Color map design for visualization in flood risk assessment

Visualizations of flood maps from simulation models are widely used for assessing the likelihood of flood hazards in spatial planning. The choice of a suitable type of visualization as well as efficient color maps is critical to avoid errors or bias when interpreting the data. Based on a review of previous flood uncertainty visualization techniques, this paper identifies areas of improvements and suggests criteria for the design of a task-specific color scale in flood map visualization. We contribute a novel color map design for visualizing probabilities and uncertainties from flood simulation ensembles. A user study encompassing 83 participants was carried out to evaluate the effects of this new color map on user’s decisions in a spatial planning task. We found that the type of visualization makes a difference when it comes to identification of non-hazardous sites in the flood risk map and when accepting risks in more uncertain areas. In comparison with two other existing visualization techniques, we observed that the new design was superior both in terms of task compliance and efficiency. In regions with uncertain flood statuses, users were biased toward accepting less risky locations with our new color map design.     

基于“H-E-V”框架的城市洪涝风险评估研究进展

在全球气候变化与城市扩张的背景下,城市洪涝问题频发并引发严重的社会问题与经济损失。当前城市洪涝管理的主要内容已从工程性防御性措施转向洪涝风险管理,而城市洪涝风险评估又是城市洪涝管理的关键环节。基于此背景,论文首先介绍了IPCC采纳的城市洪涝风险评估框架“危险性(Hazard)—暴露性(Exposure)—脆弱性(Vulnerability)”即“H-E-V”的概念内涵,在此基础上梳理了其危险性、暴露性、脆弱性3大要素的主要研究内容,探讨分析不同研究方法的优缺点。最后提出了城市洪涝风险评估的主要发展趋势及关键问题,主要有以下4个方面：①危险性方面,建立适应于城市地区的耦合型二维洪涝淹没模型是洪涝风险评估要求下的必然趋势;②暴露性分析在大数据及GIS技术支撑下正逐步精细化、动态化;③脆弱性正从早期侧重的物理维度定量评估转向社会、经济、文化、环境等多维度的评估;④此外,气候变化与城市扩张下的多情景城市洪涝风险评估是未来城市洪涝管理的研究热点与难题。     

基于多智能体的洪涝风险动态评估理论模型

随着全球气候变化的加剧和城市化进程的快速发展,洪涝灾害的影响和复杂性日益加剧。洪涝灾害风险评估是一项复杂的系统工程,在防洪减灾工程理论与实践中具有重要意义;作为洪涝灾害风险管理和应急处置的基础和核心,风险评估模型直接影响洪涝灾害风险评估结果的可靠性。洪涝灾害风险是洪涝灾害复杂系统组成部分相互作用的结果,综合考虑洪涝灾害系统的特点以及智能体建模的优势,提出了一种基于多智能体的洪涝风险动态评估理论模型。首先从复杂系统建模的角度出发,对洪涝灾害复杂系统进行分析建模,构建基于多智能体的洪涝灾害风险动态评估框架模型;其次,对所构建的框架模型中单个智能体模型进行研究,分别建立基于反应型的孕灾环境智能体模型和基于慎思型的致灾因子、承灾体和风险分析智能体模型,并对以上单个智能体的流程进行研究;然后以风险分析智能体联盟为例对模型框架中所涉及到4类智能体联盟的内部结构和流程进行分析,对构建的框架模型中涉及到的智能体通信协调和作用规则进行探讨;最后,在Netlogo平台上,基于30 m DEM数据和构建的模型,对淮河流域的暴雨型洪涝孕育发生发展全过程的人口风险进行动态评估。结果表明,构建的模型能有效评估洪涝灾害全过程中人口风险的动态。研究结果对洪涝灾害人口灾情评估、应急救助和应急管理都具有较强的指导意义。     

Spatiotemporal analysis of climate variability impacts on malaria prevalence in Ghana

There are conflicting results from research on the impacts of temperature and rainfall on malaria prevalence. As a result predicting malaria prevalence still remains a challenge. Generating relevant information on the role of temperature, rainfall, and humidity on malaria prevalence at different geographic scales is critical to efforts to combat the burden of prevalence. For better understanding of climate variability and the impacts on malaria prevalence, this study examined the varying spatial and seasonal distribution in malaria prevalence over time in Ghana. We used trajectory and time series analyses for temporal distribution and conducted GIS-based analyses of the spatial distribution of yearly malaria incidence and climate variables. We observed that the national annual malaria incidence has increased. Considerable inter-annual variations were also detected in the intensity of incidence across regions characterized with varying rainfall and temperature regimes. The results indicated that temperature and humidity have some association with malaria prevalence in Ghana. Although annual rainfall in the model was found to be less significant, there is evidence of rainfall as a predictor of malaria in Ghana. These findings show that public health resource allocations should focus on the areas with the highest malaria risk in Ghana.     

Climate variability and rural livelihoods: assessing the impact of seasonal climate forecasts in Lesotho

Climate variability acutely affects rural livelihoods and agricultural productivity, yet it is just one of many stresses that vulnerable rural households have to cope with. A livelihood approach is used to assess the potential role that seasonal climate forecasts might play in increasing adaptive capacity in response to climate variability, using Lesotho as a case study. An examination of the assets and strategies that rural households employ enables a holistic assessment of the impact seasonal forecasts could have on rural livelihoods. This research thereby bridges macro-level variability with local-level impacts and adaptation to provide insight into the dynamics of forecast use and impact among vulnerable groups.     

黄河中游马莲河历史与现代洪痕沉积与水文学研究

通过对马莲河流域深入调查研究,在马莲河下游峡谷峭壁发现了一组4个显著的洪痕。洪痕沉积物分析看出,马莲河洪水悬移质泥沙以粉沙为主,粘粒和沙粒含量都较低,磁化率值也很低。将这些数据与流域内马家原剖面黄土土壤的的分析结果对比,可知马莲河现代洪痕沉积物是暴雨洪水对于流域内黄土和土壤侵蚀、搬运沉积形成。采用面积－比降法对该组洪痕所记录的4次洪水事件进行了洪峰流量恢复计算。表明高于常水位3.3 m、5.5 m、6.7 m洪痕洪峰流量分别为1 170m³/s、4 060 m³/s、5 690 m³/s。它们与雨落坪水文站观测2005、2003、1977年的洪水洪峰流量值相当,误差小于5 %。最高洪痕高出常水位10～12 m,计算恢复其洪峰流量为13 980 m³/s,洪水发生年代为1841年（清代道光21年）。这些研究结果对于马莲河流域的防洪减灾、水利水电工程设计和水土流失防治具有重要科学意义。     

考虑水文趋势影响的珠江流域非一致性洪水风险分析

本文基于两参数对数正态分布和指数趋势模型建立了非一致性洪水频率计算模型,分析了珠江流域28个测站年最大日流量序列趋势性对洪水频率分析的影响。结果表明：（1）从空间分布来看,珠江流域中北部年最大日流量序列呈增加趋势,东部和南部年最大日流量序列呈减小趋势;从时间变化来看,1981-2010年年最大日流量呈显著性增加趋势的站点数较多,占总站点数的20-25%,1966-1990年年最大日流量呈显著性减小趋势的站点数较多,占总站数的25-30%;（2）珠江流域洪水放大因子(未来T年一遇设计流量与现在T年一遇设计流量比值)和重现期都受到趋势性的显著影响。西江中北部和北江洪水放大因子大于1,意味着原有的防洪工程设计标准可能无法满足未来防洪需求,存在防洪隐患;洪水放大因子较大和较小的地区集中在西江干流和东江干流;（3）非一致性条件下,同一场洪水过去、现在和未来重现期是不同的。非平稳性条件下,珠江流域近20年来20-50年一遇洪水发生站次相比平稳性条件下在减小。     

Accounting for variability in commercial flood damage estimation

Flooding in the business district of Kempsey, New South Wales, Australia, in 2001 allowed the collection and analysis of commercial flood damage data. Analysis indicated that direct losses were significant, totalling A$2.5 million. Data were variable owing to differences in the vulnerability of businesses to flood damage, differences in the impacts of the hazard upon businesses and survey uncertainty. Little direct relationship was found between direct commercial damage and over-floor water depth. Simple averaging and stage-damage curve loss estimation methods ignore the large variability present and result in inaccurate estimation of direct commercial damage. Probability loss estimation methods account for the variability present by assessing the chance of loss values occurring at specified depths of over-floor flooding.     

前期土壤湿度和降雨对小流域山洪预警指标的影响评估

山洪灾害临界雨量预警指标受多种因素影响,尤其是前期土壤湿度状况和降雨变化。基于分布式水文模型和情景分析法确定安徽省岳西流域的山洪灾害临界雨量集合,评估前期土壤湿度状况、雨型和预警时段对临界雨量变化的影响。研究表明：① 中国山洪水文模拟系统在研究区内具有较好的适用性,率定期和验证期的平均径流深和洪峰流量相对误差均在15%以内,平均峰现时间误差在1h以内,平均Nash-Sutcliffe系数为0.79和0.77;② 60种情景模式下,池墩组村的临界雨量集合为141~528 mm;③ 前期土湿状况和雨型均显著影响临界雨量变化,随着土壤饱和率从0.20分别增加到0.50和0.80,临界雨量分别减少13.7%~16.2%和26.8%~31.8%;短历时预警时,临界雨量由大到小的相应雨型分别为减弱雨型、中间雨型和增强雨型。研究可为山洪灾害预报和早期预警提供理论支持,也为中国山洪灾害防治提供参考和借鉴。     

Configurations of community in flood risk management

ABSTRACT

Despite a notable increase in the literature on community resilience, the notion of ‘community’ remains underproblematised. This is evident within flood risk management (FRM) literature, in which the understanding and roles of communities may be acknowledged but seldom discussed in any detail. The purpose of the article is to demonstrate how community networks are configured by different actors, whose roles and responsibilities span spatial scales within the context of FRM. Accordingly, the authors analyse findings from semi-structured interviews, policy documents, and household surveys from two flood prone areas in Finnish Lapland. The analysis reveals that the ways in which authorities, civil society, and informal actors take on multiple roles are intertwined and form different types of networks. By implication, the configuration of community is fuzzy, elusive and situated, and not confined to a fixed spatiality. The authors discuss the implications of the complex nature of community for FRM specifically, and for community resilience more broadly. They conclude that an analysis of different actors across scales contributes to an understanding of the configuration of community, including community resilience, and how the meaning of community takes shape according to the differing aims of FRM in combination with differing geographical settings.     

A landslide susceptibility model using the Analytical Hierarchy Process method and multivariate statistics in perialpine Slovenia

Landslides cause damage to property and unfortunately pose a threat even to human lives. Good landslide susceptibility, hazard, and risk models could help mitigate or even avoid the unwanted consequences resulted from such hillslope mass movements. For the purpose of landslide susceptibility assessment the study area in the central Slovenia was divided to 78 365 slope units, for which 24 statistical variables were calculated. For the land-use and vegetation data, multi-spectral high-resolution images were merged using Principal Component Analysis method and classified with an unsupervised classification. Using multivariate statistical analysis (factor analysis), the interactions between factors and landslide distribution were tested, and the importance of individual factors for landslide occurrence was defined. The results show that the slope, the lithology, the terrain roughness, and the cover type play important roles in landslide susceptibility. The importance of other spatial factors varies depending on the landslide type. Based on the statistical results several landslide susceptibility models were developed using the Analytical Hierarchy Process method. These models gave very different results, with a prediction error ranging from 4.3% to 73%. As a final result of the research, the weights of important spatial factors from the best models were derived with the AHP method. Using probability measures, potentially hazardous areas were located in relation to population and road distribution, and hazard classes were assessed.     

鄱阳湖区洪灾风险与农户脆弱性分析

This paper quantitatively explores farmers' vulnerability to flood in the Poyang Lake Region (PLR) with the supports of GIS spatial functions. The analysis consists of three major steps,which is based on the spatial unit of township. Firstly,the spatial extent and charac-teristics of flood risk areas were determined using a digital elevation model (DEM) derived from the 1:50,000 topographic map. Secondly,for each of the township,six indices indicating the economic activities of local farmers were calculated. These indices are: rural population proportion,cultivated land proportion,GDP per unit area,employment proportion of primary industry,net rural income per capita and agricultural income proportion. These six indices were then normalized and used for later vulnerability assessment. Thirdly,the normalized indices (as GIS data layers) were overlaid with the flood risk areas to produce the risk coeffi-cient for each township and to calculate the overall vulnerability for each township. The analysis results show that in the PLR there are high flood risk areas where the farmers' livings are seriously influenced or threatened. About 55.56% of the total 180 townships in the flood risk areas have a high degree of flood vulnerability. The townships under flood risk are mainly distributed in the areas around the Poyang Lake and the areas along the "five rivers".     

开封市黄河滩区土地资源规避洪水风险的安全利用

基于ArcGIS与ERDAS遥感影像制图软件,利用2007年SPOT2.5m分辨率遥感影像,结合实地调查,详细编绘了开封市段黄河河道边界、开封段黄河滩区土地资源的利用现状。采用1992~2007年最大洪峰时期的TM影像与沿河水文站点的观测资料,提取1992~2007年7个典型日期的河道行洪边缘线,与本底数据叠加,编制了开封段不同常遇洪水流量下滩区淹没范围。按照黄河下游二维水沙数学模型,采用2004年汛后河道大断面资料,计算生成不同流量级大洪水在滩区的可能淹没范围图(淹没区边界)。在此基础上,结合土地资源管理与河道行洪安全性的要求,总结当前黄河下游滩区利用开发的现状与存在问题,制订土地安全利用规避洪险的原则,规划土地安全利用分区,分为临河风险缓冲带、近河宜耕地带、相对稳定利用带(中风险带)和稳定利用带。提出了黄河滩区土地资源合理安全利用的对策。     

北京地区汛期降雨时空演变特征及城市化影响研究

近年来伴随着城市化的快速发展,世界各大城市汛期极端降雨事件频发,洪涝造成的社会经济损失日益严重,在此背景下,分析中国首都北京各城市化阶段汛期降雨变化显得非常有必要。论文基于30个雨量站1963—2012年汛期降雨资料,运用线性回归、滑动平均以及ArcGIS空间分析等方法对北京汛期降雨时空特征进行分析,通过对比城区和近郊区汛期降雨之间的差异来研究城市化对汛期降雨特征的影响,同时利用北京不同城市化阶段土地利用数据分析了城市下垫面变化对降雨的影响,得出以下主要结论：① 北京各区域汛期降雨时间上整体呈现下降趋势,空间上整体表现为由东向西呈逐渐减小的趋势。② 北京山区最容易发生小雨和中雨;城区则更容易发生中雨以上等级降雨事件,特别是暴雨和大暴雨;近郊区发生小雨和中雨概率与城区接近,但大雨以上等级降雨事件发生可能性小于城区;远郊发生各等级降雨事件的可能性均较大。③ 相对于北部近郊而言,在不同城市化发展阶段,城区降雨比南部近郊更大,但城市化增雨效应在城区与北部近郊之间也有所体现。④ 随着城市化的发展,北京城区和郊区城镇建设用地面积持续增长,原有下垫面条件被改变;由于城区城市化进程比近郊区更快,下垫面条件的改变使得城区汛期降雨量大于近郊区,且更易发生大雨以上等级降雨事件。     

基于FloodArea模型的暴雨洪涝灾害风险预评估技术及效果检验北大核心CSCD

利用陕西气象站点逐小时降水实况、精细化格点预报、数字高程、土地利用、灾情等资料,应用水动力模型FloodArea对暴雨洪涝进行淹没模拟,在淹没水深和范围的基础上叠置承灾体属性,引入承灾体的灾损曲线,建立暴雨洪涝灾害风险预评估模型,并从数量占比和灾情占比两个角度,以县为单元进行验证,利用格点降水量预报对陕西6次大范围暴雨过程灾害风险进行预评估以及效果检验。结果表明:暴雨洪涝气象风险预估结果与实际受灾地区分布基本吻合,正确预报率73.2%,模拟结果可信度高,对于降水区域集中暴雨的风险预评估性能较分散性暴雨较高,漏报率相对低,但是空报率较高;建立的暴雨洪涝灾害风险预评估及效果检验流程,提高了气象服务的针对性,可以用于洪涝风险预评估的实际业务中,对暴雨洪涝风险管理提供技术支撑。     

平原河网地区河流结构特征及其对调蓄能力的影响

平原河网地区是河流高度发育并受到城市化深刻影响的区域。本文以上海为例,基于上海及周边城市普遍采用的河流分类和水利片管理系统,分析不同城市化水平地区河流结构的共同特征及其差异性,探讨河流结构对河网调蓄能力的可能影响,提出估算河网调蓄能力的方法。研究表明,平原河网地区河流结构指标反映了该地区河流数量、长度以及低等级河流高度发育的自然地理特征,城市化在达到一定程度后即会干扰河流结构的自身发育规律,并表现为河流发育能力的下降;河流结构在城市化影响下表现出由复杂到简单、由多元到单一的变化趋势;河网调蓄能力受低等级河流数量及结构的影响更大,并随着城市化水平的提高而下降;就整体而言,城市化对河网调蓄能力的影响大于对河流结构的影响;以水面数量和河流结构两项指标作为参数能够更准确地估算河网调蓄能力。     

县域尺度下的陕西省洪涝灾害风险评估及区划

洪涝灾害风险评估和区划研究对区域洪灾综合管理具有重要意义。以陕西省洪涝灾害气候背景和社会经济环境为基础,利用辖区内34个气象测站1954-2015年、月降水数据和2015年社会经济统计资料,运用自然灾害风险评估理论及方法,从致灾因子危险性、孕灾环境脆弱性、承灾体暴露性和防灾减灾能力4个子系统选取17个评价指标,建立洪涝灾害风险评价指标体系,借助GIS技术进行洪涝灾害风险评估和区划。结果表明：（1）陕西省洪涝灾害致灾因子危险性等级自北向南呈递增趋势,高和次高危险区分布在陕南地区和关中盆地西部。（2）孕灾环境脆弱性空间分布差异较大,高和次高脆弱区分布在榆林北部长城沿线各县、延安市区、关中盆地渭河沿岸主要区县、陕南汉中盆地和安康市区。（3）承灾体暴露性各区县分布不均,大部分市区和农业发达地区暴露程度较高。（4）城市和经济发达地区防灾减灾能力较高,其他地区相对较低。（5）陕西省洪涝灾害综合风险等级表征为陕南汉江谷地、丹江流域和关中盆地渭河沿岸区县偏高,其他区县相对偏低。总体来看,中等以上风险区县占陕西省所辖区县的61.54%,其中陕南汉江谷地、丹江流域、关中盆地西部和渭南市应为陕西省洪涝灾害防范的重点区域。     

不同重现期下淮河流域暴雨洪涝灾害风险评价

为探讨不同重现期情景下淮河流域暴雨洪涝灾害风险变化,利用不同类型共20 种分布函数拟合得到最大日降水量结果,并将其作为致灾因子,结合其他11 种指标,定量化评价淮河流域不同重现期暴雨洪涝灾害风险。研究发现：① 淮河流域暴雨洪涝灾害高风险区为流域中上游干流蓄洪区及周边地势低洼地,流域中部、西南部以及东部部分地区为中高风险区,低风险区分布于流域北部与中南部。② 随重现期增加（10a 一遇至1000a 一遇）,最大日降水量空间分布变化为流域东部整体危险性逐渐减弱,西南部高值区域增幅较大;而最终淮河流域暴雨洪涝灾害风险区划变化则表现为中高风险区保持相对稳定;高风险区与低风险区逐渐缩小,占流域总面积分别由8.3%、42.4%减小至3.2%与30.8%,风险高值保持稳定但区域集中程度越来越明显;中风险区则由28.3%增加至40.9%;整体呈现“流域东部大灾减少、小灾不断,西部高值区遇水成灾,北部中南部相对安全”的空间分布变化格局。     

Climate variability and maize production in Cameroon: Simulating the effects of extreme dry and wet years

The effects of interyear variability of extreme rainfall events on maize yields at locations in Cameroon, in central‐west sub‐Saharan Africa were investigated through a simulation assessment combining a weather generator with a crop growth model. This study analyzes the potential of using dry/wet year predictions to reduce risk in subsistence agricultural production associated with climate variability at the site level. Weather data sets from eight provincial study localities were classified into three precipitation scenarios – dry (lower threshold), normal and wet (upper threshold) years. According to the modelling results, there is a less than 12 per cent variance in mean maize yields across six out of the eight localities when planting occurs in March, May and August. The variance is equivalent to approximately 100–300 kg per ha, which represents a significant amount of food in the household security of the majority impoverished sectors of rural and urban society, and which could greatly impact the socioeconomic activities of the entire populace. The results lead to the conclusion that all extreme dry and wet years are not equal in terms of their regional manifestation. This calls for precise monthly and sub‐seasonal local level forecasts and the effective dissemination of this information to farming communities in Cameroon, thereby facilitating the adaptive management of indigenous cropping practices and reducing their vulnerability to climate related disasters.