spatio-temporal changes in river bank mass failures in the lockyer valley, queensland, australia

Geomorphology 191 (2013) 129–141

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Geomorphology

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Spatio-temporal changes in river bank mass failures in the Lockyer Valley,Queensland, Australia

Chris Thompson a,b,⁎, Jacky Croke b, James Grove c, Giri Khanal d

a Centre for Integrated Catchment Assessment and Management (ICAM), Australian National University, ACT 0200, Australiab Australian Rivers Institute, Griffith University, Nathan Campus, Queensland 4111, Australiac Department of Resource Management and Geography, University of Melbourne, VIC 3010, Australiad Department of Environment and Resource Management, Land Centre, Woolloongabba, Queensland 4102, Australia

⁎ Corresponding author at: Centre for Integrated Catchme(ICAM), Australian National University, ACT 0200, Australia

E-mail address: [email protected]

0169-555X/$ – see front matter © 2013 Elsevier B.V. Alhttp://dx.doi.org/10.1016/j.geomorph.2013.03.010

a b s t r a c t
a r t i c l e i n f o
Article history:Received 31 December 2012Received in revised form 31 January 2013Accepted 12 March 2013Available online 20 March 2013

Keywords:Bank erosionMass failuresExfiltrationWet flowsMultitemporal LiDAR

Wet-flow river bank failure processes are poorly understood relative to themore commonly studied processes offluvial entrainment and gravity-inducedmass failures. Using high resolution topographic data (LiDAR) and nearcoincident aerial photography, this study documents the downstream distribution of river bank mass failureswhich occurred as a result of a catastrophic flood in the Lockyer Valley in January 2011. In addition, this distribu-tion is compared with wet flow mass failure features from previous large floods. The downstream analysis ofthese two temporal data sets indicated that they occur across a range of river lengths, catchment areas, bankheights and angles and do not appear to be scale-dependent or spatially restricted to certain downstreamzones. The downstream trends of each bank failure distribution show limited spatial overlap with only 17% ofwet flows common to both distributions. The modification of these features during the catastrophic flood ofJanuary 2011 also indicated that such features tend to form at some ‘optimum’ shape and show limited evidenceof subsequent enlargement even when flow and energy conditions within the banks and channel were high.Elevation changes indicate that such features show evidence for infilling during subsequent floods. The preser-vation of these features in the landscape for a period of at least 150 years suggests that the seepage processesdominant in their initial formation appear to have limited role in their continuing enlargement over time. No ev-idence of gully extension or headwall retreat is evident. It is estimated that at least 12 inundation events wouldbe required to fill these failures based on the average net elevation change recorded for the 2011 event. Existingconceptualmodels of downstreambank erosion process zonesmay need to consider awider array ofmass failureprocesses to accommodate for wet flow failures.

© 2013 Elsevier B.V. All rights reserved.

1. Introduction

Understanding the mechanisms and rates of bank erosion isparamount to the successful management of aquatic ecosystemsand off-shore environments, especially as numerous studies nowpoint to bank erosion as the dominant contributor to issues ofwater quality and river degradation (Grimshaw and Lewin, 1980;Prosser et al., 2001; Simon et al., 2002). However, in spite of therecognition of its importance, there remain surprisingly few studiesof downstream changes in bank erosion processes and rates withinindividual basins to enable effective quantification of the timingand spatial distribution of sediment delivery (Lawler et al., 1999).At the basin scalemost studies are derived from analysis of cartographic

nt Assessment andManagement.(C. Thompson).

l rights reserved.

sources and aerial photographs (Lewin, 1977; Gilvear et al., 2000;Winterbottom and Gilvear, 2000; Kemp, 2004).

The availability of high resolution topographic data provided byLight-Detection And Ranging (LiDAR), combined with aerial photogra-phy, has opened up the possibility of more accurate mapping of bankerosion volumes and processes (Bowen and Waltermire, 2002; Joneset al., 2007; Marcus and Fonstad, 2008). Grove et al. (2013) used thistechnology to classify bank forms along 100 km of the Lockyer Valleysoutheast Queensland (SEQ) to estimate the relative contribution ofboth fluvial entrainment and mass failure processes during a cata-strophic flood in 2011. This study highlighted that whilst the individualprocesses of sub-aerial, fluvial entrainment and mass failure bank ero-sion have been well-studied (Thorne, 1982; Lawler, 1992, 1993;Abernethy and Rutherfurd, 1998; Couper and Maddock, 2001; Rinaldiand Darby, 2007), wet flow failures are poorly understood withinexisting conceptual models. In addition, there is limited understandingof the effect of local, at-a-site properties on their formation and how theform of these features changes in response to subsequent flood eventsover time. As the dominantmechanism for their formation is flow seep-age from near-saturated banks (Grove et al., 2013), existing theories

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130 C. Thompson et al. / Geomorphology 191 (2013) 129–141

and conceptual models may be inappropriate in explaining their down-streamdistribution and the forces acting to change their formover time.

Existing concepts used to quantify fluvial entrainment estimatesof bank erosion have focused primarily on principles of force and re-sistance, where force is commonly measured using some expressionof energy or shear stress and resistance is reflected in variations tobank material properties and vegetation. Mass failure processes aremore spatially discrete, and are believed to be triggered by many fac-tors such as pore water pressure, matrix-suction (Simon et al., 2002;Rinaldi et al., 2004) seepage forces (Rinaldi and Darby, 2007), ante-cedent soil moisture condition (Hooke, 1979) and the force of gravity(Thorne, 1993). In general, mass failures are thought to occur as theshear strength of the soil is exceeded by the weight of the overlyingmaterial when the hydraulic conductivity (Ks) of the river sedimentlimits drainage so that water table cannot lower at the same rate asthe river stage (Dapporto et al., 2003). The timing, and potential, offailure have traditionally been quantified using the factor of safety(Fs) (Parker et al., 2008). Cohesive riverbanks have low Ks and theability to reach greater heights than other sediments, and so it hasbeen assumed that mass failure processes will be effective onlywhen a bank reaches a critical height (Thorne, 1982; Lawler, 1995).The application of these models to wet-flow failures has yet to befully investigated.

Conceptual understanding of riverbank erosion at the basin scale(Lawler, 1992, 1995; Lawler et al., 1999) tends to support the existenceof a generalised trend of sub aerial processes dominating the headwaterreaches, fluvial processes in mid-basin reaches (Graf, 1982; Lawler,1995) and mass failure processes in the downstream reaches (Lawleret al., 1999). These processes are, however, not mutually exclusiveand interactions occur between the different process types (Darby etal., 2007; Rinaldi and Darby, 2007). The extent to which any of theseconceptual models applies to wet-flowmass failure processes is largelyuntested in river systems.

This study seeks to advance our understanding of wet-flow massfailure features by addressing three specific aims. Firstly, this paperaims to compare the 2011 spatial distribution of mass failures asreported in Grove et al. (2013) with the distribution of pre-existingmass failures. Secondly, the paper will investigate the role of local,at-a-site bank and hydraulic parameters in explaining the downstreamdistribution of these features. Thirdly, this studywill investigate tempo-ral modification of these features by comparing net changes in bankform and volume between the two time periods.

2. Study area

2.1. Regional setting

The Lockyer Valley lies inland from Brisbane and extends to theGreat Dividing Range which marks the catchment divide from theMurray–Darling Basin (Fig. 1). The Lockyer catchment drains nearly3000 km2 of prime agricultural land in southeast Queensland(SEQ). SEQ is a subtropical region with mean maximum monthlytemperatures ranging between 21 and 29 °C. The total annual rain-fall ranges between 900 and 1800 mm, with the majority falling dur-ing the warm summer season (October to February). The region ischaracterised by seasonally variable patterns of floods and droughtswhich have been linked to the inter-annual rainfall variations of theEl Nino-Southern Oscillation (ENSO) and the Inter-decadal PacificOscillation (IPO) (Kiem et al., 2003; Rustomji et al., 2009).

2.2. Lockyer Creek catchment

The upper reaches of Lockyer Creek, known as Murphy's Creekflow east over Jurassic Marburg sandstones before becoming bedrockconfined within the older Helidon sandstone with a mean channelbed slope of 0.006 m m−1. Downstream of the confined reaches,

channel gradient reduces to 0.0008 m m−1 as the river flows backover the Marburg sandstones and discharges onto the unconfined al-luvial plain around Helidon, where the present low-flow channel isinset within a large ‘macrochannel’ (~150 m wide and 20 m deep)containing within-channel benches. In the lower part of the catch-ment where valley floor width is extensive (2–13 km), channel plan-form alternates between low sinuosity reaches and tight meanderingbends which have incised into the Marburg sandstone. Some alluvialcutoffs are preserved but there is little topographical evidence of re-cent lateral migration of the river in the form of remnant scroll barsor extensive point-bar development. Levees are also notable featureswith floodplain surfaces sloping steeply away from the present chan-nel (Fig. 1D).

Early settlement commenced in the 1840s in the Lockyer Valleywith approximately half of the native vegetation in the region nowcleared, the majority of this occurring between 1840s–1940s(Galbraith, 2009). The clearing mainly focused on the lower half ofthe valley across its broad alluvial plains whilst the steep upper catch-ment remained largely uncleared (Galbraith, 2009). The density andpreservation of riparian vegetation adjacent to the macrochannelare variable with the majority of bank tops largely devoid of woodedvegetation as cropping land extends to the channel boundary.

2.3. Flood history

The January 2011 event is ranked as the second highest flood inthe past 100 years, after 1974 (Bureau of Meteorology, 2011). Majorflood events have also been documented in the Brisbane River inthe 1840s, 1890s, 1974 and 2011 (Table 1; Babister and Retallick,2011). Hydrological records are scarce during the 1800s, howeverhistorical documents and local newspapers refer back to the ‘greatflood’ of 1893 and the more recent flood of 1974 flood as the onlyother major events prior to the 2011 flood. The flood in the 1840s islikely to have coincided with first settlement in the region andwould have encountered pre-European vegetation along the channel.Riparian vegetation is likely to have been largely intact within themacrochannel at the time of the 1893 floods.

3. Methods

This study is concerned with the spatial and temporal distributionsof riverbank mass failure features both as a result of the January 2011flood and pre-existing floods. The primary data sources for themappingof these features were a combination of LiDAR and near-coincidenthigh-resolution aerial photography which were available for two timeperiods; pre-flood (2010) and immediately after the January 2011flood. Based on the combined extent of LiDAR coverage and post-floodhigh resolution air photos, 71 km of stream length extending fromjust above the township of Murphy's Creek to below Gatton (Fig. 1B,C) was selected for analysis.

High-resolution DEMs of both time periods were constructed withtriangular irregular network (TINs) using Delaunay triangulation.Error and uncertainty in both DEM surfaces were investigated andaccounted for using procedures outlined in Croke et al. (2013).

3.1. Mass failure identification

A polygon layer was created of mass failures by tracing around theheadwall on the 2011 aerial imagery, guided by the >35° slope layerderived from the LiDARDEM to define the 2011post-floodmass failures(Fig. 2). The steep slope was used to aid the visual interpretation oferoding surfaces where there was canopy cover, and the 35° thresholdchosen is coincident with values of eroding banks reported byDapporto et al. (2003). The delineation of polygons was undertaken ata scale of 1:400, as this was considered the optimum level to avoid pix-ilation but maintain detail. During this mapping phase, detailed notes

Gatton

A

B

C

D

Gatton

Brisbane

Helidon

Murphy’s Creek

Fig. 1. Lockyer Creek catchment in southeast Australia (inset), showing post-flood high resolution aerial photo coverage area and extents of 2010 and 2011 LiDAR coverage used toderive DEMs. Lines A and B represent two cross sections from the mid Lockyer Creek.

131C. Thompson et al. / Geomorphology 191 (2013) 129–141

were taken on failure form and process, notably the planform shape ofthe failure extent and themorphology of the failure floor. The presence,size, and position of failed blocks or resting material on the failure floorwere used to infer processes. As LiDARdoes not penetratewater, amaskwas placed over the inner channel and these data points were excludedfrom the analysis. The extent of erosion of the mass failure polygonsinto the channel was often limited by the water mask layer, whichformed the lower boundary of the failure polygon.

The planform shape of the digitised polygon and the surface ofthe failure floor were used to classify three main types of failures

based on the criteria summarised in Table 2 and as outlined inGrove et al. (2013). Additional attributes such as bank height, angleand floodplain width were also extracted from a cross-section whichpassed through the polygon centroid to the opposite bank and flood-plain. In addition a nearest neighbour (channel distance to next massfailure), either upstream or downstream was extracted within ArcGIS.

This approach was also used to map the distribution and attributesof the pre-existing mass failures from the pre-flood LiDAR DEM andaerial imagery (Fig. 3A, B). Although the resolution of the featureswas not as distinct as the post-flood features, the form of the failure

Table 1Major floods measured on the Lower Brisbane River (Port Office Gauge) unadjusted forriver changes and dam construction.

Flood year Flood height (AHD)† River changes affecting flood heights

1841 8.43 None1844 7.02 None1890 5.33 River mouth sand bar removed in 1864 &

ongoing river dredging for navigationcommenced

‡1893 5February

8.35 Ongoing dredging

19 February 8.09 Ongoing dredging1898 5.02 Ongoing dredging to 1940s‡1974 5.45 Flood mitigation works including river

widening commenced 1930s andSomerset dam built in 1940s

‡2011 4.27 Wivenhoe Dam built in 1980s

† River heights are unadjusted for river changes.‡ Floods recorded in local newspapers impacting the Lockyer Valley.


headwall was clearly identifiable and a similar approach of applyinga >35° slope layer was used to guide the mapping. Pre-flood massfailure length and width attributes were extracted whilst bankheight and angle were not extracted due to an absence of compara-ble resolution elevation data for the likely failure time. Further,there is also the probability of some modification of form over timesince these features were first formed. Attempts to separate thepre-flood features into discrete time steps using analysis of tradi-tional black and white air photographs proved problematic. Selectedtime periods for this preliminary analysis included time periods cov-ering 1958, 1971 and 1974. Aerial photographs were scanned andorthorectified to facilitate comparison between these data sourcesand the pre-flood and post-flood LiDAR mapped features. As illus-trated in a representative example of the 1974 air photo coveragefor a section of the river which experienced significant mass failureoccurrences in 2011 (Fig. 3C), resolution proved too coarse to confi-dently interpret the existence of mass failures within this pre-floodtime period and the data set remained temporally lumped into apre-flood distribution.

3.2. Distribution of failures within hydraulically defined geomorphic features

To determine where these features were forming, a geomorphicclassification of within-channel and floodplain features developedusing the LiDAR-derived DEM and a one dimensional (1-D) step back-water model HEC-RAS was overlaid on the mass failure shape file. Acombination of discharge modelling and slope thresholds was usedto identify: (1) inner channel bed and bars; (2) inner channelbanks; (3) within-channel benches; (4) macrochannel banks; and(5) inundated floodplain based on hydraulic modelling and terrainslope thresholds (Table 3) (Croke et al., 2013).

3.3. Estimates of mass failure volume

Estimates of mass failure length, width and area for each timeperiod (pre- and post-flood) were extracted from each digitisedmass failure polygon. Net volumetric change between mass failurefeatures from the two time periods was approximated using a sim-ple integration scheme, multiplying the calculated elevation change(a depth measurement in m) from the DoD by surface area of eachcell (1 m2).

Fig. 2. An example of river bankmass failures from the January 2011 flood shownwith (A) h≥35° slope grid.

4. Results

4.1. 2011 and pre-existing mass failures

4.1.1. January 2011 mass failuresA total of 437 mass failures, with an average area of 676 m2

(Table 4), were identified and digitised throughout the study areaas a result of the 2011 flood. The failures could be attributed directlyto the flood as they manifested as erosion on the DoD. It was not pos-sible to attribute a particular failure mechanism for 15 of these due toproblems of shading, shadows, and image resolution. Based on theirmorphological attributes, 422 failures were classified as wet flowmass failures. Three main types were recognized: (1) Piping failures(cf Jones, 2010) (n = 168), with a concentration of exfiltrating flowin one location; (2) coalesced piping failures (n = 154), where eitherseveral failures had merged, or the landward migration from seepagehad caused bifurcation of the failure (Dunne, 1980; Schumm et al.,1995); and (3) sapping failures (n = 100) (cf. Hagerty, 1991)where the seepage flow is over a more extensive area possibly dueto more permeable sand lens or confining impermeable clay layer(Fox et al., 2006).

The area occupied by each of the hydraulically defined geomor-phic features in the study area shows that 53% of mass failure area oc-curs over the macrochannel banks, 33% on benches, and 10% acrossthe inner channel banks, and 3% from floodplain surfaces (Table 5).The total area covered by 2011 flood mass failures within the studyarea is 295,350 m2 whilst a net volume of 695,214 m3 of materialwas eroded.

4.1.2. Pre-flood mass failuresA total of 234 mass failures with an average area of 421 m2 were

identified and digitised from pre-flood high resolution LiDAR DEM(Table 4). The mass failures that were evident in the earlier imageryhad the dimensions and morphology of single piping failures, with amean length: width ratio of 1.5 (±0.4), and not sapping failures.

An analysis of the spatial distribution of pre-existing mass failuredistribution shows that 60% of their area occurs over the macrochannelbanks, 21% on benches, 11% across the inner channel banks and 7% fromfloodplains (Table 5). This distribution across hydraulically definedgeomorphic classes closely resembles the 2011 distribution. Thetotal area covered by pre-existing mass failures within the studyarea is 98,508 m2, almost a third of the area compared to the recentmass failures.

4.2. Spatial trends in post- and pre-flood mass failures

Post-flood mass failures first occurred around 7 km downstreamof the Spring Bluff GS at a catchment area of 34 km2. The mass fail-ures remained sparse until 38 km downstream (446 km2) at whichpoint the failure frequency dramatically increased to the down-stream extent of the air imagery (Fig. 1C). A cumulative downstreamdistribution of mass failure area (Fig. 4) illustrates a stepped profilewith a hiatus in mass failures occurring between 30–40 km and50–62 km, and the majority occurring below 62 km (1527 km2). APoisson distribution represents the distances between failures withmedian distances of 45 and 44 m for the left and right banks respec-tively (Fig. 5; Table 6). There was no significant difference in dis-tances between the two riverbanks.

Similar to the post-2011 distribution, pre-existing mass failuresoccurred throughout most of the catchment, starting at 7 km down-stream (Fig. 6), with a cluster of failures occurring around 30 km

igh resolution air photo, (B) hillshade on LiDAR DEM and (C) air photo with overlay of

B

A

C


Table 2Riverbank mass failure erosion types and their signature features on LiDAR and aerial imagery.

Mass failure type LiDAR last return identification features Aerial imagery identification features Source

Rotationalfailure

• Arcuate vertical headwall.• Failed blocks sloping away from the channel.

• Sharp break in vegetation at headwall.• Exposed sediment at headwall.• Large failure block with surface vegetation sloping awayfrom the channel.

Varnes (1978), Thorne (1982)

Slab failure • Linear steep headwall.• High likelihood of a steep bank surface in preceding imagery.• Blocks resting at the bank basal area.• The height of the block would be similar to the scarpwall height.

• Failed blocks resting at bank toe, or resting on scarp wall.• The failed block would have a relatively narrowvegetated surface compared to its height.

Thorne (1982),Dapporto et al. (2003)

Cantileverfailure

• Linear steep headwall.• High likelihood of a steep bank surface in preceding imagery.• Blocks resting at bank basal area smaller thanthe scarp wall height.

• Failed blocks resting at bank toe.• Failures could be as an elongated beam or block that hasbeen undercut and subsequently fallen either vertically,or toppled forward. The relative position of the vegetatedsurface would indicate the failure direction.

Thorne and Tovey (1981)

Wet flow • Arcuate scarp wall.• A failurefloorwith a smooth surface, possibly incised byflow.• Concave failure surface.• Possible narrow neck width compared to scarpwall diameter.

• No obvious coherent blocks in the failure.• Fluidised failed material would be expected to leave afailure floor with flowtype features, possibly sinuous.

Wet sand, silt flow Varnes (1978)Flow slide Hutchinson (1988)Sand, silt flow slideHungr et al. (2001)


and increased in frequency from 42 km downstream. Eighty fivepercent of the identified pre-flood mass failures occurred within200 m of each other with the most isolated failure neighbourbeing 2.4 km distant. A hiatus occurred between 54 and 62 km sim-ilar to the gap in the recent mass failure distribution. A Poisson dis-tribution represents the nearest neighbour distances with mediandistances of 50 and 30 m for the left and right banks respectively(Fig. 7; Table 5). There was no significant difference in nearestneighbour distance between both banks.

4.3. Temporal changes in patterns of mass failures

In spite of similar spatial distributions downstream, further anal-yses revealed that only 17% of mass failures overlapped between thetwo time periods (Table 4). Within these 75 coincident failures, 72%of the new failures had half or greater of their area within apre-existing failure, and less than 8% were completely located within apre-existing failure. On the other hand, of the intersecting pre-existingfailures, 19% were completely engulfed by the new 2011 mass failures.In summary, of the total area occupied by mass failures (385,000 m2),only 2.3% is common to both pre-existing and 2011 mass failuredistributions.

4.3.1. Modification of existing failures during the 2011 eventChanges to the form of the existing mass failure distribution during

the 2011 flood event were calculated from the DoD. Overall, 137pre-existing failures experienced net deposition whilst 97 had net ero-sion (Fig. 8). The average amount of elevation change in the existingfailures is +0.08 m and only 2 of the 234 existing failures experiencedno erosion after the 2011 flood event. Modifications of the pre-existingmass failures consisted of three main process categories: (1) erosion atthe scarp of the failure; (2) erosion at the toe of failure; and (3) erosionof the headland(s) outside of the failure. Scarp erosion, which may bethrough both fluvial entrainment and mass failure from seepage, wasevident at 32% of the failures. Toe erosion from fluvial entrainmentwas found at 39% of the sites, whilst headland erosion was found at35% of the sites. Both net deposition and net erosion were evident inall of these categories and at 95% of the failures overall. Vegetation,which was visible after either erosion or deposition in the flood, wassignificant at 53% of the sites.Where vegetationwas able to survive ero-sion or deposition during the flood then the scarp erosion was mini-mized from 32% to 12% and toe erosion from 39% to 21%. Only 12% of

the pre-existing failures had both significant vegetation and scarperosion.

The erosion in and around the existing mass failures appeared toexhibit the features of fluvial entrainment. There were no large (inrelation to the failure size) discrete blocks on the failure floor, andthe DoD only showed change to a depth of 1–2 m around the scarpface.

To investigate the effect of failure morphology on the form resis-tance, flow velocity and erosion or deposition, the planform area ofthe failure was correlated with the net DoD change of the failure.Pre-existing failures that touched, or were contained by, 2011 failureswere excluded. The remaining 168 failures had a correlation coefficient(R2 = 0.40; n = 168) between area and net DoD change. If only thefailures that had net deposition are used to examine the relationship be-tween planform area and deposition, the R2 value increases to 0.70(n = 114). The trend of increasing depositionwith failure area appearstoweakenwith the larger failures, >2000 m2, and if thesewere exclud-ed from the correlation, the R2 value rose to 0.78 (n = 108). This rela-tionship did not appear to hold for the average elevation change in thefailure, with the 114 depositing sites only giving an R2 value of −0.15.So although the deposition increases as the failure size increases up to2000 m2, the amount of deposition is not proportional to the failuresize.

4.4. Spatial distribution of mass failure site characteristics

The mean bank height on whichmass failures occurred was 10.9 m,though ranged from as low as 4 m in the upper alluvial reaches to 19 min the mid Lockyer Valley (Table 7). Limited mass failures occurred onbanks over 15 m because banks of this height were restricted to ashort reach at 60–70 km downstream. Bank height shows a weak pos-itive correlation against distance downstream (R2 = 0.31), howeverat the reach-scale bank height shows trends of both increasing and de-creasingheightwith distance downstream(Fig. 9A). Bank slope showedno correlation against distance downstream (R2 = 0.03; Fig. 9B). Con-tributing floodplain width increases exponentially downstream with anotable step at ~70 km marking a widening of the valley floor down-stream of Gatton (Fig. 9C).

Unit stream power (W m−2) showed a weak negative correlationwith distance downstream (R2 = 0.06). In part, this weak trend isdue to a number of confined zones giving rise to peaks in unit streampower (Fig. 9D). A peak in unit stream power in the upper confinedreaches of Murphy's Creek occurs at approximately 25 km

B

C

A

Fig. 3. Images from same location in Fig. 2 with (A) air photo from 2009, (B) hillshade on 2010 LiDAR DEM showing mass failure scars and (C) a lower resolution 1971 air photo ofsame reach.


Table 3Discharge and terrain slope thresholds used to distinguish geomorphic classes.

Geo-class Modelled discharge Terrain slope

Inner-channel bed and bars ≤Q2.33 ≤10°Inner-channel bank ≤Q2.33 >10°Bench >Q2.33 and ≤Qbf ≤14°Macro-channel bank >Q2.33 and ≤Qbf >14°Floodplain/terrace >Qbf ≤14°

Table 5Areal composition of geomorphic classes within the study area and the proportionalarea occupied by the mass failures.

Geomorphicclass

Area(ha)

Proportion(%)

Area of pre-existingmass failure (%)

Area of 2011 massfailure (%)

Inner channelbed and bars

102 1.3 2 1

Inner channel bank 106 1.4 11 10Bench 206 2.7 21 33Macrochannel bank 270 2.7 59 53Floodplain 6915 91.0 7 3


downstream (235 km2), and another increase mid-valley at approxi-mately 50 km downstream.

4.5. Comparison between mass failure and non-mass failure sitecharacteristics

Bank height showed a significant difference (p b 0.001) betweenthe mass failure and non-mass failure sites (Table 8). However,non-mass failure locations are heavily biased by the limited numberof failures in the upper reaches of Murphy's Creek (Fig. 10A).Re-analysis of bank height data excluding the upper 20 km, whichcontained relatively few mass failures, resulted in no statistical differ-ence between mass failure locations and non-mass failure locationswith mean bank heights of 11.1 m for both.

The unit stream power data showed a statistically significantresult between the two populations based on a non-parametricWilcoxon test (p b 0.001) and an ANOVA on Log10 transformed data(Table 8). The inclusion of non-mass failure sites in the higher energyreaches of Murphy's creek, however, is also likely to have biased thisdistribution, but as illustrated in Fig. 10B, the non-mass failure sitesdisplay higher variation in unit stream power for the length of thestudy area. Owing to the widespread distribution of the 437 mass fail-ures in 2011, it proved problematic to accurately compare sites whichdisplayed no mass failures but nonetheless, ranges of variables are al-most identical for the two data sets.

5. Discussion

5.1. Comparisons of failure form over time

This study presents unique, spatially comprehensive data on down-stream trends in mass failure distributions as a result of a catastrophicflood in January 2011 and those pre-existing failures in the LockyerValley SEQ. The availability of high resolution LiDAR-derived DEMsand aerial photography enabled accurate mapping of these featuresfrom both the post-flood and pre-flood data sets. The features describedin this study have been related primarily to wet flow processes whichform as liquefied or saturated material that is removed from the bankface due to exfiltration and changes in pore water pressure when theflood waters remain high (Grove et al., 2013). These were subse-quently classified as piping and sapping failures in the 2011 distri-bution. Sapping failures had a more even backwall than pipingfailures and appeared reasonably homogeneous in planform, withless scalloping. The failure floor in sapping failures was often

Table 4Number and area of digitised polygons in the study area representing pre-existing and2011 mass failures, and number and area of intersecting polygons between the timeperiods.

Number of MF Total area (m2) Average area (m2)

Pre-existing 234 98,508 4212011 437 295,350 676Overlapping MFs 75 9040 120

stepped displaying multiple levelled/planar failure floors. Wetflows caused by piping were the most consistent process through-out the catchment in terms of the overall contribution of sediment(Grove et al., 2013). Analysis of the pre-flood imagery confirms thatsimilar failures occurred during past floods as the accurate shape ofthe headwall was clearly preserved, but less detail could be provid-ed on their original form. Changes in the length/width ratios andsize of the features would indicate that sapping failures are lessdominant than identified in the post-flood data set. This could indi-cate the general absence of this particular process or some subse-quent change in the form of these features over time.

5.2. Controls on spatial trends in mass failure distribution

The downstream distributions of both pre- and post-flood failuresillustrate that they occur across a wide range of river lengths, catch-ment areas and bank heights. The presence of such features in theupper reaches just 7 km downstream in both distributions suggeststhat such processes are not scale-dependent. Unlike the more widelyreported forms of mass failures due to rotational and planar processesof bank collapse, wet flow failures occur fairly ubiquitously down-stream, albeit with some areas displaying a general absence of fail-ures. As a result, existing models for bank erosion process domainswhich tend to conceptualise mass failures as occurring in the lowerreaches of valleys may not be appropriate for such features. Suchmodels are based largely on the assumption that as channel depth/bank size increases downstream, a zone in which bank height exceedssome ‘critical’ value leads to mass failure development downstream.The bivariate plots of local at-a-site controls and distance down-stream in this study illustrate some of the complexities of this gener-alised interpretation in settings where such variables do not increaselinearly with distance downstream. For example, bank height shows alinear trend of increasing for the first 25 km of river length but thenshows a notable reduction, followed by several such ‘steps’ down-stream. In this study, the presence of large ‘macrochannels’mid valleyin the Lockyer adds considerable complexity to any linear pattern ofincreasing channel depth and bank size downstream. In addition, ifbank material properties or other channel geometry variables weresignificant factors in controlling the basin-scale distribution, existingmass failures may be expected to enlarge over time. Analysis con-firmed that only 17% of post 2011 flood mass failures showed somecorrelation to an existing feature indicating that the majority of2011 failures occurred in a unique location. In addition, a comparisonof the changes in the form of pre-existing mass failures during the2011 event would also lend support to the limited role of local,at-a-site factors. There appears to have been limited modification ofthe form of these features during the 2011 flood event. They did notappear to contribute much sediment in the 2011 flood and were in-stead operating primarily as sediment sinks. The correlation betweenfailure planform area and the amount of deposition showed a signifi-cant positive relationship between the existing failure size and thenet elevation change on the DoD, up to a threshold area of 2000 m2.This could indicate that the larger failures have a limited ability tocreate a dead water zone and perhaps do not form any flow

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Cu

mu

lati

ve m

ass

failu

re a

rea

(%)

Mas

s fa

ilure

are

a (m

2 )

Distance downstream (km)

Fig. 4. Longitudinal distribution of mass failures plotted against failure area from the January 2011 catastrophic flood.

0.0

0.5

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Nea

rest

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ur

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)


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Right bank

Fig. 5. Longitudinal distribution of mass failures following the January 2011 catastrophic flood. Distance downstream commences from the Spring Bluff GS which has a contributingarea of 18 km2.


separation, which would increase average velocity and decrease de-position. As the basic mechanism for the formation of these featuresis seepage from the floodplain face, it remains unclear why this pro-cess does not continue to enlarge an existing mass failure or form agully in the headward extent of the failure wall. No gullies weremapped adjacent to any pre-existing failure and none was formedas a result of the 2011 flood. This would tend to add support to therelatively limited role of local factors such as bank height or materialproperties in explaining their distribution.

Table 6Nearest neighbour distributions on left and right banks for pre-existing and 2011 floodmass failures.

Year Bank Mean ± SD(km)

Skewness Median(km)

Min(km)

Max(km)

Pre-existing Left 0.15 ± 0.26 3.6 0.05 0 1.8Right 0.15 ± 0.36 5.2 0.03 0 3.2

2011 Left 0.10 ± 0.22 7.1 0.045 0 2.1Right 0.14 ± 0.31 4.9 0.044 0 2.4

Comparison Left 98 ± 226 7.1 0.044 0 2.1Right 144 ± 315 4.9 0.044 0 2.4

No significant difference in nearest neighbour distributions between year and bank(p b 0.05) based on non-parametric test of medians and Kruskal–Wallis test.

5.3. Residence time of mass failure features

The preservation of mass failure features from past flood events isan interesting conclusion emerging from this study. Comparison be-tween the pre- and post-flood distributions would suggest thatmass failures from different floods tend to have limited spatial over-lap and the overall form of the mass failure is retained in the land-scape over time. The precise role of past historical floods in thepre-flood mass failure distribution could not be fully elucidated, butit seems likely that each of the major floods outlined in Section 2.3contributed to the formation of these features, and as such they

have been preserved for at least 150 years. As the dominant processoccurring within an existing mass failure is now depositional, itseems likely that such features will change their planform largelythrough infilling and vertical accretion. This may explain the generalabsence of sapping failures in the pre-flood distribution, as changesin the length/width ratio may either reflect the general absence ofthis form in the initial distribution or subsequent modification of

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Cu

mu

lati

ve m

ass

failu

re a

rea

(%)

Mas

s fa

ilure

are

a (m

2 )

Distance down stream (km)

Fig. 6. Longitudinal distribution of mass failures plotted against failure area for pre-existing features.

0.0

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)


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Right bank

Fig. 7. Longitudinal distribution of pre-existing mass failures.

-5000

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Mas

s fa

ilure

vo

lum

e (m

3 )

Distance down stream (km)

2011 flood

pre-existing

Fig. 8. Change in sediment volume derived from 2010 to 2011 DoD. Positive values show sediment loss, negative values indicate in filling of mass failure areas.


Table 7Characteristics of mass failures from January 2011 flood and associated channel attributes.

Variable Mean Std. dev. Median Skewness Min. Max.

Length (m) 46 65 24 5.0 5 757Width (m) 16 11 13 2.9 3 105Length/width 2.5 1.9 1.9 2.7 1 16.8Area (m2) 676 1360 247 4.8 10 12,735Volume (m3) 1592 3770 384 4.6 2 28,129Bank height (m) 10.9 3 11 0.05 4 19Bank slope (%) 34 13 32 0.02 5 84Contributing floodplain width (m) 772 810 505 1.8 10 3954Unit stream power (W m−2) 189 227 130 4.8 1 2432


the failure form through depositional processes. It is estimated that atleast 12 inundation events would be required to fill these failuresbased on the average net elevation change for the 168 failures in2010 that did not touch the 2011 failures (0.13 m of deposition), as-suming a constant rate of deposition in each event. In reality theexisting failures appeared to experience erosion at the toe or scarpin 70% of the failures so that the failure margins would be more mod-ified in the first few events, which combined with deposition wouldresult in the smoothing of failure slopes. The degree of modificationinitially would depend on time since the last event, controlling theestablishment of vegetation.

5.4. Mass failures and the magnitude of flood events

Whist the form of the pre-existing mass failures showed limitedchange during the 2011 event, interestingly, the frequency ofpost-flood mass failures is significantly higher than the pre-flood dis-tribution for a longer time period. The 2011 event saw an almost dou-bling of mass failure features. This cannot be explained by floodmagnitude alone as the pre-flood time period also includes extremeevents which are reportedly of greater magnitude than the recent2011 flood (Bureau of Meteorology, 2011). The 2011 event, for exam-ple, is ranked as the second highest flood event in the last 100 years,but as outlined in Section 2.3, historical accounts also reveal the sig-nificance of earlier events such as 1840 and 1893 which based on

0

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idth

(m

)


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Ban

k h

eig

ht

(m)


A

C

Fig. 9. A comparison of 2011 mass failure characteristi

stage height data on adjacent rivers such as the Brisbane, were ofgreater magnitude than both 1974 and 2011. The increase in the fre-quency of the mass failures in the 2011 distribution, therefore, cannotbe explained by flood magnitude alone. However several aspectsof the 2011 flood are worth noting as they may have contributedto this notable increase in the downstream reaches. The 2011flood event occurred immediately following a very wet summer inQueensland when the catchment and antecedent soil materialswere close to saturation even prior to the event (Bureau ofMeteorology, 2011; Jordan, 2011). The dominant source of rainfall oc-curred in the upper catchment close to the headwaters near Murphy'sCreek, however due to the catchment morphology, the major tribu-tary inputs on the southern margins of the catchment only ‘switchedon’ in the days following the major flood peak on January 10th. Assuch, a double-peak was observed in the hydrograph at the lowerend of the system, which although of lower magnitude than up-stream, would have contributed to more dynamic flow conditionsand pore-water pressure changes as the hydrograph adjustedthroughout both smaller events. The timing of the arrival of the firstflood peak from the Lockyer is also known to have coincided withthe flood peak arrival down the mid-Brisbane such that flood watersfrom the Lockyer were blocked at the tributary junction, increasingthe inundation time on the floodplains in the lower reaches. The effectof bank inundation durations also increasing with flood-hydrographbase-times in a downstream direction has been noted in previous

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m-2

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k sl

op

e (m

/m)


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D

cs and associated channel and hydraulic variables.

Table 8Comparison channel and hydraulic attributes between mass failure locations andnon-mass failure locations.

Attribute Test Mean Significant difference(p > 0.01)

Bank slope (m/m) MF ANOVA 0.34 NNo MF 0.35

Bank height (m) MF ANOVA 10.9 YNo MF 8.9

Unit stream power(W m−2)

MF ANOVA on 189 YNo MF Log10(x) and

Wilcoxon test775


studies of mass failure distributions downstream (Lawler et al.,1999). Previous research also noted the existence of time-lags in-volved in river banks reaching moisture-driven critical stability con-ditions and as a result, many traditional mass failures have beenobserved to occur on the recessional limbs of, or well after, stormor seasonal hydrographs (Lawler et al., 1999). The general absenceof material on the floor of the failures post 2011 would also indicatethat such features occurred on the recessional limb, but when dis-charges remained high enough to transport much of the bank mate-rial. Whilst this study cannot elucidate the precise role any of thesemeteorological factors would have played in explaining the in-creased frequency of failures in the 2011 flood, it seems probablethat the above factors would have had a cumulative effect and thatbank erosion rates even in wet flow processes are likely to have oc-curred episodically both prior to, during, and immediately after, theflood peak.

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Un

it s

trea

m p

ow

er (

W m

-2)


MF

Non MF

A

B

Fig. 10. A comparison of (A) bank height and (B) unit stream power between 2011mass failure sites and sites of no mass failure occurrence.

6. Conclusions

This study documents the downstream distribution of mass fail-ures both as a result of a catastrophic flood which occurred in theLockyer Valley in January 2011 and those features which formed dur-ing previous large floods. The features were classified as wet flowsbased on some important diagnostics of failure form and processesand have retained a characteristic morphological shape over time.These failures are different to the more widely reported gravity af-fected bank collapses. The downstream analysis of these two tempo-ral distributions revealed the following major conclusions:

• Wet flow failures occur across a range of river lengths, catchmentareas, bank heights and angles and do not appear to be scale-dependent or spatially restricted to certain downstream zones.

• The downstream trends of each bank failure distribution show limit-ed spatial overlap.

• Conceptualmodels of downstreamprocess zonesmay need to consid-er a wider array of mass failure processes to accommodate for the al-ternative forms of bank erosion processes such as those reported here.

• The modification of these features during a catastrophic flood also in-dicated that such features tend to form at some ‘optimum’ shape andshow limited evidence for subsequent enlargement even when flowand energy conditions within the banks and channel were high.

• Such features show evidence for infilling through deposition duringsubsequent floods and their identification over time diminishes, al-though the sharp accurate form of the headwall remains obvious.

It seems clear that such features are an important mechanism forinternal adjustments in channel width during extreme flood eventsin the Lockyer Valley. It is also apparent that the increasing availabil-ity of high-resolution imagery and topographic data sources will con-tinue to improve our ability to understand the spatial and temporaldistributions of bank failures and provide valuable input to futurebank erosion prediction models.

Acknowledgements

This project was supported by the Queensland's Department of Sci-ence, Information Technology, Innovation and the Arts (DSITIA) as partof the Flood Recovery Project 2011 and an Australian Research CouncilLinkage Award (LP120200093). FionaWatson (DSITIA Remote Sensing)provided valuable advice on LiDAR mapping of these features. PhilBlosch (DSITIA Chemistry Centre) provided access to a programme inR to calculate channel attributes from LiDAR cross-sections.

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