Flood loss analysis and quantitative risk assessment in China

Risk assessment is a prerequisite for flood risk management. Practically, most of the decision making requires that the risks and costs of all risk mitigation options are evaluated in quantified terms. Therefore, a quantitative assessment of possible flood loss is very important, especially for emergency planning and pre-disaster preparedness. This paper presents a preliminary methodology and an operational approach for assessing the risk of flood loss to the population, crops, housing, and the economy at county level in China. The present work assesses the risk of loss for each element (people, crops, and so on) under low-, moderate-, and high-intensity flood using intensity-loss curves and loss rates based on historical flood data from 1990 to 2008. Results show that the counties with high flood risk are primarily located in North, East, Central, and South China, particularly in the lower reaches of rivers. On the other hand, the risk of most counties in the western region is generally lower than that of counties in the eastern region. However, for the entire country, the high-risk regions have both a substantial amount of rainfall and low terrain, making such regions highly prone to flooding. Moreover, these high-risk regions present both high population and wealth density.     

Flood risk assessment for informal settlements

The urban informal settlements are particularly vulnerable to flooding events, due to both their generally poor quality of construction and high population density. An integrated approach to the analysis of flooding risk of informal settlements should take into account, and propagate, the many sources of uncertainty affecting the problem, ranging from the characterization of rainfall curve and flooding hazard to the characterization of the vulnerability of the portfolio of buildings. This paper proposes a probabilistic and modular approach for calculating the flooding risk in terms of the mean annual frequency of exceeding a specific limit state for each building within the informal settlement and the expected number of people affected (if the area is not evacuated). The flooding risk in this approach is calculated by the convolution of flooding hazard and flooding fragility for a specified limit state for each structure within the portfolio of buildings. This is achieved by employing the flooding height as an intermediate variable bridging over the fragility and hazard calculations. The focus of this paper is on an ultimate limit state where the life of slum dwellers is endangered by flooding. The fragility is calculated by using a logic tree procedure where several possible combinations of building features/construction details, and their eventual outcome in terms of the necessity to perform structural analysis or the application of nominal threshold flood heights, are taken into account. The logic tree branch probabilities are characterized based on both the orthophoto recognition and the sample in situ building survey. The application of the methodology is presented for Suna, a sub-ward of Dar es Salaam City (Tanzania) in the Msimbazi River basin having a high concentration of informal settlements.     

Flood hazard and risk assessment in Russia

Flood risk assessment is usually performed by application of sophisticated mathematical models of river flow. However, there are cases when it is required to assess the risk in the lack of data conditions or a limited time available. In such cases, it is advisable to use some simplifications, which provide reliable results faster. This study proposes a hybrid approach to the flood risk assessment combining quantitative and qualitative indicators. The article describes various methods to assess the flood risk, such as likelihood of flooding, magnitude of the flood, average annual damage, maximum damage and expectation of damage. The authors examined special cases of calculation of the mathematical expectation of harm and zoning in the corresponding indicators. This approach is designed for the conditions of the Russian Federation, but it can be adapted for other regions. It is based on the use of two types of risk maps. The first type of maps is intended to define the mathematical expectation of damage zones for reference building with possibility of risk calculation for other buildings using multiple factors. The second type of maps is designed for the purposes of land use regulation for floodplains based on a priori statistical estimates of flood risk.     

Flood hazard and risk assessment in Russia

The occurrence of rockfall incidents on the transportation network may cause injuries, and even casualties, as well as severe damage to infrastructure such as dwellings, railways, road corridors, etc. Passive protective measures (i.e., rockfall barriers, wire nets, etc.) are mainly deployed by operators of ground transport networks to minimize the impact of detrimental effects on these networks. In conjunction with these passive measures, active rockfall monitoring should ideally include the magnitude of each rockfall, its initial and final position, and the triggering mechanism that might have caused its detachment from the slope. In this work, the operational principle of a low-cost rockfall monitoring and alerting system is being presented. The system integrates measurements from a multi-channel seismograph and commercial cameras as the primary equipment for event detection. A series of algorithms analyze these measurements independently in order to reduce alarms originated by surrounding noise and sources other than rockfall events. The detection methodology employs two different sets of algorithms: Time–frequency analyses of the rockfall event’s seismic signature are performed using moving window pattern recognition algorithms, whereas image processing techniques are utilized to deliver object detection and localization. Training and validation of the proposed approach was performed through field tests that involved manually induced rockfall events and recording of sources (i.e., passing car, walking people) that may cause a false alarm. These validation tests revealed that the seismic monitoring algorithms produce a 4.17 % false alarm rate with an accuracy of 93 %. Finally, the results of a 34-day operational monitoring period are presented and the ability of the imaging system to identify and exclude false alarms is discussed. The entire processing cycle is 10–15 s. Thus, it can be considered as a near real-time system for early warning of rockfall events.     

Flood risk assessment of River Indus of Pakistan

Annual flood peak discharges is widely used in risk assessment. Major sources of flooding in Pakistan are River Jhelum, River Chenab, River Kabul, and upper and lower parts of River Indus. These rivers are major tributaries of the River Indus System which is one of the most important systems of the world and the greatest system of Pakistan. River Indus is the longest river of Pakistan containing seven gauge stations and several barrages, and it plays a vital role in the irrigation system and power generation for the country. This paper estimates the risk of flood in River Indus using historical data of maximum peak discharges. On the basis of our analysis, we find out which dam/barrage reservoir need to be updated in capacity, and whether there are more dams/barrages needed.     

Earthquake risk assessment in NE India using deep learning and geospatial analysis

Earthquake prediction is currently the most crucial task required for the probability, hazard, risk mapping, and mitigation purposes. Earthquake prediction attracts the researchers' attention from both academia and industries. Traditionally, the risk assessment approaches have used various traditional and machine learning models. However, deep learning techniques have been rarely tested for earthquake probability mapping. Therefore, this study develops a convolutional neural network (CNN) model for earthquake probability assessment in NE India. Then conducts vulnerability using analytical hierarchy process (AHP), Venn's intersection theory for hazard, and integrated model for risk mapping. A prediction of classification task was performed in which the model predicts magnitudes more than 4 Mw that considers nine indicators. Prediction classification results and intensity variation were then used for probability and hazard mapping, respectively. Finally, earthquake risk map was produced by multiplying hazard, vulnerability, and coping capacity. The vulnerability was prepared by using six vulnerable factors, and the coping capacity was estimated by using the number of hospitals and associated variables, including budget available for disaster management. The CNN model for a probability distribution is a robust technique that provides good accuracy. Results show that CNN is superior to the other algorithms, which completed the classification prediction task with an accuracy of 0.94, precision of 0.98, recall of 0.85, and F1 score of 0.91. These indicators were used for probability mapping, and the total area of hazard (21,412.94 km²), vulnerability (480.98 km²), and risk (34,586.10 km²) was estimated.     

Mineral resource assessment using the unit regional value concept

The resources produced in some specific region may be measured in terms of the amount of resource produced and its value: if these measures are cumulated over the period of production and prorated over the area of a region. say in km², they yield the unit regional weight (u.r.w.) and unit regional value (u.r.v.) of resources produced in the region. Frequency distributions of u.r.w. and u.r.v. may be constructed by measuring them on a number of regions; for the 50 states in the U.S.A. the logarithm of u.r.v. is normally distributed and hence different regions may be ranked on this scale using the mean and standard deviation intervals as calibration levels. The u.r.w. and u.r.v. of the 50 states in the U.S.A., may be used as a reference background for such comparisons. The average u.r.v. for all resources produced over the period 1905 to 1972 for the 48 coterminous states is 54.954 (1967) U.S. (S). Alaska, over the same period, possess a u.r.v. of 2738 (1967) U.S. (S) and so its u.r.v. is some 20 times less: this yeilds a conservative measure of the future potential for development of the mineral resources of Alaska. This unconditional estimate of the u.r.v. of Alaska is based solely on its area and one way of refining this estimate is to introduce geology as a conditioning variable. The geological composition of each state in the U.S.A. was point counted from available geological maps of the states and the proportions of different rock units were expressed in terms of 65 standardized time-petrographic units. The accumulated data for ail 50 states yields a diversity (or richness=s−1) of 51 rocktypes: the range in value for the individual states extends from an s−1=1 in Louisiana to s−1=25 in California. Alaska is about seventh among the states in geological diversity and groups with Arizona, Montana. Utah. Nevada, and Washington. However, the dominant rocktype in Alaska is the detrital high-rank graywacke and this characteristic eliminates all but Nevada as a geologically comparable state. New Zealand also possesses similar geological characteristics. The diversity of mineral resources produced in each region may also be standardized and measured in a similar manner as richness=s−1. It has been found that there is a linear association between mineral resource diversity (Y) and the variety of geological roccktypes (X): the degree of common association between these two variables isr ²=80%. This relationship may now be used as predictor equation and we can calculate the expected value for Alaska as s−1=45 against an observed mincral resource variety of s−1=27. Since Nevada (s−1=49) and New Zealand (s−1=36) both possess much higher resource diversity than Alaska it is likely that the extra resources produced in these two regions should be present in Alaska. This permits us to pinpoint, first. the mineral resource sectors, such as constructional materials. fuels. metals. precious metals, and nonmetals, which are underproduced. By returning to the frequency distributions of u.r.v. (and u.r.w.) of the individual commodities which are likely to occur in Alaska, it is possible to estimate both what new resources may be expected and. very approximately. how much more of the resources already produced may be obtained in the future in Alaska. The annual value of the resources of Alaska from 1880 to 1972 may be treated as a time series and projections of future value may be made under different scenarios. This past history clearly emphasizes that the annual value of the mineral resources produced in Alaska is essentially determined by the “degree of commitment” given to investment in their development. This paper was presented at the International Geological Correlation Program (IGCP) Project 98: “Standards for Computer Applications ia Resource Studies” held at Taita Hills, Kenya, November 8–15, 1977. Par variable régionalisée. nous entendons une fonction d'espace, dont valeur varie d'un lieu à l'autre avec une certaine apparance de continuité, sans qu'il soit en général possible d'en représenter la variation par une loi mathèmatique extrapolable… Une teneur, dans un gisement minier, est une variable régionalisée.     

区域泥石流灾害的定量风险分析

概述了区域泥石流灾害的风险分析体系,指出了过去区域泥石流灾害危险性研究中的某些误区以及区域社会经济易损性评价的难点。借助于“灾害熵”的概念,提出了区域泥石流灾害危险性定量分析的一种新方法。通过将泥石流灾害的危险性和区域社会经济易损性进行分级,建立了风险评价矩阵。在此基础上,对区域泥石流灾害的风险进行了分级,可为有效地进行区域泥石流灾害的预警,以及为减灾防灾奠定了坚实的基础。     

Flood risk mapping and crop-water loss modeling using water footprint analysis in agricultural watershed,northern Iran

Natural Hazards - Spatial information on flood risk and flood-related crop losses is important in flood mitigation and risk management in agricultural watersheds. In this study, loss of water bound...     

区域气象干旱评估分析模式

为应对全球范围内日益严重的干旱问题,对区域气象干旱相对完整的评估分析模式开展了探讨。提出了从区域气象干旱识别到干旱特征值计算,再到干旱特征多变量分析的3个分析评估步骤。并以渭河流域为例,对研究区域进行了矩形干旱评估单元划分,选取了RDI（Reconnaissance Drought Index）为评估指标对区域内各单元各时段的干旱状态进行了识别,结果与历史记载的干旱年份吻合较好。分别采用了分布拟合、相关系数和Copula函数等统计学方法对区域干旱的干旱特征值（干旱历时、干旱面积、干旱强度和干旱频率）进行了特征分析,得出了一系列的单变量、双变量及多变量特征分析对比结果。通过对各类分布函数的计算和绘图,得到了渭河流域干旱事件发生的条件概率和重现期,形成了一套相对完整的区域干旱评估分析模式。     

Assessment of regional drought vulnerability and risk using principal component analysis and a Gaussian mixture model

Due to the complex characteristics of drought, drought risk needs to be quantified by combining drought vulnerability and drought hazard. Recently, the major focus in drought vulnerability has been on how to calculate the weights of indicators to comprehensively quantify drought risk. In this study, principal component analysis (PCA), a Gaussian mixture model (GMM), and the equal-weighting method (EWM) were applied to objectively determine the weights for drought vulnerability assessment in Chungcheong Province, located in the west-central part of South Korea. The PCA provided larger weights for agricultural and industrial factors, whereas the GMM computed larger weights for agricultural factors than did the EWM. The drought risk was assessed by combining the drought vulnerability index (DVI) and the drought hazard index (DHI). Based on the DVI, the most vulnerable region was CCN9 in the northwestern part of the province, whereas the most drought-prone region based on the DHI was CCN12 in the southwest. Considering both DVI and DHI, the regions with the highest risk were CCN12 and CCN10 in the southern part of the province. Using the proposed PCA and GMM, we validated drought vulnerability using objective weighting methods and assessed comprehensive drought risk considering both meteorological hazard and socioeconomic vulnerability.

     

Rapid analysis of risk assessment using developed simulation of chemical industrial accidents software package

The environmental consequences are defined as consequences of accidental release of hazardous substances to the natural environment. This release can lead to many hazards depending on the material stored. The consequences of these hazards to the environment are widespread and have significant importance to human communities living in the surroundings. The mathematical models are extremely useful tools to predict the impacts of chemical process accidents. The objective of this paper is to develop a software package for accident simulation and damage potential estimation. The software is coded in visual basic and is compatible with windows working environments. The software is called Simulation of chemical industrial accident. This application is a comprehensive software package which can be integrated with geographical information system to predict and display the consequence of chemical hazards. The software is a user-friendly and effective tool for evaluating the consequences of major chemical accidents, process decision making for land-use planning, namely locating suitable hazardous installations, hazardous waste disposal areas and emergency response plan.     

Susceptibility assessment for rainfall-induced landslides using a revised logistic regression method

Natural Hazards - Landslide susceptibility is the likelihood of a landslide occurring in an area. The logistic regression (LR) method is one of the most popular methods for landslide susceptibility...     

Flood risk assessment in Quzhou City (China) using a coupled hydrodynamic model and fuzzy comprehensive evaluation (FCE)

Natural Hazards - To evaluate urban flood risk while considering spatial and temporal characteristics, this paper establishes an assessment method based on a coupled hydrodynamic model and a fuzzy...     

Multivariate fire risk models using copula regression in Kalimantan,Indonesia

Natural Hazards - Forest fires have become a national issue yearly and elicited serious attention from the government and researchers in Indonesia. Copula-based joint distribution can construct a...