Flood Hazard Prediction from Soil Properties by Remote Sensing and Genographic Information System:A Case Study of Mae Rim Watershed,Chiang Mai Province,Thailand

Physiography and soil in Mae Rim watershed, Chiang Mai Province, Thailand were investigated by using aerial photographs and satellite image in conjunction with field work, and soil infiltration rate and soil shear resistance were measured in field. Many factors affecting runoff were analyzed using the Integrated Land and Water Information System (ILWIS). As a result, a model determining flood hazard was set up. Three maps including runoff curve number map, runoff coefficient map, and flood inundation map were created. In addition, the time of concentration was predicted.

Flash flood hazard mapping: A pilot case study in Xiapu River Basin, China

Flash flood hazard mapping is a supporting component of non-structural measures for flash flood prevention. Pilot case studies are necessary to develop more practicable methods for the technical support systems of flash flood hazard mapping. In this study, the headwater catchment of the Xiapu River Basin in central China was selected as a pilot study area for flash flood hazard mapping. A conceptual distributed hydrological model was developed for flood calculation based on the framework of the Xinanjiang model, which is widely used in humid and semi-humid regions in China. The developed model employs the geomorphological unit hydrograph method, which is extremely valuable when simulating the overland flow process in ungauged catchments, as compared with the original Xinanjiang model. The model was tested in the pilot study area, and the results agree with the measured data on the whole. After calibration and validation, the model is shown to be a useful tool for flash flood calculation. A practicable method for flash flood hazard mapping using the calculated peak discharge and digital elevation model data was presented, and three levels of flood hazards were classified. The resulting flash flood hazard maps indicate that the method successfully predicts the spatial distribution of flash flood hazards, and it can meet the current requirements in China.

Case Study on Identification of Flood Hazard in the Lower Catchment Area of the Attanagalu Oya River Basin

The present work aims to identify flood hazards and risks, particularly to the Attanagalu Oya river basin in Gampaha district, the western province in Sri Lanka. Attanagalu Oya river catchment area periodically faced flood hazards. The flood is categorized by complex like 2008, 2010, 2016, 2017, and it chose 2016 as the primary flood event. Study areas have been selected depending on data availability. Attanagalu Oya river basin is mainly focused as a study area. However, here selected only four Grama Niladhari Divisions are as a sample area. Those are;Kirindivita, Ambanvita, Thammita West, Gonagaha1. Furthermore, many flood hazards can be identified when considering the flood events history. But here selected only two years were 2010 and 2016. These two years were selected with high flood events. For the study, that flood series used 1 feet elevation contours used to identify flood levels and used LiDAR image to identify risk areas in the study site. Due to the blockage of the main waterways that discharge water into the Negombo Lagoon, limited water transportation, low lying land reclamation for development, mainly affect paddy lands and roads, and flood as a major problem identified temporarily and spatially. Eventually, the study could identify flood-prone areas and map the risk zones within the study area.

Flood Hazard Mapping of Lower Indus Basin Using Multi-Criteria Analysis

Flooding has been one of the recurring occurred natural disasters that induce detrimental impacts on humans, property and environment. Frequent floods is a severe issue and a complex natural phenomenon in Pakistan with respect to population affected, environmental degradations, and socio-economic and property damages. The Super Flood, which hit Sindh in 2010, has turned out to be a wakeup call and has underlined the overwhelming challenge of natural calamities, as 2010 flood and the preceding flood in 2011 caused a huge loss to life, property and land use. These floods resulted in disruption of power, telecommunication, and water utilities in many districts of Pakistan, including 22 districts of Sindh. These floods call for risk assessment and hazard mapping of Lower Indus Basin flowing in the Sindh Province as such areas were also inundated in 2010 flood, which were not flooded in the past in this manner. This primary focus of this paper is the use of Multi-criteria Evaluation (MCE) methods in integration with the Geographical Information System (GIS) for the analysis of areas prone to flood. This research demonstrated how GIS tools can be used to produce map of flood vulnerable areas using MCE techniques. Slope, Aspect, Curvature, Soil, and Distance from Drainage, Land use, Precipitation, Flow Direction, and Flow Accumulation are taken as the causative factors for flooding in Lower Indus Basin. Analytical Hierarchy Process-AHP was used for the calculation of weights of all these factors. Finally, a flood hazard Map of Lower Indus Basin was generated which delineates the flood prone areas in the Sindh province along Indus River Basin that could be inundated by potential flooding in future. It is aimed that flood hazard mapping and risk assessment using open source geographic information system can serve as a handy tool for the development of land-use strategies so as to decrease the impact from flooding.

Urban Sprawl in Wadi Goss Watershed (Jeddah City/Western Saudi Arabia) and Its Impact on Vulnerability and Flood Hazards

Today, climate change imposes enormous challenges on a global scale. The interactions of the balances between the need for development, population growth, massive urbanization generate a negative impact on the presence of these climate changes. One of the direct consequences of these changes is the phenomenon of flash floods, a phenomenon that hit the city of Jeddah (city located in west of Saudi Arabia) twice, one in 2009 and the other in 2011, causing significant human and material damage. Floods are considered as a direct result of the combination of extreme weather and hydrological phenomena;in most cases, the magnitude of these floods is magnified by anthropogenic factors, which increases the risk. According to the risk triangle, risk is defined as a probabilistic function that depends on three essential elements: exposure, vulnerability and hazard. If any of these three elements undergo growth the risk also does so and vice versa. Exposure and vulnerability will depend on the presence of human activities in the study area. This study is conducted on the Wadi Goss watershed as it was one of the most violent basins during the 2009 and 2011 floods. Indeed, we present in this study the extent of the urban extension in the Wadi Goss watershed, since 1984 to days and this by the using Landsat images. Given the nature of the study area, we present a method based on the calculation of various indices followed by a classification operation in order to define the urbanized zones inside the Wadi Goss watershed and then estimate the urban sprawl inside the watershed. We also present in this paper, the characteristics of the watershed as well as the evolution of the urbanized areas exposed to the phenomenon of floods and their contribution to the changes of the hydrological behavior of the basin, and to increase the evolution of the risk of the floods. We have shown through this study that the urban footprint has increased from 90 hectares in 1985 to 850 hectares in 2015. This urban footprint represents 12% of the total area of the watershed. Most of the urban evolution was operated on the wadi area with a concentration in the western part of the basin and especially at its outlet.

Assessing Flood Hazard at River Basin Scale: Comparison between HECRAS-WMS and Flood Hazard Index (FHI) Methods Applied to El Maleh Basin, Morocco

The cartography of floods by two different approaches enabled us to determine the limits and the advantages of each one of them. This cartography has been applied to the El Maleh basin situated in the South-East of Morocco. The HEC-RAS approach consists of a combination of the surface hydrologic model and the digital terrain model data. This combination allows thereafter the mapping of the flood zones by the use of the WMS software. Thus it can predict the probability occurrence of floods at various frequency times and determine the intensity of the flood (depth and velocity of flood water) inside the El Maleh river by using the existing hydrological data. Otherwise FHI method approach introduces a multi-criteria index to assess flood risk areas in a regional scale. Six parameters (flow accumulation, distance from drainage network, drainage network density, slope, land use, and geology) were used in this last method. The relative importance of each parameter for the occurrence and severity of flood has been connected to weight values. These values are calculated following an Analytical Hierarchy Process: AHP, a method originally developed for the solution of Operational Research problems. According to their weight values, information of the different parameters is superimposed, resulting to flood risk mapping. The use of the WMS model allowed us to accurately map the flood risk areas with precisely flood heights in different levels. However, this method is only applicable for a small portion of the basin located downstream of the hydrological station. Otherwise, the FHI method allows it to map the entire basin but without giving an indication of the water levels reached by floods. One method does not exclude the other since both approaches provide important information for flood risk assessment.

Flood Risk Assessment in the Lower Valley of Ouémé, Benin

In response to the increased frequency of flood events in recent years, it has become crucial to enhance preparedness and anticipation through precise flood risk assessments. To this end, this study aims to produce updated and precise flood risk maps for the Lower Valley of Ouémé River Basin, located in the South of Benin. The methodology used consisted of a combination of geographical information systems (GIS) and multi-criteria analysis, including Analytical Hierarchy Process (AHP) methods to define and quantify criteria for flood risk assessment. Seven hydro-geomorphological indicators (elevation, rainfall, slope, distance from rivers, flow accumulation, soil type, and drainage density), four socio-economic vulnerability indicators (female population density, literacy rate, poverty index, and road network density), and two exposure indicators (population density and land use) were integrated to generate risk maps. The results indicate that approximately 21.5% of the Lower Valley is under high and very high flood risk, mainly in the south between Dangbo, So-Ava, and Aguégués. The study findings align with the historical flood pattern in the region, which confirms the suitability of the used method. The novelty of this work lies in its comprehensive approach, the incorporation of AHP for weighting factors, and the use of remote sensing data, GIS technology, and spatial analysis techniques which adds precision to the mapping process. This work advances the scientific understanding of flood risk assessment and offers practical insights and solutions for flood-prone regions. The detailed flood risk indicator maps obtained stand out from previous studies and provide valuable information for effective flood risk management and mitigation efforts in the Lower Valley of Ouémé.

The Impacts of Flood and Local Communities’ Coping Strategies along the River Gambia

Flood disasters as Climate change hazards are common in developing countries, particularly in communities along the river Gambia. Local communities, for instance, had their local coping strategies that enabled them to stay in their communities even amid these ordeals, and climate change disaster threats. This work strives to understand flood impacts and the local peoples’ adaptation or coping strategies along the River Gambia basin. A community-based cross-sectional research study of 422 research participants of which 294 are males (69.7%) and females 128 (30.3%), and a focus group discussion of 10 groups which comprised 5 female groups and 5 male groups respectively found that 98.6% of the households experienced floods in their community, and 70.6% experienced flood in their houses, 2.1% have impending flood information and 88.4% do not know evacuation centres. The majority of the households had some local coping strategies, but they acknowledged their insufficient effectiveness. The result also shows that the impact of floods on farmlands, roads, buildings, and livestock was greatly felt. Coping strategies such as sandbags, raised elevations, contour bonds, dikes, and buildings on highlands were all found to be common mechanisms the local people used. The study opines that floods affect communities, but the effects vary depending on individual assets.

Analysis of Weather Anomalies to Assess the 2021 Flood Events in Yaounde, Cameroon (Central Africa)

Extreme weather anomalies such as rainfall and its subsequent flood events are governed by complex weather systems and interactions between them. It is important to understand the drivers of such events as it helps prepare for and mitigate or respond to the related impacts. In line with the above statements, quarter-hourly data for the year 2021 recorded in the Yaounde meteorological station were synthesized to come out with daily and dekadal (10-day averaged) anomalies of six climate factors (rainfall, temperature, insolation, relative humidity, dew point and wind speed), in order to assess the occurrences and severity of floods to changing weather patterns in Yaounde. In addition, Precipitation Concentration Index (PCI) was computed to evaluate the distribution and analyse the frequency and intensity of precipitation. Coefficient of variation (CV) was used to estimate the seasonal and annual variation of rainfall patterns, while Mann-Kendall (MK) trend test was performed to detect weather anomalies (12-month period variation) in quarter-hourly rainfall data from January 1st to December 31st 2021. The Standard Precipitation Index (SPI) was also used to quantify the rainfall deficiency of the observed time scale. Results reveal that based on the historical data from 1979 to 2018 in the bimodal rainfall forest zone, maximum and minimum temperature averages recorded in Yaounde in 2021 were mostly above historical average values. Precipitations were rare during dry seasons, with range value of 0 - 13.6 mm for the great dry season and 0 - 21.4 mm for the small dry season. Whereas during small and great rainy seasons, rainfalls were regular with intensity varying between 0 and 50 mm, and between 0 and 90.4 mm, respectively. The MK trend test showed that there was a statistical significant increase in rainfall trend for the month of August at a 5% level of significance, while a significant decreasing trend was observed in July and December. There was a strong irregular rainfall distribution during the months of February, July and December 2021, with a weather being mildly wetted during all the dry seasons and extremely wetted in August. Recorded flooding days within the year of study matched with heavy rainy days including during dry seasons.

Viral outbreaks and communicable health hazards due to devastating floods in Pakistan

Pakistan is a developing country that has a population of 190 million people and faces a huge burden of viral diseases. Every year during monsoon season heavy rain fall and lack of disaster management skills potentially increase the transmission of waterborne diseases, vector borne diseases and viral outbreaks. Due to severe flooding, thousands of people lose their lives and millions are displaced each year. In most of the cases the children who lose their family members are forced into illegal professions of begging, child labor and prostitution which make them prone to sexually transmitted infections. Up to date, no scientific study has been conducted nationwide to illustrate epidemiological patterns of waterborne diseases, vector borne diseases and viral epidemics during flash flood. Mosquito sprays would not be a sufficient approach for dengue eradication; mass awareness, larvicide and biological control by Guppy fishes are also effective strategies to overcome dengue problem. International health bodies and non-governmental organizations must take note of this alerting situation and take adequate steps such as financial/medical aid in order to defeat the after-effects of flood.

Assessing Social Vulnerability to Flood Hazards in the Dutch Province of Zeeland

The 2007 European Union Floods Directive encouraged member nations to pursue a more integrated view of flood risks and management strategies, taking into account social vulnerabilities of residents. To date, most flood-risk analyses conducted by the Dutch government have focused on physical risk. This study utilizes fine-scale data to construct a social vulnerability index for 147 districts of the Dutch province of Zeeland, located in the Southwestern Delta and the scene of widespread devastation following the 1953 North Sea Flood. Factor analysis of 25 indicators of social vulnerability selected from related research in Europe and the United States results in seven factors explaining roughly 66% of the total variance. These factors of social vulnerability in Zeeland are urban density,low-income households, recent population change, female gender, train access, and self-employed and service-sector employment. The index was constructed using the toploading variable in each of these factors, with weights determined by the variance explained by each factor.Scores range from a low of 0.20 in Schore, municipality of Kapelle, to the highest score of 0.64 in Oudelandse Hoeve of Terneuzen. The most vulnerable districts are located in South Zeeland, with eight of the 10 found in Terneuzen.The majority of less vulnerable districts are located in Zeeland’s central region.

城市洪涝风险的多方法组合评估与应用

近年来,受全球气候变化与城镇化快速发展的双重影响,城市极端降水事件频发,由此引发的城市洪涝灾害常造成灾难性的生命和财产损失,给城市公共安全带来了严重威胁。由于不同评估方法中指标赋权不同,评价结果往往存在较大差异,给风险评估与区划工作带来了诸多困难。因此,通过融合不同方法的权重构建一套复合权重,进而解决不同评估方法中结论非一致性的问题,这对于提升风险评估的准确性是至关重要的。该文以湖北省为例,旨从危险性、暴露性、脆弱性和恢复性四个层面构建城市洪涝风险评估体系。首先,分别采用熵权法和层次分析法计算指标权重;之后,通过Kendall检验判断两套权重序列的一致性并给出相应的复合权重计算结果;最后以湖北省下辖8个城市的历史洪涝事件为例,对上述风险评价结果进行了验证。结果显示,与熵权法和层次分析法相比,基于复合权重的组合评价方法具有更高的准确率。

考虑时间变化的洪涝灾害损失评估

洪涝灾害是对我国影响最大的自然灾害之一。聚焦灾害损失评估问题,本文构建了考虑时间变化的洪涝灾害损失函数。一方面,表征灾害损失随着致灾因子强度先递增、而后增幅趋缓的静态S型曲线关系;另一方面,通过量级、形状和位置三个参数综合考虑灾害损失随时间的动态变化情况。基于《中国水旱灾害防御公报》提供的受灾人口、直接经济损失数据,对于各省级行政区2006—2021年洪涝灾害损失进行评估分析。结果表明:通过拟合洪涝灾害损失函数,洪涝灾害损失关于致灾因子强度和时间的三维空间散点图可有效地拓展成为连续的三维空间曲面及二维空间热力图。各省级行政区受灾人口整体上呈现出逐年下降的特征,但随致灾因子强度的增加而趋于增加。各省级行政区直接经济损失则表现出明显的差异,随时间呈现出大幅下降、缓慢下降和略有增加等不同特征。考虑时间变化的洪涝灾害损失函数是变化环境下灾害评估的有效工具,可为区域洪涝灾情评估提供借鉴和参考。

The Salient Issues of Coastal Hazards and Disasters in Nigeria

The Nigerian coastline which stretches about 853 km has four distinct morphological zones namely, Barrier Lagoon, Mahin Mud coast, Niger Delta and Strand coast. Nigeria’s coastal zone is richly blessed with various natural resources like oil, gas, fish, sand etc., which are presently being exploited for economic development. Coastal populations have increased erratically from about 20% of the National population in 1993 to approximately 51,037,122 m (30% of the national population) in 2011. Development of coastal areas in Nigeria is accelerating and user conflicts are increasing. Both natural and anthropogenic activities in the coastal zone are leading to coastal hazards and eventual rapid degradation of the area. Significant coastal hazards include coastal erosion, storm surges, floods, land subsidence, pollution, especially oil spills and possibly seismicity, which could lead to earthquakes and tsunamis. These hazards are leading to disasters and effecting the socio-economic sustainability of the coastal area.

上海城区动态洪水风险图应用系统及典型暴雨内涝分析

【目的】为了提高沿海超大城市对洪涝灾害的先知先觉能力,快速预测分析洪涝潮组合影响下的淹没风险时空分布,【方法】以水文-水动力暴雨洪水分析模型为核心模块,通过与外部的气象精细化降雨预报数据库、自动雨量站实时监测数据库及实时水情、闸泵运行数据库相关联,研发了上海城区动态洪水风险图应用系统。采用由雨量站点到气象格网和水力网格的降雨二级空间融合技术,实现了模型与气象预报降雨数据的有效耦合。利用数据挖掘提取和GIS空间分析技术构建了包含10项洪水风险要素要点的城市内涝预报专报自动生成方法,实现了对内涝风险的快速一站式概览。利用系统可以对城市暴雨、河道洪水和风暴潮等单一发生或遭遇组合引起的淹没分布进行快速实时预报计算,模拟和预测城市洪涝潮灾害的有关淹没特征数据和淹没动态过程。【结果】利用系统分析了2023年6月23—24日暴雨的内涝风险分布,将模型模拟的积水区域与积水监测站、灾情直报和热线灾报的积水点进行对比,结果显示在150处对比积水点中,有129处误差不超过20 cm,占86%。模型模拟的积水空间分布与实际情况基本接近。【结论】结果表明:系统满足汛期常态化、业务化运行需求,能够为城市洪涝风险的实时动态分析和防汛指挥决策提供重要工具。

考虑降雨-洪水-泥沙作用下的淤地坝溃决致灾风险评估

淤地坝一旦遭遇极端降雨极易导致洪水漫顶溃决,将对下游人民群众造成极大威胁,亟需开展淤地坝溃决风险定量评估。现有研究忽略泥沙对溃决致灾过程的影响。本研究通过分析降雨诱发的泥沙对溃决致灾的影响过程,揭示降雨-洪水-泥沙作用下的溃决致灾机制,建立考虑降雨-洪水-泥沙作用下的淤地坝溃决致灾风险定量评估模型,将传统的“降雨-洪水”研究发展为“降雨-洪水-泥沙”,实现溃决坝体的精准判定和风险定量评估。将模型应用于王茂沟流域两次溃决案例,并评估不同重现期降雨量的溃决致灾风险。结果表明:考虑泥沙对溃决致灾过程的影响,判定关地沟3坝、背塔沟坝和康和沟3坝溃决,判定结果与实际溃决情况吻合,忽略泥沙影响则背塔沟坝的溃决判定存在差异。与忽略泥沙对溃决致灾的作用相比,考虑泥沙作用2017-7-26降雨下关地沟3坝、背塔沟坝和康和沟3坝起溃时间分别提前11 min、13 min和7 min,有利于及时发出预警,快速撤离两岸群众,提升了淤地坝预警的准确度。不同重现期降雨量下,关地沟3坝10年一遇溃决流量为4.82 m^(3)/s,200年一遇溃决流量为5.97m^(3)/s。黄柏沟2坝和关地沟4坝在目前淤积情况下,可抵御200年一遇降雨。

基于精细化空间格局的城市承灾体脆弱性评估

针对目前流域内部跨行政区单元空间精细化模拟并用于评估城市洪涝灾害工作的空白,本文着重聚焦精细化经济指标空间分布并将多源数据融合,构建了基于精细化空间格局的城市承灾体脆弱性评估体系,量化了深圳河流域脆弱性等级。研究结果表明:单一数据不足以准确模拟流域GDP密度,结合多源数据是进行GDP空间精细化更加有效的办法;深圳河流域GDP密度与第二、三产业空间化结果显示出高度一致性,产值密度最高达617214万元/km^(2);流域两岸脆弱性等级存在显著差异和区域特征,深圳侧脆弱性明显高于香港侧,高脆弱性地区约占流域面积的8.8%。研究结果有助于识别灾害危险性大小和损失程度,提高城市洪涝灾害评估的精确性。

珠江河口区复合洪水事件多要素非一致性的时变遭遇分析

利用1988—2017年珠江河口三灶站潮位、澳门风速、上游流量日极值数据,基于广义可加模型(GAMLSS)的非一致性频率计算方法与时变Copula函数,对上游洪水、台风和天文潮的复合洪水事件重现期及其主控因子展开研究,结果表明:1)珠江河口区潮位、风速、流量均为非一致性序列,构建的时变Copula模型相比传统恒定参数的Copula更符合实际情况。2)1988—2017年珠江河口区典型复合洪水事件发生周期随时间不断缩短,发生概率增大,未来极端复合洪水事件发生概率增强。“黑格比”台风引发的复合洪水事件重现期从1988年的13.06 a一遇减小到2017年的10.80 a一遇,“韦森特”“天兔”引发的复合洪水事件在1988—2017年重现期缩短了1.06和0.97 a;3)当3种因子重现期为5 a一遇时,珠江河口区复合洪水事件主要受台风风速影响较大;重现期为10、20、50 a一遇时,复合洪水事件主要受天文潮潮位影响较大。

深度不确定性下的沿海城市洪涝风险稳健决策: 方法、原理与展望

全球气候变暖、海平面上升背景下,沿海城市极端洪涝事件的发生频率和强度将显著增大,洪涝灾害风险剧增,成为沿海城市安全与发展的严峻挑战。基于深度不确定性的稳健决策(Decision Making under Deep Uncertainty,DMDU)思路,旨在提供长期稳健的决策方案,成为全球沿海城市洪涝风险管理研究的新趋势。该文对比分析了稳健决策、适应路径和期权估值三类主要DMDU方法,基于不确定性、稳健性和适应性剖析了DMDU方法基本原理,提出了DMDU稳健决策的一般性框架。最后,从稳健性与决策目标、政策环境与决策参与以及方法的融合与创新三个方面对DMDU在洪涝风险领域的实践应用进行展望,以期为沿海城市适应气候变化稳健决策提供参考。

基于混合自组织映射神经网络的云南省山洪灾害危险性区划

开展云南省山洪灾害危险性区划工作,以自组织映射神经网络为基础,混合Ward、PAM、CLARA、K-means和HK-means的5种方法进行二阶聚类,应用戴维森堡丁指数(Davies-Bouldin index,DBI)、轮廓系数(silhouette coefficient,SC)、聚类模型评估指数(Calinski-Harabaz index,CH)确定最佳聚类方案,之后以变异系数和变异系数一阶拆分确定最佳区划数量.结果显示:①SOM(self organizing map)+CLARA(clustering LARge applications)方法通过聚类有效性检验效果最好,其DBI值为1.0、SC值为0.9、CH值为0.3334,基于该方法得到云南省山洪灾害危险性最佳聚类数为5类,呈现类别空间分离,灾害属性相似的特征;②通过变异系数(coefficient of variation,CV)值变化及变异系数一阶差分(first-order difference,FOD)最低取值确定云南省山洪灾害危险性最佳区划单元为16个,具有形状上与地貌单元相近、数量上与行政单元相同,内部灾害发生机理相似的特征;③通过山洪灾害点、降水量、高程地貌的可视化比较,地理探测器定量分析,表明区划结果有较高的区内一致性和区间异质性.