicator was found to not sufficiently explain the records of past floods in the study area. Combining the morphometric indicator with land cover indicators improved the agreement and provided a more reliable assessment of debris flow susceptibility in the study area. The analysis shows that, even if morphometric parameters identify a high disposition to the occurrence of debris flow, improving land cover can reduce the susceptibility. However, if favourable morphometric conditions are present but deterioration of the land cover in the watershed takes place, then the susceptibility to debris flow events increases. The indicator of debris flow susceptibility is useful in the identification of flood type, which is a crucial step in flood risk assessment especially in mountainous environments, and it can be used as input for prioritisation of flood risk management strategies at regional level and for the prioritisation and identification of detailed flood hazard analysis. The indicator is regional in scope, and therefore it is not intended to constitute a detailed assessment but to highlight watersheds that could potentially be more susceptible to damaging floods than others in the same region.

scholarly journals Debris-flow susceptibility assessment through cellular automata modeling: an example from 15–16 December 1999 disaster at Cervinara and San Martino Valle Caudina (Campania, southern Italy)

2003 ◽  
Vol 3 (5) ◽  
pp. 457-468 ◽  
Author(s):  
G. Iovine ◽  
S. Di Gregorio ◽  
V. Lupiano
Keyword(s):  
Cellular Automata ◽  
Debris Flow ◽  
Urban Areas ◽  
Debris Flows ◽  
Soil Cover ◽  
Southern Italy ◽  
Landslide Risk ◽  
Campania Region ◽  
Optimal Values ◽  
Debris Flow Susceptibility

Abstract. On 15–16 December 1999, heavy rainfall severely stroke Campania region (southern Italy), triggering numerous debris flows on the slopes of the San Martino Valle Caudina-Cervinara area. Soil slips originated within the weathered volcaniclastic mantle of soil cover overlying the carbonate skeleton of the massif. Debris slides turned into fast flowing mixtures of matrix and large blocks, downslope eroding the soil cover and increasing their original volume. At the base of the slopes, debris flows impacted on the urban areas, causing victims and severe destruction (Vittori et al., 2000). Starting from a recent study on landslide risk conditions in Campania, carried out by the Regional Authority (PAI –Hydrogeological setting plan, in press), an evaluation of the debris-flow susceptibility has been performed for selected areas of the above mentioned villages. According to that study, such zones would be in fact characterised by the highest risk levels within the administrative boundaries of the same villages ("HR-zones"). Our susceptibility analysis has been performed by applying SCIDDICA S3–hex – a hexagonal Cellular Automata model (von Neumann, 1966), specifically developed for simulating the spatial evolution of debris flows (Iovine et al., 2002). In order to apply the model to a given study area, detailed topographic data and a map of the erodable soil cover overlying the bedrock of the massif must be provided (as input matrices); moreover, extent and location of landslide source must also be given. Real landslides, selected among those triggered on winter 1999, have first been utilised for calibrating SCIDDICA S3–hex and for defining "optimal" values for parameters. Calibration has been carried out with a GIS tool, by quantitatively comparing simulations with actual cases: optimal values correspond to best simulations. Through geological evaluations, source locations of new phenomena have then been hypothesised within the HR-zones. Initial volume for these new cases has been estimated by considering the actual statistics of the 1999 landslides. Finally, by merging the results of simulations, a deterministic susceptibility zonation of the considered area has been obtained. In this paper, aiming at illustrating the potential for debris-flow hazard analyses of the model SCIDDICA S3–hex, a methodological example of susceptibility zonation of the Vallicelle HR-zone is presented.

Impact of spatial data uncertainty in global debris flow susceptibility analysis

2021 ◽  
Author(s):  
Laurie Kurilla ◽  
Giandomenico Fubelli
Keyword(s):  
Debris Flow ◽  
Spatial Data ◽  
Debris Flows ◽  
Predisposing Factors ◽  
Susceptibility Analysis ◽  
Factors Associated ◽  
Event Location ◽  
The Impact ◽  
Debris Flow Susceptibility

<p>There are many types and degrees of uncertainty associated with spatial data and processes. </p><p>There are many factors and attributes associated with debris flow analyses which are prone to uncertainty.  For simplicity, in this presentation, only two attributes of debris flow events are investigated along with the impact of their uncertainty on the determination of environmental predisposing factors.    These two attributes, critical to debris flow susceptibility analyses, are landslide classification and event location.  The associated predisposing factors studied herein are lithology, soils, climate, ecophysiographic units, topography, hydrology, and tectonics.</p><p>In a landslide susceptibility analysis, landslide event location accuracy is paramount yet often inaccurately known.  Landslide inventories are often constructed based on mapping from aerial imagery, media reports, and field work by third party sources; and in a data-driven approach to debris flow susceptibility analysis the landslide type is important in modeling the relevant predisposing factors distinctive to each landslide type. </p><p>In a study of global debris flow susceptibility an analysis of the impact between known location and a location accuracy offset, and landslide categorization uncertainty demonstrates the impact of uncertainty in defining the appropriate predisposing factors associated with debris flows.</p><p>This analysis is part of a larger debris flow global susceptibility determination which trains on known debris flow events and the predisposing factors associated with them to identify potential areas that may be susceptible to debris flows.  This study looks at the impact/differences that mis-categorization or location uncertainty have on the determination of predisposing factors, along with methods of conveying uncertainty information. </p>

AN EVALUATION OF POST-WILDFIRE DEBRIS FLOW SUSCEPTIBILITY AND HAZARD MODELS

2016 ◽  
Author(s):  
Jordan Carey ◽  
◽  
Nicholas Pinter ◽  
Andrew L. Nichols
Keyword(s):  
Debris Flow ◽  
Hazard Models ◽  
Debris Flow Susceptibility

scholarly journals Spatial-Temporal Land Use and Land Cover Changes in Urban Areas Using Remote Sensing Images and GIS Analysis: The Case Study of Opole, Poland

Geosciences ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 312
Author(s):  
Barbara Wiatkowska ◽  
Janusz Słodczyk ◽  
Aleksandra Stokowska
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Satellite Imagery ◽  
Urban Areas ◽  
Agricultural Land ◽  
Urban Expansion ◽  
Landsat 8 ◽  
Rate Of Increase ◽  
Management Procedures

Urban expansion is a dynamic and complex phenomenon, often involving adverse changes in land use and land cover (LULC). This paper uses satellite imagery from Landsat-5 TM, Landsat-8 OLI, Sentinel-2 MSI, and GIS technology to analyse LULC changes in 2000, 2005, 2010, 2015, and 2020. The research was carried out in Opole, the capital of the Opole Agglomeration (south-western Poland). Maps produced from supervised spectral classification of remote sensing data revealed that in 20 years, built-up areas have increased about 40%, mainly at the expense of agricultural land. Detection of changes in the spatial pattern of LULC showed that the highest average rate of increase in built-up areas occurred in the zone 3–6 km (11.7%) and above 6 km (10.4%) from the centre of Opole. The analysis of the increase of built-up land in relation to the decreasing population (SDG 11.3.1) has confirmed the ongoing process of demographic suburbanisation. The paper shows that satellite imagery and GIS can be a valuable tool for local authorities and planners to monitor the scale of urbanisation processes for the purpose of adapting space management procedures to the changing environment.

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