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AbstractIn this study, a new approach of machine learning (ML) models integrated with the analytic hierarchy process (AHP) method was proposed to develop a holistic flood risk assessment map. Flood susceptibility maps were created using ML techniques. AHP was utilized to combine flood vulnerability and exposure criteria. We selected Quang Binh province of Vietnam as a case study and collected available data, including 696 flooding locations of historical flooding events in 2007, 2010, 2016, and 2020; and flood influencing factors of elevation, slope, curvature, flow direction, flow accumulation, distance from river, river density, land cover, geology, and rainfall. These data were used to construct training and testing datasets. The susceptibility models were validated and compared using statistical techniques. An integrated flood risk assessment framework was proposed to incorporate flood hazard (flood susceptibility), flood exposure (distance from river, land use, population density, and rainfall), and flood vulnerability (poverty rate, number of freshwater stations, road density, number of schools, and healthcare facilities). Model validation suggested that deep learning has the best performance of AUC = 0.984 compared with other ensemble models of MultiBoostAB Ensemble (0.958), Random SubSpace Ensemble (0.962), and credal decision tree (AUC = 0.918). The final flood risk map shows 5075 ha (0.63%) in extremely high risk, 47,955 ha (5.95%) in high‐risk, 40,460 ha (5.02%) in medium risk, 431,908 ha (53.55%) in low risk areas, and 281,127 ha (34.86%) in very low risk. The present study highlights that the integration of ML models and AHP is a promising framework for mapping flood risks in flood‐prone areas.

The transformation of land-use and land cover in Nakhon Ratchasima province, Thailand has rapidly changed over the last few years. The major factors affecting the growth in the province arise from the huge expansion of developing areas, according to the government&rsquo ; s development plans that aim to promote the province as a central business-hub in the region. This development expansion has eventually intruded upon and interfered with sub-basin areas, which has led to environmental problems in the region. The scope of this study comprises three objectives, i.e., (i) to optimize the Cellular Automata (CA) model for predicting the expansion of built-up sites by 2022 ; (ii) to model a linear regression method for deriving the transition of the digital elevation model (DEM) ; and (iii) to apply Geographic Weighted Regression (GWR) for analyzing the risk of the stativity of flood areas in the province. The results of this study show that the optimized CA demonstrates accurate prediction of the expansion of built-up areas in 2022 using Land use (LU) data of 2-year intervals. In addition, the predicting model is generalized and converged at the iteration no. 4. The prediction outcomes, including spatial locations and ground-water touch points of the construction, are used to estimate and model the DEM to extract independent hydrology variables that are used in the determination of Flood Risk Susceptibility (FRS). In GWR in the research called FRS-GWR, this integration of quantitative GIS and the spatial model is anticipated to produce promising results in predicting the growth and expansion of built-up areas and land-use change that lead to an effective analysis of the impacts on spatial change in water sub-basin areas. This research may be beneficial in the process of urban planning with respect to the study of environmental impacts. In addition, it can indicate and impose important directions for development plans in cities to avoid and minimize flood area problems.

ABSTRACT Special Capital Region of Jakarta Province is Capital City of Indonesia, which has various strategic functions, such as central government and economic and business center. Geographically DKI Jakarta Province is lowland, it caused Jakarta has high of flood hazard. This condition potentially result of high risk. Based on it, the aims of research is: 1). Making map of flood susceptibility in Special Capital Region of Jakarta area, based on geomorphology approach, and 2). Data inventory element at risk of flood. The method of data analysis used qualitative, based on interpretation satellite imagery data using elements of interpretation. Indicators used to result map of flood susceptibility are elevation, slope, and landform, using scoring and overlay technique. The result of research is flood susceptibility of low area is 13.613,40 ha, medium is 23.238,67 ha, and higt is 27.216,72 ha. Based on it, the majority of research area have hight of flood susceptibility. Based on spatial pattern, it showed that areas with high flood susceptibility are mostly located in the northern part of research area, and areas with the lowest flood susceptibility are majority in the southern part of researh area. The result analysis of element at risk, it showed that element at risk affected by flood for high, medium, or low level is settlement. Key Words: Flood Susceptibility of Map, Exposure, Geomorphology, and Special Capital Region of Jakarta ABSTRAK Provinsi DKI Jakarta merupakan Ibu Kota negara Indonesia yang memiliki beragam fungsi startegis, seperti pusat pemerintahan, dan pusat ekonomi dan bisnis. Akan tetapi, kondisi geografis Provinsi DKI Jakarta yang merupakan dataran rendah, mengakibatkan wilayah Jakarta memiliki ancaman tinggi terhadap bahaya banjir. Hal ini dapat berpotensi menghasilkan tingginya risiko kerugian terhadap bencana. Berdasarkan hal tersebut, tujuan dalam penelitian ini yaitu: 1) Membuat peta kerawanan banjir Provinsi DKI Jakarta berdasarkan pendekatan geomorfologi, dan 2). Melakukan inventarisasi elemen berisiko yang berpotensi terpapar banjir. Metode analisis data dalam penelitian ini menggunakan analisis kualitatif, karena berdasarkan teknik interpretasi data citra secara kualitatif yaitu menggunakan unsur-unsur interpretasi. Parameter- parameter yang digunakan untuk menghasilkan peta kerawanan banjir yaitu elevasi, kemiringan lereng, dan bentuklahan, dengan menggunakan skoring dan tumpang susun. Hasil penelitian menunjukkan bahwa tingkat kerawanan banjir rendah seluas 13.613,40 ha, sedang seluas 23.238,67 ha, dan tinggi seluas 27.216,72 ha. Mayoritas wilayah penelitian terletak pada tingkat kerawanan banjir tinggi. Berdasarkan pola spasial menunjukkan bahwa daerah dengan tingkat kerawanan banjir tinggi mayoritas terletak di bagian utara wilayah penelitian, dan daerah dengan tingkat kerawanan banjir rendah mayoritas dibagian selatan wilayah penelitian. Hasil analisis keterpaparan elemen berisiko wilayah penelitian menunjukkan bahwa elemen berisiko yang berpotensi tertinggi terkena banjir baik tingkat tinggi, sedang, atau rendah yaitu pemukiman. Kata Kunci: Pemetaan Kerawanan Banjir, Keterpaparan, Gemorfologi, dan DKI Jakarta

Abstract. Central Asia regions are characterized by active tectonics, high mountain chains with extreme topography with glaciers, and strong seasonal rainfall events. These key predisposing factors make large landslides a serious natural threat in the area, causing several casualties every year. The mountain crests are divided by wide lenticular or narrow, linear intermountain tectonic depressions, which are incised by many of the most important Central Asia rivers and are also subject to major seasonal river flood hazard. This multi-hazard combination is a source of potential damming scenarios, which can bring cascading effects with devastating consequences for the surrounding settlements and population. Different hazards can only be managed with a multi-hazard approach coherent within the different countries, as suggested by the requirements of the Sendai Framework for Disaster Risk Reduction. This work was carried out within the framework of the Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia (SFRARR) project as part of a multi-hazard approach with the aim of providing a damming susceptibility analysis at a regional scale for Central Asia. To achieve this, a semi-automated GIS-based mapping method, centered on a bivariate correlation of morphometric parameters defined by a morphological index, originally designed to assess the damming susceptibility at basin/regional scale, was modified to be adopted nationwide and applied to spatially assess the obstruction of the river network in Central Asia for mapped and newly formed landslides. The proposed methodology represents an improvement to the previously designed methodology, requiring a smaller amount of data, bringing new preliminary information on damming hazard management and risk reduction, and identifying the most critical area within the Central Asia regions.

Abstract. In flash flood prone areas, roads are often the first assets affected by inundations which make rescue operations difficult and represent a major threat to lives: almost half of the victims are car passengers trapped by floods. In the past years, the Gard region (France) road management services have realized an extensive inventory of the known road submersions that occurred during the last 40 years. This inventory provided an unique opportunity to analyse the causes of road flooding in an area frequently affected by severe flash floods. It will be used to develop a road submersion susceptibility rating method, representing the first element of a road warning system. This paper presents the results of the analysis of this data set. A companion paper will show how the proposed road susceptibility rating method can be combined with distributed rainfall-runoff simulations to provide accurate road submersion risk maps. The very low correlation between the various possible explanatory factors and the susceptibility to flooding measured by the number of past observed submersions implied the use of particular statistical analysis methods based on the general principals of the discriminant analysis. The analysis led to the definition of four susceptibility classes for river crossing road sections. Validation tests confirmed that this classification is robust, at least in the considered area. One major outcome of the analysis is that the susceptibility to flooding is rather linked to the location of the road sections than to the size of the river crossing structure (bridge or culvert).

Abstract. Central Asia is an area characterized by complex tectonics and active deformation; the related seismic activity controls the earthquake hazard level that, due to the occurrence of secondary and tertiary effects, also has direct implications for the hazard related to mass movements such as
landslides, which are responsible for an extensive number of casualties
every year. Climatically, this region is characterized by strong rainfall
gradient contrasts due to the diversity of climate and vegetation zones.
The region is drained by large, partly snow- and glacier-fed rivers that
cross or terminate in arid forelands; therefore, it is also affected by a
significant river flood hazard, mainly in spring and summer seasons. The
challenge posed by the combination of different hazards can only be tackled by
considering a multi-hazard approach harmonized among the different
countries, in agreement with the requirements of the Sendai Framework for
Disaster Risk Reduction. This work was carried out within the framework of
the Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia (SFRARR) project as part of a multi-hazard approach and is
focused on the first landslide susceptibility analysis at a regional scale
for Central Asia. To this aim the most detailed landslide inventories,
covering both national and transboundary territories, were implemented in a
random forest model, together with several independent variables. The
proposed approach represents an innovation in terms of resolution (from 30
to 70 m) and extension of the analyzed area with respect to previous
regional landslide susceptibility and hazard zonation models applied in
Central Asia. The final aim was to provide a useful tool for land
use planning and risk reduction strategies for landslide scientists,
practitioners, and administrators.

Abstract. In this paper a method is proposed to identify mountainous watersheds with the highest flood risk at the regional level. Through this, the watersheds to be subjected to more detailed risk studies can be prioritised in order to establish appropriate flood risk management strategies. The prioritisation is carried out through an index composed of a qualitative indicator of vulnerability and a qualitative flash flood/debris flow susceptibility indicator. At the regional level, vulnerability was assessed on the basis of a principal component analysis carried out with variables recognised in literature to contribute to vulnerability, using watersheds as the unit of analysis. The area exposed was obtained from a simplified flood extent analysis at the regional level, which provided a mask where vulnerability variables were extracted. The vulnerability indicator obtained from the principal component analysis was combined with an existing susceptibility indicator, thus providing an index that allows the watersheds to be prioritised in support of flood risk management at regional level. Results show that the components of vulnerability can be expressed in terms of three constituent indicators: (i) socio-economic fragility, which is composed of demography and lack of well-being; (ii) lack of resilience and coping capacity, which is composed of lack of education, lack of preparedness and response capacity, lack of rescue capacity, cohesiveness of the community; and (iii) physical exposure, which is composed of exposed infrastructure and exposed population. A sensitivity analysis shows that the classification of vulnerability is robust for watersheds with low and high values of the vulnerability indicator, while some watersheds with intermediate values of the indicator are sensitive to shifting between medium and high vulnerability.

Abstract. Damaging Hydrogeological Events are defined as periods during which phenomena, such as landslides, floods and secondary floods, cause damage to people and the environment. A Damaging Hydrogeological Event which heavily damaged Calabria (Southern Italy) between December 1972, and January 1973, has been used to test a procedure to be utilised in the zonation of a province according to damage susceptibility during DHEs. In particular, we analyzed the province of Catanzaro (2391 km2), an administrative district composed of 80 municipalities, with about 370 000 inhabitants. Damage, defined in relation to the reimbursement requests sent to the Department of Public Works, has been quantified using a procedure based on a Local Damage Index. The latter, representing classified losses, has been obtained by multiplying the value of the damaged element and the percentage of damage affecting it. Rainfall has been described by the Maximum Return Period of cumulative rainfall, for both short (1, 3, 5, 7, 10 consecutive days) and long duration (30, 60, 90, 180 consecutive days), recorded during the event. Damage index and population density, presumed to represent the location of vulnerable elements, have been referred to Thiessen polygons associated to rain gauges working at the time of the event. The procedure allowed us to carry out a preliminary classification of the polygons composing the province according to their susceptibility to damage during DHEs. In high susceptibility polygons, severe damage occurs during rainfall characterised by low return periods; in medium susceptibility polygons maximum return period rainfall and induced damage show equal levels of exceptionality; in low susceptibility polygons, high return period rainfall induces a low level of damage. The east and west sectors of the province show the highest susceptibility, while polygons of the N-NE sector show the lowest susceptibility levels, on account of both the low population density and high average rainfall characterizing these mountainous areas. The future analysis of further DHEs, using the tested procedure, can strengthen the obtained zonation. Afterwards, the results can prove useful in establishing civil defence plans, emergency management, and prioritizing hazard mitigation measures.

The book demonstrates the geospatial technology approach to data mining techniques, data analysis, modeling, risk assessment, visualization, and management strategies in different aspects of natural and social hazards. This book has 25 chapters associated with risk assessment, mapping and management strategies of environmental hazards. It covers major topics such as Landslide Susceptibility, Arsenic Contaminated Groundwater, Earthquake Risk Management, Open Cast Mining, Soil loss, Flood Susceptibility, Forest Fire Risk, Malaria prevalence, Flood inundation, Socio-Economic Vulnerability, River Bank Erosion, and Socio-Economic Vulnerability. The content of this book will be of interest to researchers, professionals, and policymakers, whose work involves environmental hazards and related solutions.

Abstract. The vulnerability of flood-prone areas is determined by
the susceptibility of the exposed assets to the hazard. It is a crucial
component in risk assessment studies, both for climate change adaptation and
disaster risk reduction. In this study, we analyse patterns of vulnerability
for the residential sector in a frequently hit urban area of Milan, Italy.
The conceptual foundation for a quantitative assessment of the structural
dimensions of vulnerability is based on the modified
source–pathway–receptor–consequence model. This conceptual model is used to
improve the parameterization of the flood risk analysis, describing (i) hazard scenario definitions performed by hydraulic modelling based on past
event data (source estimation) and morphological features and land-use
evaluation (pathway estimation) and (ii) the exposure and vulnerability
assessment which consists of recognizing elements potentially at risk
(receptor estimation) and event losses (consequence estimation). We
characterized flood hazard intensity on the basis of variability in water
depth during a recent event and spatial exposure also as a function of a
building's surroundings and buildings' intrinsic characteristics as a
determinant vulnerability indicator of the elements at risk. In this sense
the use of a geographic scale sufficient to depict spatial differences in
vulnerability allowed us to identify structural vulnerability patterns to
inform depth–damage curves and calculate potential losses from mesoscale
(land-use level) to microscale (building level). Results produces accurate
estimates of the flood characteristics, with mean error in flood depth
estimation in the range 0.2–0.3 m and provide a basis to obtain
site-specific damage curves and damage mapping. Findings show that the
nature of flood pathways varies spatially, is influenced by landscape
characteristics and alters vulnerability spatial distribution and hazard
propagation. At the mesoscale, the "continuous urban fabric" Urban Atlas
2018 land-use class with the occurrence of at least 80 % of soil sealing
shows higher absolute damage values. At microscale, evidence demonstrated
that even events with moderate magnitude in terms of flood depth in a
complex urbanized area may cause more damage than one would expect.

The purpose of this article is to examine the significance of the flood hazard for the functioning of the critical infrastructure in Poland and to suggest adequate methods and strategies for reducing the vulnerability of critical infrastructure to flooding. The main research method used is institutional and legal analysis, which shows how critical infrastructure is protected in Poland. The context of climate change is taken into account, the consequences of which may trigger increased threat, and its significance is discussed. It is also shown that river floods of a pluvial character constitute the greatest hazard in Poland, as they pose a threat to urban areas where most critical infrastructure is located. The author lists methods which can be used to protect critical infrastructure from flooding. Examples of systems are also provided. A conclusion is formed that the approach to this problem should be comprehensive and make use of methods related to flood prevention, flood defence and flood mitigation, and above all, the relocation of elements of the critical infrastructure. It is evident that the best time to reduce the susceptibility of specific systems to floods is when they are developed or modernised by taking into account the flood risk. Lastly, the biggest problem of the critical infrastructure in Poland is highlighted, namely its identification once it is already built, which means its location had not been thought through.

Abstract. A method for assessing regional debris flow susceptibility at the watershed scale, based on an index composed of a morphometric indicator and a land cover indicator, is proposed and applied in 106 peri-urban mountainous watersheds in Bogotá, Colombia. The indicator of debris flow susceptibility is obtained from readily available information common to most peri-urban mountainous areas and can be used to prioritise watersheds that can subsequently be subjected to detailed hazard analysis. Susceptibility is considered to increase with flashiness and the possibility of debris flows occurring. Morphological variables recognised in the literature to significantly influence flashiness and occurrence of debris flows are used to construct the morphometric indicator by applying principal component analysis. Subsequently, this indicator is compared with the results of debris flow propagation to assess its capacity in identifying the morphological conditions of a watershed that make it able to transport debris flows. Propagation of debris flows was carried out using the Modified Single Flow Direction algorithm, following identification of source areas by applying thresholds identified in the slope–area curve of the watersheds. Results show that the morphometric variables can be grouped into four indicators: size, shape, hypsometry and (potential) energy, with energy being the component that best explains the capability of a watershed to transport debris flows. However, the morphometric indicator was found to not sufficiently explain the records of past floods in the study area. Combining the morphometric indicator with land cover indicators improved the agreement and provided a more reliable assessment of debris flow susceptibility in the study area. The analysis shows that, even if morphometric parameters identify a high disposition to the occurrence of debris flow, improving land cover can reduce the susceptibility. However, if favourable morphometric conditions are present but deterioration of the land cover in the watershed takes place, then the susceptibility to debris flow events increases. The indicator of debris flow susceptibility is useful in the identification of flood type, which is a crucial step in flood risk assessment especially in mountainous environments, and it can be used as input for prioritisation of flood risk management strategies at regional level and for the prioritisation and identification of detailed flood hazard analysis. The indicator is regional in scope, and therefore it is not intended to constitute a detailed assessment but to highlight watersheds that could potentially be more susceptible to damaging floods than others in the same region.

Abstract. Glacier retreat since the Little Ice Age has resulted in the development or expansion of hundreds of glacial lakes in Patagonia. Some of these lakes have produced large (≥ 106 m3) Glacial Lake Outburst Floods (GLOFs) damaging inhabited areas. GLOF hazard studies in Patagonia have been mainly based on the analysis of short-term series (≤ 50 years) of flood data and until now no attempt has been made to identify the relative susceptibility of lakes to failure. Power schemes and associated infrastructure are planned for Patagonian basins that have historically been affected by GLOFs, and we now require a thorough understanding of the characteristics of dangerous lakes in order to assist with hazard assessment and planning. In this paper, the conditioning factors of 16 outbursts from moraine-dammed lakes in Patagonia were analysed. These data were used to develop a classification scheme designed to assess outburst susceptibility, based on image classification techniques, flow routine algorithms and the Analytical Hierarchy Process. This scheme was applied to the Baker Basin, Chile, where at least seven moraine-dammed lakes have failed in historic time. We identified 386 moraine-dammed lakes in the Baker Basin of which 28 were classified with high or very high outburst susceptibility. Commonly, lakes with high outburst susceptibility are in contact with glaciers and have moderate (> 8°) to steep (> 15°) dam outlet slopes, akin to failed lakes in Patagonia. The proposed classification scheme is suitable for first-order GLOF hazard assessments in this region. However, rapidly changing glaciers in Patagonia make detailed analysis and monitoring of hazardous lakes and glaciated areas upstream from inhabited areas or critical infrastructure necessary, in order to better prepare for hazards emerging from an evolving cryosphere.