GIS-based flood risk assessment in suburban areas: a case study of the Fangshan District,Beijing

Suburban areas have become rapid development zones during China’s current urbanization. Generally, these areas are also regional precipitation centers that are prone to flood disasters. Therefore, it is important to assess the flood risk in suburban areas. In this study, flood risk was defined as the product of hazard and vulnerability based on disaster risk theory. A risk assessment index system was established, and the analytic hierarchy process method was used to determine the index weight. The Fangshan District in Beijing, China, which is an example of a typical suburban area undergoing rapid urbanization, was selected for this study. Six factors were considered in relation to hazard, and three factors were considered for vulnerability. Each indicator was discretized, standardized, weighted, and then combined to obtain the final flood risk map in a geographical information system environment. The results showed that the high and very high risk zones in the Fangshan District were primarily concentrated on Yingfeng Street, Xingcheng Street, Xincheng Street, and Chengguanzhen Street. The comparison to an actual flood disaster suggested that the method was effective and practical. The method can quantitatively reflect the relative magnitude and spatial distribution patterns of flood risk in a region. The method can be applied easily to most suburban areas in China for land use planning and flood risk management.     

Integrated risk assessment of flood disaster based on improved set pair analysis and the variable fuzzy set theory in central Liaoning Province,China

This study presents the methodology and procedure for risk assessment of flood disasters in central Liaoning Province, which was supported by geographical information systems (GIS) and technology of natural disaster risk assessment. On the basis of the standard formulation of natural disaster risk and flood disaster risk index, of which weights were developed using combined weights of entropy, the relative membership degree functions of variable fuzzy set (VFS) theory were calculated using improved set pair analysis, while level values were calculated using VFSs, including hazard levels, exposure levels, vulnerability levels and restorability levels, and the flood risk level for each assessment unit was obtained using the natural disaster index method. Consequently, integrated flood risk map was carried out by GIS spatial analysis technique. The results show that the southwestern and central parts of the study area possess higher risk, while the northwestern and southeastern parts possess lower risk. The results got by the assessment model fits the area of historical flood data; this study offer new insights and possibility to carry out an efficient way for flood disaster prevention and mitigation. The study also provides scientific reference in flood risk management for local and national governmental agencies.     

Characterizing flood hazard risk in data-scarce areas,using a remote sensing and GIS-based flood hazard index

The frequency in occurrence and severity of floods has increased globally. However, many regions around the globe, especially in developing countries, lack the necessary field monitoring data to characterize flood hazard risk. This paper puts forward methodology for developing flood hazard maps that define flood hazard risk, using a remote sensing and GIS-based flood hazard index (FHI), for the Nyamwamba watershed in western Uganda. The FHI was compiled using analytical hierarchy process and considered slope, flow accumulation, drainage network density, distance from drainage channel, geology, land use/cover and rainfall intensity as the flood causative factors. These factors were derived from Landsat, SRTM and PERSIANN remote sensing data products, except for geology that requires field data. The resultant composite FHI yielded a flood hazard map pointing out that over 11 and 18% of the study area was very highly and highly susceptible to flooding, respectively, while the remaining area ranged from medium to very low risk. The resulting flood hazard map was further verified using inundation area of a historical flood event in the study area. The proposed methodology was effective in producing a flood hazard map at the watershed local scale, in a data-scarce region, useful in devising flood mitigation measures.     

Landslide susceptibility analysis based on ArcGIS and Artificial Neural Network for a large catchment in Three Gorges region,China

A landslide susceptibility map is very important and necessary to efficiently prevent and mitigate the losses brought by natural hazard for a large area. For the purpose of landslide susceptibility analysis for the whole Xiangxi catchment (3,209 km²), Artificial Neural Network (ANN) analysis was applied as the main method. The whole catchment was divided into two parts: the training area and the implementation area. The backwater area (559 km²) of Xiangxi catchment was used as the training area for the ANN method. In the training area the correlations between the landslide distribution and its causative factors, which includes lithology, slope angle, slope curvature and river network, have been analyzed based on the geological map and digital elevation model (DEM). The back-propagation training algorithm in ANN was selected to train the sample data from the training area, which were composed of input data (causative factors) and target output data (landslide occurrence), in order to find the correlations between them. Based on these correlations and input data in the implementation area (causative factors), the network output data were obtained for the implementation area. In the end, a map of landslide susceptibility, which was established by network output data, was presented for Xiangxi catchment. ArcGIS was applied to extract and quantify input information from a DEM for susceptibility analysis and also to present the result visually. As a result, a landslide susceptibility map, in which 70 % of all landslides are rightly classified in the training area (backwater area), was created for Xiangxi catchment.     

Assessing flood hazard using flood marks and analytic hierarchy process approach: a case study for the 2013 flood event in Quang Nam,Vietnam

The production of flood hazard assessment maps is an important component of flood risk assessment. This study analyses flood hazard using flood mark data. The chosen case study is the 2013 flood event in Quang Nam, Vietnam. The impacts of this event included 17 deaths, 230 injuries, 91,739 flooded properties, 11,530 ha of submerged and damaged agricultural land, 85,080 animals killed and widespread damage to roads, canals, dykes and embankments. The flood mark data include flood depth and flood duration. Analytic hierarchy process method is used to assess the criteria and sub-criteria of the flood hazard. The weights of criteria and sub-criteria are generated based on the judgements of decision-makers using this method. This assessment is combined into a single map using weighted linear combination, integrated with GIS to produce a flood hazard map. Previous research has usually not considered flood duration in flood hazard assessment maps. This factor has a rather strong influence on the livelihood of local communities in Quang Nam, with most agricultural land within the floodplain. A more comprehensive flood hazard assessment mapping process, with the additional consideration of flood duration, can make a significant contribution to flood risk management activities in Vietnam.     

Landslide hazard and risk assessment: a?case study from the Hlohovec–Sered’ landslide area in south-west Slovakia

Landslide hazard or susceptibility assessment is based on the selection of relevant factors which play a role on the slope instability, and it is assumed that landslides will occur at similar conditions to those in the past. The selected statistical method compares parametric maps with the landslide inventory map, and results are then extrapolated to the entire evaluated territory with a final product of landslide hazard or susceptibility map. Elements at risk are defined and analyzed in relation with landslide hazard, and their vulnerability is thus established. The landslide risk map presents risk scenarios and expected financial losses caused by landslides, and it utilizes prognoses and analyses arising from the landslide hazard map. However, especially the risk scenarios for future in a selected area have a significant importance, the literature generally consists of the landslide susceptibility assessment and papers which attempt to assess and construct the map of the landslide risk are not prevail. In the paper presented herein, landslide hazard and risk assessment using bivariate statistical analysis was applied in the landslide area between Hlohovec and Sered?? cities in the south-western Slovakia, and methodology for the risk assessment was explained in detail.     

A Hazard Assessment Method for Potential Earthquake-Induced Landslides – A Case Study in Huaxian County, Shaanxi Province

The hazard assessment of potential earthquake-induced landslides is an important aspect of the study of earthquake-induced landslides. In this study, we assessed the hazard of potential earthquake-induced landslides in Huaxian County with a new hazard assessment method. This method is based on probabilistic seismic hazard analysis and the Newmark cumulative displacement assessment model. The model considers a comprehensive suite of information, including the seismic activities and engineering geological conditions in the study area, and simulates the uncertainty of the intensity parameters of the engineering geological rock groups using the Monte Carlo method. Unlike previous assessment studies on ground motions with a given exceedance probability level, the hazard of earthquake-induced landslides obtained by the method presented in this study allows for the possibility of earthquake-induced landslides in different parts of the study area in the future. The assessment of the hazard of earthquake-induced landslides in this study showed good agreement with the historical distribution of earthquake-induced landslides. This indicates that the assessment properly reflects the macroscopic rules for the development of earthquake-induced landslides in the study area, and can provide a reference framework for the management of the risk of earthquake-induced landslides and land planning.     

Landslide hazard mapping along national highway-154A in Himachal Pradesh,India using information value and frequency ratio

For the socio-economic development of a country, the highway network plays a pivotal role. It has therefore become an imperative to have landslide hazard assessment along these roads to provide safety. The current study presents landslide hazard zonation maps, based on the information value method and frequency ratio method using GIS on 1:50,000 scale by generating the information about the landslide influencing factors. The study was carried out in the year 2017 on a part of Ravi river catchment along one of the landslide-prone Chamba to Bharmour road corridor of NH-154A in Himachal Pradesh, India. A number of landslide triggering geo-environmental factors like “slope, aspect, relative relief, soil, curvature, Land Use and Land Cover (LULC), lithology, drainage density, and lineament density” were selected for landslide hazard mapping based on landslide inventory. The landslide inventory has been developed using satellite imagery, Google earth and by doing exhaustive field surveys. A digital elevation model was used to generate slope gradient, slope aspect, curvature, and relative relief map of the study area. The other information, i.e., soil maps, geological maps, and toposheets, have been collected from various departments. The landslide hazard zonation map was categorized namely “very high hazard, high hazard, medium hazard, low hazard, and very low hazard.” The results from these two methods have been validated using area under curve (AUC) method. It has been found that hazard zonation map prepared using frequency ratio model had a prediction rate of 75.37% while map prepared using information value method had prediction rate of 78.87%. Hence, on the basis of prediction rate, the landslide hazard zonation map, obtained using information value method, was experienced to be more suitable for the study area.     

Assessment of flood hazard,vulnerability and risk of mid-eastern Dhaka using DEM and 1D hydrodynamic model

Floods are regular feature in rapidly urbanizing Dhaka, the capital city of Bangladesh. It is observed that about 60% of the eastern Dhaka regularly goes under water every year in monsoon due to lack of flood protection. Experience gathered from past devastating floods shows that, besides structural approach, non-structural approach such as flood hazard map and risk map is effective tools for reducing flood damages. In this paper, assessment of flood hazard by developing a flood hazard map for mid-eastern Dhaka (37.16 km²) was carried out by 1D hydrodynamic simulation on the basis of digital elevation model (DEM) data from Shuttle Radar Topography Mission and the hydrologic field-observed data for 32 years (1972–2004). As the topography of the area has been considerably changed due to rapid land-filling by land developers which was observed in recent satellite image (DigitalGlobe image; Date of imagery: 7th March 2007), the acquired DEM data were modified to represent the current topography. The inundation simulation was conducted using hydrodynamic program HEC-RAS for flood of 100-year return period. The simulation has revealed that the maximum depth is 7.55 m at the southeastern part of that area and affected area is more than 50%. A flood hazard map was prepared according to the simulation result using the software ArcGIS. Finally, to assess the flood risk of that area, a risk map was prepared where risk was defined as the product of hazard (i.e., depth of inundation) and vulnerability (i.e., the exposure of people or assets to flood). These two maps should be helpful in raising awareness of inhabitants and in assigning priority for land development and for emergency preparedness including aid and relief operations in high-risk areas in the future.     

Monte Carlo simulation-aided analytical hierarchy process (AHP) for flood susceptibility mapping in Gabes Basin (southeastern Tunisia)

Flash floods are among the most severe hazards which have disastrous environmental, human, and economic impacts. This study is interested in the characterization of flood hazard in Gabes Catchment (southeastern Tunisia), considered as an important step for flood management in the region. Analytical hierarchy process (AHP) and geographic information system are applied to delineate and characterize flood areas. A spatial database was developed based on geological map, digital elevation model, land use, and rainfall data in order to evaluate the different factors susceptible to affect flood analysis. However, the uncertainties that are associated with AHP techniques may significantly impact the results. Flood susceptibility is analyzed as a function of weights using Monte Carlo (MC) simulation and Global sensitivity analysis. AHP and MC–AHP models gave similar results. However, compared to AHP approach, MC–AHP confidence intervals (95%) of the overall scores had small overlaps. Results obtained were validated by remote sensing data for the zones that showed very high flood hazard during the extreme rainfall event of June 2014 that hit the study basin.     

基于指标信度测度赋权的岩溶隧道水害危险性集对云评价研究

隧道水害危险性评价是一个非线性复杂的不确定系统问题。首先,针对其评价指标参数具有不确定性、模糊性和随机性等特点,在充分考虑岩溶隧道水害危险性评价指标关联性的基础上,提出了基于Jousselme距离的指标信度测度动态赋权理论,实现不同的实例、不同的指标实测值对整个系统的动态赋权,降低实际工作中由于指标实测值误差或错误导致评价结果偏差的风险;其次,运用云理论优化集对联系度,与所得权重加权得出系统综合云联系度,并与等级评价区间期望加权平均得到危险值,同时生成对应的等级云图判定隧道水害危险性等级,进而判定岩溶隧道水害危险状态,实现水害危险等级判定的可视化;再次,基于大气降水为岩溶隧道水害主要来源的视角,选取年均降水量、入渗系数、汇水面积、渗透系数和单位涌水量5项指标作为集对云评价指标,并以6条典型岩溶隧道为样本数据进行模型检验,发现评价结果与其他方法的评价结果相吻合,证明了该模型的可靠性和有效性。最后,将模型应用于京珠高速公路媲双坳岩溶隧道水害事故中,评价结果与实际情况相符,采取与评价等级相对应的处治措施,取得了良好的水害治理效果,表明该模型具有工程实用价值,评价流程可操作性强,为岩溶隧道水害的预测和防治提供参考。      

Exploring the sample size and replications scenarios effect on spatial prediction of flood,using MARS and MaxEnt methods case study: saliantape catchment,Golestan, Iran

Flood has always been a destructive natural hazard during the recent years. Hence, this research aimed to predict the potentiality and probability of flood phenomenon by using the two well-known models, i.e., the MARS algorithm (multivariate adaptive regression splines) and MaxEnt (maximum entropy) method in the Saliantapeh catchment, Golestan province, Iran, covering 4515.47 km². First, documentary sources report and field surveys were used to provide a flood database map. Then, to prepare the flood spatial potentiality map (FSPM), we select sixteen influential variables as predictors. Furthermore, the relative contributions of predicting factors are estimated using the MaxEnt method. For the analysis of data sensitivity and the uncertainty of the proposed models, different scenarios including the sample size (50%/50%, 80%/20%, and 70%/30%, respectively, for training and validation), and the number of replications (5, 10, and 20) were used. Along with the area under the ROC curve (AUC), the highest accuracy for both models corresponds to the first scenario of sample size (80/20%). Contrarywise, it can be concluded that for this scenario, the MARS technique indicated higher predictive skill (AUC?=?98.51%). Regarding the second scenario, which is corresponding to the replicate, the MARS model with 20 replications still has the highest accuracy (94.70%) compared to the other scenarios and the MaxEnt model. The findings of robustness demonstrated that the scenarios with the greatest AUC value have the highest robustness. This work demonstrates that the utilization of the best accurate model with high certainty along with FSPM may be useful to identify and manage the areas that are most susceptible to flood.

     

Assessment of shallow landslide susceptibility using the transient infiltration flow model and GIS-based probabilistic approach

This study proposes a probabilistic analysis method for modeling rainfall-induced shallow landslide susceptibility by combining a transient infiltration flow model and Monte Carlo simulations. The spatiotemporal change in pore water pressure over time caused by rainfall infiltration is one of the most important factors causing landslides. Therefore, the transient infiltration hydrogeological model was adopted to estimate the pore water pressure within the hill slope and to analyze landslide susceptibility. In addition, because of the inherent uncertainty and variability caused by complex geological conditions and the limited number of available soil samples over a large area, this study utilized probabilistic analysis based on Monte Carlo simulations to account for the variability in the input parameters. The analysis was performed in a geographic information system (GIS) environment because GIS can deal efficiently with a large volume of spatial data. To evaluate its effectiveness, the proposed analysis method was applied to a study area that had experienced a large number of landslides in July 2006. For the susceptibility analysis, a spatial database of input parameters and a landslide inventory map were constructed in a GIS environment. The results of the landslide susceptibility assessment were compared with the landslide inventory, and the proposed approach demonstrated good predictive performance. In addition, the probabilistic method exhibited better performance than the deterministic alternative. Thus, analysis methods that account for uncertainties in input parameters are more appropriate for analysis of an extensive area, for which uncertainties may significantly affect the predictions because of the large area and limited data.     

山东暴雨洪涝灾害的风险区划与分析

根据暴雨洪涝灾害致灾因子危险性、孕灾环境敏感性、承载体易损性和防灾减灾能力4个一级因子,以山东地区为研究对象,综合考虑降雨、地形地势、河网密度、植被、人口和经济实力、道路交通信息等因子进行风险区划与分析。利用地理信息系统软件（ArcGIS）将上述因子进行归一化来获得标准化的多源栅格数据,结合层次分析法和自然断点法确定相关指标的权重,建立了暴雨洪涝灾害的风险评估模型,最后得到了山东地区暴雨洪涝灾害综合风险区划等级评估图。对研究区进行定性和定量分析后得出结论,山东地区暴雨洪涝灾害发生的高风险区在鲁中西部、鲁南及山东半岛东部沿海部分地区,此结论与历史数据基本吻合。研究结果为预防山东暴雨洪涝灾害提供了参考信息。     

A new probabilistic seismic hazard study of Spain

In this paper, we present a probabilistic seismic hazard analysis (PSHA) for mainland Spain that takes into account recent new results in seismicity, seismic zoning, and strong ground attenuation not considered in the latest PSHA of the Spanish Building Code. Those new input data have been obtained as a three-step project carried out in order to improve the existing hazard map for mainland Spain. We have produced a new earthquake catalogue for the area, in which the earthquakes are given in moment magnitude through specific deduced relationships for our territory based on intensity data (Mezcua et al. in Seismol Res Lett 75:75–81, 2004). In addition, we included a new seismogenetic zoning based on the recent partial zoning studies performed by different authors. Finally, as we have developed a new strong ground motion model for the area García Blanco (2009), it was considered in the hazard calculation together with other attenuations gathered from different authors using data compatible with our region. With this new data, a logic tree process is defined to quantify the epistemic uncertainty related to those parts of the process. A sensitivity test has been included in order to analyze the different models of ground motion and seismotectonic zonation used in this work. Finally, after applying a weighting scheme, a mean hazard map for PGA, based on rock type condition for 10% exceedance probability in 50 years, is presented, including 15th and 85th percentile hazard maps. The main differences with the present official building code hazard map are analyzed.     

Evaluation of food risk parameters in the Day River Flood Diversion Area,Red River Delta,Vietnam

An interdisciplinary approach is necessary for flood risk assessment. Questions are often raised about which factors should be considered important in assessing the flood risk in an area and how to quantify these factors. This article defines and quantitatively evaluates the flood risk factors that would affect the Day River Flood Diversion Area in the context of integrated flood management in the Red River Delta, Vietnam. Expert analysis, in conjunction with field survey and Analytical Hierarchy Process (AHP), is applied to define and quantify parameters (indicators, subcomponents, and components) that contribute to flood risk. Flood duration is found to be the most prominent indicator in determining flood hazard. Residential buildings, population, and pollution are other fairly significant indicators contributing to flood vulnerability from the economic, social, and environmental perspectives, respectively. The study results will be useful in developing comprehensive flood risk maps for policy-makers and responsible authorities. Besides, local residents will also be able to implement suitable measures for reducing flood risk in the study area.     

广州东濠涌流域城市洪涝灾害情景模拟与风险评估

绘制直观与可靠的城市洪涝灾害风险区划图,为城市防洪排涝相关部门决策提供参考依据。以广州市东濠涌流域为研究区域,综合考虑城市降雨、径流、地形和排水系统特性,构建基于InfoWorks ICM的一维-二维耦合城市洪涝仿真模型,模拟暴雨重现期为1年、5年、50年情景下的洪涝过程并获取致灾因子数据。调研分析区域的孕灾环境、承灾体和防灾减灾能力概况,结合层次分析法、评价等级和阈值划分等进行洪涝灾害风险评估。结果表明:城市洪涝仿真模型在一维排水系统和二维地面淹没模拟上均有较好的精度和可靠性,保证了致灾因子数据的可靠性;风险区划图能较好地反映流域的风险分布;随着重现期增大,较高、高风险区的面积显著增加,为防洪排涝重点关注区域。     

Landslide hazard zonation using analytical hierarchy process along National Highway-3 in mid Himalayas of Himachal Pradesh,India

Landslide zonation studies emphasize on preparation of landslide hazard zonation maps considering major instability factors contributing to occurrence of landslides. This paper deals with geographic information system-based landslide hazard zonation in mid Himalayas of Himachal Pradesh from Mandi to Kullu by considering nine relevant instability factors to develop the hazard zonation map. Analytical hierarchy process was applied to assign relative weightages over all ranges of instability factors of the slopes in study area. To generate landslide hazard zonation map, layers in geographic information system were created corresponding to each instability factor. An inventory of existing major landslides in the study area was prepared and combined with the landslide hazard zonation map for validation purpose. The validation of the model was made using area under curve technique and reveals good agreement between the produced hazard map and previous landslide inventory with prediction accuracy of 79.08%. The landslide hazard zonation map was classified by natural break classifier into very low hazard, low hazard, moderate hazard, high hazard and very high landslide hazard classes in geographic information system depending upon the frequency of occurrence of landslides in each class. The resultant hazard zonation map shows that 14.30% of the area lies in very high hazard zone followed by 15.97% in high hazard zone. The proposed model provides the best-fit classification using hierarchical approach for the causative factors of landslides having complex structure. The developed hazard zonation map is useful for landslide preparedness, land-use planning, and social-economic and sustainable development of the region.     

Analyzing Hazard Potential of Typhoon Damage by Applying Grey Analytic Hierarchy Process

This study develops a model using the grey analytic hierarchy process to analyze hazard potential of typhoon damage. The main component of the model is the grey analytic hierarchy process involving the analytic hierarchy process and grey relational analysis. First, the model is employed to determine the hazard potential indices. Each region in the project area is then divided into various classes using the two breaking points method to classify appropriately the hazard potential indices. The map of classified hazard potential in the project area can enable decision makers to establish a strategy for preventing flood disaster.     

Flood inundation mapping and hazard assessment of Baitarani River basin using hydrologic and hydraulic model

Frequent flood is a concern for most of the coastal regions of India. The importance of flood maps in governing strategies for flood risk management is of prime importance. Flood inundation maps are considered dependable output generated from simulation results from hydraulic models in evaluating flood risks. In the present work, a continuous hydrologic-hydraulic model has been implemented for mapping the flood, caused by the Baitarani River of Odisha, India. A rainfall time-series data were fed into the hydrologic model and the runoff generated from the model was given as an input into the hydraulic model. The study was performed using the HEC-HMS model and the FLO-2D model to map the extent of flooding in the area. Shuttle Radar Topographic Mission (SRTM) 90 m Digital Elevation Model (DEM) data, Land use/Land cover map (LULC), soil texture data of the basin area were used to compute the topographic and hydraulic parameters. Flood inundation was simulated using the FLO-2D model and based on the flow depth, hazard zones were specified using the MAPPER tool of the hydraulic model. Bhadrak District was found to be the most hazard-prone district affected by the flood of the Baitarani River. The result of the study exhibited the hydraulic model as a utile tool for generating inundation maps. An approach for assessing the risk of flooding and proper management could help in mitigating the flood. The automated procedure for mapping and the details of the study can be used for planning flood disaster preparedness in the worst affected area.