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Frontiers of Earth Science

Front. Earth Sci.    2015, Vol. 9 Issue (2) : 165-178     DOI: 10.1007/s11707-014-0485-0
Development of a GIS-based failure investigation system for highway soil slopes
Raghav RAMANATHAN1,Ahmet H. AYDILEK2,*(),Burak F. TANYU3
1. Paul C. Rizzo Associates, Inc., 500 Penn Center Blvd., Pittsburgh PA 15235, USA
2. Department of Civil and Environmental Engineering, University of Maryland, MD 20742, USA
3. Department of Civil, Environmental and Infrastructure Engineering, George Mason University, Fairfax VA 22030, USA
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A framework for preparation of an early warning system was developed for Maryland, using a GIS database and a collective overlay of maps that highlight highway slopes susceptible to soil slides or slope failures in advance through spatial and statistical analysis. Data for existing soil slope failures was collected from geotechnical reports and field visits. A total of 48 slope failures were recorded and analyzed. Six factors, including event precipitation, geological formation, land cover, slope history, slope angle, and elevation were considered to affect highway soil slope stability. The observed trends indicate that precipitation and poor surface or subsurface drainage conditions are principal factors causing slope failures. 96% of the failed slopes have an open drainage section. A majority of the failed slopes lie in regions with relatively high event precipitation (P>200 mm). 90% of the existing failures are surficial erosion type failures, and only 1 out of the 42 slope failures is deep rotational type failure. More than half of the analyzed slope failures have occurred in regions having low density land cover. 46% of failures are on slopes with slope angles between 20° and 30°. Influx of more data relating to failed slopes should give rise to more trends, and thus the developed slope management system will aid the state highway engineers in prudential budget allocation and prioritizing different remediation projects based on the literature reviewed on the principles, concepts, techniques, and methodology for slope instability evaluation (Leshchinsky et al., 2015).

Keywords soil slope      slope management system      geographic information system      hazard mapping     
Corresponding Authors: Ahmet H. AYDILEK   
Just Accepted Date: 03 December 2014   Online First Date: 28 January 2015    Issue Date: 30 April 2015
 Cite this article:   
Raghav RAMANATHAN,Ahmet H. AYDILEK,Burak F. TANYU. Development of a GIS-based failure investigation system for highway soil slopes[J]. Front. Earth Sci., 2015, 9(2): 165-178.
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Fig.1  The study area with elevations and locations of slope failures.
Fig.2  A generalized geological map of the State of Maryland (Source: Maryland Geological Survey,
Fig.3  Distribution of failures in the different subcategories of (a) elevation and (b) slope angle.
Fig.4  The failure distribution pattern for the different storm events (a) 2 year 24 h duration, and (b) 100 year 24 h duration.
Fig.5  The distribution of slope failures for different classes of (a) land covers, and (b) failure type.
Failure type Failure type sub- classification
Rotational failure—Circular Deep
Rotational failure—Noncircular Deep Shallow
Translational failure Block Slide
Others Landslide Flow Spread
Erosion Head Toe Flank Body
Tab.1  Proposed failure type classification used in the current study (after Cruden and Varnes, 1996)
Fig.6  Slope failure distribution patterns for different (a) slope types, and (b) slope drainage section type.
Fig.7  The slope failure distribution patterns for different (a) physiographic provinces, and (b) lithology or soil type.
Fig.8  Schematic of the mapping system used in the current study. The system uses the qualitative index overlay model with a raster output.
Factor Subclass Area ratio Failure density index Normalized index
Slope angle/(°) <10 89.4 0.2083 0.4545
10–20 8.7 0.3125 0.6818
20–30 1.6 0.4583 1.0000
30–40 0.3 0.0208 0.0455
>40 0.0 0.0000 0.0000
Land cover (based on NLCD classification) Grass 13.9 0.5625 1.0000
Shrubs 1.6 0.0417 0.0741
Woodland 31.8 0.0625 0.1111
Developed land 2.5 0.2292 0.4074
Cultivated land 30.4 0.0208 0.0370
Other: Wetlands, Barren 19.7 0.0833 0.1481
Elevation/m <10 27.7 0.1250 0.2222
10–30 18.9 0.2292 0.4074
30–90 14.2 0.5625 1.0000
90–270 28.2 0.0833 0.1481
>270 9.4 0.0000 0.0000
Physiographic province (Maryland Geological Survey) Appalachian Plateaus Province 7.4 0.0000 0.0000
Ridge and Valley Province 6.7 0.0000 0.0000
Piedmont Plateau Province 26.3 0.1667 0.2000
Blue Ridge Province 2.9 0.0000 0.0000
Atlantic Coastal Plain Province 56.6 0.8333 1.0000
Storm event precipitation- 2 year recurrence, 6 hrs. duration/mm <56 26 0.0000 0.0000
56–58 17 0.6250 1.0000
58–60 27 0.2500 0.4000
60–62 17 0.0000 0.0000
>62 13 0.1250 0.2000
Storm event precipitation- 100 year recurrence, 6 hrs. duration/mm <135 30 0.0000 0.0000
135–140 34 0.7292 1.0000
140–145 13 0.1458 0.2000
145–150 19 0.1250 0.1714
>150 5 0.0000 0.0000
Tab.2  Physical parameters classified into sub-categories along with the density and normalized indices for each sub categories
Fig.9  Variation of the failure density index and normalized failure density for the subclasses of parameters (a) slope angle and (b) storm event precipitation (100 yr, 24 h).
Fig.10  Variation of failure density indices for the different parameter subclasses over the area of the study region.
Factor Map 1 Map 2 Map 3 Map 4
Slope angle 1 3 1 3
Land cover 1 3 1 3
Elevation 1 1 1 1
Physiographic provinces 1 2 1 2
Storm event precipitation – 2 yr recurrence 24 h duration 1 3 0 0
Storm event precipitation- 100 yr recurrence 24 h duration 0 0 1 3
Slope failure history 1 2 1 2
Tab.3  The weightage scheme assumed for the different test maps
Fig.11  Failure density maps generated by layers and weights provided in Table 2. (a) Follows weighing scheme – Map 1 (b) follows weighing scheme – Map 2 (c) follows weighing scheme – Map 3 (d) follows weighing scheme – Map 4.
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