Geomorphometric characteristics of New Zealand landslide dams

Engineering Geology 73 (2004) 13 – 35 www.elsevier.com/locate/enggeo

Geomorphometric characteristics of New Zealand landslide dams Oliver Korup * School of Earth Sciences, Victoria University of Wellington, Cotton Bldg., Block A&B (P.O. Box 600), Wellington, New Zealand Received 10 April 2003; accepted 20 November 2003

Abstract This study presents results from a quantitative analysis of a new inventory of n = 232 landslide dam occurrences in New Zealand. Previously published data were expanded by documentation of recent events and evidence from a regional airphoto reconnaissance focused on the upland regions of southwestern South Island. Additional geomorphometric data on landslide dams, associated lakes, and contributing catchment characteristics, were extracted from a 25-m Digital Elevation Model (DEM), augmented by limited ground truthing, and compiled in a GIS-based inventory. The New Zealand case examples fall into the global trend, although they contain both two extremely large features in terms of landslide dam volume VD and lake volume VL. Analysis suggests that landslide dam height HD, landslide dam volume VD, lake volume VL, contributing catchment area AC, and local relief HR, are key variables for assessing landslide dam stability independently from other catchment parameters such as lithology, climate, or dam sedimentology. They may be provisionally used as representative characteristics of landslide dams, irrespective of environmental boundary conditions, such as climate, geology, or site-specific valley geomorphometry. Three newly proposed dimensionless indices, i.e., the Backstow Index Is, Basin Index Ia, and Relief Index Ir, based on landslide dam height HD allow limited, yet promising, preliminary assessments of landslide dam stability. Compared with worldwide examples, they also demonstrate a much narrower conditional range for the formation of stable landslide dams in New Zealand. Catchment parameters such as maximum elevation Emax, upstream relief HR, contributing catchment area AC, and relief ratio RR are significantly different at sites of former and existing landslide-dammed lakes, and may be used as independent variables in future terrain-based classification schemes. Generally, data are incomplete with underreporting of small and ephemeral landslide dams, and over-representation of earthquake case studies. Nonparametric correlation highlights the statistical interdependence between geomorphometric variables as an artefact of initial data calculation, while varying accuracy poses a significant drawback for complex multivariate statistical techniques such as principal component, cluster, or discriminant analyses. D 2004 Published by Elsevier B.V. Keywords: Landslide dam; Geomorphometry; New Zealand; Slope stability

1. Introduction * Present address: Swiss Federal Institute for Snow and Avalanche Research, Flu¨elastr. 11, CH-7260 Davos, Switzerland. Fax: +64-4-463-5186. E-mail address: [email protected] (O. Korup). 0013-7952/$ - see front matter D 2004 Published by Elsevier B.V. doi:10.1016/j.enggeo.2003.11.003

New Zealand is a country endowed with high endogenic and exogenic input, manifest in tectonic uplift and orographic precipitation, respectively, with

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a mean elevation of nearly 500 m a.s.l. Consequently, slope instability triggered by rainfall, snowmelt, and earthquakes is very often intimately coupled with basal stream channels, promoting landslide impacts on fluvial geomorphology. Landslide dams, i.e., the natural blockage of river channels by hillslope-derived mass movements (Costa and Schuster, 1988), are amongst the most obvious and widely recognised of such features in New Zealand. Perrin and Hancox (1992) have presented a list of 82 landslide-dammed lakes, while recent research on landslide dams has been reviewed by Korup (2002).

Landslide dams induce a range of significant geomorphic hazards, of which catastrophic outburst floods or debris flows following rapid dam failure bear the highest direct physical impact potential. One of the earliest historic accounts of a landslide dam-break flood has been described by Hegan et al. (2001) and IGNS (2003) for Waimatai Stream near Waihi Village at the shores of Lake Taupo (Fig. 1): Some years before 1846, a landslide occurred on the side of Kakaramea, the mountain [1300 m a.s.l.]

Fig. 1. Occurrence of n = 232 presently documented landslide-dammed lakes and former landslide dams in New Zealand. The spatial distribution pattern is largely a result of both underreporting of ephemeral events and emphasis on detailed regional studies on event (earthquake) response. Locations referred to in the text are indicated.

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above Waihi settlement at the southern end of Lake Taupo. The slide dammed a stream, forming a lake about 600 m above the Maori village of Te Rapa. On 7 May 1846, the landslide dam collapsed during heavy rain. The water and debris created a mudflow that overwhelmed the village, killing the Maori chief Te Heuheu and 63 members of his tribe (IGNS, 2003, p. 7). Depending on their longevity as well as stability, landslide barriers may create adverse long-term effects of backwater inundation and aggradation, promoting channel instability throughout both upstream and downstream reaches. This was recently exemplified by the formation and subsequent failure of a large rock-avalanche dam on the Poerua River, Westland (Hancox et al., 1999; Fig. 1). There, excessive sediment delivery from the eroding landslide deposit continues to be a long-term problem for pastoral land use and infrastructure along strongly aggrading and laterally unstable downstream reaches. Both the spatio-temporal upscaling effect of geomorphic impact and the fact that landslide dams often occur in multiple numbers in the wake of large-magnitude rainstorms or earthquakes (Hancox et al., 1997; Yetton et al., 1998) justify more detailed research on these complex geomorphic phenomena. The purpose of this study is to provide an overview of the present state of knowledge on landslide dams in New Zealand based on a recently expanded inventory. Methods of data acquisition and evaluation of information sources will be followed by a descriptive outline of landslide dam types, present status, trigger mechanisms, age, and their spatial distribution pattern. The focus will be on geomorphometric parameters of New Zealand landslide dams and their potential for 

quantifying driving and resisting forces with respect to landslide-induced river blockage;  representing environmental boundary conditions and variations of site-specific valley geomorphometry;  providing a quantitative basis for objective classification; and  assessing trends in the stability of landslide dams.

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2. Data acquisition Previously published accounts of landslide dams in New Zealand (e.g., Adams, 1981; Perrin and Hancox, 1992; Hancox et al., 1997) were starting points for the compilation of a nationwide inventory. New locations of landslide dams situated mainly in the remote mountainous terrain of Westland and Fiordland (Fig. 1) were inferred from a regionalscale reconnaissance of multi-temporal air photos at f 1:50,000 scale, analysis of a 25-m cell-size Digital Elevation Model (DEM), and selected ground truthing. Figures from several unpublished sources, such as university theses, project reports, newspaper clippings, as well as historic or anecdotal accounts, have further contributed to the inventory. Limitations of the spatio-temporal coverage of air photography have essentially precluded the identification of many short-lived landslide dams. Nevertheless, these findings have begun to fill a gap in documentation covering these regions, which provide ideal conditions for the formation of landslide dams, i.e., high relief and orographic rainfall, slope steepness, and episodic seismic activity (Fig. 2). As a general rule, quantitative information from many sources was found to be incomplete, inconsistent, or associated with prominent error margins. Accordingly, acquisition of accurate geomorphometric data for identified locations of landslide dams and their associated reservoirs remains a rather difficult task. In general, factors such as low longevity, rapid erosion, re-vegetation, or masking by water bodies or sediment, amalgamate to a considerable degree of uncertainty of correctly reconstructing the original area and volume of many landslide dams. Consequently, numerous sites of tentatively identified former landslide dams were excluded from this study. Morphostratigraphic evidence of former landslidedammed lakes, such as lacustrine silts (Whitehouse, 1983) is rarely documented. Yetton et al. (1998) have described a sequence of fine gravels topping a longrunout debris avalanche deposit, which was inferred to having temporarily blocked the Karangarua River, South Westland (Fig. 1). In several cases, conspicuous landform assemblages such as perched alluvial flats or swamps in otherwise mainly confined river reaches, in conjunction with subdued hummocky terrain and a clearly

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Fig. 2. Remnants of prehistoric rock-avalanche dam in the Otira Gorge, Westland. Ongoing instability of the landslide deposit has necessitated construction of a viaduct along the former dam-breach channel. (a) View upstream towards Arthur’s Pass and the remnants of the landslide dam (‘‘?’’ tentatively indicates former dam crest); (b) View from the old State Highway 93 (Zig-Zag) onto massive scree ramparts derived from the rock-avalanche deposit, which also supports the bridge pylons. River flow is from left to right (for location cf. Fig. 1).

defined landslide headscarp, were used as indicators of potential former stream blockage. In many of the valleys inspected, progradation of tributary debris fans has occluded trunk river channels and in some locations formed lakes. Since many of these features have resulted from a variety of additional geomorphic

processes other than landsliding (e.g., fluvial deposition, hyperconcentrated flow, sheetflow), the scale of this study has necessitated restriction to landslide dams sensu stricto. Identification, classification of landslides and dam types, and extraction of terrain parameters proves

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Fig. 3. The headwaters of Twin Fall Stream near Arthur’s Pass, Central Southern Alps (for location, cf. Fig. 1), depict the possibility of polygenetic natural dam formation. The small lake may initially have formed as a glacial tarn, yet was subsequently modified by rock fall/ avalanching during the 1929 Arthur’s Pass Earthquake (Hancox et al., 1997).

difficult in alpine headwaters particularly, where possible superposition of landslide debris on pre-existing cirque or moraine-impounded lakes may produce

polygenetic dams (Fig. 3). Multiple slope failures and associated landslide-dammed lakes may cluster along short river reaches and thus blur the distinctive-

Fig. 4. Shaded relief image of Lake McIvor near Lake Te Anau, Fiordland (cf. Fig. 1). Several deep-seated rotational rock-block slides (A, B, and C) have disrupted drainage the lower catchment, causing the formation of landslide-dammed Lake McIvor and several landslide ponds in a partly infilled toma landscape. Arrows indicate inferred main direction of mass movement and indicate the difficulty of accurately acquiring geomorphometric data on landslide dams.

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ness of individual geomorphometric dimensions, as is the case in the upper McIvor Burn, which drains into Lake Te Anau, Fiordland (Fig. 4). Extensive parts of the small basin (catchment area A f 18.5 km2) had been subject to valley side-wall collapse due to what has been interpreted as deep-seated complex, dominantly rotational, rock-block slide. The chaotic arrangement of tilted blocks within the landslide deposit has caused drainage obliteration along a 3-km reach, forming a partly infilled toma landscape. The large dam impounding Lake McIvor has an estimated minimum volume of f 1.1  108 m3 (‘‘A’’, Fig. 4), whereas the exact dimensions of the downstream deposits associated with several landslide ponds are difficult to delineate. Examples like this are common in Fiordland and highlight the difficulties of geomorphometric analysis arising from the complexity and potential superposition of glacial and mass-movement landforms.

Analysis of the vertical stratification of alluvial flats in alpine valley trains is another means of semiquantitatively identifying potential locations of landslide dams. The characteristic knickline between toe slopes and fluvial braidplains or terraces in high mountain valleys may be extracted from DEM-derived slope data. Following several tests, plots of the 9j-slope contour line were found useful to empirically distinguish the approximate extent of fluvial/alluvial low-gradient alpine valley fills (2j to 7j) from steeper mass movement-dominated valley sides (>9j) throughout alpine Westland and Fiordland (Fig. 5). This graphic method has been used to identify locations of significant breaks in the long profile of mountain rivers, such as bedrock gorges at tributary junctions of hanging valleys or active glacier snouts. The varying extent of this knickline in lower or midreaches of major trunk valleys suggests either structural channel constriction (bedrock gorges), or the

Fig. 5. Plot of the 9j slope contour line between the Waitaha and Moeraki Rivers, South Westland. This method is efficient in delineating the extent of large intramontane valley trains. Termination of this knickline in lower- or mid-reaches of major valleys implies a significant break in river long profile induced by either structural or glacial control (bedrock gorges, glacier snouts) or potential damming by landslides, moraine walls, or debris fans.

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downstream end of high-gradient spillways through natural dams or occlusions by landslides, moraine walls, or debris fans. The list of landslide dams tentatively identified by this technique, however, still requires careful cross-checking from air photography or ground truthing. A final problem associated with data compilation arises from the inconsistent use of terminology. It is often difficult to determine whether published data can be readily calibrated; in some cases, it remains unclear, whether the use of ‘‘landslide volume’’ refers to the landslide deposit in total or the landslide dam

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exclusively. The same applies to landslide dam ‘‘width’’ and ‘‘length’’, which should be used to quantify planform axes in an along- and cross-valley sense, respectively (Costa and Schuster, 1988). The attributes derived for this study were divided into three groups, which delineate the geomorphometry of the landslide dam, its associated natural reservoir (where applicable), and the contributing catchment area, respectively (A – C, Table 1). All available data in the digital database were compiled on a GIS-platform to facilitate extraction and analysis of terrain parameters as well as their spatial

Table 1 List of geomorphometric and other relevant parameters extracted for this study Geomorphometric parameter

Description

Main source

(A) Landslide dam Landslide dam height HD (m) Landslide dam length LD (m) Landslide dam width WD (m) Landslide dam volume VD (Mm3) Landslide type* Trigger mechanism* Age* Status*

Maximum crest height of landslide dam Maximum length of landslide dam (across valley) Maximum width of landslide dam (along valley) Approximate volume of landslide dam deposit Classification of landslide (Cruden and Varnes, 1996) Inferred causative agent of landslide dam formation Inferred date of landslide dam formation Presently observed state of landslide-dammed lake

25-m DEM (Profile extraction) Air photos, 25-m DEM Air photos, 25-m DEM 25-DEM Air photos Published data Published data Air photos, published data

Maximum length of landslide-dammed lake along medial axis Maximum width of landslide-dammed lake normal to length axis Area of landslide-dammed lake calculated from NZMS260 (1:50,000 scale) Perimeter of landslide-dammed lake calculated from NZMS260 (1:50,000 scale) Approximate volume of natural impoundment

NZMS260** (digital format)

(B) Landslide-dammed lake Lake length LL (m) Lake width WL (m) Lake area AL (km2) Lake perimeter PL (km) Lake volume VL (Mm3) (C) Upstream catchment Catchment area AC (km2) Maximum altitude Emax (m) Minimum altitude Emin (m) Relief HR (m) Relief ratio RR (mkm 2) Melton’s ruggedness number RM Modal slope umod (j)

Catchment area upstream of the point of stream blockage Highest elevation point in contributing catchment area Elevation of landslide dam (crest) Relief upstream of the point of blockage (HR = Emax [Emin Ratio of relief versus catchment area upstream of the point of blockage (RR = HRAC 1) Index of ruggedness of the basin upstream of the point of blockage (RM = HRAC 0.5; Melton, 1965) Dominant slope angle in catchment upstream of the point of blockage derived from slope angle histogram

NZMS260** (digital format) NZMS260** (digital format) NZMS260** (digital format) Published data

HD])

25-m 25-m 25-m 25-m 25-m

DEM (watershed) DEM DEM DEM DEM

25-m DEM 25-m DEM (SLOPE)

Terrain parameters can be grouped in terms of describing (A) the landslide dam, (B) its associated impoundment (if applicable), and (C) the catchment upstream of the point of blockage. * Additional information. ** New Zealand Map Series 260.

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distribution patterns. Subsequent data processing incorporated standard descriptive statistics, examination of bivariate plots, graphic envelope curves, computation of correlation coefficients, and cluster or discriminant analyses, with standard software packages.

3. Status of landslide dams, trigger mechanisms, and landslide types From a hazard management perspective, the most important attribute of a landslide dam is its stability, especially after it has ponded a water body of large volume. The term ‘‘stable’’ in relation to landslide dams has to be treated with caution, since it is not time-invariant. Seemingly stable landslide barriers were reported to fail years or even decades after their formation without any obvious relationship to their dam or reservoir dimensions (Fig. 6). Even a barrier that may satisfy basic geomechanical requirements such as internal cohesion or resistance to shear stress by the volume of the impounded water body, may be subject to failure by excess stress from earthquake-induced ground acceleration or landslide-induced displacement waves. In the New

Zealand environment, there is ample potential for such post-damming disturbances; however, several prehistoric landslide-dammed lakes such as Waikaremoana or Tutira (Fig. 1) have remained impounded for several millennia despite presumably multiple high-magnitude seismic events. The New Zealand landslide-dam inventory unfortunately does not provide much detailed information on dam longevity or times to failure. The persistence of a landslidedammed lake for >10 years, and usually several decades, has thus been used to assign the ‘‘stable’’ status class to a given landslide dam site (cf. Perrin and Hancox, 1992). Former landslide-dammed lakes that had been infilled were taken as an indication for a stable dam. Clearly, such simplification does not allow for scenarios involving partial dam failures, dam enlargement by secondary landsliding, or multiple outburst floods. The present inventory of n = 232 landslide dams includes 140 existing landslide-dammed lakes as well as seven landslide ponds, i.e., impoundments completely perched on top of landslide deposits (Figs. 7 and 8). The fact that only 37% of all landslide dams appear to have failed reflects an unknown degree of underreporting of ephemeral stream blockage. Of the 85 landslide dams that had formerly blocked lakes, 24

Fig. 6. Estimated volumes of landslide dams (n = 73) and related lakes (n = 77) versus the time to dam failure, based on selected worldwide examples. The large scatter in the plot suggests that neither the size of the landslide dam or dammed lake are useful predictors for the longevity of stream blockage. The dotted envelope curve may be helpful in roughly indicating a ‘‘minimum decision-making time’’ for a given landslide dam volume.

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Fig. 7. Present status of n = 232 landslide dams in relation to the observed state of impoundment.

have been breached and 10 backfilled; there is no information on the modes of failure of the remaining 51 sites. The sparse data on triggering mechanisms and types of landslides causing river blockage highlight the varying level of detail in documentation of the New Zealand inventory. For about 59% of the 232 landslide dams examined, the trigger mechanisms

remain unexplained; 28% were formed during earthquakes, whereas another 11% are classified as tentatively coseismic (Fig. 9a). Only 3% have formed in the wake of highintensity rainstorms, usually tropical cyclones; this figure is most likely an underestimate, since Cyclone Bola triggered at least 10 landslide dams in

Fig. 8. Landslide lake/pond on the upper Edwards River, at the lobate upstream fringe of a large rock avalanche from Falling Mountain triggered during the 1929 Arthur’s Pass earthquake. Although being retained by an large type III dam (Costa and Schuster, 1988), the pond is only seasonally filled with meltwater, and renders exact definition of landslide dam or lake ‘‘status’’ difficult. Note person at left of pond for scale.

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(a) Rainstorm 3%

Earthquake?

Other 3%

11%

Earthquake Unknown

28%

59% Rock-block

(b)

slide

Complex 5%

Other 2%

Unknown 34%

6% Rotational 8%

Rock fall, slide 9%

Debris flow 12%

Rock avalanche 27%

Fig. 9. (a) Trigger mechanisms; and (b) landslide types involved with the formation of n = 232 landslide dams in New Zealand.

1988 (M. Page, Landcare Research New Zealand, 2000). The remaining 3% were caused by fluvial undercutting, anthropogenic activity, or other less obvious mechanisms. In terms of the landslide types causing blockage (terminology follows Cruden and Varnes, 1996), 34% of the samples have remained unclassified as yet. Extremely rapid landslides involving rock ava-

lanching are the most common type and account for 27% of the data. Debris flows form 12%, rock falls and slides 9%, rotational failures 8%, rock-block slides 6%, and deep-seated complex failures 5% of the documented landslide dams; about 2% comprise various types of shallow landslides (Fig. 9b). Seventy-five percent of the current data were classified according to the scheme of Costa and Schuster

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(1988). The dominant types of blockage comprise Types II and III, i.e., landslide barriers encompassing the whole width of the valley floor (66%), or extending considerable distances beyond the entry point (15%), respectively. About 8% were separately classified as landslide-dammed lakes in headwater basins. These are commonly formed by large (>106 m3) landslides, and are considered to be transitional forms between landslide-dammed lakes and landslide ponds.

4. Spatial distribution pattern and age of formation The landslide dams presently documented in New Zealand are concentrated in a broad SW –NE trending axis, corresponding to the country’s major steepland areas. The spatial concentration of the nation’s largest landslide dams and related lakes (by either landslide dam or lake volume, VD or VL, respectively) is incoherent and situated in Fiordland as well as in parts of the East Cape region. The locations of other existing landslide-dammed lakes are conspicuously clustered in the Taranaki, East Cape, Northwest Nel-

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son, and Fiordland areas (Fig. 1). This clustering is mainly a documentary artefact, bearing a strong imprint of more detailed regional studies. For example, some 40 dams have formed synchronously by coseismic landsliding during the 1929 Murchison Earthquake in Northwest Nelson (Ms = 7.7, Hancox et al., 1997; Fig. 10). Fiordland hosts nearly 30% of all existing landslide-dammed lakes in New Zealand, which may be interpreted accordingly to reflect the possibility of coseismic formation. Although the distribution of existing landslide-dammed lakes in New Zealand coincides with zones of high seismic activity, concurrent trigger mechanisms such as high-intensity rainstorms, snowmelt, or fluvial undercutting, as well as variations in landslide susceptibility render this notion speculative. The oldest landslide dams in New Zealand are of Pleistocene age: Macfarlane and Roberts (2001) have attributed an age of 80 – 110 ka to the Rip Landslide in the Roxbourgh Gorge, which is believed to be a breached landslide barrier; Crawford (1994) has dated the formation of a landslidedammed polje in the Paparoa Limestone karst at Bullock Creek to at least 45 ka (Fig. 1). Nonethe-

Fig. 10. Cumulative distribution of absolute dates attributed to formation of landslide dams in New Zealand (n = 104). About 75% of all dated landslide dams fall into the 20th century, largely due to the effects of documented large earthquakes. Prehistoric dates appear to be relatively undersampled due to potential lack of preservation or lower average frequency of dam formation.

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less some 75% of all dated occurrences fall into the 20th century and are biased by the effects of large earthquakes and increasingly detailed historic documentation. Thus, care should be taken when implementing this observed spatial clustering of landslidedammed lakes for a proposed regional classification (e.g., Lowe and Green, 1987).

5. Geomorphometric properties Landslide dams were identified within an altitudinal spectrum between sea-level and 1370 m a.s.l. with a mean of f 470 m a.s.l., while they abound in areas of high relief (mean HR f 970 m) and slope angles (mean umod f 32j; Table 2). Many low-altitude impoundments occur in glacial troughs or infilled fjords near sea level in Fiordland particularly, whereas the majority of the South Island landslide dams is situated at elevations between 400 and 1000 m a.s.l., thus mirroring the topography of the Southern Alps and adjacent uplands. The remaining landslide dams in low-relief terrain ( < 500 m) are situated in the Tertiary soft-rock lithology of the Taranaki and East Cape regions of the North Island, where large complex deep-seated failures dominate.

The observation that large landslides impound small lakes mainly in tributary and headwater basins has been stated earlier (Adams, 1981; Perrin and Hancox, 1992) and is underlined by the fact that 88% of all landslide dams have a contributing catchment area AC < 100 km2. About 79% of those formed in small headwater basins (AC < 10 km2) have retained lakes, whereas 5% were infilled without a dam failure. These numbers may reflect low available discharge, surface roughness and armouring effects of dominantly coarse sediment, and thus low fluvial removal power in headwater catchments. New Zealand hosts some of the largest landslide dams and related lakes by worldwide comparison (Fig. 11). For example, Hancox and Perrin (1994) have described the extremely large (f 27 km3) Green Lake rock slide/avalanche, which has dammed and obliterated the mid-reaches of the Monowai River, Fiordland, some 13,000 years ago. The largest existing landslide-dammed lake in New Zealand, Lake Waikaremoana (VL f 5  109 m3), is used for hydropower generation, and has been investigated by Read et al. (1992) and Riley and Read (1992). Both locations coincide with zones of high neotectonic activity. Despite their extreme size, however, comparison of mean with median values of landslide dams

Table 2 Descriptive statistics of geomorphometric parameters of New Zealand landslide dams Geomorphometric parameter

Min

Max

Mean

S.E.*

Stdev**

Median

Landslide dam height HD (m) Landslide dam length LD (m) Landslide dam width WD (m) Landslide dam volume VD (Mm3) Lake length LL (m) Lake width WL (m) Lake area AL (km2) Lake perimeter PL (km) Lake volume VL (Mm3) Catchment area AC (km2) Altitude Emax (m) Altitude Emin (m) Relief HR (m)*** Relief ratio RR (mkm 2) Melton’s ruggedness number RM Modal slope umod (j)

5 50 100 0.04 60 20 0.0 0.1 0.01 0.2 210 0 141 1 0.03 11

800 2700 3700 27,000 18,300 11,740 49.9 104.7 5000 4491.8 3125 1370 2470 780 0.54 39

67 632 957 302.6 1263 410 0.8 3.4 72.9 123.5 1468 465 1101 96 0.25 32.2

9 70 95 229.6 174 86 0.3 0.7 57.5 38.4 44 21 50 1 0.01 0.7

97 492 698 2493.8 2104 1027 4.1 9.1 536.0 542.4 632 310 526 113 0.12 9.3

40 580 725 4.0 545 195 0.1 1.3 2.0 11.7 1540 424 1131 60 0.24 37.0

Note the high values in skewness and kurtosis, indicating log-normal distribution of some variables. * S.E. = Standard error of the mean. ** Stdev = Standard deviation. *** Corrected for landslide dam height; for calculation see Table 1.

Skew 4.68 2.10 1.97 10.67 4.93 9.71 11.40 9.88 9.25 7.02 0.23 0.52 0.35 3.01 0.36 1.90

Kurtosis

n

29.61 5.99 4.67 115.09 32.79 106.16 135.95 109.83 85.94 51.52 0.35 0.57 0.00 13.21 0.59 3.27

118 49 54 118 146 143 151 146 87 200 202 218 112 109 110 197

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Fig. 11. Bivariate plot of landslide-dammed lake volumes versus landslide dam volume derived from a worldwide data set (n = 184), highlighting occurrences in New Zealand, Japan, and the USA. Note the general scatter of New Zealand data.

and landslide-dammed lake dimensions indicates a strongly skewed data distribution (Table 3). The size of New Zealand landslide-dammed lakes tend to fall below the global average, as opposed to the geomorphometry of New Zealand landslide dams, which correspond well with the worldwide data. On a nationwide basis, at least 14 landslide dams have estimated volumes VD>108 m3, with nearly half of the measured sites exceeding VD = 106 m3. Dams with a crest height greater than HD = 100 m seem to occur in the Southern Alps predominantly, although some of the impoundments in the East Cape region easily compete in size. The ratio of landslide dam width to height WDHD 1 often provides a means of

distinguishing landslide dams from other natural barriers, such as moraine dams, in particular. On average, New Zealand landslide dams are about 20 times as wide as they are high (n = 40); correspondingly, the average slope angles of the dam face are rather low (4j < h < 5j), compared to those of moraine dams (Costa and Schuster, 1988).

6. Correlation of terrain parameters and the role of valley geomorphometry The high values of skewness and kurtosis suggest that most of the sampled geomorphometric parameters

Table 3 Comparison of geomorphometric variables of New Zealand landslide dams with a data set of worldwide examples compiled from different sources Geomorphometric parameter

Landslide dam height HD (m) Landslide dam length LD (m) Landslide dam width WD (m) Landslide dam volume VD (Mm3) Lake length LL (m) Lake area AL (km2) Lake volume VL (Mm3)

New Zealand

Worldwide

Mean

S.E.*

Median

n

Mean

S.E.*

Median

n

67 632 957 303 1263 0.8 73

9 70 95 230 174 0.3 58

40 580 725 4 545 0.1 2

118 49 54 118 146 151 87

74 521 1008 213 7858 143 199

10 66 175 50 1820 73 133

45 250 350 5 2100 49 2.5

148 131 127 144 121 12 129

New Zealand lake geomorphometry seems to deviate negatively from the global trend. * S.E. = Standard error of the mean.

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exhibit a skewed (log-normal) distribution (Table 2). Consequently nonparametric (Spearman-q) correlation coefficients were used to avoid log-transformation and inherent statistical bias of variables. Correlation coefficients for terrain parameters were grouped to characterise the geomorphic units of the landslide dam, landslide-dammed lake, and upstream catchment (Table 4). Within-groups correlation has been shaded grey to indicate the possibility of statistical replication of the original method of data computation. Landslide dam volume VD, for example, is commonly derived from the product of landslide dam planform area and average deposit thickness. The problem of accurate capture of the vertical dimension in landslide deposits is partly mirrored in a moderate correlation (q = 0.699; R2 = 0.49) of landslide dam height HD with landslide dam volume VD. In contrast, landslide length LD and width WD explain 76% and 74% of the variance of VD, respectively. This is not necessarily interpreted as an indication of an intrinsic physical relationship within the deposit geomorphometry. It rather appears a statistical legacy of the original method of data acquisition and computation conditioned by the more accurate extraction of planform dimen-

sions. The same applies to parameters of landslidedammed lake geomorphometry, where the correlation between lake area AL and volume VL produces a coefficient of q = 0.845 (R2 = 0.71). An independent sample of n = 113 landslide dams throughout the world confirms the high degree of dependence of dam volume VD on planform characteristics (WD and LD, Fig. 12). Despite these limitations envelope curves may be used to very crudely predict dimensional limitations (due to runout and deposit emplacement geometry) by graphic interpolation. The plotted data suggest that, for example, a 100-m-high landslide dam would require a landslide volume of at least in the order of 106 m3, regardless of the valley topography of the blockage site. Generally speaking, statistical relationships between groups of geomorphometric parameters are not very instructive and seem to be lowest between variables relating to the landslide dam and its upstream catchment. The most important observation is that landslide-dam volume VD and height HD are statistically independent of all upstream catchment variables, such as contributing area AC, relief HR, relief ratio RR, or ruggedness RM. Correlation between

Table 4 Matrix of Spearman-q correlation coefficients of geomorphometric parameters

Coefficients are grouped with reference to the landslide dam, landslide-dammed lake, and upstream catchment area. Correlation within groups (boxes shaded grey) are higher than between groups (non-shaded boxes) and partially indicate statistical artefacts of the original data acquisition process. For explanation of parameters, cf. Table 1. All correlation coefficients are statistically significant on the 0.01 level (two-tailed) with exception of values in italics; missing values have been excluded pairwise.

O. Korup / Engineering Geology 73 (2004) 13–35

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Fig. 12. Bivariate plot of landslide dam height, width, and length against landslide dam volume for a censored data set of n = 113 worldwide landslide dams. R2 values for planform variables landslide dam length LD and width WD are around 0.6, partly replicating the initial method of volume computation. Straight line depicts crude envelope curve for landslide dam height HD, which may be used to empirically predict dimensional constraints on stream blockage.

landslide dam volume VD and respective lake volume V L is moderate (q = 0.558; R 2 = 0.31); planform dimensions of the landslide dam appear to be marginally better predictors for assessing scaling relationships between barrier and impoundment, however, bearing in mind the problem of statistical replication. Theoretically, the site-specific valley geomorphometry should exert a major control on the dimensions of both landslide dam and the impounded lake. It is commonly argued that laterally confined valleys would favour landslide dam formation, since less volume VD would be required to produce a given dam height HD (Costa and Schuster, 1988). The generally steeper gradient in river gorges, however, also produces a shorter lake for a given landslide dam height on the premise of full reservoir capacity. Correlation between the length of the landslidedammed lake LL (approximating the length scale or ‘‘magnitude’’ of backwater effects) and contributing catchment area AC is moderate (q = 0.642; R2 = 0.41), indicating several additional influences within the long-profile such as mean (reach-scale) gradient. Obviously, the problem of differentiating the effects of on-site valley geomorphometry may not be readily solved with simple bivariate plots. Moreover, the pre-

landslide topography of valley-floors is often unknown and thus difficult to quantify in terms of cross-sectional area or shape factors. The errors of estimating landslide dam height would thus propagate into the calculation of local valley geomorphometry.

7. Prediction potential for landslide dam stability Recent studies have shown that geomorphometric parameters are not only suitable for describing, but also quantitatively predicting or assessing the stability of landslide dams. Casagli and Ermini (1999) have proposed a Blockage Index Ib = log(VDAC 1) and an Impoundment Index Ii = log(VDVL 1), where VD and VL are volumes of landslide dam and impoundment [in m3], respectively, and AC is catchment area upstream of the blockage [in km2]. Both indices are useful in graphically delineating ‘‘domains’’ of dam stability from geomorphometric parameters. Adaptation of this method by grouping landslide dams by their status (Table 1) produces a data pattern similar to that from the Apennines, Italy (Casagli and Ermini, 1999), although index values differ markedly (Fig. 13).

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O. Korup / Engineering Geology 73 (2004) 13–35

Fig. 13. Bivariate plots of landslide dam parameters and graphic envelope curves for (a) the Blockage Index Ib; and (b) Impoundment Index Ii (Casagli and Ermini, 1999), based on available data from New Zealand landslide-dammed lakes. Critical index values (envelope curves) are based on graphic interpretation of empirical data solely and do not explain any physical relationships between the respective variables. Data outliers are discussed in the text.

The graphic envelope representing the Blockage Index Ib depicts that generally no landslide-dammed lakes formed below Ib = 2, whereas unstable lakes

form at I b < 4. Impoundments with I b >7 have remained stable and are classified as existing; the remaining ‘‘midfield’’ contains the majority of cases

O. Korup / Engineering Geology 73 (2004) 13–35

and hence a large degree of uncertainty (Fig. 13a). This lower limit for stable landslide dams is significantly higher than that in the Apennines (Ib>5; Casagli and Ermini, 1999). In other words, the impounding volume VD needs to be a hundred times higher to create a stable reservoir for a given catchment area AC. An Impoundment Index of Ii = 1 appears to be a good criterion in differentiating stable from unstable landslide dams: Sites where Ii>1 have retained existing lakes, whereas locations with Ii < 1 comprise both stable and unstable landslide dams (Fig. 13b). In contrast to the Apennine examples, a stable landslide dam in New Zealand would require a tenfold dam volume VD for a given lake volume VL. Use of a dimensionless Blockage Index Ib = log(VDAC 1HD 1), where HD is height of the landslide barrier (Ermini and Casagli, 2002) [in m], yields similar results with IbV = 5 (3.25) and IbV = 3 (2.92) delimiting the lower threshold ratio for stable, and the upper threshold for unstable dams, respectively (bracketed values refer to n = 83 worldwide sites examined by Ermini and Casagli, 2002; Fig. 14). From a geomorphometric perspective, the formation of stable landslide dams in New Zealand appears to be more closely constrained than that of the global average, requiring relatively higher landslide volumes for a given reservoir size. The plots

29

show four interesting data outliers, i.e., Lakes Perrine and Garribaldi, and two tiny backwater ‘‘pools’’, all of which are located in the Northwest Nelson region (Fig. 1). Lake Perrine had been created on the Mokihinui River during the 1929 Murchison Earthquake. The present river reach is dominated by an elongated pool rather than a lake, resulting from a partial drop in lake level (Adams, 1981), a feature that is common with several former landslide dams. Similarly, Lake Garribaldi, also known as ‘‘Earthquake Lakes’’, and two other small ponds on Six Mile Stream, are backwater pools rather than actual lakes, although they were treated as ‘‘existing lakes’’. Generally speaking, the New Zealand sample displays a spectrum roughly similar to that of the Italian data set, yet encompass at least three additional orders of magnitude, resulting in different critical values for the proposed indices. The Blockage Index Ib in particular appears to be a good approach to simulating a ratio between ‘‘removing’’ and ‘‘resisting’’ forces: The former are aptly represented by contributing catchment area AC, which in many New Zealand drainage basins is used as a proxy for discharge (McKerchar and Pearson, 1989), whereas VD reflects the magnitude of the geomorphic barrier. Although stream power X is given preference as a more integrative parameter in

Fig. 14. Bivariate plot of the ratio of landslide dam volume VD to crest height HD versus contributing catchment area AC and envelope curve depicting the dimensionless Impoundment Index IbV proposed by Ermini and Casagli (2002). Data outliers are discussed in the text.

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O. Korup / Engineering Geology 73 (2004) 13–35

Fig. 15. Bivariate plots and envelope curves of three proposed dimensionless indices of landslide dam stability, based on dam crest height HD; (a) Backstow Index Is, (b) Basin Index Ia, and (c) Relief Index Ir. Definitions and data outliers are discussed in the text.

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modelling stream erosion (e.g., Gallant and Wilson, 2000; Sklar and Dietrich, 1998), its application for landslide dams is only of limited suitability, since formation of a natural reservoir triggers a timevariant increase in local base level and ensuing loss of gradient, which propagates upstream as the lake expands by infilling. Three new dimensionless indices are suggested here, all of which employ landslide dam height HD of the New Zealand data set. The ‘‘Backstow Index’’ is defined as Is = log(HD3VL 1), where HD is the maximum crest height of the landslide dam in [m] (Fig. 15a). Values of Is < 3 and Is>0 delimit unstable and stable landslide dam domains, respectively, whereas data between these envelopes remain inconclusive. Similarly, the ‘‘Basin Index’’ Ia = log(HD2AC 1) can be used to delineate stable lakes with values of Ia>3 (Fig. 15b). Finally, the ‘‘Relief Index’’ Ir = log(HDHR 1), where HR is the relief upstream of the point of blockage [in m], may be used to discern stable from unstable lakes at a ‘‘critical’’ value of Ir = 1 (Fig. 15c). All plots of these dimensionless indices feature the former ‘‘Lake Graham’’ landslide dam as an outlier, which may be a result of a crude overestimate of the dam height of HD = 170 m. In general, care should be taken when using these graphic envelopes for predicting landslide dam stability. The relatively low separation performance ( < 35%) highlights their simplistic nature (Table 5). The Impoundment Index Ii and Relief Index Ir achieve the best results by correctly assigning 34.5% and 32.4% of existing landslide dams to the stable domain, respectively. The choice of index will in many cases also be determined by available data. Despite these obvious limitations, the method provides a convenient means for rapid first-order estimates of landslide-dam stability not only for future occurrences, but also regional comparison. The empirical nature of this approach further implies that so-called ‘‘critical’’ values of stability indices will essentially be subject to ongoing modification by increasing data availability. In addition to this mere graphical interpretation, discriminant analyses were carried out to more objectively quantify any divergence in the geomorphometry between stable ( = existing) and unstable ( = former) landslide dams. The resulting discriminant functions

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Table 5 Separation performance of graphical envelope curves when used for distinction of discrete domains of landslide dam stability Index

Blockage Blockage* Impoundment Backstow Basin Relief

‘Critical’ value

Ib Ib IbV IbV Ii Is Is Ia Ir

7 4 5 3 1 0 3 3 1

Percent of landslide dams Existing

Former

21.7 – 20.0 – 34.5 13.0 – 20.3 32.4

– 7.8 – 22.9 – – 20.7 – –

Percentages refer to the total number of landslide dams in each respective stability domain which are correctly allocated by stability-index envelope curves defined by ‘‘critical’’ values (cf. Figs. 13 and 14). * Dimensionless.

do not perform well with either the original or logtransformed variables and achieve only poor quality: the best test result, in which 69% of the landslide dams were classified correctly by standardised discriminant coefficients, was considered to be insignificantly different from an arbitrary 50% – 50% classification.

8. Potential for classification The viability of employing all geomorphometric parameters as a base for quantitatively classifying landslide dams is seriously impeded by the fact that only 19 sites (i.e., 8% of the total data set) have a complete range of documented geomorphometric parameters. Furthermore a quantitative classification would ideally necessitate variables that are statistically independent of each other; this requirement cannot be met on the grounds of the existing correlation coefficient matrix (Table 4). The variable accuracy and partial deficiency of data impedes the reasonable use of more sophisticated statistical procedures such as partial correlation or cluster analyses. Comparison of geomorphometric parameters of the landslide dams is somewhat problematic, since reconstructed dimensions in the ‘‘former lake’’ group might include underestimates derived from partly eroded dams. It is also reasonable to expect that data from failed dams or drained

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O. Korup / Engineering Geology 73 (2004) 13–35

reservoirs might be obtained on a different level of accuracy compared to sites of existing landslidedammed lakes. Keeping these reservations in mind, dimensions of both landslide dams and impoundments seem to be inferior for former lakes to those of their existing counterparts. Nonparametric tests (Mann – Whitney U, Kruskal – Wallis H) using the present status of the landslide-dammed lake, i.e., simplified to either ‘‘existing lake’’ or ‘‘former lake, unspecified’’ (failure mechanism), as a grouping variable,

were used to check whether these inferred differences are statistically significant (Table 6). Parameter values of the contributing drainage basin exhibits marked discrepancy with regard to the landslide dam status. Locations of former landslidedammed lakes are characterised by significantly higher values in maximum altitude Emax, relief HR, upstream catchment area AC, and correspondingly lower values of relief ratio RR and ruggedness RM. Based on their independence in computation and

Table 6 Nonparametric test results for differentiating geomorphometric data from existing and failed landslide dams throughout New Zealand Ranks

HD

LD

WD

VD

VL

Emin

Emax

HR

AC

RR

RM

umod

Test statistics

Status

n

Existing Failed Total Existing Failed Total Existing Failed Total Existing Failed Total Existing Failed Total Existing Failed Total Existing Failed Total Existing Failed Total Existing Failed Total Existing Failed Total Existing Failed Total Existing Failed Total

78 34 112 28 13 41 29 13 42 73 41 114 61 24 85 135 63 198 135 63 198 135 63 198 133 63 196 133 63 196 133 63 196 133 63 196

Mean rank

Rank sum

59.11 50.51

4610.5 1717.5

22.86 17

640 221

23.45 17.15

680 223

62.51 48.57

4563.5 1991.5

41.48 46.85

2530.5 1124.5

97.34 104.13

13,141 6560

82.77 135.36

11,173.5 8527.5

82.08 136.83

11,080.5 8620.5

82.91 131.41

11,027 8279

111.39 71.29

14,815 4491

103.67 87.59

13,788 5518

91.87 112.5

12,218.5 7087.5

Mann – Whitney U

Wilcoxon W

Z

Asymptotic significance (two-tailed)

1123

1718

1.291

0.197

130

221

1.458

0.145

132

223

1.538

0.124

1131

1992

2.162

0.031

640

2531

0.903

0.366

3961

13,141

0.776

0.438

1994

11,174

6.015

0.000

1901

11,081

6.263

0.000

2116

11,027

5.591

0.000

2475

4491

4.623

0.000

3502

5518

1.854

0.064

3308

12,219

2.408

0.016

Statistically significant differences at a level < 0.001 are highlighted in bold.

O. Korup / Engineering Geology 73 (2004) 13–35

statistical correlation, these catchment variables might be appropriate indicators of altitudinal stratification of landslide dams in headwater, mid- and lower reach locations, respectively.

9. Discussion The formation and failure of landslide dams are common, yet undersampled and poorly understood process sequences of geomorphic channel – hillslope coupling not only in New Zealand, but also in many mountain ranges throughout the world (Costa and Schuster, 1991). The range of their dimensions is exemplified by occurrences of very large landslide dams, which have retained lakes in both Fiordland and parts of the East Cape region. Analysis of geomorphometric parameters suggests that landslide dam height HD, landslide dam volume VD, lake volume VL, upstream catchment area AC, and relief HR upstream of the point of blockage are key variables for assessing landslide dam stability. Best results are achieved by stratifying variables according to discrete geomorphic units, i.e., the landslide barrier, landslidedammed lake, and contributing catchment area. Geomorphometric dimensions of landslide dams were found to be statistically independent from any terrain parameters of their respective upstream catchments (Table 4). Correlation between landslide dam and lake variables is moderate apart from where statistical relationships might replicate computation of initial data acquisition and computation. This inherent statistical interdependence impedes more sophisticated quantitative analysis. It is suggested that contributing catchment area AC as a proxy for discharge and hydraulic head (fluvial removal power) be a prime control on the long-term stability of landslide dams. Likewise, landslide dam height HD can be employed in a series of dimensionless indices that provide firstorder indications of general quantitative scaling relationships for stable and unstable dams (Fig. 16). One interesting implication of this geomorphometric approach is that the potential control of other catchment characteristics such as lithology, climate, seismicity, or vegetation cover is ruled out. The same applies for landslide type, velocity, or the dam sedimentology, for which it is reasonable to assume to produce much of the scatter in the plots observed. The major advantage

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of the geomorphometric approach thus lies in its simplicity and scope for regional comparison. Evaluation of the Impoundment Index Ii and Blockage Index Ib displays much narrower geomorphometric conditions for the formation of stable landslide dams in New Zealand in terms of the required landslide dam volume VD. The prevailing high rates of tectonic uplift and surface erosion during earthquakes and highintensity rainstorms may be limiting factors to the longevity of landslide dams (Adams, 1981; Yetton et al., 1998) and thus promote the failure of smaller dams in New Zealand. The empirical character of the approach however limits such notions. Although the varying data quality and accuracy is adequately dealt with within a graphical approach on an order-ofmagnitude scale, the problem of underreporting remains. The geomorphometric analysis undertaken in this study also cannot account for any morphodynamic changes such as multiple dam-break floods, partial dam failure, or gradual infilling and thus reduction of lake size (Costa and Schuster, 1991). Furthermore should site-specific assessments of landslide dam stability always be based on detailed geotechnical investigations.

10. Conclusion A first attempt to use geomorphometric parameters for characterising landslide dams in New Zealand has been presented. Similar to landslide-dam inventories in other parts of the world (e.g., Costa and Schuster, 1991; Casagli and Ermini, 1999), incompleteness and varying accuracy of data render the use of multivariate analyses for meaningful differentiation, classification, or stability prediction problematic. It has been shown that the seemingly inhomogeneous geomorphometric data may be more sensitive to graphical analyses than nonparametric correlation, which is bound to statistically replicate methods of initial data acquisition and calculation. Three new dimensionless bivariate indices, i.e., the Backstow Index Is, the Basin Index Ia, and the Relief Index Ir, based on landslide dam height HD, as well as landslide-dammed lake volume VD, contributing area AC, and upstream relief HR, respectively, provide means to graphically derive critical thresholds for the formation of persistent

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O. Korup / Engineering Geology 73 (2004) 13–35

landslide dams. Although generally < 35% of the data points were allocated correctly, the index-based graphical approach allows first-order estimates of landslide dam stability and regional comparison of geomorphometric boundary conditions necessary for landslide dam formation and failure. Nevertheless, catchment parameters such as such as maximum elevation Emax, upstream relief HR, contributing catchment area AC, or relief ratio RR show significant differences for sites of former and existing landslide-dammed lakes. With increasing data availability and GIS-based geospatial extrapolation capability, the scope for future research lies within the formulation of regional susceptibility models of landslide-driven stream blockage based on these catchment parameters. The value of such an approach lies not so much in the accurate prediction of landslide dam longevity at a given site, but rather in indicating general tendency for stable landslide dams to form within a given region or catchment. This is aptly demonstrated in the much narrower conditional range for the formation of stable landslide dams in New Zealand, when compared with data from other parts of the world.

Acknowledgements The author would like to thank Nick Perrin and Grant Dellow at IGNS Gracefield, Lower Hutt, for use of relevant New Zealand landslide data. Professor Michael Crozier kindly supplied material on landslide dams in the Taranaki region, while discussions with Dr. Robert Schuster, U.S. Geological Survey, Denver/ Colorado, helped to put this work into a worldwide perspective. The comments of two anonymous reviewers are greatly appreciated.

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