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Landslide hazard zonation plays an important role in safe and viable infrastructure development, urbanization, land use, and environmental planning. The Shafe and Baso catchments are found in the Gamo highland which has been highly degraded by erosion and landslides thereby affecting the lives of the local people. In recent decades, recurrent landslide incidences were frequently occurring in this Highland region of Ethiopia in almost every rainy season. This demands landslide hazard zonation in the study area in order to alleviate the problems associated with these landslides. The main objectives of this study are to identify the spatiotemporal landslide distribution of the area; evaluate the landslide influencing factors and prepare the landslide hazard map. In the present study, lithology, groundwater conditions, distance to faults, morphometric factors (slope, aspect and curvature), and land use/land cover were considered as landslide predisposing/influencing factors while precipitation was a triggering factor. All these factor maps and landslide inventory maps were integrated using ArcGIS 10.4 environment. For data analysis, the principle of logistic regression was applied in a statistical package for social sciences. The result from this statistical analysis showed that the landslide influencing factors like distance to fault, distance to stream, groundwater zones, lithological units and aspect have revealed the highest contribution to landslide occurrence as they showed greater than a unit odds ratio. The resulting landslide hazard map was divided into five classes: very low (13.48%), low (28.67%), moderate (31.62%), high (18%), and very high (8.2%) hazard zones which was then validated using the goodness of fit techniques and receiver operating characteristic curve with an accuracy of 85.4. The high and very high landslide hazard zones should be avoided from further infrastructure and settlement planning unless proper and cost-effective landslide mitigation measures are implemented.

The present study aims to suggest an approach that allows the simultaneous hazard zonation mapping of earthquake-induced secondary effects. The modeling process of the applied methodology involves an initial separate evaluation of the hazard imposed by seismically induced landslides and soil liquefaction and a subsequent stacking into one single hazard map that reflects an integrated assessment of areas exposed to both earthquake-induced phenomena under seismic shaking. To this end, we adopted a spatial multi-criteria method to support the evaluation of the controlling factors that contribute to the occurrence of coseismic landslides and soil liquefaction and we exploited the potential of Geographic Information Systems to process the various thematic layers and produce hazard zonation maps that can be used to help communities become more resilient to future coseismic hazards. The implemented methodology has the potential to categorize and discriminate regions that are threatened either by coseismic landslides, by soil liquefaction or by their combined occurrence. The results demonstrate the necessity, especially in seismically active regions which consist of mountainous terrain along with coastal plain areas and consequently imply susceptibility to slope destabilization phenomena and soil liquefaction, to jointly evaluate the hazard posed by both of these earthquake-induced secondary effects.

In this study, seismic landslide hazard analysis is performed for central seismic gap (CSG) region of Himalaya for a future scenario earthquake of magnitude (Mw) 8.5. Initially, PGA values are estimated by using stochastic finite fault seismological model. Further, the PGA values along with slope displacement prediction equation are used to estimate the Newmark’s sliding displacement. Monte Carlo simulations are performed by considering uncertainties in the material properties. Finally, the hazard map in terms of the probability of slope displacement (DN) value exceeding the threshold values of 5 cm is presented. The probability value varies between 0.1 and 1 and high probability in higher Himalayas highlights the possibility of huge number of co-seismic landslides in this region. The developed seismic landslide hazard map will help local authorities and planners with tools for assessing the seismic landslide risk associated with the use of land and taking necessary measures to minimize the damages.

On August 20, 2019, many catastrophic debris flows broke out in meizoseismal area of Wenchuan M s 8.0 earthquake in China under the influence of continuous heavy rainfall. This paper takes the Chutou gully debris flow event occurred on August 20, 2019 as an example. The 3-D numerical simulation software, RAMMS, is used to back calculate the event and predict the future hazard. Coulomb and viscous turbulent friction, μ and ξ are calibrated in RAMMS. Numerical simulation reveals the movement process of Chutou gully from the aspects of flow depth, velocity, discharge, and run-out solid materials volume. The simulation results show that more than two-thirds of the solid materials are still deposited in the main channel, which could provide material basis for the re-occurrence of high hazard debris flow. In addition, based on the intensity and probability of debris flow, the hazard of debris flow is divided into high, middle, and low degrees. According to the simulation results and hazard assessment model, the hazard map of Chutou gully debris flow in various rainstorm return periods (20, 50, 100, and 200 years) is established, which can provide guidance for the future land-use planning and debris flow prevention works.

Rainstorm disaster brings serious threat to people's life and property safety. Constructing reasonable rainstorm disaster risk index and drawing rainstorm disaster risk map can help decision-makers to deal with rainstorm disaster effectively and reduce disaster loss. It has important practical significance. This paper, for the first time, proposes a comprehensive risk index for death caused by rainstorm disasters. According to this index, the regional hazard map of Beijing is drawn, so as to directly reflect the damage degree of rainstorm disaster in Beijing. In the process of index construction, the weight is determined by regression coefficient innovatively, and the disadvantage of subjective setting weight is avoided, and the spatial distribution of risk can be more accurately reflected by constructing disaster risk index by using fused grid data. Research shows that the rainstorm death risk index proposed in this paper can well reflect the risk of death caused by rainstorms in various areas of Beijing. Combined with the ArcGIS software, a risk map of death due to rainstorm disasters is drawn. It is found that Fangshan District of Beijing is a major disaster area with the highest risk of death. Finally, the managerial implication included that government administrators should evaluate the risk of rainstorm disasters in a certain area according to the established rainstorm death risk indexes and draw a risk map accordingly.

Preparedness saves lives. Forecasts can help improve preparedness by triggering early actions as part of pre-defined protocols under the Forecast-based Financing (FbF) approach; however it is essential to understand the skill of a forecast before using it as a trigger. In order to support the development of early-action protocols over Kenya, we evaluate the 33 heavy rainfall advisories (HRAs) issued by the Kenya Meteorological Department (KMD) during 2015–2019. The majority of HRAs warn counties which subsequently receive heavy rainfall within the forecast window. We also find a significant improvement in the advisory ability to anticipate flood events over time, with particularly high levels of skill in recent years. For instance actions with a 2-week lifetime based on advisories issued in 2015 and 2016 would have failed to anticipate nearly all recorded flood events in that period, whilst actions in 2019 would have anticipated over 70 % of the instances of flooding at the county level. When compared against the most significant flood events over the period which led to significant loss of life, all three such periods during 2018 and 2019 were preceded by HRAs, and in these cases the advisories accurately warned the specific counties for which significant impacts were recorded. By contrast none of the four significant flooding events in 2015–2017 were preceded by advisories. This step change in skill may be due to developing forecaster experience with synoptic patterns associated with extremes as well as access to new dynamical prediction tools that specifically address extreme event probability; for example, KMD access to the UK Met Office Global Hazard Map was introduced at the end of 2017. Overall we find that KMD HRAs effectively warn of heavy rainfall and flooding and can be a vital source of information for early preparedness. However a lack of spatial detail on flood impacts and broad probability ranges limit their utility for systematic FbF approaches. We conclude with suggestions for making the HRAs more useful for FbF and outline the developing approach to flood forecasting in Kenya.

The torrential rain (named “the July 2018 heavy rain”) from June 28 to July 8 in 2018 resulted in tremendous human and property damage. There were 237 deaths and 7,173 cases of flooding above the floor level. During the torrential rain, the low rate of evacuation behavior of residents in the affected area was also a problem. The Okayama prefecture conducted a mail survey with residents that suffered housing damage caused by the torrential rain (valid sample n = 3,765). The survey measured what residents’ awareness and knowledge were of flooding before the torrential rain, residents’ prediction of flooding and choice and reason of evacuation behavior during the emergency heavy rain warning and the evacuation order (emergency). This study analyzed the determinants of residents’ evacuation behaviors during the torrential rain with the survey data. The results indicated that, although most residents were aware of hazard maps before the torrential rain, few predicted flooding. Most residents were aware of the evacuation shelters and had a prior evacuation plan. However, some residents made no attempt to evacuate, even when their houses were damaged. During the emergency heavy rain warning, feeling a sense of crisis was an important factor to promote evacuation behavior. And, during the evacuation order (emergency), the majority of those who took actual evacuation behaviors was those who were approached by public sectors such as the fire department and the police. Moreover, residents’ judgment based on scientific information such as hazard maps and prediction of flooding before the torrential rain had little effect on evacuation behavior during the emergency heavy rain warning and the evacuation order (emergency). Therefore, the study indicates the importance of approaching residents’ affective decision-making, instead of relying on rational decision-making, to promote evacuation behavior when people are in unusual situations.

In the last years, metropolitan areas are more and more exposed to natural risks often intensified by the effects of climatic changes. Clear and complete information about hazards impending on the territory is indispensable for local authorities to define efficient territorial management strategies focused on the risk reduction. A flexible hazard tool which works at different scale and with several sources of hazard is here proposed. We drew maps of monothematic and synthetic indices to describe the hazard status of metropolitan areas. A hazard hotspot map was also elaborated to identify both the areas with high hazard for the single dangerous event and the areas characterized by the concomitance of several hazards. We computed hazard indices for Napoli and Pozzuoli, a densely populated area, located in the Somma-Vesuvio and Campi Flegrei multi-source volcanic zone and also exposed to landslide, flood and coastal erosion hazard.

Purpose Cambodia is considered one of the countries that are most vulnerable to adverse effects of climate change, particularly floods and droughts. Kampong Speu Province is a frequent site of calamitous flash floods. Reliable sources of flash flood information and analysis are critical in efforts to minimize the impact of flooding. Unfortunately, Cambodia does not yet have a comprehensive program for flash flood hazard mapping, with many places such as Kampong Speu Province having no such information resources available. The purpose of this paper is, therefore, to determine flash flood hazard levels across all of Kampong Speu Province using analytical hierarchy process (AHP) and geographical information system (GIS) with satellite information. Design/methodology/approach The integrated AHP–GIS analysis in this study encompasses ten parameters in the assessment of flash flood hazard levels across the province: rainfall, geology, soil, elevation, slope, stream order, flow direction, distance from drainage, drainage density and land use. The study uses a 10 × 10 pairwise matrix in AHP to compare the relative importance of each parameter and find each parameter’s weight. Finally, a flash flood hazard map is developed displaying all areas of Kampong Speu Province classified into five levels, with Level 5 being the most hazardous. Findings This study reveals that high and very high flash flood hazard levels are identified in the northwest part of Kampong Speu Province, particularly in Aoral, Phnum Srouch and Thpong districts and along Prek Thnot River and streams. Originality/value The flash flood hazard map developed here provides a wealth of information that can be invaluable for implementing effective disaster mitigation, improving disaster preparedness and optimizing land use.

While there has been significant research on probabilistic seismic hazard analysis (PSHA) using several different seismic sources, this paper focuses particularly on understanding the spatially varying seismic hazard controlled only by earthquakes. In that vein, regarding Turkish seismicity, this study is the first of its kind to explore this conundrum from a Bayesian point of view and offer new estimates to compare with the existing ones. In this study, a national-extent peak ground acceleration (PGA)-driven hazard map (upon 90% quantile of maxima,V-S30 = 760 m/s, and a return period of 475 years) was created and then compared both with the old and new versions of the officially recognized seismic hazard maps of Turkey. Regarding 10 earthquake-prone cities, the new PGA estimates were compared with those picked from these two maps. Next, individual site-based hazard estimates were drawn for these city centers considering the return periods of 43, 72, 140, and 475 years. The present hazard map was in compliance with the seismotectonic setup of Turkey and its PGA estimates were slightly high compared with the last two hazard maps for some specific regions, most of which are located in major active fault zones with a history of intense seismic activity, albeit the figures for low seismic zones were relatively low. With this study, it becomes clear that the process of PSHA, which innately requires a long and tiresome effort, can instantaneously be performed against the changing of catalog data over time, and thence prompt evaluations on variations can consequently be made.

Malaria has been the focus of multiple declarations, and a range of targets has been set since the beginning of the millennium. Poor people are at increased risk of both becoming infected with malaria as well as becoming infected more frequently. Malaria is also a major contributor to deaths among hospital inpatients in Africa. The purpose of this research is to employ geospatial techniques to map out areas that are vulnerable to malaria breeding vectors using weighted multi-criteria decision analysis to determine the risk levels within the study area and to determine the factors influencing the population at risk of malaria with a view to providing an effective malaria management. Malaria incidence records were used to determine the incidence rate of the disease from 2014 – 2016 and the rate of severity and total confirmed cases of the disease occurrence during the study period. Malaria risk map, which was produced through the integration of malaria hazard map, vulnerability map and elements at risk map, was used to determine the most susceptible areas to malaria attacks in the study area. The results showed about 87% of the entire study area being at high risk of malaria attack. It is observed that there is an increasing trend of malaria cases in the study area despite its variability over the years. It can be concluded that the study area as a whole is prone to malaria infestation and this requires immense attention in order to mitigate the scourge of the disease and its vector. It will be cost effective if GIS and remote sensing could be integrated in monitoring and early warning system in the ongoing malaria control and prevention activities especially in Nassarawa and Kumbotso local government areas that have a very high risk of malaria attacks. There is also the need to research more on the relationship between malaria prevalence and some key socio-anthropogenic factors such as literacy level, income level, HIV status, pregnancy status and meteorological factors. Keywords: Malaria Risk, Vulnerability, Hazard, Weighted multi-criteria decision analysis.

Indo-Gangetic plains are seismically most vulnerable due to the proximity of adjacent great Himalayan earthquakes and thick alluvium deposits of the Ganga River system. As the urbanization on this plain is increasing, there is a need to quantify seismic hazard in the Indo-Gangetic plains (IGPs). IGP also includes major cities with high population density. A probabilistic seismic hazard analysis (PSHA) plays an essential role in ensuring the safety of buildings, bridges and nuclear power stations. A seismic hazard analysis (SHA) was performed deterministically for most of the atomic power stations in India. An attempt has been made to perform PSHA of the part of Indo-Gangetic plains around Narora nuclear power plant (NNPP), accounting for a wide variety of uncertainties associated with SHA. Geological and tectonic features, as well as seismicity distribution around NNPP, are studied in detail, and four source zones are identified according to the geology, seismotectonics and diffuse seismicity. Mmax values for all the source zones based on 300-km distance around NNPP are 7.61 ± 0.54 for Himalaya zone (Zone 1), 6.12 ± 0.54 for Indo-Gangetic Peninsular India (IGPI) East zone (Zone 2), 6.29 ± 0.54 for IGPI Central zone (Zone 3) and 6.38 ± 0.64 for IGPI West zone (Zone 4). The b-value and return period of earthquakes in these zones are also estimated using Kijko–Sellevoll–Bayes model. The hazard curve for peak ground acceleration (PGA) and pseudo-spectral acceleration (PSA) at 0.2 s for the study region is obtained. Hazard map shows a PGA value of 0.0294 g for 100-year return period, 0.0616 g for 475-year return period design-based earthquakes, 0.1033 g for 2475-year return period maximum considered earthquakes, 0.1508 g for 10K-year return period and 0.2598 g for 100K-year return period level at PGA considering all source zones. Similarly, the hazard curve and maps for PSA at 0.2 s are also plotted. According to seismic zonation map of India, most of the study area lies in Zone 4, and the PGA values reported in seismic zonation map and Global Seismic Hazard Analysis Program for the study area range from 0.3 to 0.4 g. The obtained PGA values denote the maximum expected PGA at bedrock level in the study area.

A seismic hazard map for the national seismic design code of Pakistan (i.e., Building Code of Pakistan) is derived using probabilistic seismic hazard assessment (PSHA) approach. In order to update the seismic code, an updated seismic zoning map is required that should be based on usage of the recent seismic hazard elements. PSHA of Pakistan is an essential and important milestone. For this purpose, the standard Cornell–McGuire (1968–1976) approach is employed, and the computations are made over a rectangular grid of 0.1°. The main features of this study include usage of a recently compiled earthquake catalogue, recent ground motion prediction equations and an updated seismic source model. The resulting ground motions are obtained as peak ground acceleration (PGA) and 5% damped spectral acceleration (SA) at T = 0.2 s and T = 1.0 s for 475-, 975- and 2475-year return periods (RPs) (evaluated for the flat rock site conditions). Results of the study show that seismic hazard in Pakistan is highest in its central and northern parts. In the central part near Quetta, severe seismic hazard (PGA 0.40 g) is observed. Among the important cities in Pakistan, Balakot city is likely to experience a PGA value of 0.36 g, while Islamabad, Peshawar and Chitral are likely to experience 0.33 g. The cities of Gilgit, Karachi and Gwadar experience ground motion values of 0.34, 0.26 and 0.29 g, respectively, for the 475-year return period (RP). It has also been observed that ground motion values show variation in the distribution and magnitude in contrast to the hazard map of national design code. The hazard map presented in this study is the improved seismic hazard zoning map of Pakistan that would be helpful in developing pre-disaster mitigation strategies and risk assessment studies in Pakistan. It is concluded that the seismic zoning map of the national seismic design code of Pakistan underestimates the ground motion values, and it should be updated or replaced.

© 2019 China University of Geosciences (Beijing) and Peking University Catastrophic natural hazards, such as earthquake, pose serious threats to properties and human lives in urban areas. Therefore, earthquake risk assessment (ERA) is indispensable in disaster management. ERA is an integration of the extent of probability and vulnerability of assets. This study develops an integrated model by using the artificial neural network–analytic hierarchy process (ANN–AHP) model for constructing the ERA map. The aim of the study is to quantify urban population risk that may be caused by impending earthquakes. The model is applied to the city of Banda Aceh in Indonesia, a seismically active zone of Aceh province frequently affected by devastating earthquakes. ANN is used for probability mapping, whereas AHP is used to assess urban vulnerability after the hazard map is created with the aid of earthquake intensity variation thematic layering. The risk map is subsequently created by combining the probability, hazard, and vulnerability maps. Then, the risk levels of various zones are obtained. The validation process reveals that the proposed model can map the earthquake probability based on historical events with an accuracy of 84%. Furthermore, results show that the central and southeastern regions of the city have moderate to very high risk classifications, whereas the other parts of the city fall under low to very low earthquake risk classifications. The findings of this research are useful for government agencies and decision makers, particularly in estimating risk dimensions in urban areas and for the future studies to project the preparedness strategies for Banda Aceh.

Earthquake-induced liquefaction is responsible for the extensive damage to the infrastructures in both developed and developing cities. Chattogram, the second largest city of Bangladesh and one of the vital port city in the south Asian region is situated in the active seismic region, and the frequency of recent small magnitude earthquakes around the city reveals that a significant earthquake of probable magnitude 7.0 or higher is due. Therefore, liquefaction severity at different locations of Chattogram Metropolitan Area is estimated based on the in situ parameters. Two widely used liquefaction assessment procedures has been applied to estimate the liquefaction susceptibility at the selected locations. Later, geospatial techniques are applied to prepare a hazard map based on liquefaction potential of discrete locations. The flat tidal part of the city is identified as extremely liquefy prone areas, while the small hillocks and nearby areas at the central part of city are safe against liquefaction hazard. Geological variation of parameter in all directions are also taken into account to prepare the hazard map. Predicted liquefaction potential is then compared with a second data set and the linear regression between the observed and predicted liquefaction potential portray consistent approximation in all cases. Case studies and practical experience also justify the developed hazard map. Therefore, the developed hazard map can be a useful tool for the disaster mitigation policy of Bangladesh Government.

This study aims to evaluate risk and discover the distribution law for landslides, so as to enrich landslide prevention theory and method. It first selected Fengjie County in the Three Gorges Reservoir Area as the study area. The work involved developing a landslide risk map using hazard and vulnerability maps utilizing landslide dataset from 2001 to 2016. The landslide dataset was built from historical records, satellite images and extensive field surveys. Firstly, under four primary conditioning factors (i.e., topographic factors, geological factors, meteorological and hydrological factors and vegetation factors), 19 dominant factors were selected from 25 secondary conditioning factors based on the GeoDetector to form an evaluation factor library for the LSM. Subsequently, the random forest model (RF) was used to analyze landslide susceptibility. Then, the landslide hazard map was generated based on the landslide susceptibility mapping (LSM) for the study region. Thereafter, landslide vulnerability assessment was conducted using key elements (economic, material, community) and the weights were provided based on expert judgment. Finally, when risk equals vulnerability multiplied by hazard, the region was categorized as very low, low, medium, high and very high risk level. The results showed that most landslides distribute on both sides of the reservoir bank and the primary and secondary tributaries in the study area, which showed a spatial distribution pattern of more north than south. Elevation, lithology and groundwater type are the main factors affecting landslides. Fengjie County landslide risk level is mostly low (accounting for 73.71% of the study area), but a small part is high and very high risk level (accounting for 2.5%). The overall risk level shows the spatial distribution characteristics of high risk in the central and eastern urban areas and low risk in the southern and northern high-altitude areas. Secondly, it is necessary to strictly control the key risk areas, and carry out prevention and control zoning management according to local conditions. The study is conducted for a specific region but can be extended to other areas around the investigated area. The developed landslide risk map can be considered by relevant government officials for the smooth implementation of management at the regional scale.

Storm surge is one of the most devastating marine disasters in China, leading to tremendous economic damage and a large number of casualties. Combined storm surge hazard assessment and zonation is an important method for coastal disaster risk reduction and mitigation management. Based on observational data from tide-gauge and hydrological stations in coastal areas, we analyzed storm surge hazard intensity and generated a storm surge hazard map at the county level using the expected values of storm surge and over-warning water levels. The results show that 87, 67, 62, and 40 counties along the coast of China are exposed to the first (highest), second (higher), third (medium), and fourth (low) degree of hazard level, respectively. The areas with the highest risk of storm surge are the coasts of Bohai Bay, Laizhou Bay, and the Yangtze Delta, the coast from the north of Fuzhou to the south of Zhejiang, and the coastal area of Huizhou, Pearl River, and Yangjiang in Guangdong Province. This assessment, which is based on a national storm surge hazards map, can provide decision-making support for the government’s urban planning of coastal cities and site selection in large national projects.

One of the requirements for planning and decision-making to develop the infrastructures is to prepare the landslide occurrence hazard map. For this purpose, in this article, the Shannon entropy and Dempster–Shafer intuition theory methods were used to prepare the hazard map and applying the data uncertainty in the Tutkabon region, Guilan Province. In this study, parameters of the slope, elevation, geomorphological conditions, the curvature of the earth, proximity to the river and proximity to faults were used as the affecting factors on the landslide occurrence. By using these parameters, the map of the landslide occurrence hazard was prepared using the entropy index; besides, the belief values were calculated by the Dempster–Shafer method. To investigate the uncertainty, the disbelief and uncertainty values were calculated by the Dempster–Shafer method. Besides, in the Shannon entropy method the maps were compared before and after applying the entropy. Finally, by evaluating the results using comparing the landslide occurrence places in the study area and modeled hazard map, the value of 0.69 was obtained for the area under the prediction rate curve (as the parameter of prediction total precision) in the status with entropy and the value of 0.54 was obtained for the status without entropy. Similarly, the evaluation of the hazard belief map by the Dempster–Shafer method indicates that 65% of the landslide occurrence places occur in the classes of high and very high hazard and the value of 0.74 was obtained for the area under the prediction rate curve in the belief map.

Many natural disasters have recently occurred in Laos. Among them, flooding has been the greatest problem. Land use change (deforestation and urbanization) and climate change have played significant roles, and it is important to understand the impacts of these changes on flooding. We have developed an integrated hazard map based on a combination of four hazard maps of flooding, land use change and climate change to assess hazard areas at the national scale. The hazard map was developed using the analytical hierarchy process (AHP) and a hazard index. Finally, we divided the map into four hazard area categories, which include low, medium, intermediate and high. Based on this analysis, the integrated hazard map of Laos indicates that low hazard areas cover 87.44% of the total area, medium hazard areas cover 8.12%, and intermediate and high hazard areas respectively cover 2.42% and 2% of the land area. We compared the results with historical events to confirm that the proposed methodology is valid.

In this study, three machine learning models, namely, support vector machine, naive Bayes, and random forest, along with the geographic information system, are used to delineate the tar mat occurrence hazard in the upper part of Zubair Formation (named as DJ unit) in Rumaila oil field, southern Iraq. To build these models, a well inventory map that consists of 213 wells (tar and free-tar) is used with five factors that control the mat distribution in the DJ reservoir unit. These factors are porosity, volume of shale, water saturation, DJ unit thickness, and distance to the major fold axis. Multicollinearity and feature selection tests demonstrate that three of the five factors (distance to the major fold axis, water saturation, and porosity) are responsible for the tar distribution in the reservoir unit. The important factors with well inventory are used to develop the machine models and the results are compared using five evaluation measures namely, accuracy, sensitivity, specificity, kappa, and the relative operating characteristics curve. Findings from the models suggest that random forest is the best model, followed by support vector machine with polynomial kernel. The prediction random forest model is used to delineate the mat distribution, and the probability of tar mat occurrence hazard is classified into five zones, namely, very low, low, moderate, high, and very high. The produced hazard map in this study can be used as guide in the drilling of new wells in the considered reservoir unit and in avoiding the drilling of wells where the tar expected to occur.

Climate change is likely to increase the risks related to heat waves in urban areas. We map spatial pattern of heat wave vulnerability and risk in the Helsinki metropolitan area in southern Finland. First, we assess differences that zoning, i.e., differences in spatial units of analysis, and weighting, i.e., weights given to indicators when constructing the index, cause in map production. Second, we evaluate how maps of consensus and certainty could pave the way for visualizing and assessing uncertainties in risk and vulnerability indices. For vulnerability, we use socioeconomic data using 5 different zoning options and 11 different weighting options. For risk, we add two extra layers to vulnerability maps: hazard map showing the spatial pattern of heat based on Landsat satellite images and exposure map showing the spatial pattern of population. We found that when different zoning options are used, the spatial pattern of vulnerability may differ dramatically. In risk maps, the differences between zoning options are smaller. Contrary to previous literature, differences in indicator weighting alter the final maps slightly. The consensus and certainty maps show their potential, e.g., in pointing out areas which may have both high risk/vulnerability and high certainty for risk/vulnerability. Finally, we discuss other possibilities in tackling the uncertainties in mapping and propose new avenues for research.

This paper presents a high-altitude hazard detection method for Mars landing. Current terminal-triggered methods do not fully support re-targeting maneuvers if all regions are found unsafe. Towards safe landing requirements for future missions, hazard detection should be triggered as soon as possible. We therefore proposed a lidar-based high altitude hazard detection approach, consisting of two main procedures: Terrain reconstruction and Hazard mapping. Morphological filters are first carried out to remove outliers. An interpolation-based terrain reconstruction algorithm is then proposed to model the datum surface of landing region. For hazard mapping, an innovative hazard assessment function is proposed to generate a continuous hazard map that with full hazard information. The new approach is simple but well-performed, and only few parameters are needed. Both synthetic and real data are used to validate the detection performance, and preliminary results show the superiority of the proposed algorithms compared with current plane-based hazard detectors.

Landslides are one of the most damaging disastrous phenomena that frequently lead to serious problems in hilly areas. The Namchi region of South Sikkim district as a part of Eastern Himalayas is not an exception to it. In the present study, multi-criteria analysis technique is used for landslide hazard zonation mapping. Various thematic layers, namely slope, rainfall distribution map, lineament density, drainage density, slope aspect, geology, land use/land cover and soil map, were integrated in a GIS platform (ArcGIS 10.1) to delineate landslide hazard zone. Analytic hierarchy process was used to determine the weight values of different factors. Relative rating values are assigned for the subclasses of each thematic layer based on their corresponding impact on the landslide triggers, and within a thematic layer, each class was assigned an ordinal rating from 0 to 9. The landslide hazard zonation map of Namchi region was produced based on weighted overly techniques. The landslide hazard map of Namchi region is divided into five vulnerable zones, namely very low-, low-, moderate-, high- and very high-hazard zones. Resulted landslide hazard zonation map was further validated with field study and geospatial technology-based analysis. The findings demonstrate high-landslide-hazard zones are associated with areas of active erosive processes (steep slopes/cut slopes/lineaments). The results indicate the villages Bomtar, Jorethang, Kopchey, Donok, Namthang, Sumbuk, Longchok, Mamring, Turung, Mikkhola, etc. are highly prone to landslides. The final landslide hazard zonation map can be used for the landslide hazard prevention, proper planning of future infrastructure and geoenvironmental development in Namchi region.

Sediment hazard mapping is a fundamental tool for disaster management and mitigation activities in Thailand. Several countries are at risk of suffering landslide damages, but few studies have focused on the quantitative estimate of damages at a large scale. Most studies have considered the effects of landslide and soil erosion events from the perspective of their economic drawbacks, and there is no consensus on the quantitative assessment of the positive economic impacts of these events. Therefore, this study aimed to support the future assessment of landslides and other soil erosion events on sediment resources from positive economic perspectives. The results showed that the expected annual landslide damage cost in Thailand is approximately 204,000 USD per square kilometer. The cost for dredging sediment in Thailand is 108 USD per square kilometer. However, the benefit of sediment to private sectors is cost more than an average of 2040 USD per square kilometer, and the benefit values increased to approximately 15,000 USD per square kilometer in areas upstream of dams. In addition, there is an average benefit of 16,627 USD per year to the public sectors in each subdistrict of Thailand.

Ceboruco volcano in the western Trans-Mexican Volcanic Belt is one of the eleven most active stratovolcanoes in Mexico. Due to its recent eruptive history including a large Plinian eruption ~ 1000 years ago, the AD 1870 eruption, and recurrent recent seismic activity, it seemed highly appropriate to construct a hazard map in order to be prepared for future eruptions and their associated hazards. Ceboruco volcano eruptions are predominantly effusive; however, it also has been characterized by a great variability of eruptive styles throughout its record of activity. In fact, some eruptions comprise a significant diversity of volcanic processes, including lava flows, tephra fallout, ballistic emission, pyroclastic flows and surges, and lahars. In this work, we present (1) an integrated and simplified hazard map and (2) more detailed scenario-based hazard maps showing the areas affected by the different expected volcanic phenomena attempting to account for this great diversity of eruptive processes. The maps represent the basis to identify the main hazard zones during a future eruption and the related impacts on population and infrastructure within the area of influence of Ceboruco (~ 700 km2), as well as for undertaking subsequent vulnerability and risk analyses. The maps provide a tool to develop measures of prevention and mitigation of volcanic hazards (preparedness of the population, establishment of evacuation routes and refuges, etc.), as well as for decision-making by authorities during territorial planning (urban expansion for example). The integrated simplified hazard map can also be a tool for dissemination purposes, in order to create awareness of associated hazards derived from a possible future activity of the volcano among the public in general. This is important because in the western sector of the Trans-Mexican Volcanic Belt (and specifically in the State of Nayarit) most volcanic edifices (with the exception of Colima volcano) are closed-vent volcanoes (sealed volcanic vent vs. open-vent systems) with long repose periods (up to ~ 16,000 years for example in the case of San Juan volcano 60 km to the W), a situation that consequently and unfortunately has led to a practically nonexistent volcanic risk perception.

Modeling land movements hazard by multi-criteria approach is a line of research to provide a methodological framework for risk mapping. This work is intended to establish a model for mapping “land movements hazard” by GIS approach based on multi-criteria analysis. The methodology is to create thematic maps by combining in GIS, determining factors (slope, lithology, water, …) in triggering landslides phenomena and shrinking-swelling soil, using the method of Weighted Sum Model (WSM). These maps are then combined to provide a hazard map of land movements. The application of this method allows the spatial distribution of different criteria and phenomena in Berhoum area, region of Hodna Basin, eastern Algeria. As a result, the study area has been divided into four different areas: 1) areas with no land movements hazard, 2) areas with a medium land movements hazard, 3) areas with a high land movements hazard, and 4) areas with very high land movements hazard.

The San Salvador volcanic complex (El Salvador) and Nejapa-Chiltepe volcanic complex (Nicaragua) have been characterized by a significant variability in eruption style and vent location. Densely inhabited cities are built on them and their surroundings, including the metropolitan areas of San Salvador (∼2.4 million people) and Managua (∼1.4 million people), respectively. In this study we present novel vent opening probability maps for these volcanic complexes, which are based on a multi-model approach that relies on kernel density estimators. In particular, we present thematic vent opening maps, i.e., we consider different hazardous phenomena separately, including lava emission, small-scale pyroclastic density currents, ejection of ballistic projectiles, and low-intensity pyroclastic fallout. Our volcanological dataset includes: (1) the location of past vents, (2) the mapping of the main fault structures, and (3) the eruption styles of past events, obtained from critical analysis of the literature and/or inferred from volcanic deposits and morphological features observed remotely and in the field. To illustrate the effects of considering the expected eruption style in the construction of vent opening maps, we focus on the analysis of small-scale pyroclastic density currents derived from phreatomagmatic activity or from low-intensity magmatic volcanism. For the numerical simulation of these phenomena we adopted the recently developed branching energy cone model by using the program ECMapProb. Our results show that the implementation of thematic vent opening maps can produce significantly different hazard levels from those estimated with traditional, non-thematic maps.

In the past few decades, various natural hazards have occurred in Laos. To lower the consequences and losses caused by hazardous events, it is important to understand the magnitude of each hazard and the potential impact area. The main objective of this study was to propose a new approach to integrating hazard maps to detect hazardous areas on a national scale, for which area-limited data are available. The integrated hazard maps were based on a merging of five hazard maps: floods, land use changes, landslides, climate change impacts on floods, and climate change impacts on landslides. The integrated hazard map consists of six maps under three representative concentration pathway (RCP) scenarios and two time periods (near future and far future). The analytical hierarchy process (AHP) was used as a tool to combine the different hazard maps into an integrated hazard map. From the results, comparing the increase in the very high hazard area between the integrated hazard maps of the far future under the RCP2.6 and RCP4.5 scenarios, Khammouan Province has the highest increase (16.45 %). Additionally, the very high hazard area in Khammouan Province increased by approximately 12.47 % between the integrated hazard maps under the RCP4.5 and RCP8.5 scenarios of the far future. The integrated hazard maps can pinpoint the dangerous area through the whole country, and the map can be used as primary data for selected future development areas. There are some limitations of the AHP methodology, which supposes linear independence of alternatives and criteria.

As part of a feasibility study for a potential electronuclear power plant in Tunisia, a new seismic catalogue and a new seismic source model have been proposed, for Tunisia and adjacent areas. These findings are used in this study to evaluate the seismic hazard for two selected nuclear power plant sites: Marsa-Douiba in the north and Skhira in the southeast. The investigations and the assessment are conducted at a regional scale. The location of these sites and the choice of a regional review extent allow us to consider the entire Tunisian territory as the study area and also to conduct the hazard evaluation at a ‘national level’. In this study, a probabilistic seismic hazard analysis is performed using the R-CRISIS software, and a logic tree is developed to capture uncertainties related to the characterisation of both seismic sources and ground-motion. First, a hazard map of Tunisia for the return period of 475 years is generated to compare it with the ones obtained within previous studies. Then, the 10,000-year return period is considered, and the recommendations of the International Atomic Energy Agency are applied to determine the uniform hazard spectrums and perform disaggregation for the selected sites.

Recent large wildfires have caused serious environmental and social impacts in different areas of the world, such as Portugal, Greece and Australia. Sociodemographic changes in rural areas and climate change issues create unprecedented and challenging circumstances that call for an adjustment of fire management strategies and planning tools. In this research, we revise the procedure to assess wildfire susceptibility and hazard for mainland Portugal in a structural perspective. Based on a dataset of burned areas covering 44 years and a set of predisposing factors related to topography and landcover, we tested several susceptibility models using the Likelihood Ratio method, to calculate favourability scores. Landcover classes were analysed using national detailed sources and considering different timeframes. Hazard levels were obtained by combining the susceptibility model with the best accuracy and the probability to burn estimated from fire history (1975–2018). The resulting hazard values were classified in 5 levels based on the breaks of the success curve, instead of quantiles as in previous maps, to ensure territorial continuity at different spatial scales. The results show where the combination of terrain features is more favorable to fire propagation. The higher favourability scores were found for shrubland-type vegetation, whereas agricultural areas, cork and holm forests show lower scores. Eucalyptus and maritime pine forests show similar intermediate scores and have increased since 2007. The two highest hazard classes classify correctly 90% of the burned area over 44 years, demonstrating the high accuracy of the model. If integrated in spatial planning instruments, in conjunction with municipal plans, the two most hazardous classes may hinder the expansion of built-up areas. About 2% of the municipalities have more than 90% of their territory classified as hazardous, whereas 32% of the municipalities have, instead, less than 10% of hazardous area. These structural maps are a useful baseline for a long-term approach and can be complemented by estimations regarding the behavior and severity of wildfires, which should be further explored.

This study undertook a comprehensive application of 15 data mining (DM) models, most of which have, thus far, not been commonly used in environmental sciences, to predict land susceptibility to water erosion hazard in the Kahorestan catchment, southern Iran. The DM models were BGLM, BGAM, Cforest, CITree, GAMS, LRSS, NCPQR, PLS, PLSGLM, QR, RLM, SGB, SVM, BCART and BTR. We identified 18 factors usually considered as key controls for water erosion, comprising 10 factors extracted from a digital elevation model (DEM), three indices extracted from Landsat 8 images, a sediment connectivity index (SCI) and three other intrinsic factors. Three indicators consisting of MAE, MBE, RMSE, and a Taylor diagram were applied to assess model performance and accuracy. Game theory was applied to assess the interpretability of the DM models for predicting water erosion hazard. Among the 15 predictive models, BGAM and PLS respectively returned the best and worst performance in predicting water erosion hazard in the study area. The most accurate model, BGAM predicted that 22%, 8.2%, 9.4% and 60.4% of the total area should be classified as low, moderate, high and very high susceptibility to soil erosion by water, respectively. Based on BGAM and game theory, the factors extracted from the DEM (e.g., DEM, TWI, Slope, TST, TRI, and SPI) were considered the most important ones controlling the predicted severity of soil erosion by water. We conclude that overall, game theory is a valuable technique for assessing the interpretability of predictive models because this theory through SHAP (Shapley additive explanations) and PFIM (permutation feature importance measure) addresses the important concerns regarding the interpretability of more complex DM models.

Landslides and rock falls are among the many phenomena that have an impact on sustainable construction and infrastructure safety. The main causes of landslides are natural meteorological and hydrological phenomena. In building design and construction, environmental monitoring by identifying geotechnical hazards must be taken into account, as appropriate hazard assessment contributes to ensuring future construction safety. The Carpathian region in southern Poland is particularly predisposed to landslide formation. This may be favored by the nature of the shapes associated with the high and steep slopes of the region’s valleys. Another reason for concern is the flysch geological structure, which is characterized by alternating layers of water-permeable sandstones and poorly permeable shales, clays, and marls. Furthermore, the presence of a quaternary weathering cover makes the geological structure more susceptible to landslide processes and tectonic formations. The paper presents the results of a study whose aim was to elaborate a detailed landslide hazard map for a selected area in the Polish Carpathians, using statistical methods. The approach is based on the Hellwig method, which seems particularly useful in the assessment of susceptibility and landslide hazards on a local scale for a relatively small area. A two-stage study was conducted. The first stage of the research involved the creation of a database associated with environmental parameters and triggering factors, whereas the second stage consisted of the adoption of weights for seven thematic sections and their special features on the basis of expert knowledge. The hazard map developed as a result was compared to the mapping made using the weight-of-evidence method. The proposed data normalization method allows the use and analysis of both qualitative and quantitative data collected from various sources. The advantage of this method is the simple calculation procedure. A large-scale (1:2000) map might be used to assess the landslide hazard for specific cadastral units. Such a map becomes the basis for municipal spatial planning and may be able to influence investment decisions. Detailed landslide hazard maps are crucial for more precise risk evaluation for specific cadastral units. This, in turn, allows one to reduce serious economic and social losses, which might be the future results of landslides.

O desenvolvimento de áreas urbanas intensifica o risco de inundação pelo acréscimo tanto do escoamento superficial quanto da exposição da população e infraestrutura. Neste trabalho, nós evidenciamos a importância da escolha do período de retorno para determinar o grau de perigo de inundação e suas características hidráulicas. A bacia do campus da UFSC foi utilizada para o teste, onde combinamos modelos hidrológicos e hidráulicos para definir a intensidade e grau de perigo de inundação. Seis mapas de intensidade de perigo foram elaborados a partir de diferentes períodos de retorno (2, 10, 25, 50, 100 e 500 anos), que foram usados para caracterizar cenários de baixa recorrência e alta recorrência. O mapa de baixa recorrência pode ser ideal para ver os efeitos nas construções enquanto o mapa de alta recorrência ajuda a identificar a segurança das pessoas. Observou-se que uma linha de tendência logarítmica se encaixa bem para todas as variáveis verificadas relacionadas a inundação (e.g. intensidade da chuva, velocidade média de inundação, área total de inundação). Este estudo é importante para compreender as diferenças entre os efeitos no mapeamento de perigo de inundação aos períodos de retorno e como podem influenciar as variáveis hidráulicas de inundação. The development of urban areas exacerbates flood risk by increasing both runoff and the exposure of population and infrastructure. In this study, we highlight the importance of return period choice on flood hazard degree and flood hydraulics characteristics. We use the UFSC campus basin as a test bed and combine a hydrological and a hydrodynamic model to define the flood hazard intensity and flood hazard degree. Six hazard intensity maps were elaborated using different return periods (2, 10, 25, 50, 100 and 500-years) that characterize low and high recurrence scenarios. The low recurrence hazard map can be ideal to verify hazard effects on buildings, while the high recurrence hazard map helps to identify people security. All variables related to the rainfall effect and its consequences (e.g. rainfall intensity, flood mean velocity, and total flood area) follow a logarithmic relationship, with a small variation for higher return periods. We highlight how different return periods can influence flood hydraulics and flood hazard and should therefore be considered in flood hazard mapping.

This paper describes a novel methodology where Machine Learning Algorithms (MLAs) have been integrated to assess the landslide risk for slow moving mass movements, processes whose intermittent activity makes challenging any risk analysis worldwide. MLAs has been trained on datasets including Interferometric Synthetic Aperture Radar (InSAR) and additional remote sensing datasets such as aerial stereo photographs and LiDAR and tested in the Termini-Nerano landslides system (southern Apennines, Italy). The availability of such a wealth of materials allows also an unprecedented spatio-temporal reconstruction of the volume and the kinematic of the landslides system through which we could generate and validate the hazard map. Our analysis identifies fifteen slow-moving phenomena, traceable since 1955, whose total area amounts to 4.1 × 105 m2 and volume to ~1.4 × 106 m3. InSAR results prove that seven out of the fifteen slow-moving landslides are currently active and characterized by seasonal velocity patterns. These new insights on the dynamic of the landslides system have been selected as the main independent variables to train three MLAs (Artificial Neural Network, Generalized Boosting Model and Maximum Entropy) and derive the landslide hazard for the area. Finally, official population and buildings census data have been used to assess the landslide risk whose highest values are located in the crown area, south of Termini village, and nearby Nerano. This new methodology provides a different landslide risk scenario compared to the existing official documents for the study area and overall new insights on how to develop landslide risk management strategies worldwide based on a better understanding of slope processes thanks to the latest satellite technologies available.

Piton de la Fournaise, situated on La Réunion island (France), is one of the most active hot spot basaltic shield volcanoes worldwide, experiencing at least two eruptions per year since the establishment of the volcanological observatory in 1979. Eruptions are typically fissure-fed and form extensive lava flow fields. About 95 % of some ∼ 250 historical events (since the first confidently dated eruption in 1708) have occurred inside an uninhabited horseshoe-shaped caldera (hereafter referred to as the Enclos), which is open to the ocean on its eastern side. Rarely (12 times since the 18th century), fissures have opened outside of the Enclos, where housing units, population centers, and infrastructure are at risk. In such a situation, lava flow hazard maps are a useful way of visualizing lava flow inundation probabilities over large areas. Here, we present the up-to-date lava flow hazard map for Piton de la Fournaise based on (i) vent distribution, (ii) lava flow recurrence times, (iii) statistics of lava flow lengths, and (iv) simulations of lava flow paths using the DOWNFLOW stochastic numerical model. The map of the entire volcano highlights the spatial distribution probability of future lava flow invasion for the medium to long term (years to decades). It shows that the most probable location for future lava flow is within the Enclos (where there are areas with up to 12 % probability), a location visited by more than 100 000 visitors every year. Outside of the Enclos, probabilities reach 0.5 % along the active rift zones. Although lava flow hazard occurrence in inhabited areas is deemed to be very low (< 0.1 %), it may be underestimated as our study is only based on post-18th century records and neglects older events. We also provide a series of lava flow hazard maps inside the Enclos, computed on a multi-temporal (i.e., regularly updated) topography. Although hazard distribution remains broadly the same over time, some changes are noticed throughout the analyzed periods due to improved digital elevation model (DEM) resolution, the high frequency of eruptions that constantly modifies the topography, and the lava flow dimensional characteristics and paths. The lava flow hazard map for Piton de la Fournaise presented here is reliable and trustworthy for long-term hazard assessment and land use planning and management. Specific hazard maps for short-term hazard assessment (e.g., for responding to volcanic crises) or considering the cycles of activity at the volcano and different event scenarios (i.e., events fed by different combinations of temporally evolving superficial and deep sources) are required for further assessment of affected areas in the future – especially by atypical but potentially extremely hazardous large-volume eruptions. At such an active site, our method supports the need for regular updates of DEMs and associated lava flow hazard maps if we are to be effective in keeping up to date with mitigation of the associated risks.

Landslide susceptibility and hazard mapping has been developed providing remarkable results through the integration of geographic information system (GIS) and remote sensing. In this regard, some approaches have considered the use of Sentinel-1 data and time-series interferometric synthetic aperture radar (InSAR) techniques, such as differential InSAR (D-InSAR) and persistent scatterers interferometric (PSI), for providing precise information about total amount and velocity of ground-surface deformations and landslides within a specific area during a specific time period which is important for disaster management’s planning process.In this paper, artificial neural network (ANN) was used as a statistical analysis method for landslide susceptibility mapping in Northwest Syria using multi-layer perceptron (MLP) neural network on a training dataset of one dependent variable (landslide or non-landslide) and nine independent variables (slope, aspect, curvature, land cover, NDVI, lithology, distance from faults, distance from road, distance from stream networks). The resulting map of landslide susceptibility was validated using area under curve (AUC) analysis using a testing dataset which showed 90.28% of AUC value. Then, landslide susceptibility map was reclassified into high-moderate-low classes and integrated with intensity map of mean velocity of ground-surface deformations during the time period form (16 October 2018) until (21 March 2019) by using a landslide hazard matrix in a GIS environment in order to get landslide hazard map of the study area for that time period. The result shows that around 44.4%, 52.9% and 2.5% of total study area was classified as a high, moderate and low hazard zone of landslide, respectively.

Landslides can cause considerable loss of life and damage to property, and are among the most frequent natural hazards worldwide. One of the most fundamental and simple approaches to reduce damage is to prepare a landslide hazard map. Accurate prediction of areas highly prone to future landslides is important for decision-making. In the present study, for the first time, the group method of data handling (GMDH) was used to generate landslide susceptibility map for a specific region in Uzbekistan. First, 210 landslide locations were identified by field survey and then divided randomly into model training and model validation datasets (70% and 30%, respectively). Data on nine conditioning factors, i.e., altitude, slope, aspect, topographic wetness index (TWI), length of slope (LS), valley depth, distance from roads, distance from rivers, and geology, were collected. Finally, the maps were validated using the testing dataset and receiver operating characteristic (ROC) curve analysis. The findings showed that the &ldquo, optimized&rdquo, GMDH model (i.e., using the gray wolf optimizer [GWO]) performed better than the standalone GMDH model, during both the training and testing phase. The accuracy of the GMDH&ndash, GWO model in the training and testing phases was 94% and 90%, compared to 85% and 82%, respectively, for the standard GMDH model. According to the GMDH&ndash, GWO model, the study area included very low, low, moderate, high, and very high landslide susceptibility areas, with proportions of 14.89%, 10.57%, 15.00%, 35.12%, and 24.43%, respectively.

The aim of this research was to produce a new methodology for a special river bottom hazard mapping for the stability purposes of the biggest Polish water power plant: Włocławek. During the operation period of the water power plant, an engineering-geological issue in the form of pothole formation on the Wisła River bed in the gravel-sand alluvium was observed. This was caused by increased fluvial erosion resulting from a reduced water level behind the power plant, along with frequent changes in the water flow rates and water levels caused by the varying technological and economic operation needs of the power plant. Data for the research were obtained by way of a 4-year geodetic/bathymetric monitoring of the river bed implemented using integrated GNSS (Global Navigation Satellite System), RTS (Robotized Total Station) and SBES (Single Beam Echo Sounder) methods. The result is a customized river bottom hazard map which takes into account a high, medium, and low risk levels of the potholes for the water power plant structure. This map was used to redevelop the river bed by filling. The findings show that high hazard is related to 5% of potholes (capacity of 4308 m3), medium with 38% of potholes (capacity of 36,455 m3), and low hazard with 57% of potholes (capacity of 54,396 m3). Since the construction of the dam, changes due to erosion identified by the monitoring have concerned approximately 405,252 m3 of the bottom, which corresponds to 130 Olympic-size pools. This implies enormous changes, while a possible solution could be the construction of additional cascades on the Wisła River.

International audience; Dating recent lava flows is a critical issue to assess the volcanic hazards for nearby human populations, but traditional methods such as radiocarbon dating are often not applicable. We propose here a simple statistical method that relates the age of lava flows of the Piton de la Fournaise volcano (PdF) to the size of Agarista salicifolia (Ericaceae), a long-lived pioneer tree that quickly establishes after eruption and able to live >600 years. We measured the diameter at base of 711 trees on 20 dated lava flows (between 1401 CE and 2007 CE). We used a log-log linear model to assess the relationship between maximum diameter at base of Agarista salicifolia and the age of lava flows, and showed a very strong correlation (R2 = 0.987, p

The Siret River is one of the most important tributaries of the Danube River in the Romanian territory. With a total length of 596 km in this territory, the confluence section of the Siret River with the Danube represents an area where major floods have occurred over time. In the last 50 years, over 20 floods have been recorded in the lower area of the Siret River, and the most recent important flood, which happened in 2010, had a negative impact on the local population, the environment, and the economy. Although it is a buffer zone, the Danube River has a significant impact on the discharge rate of the Siret River. Since few studies have been conducted on the prediction of flooding in the lower area of the Siret River, the present study aims at presenting the most important steps to be taken for designing risk and hazard maps for floods, which could be further applied to other rivers. The confluence of the Siret River with the Danube, a distance of 35 km upstream, was chosen as a study area. Techniques of topographic and bathymetric measurements were combined in order to design the risk and hazard maps for floods in this area and to improve the digital terrain model of the minor riverbed for the studied river area. The 1D hydrodynamic model of the HEC-RAS software was used in this research for developing the flood risk and flood hazard maps. The hazard and risk maps were generated based on 10%, 5%, and 1% flood scenarios, which are in accordance with Floods Directive 2007/60/EC, no historical data were available for the 0.1% scenarios. Thus, in a flood scenario that can occur every 100 years, about 9500 inhabitants are vulnerable at a medium flood risk. In this scenario, over 19.5 km of road infrastructure, about 16.5 km of railways, eight cultural heritage indicators, and three environmental indicators may be affected.

In this study, an inventory of landslides induced by the 2011 Lorca earthquake (Mw 5.1) has been used in order to develop a new procedure to obtain objective logic-tree weights for a probabilistic earthquake-induced landslide hazard analysis. The 2011 Lorca earthquake triggered more than 250 landslides, mainly of disrupted type. The logic-tree was designed having regard to variability of relevant geotechnical parameters involved in the problem and uncertainties associated with the use of several empirical relationships in order to compute Newmark displacements. For the purpose, the resulting hazard maps were compared with this landslide inventory, and weights estimated for each branch of the logic tree based on these results. The best model for seismic landslide hazard mapping for a moderate earthquake correctly identifies around 72% of landslide areas. Based on the set of parameters that comprises (depth of failure surface, specific weight, cohesion, friction angle and Newmark displacement model), the corresponding weights were objectively established. These weights are reliable enough for the obtaining seismic landslide hazard maps and may be implemented in similar environments characterized by moderate-low magnitude earthquakes (Mw

The growing concentration of population and the related increase in human activities in coastal areas require numerical simulations to analyze the effects of flooding events that might occur in susceptible coastal areas in order to determine effective coastal management practices and safety measures to safeguard the inhabited coastal areas. The reliability of the analysis is dependent on the correct evaluation of key inputs such as return period of flooding events, vulnerability of exposed assets, and other risk factors (e.g., spatial distribution of elements at risk, their economic value, etc.). This paper defines a methodology to assess the effects of flooding events associated with basin run-off and storm surge in coastal areas. The assessment aims at quantifying in economic terms (e.g., loss of assets) the risk of coastal areas subject to flooding events. The methodology proposed in this paper was implemented to determine the areas subject to inundation on a coastal area in Southern Italy prone to hydrogeological instability and coastal inundation. A two-dimensional hydraulic model was adopted to simulate storm surges generated by severe sea storms coupled with intense rainfalls in order to determine the areas subject to inundation in the low-land area along the Adriatic coast object of this study. In conclusion, the economic risk corresponding to four different flooding scenarios was assessed by correlating the exceedance probability of each flooding scenario with the potential economic losses that might be realized in the inundated areas. The results of the assessment can inform decision-makers responsible for the deployment of risk mitigation measures.

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Landslides are one of the most destructive and most recurring natural calamities in the Himalayan region. Their occurrence leads to immense damage to infrastructure and loss of land, human lives, and livestock. One of the most affected regions is the Bhutan Himalayas, where the majority of the landslides are rainfall-induced. The present study aims to determine the hazard and risk associated with rainfall-induced landslides for the Phuentsholing region located in the southwestern part of the Bhutan Himalayas. The work involves developing a landslide risk map using hazard and vulnerability maps utilizing landslide records from 2004 to 2014. The landslide hazard map was generated by determining spatial and temporal probabilities for the study region. The spatial probability was computed by analyzing the landslide contributing factors like geology, slope, elevation, rainfall, and vegetation based on comprehensive field study and expertise about the area. The contributing factors were divided into various classes and the percentage of landslide occurrence under each class was calculated to understand its contributing significance. Thereafter, a weighted linear combination approach was used in a GIS environment to develop the spatial probability map which was multiplied with temporal probabilities based on regional rainfall thresholds already determined for the region. Consequently, vulnerability assessment was conducted using key elements at risk (population, land use/land cover, proximity to road, proximity to stream) and the weights were provided based on expert judgment and comprehensive field study. Finally, risk was determined and the various regions in the study area were categorized as high, medium, and low risk. Such a study is necessary for low-economic countries like Bhutan which suffers from unavailability of extensive data and research. The study is conducted for a specific region but can be extended to other areas around the investigated area. The tool can serve as an indicator for the civil authorities to analyze the risk posed by landslides due to the rapid infrastructure development in the region.

Studies on earthquake-induced liquefaction and identification of source unit for causing liquefaction have been a major concern in sustainable land use development especially in low to moderate seismic areas. During the 2017 Mw 5.4 Pohang earthquake, widespread liquefaction was reported around the Heunghae basin, which was the first ever reported case of liquefaction in the modern seismic history of Korea. The epicentral area is one of the major industrial hubs along the SE Korean Peninsula with no detailed liquefaction hazard map. The purpose of this study was to determine the land damage classification on the basis of surface manifestation of liquefaction features and carry out detailed liquefaction potential analysis to delineate the depth of liquefiable soil. This will eventually support developing a liquefaction hazard zonation map and sustainable development of infrastructure to minimize earthquake damages. In this present study, the southern part of the Heunghae basin, which has more field evidences of liquefaction than the northern part, was taken for detailed liquefaction analysis. From the detailed analysis, it was observed that the soils from 1.5 to 15 m depth with the probability of liquefaction varying from 2 to 20 are prone to liquefaction. On the basis of land damage pattern, the epicentral area falls in orange to red zone, which means the necessity of further detailed liquefaction analysis. This study urges more detailed liquefaction zonation should be carried out for the epicentral area and liquefaction hazard should be included in the multi-hazard map in the future for the sustainable land use planning.

Hazards from sea cliff instabilities are increasing because of the growing human occupation in coastal areas. Assessment of cliff hazards is very important in order to develop appropriate coastal management plans. In this study, a semi-quantitative heuristic method was developed to assess instability hazard for rocky coasts at Chabahar (Iran) along the northern coastline of the Gulf of Oman. In this method, seven factors affecting cliff instability, including: wave exposure, cliff height, cliff slope, rock resistance, lithology, bathymetry and beach width, were used to calculate an instability hazard index, from which a hazard map was constructed for the study area. Results were validated by statistical analysis of the previous instabilities detected by comparing old and new satellite images. According to the instability hazard class and cliff height, a hazard zone from the top of cliffs was determined within which development is not recommended.

Referring to the Indonesian earthquake source and hazard map published by the National Earthquake Center (Pusgen) in 2017, it was stated that there were 34 active faults on the island of Java and could potentially be a source of earthquakes with earthquake strength more than the 6.5 M scale. Each potential source of earthquake needs to be carried out detailed research on each fault that is declared active so as to reduce uncertainty in the seismic hazard analysis. Due to limited funding and human resources researching, it is necessary to make research priorities based on the level of urgency. By utilizing decision making analysis techniques, priority of research is carried out by considering several aspects, such as the magnitude of the earthquake that may occured possible economic impact factors, population density and the level of importance of a region on a national and international scale. From the modeling results, it is shown that faults that have the potential to become earthquake sources that are located near large cities are a top priority for detailed research such as the Lembang, Semarang and Surabaya Faults.

Rapid urbanisation and economic growth in developing Asian countries have exacerbated their exposure to flood hazards, particularly evident in low-lying urban cities that are currently facing increasing risks from extreme precipitations, likely made worse by the impending climate change. We present a set of simplified indices representative of the characteristics of rainfall-runoff process for evaluating pluvial flood hazard using the fuzzy comprehensive evaluation method. The highly urbanised Pearl River Delta (PRD) region in southern China is studied as an example of mapping the regional pluvial flood hazard and assessing the socio-economic exposure at risk. The developed hazard map captures the broad patterns of high flood hazard zones when compared with reported surface water flooding hotspots and the PRD riverine flood map from the 2015 Global Assessment Report. Further analysis on the regional socio-economic profiles suggests that most PRD cities are faced with large flood loss potential, with estimates of approximate 23 million people and 2.4 trillion RMB Gross Domestic Product (GDP) exposed to high flood hazard. Mega cities Guangzhou and Shenzhen top the ranking with over 20% to 40% of their dense urban settlements in the high flood hazard zone. This highlights the impact of human activities on the natural surface runoff process, and the need for robust flood hazard assessment for better understanding and design of holistic solutions towards more adequate flood mitigation systems for continuous urbanisation and future climate conditions. Accepted version This work was partially supported by the Sino-Singapore International Joint Research Institute (Project No. 205-A017020) and the National Key R&D Program of China (2018YFC1508200).

In recent years the European Alps experienced higher temperatures, more heatwaves, and more severe wildfires. Improving fire danger assessment for these sensitive ecosystems is a core element of future-oriented fire management strategies in the face of climate change. While meteorological systems are common to predict fire danger in many countries, other factors such as vegetation, topography, lightning occurrence and human impact are generally not considered. We introduce an Integrated forest Fire Danger assessment System (IFDS) for the Alpine country Austria that includes i) daily fire weather index data, ii) a countrywide hazard map for fire ignition through human activities, iii) a lightning fire hazard map, iv) a high-resolution fuel type map, and v) a topography-based estimation of the fire hazard. The system was implemented as an online Web-GIS prototype. The objectives of this contribution are to describe the conceptual approach for the IFDS, to understand the predictive power of different data layers in fire danger rating and to identify potential improvements, especially regarding the role of vegetation and human influence. A first validation was done with 2018–2019 forest fire data. Some variants of the IFDS produced better overall prediction accuracy regarding forest fire ignitions compared to common fire weather indices. They typically performed relatively better when considering the number of false alerts as well. However, correlation between larger burned areas and higher index values was low. Conclusions for the implementation of the IFDS in other Alpine countries are discussed and recommendations for necessary and reliable datasets at high resolution are given. This research has been conducted partly within the frame of the "Austrian Forest Research Initiative II" (AFFRI 2), which is funded by DaFNE as a "Bund-Länder-Kooperation" (Transaction number LE.3.2.3/0019-III/2/2015) and within the project “Copernicus Data for Novel High-resolution Wildfire Danger Services in Mountain Regions” (CONFIRM), which is funded by the Austrian Space Applications Programme (ASAP) (Project number 873674).

Risk assessment is indispensable for the efficient monitoring and management of groundwater contamination. This study presents the first application of comprehensive risk assessment in a weathered hard-rock aquifer of India at a macro-scale by integrating aquifer vulnerability with the sources and consequences of groundwater contamination. Aquifer vulnerability was evaluated using a modified DRASTIC model, contaminant sources were identified using hazard inventory, and the consequences of groundwater contamination were estimated based on the significance of groundwater. Finally, these three components were integrated in the GIS environment to determine the risk of groundwater contamination. The results were validated using two approaches based on the concentration of groundwater-quality parameters that pose threat to groundwater contamination. The results of aquifer vulnerability reveal that 70% of the study area has ‘High’ to ‘Very High’ vulnerability and the hazard map indicates that about 44% of the area has ‘Rare’ likelihood of hazard incidence. On the other hand, the consequence map reveals that 83% of the study area may experience ‘Maximum’ to ‘Extreme’ consequences due to groundwater contamination. The developed risk map shows that 37% of the study area has ‘Major’ risk of groundwater contamination, whereas 10% has ‘Catastrophic’ risk. Further, both the validation approaches confirmed that the developed risk map is reliable. It is emphasized that the higher vulnerability does not necessarily indicate higher risk of groundwater pollution, rather the occurrence of hazard determines the actual risk of groundwater contamination in any region. Hence, the assessment of risk is imperative for exploring current status of groundwater quality and for formulating efficient strategies to minimize or avoid groundwater contamination.

The present paper deals with landslide hazards in the Ebantu district of the Oromia regional state of western Ethiopia. Ninety-two landslides were recorded during field investigations and Google Earth interpretation. The data sets were prepared as a layer in the spatial GIS database that was later utilized for generating the landslide susceptibility zonation map. Slope, elevation, and distance from drainage were extracted from the digital elevation model, the geology is modified from the geological map of Nekemte, and the land use map was prepared from Landsat +ETM satellite (2015) using digital image processing techniques. The statistical index method was applied to identify landslide hazard areas, and statistical analysis was carried out based on the relationship between past landslides and the causative factors. The causative factor map is further classified into a number of classes based on their relative influence on mass movement and rating values are assigned to each class depending on their influence on slope instability. Based on their assigned weight values, the map overlay process is performed using Arc GIS 10.3, and finally, the landslide hazard map showing various zones is produced by the overlay technique.