Analysis of environmental controls on tsunami deposit texture

Marine Geology 368 (2015) 1–14

Contents lists available at ScienceDirect

Marine Geology journal homepage: www.elsevier.com/locate/margeo

Analysis of environmental controls on tsunami deposit texture Claire L. Kain a,⁎, Christopher Gomez b, Deirdre E. Hart b, Catherine Chagué-Goff a,c, James Goff a a b c

School of Biological Earth and Environmental Sciences, UNSW Australia, Sydney, 2052 NSW, Australia Department of Geography, University of Canterbury, Christchurch, New Zealand Australian Nuclear Science and Technology Organisation (ANSTO), Kirrawee DC, 2232 NSW, Australia

a r t i c l e

i n f o

Article history: Received 30 October 2014 Received in revised form 17 June 2015 Accepted 24 June 2015 Available online 30 June 2015 Keywords: Tsunami deposit Database Grain size Sediment transport Principal Component Analysis Cluster analysis

a b s t r a c t Tsunamis transport large amounts of sediment and can leave recognisable signatures in the landscape. The form and composition of onshore tsunami deposits are a function of wave dynamics, sediment availability and characteristics of the local environment, the latter of which also partially controls preservation of the deposit. This research reviews these relationships in a global context and assesses the connection between tsunami deposit particle size and four controlling parameters: climate (temperature and rainfall), density of tsunami sediments, degree of coastal protection and distance between tsunami source and sediment deposition. An international dataset of tsunami deposit locations and texture was compiled from published literature and existing databases. Values for environmental variables were calculated for each location from global datasets of temperature, rainfall, coastline shape and tsunami source locations. Spearman's rank-order correlation, Principal Component Analysis (PCA) and hierarchical Cluster Analysis (CA) were used to analyse relationships between these variables. PCA results show an inverse relationship between particle size and sediment density, climate variables and distance from source. CA results support this, suggesting a cluster structure controlled primarily by particle size and secondly by climate and sediment density. These relationships can be explained by the influence of the environment on antecedent morphology and the composition of sediments available for tsunami transport. © 2015 Elsevier B.V. All rights reserved.

1. Introduction 1.1. Tsunami deposits A tsunami has the power to erode, transport and deposit large amounts of sediment, leaving signatures in the sedimentary record that may be used to infer the hydrodynamic mechanisms of inundation. Tsunami deposits take a variety of forms, resulting from differences in the waveform, local bathymetry, topography, and coastal configuration, as well as sediment type and its availability to be transported (e.g. Sugawara et al., 2008). Sediment characteristics and coastal form are in turn controlled by interacting external parameters, which include tectonics, continental lithology, coastal and fluvial energy and climate (e.g. Hayes, 1967; Masselink and Hughes, 2003). Deposits from an individual tsunami will differ considerably at different locations and significant internal variability may occur within a single deposit. This has significant implications for the interpretation of tsunamis from their deposits. Tsunami deposits are often initially identified by their stratigraphic context, occurring frequently as anomalous sediment (often sand) layers laid down in a lower-energy coastal environment (e.g. Chagué-Goff et al., 2002; Clague and Bobrowsky, 1994; De Martini ⁎ Corresponding author. E-mail address: [email protected] (C.L. Kain).

http://dx.doi.org/10.1016/j.margeo.2015.06.011 0025-3227/© 2015 Elsevier B.V. All rights reserved.

et al., 2010; Kelsey et al., 2005; Nanayama et al., 2007; Nichol et al., 2007; Sawai et al., 2008; Sugawara et al., 2012). Tsunami deposits may occur onshore or offshore, but research has tended to focus on the most accessible onshore deposits. These deposits commonly take the form of a large sediment sheet, usually sourced from the adjacent nearshore or beach environment during inundation (e.g. Sugawara et al., 2008), although deposits may be discontinuous or absent where the signature is predominantly erosional (e.g. MacInnes et al., 2009). It is common for deposits to contain mud, gravel layers and clasts up to large boulder size, depending on the source material available (e.g. Chagué-Goff et al., 2012a; Goto et al., 2011; Maouche et al., 2009; Mastronuzzi et al., 2007; Medina et al., 2011; Nandasena et al., 2011; Paris et al., 2010; Scicchitano et al., 2007). The thickness of a deposit can vary from millimetres to tens of metres (e.g. Sugawara et al., 2005), depending on the energy of the wave, amount of sediment available and preservation potential of the deposit (e.g. Sugawara et al., 2008). Characteristics of tsunami deposits have been reviewed extensively in recent decades (Chagué-Goff et al., 2011; Dawson, 1994; Dawson and Shi, 2000; Engel and Brückner, 2011; Etienne et al., 2011; Fujiwara, 2008; Goff et al., 2001; 2012; Shanmugam, 2012; Shiki et al., 2008; Tappin, 2007) and research has expanded considerably following the 2004 Indian Ocean tsunami (IOT) and 2011 Tohoku-oki tsunami (ToT). Common defining sedimentary features include: predominantly marine sediment origin, graded sediment layers that generally fine

2

C.L. Kain et al. / Marine Geology 368 (2015) 1–14

and thin upwards and inland, erosional lower contacts, loading structures and rip-up clasts, and evidence of repeated reversal of current direction (e.g. Chagué-Goff et al., 2011; Fujiwara, 2008; Goff et al., 2012; Kortekaas and Dawson, 2007; Morton et al., 2007; Nichol et al., 2007; Peters and Jaffe, 2010a; Peters et al., 2007; Sugawara et al., 2008; Switzer and Jones, 2008). It is important to note that not every indicator is present in a given deposit and tsunami deposit identification relies on the use of multiple proxies, which have been added to in recent years as new techniques have been developed and applied from other disciplines (Chagué-Goff et al., 2011; Goff et al., 2012). The geographical distribution of tsunami research is not evenly spread, which has implications for any patterns inferred from this research. Studies of both recent and palaeo-tsunami deposits have been particularly focused on landmasses adjacent to the Pacific Ocean, where tsunamis frequently result from subduction zone earthquakes (e.g. Cisternas et al., 2005; McFadgen and Goff, 2007; Minoura et al., 1996; Nanayama et al., 2007; Nichol et al., 2010; Switzer and Jones, 2008). This gap is partially addressed by the increasing availability of tsunami databases, which are continually updated as new research becomes available and new tsunamis occur. These include global catalogues of tsunami events and deposits (Dunbar and McCullough, 2012; NGDC/WDS, 2014; Peters and Jaffe, 2010b) alongside ongoing projects with a palaeotsunami and/or a regional focus (e.g. New Zealand: Goff, 2008; Australia: Goff and Chagué-Goff, 2014; France: Lambert and Terrier, 2011; Western North America: Peters et al., 2003; Italy: Tinti et al., 2004).

1.2. Statistics in tsunami science Exploratory statistical analysis of a dataset provides insight into data trends, structure and variability. These techniques are commonplace in social science and biological research, but are less so in earth science, because this type of data is not often obtained in a systematic experimental manner that meets statistical criteria for sample size and data type (Borradaile, 2003). However, some areas of earth science have successfully applied statistical methods, and as such there is a precedent for their implementation in physical tsunami research. Multivariate techniques are regularly applied in geochemical investigations of water composition, to determine source and transport pathways (e.g. Praus, 2006; Zhang et al., 2009), and similar methods have also been applied to dust and soil (e.g. Yongming et al., 2006). Other research has used a combination of multivariate techniques in a less direct manner, to explore the influence of environment and geology on complex physical processes such as landslide susceptibility (e.g. Baeza and Corominas, 2001; Komac, 2006) and river hydrology and channel evolution (e.g. Bertrand et al., 2013; Thoms and Parsons, 2003). The science of tsunami deposits has largely been developed through observational studies and, more recently, modelling of sediment transport processes. Statistical analysis is sometimes applied to individual aspects of a tsunami deposit, such as grain size or geochemical data processing (e.g. Chagué-Goff et al., 2012a; 2012c; Jagodziński et al., 2012; Sakuna et al., 2012; Szczuciński et al., 2005; Yoshii et al., 2013), but statistical methods are not generally appropriate for solving the research questions of tsunami-focused geological investigations. Nevertheless, statistics is an underutilised tool for the analysis of the dense information catalogued in tsunami databases. Relationships between tsunami deposit form and the local environment have been well documented in an observational context for individual deposits, but have not yet been explored from a global predictive perspective. The purpose of this research is to investigate the relationships between tsunami deposit texture and four key parameters in the depositional environment: climate (temperature and rainfall), density of tsunami sediments, degree of coastal protection (as will be explained later) and distance between tsunami source and sediment deposition. These parameters were chosen due to their

fundamental importance in controlling coastal morphodynamics and sediment supply (Masselink and Hughes, 2003). 2. Material and methods 2.1. Data sources and preparation A database of tsunami deposit characteristics and grain size information was compiled from published literature and other available tsunami databases (Fig. 1, Table 1). Entries were restricted to deposits emplaced within the late Holocene, based on the assumption that the environment has remained relatively constant during this timeframe. Where multiple tsunami deposits were described for distinct events at the same site, these were included as separate entries. This database is not intended as an exhaustive list of all possible tsunami deposits, but rather a representative sample to allow a robust global analysis. Additionally, some published research that was initially consulted did not contain sufficient numerical data to allow inclusion in the database. Database parameters are presented in Table 2, along with sources of information, calculations and percentage of entries with values for each variable. In the case of climatic variables, global temperature and rainfall datasets were obtained from Hijmans et al. (2005) and together act as a proxy for weathering processes and chemical weathering in particular. Values at tsunami deposit locations were extracted from a raster using ArcGIS, then manually cross-checked to eliminate errors in the extraction process. Where a deposit location had no corresponding value for one of these parameters, this was interpolated from the nearest area. Mean monthly temperature and rainfall values were averaged to provide a mean annual value for each parameter. We acknowledge the uncertainty introduced in the averaging process, but the values compared well with deposit locations' classifications on the KöppenGeiger Climate Classification system (Kottek et al., 2006) and the resolution was deemed satisfactory for our purpose. Sediment density was either reported directly from the original research or calculated based on descriptions of the mineral composition of tsunami deposits. Where the tsunami source was reported, this was mapped and the shortest travel distance calculated across the Earth's surface. If no information for composition or tsunami source was available, a value of NA was reported for that parameter. The protection factor is a dimensionless empirical parameter that represents the degree of coastal exposure, with values of 0 corresponding to a promontory, 1 equal to a straight coast and values increasing with higher levels of protection. This was calculated for each deposit location based on the level of embaymentisation and the presence of protective features such as islands or reefs. The following equation was developed, where Sl refers to shoreline length and Cl to chord length between headlands, after Short (1996). K refers to a sheltering factor, measured on a scale of 1–10 based on the percentage of protection offered by reefs or offshore islands. PF ¼ Sl=Cl  K The final database contains 273 entries, of which 92 have values for all parameters and 199 have values for at least 5 of the 6 variables. 2.2. Statistical analyses Numerical analyses were undertaken using the open source statistical package, R. Descriptive statistics were calculated for each variable and data distributions were assessed. Correlation analysis was performed by Spearman's rank-order correlation, which is a nonparametric test that is more robust for data that are non-linearly related or contain outliers that must be included (Schuenemeyer and Drew, 2011). A matrix of Spearman's correlation coefficients was constructed to assess individual relationships between variables, with significant

C.L. Kain et al. / Marine Geology 368 (2015) 1–14

3

Fig. 1. Locations of database entries, marked in red.

relationships reported where the coefficient met the required critical value (Ramsey, 1989) and the p-value b 0.05. Principal Component Analysis (PCA) and Cluster Analysis (CA) were applied, using the package FactoMineR, to investigate the structure of the data and infer more complex relationships between variables. PCA and CA are multivariate statistical techniques commonly used for exploratory data analysis in the environmental and earth sciences (Schuenemeyer and Drew, 2011). PCA is used to describe, summarise or simplify a dataset, by determining a set of uncorrelated orthogonal components that are calculated according to the composition of the dataset and the relationships between variables. The purpose of CA is to group the data into a given set of ‘clusters’ based on similarities between the data entries across some or all variables. Several algorithms for CA exist, but Hierarchical CA (HCA) is especially suited for exploratory purposes, where the optimum number of groups to describe the data is not known prior to analysis (Schuenemeyer and Drew, 2011). HCA constructs a nested set of clusters; one end of which includes all entries in the dataset while the other extreme contains each individual as a separate cluster. An optimum number of clusters to describe a dataset can be determined by examining the change in variance within the dataset after each further division. Both PCA and HCA are sensitive to differences in scale and variance between variables, so standardisation of the data is recommended prior to analysis (Schuenemeyer and Drew, 2011). Consequently, data were scaled and centred to a mean of 0 and standard deviation of 1 prior to these analyses. PCA was performed on a covariance matrix of the dataset to return 6 uncorrelated dimensions and examine the contribution of each variable to variance in the dataset. HCA was applied on principal components using Ward's method of minimum variance and Euclidean distance as an initial measure of similarity between data entries. A dendrogram was constructed to determine the optimum number of clusters and results were plotted on a 3-dimensional factor plot.

3. Results 3.1. Patterns in data distributions and bivariate analysis The percentage distributions for each variable are presented in Fig. 2. Mean particle size ranges from silt to boulders up to 4 m in length (aaxis), with 70% of entries falling between 0.125 and 1 mm (fine-coarse sand). A further 6.3% of entries are boulders of over 0.5 m in length. Mean monthly precipitation for tsunami deposit locations ranges from 0 to 323 mm and is quasi-normally distributed. Mean monthly temperature shows two peaks; one corresponding to temperate climate zones with values of 7–12 °C, and another representing equatorial regions with values of 27–30 °C. Sediment density ranges from 0.25 (pumice) to 4.5 g cm−3 (black sands containing heavy mineral assemblages), with most values falling between 2.5 and 2.7 g cm−3 (quartz, carbonate, granite, limestone). 7.5% of entries exhibit densities of between 1.2 and 1.7 g cm−3 (coral and beachrock, respectively) and 5.0% fall between 3 and 3.5 g cm− 3 (basalt and mafic mineral assemblages). Protection factor values range from 0 (peninsula) to 184 (highly embayed fjord environment). Most locations exhibit a straight to slightly embayed open coast environment, with a protection factor b 5. Distance from tsunami source to deposit location ranged from 16 to 13232 km and 54% of all deposit entries were less than 500 km from their tsunami source. Of the tsunamis in the database with a known source (63%), 95.8% were earthquake-generated, with a minority of 2.6 and 1.6% generated by landslides and volcanoes, respectively. 3.1.1. Spearman's rank-order correlation analysis Results of Spearman's rank-order correlation analysis are presented in Table 3 alongside a scatterplot matrix of relationships between variables (Fig. 3). Most notably, mean grain size is inversely correlated with sediment density, protection factor and distance from source. Significant correlations are also present amongst several of the other

4

C.L. Kain et al. / Marine Geology 368 (2015) 1–14

Table 1 Summary of geographic areas and tsunami events covered by the database. Geographic area

Events recorded

References

Indian Ocean and Indonesia

1883 1992 1994 2004 2006 2010 prehistoric

Japan

869 1640 1983 1993 2011 prehistoric

North America West coast

1700 1964 prehistoric

Central and South America

1960 1992 1996 2001 2010 prehistoric 1456 1743 1755 1908 1956 prehistoric 1923 1929 1964 1969 prehistoric 1946 1975 1868 1998 2006 2009 prehistoric

Bahlburg and Weiss (2007), Brill et al. (2011, 2014), Carey et al. (2001), Choowong et al. (2007, 2008), Dawson et al. (1996), Fujino et al. (2009, 2010), Goto et al. (2009), Hawkes et al. (2007), Hentry et al. (2010), Hori et al. (2007), Jaffe et al. (2006), Jagodziński et al. (2009), Jankaew et al. (2011), Kench et al. (2006, 2008), Matsumoto et al. (2008, 2010), Minoura et al. (1997), Monecke et al. (2008), Moore et al. (2006, 2011), Morton et al. (2008), Nandasena et al. (2011), Narayana et al. (2007), Nichol and Kench (2008), Paris et al. (2007, 2009, 2010), Putra et al. (2013), Razzhigaeva et al. (2006), Scheucher and Vortisch (2010), Shi et al. (1995), Shi and Smith (2003), Spiske et al. (2010), Srinivasalu et al. (2007, 2009), Srisutam and Wagner (2009), Szczuciński et al. (2006), Yawsangratt et al. (2009). Abe et al. (2012), Araoka et al. (2010), Chagué-Goff et al. (2012a,c), Fujiwara et al. (2013), Goto et al. (2011, 2012), Jaffe et al. (2012), Jagodziński et al. (2012), Kitamura et al. (2013), Minoura et al. (2013), Minoura and Nakaya (1991), Minoura and Nakata (1994), Nakamura et al. (2012), Nanayama et al. (2000), Nanayama and Shigeno (2006), Nandasena et al. (2013), Nishimura and Miyaji (1995), Richmond et al. (2012), Sato et al. (1995), Sato et al. (2014), Schneider et al. (2014), Sugawara et al. (2012, 2013), Szczuciński et al. (2012), Takashimizu et al. (2012), Tanigawa et al. (2014), Yamada et al. (2014). Abramson (1998), Atwater (1992), Atwater et al. (1999), Atwater and Hemphill-Haley (1997), Benson et al. (1997), Briggs (1994), Clague et al. (1999), Clague and Bobrowsky (1994), Hemphill-Haley (1995), Hutchinson et al. (1997, 2000), Kelsey et al. (1993, 1995, 1998), Li (1992), López and Bobrowsky (2001), López (2012), Minor and Grant (1996), Nelson et al. (1998), Peterson et al. (2010, 2011, 2013), Reinhart (1991), Reinhart and Bourgeois (1987), Schlichting (2000), Williams and Hutchinson (2000), Witter (1999), Witter and Kelsey (1994), Witter et al. (2012). Arcos et al. (2013), Bahlburg and Spiske (2012), Bourgeois et al. (1999), Cisternas et al. (2005), Higman and Bourgeois (2008), Horton et al. (2011), Jaffe et al. (2003), Morton et al. (2007, 2011). Spiske et al. (2013)

Mediterranean/Southern Europe

Northern high latitudes

Pacific Ocean islands

Becker-Heidmann et al. (2007), Bruins et al. (2008), Costa et al. (2012a, 2012b), Cuven et al. (2013), De Martini et al. (2003, 2010), Dominey-Howes et al. (2000), Font et al. (2013), Gerardi et al. (2012), Hindson et al. (1996), Hindson and Andrade (1999), Kortekaas and Dawson (2007), Pignatelli et al. (2009), Rodríguez-Vidal et al. (2011), Smedile (2012).

Banerjee et al. (2001), Bondevik et al. (1997), Bourgeois et al. (2006), Foster et al. (1991), Minoura et al. (1996), Moore et al. (2007), Nanayama et al. (2007), Razjigaeva et al. (2014), Romundset and Bondevik (2011), Smith et al. (2004, 2007), Tuttle et al. (2004).

Bourgeois (2009), Chagué-Goff et al. (2002, 2011, 2012b), Cochran et al. (2005), Gelfenbaum and Jaffe (2003), Goff et al. (2004, 2006, 2010a, 2010b, 2011), Jaffe and Gelfenbaum (2007), Jaffe et al. (2010, 2011), Morton et al. (2007), Nichol et al. (2010), Richmond et al. (2011).

variables. Mean monthly precipitation is positively correlated with mean monthly temperature, while distance from source is correlated with mean monthly temperature and inversely correlated with mean monthly precipitation. Explanations of these relationships are provided in Section 4.1.

temperature and mean monthly precipitation, respectively. Again, mean grain size exhibits a negative relationship with these two variables (loading of − 0.47). Component 3 accounts for 17% of total variance and is explained by Mean monthly precipitation (− 0.56), Protection Factor (−0.65) and tsunami source distance (0.41) (Table 4).

3.2. Multivariate analysis of relationships

3.2.2. Cluster analysis Hierarchical cluster analysis was performed on principal components and results show data can be grouped into four primary clusters (Fig. 5). The characteristics of each primary cluster are summarised in Table 5. Mean values for each variable were calculated within each cluster and can be interpreted relative to a standardised mean and standard deviation (for the entire dataset) of 0 and 1 respectively. Cluster 1 is characterised by an extremely low mean grain size (−2.6), lower than average mean monthly precipitation (−1.4) and higher sediment density (0.75), thus representing fine deposits in temperate environments. Cluster 2 also displays a finer than average class of sediments (−0.45), but conversely, temperature and precipitation are higher than average (1.1 and 0.49, respectively). Consequently, Cluster 2 describes fine sediments in tropical environments. Mean grain size and sediment density are higher than average in Cluster 3 (0.94 and 0.80 respectively), but temperature is lower than average (−1.2), corresponding to large clasts

3.2.1. Principal Component Analysis PCA was used to assess the relationships between the variables within the dataset. PCA loadings are presented in Table 4 and the relationships between variables along the first two dimensions are visualised in Fig. 4. The data were transformed into six uncorrelated components, with the Components 1 and 2 accounting for 58% of total variance in the dataset. Components 4, 5 and 6 present eigenvalues of b1 and explain only 11% of the variance, thus they can be disregarded. The dominant variables contributing to variance along Component 1 are mean grain size (0.48), sediment density (− 0.52) and tsunami source distance (−0.47). Sediment density and source distance show a negative loading, indicating an inverse association between these variables and particle size. Variance along Component 2 is accounted for primarily by climate, with loadings of 0.53 and 0.55 for mean monthly

C.L. Kain et al. / Marine Geology 368 (2015) 1–14

5

Table 2 Sources of global data pertaining to environmental factors. Variable

Name in database

Percentage of entries

Source

Tsunami deposit location (WGS-84)

Lat Long

100

Mean grain size(mm)

GSmean

99.5

Mean monthly precipitation (mm)

MMP

100

MMT

100

SedDens

44

Protection Factor

ProFact

100

Distance from source(km)

DistSource

63

Directly from literature or taken from existing database entries: Dunbar and McCullough (2012) Peters et al. (2003) Peters and Jaffe (2010b) Directly from literature or taken from existing database entries: Dunbar and McCullough (2012) Peters et al. (2003) Peters and Jaffe (2010b) Global dataset from Hijmans et al. (2005). Mean values for each month were averaged to provide a single value for analysis. Global dataset from Hijmans et al. (2005). Mean values for each month were averaged to provide a single value for analysis. Values taken as reported in source literature or calculated from descriptions of mineral composition. Where mineralogy was not described, a value of NA was entered. Represents degree of coastal exposure (high values = more protection). Calculated for each location according to Section 2.1. Calculated according to the Haversine equation (Veness, 2011). Where tsunami source was not known, a value of NA was entered.

Mean monthly temperature (°C) Density of tsunami sediments(g cm

−3

)

Fig. 2. Distributions of variables in the total dataset and distributions of the complete observations (entries with data for all variables — used for PCA and CA). Note: Mean grain size data (mm) has been plotted with a logarithmic transformation, to more sensibly display the data.

6

C.L. Kain et al. / Marine Geology 368 (2015) 1–14

Table 3 Spearman's correlation matrix for database variables, using pairwise complete entries. The lower left values are Spearman's correlation coefficients, while the right upper values are the associated p-values. Significant correlations are marked with an asterisk and in bold (green for correlation coefficients and red for p-values). Mean grain size Mean grain size

Table 4 Varimax rotated principal component matrix of factors affecting tsunami deposit sedimentology. The higher the loading value, the higher the contribution of that variable along the component. Significant contributions (loadings above 0.4) are marked in red with an asterisk.

Mean Mean monthly monthly precipitation temperature

Sediment density

Protection factor

Distance from source

Variable

0.03

0.10

0.00

0.04

0.47

0.04

0.44

0.07

0.42

0.59 0.32

Mean monthly precipitation

–0.23*

Mean monthly temperature

0.18

0.23*

Sediment density

–0.41**

0.08

Protection factor

–0.23*

0.20

–0.06

0.11

Distance from source

–0.08

–0.28**

0.24*

0.18

–0.09

Component 1

2

3

4

Mean grain size

0.483644*

–0.46524*

0.058767

–0.14446

0.01

Mean monthly precipitation

0.217865

0.546744*

0.03

Mean monthly temperature

0.3104

0.534688*

0.11

Sediment density

–0.52203*

0.355099

0.08 0.19

in higher latitude areas. Cluster 4 also contains larger clasts (mean of 1.1), with higher temperature, lower precipitation and less dense sediments (0.42, − 1.3 and − 0.75), thus relating to coral boulders at low latitudes. 4. Discussion 4.1. Relationship between tsunami deposit texture and environmental factors Tsunami deposits are commonly interpreted individually in the context of their depositional environment, but the relationship between these factors has not been explored in a global context. Results of statistical analyses confirm the existence of relationships between tsunami deposit sedimentology and factors related to the depositional environment These findings provide insights into the nature of these relationships and interaction between the variables studied.

5

6

0.6997*

0.189049

–0.55566* –0.17652

0.342831

–0.44289*

0.295131

–0.47812*

–0.12701

0.534726*

0.08343

0.37072

0.567031*

0.368065

Protection factor

–0.35931

–0.26104

–0.65488* –0.42443*

–0.07502

0.433725*

Distance from source

–0.46974*

–0.06707

0.406027* –0.63388*

0.222719

–0.39823

Eigenvalue

1.912

1.561

1.024

0.842

0.374

0.285

Percent of variance

31.86

26.02

17.07

14.04

6.248

4.763

Cumulative percent of variance 31.86

57.88

74.95

88.99

95.24

100

4.1.1. Sediment properties The mean grain size of tsunami deposits is the primary explanatory variable in this dataset, as demonstrated by the PCA and HCA results. The size of particles transported by water waves is a function of the size and type of material available for transport and the energy of the wave, as well as the balance of tractive force and sediment cohesion in the substrate (van Rijn, 1984a). The energy of a large tsunami wave is sufficient to mobilise any type of sediment up to and including boulder size (e.g. Nandasena et al., 2013; Nott, 2003; Paris et al., 2010), therefore relationships between particle size and environmental variables must be interpreted with this in mind. HCA results suggest a marked differentiation between large-clast deposits and finer sediments (Fig. 5), then further divides the entries based on climatic variables and distance from source. This provides a basis for the order of interpretation when considering the influence of each external variable on sediment texture.

Fig. 3. Scatterplot matrix of relationships between variables, with regression lines plotted in red.

C.L. Kain et al. / Marine Geology 368 (2015) 1–14

7

Fig. 4. a) PCA loading plot of variables along components 1 and 2 (accounting for 58% of total variance), showing the spatial relationship of the variables along these dimensions. b) Score plot, showing individual data points plotted in coordinate space along components 1 and 2.

Fig. 5. Graphical representation of cluster analysis results. a) Cluster dendrogram showing structure of the dataset from Ward's hierarchical cluster analysis. b) Factor plot of individuals and clusters along the axes of greatest variance. c) 3-dimensional plot of clusters on the factor map, showing linkages between individuals via the dendrogram.

8

C.L. Kain et al. / Marine Geology 368 (2015) 1–14

Table 5 Results of hierarchical cluster analysis, showing the mean value of each variable in each cluster. Data were scaled to a mean of 0 and a standard deviation of approximately 1 prior to cluster analysis, so means calculated within each cluster can be compared to these reference values. Defining characteristics for each cluster are highlighted in red. Mean value in cluster 1

2

3

4

Mean grain size

–2.67936

–0.45186

0.94272

1.08812

Mean monthly precipitation

–1.43121

1.097397

0.278774

–1.30845

Mean monthly temperature

0.023961

0.484584

–1.24835

0.416002

Sediment density

0.745364

–0.23427

0.801064

–0.74972

Protection factor

–0.00301

0.047501

–0.02645

–0.04802

Distance from tsunami source

–0.15762

0.086598

0.071896

–0.1295

Sediment density is an inherent property of the deposited material and was most strongly related to grain size in the correlation and PCA results (Tables 3 and 4). This can primarily be explained by differences between boulder deposits and finer material. Deposits composed of large clasts (cobbles and boulders) in this dataset are commonly lower density material, which we would expect to be more easily transported than large clasts of heavier mineralogy. However, many other factors contribute to the transportability of boulders, including wave form, pre-transport setting and sediment volume within the wave (Etienne et al., 2011; Nott, 2003), and this may explain the only moderate strength of the calculated correlation. Interestingly, in some cases where higher density material was transported by tsunamis, the origin of that material was man-made beachfront structures such as concrete walls (e.g. Goto et al., 2012) or basaltic rip-rap revetments (e.g. Goff et al., 2006); the availability of which is primarily anthropogenically rather than environmentally controlled. The number of boulder entries in this database was also relatively small, but these findings agree with existing site-specific research and we are therefore confident that this relationship is genuine. For example, Paris et al. (2010) found significant differences in tsunami-transported boulder sizes in Lhok Nga, Indonesia, depending on source and composition. Density is also a factor when considering the spatial distribution of boulder deposits in the dataset. Larger clasts are more common in the coastal environments of mid-high latitude regions, as a result of Pleistocene paraglacial processes and lower rates of chemical weathering (Hayes, 1967), but boulder deposits in this database show no corresponding spatial trend. This is likely a consequence of the effect of latitude and climate on the mineralogy and thus density of sediments available for transport, with equatorial regions producing low-density coral-derived material and more biogenic sediments than mid-high latitudes, which are dominated by higher-density lithics (Hayes, 1967). The relative increased availability of coarse sediments in midhigh latitudes may be effectively cancelled out by the increased transportability of coral boulders at lower latitudes in the statistical analysis presented here. However, it is important to note that boulder availability in tropical environments is not limited to low-density material and, in particular, high density basalt material is commonly transported by tsunamis on volcanic tropical islands (e.g. Etienne et al., 2011; Goff et al., 2006). The connection between mineralogy, sediment density and grain size in sand-sized tsunami deposits is more complex, unlike the comparatively strong relationship in boulder emplacement. The sandy deposits in this dataset were most commonly in the range of 2.6– 2.8 g cm−3, dominated by silicates and carbonates, so this lack of diversity alone may mask the presence of any weak relationship. However, because the entrainment threshold for loose sand (Paphitis, 2001) is so much less than the force of a large tsunami wave, the role of density in explaining grain size variation in the finer-grained database entries is likely to be negligible. There is still some consideration required when interpreting deposition from suspension, as density affects settling

velocity and thus sediment transport by suspension load (van Rijn, 1984b), but wave dynamics are likely to be more important than sediment properties in controlling finer-grained deposit form. Tsunami deposition usually occurs at least partially from suspension, inferred from the common presence of normal grading and mud caps in tsunami deposits and modelling of deposition processes (e.g. Goto et al., 2011; Jaffe and Gelfenbaum, 2007; Witter et al., 2012). Such structures have been commonly described as indicators of tsunami deposition (Goff et al., 2012) and further statistical work may be able to address trends in detailed sedimentary structures and textural variations. 4.1.2. Environmental properties affecting deposition Relationships are also evident in the correlation and/or PCA analyses between mean grain size and the other four factors studied: mean monthly temperature, mean monthly precipitation, distance from source and protection factor. In contrast to sediment density, these parameters do not represent inherent properties of the deposited sediment, but are rather indicative of depositional controls. Moreover, these environmental factors are not independent of each other, as results of the correlation and PCA show. This suggests that their influence on tsunami deposit sedimentology is complex and interactive. The inverse relationship between mean grain size and protection factor can be explained by the capability of highly embayed environments to dissipate tsunami wave energy and prevent larger clasts from being transported. Interrogation of individual data point locations on the PCA factor map and scatterplots suggests that this statistical relationship results from the contrast between highly embayed fjord environments (particularly around the Cascadia region) and straight coasts where boulder deposition was concentrated. This relationship was statistically weak, which is consistent with modelling and observational studies of tsunami wave behaviour. Although boulder deposition does occur more frequently on open coasts with a gentle slope (Goto et al., 2009), embaymentisation in conjunction with steeper slopes has been shown to cause amplification rather than attenuation of tsunami waves in many cases (e.g. Bellotti et al., 2012; Didenkulova and Pelinovsky, 2011; Mori et al., 2011). The protective capacity of reef features has also been questioned and in some cases has been shown to trap tsunami wave energy rather than reduce it, via resonance and amplification (Gelfenbaum et al., 2011; Roeber et al., 2010). Reef environments in this dataset gave rise to both boulder and fine-sediment deposits, which we consider to be a function of sediment availability in terms of sand-sized material and coral boulders. Antecedent morphology may also compound this relationship, as highly embayed beaches and reef-fringed lagoons are generally less exposed to ocean swell and storm waves, except in cases of specific swell approach direction and/or wave period. This would maximise the availability of finer sediments for tsunami transport in the beach and nearshore environment through initial control by local geology, rainfall and fluvial activity (Hayes, 1967; Masselink and Hughes, 2003). Continental lithology not only determines the composition of the tsunami deposit, but also controls coastal configuration on a geological timescale through erodibility of the rock and coastal type, which is partially accounted for in the Protection Factor parameter. PCA results suggest that the mean grain size of tsunami deposits and distance from tsunami source contribute inversely to the variance along the first principal component. This finding can be partially explained by refraction and diffraction as the waves travel long distances and encounter landmasses and bathymetric changes (Okal, 1988; Titov et al., 2005). However, these two variables were not correlated in Spearman's correlation analysis. This is likely due to oversimplification of the relationship, as modelling research suggests that bathymetry and coastal configuration at the inundation site and bathymetry across the travel distance are the controlling factors of tsunami wave height at a farfield location (Hébert et al., 2001; Okal, 1988; Okal et al., 2014; Titov et al., 2005). This statistical relationship is also particularly sensitive to researcher bias, as much historical tsunami research has been

C.L. Kain et al. / Marine Geology 368 (2015) 1–14

undertaken in response to large tsunamis (e.g. 2004 IOT and the 2011 ToT) and has largely focused on source-adjacent coastlines. Since subduction zones tend to be more frequently responsible for large tsunamis than other source mechanisms (Ward, 2002), it is expected that more tsunami deposits would be identified adjacent to these zones than elsewhere and this is supported by the spatial distribution of tsunami deposits in this dataset (Fig. 1). Palaeotsunami research also remains most concentrated adjacent to large subduction zones, volcanic ridges (e.g. the Hawaiian Islands) or submarine volcanoes (Goff et al., 2012). Determining a source for prehistoric deposits relies on dating techniques and correlation with seismic records and other deposits, which can result in large uncertainties. As a consequence of identification problems and source ambiguity, prehistoric deposits from far-field tsunami events are under-represented in this dataset, although substantial deposits from such events are known to exist (e.g. Gerardi et al., 2012; Goff et al., 2010a). Climate is described in this analysis by two separate variables; mean monthly temperature and mean monthly precipitation, which are inversely related to mean grain size along the second dimension of the PCA (Fig. 4, Table 4). Mean monthly temperature and mean monthly precipitation show a significant positive correlation, which can be explained by global climate patterns. When averaged over an annual timescale in the current climate, temperature and rainfall are higher in equatorial regions and lower in mid-high latitudes. However, this representation does not account for seasonal variation in temperature (important in mid-high latitudes) and rainfall (important in tropical regions) and this is a potential limitation in the interpretation of the climatic effects on tsunami deposit sedimentology and preservation. These two climate variables also show significant correlations with distance from tsunami source, but this correlation is most likely an artefact of the data, whereby source locations in equatorial regions are over-represented in the dataset. The impact of climate on mean grain size can be explained through processes that indirectly affect tsunami deposition and deposit preservation. Chemical weathering processes occur more rapidly in equatorial regions and so the particle size of sediments available for transport in the nearshore environment is likely to be smaller (Hayes, 1967), resulting in finer-grained tsunami deposits. These same processes affect deposit preservation following emplacement through interactions with other environmental processes such as aeolian and fluvial activity, particularly in the immediate aftermath of the event (Liew et al., 2010; Szczuciński, 2012). In particular, wind patterns are an important factor in mobilising exposed sand or fine tsunami sediments (Richmond et al., 2012; Spiske et al., 2013). Vegetation is also likely to provide an important link between climate and tsunami sedimentation and sediment preservation, affecting both onland inundation and stabilisation of the deposit post-event (Olwig et al., 2007; Tanaka et al., 2007). The timing of post-tsunami research was not considered in this study, which is a possibility for further investigation of this dataset alongside analysis of preservation level. The interpretation of particle size relationships is further complicated by the fact that tsunami deposits are composed of a range of particle sizes. Indeed, a fining inland trend is often cited as a defining characteristic of tsunami deposits (e.g. Fujiwara, 2008; Kortekaas and Dawson, 2007; Morton et al., 2007; Nichol et al., 2007; Peters et al., 2007; Sugawara et al., 2008). Silt and clay sized material was underrepresented in our analysis, since most tsunami deposits that are reported are dominated by sandy material. Deposits that contain boulders will almost always contain finer particles as well, either co-deposited with the boulders or occurring further inland where the tsunami wave loses energy (e.g. Goto et al., 2007; Goto et al., 2012; Paris et al., 2010) and the same trend applies to sandy deposits (e.g. Chagué-Goff et al., 2012a; Morton et al., 2007; Szczuciński et al., 2012). Furthermore, deposits are often composed of a set of layers related to separate tsunami waves or run-up and backwash sequences of the same wave, resulting in grain size variations (e.g. Matsumoto et al., 2010; Moore et al., 2011; Takashimizu et al., 2012). Such variability is not accounted

9

for in this research, because values of mean grain size were used as the particle size parameter and standard deviation values were not commonly reported, which limits the resolution of the analyses. However, these variations have been well studied at a local scale and, as the aim of this research is to investigate relationships on a broader scale, the assumption that mean grain size is representative of the entire deposit is unlikely to create significant errors. Thickness of tsunami deposits was not analysed, due to large potential variability in thickness within the same deposit in response to topographic control, distance from the coast and volume of material available for transport (e.g. Hori et al., 2007). We were unable to control for these drivers of deposit thickness and so we elected to omit thickness analyses from our methodology. 4.1.3. Process interactions and geomorphological control The local characteristics that control tsunami deposit geometry and composition are a function of broader-scale geomorphological processes that operate on a variety of timescales. Statistically, the relationships determined here are significant but remain weak to moderate, suggesting that environmental controls are complex and interactive. Ultimately, geology and climate control the composition and configuration of a coastline, which in turn affect tsunami propagation and inundation. Over long timescales, climatic variation and sea level changes become particularly important when considering tsunami source material, weathering processes and depositional distance from a coastline. For example, sediment transport rates increase in high latitudes during glacial periods (Hayes, 1967), which would result in different sediment availability conditions for a tsunami deposit emplaced at this time. Similarly, coral reef growth and sedimentation rates are highly sensitive to sea level and temperature changes (Buddemeier and Smith, 1988), thus affecting sediment availability in the tropics. A conceptual model of factors affecting tsunami deposit form can be constructed based on geomorphic factors, accounting for differences in temporal scale and the mechanism of influence on tsunami deposit form and composition (Fig. 6). The long term preservation of tsunami deposits requires consideration. Many of the entries in the database pertain to deposits studied immediately following a tsunami and thus the question arises as to whether or not these signatures are representative of what will be

Fig. 6. Timescale of influence of factors affecting tsunami deposit form. Variables are listed in black according to their sphere of influence. Red text in the small triangles refers to the mechanism that controls tsunami deposits during each timeframe.

10

C.L. Kain et al. / Marine Geology 368 (2015) 1–14

(or has been) preserved in the long term sedimentary record. As well as the influence of climate on weathering and erosion, processes such as compaction and bioturbation result in the blurring or loss of internal structure within tsunami deposits, making their interpretation more complicated. This can occur relatively quickly after deposition with the blurring of internal structures through root growth and animal bioturbation being observed as rapidly as one to two years after tsunami deposition (Nichol and Kench, 2008; Spiske et al., 2013; Szczuciński, 2012). It is therefore important to take care when interpreting older deposits using the same principles as those applied to fresh ones. Moreover, the impact of a tsunami does not always occur in isolation. A large tsunami often occurs alongside seismic-related landscape changes near the source, such as subsidence, uplift, liquefaction and sediment mobilisation. This may have a significant effect on the coastal environment and sediment transport patterns in the region for decades afterwards (Goff and Sugawara, 2014; Wells and Goff, 2007), although research following the 2004 IOT and 2011 ToT indicates that some sandy areas returned to a pre-event equilibrium relatively quickly (e.g. Choowong et al., 2007; Kain et al., 2014; Liew et al., 2010; Richmond et al., 2012). Erosion by large tsunamis or seismic-related changes may create a new morphology that functions differently to the pre-event environment, resulting in implications for deposit preservation. This idea has become increasingly prominent in recent years, as research has addressed geomorphic recovery following earthquakes and tsunamis (e.g. Liew et al., 2010; Kain et al., 2014; Paris et al., 2009; Spiske et al., 2013). Anthropogenic modification of coastal environments was also commonly observed following the 2004 IOT tsunami, as residents attempted to restore pre-event landscapes through sediment removal, building new infrastructure or re-vegetation (Szczuciński, 2012; Wong, 2009).

Tsunami research has developed extensively in the last decade in response to the 2004 IOT and 2011 ToT, moving towards a more interdisciplinary approach that incorporates geological, social and mathematical techniques. However, when compiling this database it became apparent that many publications do not contain sufficient data on the physical characteristics of the tsunami deposits to allow them to be included in databases or meta-analyses such as this study. Consequently, we encourage tsunami researchers to continue moving away from a descriptive approach (common in post-tsunami field surveys in particular) to a more robust set of analyses and data reporting that can advance tsunami science.

4.2. Implications for tsunami deposit research

References

In the context of this research, there is a bias towards recent events, particularly the 2004 IOT. Deposits were intensively researched following this event and much knowledge was gained in the field of tsunami research in the following years. The bias was enhanced in the database through systematic discarding of any events that were not confirmed to be tsunami-related, did not contain sufficient sedimentological data or were older than late Holocene. This led to the exclusion of much palaeotsunami research, as it would have been erroneous to analyse ancient deposits using measures of today's coastal configuration, temperature and climate. Palaeotsunami research has also historically been less prolific than research related to new events, due to difficulties with identification and the cost of undertaking palaeotsunami research (Goff and Chagué-Goff, 2014). Tsunami deposit research is further complicated by several biases, concerning geographical areas of research and convention of how and what to report. Several geographic areas are notably underrepresented in the database (Fig. 1), which can be due to either lack of research or the unsuitability of existing research for this analysis. For example, no entries occur in Australia despite the existence of work addressing tsunami deposits here. These publications are related to either ancient or disputed tsunamis, or did not contain sufficient numerical data for our purpose. As with many fields of research, researchers tend not to report null results, so we do not know where scientists may have looked and failed to find tsunami evidence. There are also challenges in the interpretation of ancient deposits, where the depositional environment is poorly understood, preservation level is low and the source event is unknown. This particularly applies to finer grained deposits, as often these are widespread immediately following an event and for several years afterwards, but experience varying levels of taphonomy over time (Goff et al., 2001; Spiske et al., 2013). Many papers report deposits immediately post-event and we urge caution in comparing these with their palaeotsunami counterparts.

Abe, T., Goto, K., Sugawara, D., 2012. Relationship between the maximum extent of tsunami sand and the inundation limit of the 2011 Tohoku-oki tsunami on the Sendai Plain, Japan. Sediment. Geol. 282, 142–150. Abramson, H.F., 1998. Evidence for tsunamis and earthquakes during the last 3500 years from Lagoon Creek, a coastal freshwater marsh, northern California (M.S. thesis), Humboldt State University (76 pp). Araoka, D., Inoue, M., Suzuki, A., Yokoyama, Y., Edwards, R.L., Cheng, H., Matsuzaki, H., Kan, H., Shikazono, N., Kawahata, H., 2010. Historic 1771 Meiwa tsunami confirmed by high‐resolution U/Th dating of massive Porites coral boulders at Ishigaki Island in the Ryukyus, Japan. Geochem. Geophys. Geosyst. 11, Q06014. http://dx.doi.org/ 10.1029/2009GC002893 (11 pp.). Arcos, M.E.M., MacInnes, B.T., Arreaga, P., Rivera-Hernandez, F., Weiss, R., Lynett, P., 2013. An amalgamated meter-thick sedimentary package enabled by the 2011 Tohoku tsunami in El Garrapatero, Galapagos Islands. Quat. Res. 80, 9–19. Atwater, B.F., 1992. Geologic evidence for earthquakes during the past 2000 years along the Copalis River, southern coastal Washington. J. Geophys. Res. Solid Earth 97, 1901–1919. Atwater, B.F., Hemphill-Haley, E., 1997. Recurrence intervals for great earthquakes of the past 3,500 years at northeastern Willapa Bay, Washington. U.S. Geological Survey Professional Paper 1576 (108 pp.). Atwater, B.F., Cisternas, V.M., Bourgeois, J., Dudley, W.C., Hendley, J., Stauffer, P.H., 1999. Surviving a tsunami: lessons from Chile, Hawaii, and Japan. US Geol. Sur. Circ. 1–18. Baeza, C., Corominas, J., 2001. Assessment of shallow landslide susceptibility by means of multivariate statistical techniques. Earth Surf. Process. Landf. 26, 1251–1263. Bahlburg, H., Spiske, M., 2012. Sedimentology of tsunami inflow and backflow deposits: key differences revealed in a modern example. Sedimentology 59, 1063–1086. Bahlburg, H., Weiss, R., 2007. Sedimentology of the December 26, 2004, Sumatra tsunami deposits in eastern India (Tamil Nadu) and Kenya. Int. J. Earth Sci. 96, 1195–1209. Banerjee, D., Murray, A., Foster, I., 2001. Scilly Isles, UK: optical dating of a possible tsunami deposit from the 1755 Lisbon earthquake. Quat. Sci. Rev. 20, 715–718. Becker-Heidmann, P., Reicherter, K., Silva, P.G., 2007. 14C-dated charcoal and sediment drilling cores as first evidence of Holocene tsunamis at the southern Spanish Coast. Radiocarbon 49, 827–835. Bellotti, G., Briganti, R., Beltrami, G., 2012. The combined role of bay and shelf modes in tsunami amplification along the coast. J. Geophys. Res. Oceans 117, C08027. http://dx.doi.org/10.1029/2012JC008061. Benson, B.E., Grimm, K.A., Clague, J.J., 1997. Tsunami deposits beneath tidal marshes on northwestern Vancouver Island, British Columbia. Quat. Res. 48, 192–204. Bertrand, M., Piegay, H., Pont, D., Liébault, F., Sauquet, E., 2013. Sensitivity analysis of environmental changes associated with riverscape evolutions following sediment reintroduction: geomatic approach on the Drome River network, France. Int. J. River Basin Manag. 11, 19–32.

5. Conclusions Relationships between tsunami deposit sedimentology and environmental controls were analysed using Spearman's rank-order correlation, Principal Component Analysis and Hierarchical Cluster Analysis. These connections are inherently understood by tsunami researchers and have been used to interpret and model individual deposits, but this research explores and quantifies them on a broader scale. Results show significant relationships between mean grain size of tsunami sediments and sediment density, degree of coastal protection (embaymentisation and sheltering) and climate parameters. In particular, boulder deposits were more likely to be composed of lower density material and occur on source-adjacent unprotected coasts, although no geographical patterns in location of tsunami boulder fields were evident. These relationships can be explained through the influence of the antecedent environment on coastal configuration and the source material available to be transported by the tsunami.

C.L. Kain et al. / Marine Geology 368 (2015) 1–14 Bondevik, S., Svendsen, J.I., Mangerud, J., 1997. Tsunami sedimentary facies deposited by the Storegga tsunami in shallow marine basins and coastal lakes, western Norway. Sedimentology 44, 1115–1131. Borradaile, G.J., 2003. Statistics of Earth Science Data: Their Distribution in Time, Space and Orientation. Springer, Berlin. Bourgeois, J., 2009. Geologic effects and records of tsunamis. The Sea. 15 pp. 55–91. Bourgeois, J., Petroff, C., Yeh, H., Titov, V., Synolakis, C.E., Benson, B., Kuroiwa, J., Lander, J., Norabuena, E., 1999. Geologic setting, field survey and modeling of the Chimbote, Northern Peru, Tsunami of 21 February 1996. Pure Appl. Geophys. 154, 513–540. Bourgeois, J., Pinegina, T.K., Ponomareva, V., Zaretskaia, N., 2006. Holocene tsunamis in the southwestern Bering Sea, Russian Far East, and their tectonic implications. Geol. Soc. Am. Bull. 118, 449–463. Briggs, G.G., 1994. Coastal crossing of the elastic strain zero-isobase, Cascadia margin, south central Oregon coast (M.S. thesis), Portland State University (251 pp.). Brill, D., Brückner, H., Jankaew, K., Kelletat, D., Scheffers, A., Scheffers, S., 2011. Potential predecessors of the 2004 Indian Ocean Tsunami — sedimentary evidence of extreme wave events at Ban Bang Sak, SW Thailand. Sediment. Geol. 239, 146–161. Brill, D., Pint, A., Jankaew, K., Frenzel, P., Schwarzer, K., Vött, A., Brückner, H., 2014. Sediment transport and hydrodynamic parameters of tsunami waves recorded in onshore geoarchives. J. Coast. Res. 30 (5), 922–941. Bruins, H.J., MacGillivray, J.A., Synolakis, C.E., Benjamini, C., Keller, J., Kisch, H.J., Klügel, A., Van Der Plicht, J., 2008. Geoarchaeological tsunami deposits at Palaikastro (Crete) and the Late Minoan IA eruption of Santorini. J. Archaeol. Sci. 35, 191–212. Buddemeier, R., Smith, S., 1988. Coral reef growth in an era of rapidly rising sea level: predictions and suggestions for long-term research. Coral Reefs 7, 51–56. Carey, S., Morelli, D., Sigurdsson, H., Bronto, S., 2001. Tsunami deposits from major explosive eruptions: an example from the 1883 eruption of Krakatau. Geology 29, 347–350. Chagué-Goff, C., Dawson, S., Goff, J., Zachariasen, J., Berryman, K., Garnett, D., Waldron, H., Mildenhall, D., 2002. A tsunami (ca. 6300 years BP) and other Holocene environmental changes, northern Hawke's Bay, New Zealand. Sediment. Geol. 150, 89–102. Chagué-Goff, C., Schneider, J.-L., Goff, J.R., Dominey-Howes, D., Strotz, L., 2011. Expanding the proxy toolkit to help identify past events — lessons from the 2004 Indian Ocean Tsunami and the 2009 South Pacific Tsunami. Earth Sci. Rev. 107, 107–122. Chagué-Goff, C., Andrew, A., Szczuciński, W., Goff, J., Nishimura, Y., 2012a. Geochemical signatures up to the maximum inundation of the 2011 Tohoku-oki tsunamiimplications for the 869 AD Jogan and other palaeotsunamis. Sediment. Geol. 282, 65–77. Chagué-Goff, C., Goff, J., Nichol, S., Dudley, W., Zawadzki, A., Bennett, J., Mooney, S., Fierro, D., Heijnis, H., Dominey-Howes, D., 2012b. Multi-proxy evidence for trans-Pacific tsunamis in the Hawai'ian Islands. Mar. Geol. 299, 77–89. Chagué-Goff, C., Niedzielski, P., Wong, H.K., Szczuciński, W., Sugawara, D., Goff, J., 2012c. Environmental impact assessment of the 2011 Tohoku-oki tsunami on the Sendai plain. Sediment. Geol. 282, 175–187. Choowong, M., Murakoshi, N., Hisada, K., Charusiri, P., Daorerk, V., Charoentitirat, T., Chutakositkanon, V., Jankaew, K., Kanjanapayont, P., 2007. Erosion and deposition by the 2004 Indian Ocean tsunami in Phuket and Phang-nga Provinces, Thailand. J. Coast. Res. 23 (5), 1270–1276. Choowong, M., Murakoshi, N., Hisada, K.-i, Charusiri, P., Charoentitirat, T., Chutakositkanon, V., Jankaew, K., Kanjanapayont, P., Phantuwongraj, S., 2008. 2004 Indian Ocean tsunami inflow and outflow at Phuket, Thailand. Mar. Geol. 248, 179–192. Cisternas, M., Atwater, B.F., Torrejón, F., Sawai, Y., Machuca, G., Lagos, M., Eipert, A., Youlton, C., Salgado, I., Kamataki, T., 2005. Predecessors of the giant 1960 Chile earthquake. Nature 437, 404–407. Clague, J.J., Bobrowsky, P.T., 1994. Tsunami deposits beneath tidal marshes on Vancouver Island, British Columbia. Geol. Soc. Am. Bull. 106, 1293–1303. Clague, J.J., Hutchinson, I., Mathewes, R.W., Patterson, R.T., 1999. Evidence for late Holocene tsunamis at Catala Lake, British Columbia. J. Coast. Res. 15, 45–60. Cochran, U., Berryman, K., Mildenhall, D., Hayward, B., Southall, K., Hollis, C., 2005. Towards a record of Holocene tsunami and storms for northern Hawke's Bay, New Zealand. N. Z. J. Geol. Geophys. 48, 507–515. Costa, P., Andrade, C., Freitas, M., Oliveira, M., Lopes, V., Dawson, A., Moreno, J., Fatela, F., Jouanneau, J., 2012a. A tsunami record in the sedimentary archive of the central Algarve coast, Portugal: characterizing sediment, reconstructing sources and inundation paths. The Holocene 22, 899–914. Costa, P.J.M., Leroy, S.A.G., Dinis, J.L., Dawson, A.G., Kortekaas, S., 2012b. Recent highenergy marine events in the sediments of Lagoa de óbidos and Martinhal (Portugal): recognition, age and likely causes. Nat. Hazards Earth Syst. Sci. 12, 1367–1380. Cuven, S., Paris, R., Falvard, S., Miot-Noirault, E., Benbakkar, M., Schneider, J.-L., Billy, I., 2013. High-resolution analysis of a tsunami deposit: case-study from the 1755 Lisbon tsunami in southwestern Spain. Mar. Geol. 337, 98–111. Dawson, A., 1994. Geomorphological effects of tsunami run-up and backwash. Geomorphology 10, 83–94. Dawson, A.G., Shi, S., 2000. Tsunami deposits. Pure Appl. Geophys. 157, 875–897. Dawson, A.G., Shi, S., Dawson, S., Takahashi, T., Shuto, N., 1996. Coastal sedimentation associated with the June 2nd and 3rd, 1994 tsunami in Rajegwesi, Java. Quat. Sci. Rev. 15, 901–912. De Martini, P.M., Burrato, P., Pantosti, D., Maramai, A., Graziani, L., Abramson, H., Geomatrix Consultants, C., 2003. Identification of tsunami deposits and liquefaction features in the Gargano area (Italy): paleoseismological implication. Ann. Geophys. 46 (5), 883–902. De Martini, P.M., Barbano, M.S., Smedile, A., Gerardi, F., Pantosti, D., Del Carlo, P., Pirrotta, C., 2010. A unique 4000 year long geological record of multiple tsunami inundations in the Augusta Bay (eastern Sicily, Italy). Mar. Geol. 276, 42–57.

11

Didenkulova, I., Pelinovsky, E., 2011. Runup of tsunami waves in U-shaped bays. Pure Appl. Geophys. 168, 1239–1249. Dominey-Howes, D., Cundy, A., Croudace, I., 2000. High energy marine flood deposits on Astypalaea Island, Greece: possible evidence for the AD 1956 southern Aegean tsunami. Mar. Geol. 163, 303–315. Dunbar, P., McCullough, H., 2012. Global tsunami deposits database. Nat. Hazards 63, 267–278. Engel, M., Brückner, H., 2011. The identification of palaeo-tsunami deposits — a major challenge in coastal sedimentary research. Coastline Reports. 17 pp. 65–80. Etienne, S., Buckley, M., Paris, R., Nandasena, A.K., Clark, K., Strotz, L., Chagué-Goff, C., Goff, J., Richmond, B., 2011. The use of boulders for characterising past tsunamis: lessons from the 2004 Indian Ocean and 2009 South Pacific tsunamis. Earth Sci. Rev. 107, 76–90. Font, E., Veiga-Pires, C., Pozo, M., Nave, S., Costas, S., Ruiz Muñoz, F., Abad, M., Simões, N., Duarte, S., Rodríguez-Vidal, J., 2013. Benchmarks and sediment source(s) of the 1755 Lisbon tsunami deposit at Boca do Rio Estuary. Mar. Geol. 343, 1–14. Foster, I., Albon, A., Bardell, K., Fletcher, J., Jardine, T., Pritchard, M., Turner, S., 1991. High energy coastal sedimentary deposits; an evaluation of depositional processes in southwest England. Earth Surf. Process. Landf. 16, 341–356. Fujino, S., Naruse, H., Matsumoto, D., Jarupongsakul, T., Sphawajruksakul, A., Sakakura, N., 2009. Stratigraphic evidence for pre-2004 tsunamis in southwestern Thailand. Mar. Geol. 262, 25–28. Fujino, S., Naruse, H., Matsumoto, D., Sakakura, N., Suphawajruksakul, A., Jarupongsakul, T., 2010. Detailed measurements of thickness and grain size of a widespread onshore tsunami deposit in Phang‐nga Province, southwestern Thailand. Island Arc 19, 389–398. Fujiwara, O., 2008. Bedforms and sedimentary structures characterizing tsunami deposits. In: Shiki, T., Tsuji, Y., Minoura, K., Yamazaki, T. (Eds.), Tsunamiites — Features and Implications. Elsevier Science B.V., Berlin, pp. 51–62. Fujiwara, O., Ono, E., Yata, T., Umitsu, M., Sato, Y., Heyvaert, V., 2013. Assessing the impact of 1498 Meio earthquake and tsunami along the Enshu-nada coast, central Japan using coastal geology. Quat. Int. 308, 4–12. Gelfenbaum, G., Jaffe, B., 2003. Erosion and sedimentation from the 17 July, 1998 Papua New Guinea tsunami. Pure Appl. Geophys. 160, 1969–1999. Gelfenbaum, G., Apotsos, A., Stevens, A.W., Jaffe, B., 2011. Effects of fringing reefs on tsunami inundation: American Samoa. Earth Sci. Rev. 107, 12–22. Gerardi, F., Smedile, A., Pirrotta, C., Barbano, M., De Martini, P., Pinzi, S., Gueli, A., Ristuccia, G., Stella, G., Troja, S., 2012. Geological record of tsunami inundations in Pantano Morghella (south-eastern Sicily) both from near and far-field sources. Nat. Hazards Earth Syst. Sci. 12, 1185–1200. Goff, J., 2008. The New Zealand Palaeotsunami Database. NIWA Technical Report 131 (1174–2631, 24 pp. + Appendix.). Goff, J., Chagué-Goff, C., 2014. The Australian tsunami database: a review. Prog. Phys. Geogr. 38, 218–240. Goff, J., Sugawara, D., 2014. Seismic-driving of sand beach ridge formation in northern Honshu, Japan? Mar. Geol. 358, 138–149. Goff, J., Chagué-Goff, C., Nichol, S., 2001. Palaeotsunami deposits: a New Zealand perspective. Sediment. Geol. 143, 1–6. Goff, J., McFadgen, B., Chagué-Goff, C., 2004. Sedimentary differences between the 2002 Easter storm and the 15th-century Okoropunga tsunami, southeastern North Island, New Zealand. Mar. Geol. 204, 235–250. Goff, J., Dudley, W., Demaintenon, M., Cain, G., Coney, J., 2006. The largest local tsunami in 20th century Hawaii. Mar. Geol. 226, 65–79. Goff, J., Nichol, S., Chagué-Goff, C., Horrocks, M., McFadgen, B., Cisternas, M., 2010a. Predecessor to New Zealand's largest historic trans-South Pacific tsunami of 1868 AD. Mar. Geol. 275, 155–165. Goff, J., Pearce, S., Nichol, S.L., Chagué-Goff, C., Horrocks, M., Strotz, L., 2010b. Multi-proxy records of regionally-sourced tsunamis, New Zealand. Geomorphology 118, 369–382. Goff, J., Chagué-Goff, C., Dominey-Howes, D., McAdoo, B., Cronin, S., Bonté-Grapetin, M., Nichol, S., Horrocks, M., Cisternas, M., Lamarche, G., 2011. Palaeotsunamis in the Pacific Islands. Earth Sci. Rev. 107, 141–146. Goff, J., Chagué-Goff, C., Nichol, S., Jaffe, B., Dominey-Howes, D., 2012. Progress in palaeotsunami research. Sediment. Geol. 243, 70–88. Goto, K., Chavanich, S.A., Imamura, F., Kunthasap, P., Matsui, T., Minoura, K., Sugawara, D., Yanagisawa, H., 2007. Distribution, origin and transport process of boulders deposited by the 2004 Indian Ocean tsunami at Pakarang Cape, Thailand. Sediment. Geol. 202, 821–837. Goto, K., Okada, K., Imamura, F., 2009. Importance of the initial waveform and coastal profile for tsunami transport of boulders. Pol. J. Environ. Stud. 18 (1), 53–61. Goto, K., Chagué-Goff, C., Fujino, S., Goff, J., Jaffe, B., Nishimura, Y., Richmond, B., Sugawara, D., Szczuciński, W., Tappin, D.R., Witter, R.C., Yulianto, E., 2011. New insights of tsunami hazard from the 2011 Tohoku-oki event. Mar. Geol. 290, 46–50. Goto, K., Sugawara, D., Ikema, S., Miyagi, T., 2012. Sedimentary processes associated with sand and boulder deposits formed by the 2011 Tohoku-oki tsunami at Sabusawa Island, Japan. Sediment. Geol. 282, 188–198. Hawkes, A.D., Bird, M., Cowie, S., Grundy-Warr, C., Horton, B.P., Shau Hwai, A.T., Law, L., Macgregor, C., Nott, J., Ong, J.E., 2007. Sediments deposited by the 2004 Indian Ocean tsunami along the Malaysia–Thailand Peninsula. Mar. Geol. 242, 169–190. Hayes, M.O., 1967. Relationship between coastal climate and bottom sediment type on the inner continental shelf. Mar. Geol. 5, 111–132. Hébert, H., Heinrich, P., Schindelé, F., Piatanesi, A., 2001. Far‐field simulation of tsunami propagation in the Pacific Ocean: impact on the Marquesas Islands (French Polynesia). J. Geophys. Res. Oceans 106, 9161–9177. Hemphill-Haley, E., 1995. Diatom evidence for earthquake-induced subsidence and tsunami 300 yr ago in southern coastal Washington. Geol. Soc. Am. Bull. 107, 367–378.

12

C.L. Kain et al. / Marine Geology 368 (2015) 1–14

Hentry, C., Chandrasekar, N., Saravanan, S., Dajkumar Sahayam, J., 2010. Influence of geomorphology and bathymetry on the effects of the 2004 tsunami at Colachel, South India. Bull. Eng. Geol. Environ. 69, 431–442. Higman, B., Bourgeois, J., 2008. Deposits of the 1992 Nicaragua tsunami. In: Shiki, T., Tsuji, Y., Minoura, K., Yamazaki, T. (Eds.), Tsunamiites — Features and Implications. Elsevier Science B.V., Berlin, pp. 81–104. Hijmans, R.J., Cameron, S.E., Parra, J.L., Jones, P.G., Jarvis, A., 2005. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25, 1965–1978. Hindson, R., Andrade, C., 1999. Sedimentation and hydrodynamic processes associated with the tsunami generated by the 1755 Lisbon earthquake. Quat. Int. 56, 27–38. Hindson, R., Andrade, C., Dawson, A., 1996. Sedimentary processes associated with the tsunami generated by the 1755 Lisbon earthquake on the Algarve coast, Portugal. Phys. Chem. Earth 21, 57–63. Hori, K., Kuzumoto, R., Hirouchi, D., Umitsu, M., Janjirawuttikul, N., Patanakanog, B., 2007. Horizontal and vertical variation of 2004 Indian tsunami deposits: an example of two transects along the western coast of Thailand. Mar. Geol. 239, 163–172. Horton, B.P., Sawai, Y., Hawkes, A.D., Witter, R.C., 2011. Sedimentology and paleontology of a tsunami deposit accompanying the great Chilean earthquake of February 2010. Mar. Micropaleontol. 79, 132–138. Hutchinson, I., Clague, J.J., Mathewes, R.W., 1997. Reconstructing the tsunami record on an emerging coast: a case study of Kanim Lake, Vancouver Island, British Columbia, Canada. J. Coast. Res. 13 (2), 545–553. Hutchinson, I., Guilbault, J.P., Clague, J.J., Bobrowsky, P.T., 2000. Tsunamis and tectonic deformation at the northern Cascadia margin: a 3000-year record from Deserted Lake, Vancouver Island, British Columbia, Canada. The Holocene 10, 429–439. Jaffe, B.E., Gelfenbaum, G., 2007. A simple model for calculating tsunami flow speed from tsunami deposits. Sediment. Geol. 200, 347–361. Jaffe, B., Gelfenbaum, G., Rubin, D., Peters, R., Anima, R., Swensson, M., Olcese, D., Anticona, L.B., Gomez, J.C., Riega, P.C., 2003. Identification and interpretation of tsunami deposits from the June 23, 2001 Peru tsunami. Proceedings of the International Conference on Coastal Sediments 2003. Corpus Christi, TX, USA (981-238-422-7, 13 pp.). Jaffe, B.E., Borrero, J.C., Prasetya, G.S., Peters, R., McAdoo, B., Gelfenbaum, G., Morton, R., Ruggiero, P., Higman, B., Dengler, L., Hidayat, R., Kingsley, E., Kongko, W., Lukiyanto, Moore, A., Titov, V., Yulianto, E., 2006. The December 26th 2004 Indian Ocean tsunami in Northwest Sumatra and Offshore Islands. Earthquake Spectra 22 (S3), 105–135. Jaffe, B.E., Gelfenbaum, G., Buckley, M.L., Watt, S., Apotsos, A., Stevens, A.W., Richmond, B.M., 2010. The limit of inundation of the September 29, 2009, tsunami on Tutuila, American Samoa. U.S. Geological Survey Open-File Report 2010–1018 (27 pp.). Jaffe, B., Buckley, M., Richmond, B., Strotz, L., Etienne, S., Clark, K., Watt, S., Gelfenbaum, G., Goff, J., 2011. Flow speed estimated by inverse modeling of sandy sediment deposited by the 29 September 2009 tsunami near Satitoa, east Upolu, Samoa. Earth Sci. Rev. 107, 23–37. Jaffe, B.E., Goto, K., Sugawara, D., Richmond, B.M., Fujino, S., Nishimura, Y., 2012. Flow speed estimated by inverse modeling of sandy tsunami deposits: Results from the 11 March 2011 tsunami on the coastal plain near the Sendai Airport, Honshu, Japan. Sediment. Geol. 282, 90–109. Jagodziński, R., Sternal, B., Szczuciński, W., Lorenc, S., 2009. Heavy minerals in 2004 tsunami deposits on Kho Khao Island, Thailand. Pol. J. Environ. Stud. 18 (1), 103–110. Jagodziński, R., Sternal, B., Szczuciński, W., Chagué-Goff, C., Sugawara, D., 2012. Heavy minerals in the 2011 Tohoku-oki tsunami deposits-insights into sediment sources and hydrodynamics. Sediment. Geol. 282, 57–64. Jankaew, K., Martin, M.E., Sawai, Y., Prendergast, A.L., 2011. Sand sheets on a beach-ridge plain in Thailand: identification and dating of tsunami deposits in a far-field tropical setting. In: Mörner, N.A. (Ed.), The Tsunami Threat — Research and Technology, pp. 299–324 http://dx.doi.org/10.5772/573 (InTech). Kain, C.L., Gomez, C., Lavigne, F., Wassmer, P., Hart, D.E., 2014. Truncated dunes as evidence of the 2004 tsunami in North-Sumatra and environmental recovery one year post-tsunami. N. Z. Geogr. 70, 165–178. Kelsey, H., Witter, R., Polenz, M., 1993. Cascadia paleoseismic record derived from late Holocene fluvial and lake sediments, Sixes River valley, Cape Blanco, south coastal Oregon. Eos Trans. Am. Geophys. Union 74, 43. Kelsey, H.M., Nelson, A.R., Hemphill-Haley, E., 1995. Properties and depositional characteristics of tsunamis in south coastal Oregon from a paired coastal-lake and marsh study. Tsunami Deposits: Geologic Warnings of Future inundation. University of Washington, p. 20. Kelsey, H.M., Witter, R.C., Hemphill-Haley, E., 1998. Response of a small Oregon estuary to coseismic subsidence and postseismic uplift in the past 300 years. Geology 26, 231–234. Kelsey, H.M., Nelson, A.R., Hemphill-Haley, E., Witter, R.C., 2005. Tsunami history of an Oregon coastal lake reveals a 4600 yr record of great earthquakes on the Cascadia subduction zone. Geol. Soc. Am. Bull. 117, 1009–1032. Kench, P.S., McLean, R.F., Brander, R.W., Nichol, S.L., Smithers, S.G., Ford, M.R., Parnell, K.E., Aslam, M., 2006. Geological effects of tsunami on mid-ocean atoll islands: the Maldives before and after the Sumatran tsunami. Geology 34, 177–180. Kench, P., Nichol, S., Smithers, S., McLean, R., Brander, R., 2008. Tsunami as agents of geomorphic change in mid-ocean reef islands. Geomorphology 95, 361–383. Kitamura, A., Fujiwara, O., Shinohara, K., Akaike, S., Masuda, T., Ogura, K., Urano, Y., Kobayashi, K., Tamaki, C., Mori, H., 2013. Identifying possible tsunami deposits on the Shizuoka Plain, Japan and their correlation with earthquake activity over the past 4000 years. The Holocene 23, 1684–1698. Komac, M., 2006. A landslide susceptibility model using the Analytical Hierarchy Process method and multivariate statistics in perialpine Slovenia. Geomorphology 74, 17–28. Kortekaas, S., Dawson, A.G., 2007. Distinguishing tsunami and storm deposits: an example from Martinhal, SW Portugal. Sediment. Geol. 200, 208–221. Kottek, M., Grieser, J., Beck, C., Rudolf, B., Rubel, F., 2006. World map of the Koppen-Geiger climate classification updated. Meteorol. Z. 15, 259–264.

Lambert, J., Terrier, M., 2011. Historical tsunami database for France and its overseas territories. Nat. Hazards Earth Syst. Sci. 11, 1037–1046. Li, W., 1992. Evidence for the late Holocene coseismic subsidence in the lower Eel River Valley, Humboldt county, northern California: an application of foraminiferal zonation to indicate tectonic submergence (M.S. thesis), Humboldt State University (80 pp.). Liew, S.C., Gupta, A., Wong, P.P., Kwoh, L.K., 2010. Recovery from a large tsunami mapped over time: the Aceh coast, Sumatra. Geomorphology 114, 520–529. López, G.I., 2012. Evidence for mid-to late-Holocene palaeotsunami deposits, Kakawis Lake, Vancouver Island, British Columbia. Nat. Hazards 60, 43–68. López, G.I., Bobrowsky, P.T., 2001. A 14,000 year-old-record from a coastal freshwater lake: sedimentological evidence for tsunamigenic events on the west coast of Vancouver Island, British Columbia, Canada. IUGG Tsunami Commission, NOAA, USGS. International Tsunami Symposium, Seattle, Washington, pp. 491–500. MacInnes, B.T., Bourgeois, J., Pinegina, T.K., Kravchunovskaya, E.A., 2009. Tsunami geomorphology: erosion and deposition from the 15 November 2006 Kuril Island tsunami. Geology 37, 995–998. Maouche, S., Morhange, C., Meghraoui, M., 2009. Large boulder accumulation on the Algerian coast evidence tsunami events in the western Mediterranean. Mar. Geol. 262, 96–104. Masselink, G., Hughes, M.G., 2003. Introduction to Coastal Processes and Geomorphology. Arnold, Hodder Headline Group, London (354 pp.). Mastronuzzi, G., Pignatelli, C., Sansò, P., Selleri, G., 2007. Boulder accumulations produced by the 20th of February, 1743 tsunami along the coast of southeastern Salento (Apulia region, Italy). Mar. Geol. 242, 191–205. Matsumoto, D., Naruse, H., Fujino, S., Surphawajruksakul, A., Jarupongsakul, T., Sakakura, N., Murayama, M., 2008. Truncated flame structures within a deposit of the Indian Ocean Tsunami: evidence of syn‐sedimentary deformation. Sedimentology 55, 1559–1570. Matsumoto, D., Shimamoto, T., Hirose, T., Gunatilake, J., Wickramasooriya, A., DeLile, J., Young, S., Rathnayake, C., Ranasooriya, J., Murayama, M., 2010. Thickness and grainsize distribution of the 2004 Indian Ocean tsunami deposits in Periya Kalapuwa Lagoon, eastern Sri Lanka. Sediment. Geol. 230, 95–104. McFadgen, B.G., Goff, J.R., 2007. Tsunamis in the New Zealand archaeological record. Sediment. Geol. 200, 263–274. Medina, F., Mhammdi, N., Chiguer, A., Akil, M., Jaaidi, E.B., 2011. The Rabat and Larache boulder fields; new examples of high-energy deposits related to storms and tsunami waves in north-western Morocco. Nat. Hazards 59 (2), 725–747. Minor, R., Grant, W.C., 1996. Earthquake-induced subsidence and burial of late Holocene archaeological sites, northern Oregon coast. Am. Antiq. 61 (4), 772–781. Minoura, K., Nakata, T., 1994. Discovery of an ancient tsunami deposit in coastal sequences of southwest Japan: verification of a large historic tsunami. Island Arc 3, 66–72. Minoura, K., Nakaya, S., 1991. Traces of tsunami preserved in inter-tidal lacustrine and marsh deposits: some examples from northeast Japan. J. Geol. 99, 265–287. Minoura, K., Gusiakov, V.G., Kurbatov, A., Takeuti, S., Svendsen, J.I., Bondevik, S., Oda, T., 1996. Tsunami sedimentation associated with the 1923 Kamchatka earthquake. Sediment. Geol. 106, 145–154. Minoura, K., Imamura, F., Takahashi, T., Shuto, N., 1997. Sequence of sedimentation processes caused by the 1992 Flores tsunami: evidence from Babi Island. Geology 25, 523–526. Minoura, K., Hirano, S.-i., Yamada, T., 2013. Identification and possible recurrence of an oversized tsunami on the Pacific coast of northern Japan. Nat. Hazards 68, 631–643. Monecke, K., Finger, W., Klarer, D., Kongko, W., McAdoo, B.G., Moore, A.L., Sudrajat, S.U., 2008. A 1,000-year sediment record of tsunami recurrence in northern Sumatra. Nature 455, 1232–1234. Moore, A., Nishimura, Y., Gelfenbaum, G., Kamataki, T., Triyono, R., 2006. Sedimentary deposits of the 26 December 2004 tsunami on the northwest coast of Aceh, Indonesia. Earth Planets Space 58, 253–258. Moore, A.L., McAdoo, B.G., Ruffman, A., 2007. Landward fining from multiple sources in a sand sheet deposited by the 1929 Grand Banks tsunami, Newfoundland. Sediment. Geol. 200, 336–346. Moore, A., Goff, J., McAdoo, B.G., Fritz, H.M., Gusman, A., Kalligeris, N., Kalsum, K., Susanto, A., Suteja, D., Synolakis, C.E., 2011. Sedimentary deposits from the 17 July 2006 Western Java Tsunami, Indonesia: use of grain size analyses to assess tsunami flow depth, speed, and traction carpet characteristics. Pure Appl. Geophys. 168, 1951–1961. Mori, N., Takahashi, T., Yasuda, T., Yanagisawa, H., 2011. Survey of 2011 Tohoku earthquake tsunami inundation and run‐up. Geophys. Res. Lett. 38, L00G14. http://dx.doi.org/10.1029/2011GL049210. Morton, R.A., Gelfenbaum, G., Jaffe, B.E., 2007. Physical criteria for distinguishing sandy tsunami and storm deposits using modern examples. Sediment. Geol. 200, 184–207. Morton, R.A., Goff, J.R., Nichol, S.L., 2008. Hydrodynamic implications of textural trends in sand deposits of the 2004 tsunami in Sri Lanka. Sediment. Geol. 207, 56–64. Morton, R.A., Gelfenbaum, G., Buckley, M.L., Richmond, B.M., 2011. Geological effects and implications of the 2010 tsunami along the central coast of Chile. Sediment. Geol. 242, 34–51. Nakamura, Y., Nishimura, Y., Putra, P.S., 2012. Local variation of inundation, sedimentary characteristics, and mineral assemblages of the 2011 Tohoku-oki tsunami on the Misawa coast, Aomori, Japan. Sediment. Geol. 282, 216–227. Nanayama, F., Shigeno, K., 2006. Inflow and outflow facies from the 1993 tsunami in southwest Hokkaido. Sediment. Geol. 187, 139–158. Nanayama, F., Shigeno, K., Satake, K., Shimokawa, K., Koitabashi, S., Miyasaka, S., Ishii, M., 2000. Sedimentary differences between the 1993 Hokkaido-nansei-oki tsunami and the 1959 Miyakojima typhoon at Taisei, southwestern Hokkaido, northern Japan. Sediment. Geol. 135, 255–264.

C.L. Kain et al. / Marine Geology 368 (2015) 1–14 Nanayama, F., Furukawa, R., Shigeno, K., Makino, A., Soeda, Y., Igarashi, Y., 2007. Nine unusually large tsunami deposits from the past 4000 years at Kiritappu marsh along the southern Kuril Trench. Sediment. Geol. 200, 275–294. Nandasena, N.A.K., Paris, R., Tanaka, N., 2011. Numerical assessment of boulder transport by the 2004 Indian ocean tsunami in Lhok Nga, West Banda Aceh (Sumatra, Indonesia). Comput. Geosci. 37, 1391–1399. Nandasena, N., Tanaka, N., Sasaki, Y., Osada, M., 2013. Boulder transport by the 2011 Great East Japan tsunami: comprehensive field observations and whither model predictions? Mar. Geol. 346, 292–309. Narayana, A., Tatavarti, R., Shinu, N., Subeer, A., 2007. Tsunami of December 26, 2004 on the southwest coast of India: post-tsunami geomorphic and sediment characteristics. Mar. Geol. 242, 155–168. National Geophysical Data Center / World Data Service (NGDC/WDS), 2014. Global historical tsunami database. National Geophysical Data Center, NOAA http://dx.doi.org/10.7289/ V5PN93H7 (Accessed 13/06/2014). Nelson, A.R., Ota, Y., Umitsu, M., Kashima, K., Matsushima, Y., 1998. Seismic or hydrodynamic control of rapid late-Holocene sea-level rises in southern coastal Oregon, USA? The Holocene 8, 287–299. Nichol, S.L., Kench, P.S., 2008. Sedimentology and preservation potential of carbonate sand sheets deposited by the December 2004 Indian Ocean tsunami: South Baa Atoll, Maldives. Sedimentology 55, 1173–1187. Nichol, S.L., Goff, J.R., Devoy, R.J.N., Chagué-Goff, C., Hayward, B., James, I., 2007. Lagoon subsidence and tsunami on the West Coast of New Zealand. Sediment. Geol. 200, 248–262. Nichol, S.L., Chagué-Goff, C., Goff, J.R., Horrocks, M., McFadgen, B.G., Strotz, L.C., 2010. Geomorphology and accommodation space as limiting factors on tsunami deposition: Chatham Island, southwest Pacific Ocean. Sediment. Geol. 229, 41–52. Nishimura, Y., Miyaji, N., 1995. Tsunami deposits from the 1993 Southwest Hokkaido earthquake and the 1640 Hokkaido Komagatake eruption, northern Japan. Pure Appl. Geophys. 144, 719–733. Nott, J., 2003. Waves, coastal boulder deposits and the importance of the pre-transport setting. Earth Planet. Sci. Lett. 210, 269–276. Okal, E.A., 1988. Seismic parameters controlling far-field tsunami amplitudes: a review. Nat. Hazards 1, 67–96. Okal, E.A., Reymond, D., Hébert, H., 2014. From earthquake size to far-field tsunami amplitude: development of a simple formula and application to DART buoy data. Geophys. J. Int. 196, 340–356. Olwig, M., Sørensen, M., Rasmussen, M., Danielsen, F., Selvam, V., Hansen, L., Nyborg, L., Vestergaard, K., Parish, F., Karunagaran, V., 2007. Using remote sensing to assess the protective role of coastal woody vegetation against tsunami waves. Int. J. Remote Sens. 28, 3153–3169. Paphitis, D., 2001. Sediment movement under unidirectional flows: an assessment of empirical threshold curves. Coast. Eng. 43, 227–245. Paris, R., Lavigne, F., Wassmer, P., Sartohadi, J., 2007. Coastal sedimentation associated with the December 26, 2004 tsunami in Lhok Nga, west Banda Aceh (Sumatra, Indonesia). Mar. Geol. 238, 93–106. Paris, R., Wassmer, P., Sartohadi, J., Lavigne, F., Barthomeuf, B., Desgages, E., Grancher, D., Baumert, P., Vautier, F., Brunstein, D., 2009. Tsunamis as geomorphic crises: lessons from the December 26, 2004 tsunami in Lhok Nga, west Banda Aceh (Sumatra, Indonesia). Geomorphology 104, 59–72. Paris, R., Fournier, J., Poizot, E., Etienne, S., Morin, J., Lavigne, F., Wassmer, P., 2010. Boulder and fine sediment transport and deposition by the 2004 tsunami in Lhok Nga (western Banda Aceh, Sumatra, Indonesia): a coupled offshore–onshore model. Mar. Geol. 268, 43–54. Peters, R., Jaffe, B., 2010a. Identification of tsunami deposits in the geologic record; developing criteria using recent tsunami deposits. U.S. Geological Survey Open-File Report 2010–1239 (38 pp.). Peters, R., Jaffe, B.E., 2010b. Database of recent tsunami deposits. US Geological Survey Open-File Report 2010–1172 (12 pp.). Peters, R., Jaffe, B., Gelfenbaum, G., Peterson, C., 2003. Cascadia tsunami deposit database. US Geological Survey Open-File Report 03–13. Department of the Interior (24 pp.). Peters, R., Jaffe, B., Gelfenbaum, G., 2007. Distribution and sedimentary characteristics of tsunami deposits along the Cascadia margin of western North America. Sediment. Geol. 200, 372–386. Peterson, C.D., Jol, H.M., Horning, T., Cruikshank, K.M., 2010. Paleotsunami inundation of a beach ridge plain: Cobble ridge overtopping and interridge valley flooding in Seaside, Oregon, USA. J. Geol. Res. http://dx.doi.org/10.1155/2010/276989 (2010, Article ID 276989, 22 pp.). Peterson, C.D., Carver, G.A., Cruikshank, K.M., Abramson, H.F., Garrison‐Laney, C.E., Dengler, L.A., 2011. Evaluation of the use of paleotsunami deposits to reconstruct inundation distance and runup heights associated with prehistoric inundation events, Crescent City, southern Cascadia margin. Earth Surf. Process. Landf. 36, 967–980. Peterson, C.D., Clague, J.J., Carver, G.A., Cruikshank, K.M., 2013. Recurrence intervals of major paleotsunamis as calibrated by historic tsunami deposits in three localities: Port Alberni, Cannon Beach, and Crescent City, along the Cascadia margin, Canada and USA. Nat. Hazards 68, 321–336. Pignatelli, C., Sans, P., Mastronuzzi, G., 2009. Evaluation of tsunami flooding using geomorphologic evidence. Mar. Geol. 260, 6–18. Praus, P., 2006. Water quality assessment using SVD-based principal component analysis of hydrological data. Water SA 31, 417–422. Putra, P.S., Nishimura, Y., Yulianto, E., 2013. Sedimentary features of tsunami deposits in carbonate-dominated beach environments: a case study from the 25 October 2010 Mentawai Tsunami. Pure Appl. Geophys. 170, 1583–1600. Ramsey, P.H., 1989. Critical values for Spearman's rank order correlation. J. Educ. Behav. Stat. 14, 245–253.

13

Razjigaeva, N., Ganzey, L., Grebennikova, T., Ivanova, E., Kharlamov, A., Kaistrenko, V., Arslanov, K.A., Chernov, S., 2014. The Tohoku Tsunami of 11 March 2011: the key event to understanding tsunami sedimentation on the coasts of closed bays of the Lesser Kuril Islands. Pure Appl. Geophys. 171, 3307–3328. Razzhigaeva, N., Ganzei, L., Grebennikova, T., Ivanova, E., Kaistrenko, V., 2006. Sedimentation particularities during the tsunami of December 26, 2004, in northern Indonesia: Simelue Island and the Medan coast of Sumatra Island. Oceanology 46, 875–890. Reinhart, M., 1991. Sedimentological analysis of postulated tsunami-generated deposits from Cascadia great-subduction earthquakes along southern coastal Washington (M.S. thesis), University of Washington Department of Geological Sciences (83 pp.). Reinhart, M., Bourgeois, J., 1987. Distribution of anomalous sand at Willapa Bay, Washington-Evidence for large-scale landward-directed processes, Eos. Trans. Am. Geophys. Union 68 (44), 1469. Richmond, B.M., Buckley, M., Etienne, S., Chagué-Goff, C., Clark, K., Goff, J., DomineyHowes, D., Strotz, L., 2011. Deposits, flow characteristics, and landscape change resulting from the September 2009 South Pacific tsunami in the Samoan islands. Earth Sci. Rev. 107, 38–51. Richmond, B., Szczuciński, W., Chagué-Goff, C., Goto, K., Sugawara, D., Witter, R., Tappin, D.R., Jaffe, B., Fujino, S., Nishimura, Y., 2012. Erosion, deposition and landscape change on the Sendai coastal plain, Japan, resulting from the March 11, 2011 Tohoku-oki tsunami. Sediment. Geol. 282, 27–39. Rodríguez-Vidal, J., Cáceres, L., Abad, M., Ruiz, F., González-Regalado, M., Finlayson, C., Finlayson, G., Fa, D., Rodríguez-Llanes, J., Bailey, G., 2011. The recorded evidence of AD 1755 Atlantic tsunami on the Gibraltar coast. J. Iber. Geol. 37, 177–193. Roeber, V., Yamazaki, Y., Cheung, K.F., 2010. Resonance and impact of the 2009 Samoa tsunami around Tutuila, American Samoa. Geophys. Res. Lett. 37, L21604. http://dx. doi.org/10.1029/2010GL044419. Romundset, A., Bondevik, S., 2011. Propagation of the Storegga tsunami into ice‐free lakes along the southern shores of the Barents Sea. J. Quat. Sci. 26, 457–462. Sakuna, D., Szczucinski, W., Feldens, P., Schwarzer, K., Khokiattiwong, S., 2012. Sedimentary deposits left by the 2004 Indian Ocean tsunami on the inner continental shelf offshore of Khao Lak, Andaman Sea (Thailand). Earth Planets Space 64, 931–943. Sato, H., Shimamoto, T., Tsutsumi, A., Kawamoto, E., 1995. Onshore tsunami deposits caused by the 1993 Southwest Hokkaido and 1983 Japan Sea earthquakes. Pure Appl. Geophys. 144, 693–717. Sato, T., Nakamura, N., Goto, K., Kumagai, Y., Nagahama, H., Minoura, K., 2014. Paleomagnetism reveals the emplacement age of tsunamigenic coral boulders on Ishigaki Island, Japan. Geology 42 (10). http://dx.doi.org/10.1130/G35366.1. Sawai, Y., Fujii, Y., Fujiwara, O., Kamataki, T., Komatsubara, J., Okamura, Y., Satake, K., Shishikura, M., 2008. Marine incursions of the past 1500 years and evidence of tsunamis at Suijin-numa, a coastal lake facing the Japan Trench. The Holocene 18, 517–528. Scheucher, L.E.A., Vortisch, W., 2010. Sedimentological and geomorphological effects of the Sumatra–Andaman Tsunami in the area of Khao Lak, southern Thailand. Environ. Earth Sci. 63 (4), 785–796. Schlichting, R.B., 2000. Establishing the inundation distance and overtopping height of paleotsunami from the late-Holocene geologic record at open-coastal wetland sites, central Cascadia margin (Masters Thesis), Portland State University (166 pp.). Schneider, J.-L., Chagué-Goff, C., Bouchez, J.-L., Goff, J., Sugawara, D., Goto, K., Jaffe, B., Richmond, B., 2014. Using magnetic fabric to reconstruct the dynamics of tsunami deposition on the Sendai Plain, Japan — the 2011 Tohoku-oki tsunami. Mar. Geol. 358, 89–106. Schuenemeyer, J., Drew, L., 2011. Statistics for earth and environmental scientists. Wiley, Hoboken (407 pp.). Scicchitano, G., Monaco, C., Tortorici, L., 2007. Large boulder deposits by tsunami waves along the Ionian coast of south-eastern Sicily (Italy). Mar. Geol. 238, 75–91. Shanmugam, G., 2012. Process-sedimentological challenges in distinguishing paleotsunami deposits. Nat. Hazards 63, 5–30. Shi, S., Smith, D., 2003. Coastal tsunami geomorphological impacts and sedimentation processes: Case studies of modern and prehistorical events. Proceedings of the International Conference on Estuaries and Coasts, Hangzhou, pp. 189–198. Shi, S., Dawson, A.G., Smith, D.E., 1995. Coastal sedimentation associated with the December 12th, 1992 tsunami in Flores, Indonesia,. Pure Appl. Geophys. 144, 526–536. Shiki, T., Tsuji, Y., Yamazaki, T., Minoura, K., 2008. Tsunamiites: Features and Implications. Elsevier, Oxford (425pp.). Short, A.D., 1996. The role of wave height, period, slope, tide range and embaymentisation in beach classifications: a review. Rev. Chil. Hist. Nat. 69, 589–604. Smedile, A., 2012. Combining inland and offshore paleotsunamis evidence: the Augusta Bay (eastern Sicily, Italy) case study. Nat. Hazards Earth Syst. Sci. 12, 2557–2567. Smith, D., Shi, S., Cullingford, R., Dawson, A.G., Dawson, S., Firth, C., Foster, I.D.L., Fretwell, P., Haggart, B., Holloway, L., 2004. The Holocene storegga slide tsunami in the United Kingdom. Quat. Sci. Rev. 23, 2291–2321. Smith, D.E., Foster, I.D.L., Long, D., Shi, S., 2007. Reconstructing the pattern and depth of flow onshore in a palaeotsunami from associated deposits. Sediment. Geol. 200, 362–371. Spiske, M., Weiss, R., Bahlburg, H., Roskosch, J., Amijaya, H., 2010. The TsuSedMod inversion model applied to the deposits of the 2004 Sumatra and 2006 Java tsunami and implications for estimating flow parameters of palaeo-tsunami. Sediment. Geol. 224, 29–37. Spiske, M., Piepenbreier, J., Benavente, C., Bahlburg, H., 2013. Preservation potential of tsunami deposits on arid siliciclastic coasts. Earth Sci. Rev. 126, 58–73. Srinivasalu, S., Thangadurai, N., Switzer, A.D., Ram Mohan, V., Ayyamperumal, T., 2007. Erosion and sedimentation in Kalpakkam (N Tamil Nadu, India) from the 26th December 2004 tsunami. Mar. Geol. 240, 65–75.

14

C.L. Kain et al. / Marine Geology 368 (2015) 1–14

Srinivasalu, S., Rajeshwara Rao, N., Thangadurai, N., Jonathan, M., Roy, P., Ram Mohan, V., Saravanan, P., 2009. Characteristics of 2004 tsunami deposits of the northern Tamil Nadu coast, southeastern India. Bol. Soc. Geol. Mex. 61, 111–118. Srisutam, C., Wagner, J.F., 2009. Reconstructing tsunami run-up from the characteristics of tsunami deposits on the Thai Andaman Coast. Coast. Eng. 57, 493–499. Sugawara, D., Minoura, K., Imamura, F., Takahashi, T., Shuto, N., 2005. A huge sand dome formed by the 1854 earthquake tsunami in Suruga Bay, central Japan. ISET J. Earthq. Technol. 42, 147–158. Sugawara, D., Minoura, K., Imamura, F., 2008. Tsunamis and tsunami sedimentology. In: Shiki, T., Tsuji, Y., Minoura, K., Yamazaki, T. (Eds.), Tsunamiites — Features and Implications. Elsevier Science B.V., Berlin, pp. 9–49. Sugawara, D., Goto, K., Imamura, F., Matsumoto, H., Minoura, K., 2012. Assessing the magnitude of the 869 Jogan tsunami using sedimentary deposits: prediction and consequence of the 2011 Tohoku-oki tsunami. Sediment. Geol. 282, 14–26. Sugawara, D., Imamura, F., Goto, K., Matsumoto, H., Minoura, K., 2013. The 2011 Tohokuoki Earthquake Tsunami: similarities and differences to the 869 Jogan Tsunami on the Sendai Plain. Pure Appl. Geophys. 170, 831–843. Switzer, A.D., Jones, B.G., 2008. Large-scale washover sedimentation in a freshwater lagoon from the southeast Australian coast: sea-level change, tsunami or exceptionally large storm? The Holocene 18, 787–803. Szczuciński, W., 2012. The post-depositional changes of the onshore 2004 tsunami deposits on the Andaman Sea coast of Thailand. Nat. Hazards 60, 115–133. Szczuciński, W., Niedzielski, P., Rachlewicz, G., Sobczyński, T., Zioła, A., Kowalski, A., Lorenc, S., Siepak, J., 2005. Contamination of tsunami sediments in a coastal zone inundated by the 26 December 2004 tsunami in Thailand. Environ. Geol. 49, 321–331. Szczuciński, W., Chaimanee, N., Niedzielski, P., Rachlewicz, G., Saisuttichai, D., Tepsuwan, T., Lorenc, S., Siepak, J., 2006. Environmental and geological impacts of the 26 December 2004 Tsunami in coastal zone of Thailand — overview of short and long-term effects. Pol. J. Environ. Stud. 15 (5), 793–810. Szczuciński, W., Kokociński, M., Rzeszewski, M., Chagué-Goff, C., Cachão, M., Goto, K., Sugawara, D., 2012. Sediment sources and sedimentation processes of 2011 Tohoku-oki tsunami deposits on the Sendai Plain, Japan-insights from diatoms, nannoliths and grain size distribution. Sediment. Geol. 282, 40–56. Takashimizu, Y., Urabe, A., Suzuki, K., Sato, Y., 2012. Deposition by the 2011 Tohoku-oki tsunami on coastal lowland controlled by beach ridges near Sendai, Japan. Sediment. Geol. 282, 124–141. Tanaka, N., Sasaki, Y., Mowjood, M.I.M., Jinadasa, K.B.S.N., Homchuen, S., 2007. Coastal vegetation structures and their functions in tsunami protection: experience of the recent Indian Ocean tsunami. Landsc. Ecol. Eng. 3, 33–45. Tanigawa, K., Sawai, Y., Shishikura, M., Namegaya, Y., Matsumoto, D., 2014. Geological evidence for an unusually large tsunami on the Pacific coast of Aomori, northern Japan. J. Quat. Sci. 29, 200–208. Tappin, D.R., 2007. Sedimentary features of tsunami deposits — their origin, recognition and discrimination: an introduction. Sediment. Geol. 200, 151–154. Thoms, M.C., Parsons, M., 2003. Identifying spatial and temporal patterns in the hydrological character of the Condamine–Balonne River, Australia, using multivariate statistics. River Res. Appl. 19, 443–457.

Tinti, S., Maramai, A., Graziani, L., 2004. The new catalogue of Italian tsunamis. Nat. Hazards 33, 439–465. Titov, V., Rabinovich, A.B., Mofjeld, H.O., Thomson, R.E., González, F.I., 2005. The global reach of the 26 December 2004 Sumatra tsunami. Science 309, 2045–2048. Tuttle, M.P., Ruffman, A., Anderson, T., Jeter, H., 2004. Distinguishing tsunami from storm deposits in eastern North America: the 1929 Grand Banks tsunami versus the 1991 Halloween storm. Seismol. Res. Lett. 75, 117–131. van Rijn, L.C., 1984a. Sediment transport, part I: bed load transport. J. Hydraul. Eng. 110, 1431–1456. van Rijn, L.C., 1984b. Sediment transport, part II: suspended load transport. J. Hydraul. Eng. 110, 1613–1641. Veness, C., 2011. Calculate distance and bearing between two Latitude/Longitude points using Haversine formula in JavaScript. http://www. movable-type. co. ukscriptslatlong. htmldiakses pada (Accessed August 30th 2014.). Ward, S., 2002. Tsunamis. In: Meyers, R. (Ed.), Academic Press, pp. 175–191. Wells, A., Goff, J., 2007. Coastal dunes in Westland, New Zealand, provide a record of paleoseismic activity on the Alpine fault. Geology 35, 731–734. Williams, H., Hutchinson, I., 2000. Stratigraphic and microfossil evidence for late Holocene tsunamis at Swantown marsh, Whidbey Island, Washington. Quat. Res. 54, 218–227. Witter, R.C., 1999. Late Holocene paleoseismicity, tsunamis and relative sea-level changes along the south-central Cascadia subduction zone, southern Oregon (Ph.D. thesis), University of Oregon (152 pp.). Witter, R., Kelsey, H., 1994. Abrupt late Holocene relative sea-level changes in three coastal marshes along the southern Oregon portion of the Cascadia Subduction Zone. Eos. Trans. AGU 75, 621–622. Witter, R.C., Jaffe, B., Zhang, Y., Priest, G., 2012. Reconstructing hydrodynamic flow parameters of the 1700 tsunami at Cannon Beach, Oregon, USA. Nat. Hazards 63, 223–240. Wong, P., 2009. Impacts and recovery from a large tsunami: coasts of Aceh. Pol. J. Environ. Stud. 18, 5–16. Yamada, M., Fujino, S., Goto, K., 2014. Deposition of sediments of diverse sizes by the 2011 Tohoku-oki tsunami at Miyako City, Japan. Mar. Geol. 358, 67–78. Yawsangratt, S., Szczuciński, W., Chaimanee, N., Jagodzinski, R., Lorenc, S., Chatprasert, S., Saisuttichai, D., Tepsuwan, T., 2009. Depositional effects of 2004 Tsunami and hypothetical paleotsunami near Thap Lamu Navy Base in Phang Nga Province, Thailand. Pol. J. Environ. Stud. 18 (1), 17–23. Yongming, H., Peixuan, D., Junji, C., Posmentier, E.S., 2006. Multivariate analysis of heavy metal contamination in urban dusts of Xi'an, Central China. Sci. Total Environ. 355, 176–186. Yoshii, T., Imamura, M., Matsuyama, M., Koshimura, S., Matsuoka, M., Mas, E., Jimenez, C., 2013. Salinity in soils and tsunami deposits in areas affected by the 2010 Chile and 2011 Japan tsunamis. Pure Appl. Geophys. 170 (6–8), 1047–1066. Zhang, Q., Li, Z., Zeng, G., Li, J., Fang, Y., Yuan, Q., Wang, Y., Ye, F., 2009. Assessment of surface water quality using multivariate statistical techniques in red soil hilly region: a case study of Xiangjiang watershed, China. Environ. Monit. Assess. 152, 123–131.