1999年我国主要气象灾害及异常气候事件

１９９９年,我国先后出现了干旱、暴雨洪涝、台风、风雹、沙尘暴、雪灾和冻害等多种气象灾害,特别是干旱持续时间长、范围广,旱情重。除上述气象灾害外,本年度还出现了冬暖,夏凉、春寒、倒春寒、夏季高温和秋老虎等异常气候事件,本文主要是几种主要气旬灾害和异常气候事件的发生特点和影响进行了分析和评述。     

统计降尺度在AREM模式洪水预报试验中应用初探

利用2006~2008年AREM模式预报降雨和漳河水库逐小时雨量站观测降雨及入库流量资料,对水库流域进行网格划分,建立了基于网格的空间分辨率分别为(0.25°×0.25°)和(0.5°×0.5°)的降雨预报统计降尺度模型,同时对降尺度模型了进行了模拟效果的检验,证明该降尺度模型的计算结果可以用于漳河水库洪水预报试验。从2009~2010年中选取了4次洪水过程,进行个例试验,试验结果表明,统计降尺度模型对洪水过程效率系数的改进效果不明显,但对减小预报洪峰流量相对误差有一定的效果,平均相对误差降低了10%左右,峰现时差也略有减小。     

洪涝灾害后城镇景观长距离输水系统水文风险评估

对输水系统运作过程存在风险采取准确评估,可有效维护洪涝灾害后城镇景观设施完整性.该文提出一种基于MS-AR模型的长距离输水系统水文风险评估方法,首先分析输水节点结构重要性与网络结构抗毁性的耦联关系,推算平均节点结构重要度,明确节点对系统损坏贡献水平,利用节点结构重要度离散性质表示输水系统网络结构抗毁性,获取长距离输水系...     

Willingness to pay for agricultural flood insurance in the Mekong River Delta

Increasing urbanization and industrial development upstream of the Mekong River Delta of Vietnam (MRD) including the construction of a series of dams for hydroelectricity generation is changing the downstream risk of flooding. Concerns about the likely influence of global climate change and rising sea levels add further uncertainty to this risk that threatens the livelihood of farmers. With this in mind and in view of the under-developed state of the market for crop insurance in the MRD, we survey rice growers to explore their willingness-to-pay (WTP) for crop insurance by using a choice experiment. The experimental design comprised five attributes, including the type of peril covered – riverine flooding (flooding); flooding triggered by tidal regimes (inundation); or flooding, inundation and wind damage – type of provider; extent of cover and deductible and premium. Two hundred and twenty-six rice-growing farmers were surveyed with each farmer responding to six different choices. Our study shows that WTPs for an insurance plan covering a loss up to 2 million VND/1000m²/farming season and having a deductible of 25% of the potential (profit) crop value varied between 200,000 and 500,000?VND/1000m² (1USD?=?22,550 Vietnamese Dong – VND) for each rice growing season, implying a potential market for crop insurance.     

基于信息扩散理论的福建省农业水灾风险评估

利用1978—2008年福建省农业水灾受灾和成灾面积数据,以灾情(受灾和成灾)指数反映水灾的影响范围,以成受比(成灾与受灾指数的比值)指数反映水灾影响强度,基于正态信息扩散计算方法对农业水灾进行风险评估,利用发生频次法对评估结果进行检验。结果表明:农业受水灾影响的风险概率随风险指数提高而下降;在相同风险指数下,成受比风险概率>受灾风险概率>成灾风险概率;受灾、 成灾、 成受比的平均风险概率分别为0.448 7、 0.480 0、 0.651 6,水灾对福建农业的影响比较频繁,影响范围和强度比较严重。风险评估结果与实际情况基本相符。     

FLOOD DAMAGES IN CHANGING FLOOD PLAINS: A FORENSIC‐HYDROLOGIC CASE STUDY1

ABSTRACT: Hydraulic modification of flood plains by human activity is the primary cause of rising flood damages throughout the world. As flood‐plain hydraulic roughness increases, so does the water level for a fixed flow rate. This raises the flood damage associated with a flood of given return period, and thus, magnifies the flood risk. This article presents an approach that integrates climatic, hydrologic, and hydraulic principles and presents models to discern the probable causes of flood damage in a basin that undergoes flood‐plain development. The article documents key factors that govern flood damage and presents a case study that illustrates the principles of forensic hydrology in an impacted flood plain. The study demonstrates flood level rise caused by hydraulic alteration of a flood plain between 1969 and 1995 and apportioned the increased water level among agricultural and structural factors located in the study area.     

镉对小麦叶片DNA伤害的彗星实验研究

为了建立植物基因毒性的研究方法 ,以小麦为对象 ,进行了植物彗星实验方法的研究 .以 0 1mg·L- 1 的Cd2 + 溶液处理小麦叶片后 ,采用机械方法分离细胞核 ,制备玻片后变性 0 ,5 ,15 ,3 0min ,在 10 0 ,2 0 0 ,3 0 0mA下电泳 5 ,15 ,3 0min .实验结果表明 ,采用机械分离的方法可以获得大量的、能够进行彗星实验的细胞核 ,增加DNA的变性时间、电泳电流大小和电泳时间可以增加DNA片段在电场中的迁移 ,提高实验的灵敏度 ,但变性时间和电泳时间过长增加了对照处理DNA片段的迁移 .因此 ,本实验提出了小麦叶片彗星实验的最佳条件是DNA变性 15min ,3 0 0mA下电泳 15min ,并在该条件下研究了重金属镉对小麦的基因损伤 .结果表明 ,重金属镉能引起小麦基因的损伤 ,并随镉浓度的增加伤害程度加大     

广西漓江洪涝灾害及防御对策研究

利用GIS信息系统和降水实况资料,对发生在广西漓江的洪涝情况进行分析。通过对洪涝灾害进行实地调查,利用灾害风险评估技术,对漓江洪涝灾害进行风险区划,对洪涝灾害的防御措施进行探讨。漓江上游是广西的暴雨中心,汛期暴雨常造成漓江洪涝灾害,特别是5-6月份,每年基本上都有2~3次大面积的洪灾;沿江两岸都是洪涝灾害的高风险区;漓江洪水具有来得快,消得也快的特点;造成漓江致洪暴雨的天气形势主要是华南静止锋;加强上游降水量的监测和预报,加强上游水库蓄水错峰的调控能力,完善低洼地段防洪堤坝建设,可以有效地防御洪涝灾害。     

Diffusive wave models for operational forecasting of channel routing at continental scale

Operational forecast models require robust, computationally efficient, and reliable algorithms. We desire accurate forecasts within the limits of the uncertainties in channel geometry and roughness because the output from these algorithms leads to flood warnings and a variety of water management decisions. The current operational Water Model uses the Muskingum-Cunge method, which does not account for key hydraulic conditions such as flow hysteresis and backwater effects, limiting its ability in situations with pronounced backwater effects. This situation most commonly occurs in low-gradient rivers, near confluences and channel constrictions, coastal regions where the combined actions of tides, storm surges, and wind can cause adverse flow. These situations necessitate a more rigorous flow routing approach such as dynamic or diffusive wave approximation to simulate flow hydraulics accurately. Avoiding the dynamic wave routing due to its extreme computational cost, this work presents two diffusive wave approaches to simulate flow routing in a complex river network. This study reports a comparison of two different diffusive wave models that both use a finite difference solution solved using an implicit Crank–Nicolson (CN) scheme with second-order accuracy in both time and space. The first model applies the CN scheme over three spatial nodes and is referred to as Crank–Nicolson over Space (CNS). The second model uses the CN scheme over three temporal nodes and is referred to as Crank–Nicolson over Time (CNT). Both models can properly account for complex cross-section geometry and variable computational points spacing along the channel length. The models were tested in different watersheds representing a mixture of steep and flat topographies. Comparing model outputs against observations of discharges and water levels indicated that the models accurately predict the peak discharge, peak water level, and flooding duration. Both models are accurate and computationally stable over a broad range of hydraulic regimes. The CNS model is dependent on the Courant criteria, making it less computational efficient where short channel segments are present. The CNT model does not suffer from that constraint and is, thus, highly computationally efficient and could be more useful for operational forecast models.     

“历史模型”与灾害研究

灾害研究涉及多学科的交叉领域．水灾“历史模型”的研究方法是循社会科学的历史科学与自然科学的水利学科相结合的研究途径．将“历史模型”引人灾害研究．增强了研究与自然环境和社会经济密切相关的灾害问题的能力．本文论述了“历史模型”方法及其在灾害问题研究中的应用．