Volume estimate of flow-type landslides along carbonatic and volcanic slopes in Campania (Southern Italy)

Recent studies on flow-type landslides in pyroclastic deposits have been performed to identify potential source areas and the main depositional mechanisms. Interesting methods for mapping landslide susceptibility have also been proposed. Since the potential volume of flow-type landslides is a measure of event magnitude, hence of considerable use in hazard assessment, we propose a method to estimate the potential volume for the morphometric analysis of 213 flow-like landslides occurred in Campania in recent centuries. First, our data show that the height, H, of the detachment and erosion-transport zones (i.e. the difference in height between the top of source area and a point, the first break at the foot of the slope, where the deposition stars to take place and the landslide loses velocity) and the area, A _f, of the same zones are linked by a mathematical function. Secondly, only part of the entire thickness of the pyroclastic material on the slope is involved. To define the potential volumes of the flow-type landslides, we analysed slopes, both in volcanic and carbonatic contexts, considering both channelled and unchannelled flow-type landslides. The most susceptible areas are identified by using a landslide-triggering susceptibility map, and then in each case the height H was estimated. This height is the difference in level between the point on the slope with highest susceptibility and the first break at the foot of the slope. Using the statistical correlation between H and A _f, both calculated for historical landslides, we evaluate the area of a potential landslide on a slope. Finally, potential volumes are calculated by using A _f and a constant thickness of the pyroclastic cover for the whole slope. This method could represent a useful tool to detect the main areas where risk mitigation works are required.     

Landslide management in the UK—the problem of managing hazards in a ‘low-risk’ environment

The UK is a country with limited direct experience of natural disasters. Whilst landslide losses are not negligible and fatalities are rare, accounts are under-reported. Financial losses from landslides are poorly understood but likely to be considerably in excess of £10 million per year. As a result, a strategic management framework has evolved based upon small, low-impact events punctuated by occasional larger events or larger landslides affecting urban areas. We present an overview of the different landslide management mechanisms in the UK and discuss them in context of cases studies to explore their effectiveness. We conclude with three issues that may have implications for landslide management in the UK and other ‘low-risk’ countries. Firstly, the evidence base by which landslide hazards and risks are measured is insufficient and limitations in existing information need to be better understood. Secondly, existing guidance on strategic and responsive management needs to be assessed for its fitness for purpose. Thirdly, we encourage debate about the importance of near misses.     

A simple numerical procedure for timely prediction of precipitation-induced landslides in unsaturated pyroclastic soils

In the last 20 years, several catastrophic precipitation-induced landslides have hit villages, towns and roads in Campania (southern Italy), causing extensive damage and many fatalities. Although such phenomena have occurred since time immemorial, recent urbanisation and infrastructural development have produced a major increase in landslide risk. Due to climatic changes and further unavoidable increases in exposure, in the near future, the risk will become even greater. It is therefore high time to develop reliable criteria for landslide prediction. The paper discusses the main factors which affect the triggering of precipitation-induced landslides, highlighting the key role played by antecedent rainfalls which cannot be precisely accounted for using empirical criteria. We propose a simple 1D numerical approach able to predict the evolution of the key factors governing slope stability as a tool to predict the onset of slope failure, with potential benefits for early warning systems. The approach is calibrated through a well-documented case history.     

Spatial and temporal analysis of a fatal landslide inventory in China from 1950 to 2016

Landslides result in severe casualties every year in China. However, there are few historical fatal landslide catalogs available to quantitatively assess the impact as well as the temporal and spatial patterns of landslides. The Fatal Landslide Event Inventory of China (FLEIC), which spans from 1950 to 2016, was compiled based on multiple data sources. The inventory contains 1911 non-seismically triggered landslides, which resulted in a total of 28,139 deaths in China during 1950–2016. The occurrence frequency of fatal landslides presented significantly different trends for different grades of events. Very large fatal landslide events (fatalities >?=?30) were on the rise during 1950–1999 and declined from 2000 to 2016. The decreasing trend after 2000 can be attributed to the increase in landslide mitigation investments. The small and medium-sized fatal landslide events (fatalities <?10) showed a significant increasing trend between 1950 and 2016, especially during the period of 2000–2016. This significant increasing trend is partly due to the improvement of the availability of landslide data online and may also be related to other factors including an increase in extreme precipitation events, the effects of land urbanization, and so on. This suggested that the inherent incompleteness of the landslide time series should be considered when analyzing. The fatal landslides mainly occurred between April and September (82.15%), which is consistent with the monthly precipitation variation in China. Spatially, most of the fatal landslides occurred in 14 provinces: five southwestern provinces (Yunnan, Sichuan, Guangxi, Guizhou, and Chongqing), five southeastern provinces (Hunan, Guangdong, Fujian, Jiangxi, and Zhejiang), Shaanxi and Shanxi, Hubei and Gansu. These 14 provinces account for 86% of the total fatal landslides and their associated fatalities. The spatial association between the fatal landslide density and possible influencing factors was assessed based on a geographical detector method. The results showed that the interacting factors between the precipitation and topography, soil, lithology, vegetation and population density are more closely related to the spatial distribution of fatal landslides than each individual factor.     

Fatal landslides in Europe

Landslides are a major hazard causing human and large economic losses worldwide. However, the quantification of fatalities and casualties is highly underestimated and incomplete, thus, the estimation of landslide risk is rather ambitious. Hence, a spatio-temporal distribution of deadly landslides is presented for 27 European countries over the last 20  years (1995–2014). Catastrophic landslides are widely distributed throughout Europe, however, with a great concentration in mountainous areas. In the studied period, a total of 1370 deaths and 784 injuries were reported resulting from 476 landslides. Turkey showed the highest fatalities with 335. An increasing trend of fatal landslides is observed, with a pronounced number of fatalities in the latest period from 2008 to 2014. The latter are mostly triggered by natural extreme events such as storms (i.e., heavy rainfall), earthquakes, and floods and only minor by human activities, such as mining and excavation works. Average economic loss per year in Europe is approximately 4.7 billion Euros. This study serves as baseline information for further risk mapping by integrating deadly landslide locations, local land use data, and will therefore help countries to protect human lives and property.     

Is there a tolerable level of risk from natural hazards in New Zealand?

Following the 2010 and 2011 earthquake and aftershocks in Canterbury, New Zealand, extensive research was carried out on the rockfall hazard to residential buildings on Christchurch's Port Hills. To determine which dwellings faced an unacceptable risk to life safety, the recommendation was made to adopt a tolerable threshold for individual risk of 1/10,000 p.a. (10^?4 p.a.). The 10^?4 p.a. threshold has subsequently been considered for application to other natural hazards. However, this threshold is far too high. It is about 35 times higher than the post-colonial historic average for natural hazards, it is 100 times greater than New Zealand's structural design standard for new buildings and it is 10–100 times greater than the risk tolerated by comparable jurisdictions for existing and new risks, respectively. A more appropriate threshold for the risk from natural hazards is within the range from 10^?5 p.a. for existing exposure to 10^?6 p.a. for new exposure. The reason for adopting this arbitrarily high threshold for rock roll hazard appeared to be to balance an overestimation of calculated risk given the large uncertainties inherent in the data. However, there are some concerns if this acceptance criterion is applied to other natural hazards where underlying risk might be more accurately estimated.     

Application of a GIS-aided method for the assessment of volcaniclastic soil sliding susceptibility to sample areas of Campania (Southern Italy)

A significant part of Campania is extensively covered by volcaniclastic soils, deriving from the alteration of airfall-sedimented formations of layered ashes and pumices that were ejected by Campi Flegrei and Mt. Somma–Vesuvius during explosive eruptions. Where such soils cover steep slopes cut in carbonate bedrock, landforms depend essentially on the morpho-evolution of such slopes prior to the deposition of the volcaniclastic soils, because these are generally present only as thin veneers, up to a few meters of total thickness. Historical records and local literature testify that, in this part of Campania, landslides that originate on carbonate slopes covered by such soils and terminate at their foot or at gully outlets are frequent, following critical rainfall events. Such landslides can be classified as complex, occurring initially as debris slides, but rapidly evolving into debris avalanches and/or debris flows. The localization of the initial sliding areas (i.e. “sources”) on the slopes depends on both the spatial distribution of characters of the soil cover and the spatial distribution of the triggering rainfall events. It therefore appears reasonable to separate the two aspects of the problem and focus on the former one, in order to attempt an assessment of soil sliding susceptibility in the event of landslide-triggering rainfall. In this paper, some results of the application of a method aimed at such an assessment are presented. The method, called SLIDE (from SLiding Initiation areas DEtection), is based on the concept that, for a spatially homogeneous soil cover and a spatially homogeneous landslide-triggering rainfall sequence, different values of threshold slope gradient for limit equilibrium conditions exist, depending on morphological characters of the soil cover, such as its continuity and planform curvature. The method is based on the assessment of (1) soil cover presence, (2) discontinuities within soil cover, (3) slope gradients and curvature, by means of good resolution DEMs. It has been applied to sample carbonate slopes of Campania, where landslides originated either repeatedly or recently. Results are encouraging, and a soil sliding susceptibility map of a large area, based on a simplified version of method, is also presented.     

Susceptibility analysis of shallow landslides source areas using physically based models

Rainfall-induced shallow landslides of the flow-type involve different soils, and they often cause huge social and economical disasters, posing threat to life and livelihood all over the world. Due to the frequent large extension of the rainfall events, these landslides can be triggered over large areas (up to tens of square kilometres), and their source areas can be analysed with the aid of distributed, physically based models. Despite the high potential, such models show some limitations related to the adopted simplifying assumptions, the quantity and quality of required data, as well as the use of a quantitative interpretation of the results. A relevant example is provided in this paper referring to catastrophic phenomena involving volcaniclastic soils that frequently occur in southern Italy. Particularly, three physically based models (SHALSTAB, TRIGRS and TRIGRS-unsaturated) are used for the analysis of the source areas of huge rainfall-induced shallow landslides occurred in May 1998 inside an area of about 60 km². The application is based on an extensive data set of topographical, geomorphological and hydrogeological features of the affected area, as well as on both stratigraphical settings and mechanical properties of the involved soils. The results obtained from the three models are compared by introducing two indexes aimed at quantifying the “success” and the “error” provided by each model in simulating observed source areas. Advantages and limitations of the adopted models are then discussed for their use in forecasting the rainfall-induced source areas of shallow landslides over large areas.     

Quantitative assessment of the residual risk in a rockfall protected area

Quantitative Risk Assessment (QRA) has become an indispensable tool for the management of landslide hazard and for planning risk mitigation measures. In this paper we present the evaluation of the rockfall risk at the Solà d’Andorra slope (Andorra Principality) before and after the implementation of risk mitigation works, in particular, the construction of protective fences. To calculate the risk level we have (i) identified the potential rockfall release areas, (ii) obtained the volume distribution of the falling rocks, (iii) determined the frequency of the rockfall events, and (iv) performed trajectographic analysis with a 3D numerical model (Eurobloc) that has provided both the expected travel distances and the kinetic energy of the blocks. The risk level at the developed area located at the foot of the rock cliff has been calculated taking into account the nature of the exposed elements and their vulnerability. In the Forat Negre basin, the most dangerous basin of the Solà d’Andorra, the construction of two lines of rockfall protection fences has reduced the annual probability of loss of life for the most exposed person inside the buildings, from 3.8×10⁻⁴ to 9.1×10⁻⁷ and the societal risk from 1.5×10⁻² of annual probability of loss of life to 1.2×10⁻⁵.     

Rainfall thresholds for prediction of shallow landslides around Chamoli-Joshimath region,Garhwal Himalayas,India

Majority of landslides in the Indian sub-continent are triggered by rainfall. Several attempts in the global scenario have been made to establish rainfall thresholds in terms of intensity-duration and antecedent rainfall models on global, regional and local scales for the occurrence of landslides. However, in the context of the Indian Himalayas, the rainfall thresholds for landslide occurrences are not yet understood fully. Neither on regional scale nor on local scale, establishing such rainfall thresholds for landslide occurrences in Indian Himalayas has yet been attempted. This paper presents an attempt towards deriving local rainfall thresholds for landslides based on daily rainfall data in and around Chamoli-Joshimath region of the Garhwal Himalayas, India. Around 128 landslides taken place in last 4 years from 2009 to 2012 have been studied to derive rainfall thresholds. Out of 128 landslides, however, rainfall events pertaining to 81 landslides were analysed to yield an empirical intensity–duration threshold for landslide occurrences. The rainfall threshold relationship fitted to the lower boundary of the landslide triggering rainfall events is I?=?1.82 D ^?0.23 (I?=?rainfall intensity in millimeters per hour and D?=?duration in hours). It is revealed that for rainfall events of shorter duration (≤24 h) with a rainfall intensity of 0.87 mm/h, the risk of landslide occurrence in this part of the terrain is expected to be high. Also, the role of antecedent rainfall in causing landslides was analysed by considering daily rainfall at failure and different period cumulative rainfall prior to failure considering all 128 landslides. It is observed that a minimum 10-day antecedent rainfall of 55 mm and a 20-day antecedent rainfall of 185 mm are required for the initiation of landslides in this area. These rainfall thresholds presented in this paper may be improved with the hourly rainfall data vis-à-vis landslide occurrences and also data of later years. However, these thresholds may be used in landslide warning systems for this particular region of the Garhwal Himalayas to guide the traffic and provide safety to the tourists travelling along this pilgrim route during monsoon seasons.     

Susceptibility regional zonation of earthquake-induced landslides in Campania,Southern Italy

In this paper, we present a GIS-based method for regional zoning of seismic-induced landslide susceptibility and show its application to the territory of the Campania region, Southern Italy. The method employs only three factors that we believe are most significant in the susceptibility assessment: the type of outcropping rock/soil, the slope angle, and the MCS intensity. Each of the three parameters is quantified in terms of relative weight expressed as indices, and the resulting Seismic Landslide Susceptibility index of an area is given by the average of the indices of the first two factors multiplied by the index of the third factor. The result of this susceptibility zonation applied to Campania shows a good agreement between the distribution of the historical earthquake-triggered landslides and the highly susceptible zones.     

Frequency–size relation of shallow debris slides on cut slopes along a railroad corridor: A case study from Nilgiri hills, Southern India

The probability of landslide volume, V _L , is a key parameter in the quantitative hazard analysis. Several studies have demonstrated that the non-cumulative probability density, p(V _L ), of landslide volumes obeys almost invariably a negative power law scaling of p(V _L ) for landslides exceeding a threshold volume and a roll-over of small landslides. Some researchers attributed the observed roll-over to under-sampling of data, while others relate it to a geo-morphological (physical) property of landslides. We analyzed 15 sets of a complete landslide inventory containing shallow debris slides (2 ≤ V _L  ≤ 3.6 × 10³ m³) with sources located on cut slopes along a 17-km-long railroad corridor. The 15 datasets belong to individual years from 1992 to 2007. We obtained the non-cumulative probability densities of landslide volumes for each dataset and analyzed the distribution pattern. The results indicate that for some datasets the probability density exhibits a negative power law distribution for all ranges of volume, while for others, the negative power scaling exists only for a volume greater than 10 m³, with scaling exponent β varying between 0.96 and 2.4. When the spatial distribution of landslides were analyzed in relation to the terrain condition and triggering rainfall, we observed that the number of landslides and the range and the frequency of volumes vary according to the changes in local terrain condition and the amount of rainfall that trigger landslides. We conclude that the probability density distribution of landslide volumes has a dependency on the local morphology and rainfall intensity and the deviation of small landslides from power law, i.e., the roll-over is a “real effect” and not an artifact due to sampling discrepancies.     

Contribution of the SISCam Web-based GIS to the seismotectonic study of Campania (Southern Apennines): an example of application to the Sannio-area

In this article the implementation and potential of the Seismotectonic Information System of the Campania Region (SISCam) are described, in particular an application of this Web-based GIS system to the seismotectonic analysis of the Sannio area (Southern Apennines) is performed. WEB-GIS technologies greatly contribute to both the environmental monitoring and the disaster management of areas affected by high natural risks. Specifically the SISCam system has been developed with the aim of providing easy access and fast diffusion, through Internet technology, of the most significant geological, geophysical, and territorial data relative to the Campania Region. The Sannio area has been selected as our application example because it is among the most active seismic regions in Italy. This portion of the Southern Apennines which was hit by the June 5, 1688 strong earthquake (M _W = 6.7, CPTI 1999) and by some low- and moderate-energy seismic sequences (1990–1992, 1997), is characterized by a complex inherited tectonic setting and low-tectonic deformation rates that hide the seismogenic sources position. Since this case study turned out to be complicated, the use of the SIScam WEB-GIS has become indispensable because it allowed us to visualize, integrate and analyze all the data available, in order to obtain an accurate and direct picture of the seismotectonic setting of the area. Moreover, a different approach of data analysis was necessary, due to the lack of up-to-date neotectonic and structural data; therefore, the operation of this GIS system enabled us to process and generate some original informative layers, through image analysis, such as new structural lineaments represented on a map of the potential active faults of the area, which has been the final result of our application, as a contribution to new knowledge about the local seismic risk parameters.     

Tsunami hazard evaluation for Kuwait and Arabian Gulf due to Makran Subduction Zone and Subaerial landslides

Given the recent historical disastrous tsunamis and the knowledge that the Arabian Gulf (AG) is tectonically active, this study aimed to evaluate tsunami hazards in Kuwait from both submarine earthquakes and subaerial landslides. Despite the low or unknown tsunami risks that impose potential threats to the coastal area’s infrastructures and population of Kuwait, such an investigation is important to sustain the economy and safety of life. This study focused on tsunamis generated by submarine earthquakes with earthquake magnitudes (M _w ) of 8.3–9.0 along the Makran Subduction Zone (MSZ) and subaerial landslides with volumes of 0.75–2.0 km³ from six sources along the Iranian coast inside the AG and one source at the Gulf entrance in Oman. The level of tsunami hazards associated with these tsunamigenic sources was evaluated using numerical modeling. Tsunami model was applied to conduct a numerical tsunami simulation and predict tsunami propagation. For landslide sources, a two-layer model was proposed to solve nonlinear longwave equations within two interfacing layers with appropriate kinematic and dynamic boundary conditions. Threat level maps along the coasts of the AG and Kuwait were developed to illustrate the impacts of potential tsunamis triggered by submarine earthquakes of different scales and subaerial landslides at different sources. GEBCO 30 arc-second grid data and others were used as bathymetry and topography data for numerical modeling. Earthquakes of M _w 8.3 and M _w 8.6 along the MSZ had low and considerable impacts, respectively, at the Gulf entrance, but negligible impacts on Kuwait. An earthquake of M _w 9.0 had a remarkable impact for the entire Gulf region and generated a maximum tsunami amplitude of up to 0.5 m along the Kuwaiti coastline 12 h after the earthquake. In the case of landslides inside the AG, the majority impact occurred locally near the sources. The landslide source opposite to Kuwait Bay generated the maximum tsunami amplitudes reaching 0.3 m inside Kuwait Bay and 1.8 m along the southern coasts of Kuwait.

     

四川九寨沟Ms7.0级地震滑坡应急快速评估

基于地震滑坡危险性评估的Newmark累积位移模型,利用震前获取的震区地形数据、区域地质资料,结合地震动近实时获取技术,开展了四川九寨沟M_s7.0级地震诱发滑坡的应急快速评估。地震滑坡位移分析结果表明,同震滑坡活动的中—高强度区分布在断层两侧宽约4 km的带状区域内,整体沿北西方向延伸。其中,极震区的丰雪塘、日则和干海子等城镇驻地及附近道路的滑坡强度相对较高;震前、震后影像对比表明九寨沟地震诱发的滑坡类型以浅表型碎屑流及小规模崩塌为主,且同震碎屑流多是在震前已有碎屑流的基础上进一步活动扩展而来,震后汛期泥石流隐患也不容忽视;通过典型地区滑坡位移分析结果与震前、震后影像对比,表明滑坡位移分析结果能够较好的反映同震滑坡的宏观分布特征,但在场地尺度上吻合程度欠佳,后续将通过提升岩性和地形等数据质量进行改进。研究结果可为灾情研判提供宝贵信息,对提高灾害应急救援效率具有重要意义。     

Distribution of landslides in southwest New Zealand

This study examines the size distribution of a regional medium-scale inventory of 778 landslides in the mountainous southwest of New Zealand. The spatial density of mapped landslides per unit area can be expressed as a negative power–law function of Landslide area A_L spanning three orders of magnitude (10^–2–10¹ km²). Although observed in other studies on landslide inventories, this relationship is surprising, given the lack of absolute ages, and thus uncertainty about the temporal observation window encompassed by the data. Large slope failures (arbitrarily defined here as having a total affected area A_L>1 km²) constitute 83% of the total affected landslide area A_LT. This dominance by area affects slope morphology, where large-scale landsliding reduces slope angles below the regional modal value of hillslopes, _mod39°. More numerous smaller and shallower failures tend to be superimposed on the pre-existing relief. Empirical scaling relationships show that large landslides involve >10⁶ m³ of material. The volumes V_L of individual preserved and presumably prehistoric (i.e. pre-1840) landslide deposits equate to 10⁰–10² years of total sediment production from shallow landsliding in the respective catchments, and up to 10³ years of contemporary regional sediment yield from the mountain ranges. Their presence in an erosional landscape indicates the geomorphic importance of landslides as temporary local sediment storage.     

Characteristics of moderate- to large-scale landslides triggered by the <Emphasis Type="Italic">M</Emphasis><Subscript><Emphasis Type="Italic">w</Emphasis></Subscript> 7.8 2015 Gorkha earthquake and its aftershocks

The M _w 7.8 2015 Gorkha earthquake and its aftershocks significantly impacted the lives and economy of Nepal. The consequences of landslides included fatalities, property losses, blockades of river flow, and damage to infrastructural systems. Co-seismic landslides triggered by this earthquake were significantly widespread and pose a major geodisaster. There were tens of thousands of landslides triggered by the earthquake, majority of which were distributed in between the epicenter of the main shock and the M _w 7.3 aftershock. Although 14,670 landslides triggered by this earthquake were identified, only approximately 23% of them were of moderate to large scale with areas greater than 100 m². Of the moderate- to large-scale landslides identified, just over 90% were triggered by the main shock and smaller aftershocks prior to the major (M _w 7.3) aftershock, while nearly 10% were triggered by the ground shaking induced by the major aftershock. Moreover, the number of landslides triggered by the 2015 Gorkha earthquake, specifically by the main shock, was slightly more than the expected number of landslides for the recorded maximum peak ground acceleration (PGA) in comparison to the co-seismic landslides triggered by 26 earthquakes. Over 90% of those moderate- to large-scale landslides were concentrated within the estimated fault rupture surface. Majority of these moderate- to large-scale landslides were disrupted failures with over 96% of which were classified as earth falls. However, the majority of small-scale landslides were rock or boulder falls. The most number of moderate- to large-scale landslides were triggered in the slate, shale, siltstone, phyllite, and schist of the Lesser Himalayan formation followed by an equally significant number in both schist, gneiss, etc. of the Higher Himalayan formation and the phyllite, metasandstone, schist, etc. of the Lesser Himalayan formation. The sizes (i.e., areas) of the landslides were lognormally distributed, with a mode area of 322.0 m². Slope inclinations of the moderate- to large-scale landslides followed a normal distribution with a mean slope inclination of 32.6° and standard deviation of 13.5°. There exists a strong correlation between the number of landslides and the peak ground acceleration within the study area, specific for different geological formations.     

Is multi-hazard mapping effective in assessing natural hazards and integrated watershed management?

Natural hazards are often studied in isolation.However,there is a great need to examine hazards holistically to better manage the complex of threats found in any region.Many regions of the world have complex hazard landscapes wherein risk from individual and/or multiple extreme events is omnipresent.Extensive parts of Iran experience a complex array of natural hazards-floods,earthquakes,landslides,forest fires,subsidence,and drought.The effectiveness of risk mitigation is in part a function of whether the complex of hazards can be collectively considered,visualized,and evaluated.This study develops and tests individual and collective multihazard risk maps for floods,landslides,and forest fires to visualize the spatial distribution of risk in Fars Province,southern Iran.To do this,two well-known machine-learning algorithms-SVM and MARS-are used to predict the distribution of these events.Past floods,landslides,and forest fires were surveyed and mapped.The locations of occurrence of these events(individually and collectively) were randomly separated into training(70%) and testing(30%) data sets.The conditioning factors(for floods,landslides,and forest fires) employed to model the risk distributions are aspect,elevation,drainage density,distance from faults,geology,LULC,profile curvature,annual mean rainfall,plan curvature,distance from man-made residential structures,distance from nearest river,distance from nearest road,slope gradient,soil types,mean annual temperature,and TWI.The outputs of the two models were assessed using receiver-operating-characteristic(ROC) curves,true-skill statistics(TSS),and the correlation and deviance values from each models for each hazard.The areas-under-the-curves(AUC) for the MARS model prediction were 76.0%,91.2%,and 90.1% for floods,landslides,and forest fires,respectively.Similarly,the AUCs for the SVM model were 75.5%,89.0%,and 91.5%.The TSS reveals that the MARS model was better able to predict landslide risk,but was less able to predict flood-risk patterns and forest-fire risk.Finally,the combination of flood,forest fire,and landslide risk maps yielded a multi-hazard susceptibility map for the province.The better predictive model indicated that 52.3% of the province was at-risk for at least one of these hazards.This multi-hazard map may yield valuable insight for land-use planning,sustainable development of infrastructure,and also integrated watershed management in Fars Province.     

Multiple-occurrence regional landslide events in New Zealand: Hazard management issues

Landsliding in New Zealand most commonly occurs in the form of multiple-occurrence landslide events, simultaneously involving thousands to ten thousands of landslides over areas extending up to 20,000 km². The scale of these events, together with their multiple-hazard character, provide a unique set of management issues that stretch the capabilities of available emergency management services. Several measures for characterising the magnitude and impact potential of these events are presented and compared. While the median density of landsliding is approximately 30 landslides/km², over 100 landslides/km² have been recorded in some events. Specific soil displacement volumes vary widely between events—New Zealand events yield a median value of approximately 140 m³/ha. Measured Ratios of runout length to scar length are commonly about 3:1. However, comparison between events is constrained by lack of standardisation in methods of measurement and recording. Agricultural production loss, damage to road and rail infrastructure and increased flooding are the main consequences of these events. Treatment options involve loss sharing, resource management legislation, and various forms of bio-engineering.     

Earthquake-and-landslide events are associated with more fatalities than earthquakes alone

Natural hazards are natural processes of the complex Earth system and may interact and affect each other. Often a single hazard can trigger a subsequent, different hazard, such as earthquakes triggering landslides. The effect of such cascading hazards has received relatively little attention in the literature. The majority of previous research has focused on single hazards in isolation, and even multi-hazard risk assessment currently does not account for the interaction between hazards, therefore ignoring potential amplification effects. Global earthquake-and-landslide fatality data were used to model cascading events to explore relationships between the number of fatalities during single and cascading events and covariates. A multivariate statistical approach was used to model the relationship between earthquake fatalities and several covariates. The covariates included earthquake magnitude, gross domestic product, slope, poverty, health, access to cities, exposed population to earthquake shaking, building strength and whether a landslide was triggered or not. Multivariate regression analysis showed the numbers of earthquake fatalities are significantly affected by whether a subsequent landslide is triggered or not.