Risk assessment of maize drought disaster in southwest China using the Environmental Policy Integrated Climate model

The East Asian monsoon has a tremendous impact on agricultural production in China. An assessment of the risk of drought disaster in maize-producing regions is therefore important in ensuring a reduction in such disasters and an increase in food security. A risk assessment model, EPIC（Environmental Policy Integrated Climate） model, for maize drought disasters based on the Erosion Productivity Impact Calculator crop model is proposed for areas with the topographic characteristics of the mountainous karst region in southwest China. This region has one of the highest levels of environmental degradation in China. The results showed that the hazard risk level for the maize zone of southwest China is generally high. Most hazard index values were between 0.4 and 0.5,accounting for 47.32% of total study area. However,the risk level for drought loss was low. Most of the loss rate was ＆lt;0.1, accounting for 96.24% of the total study area. The three high-risk areas were mainlydistributed in the parallel ridge–valley areas in the east of Sichuan Province, the West Mountain area of Guizhou Province, and the south of Yunnan Province.These results provide a scientific basis and support for the reduction of agricultural drought disasters and an increase in food security in the southwest China maize zone.

Influence Factors and Assessment of Risk Perception for Agricultural Drought Based on Household-scale

This paper describes the basic connotation of risk perception, the influence factors of the risk perception for agricultural drought and the mainstream assess- ment model. Additionally, it summarizes the latest developments of research meth- ods for risk perception for the agricultural drought, and the research status of the risk perception for agricultural drought, and put forward the trends of risk perception for the agricultural drought. Finally, it proposes the research areas of the risk per- ception for agricultural drought should be improved in future.

Development and Application of Oil-Spill Risk Assessment Model for Offshore Pipeline

To the potential oil-spill risk caused by offshore pipeline more attention has been paid after the Dalian oil spill incident from oil-pipeline explosion. Since then an issue about how to prevent and control the sudden oil-spill from the offshore pipeline has been raised. In this paper, we proposed an optimized model to analyze the main causes(probability) of spill and the consequence with the fuzzy comprehensive assessment model. Considering the complicated assessment process for oil-spill, the assessment factor system involving the spill probability and consequence was established based on the operative manual and statistic leakage/damage data of offshore pipeline in order to estimate the integrated spill risk score automatically. The evaluated factors of spill probability could be grouped into five aspects: corrosion, fatigue, national damage, third party, and operational fault; the consequence evaluated factors of spill included hazard of oil and impact-controlling capability. With some modifications based on experts' opinions, each of the evaluated factors in our work was developed with a relative weight and evaluation criterion. A test example for an offshore pipeline in the Bohai waters was described to show how the model can be used for an actual case in more detail. By using the oil-spill risk assessment model, it is easy to determine the risk level associated with the ongoing activity and management level and hence to take the risk mitigation action immediately.

Risk Assessment of Coal Mine Water Hazard Based on Three-Dimensional Model of Geology and Underground Space

Mine safety have top-five disasters,which including the water,gas,fire,dust and geological dynamic disaster.The coal mine water disaster is one of the important factors which restricted the development of China’s coal production.It is showed by statistics that 60%of mine accidents are affected by groundwater,which not only result in the production losses,casualties and a variety of

Landslide susceptibility assessment in Western Henan Province based on a comparison of conventional and ensemble machine learning

Landslide is a serious natural disaster next only to earthquake and flood,which will cause a great threat to people’s lives and property safety.The traditional research of landslide disaster based on experience-driven or statistical model and its assessment results are subjective,difficult to quantify,and no pertinence.As a new research method for landslide susceptibility assessment,machine learning can greatly improve the landslide susceptibility model’s accuracy by constructing statistical models.Taking Western Henan for example,the study selected 16 landslide influencing factors such as topography,geological environment,hydrological conditions,and human activities,and 11 landslide factors with the most significant influence on the landslide were selected by the recursive feature elimination(RFE)method.Five machine learning methods[Support Vector Machines(SVM),Logistic Regression(LR),Random Forest(RF),Extreme Gradient Boosting(XGBoost),and Linear Discriminant Analysis(LDA)]were used to construct the spatial distribution model of landslide susceptibility.The models were evaluated by the receiver operating characteristic curve and statistical index.After analysis and comparison,the XGBoost model(AUC 0.8759)performed the best and was suitable for dealing with regression problems.The model had a high adaptability to landslide data.According to the landslide susceptibility map of the five models,the overall distribution can be observed.The extremely high and high susceptibility areas are distributed in the Funiu Mountain range in the southwest,the Xiaoshan Mountain range in the west,and the Yellow River Basin in the north.These areas have large terrain fluctuations,complicated geological structural environments and frequent human engineering activities.The extremely high and highly prone areas were 12043.3 km^(2)and 3087.45 km^(2),accounting for 47.61%and 12.20%of the total area of the study area,respectively.Our study reflects the distribution of landslide susceptibility in western Henan Province,which provides a scientific basis for regional disaster warning,prediction,and resource protection.The study has important practical significance for subsequent landslide disaster management.

Maize drought disaster risk assessment of China based on EPIC model

Digital Agriculture is one of the important applications of Digital Earth.As the global climate changes and food security becomes an increasingly important issue,agriculture drought comes to the focus of attention.China is a typical monsoon climate country as well as an agricultural country with the world’s largest population.The East Asian monsoon has had a tremendous impact upon agricultural production.Therefore,a maize drought disaster risk assessment,in line with the requirements of sustainable development of agriculture,is important for ensuring drought disaster reduction and food security.Meteorology,soil,land use,and agro-meteorological observation information of the research area were collected,and based on the concept framework of‘hazard-inducing factors assessment(hazard)-vulnerability assessment of hazard-affected body(vulner-ability curve)-risk assessment(risk),’importing crop model EPIC(Erosion-Productivity Impact Calculator),using crop model simulation and digital mapping techniques,quantitative assessment of spatio-temporal distribution of maize drought in China was done.The results showed that:in terms of 2,5,10,and 20 year return periods,the overall maize drought risk decreased gradually from northwest to southeast in the maize planting areas.With the 20 year return period,high risk value regions(drought loss rate]0.5)concentrate in the irrigated maize region of Northwest china,ecotone between agriculture and animal husbandry in Northern China,Hetao Irrigation Area,and north-central area of North China Plain,accounting for 6.41%of the total maize area.These results can provide a scientific basis for the government’s decision-making in risk management and drought disaster prevention in China.

基于空间信息格网的南京市洪水风险评估

分别采用MIKE模型和ArcGIS平台搭建洪水风险自然属性和社会属性空间信息格网并进行格网叠加,构建洪水风险评价指标体系,利用层次分析法和熵权法确定主客观权重,进而计算得出洪水风险综合指数并对南京市秦淮区3个相邻街道进行洪水风险评估。结果表明:不同降雨强度下,洪水风险综合指数西北部较高、东南部较低、易受损敏感区相对较高;随着降雨强度增大,洪水风险综合指数较高的区域范围不断扩大;研究区主要积淹点均处于洪水风险综合指数较高区域;基于空间信息格网的洪水风险评估可为精细化、动态化的洪水灾害风险评估与洪水管理提供参考。

Community-based scenario modelling and disaster risk assessment of urban rainstorm waterlogging

Scenario modelling and the risk assessment of natural disasters is one of the hotspots in disaster research. However, up until now, urban natural disaster risk assessments lack common procedures and programmes. This paper selects rainstorm waterlogging as a disaster to research, which is one of the most frequently occurring hazards for most cities in China. As an example, we used a small-scale integrated methodology to assess risks relating to rainstorm waterlogging hazards in the Jing＇an District of Shanghai. Based on the basic concept of disaster risk, this paper applies scenario modelling to express the risk of small-scale urban rainstorm waterlogging disasters in different return periods. Through this analysis of vulnerability and exposure, we simulate different disaster scenarios and propose a comprehensive analysis method and procedure for small-scale urban storm waterlogging disaster risk assessments. A grid-based Geographical Information System （GIS） approach, including an urban terrain model, an urban rainfall model and an urban drainage model, was applied to simulate inundation area and depth. Stage-damage curves for residential buildings and contents were then generated by the loss data of waterlogging from field surveys, which were further applied to analyse vulnerability, exposure and loss assessment. Finally, the exceedance probability curve for disaster damage was constructed using the damage of each simulated event and the respective exceedance probabilities. A framework was also developed for coupling the waterlogging risk with the risk planning and management through the exceedance probability curve and annual average waterlogging loss. This is a new exploration for small-scale urban natural disaster scenario simulation and risk assessment.

自然灾害人口综合风险评估——以宁波市奉化区为例

为评估自然灾害人口综合风险,加强多灾种风险防范,以人类生命体为承灾体,建立了基于危险性、暴露度、脆弱性和防灾减灾能力的风险评估指标体系,利用改进的CRITIC法确定指标权重。考虑不同灾害间的相关关系,引入风险系数并建立多灾种综合危险性的分析模型。以宁波市奉化区为例,选取了该地区常见的6种自然灾害,评估多灾种人口综合风险。研究结果表明:单灾种的危险性评估结果符合实际,奉化地区主要受台风洪涝灾害影响,岳林街道、锦屏街道、松岙镇和溪口镇的多灾种人口综合风险指数较高。

洪涝风险与发展潜力视角下村庄居民点布局优化——以福建省长汀县为例

全球气候变化加剧和城镇化快速推进使得洪涝灾害发生频率和破坏性显著升高,为应对洪涝灾害利用风险评估指导村庄居民点布局优化,以福建省长汀县为例,运用模糊综合评价方法划定洪涝风险等级区,通过双重目标决策法对村庄灾害风险和发展潜力进行综合评价,并基于引力模型确定村庄迁移方案。结果表明,长汀县洪涝灾害高风险区域主要分布在以汀州镇与大同镇为主体的集中建设区及以部分村庄居民点,针对高风险村庄居民点,以“避灾”为导向提出了村庄迁移合并方案,实现了村庄居民点布局的适灾和减灾优化调整。对于区域防控洪涝灾害、减少灾害损失具有重要作用,对山地村庄空间防灾减灾规划实施有较强指导意义。

基于GIS技术的山地小城镇雨洪灾害风险评估

在快速城镇化和工业化背景下,城市的自然灾害风险日益暴露,尤其是雨洪灾害问题日益突出。针对巩义市近年来不断发生的洪涝灾害,基于自然灾害风险评估理论,构建以致灾因子危险性、孕灾环境孕险性、承灾体易损性、防灾减灾能力为评价因子的雨洪灾害风险模型,共选取14个指标进行定量分析,运用SCS模型和GIS空间分析功能,最终得出巩义市雨洪灾害综合风险区划图。结果表明:巩义市米河镇、回郭镇、芝田镇、孝义街道等地区致灾因子危险性较大;北部、西部和东部包括河洛镇、孝义街道、回郭镇、芝田镇、米河镇等孕灾环境孕险性较高;西部和中部承灾体易损性较大,包括回郭镇、芝田镇、站街镇等;北部整体防灾减灾能力较强,包括站街镇、紫荆路街道等地区。综合来说,巩义市雨洪灾害总体风险等级较高,高风险区主要分布在中部偏北和西部,呈带状分布。

暴雨灾害下的建筑施工现场风险评价研究

为了准确判断施工现场在突降暴雨情况下的安全状态,采用贝叶斯最优最劣法(Bayesian Best Worst Method,BBWM)和云模型方法,提出暴雨灾害下的建筑施工现场风险评价模型,以确定施工现场在遭受暴雨灾害时的风险等级。该模型利用了压力状态响应模型(Pressure State Response,PSR)和灾害系统理论,在考虑致灾因子危险性、孕灾环境稳定性、承灾体脆弱性和减灾能力抵御性4方面的基础上,构建18个风险因素的施工现场风险评价指标体系,并以武汉市某施工现场为例进行验证。结果显示,施工现场的减灾能力抵御性处于最重要的地位,做好现场减灾应对措施对灾害有非常重要的帮助;案例项目的评价结果处于一般风险状态,与现场实际情况相符。

基于四维度模型的湖南省湘江流域洪涝灾害风险评估

当前极端气候事件频发,降水频次与强度剧增,致使区域洪涝风险提高。为了降低区域洪涝风险,从致灾因子危险性、孕灾环境敏感性、承灾体脆弱性和防灾减灾能力四维度分析洪涝灾害风险的形成机理,基于11项指标,综合运用ArcGIS地理信息软件与熵权法等数理统计方法客观赋权,对湖南省湘江流域的洪涝风险进行综合性评估,最终制作出区县尺度的洪涝风险分布图。结果表明:湘江流域中西部致灾因子危险性低,中游地区孕灾环境敏感性高;环长株潭地区与衡阳市的承灾体脆弱性较高,但前者凭借良好的经济基础,其防灾减灾能力相对较强;湘江流域洪涝风险分布从东北向西南呈增强趋势,高洪涝风险区位于长沙市、益阳市、衡阳市及永州市南部,不同地区洪涝风险的主导因子不同。研究结果较好地反映了多因子作用下地区洪涝风险的差异,可为区域防洪减灾提供支撑。

基于VWM-GRA的新型Fuzzy-FMEA复杂装备风险评估方法

失效模式和影响分析(Failure Mode and Effect Analysis,FMEA)是一种识别和预防复杂装备潜在故障模式的风险评估方法,然而,现有FMEA方法采用等权重和精确数表征不确定情形下的风险因素评估信息,导致风险优先数(Risk Priority Number,RPN)难以准确评估复杂装备故障模式的风险优先级。针对这一难题,文中提出了一种基于变权方法-灰色关联分析(Variable Weight Method-Grey Relation Analysis,VWM-GRA)的新型Fuzzy-FMEA复杂装备风险评估方法。在风险因素权重分配方面,在模糊熵值法的基础上,考虑风险评估信息对风险因素权重的影响,构建风险因素变权综合模型以动态调整风险因素权重值,据此确定风险因素的客观变权重;在风险优先数排序方面,在模糊语言变量表征风险因素评估信息的基础上,考虑风险因素评估信息不确定性量化对故障模式排序精度的影响,构建故障模式模糊灰色关联分析模型,以获取评估信息数据序列间的相对关联度,据此评估故障模式的风险优先级。最后,通过航空发动机主轴轴承的故障模式风险实例,分析验证文中方法的有效性。案例分析表明:该方法能够有效解决不确定情形下准确评估复杂装备故障模式风险优先级的难题。

不同降雨工况条件下的崩滑地质灾害危险性评价

为针对性地采取预防、避让、治理等地质灾害防治与管控提供依据,完善在地质灾害危险性评价中将降雨作为单一诱发因子参与评价体系的弊端,在大雨、暴雨、大暴雨和特大暴雨4种不同降雨工况条件下进行了研究区崩滑地质灾害危险性评价。以云南省元阳县作为研究区域,以栅格单元作为评价单元,选取地貌类型、高程、坡度、坡向、曲率、工程地质岩组、土地利用类型、断层距离和河流距离9个评价因子,采用主观的层次分析法与客观的信息量模型相结合的加权信息量模型对元阳县崩塌、滑坡进行了地质灾害易发性评价。研究结果表明:基于自然间断点法元阳县域可分为低、中、高、极高4类易发区,4类易发区面积分别占元阳县面积的21.55%,35.46%,25.53%和17.16%。利用ROC曲线得出区划结果精度AUC值为0.812,表明区划结果很好。在易发性评价基础上,以年平均最大日降雨量为诱发因素,分别对大雨、暴雨、大暴雨和特大暴雨4种工况条件下的研究区进行了崩塌、滑坡地质灾害危险性评价,得到了大雨([25,50) mm)工况、暴雨([50,100) mm)工况、大暴雨([100,250]mm)工况和特大暴雨(>250 mm)工况4种条件下基于极值假设的研究区崩滑地质灾害危险性评价结果,并对不同降雨工况条件下的地质灾害危险性评价结果进行了对比分析,确定了地质灾害危险性评价结果在不同降雨条件下的空间合理性。通过与实际调查结果的对比表明,4种不同降雨工况条件下的崩滑地质灾害危险性评价结果与实际高度吻合,说明评价结果具有较高的可靠性与合理性。

基于SPAC系统的阿克苏地区农业干旱灾害风险评估与区划

为明确阿克苏地区干旱灾害风险及其区划,利用层次分析法和加权综合评价法,基于SPAC(soil-plant-atmosphere continuum)系统,从致灾因子危险性、孕灾环境脆弱性、承载体暴露性三个方面构建农业干旱灾害风险评价指标体系。整合多源数据信息,将阿克苏地区划分为5个干旱灾害风险等级。结果表明:阿克苏地区农业干旱灾害风险高,中等风险及以上的区域占阿克苏地区总面积的78.1%,且呈“南高北低”的特征。高风险区主要分布在阿瓦提县、沙雅县和温宿县的南部;中高风险区主要分布在新和县西部、拜城县东部、库车市中部、柯坪县南部和阿克苏市南部;中风险区主要分布在库车市西南部和阿瓦提县北部。阿克苏地区绿洲农业干旱灾害风险不高,中低风险区和中风险区占绿洲总面积的68.6%,绿洲地区干旱灾害风险低于阿克苏其他区域,但温宿县绿洲区域干旱灾害风险高。

变暖环境下华北地区农业气象灾害风险评估Ⅰ:基于综合指标体系法农业干旱风险评估及适应对策建议

随着全球气候变化,干旱发生频率及强度持续增加,农业干旱灾害风险评估是当前防灾减灾的重要方法之一。基于自然灾害风险形成机理,构建华北农业干旱风险评估指标体系模型,利用内部检验法对模型进行稳健性检验,根据华北34个市农业干旱风险形成特点聚类分类,并提出相应的风险防范建议。结果表明:调整风险评估模型中的指标和方法时,华北地区34个市农业干旱风险排名变化幅度多为1~2.5位,模型稳健性较好;除防灾减灾能力较高的北京、天津外,华北中部和北部农业干旱风险最高,与危险性和脆弱性指标较高有关,河南北部以及山东南部农业干旱风险较低,主要得益于该地区各市危险性较低;华北34个市可分为6个农业干旱风险集群,集群分布在空间上无分散、跨市分布,城市聚集性较好,其中北部山区集群4干旱风险最高,与其极高的环境脆弱性和低防灾减灾能力有关,应在农业种植结构上适当降低农业种植面积并加大农业投入;位于中部和南部的集群2、5和6具有较高的粮食种植面积且粮食因干旱减产率较高,可通过增加农业投入、提高灌溉保证率等进一步降低农业干旱风险。

基于WOFOST模型的辽宁省春玉米干旱灾损风险评估

利用锦州农业气象试验站的作物生长发育和土壤实测数据对WOFOST模型水分胁迫模块进行了调参,适用性验证表明,WOFOST模型适用于辽宁省春玉米生长发育和产量的模拟,辽宁省春玉米受干旱的影响可以利用WOFOST模型较敏感地反映出来。利用调参后的WOFOST模型模拟了全生育期及出苗~拔节、拔节~抽雄、抽雄~乳熟和乳熟~成熟各阶段发生轻、中、重旱情景对辽宁省春玉米产量的影响,并根据模拟结果确定了不同干旱风险等级下辽宁省东、中、西部玉米生产的灾损范围。结果表明:不同生育期发生干旱对产量的影响不同,总体上,抽雄~乳熟期发生干旱的影响最大,其次是拔节~抽雄期,而出苗~拔节期和乳熟~成熟期发生干旱对产量的影响较小,全省春玉米在抽雄~乳熟期发生重旱的减产风险达30%~70%;在相同干旱水平下,不同区域受影响程度也不同,在全生育期及各生育阶段发生轻、中、重旱情景下,干旱导致的减产率总体上表现为由东部向西部地区逐渐加重的趋势,在全生育期重旱情景下,辽宁省东部的春玉米减产率为40%~75%,中部为60%~90%,西部达65%~95%。

基于PSO-SVM的鹤盛溪流域山洪风险评价

为探究温州市鹤盛溪流域山洪风险空间分布,综合考虑山洪致灾因子、孕灾环境和承灾体3方面的山洪影响因子,建立基于粒子群优化-支持向量机(PSO-SVM)混合算法的山洪风险评价模型。选取准确度、灵敏度、特异性、F-score值、Kappa系数和受试者工作特征曲线等6个指标,采用学习矢量量化(LVQ)算法量化山洪影响因子对山洪灾害发生的影响程度,并将PSO-SVM混合算法模型与单一算法模型进行对比。结果表明:混合算法具有一定的迁移能力,能够更加准确地反映山洪风险的空间分布特征;验证集受试者工作特征曲线指标、Kappa系数和准确度分别为0.934、0.833、0.912,PSO-SVM混合算法模型能显著提高山洪风险评价精度。

基于普查数据的地震灾害隐患评估及其影响因素分析

地震灾害隐患评估是第一次全国自然灾害综合风险普查涵盖的工作,随着地震灾害隐患评估工作的推进,多省市承灾体地震灾害隐患评估工作相继完成,为利用普查结果辅助有关部门有针对性地做出决策,需分析承灾体隐患评估的影响因素。基于第一次全国自然灾害综合风险普查项目建筑调查数据,首先统计分析某省级行政区内不同烈度区域及峰值加速度调整区内5类承灾体数量、抗震设防水平、变形损伤现状、建造年代等情况;其次采用隐患等级技术评定规范计算承灾体单体隐患指数,并给出不同类别区域地震灾害隐患等级;最后结合烈度调升及峰值加速度调整情况对隐患评定结果影响因素进行对比分析。研究结果表明,烈度和设防峰值加速度提升均会使承灾单体及区域隐患等级整体提高;农村建筑区域地震灾害隐患等级总体较高,其中农村非住宅为地震灾害重点隐患的主要承灾体;重点隐患单体中变形损伤的影响随抗震设防烈度的升高而降低,一般隐患等级单体中变形损伤及建造年代的影响随抗震设防烈度的升高而降低。