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 <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.

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

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.

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.

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.

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。

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。

曼谷地区干旱灾害风险分布及变化趋势分析

基于自然灾害风险评估理论,依据致灾因子危险性、承灾体的脆弱性,综合评估曼谷节点地区的干旱灾害风险。进而分析2000—2020年曼谷干旱灾害危险性、脆弱性和风险的空间分布特征和变化趋势。结果表明:1)曼谷干旱危险性在地区间存在差异,符合“北高南低”的规律。高脆弱性地区集中在曼谷都市区中部、佛统府西北部和沙没巴干府西部,与自然条件、人口和经济分布以及城市活动有关。曼谷干旱风险较高,中等及以上干旱灾害风险土地占总面积的41.64%,佛统府西北部和巴吞他尼府中部具有最高风险,同时具有较高的脆弱性和危险性。2)曼谷的风险性、脆弱性和危险性均呈线性上升趋势。巴吞他尼府和佛统府的危险性,佛统府西北部和曼谷中部城乡居民用地的脆弱性,以及佛统府西北部和、巴吞他尼府中部和曼谷都市区中部的干旱风险程度上升较快。3)M-K检验结果显示,曼谷危险性和风险均呈现“东升西降”的空间分布特征,但变化趋势均不显著。曼谷的脆弱性在大部分地区呈极显著上升趋势,沙没沙空府的脆弱性上升趋势最为显著,达到71.23%。4)曼谷的干旱灾害风险程度由危险性和脆弱性共同决定,一元线性线性回归分析结果与M-K检验分析结果在空间分布上存在明显差异,但都表明需采取措施降低脆弱性以降低城市干旱灾害风险。利用精细尺度的空间数据进行分析可以更准确反映该地区的资源管理能力,提高风险评估的合理性,为节点城市的灾害风险管理和风险分布研究提供有价值的参考。

基于AHP-模糊综合评价法的化工园区雷电灾害风险评估

为了评估化工园区的雷电灾害区域风险,选取包含园区等级、经济产值、区域防雷安全管理和防雷检查覆盖率等在内的19个评估指标,采用层次分析法和模糊综合评价法,建立化工园区雷电灾害区域风险评估模型,并对河北衡水高新区化工片区开展雷电灾害区域风险评估,以发现化工片区的雷灾隐患点和防雷措施薄弱环节,确定科学的防雷减灾策略,有效保障园区内生产安全和人员生命财产安全.

1961—2020年宁夏干旱事件年代际变化及风险评估

利用1961—2020年宁夏20个国家气象站气象观测资料,结合近40 a宁夏社会经济统计数据,建立宁夏干旱过程事件指标,并基于灾害风险评估理论建立宁夏年代际干旱灾害风险评估模型,分析宁夏干旱事件和主要农作物干旱灾害风险的年代际变化特征和区域差异性,并探讨造成区域农作物年代际风险变化的可能影响因素。结果表明:(1)近60 a宁夏干旱事件的累积效应、持续时间以及强度指标具有明显的年代际变化特征,宁夏中北部和南部山区分别在1980年和2010年前后出现趋势和均值的突变;干旱事件指标及致灾危险性指标大值区空间范围均呈现出增加-减少-增加-减少的变化特征。(2)20世纪80年代以来,宁夏不同地区玉米干旱灾害风险等级依次为引黄灌区>中部干旱带>南部山区,受玉米种植面积不断扩大和国内生产总值(GDP)持续增加影响,在中南部地区其干旱风险呈逐年代际增大趋势;小麦干旱灾害风险增加幅度为中部干旱带>南部山区>引黄灌区,致灾危险性、小麦种植面积及GDP等级较高是2010s中部干旱带部分地区干旱风险增大的主要原因。(3)面对未来宁夏中南部地区水资源短缺和灌溉用水不足的挑战,建议通过提高人工增雨能力、开发种植品种、退耕或移民等措施,减少干旱致灾危险性、孕灾环境脆弱性和承灾体暴露度,从而降低当地玉米和小麦的干旱灾害风险等级。研究结果可为地方科学规划农业生产、高效利用水资源、抗旱救灾等提供科学理论依据,促进宁夏黄河流域生态保护和高质量发展先行区建设。

基于GB 18401要求的进口纺织服装产品风险评价模型研究

本文基于国家强制性标准规定的纺织产品的基本质量安全指标,研究建立了对进口纺织服装产品质量安全风险进行量化分析的数学模型。通过实验室数据计算结果分析表明,单项目不合格因子(SIF)和综合质量安全风险值(CRV)两个指标,能够从产品本身质量方面比较客观准确地反映产品的质量安全风险问题,为国家相关部门开展对进口纺织服装产品的监管和风险监测提供可靠的决策参考数据。

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河北省海啸灾害风险评估和区划研究

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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。