基于多元回归分析的铬污染地下水风险评价方法

土-水分配系数（K_d）是表征重金属污染物在土壤包气带中迁移能力的重要参数,受污染物质量浓度、pH值、有机质质量分数、铁铝氧化物质量分数等多种因素影响。本文通过实验研究了分配系数与各种影响因素之间的关系,基于多元回归分析方法得到了分配系数与影响因素的关系方程;并以分配系数、泄漏量、土壤孔隙度、初始含水率为风险因子建立了地下水污染风险评价方法。以某工厂铬废液的泄露为案例,采用构建的方法进行地下水污染风险评价。结果表明：该处地下水被污染的风险等级为中等。地下水污染风险评价方法的建立为重金属污染地下水的监测管理提供了一种有效方法。     

青藏铁路西大滩-拉萨地段活动构造、地质灾害及其工程评价

本文是作者在1975~1977年间青藏铁路(格尔木-那曲地段)沿线水文地质、工程地质调查所获资料基础上,参考了后期他人在该区段研究的成果撰写而成。文中主要涉及活动构造、地质灾害及工程评价三大部分,其中特别是活动构造部分,除了所表现的一般标志外,重点探讨了活动构造与现代地震和古地震的关系、活动构造带与地震构造带的对应关系、活动断裂的活动年龄及其活动速率、活动断裂与地震地表破裂以及主要地震构造带中的地震活动周期等诸多方面的问题,并结合铁路沿线地质灾害类型,在综合分析基础上,首次较系统地将铁路沿线工程地质评价划分为:①良好的;②一般的;③不良好的和④极不良好的等四大类型工程地质地段,从而为现今青藏铁路建设进一步详查和评价提供了重要依据。      

Differences in flood hazard projections in Europe – their causes and consequences for decision making

This paper interprets differences in flood hazard projections over Europe and identifies likely sources of discrepancy. Further, it discusses potential implications of these differences for flood risk reduction and adaptation to climate change. The discrepancy in flood hazard projections raises caution, especially among decision makers in charge of water resources management, flood risk reduction, and climate change adaptation at regional to local scales. Because it is naïve to expect availability of trustworthy quantitative projections of future flood hazard, in order to reduce flood risk one should focus attention on mapping of current and future risks and vulnerability hotspots and improve the situation there. Although an intercomparison of flood hazard projections is done in this paper and differences are identified and interpreted, it does not seems possible to recommend which large-scale studies may be considered most credible in particular areas of Europe.

EDITOR D. Koutsoyiannis

ASSOCIATE EDITOR not assigned     

汶川特大地震之北川县城震害分析

2008年5月12日汶川8.0级地震在北川县城造成了巨大的破坏,导致上万人死亡,整个北川县城变为废墟。现场地震科考分析显示,造成北川县城建筑物和道路严重损毁以及人员重大伤亡的三个主要原因为:活断层错动产生的地表破裂效应,地震引发的次生地质灾害(崩塌、滑坡)和强地震动产生的振动破坏效应。北川县城主断裂和次级断裂沿线分布的建筑物震害较重,而邻近断裂的建筑物震害相对较轻;地震触发的王家岩滑坡和景家山崩塌对北川县城造成了极大的破坏,导致2000余人死亡;而振动破坏效应在北川县城普遍存在,它产生的水平剪切运动对建筑物的危害很严重。     

The U.S. National Tsunami Hazard Mitigation Program: A Successful State–Federal Partnership

The U.S. National Tsunami Hazard Mitigation Program (NTHMP) is a State/Federal partnership created to reduce tsunami hazards along U.S. coastlines. Established in 1996, NTHMP coordinates the efforts of five Pacific States: Alaska, California, Hawaii, Oregon, and Washington with the three Federal agencies responsible for tsunami hazard mitigation: the National Oceanic and Atmospheric Administration (NOAA), the Federal Emergency Management Agency (FEMA), and the U.S. Geological Survey (USGS). In the 7 years of the program it has, 1. established a tsunami forecasting capability for the two tsunami warning centers through the combined use of deep ocean tsunami data and numerical models; 2. upgraded the seismic network enabling the tsunami warning centers to locate and size earthquakes faster and more accurately; 3. produced 22 tsunami inundation maps covering 113 coastal communities with a population at risk of over a million people; 4. initiated a program to develop tsunami-resilient communities through awareness, education, warning dissemination, mitigation incentives, coastal planning, and construction guidelines; 5. conducted surveys that indicate a positive impact of the programs activities in raising tsunami awareness. A 17-member Steering Group consisting of representatives from the five Pacific States, NOAA, FEMA, USGS, and the National Science Foundation (NSF) guides NTHMP. The success of the program has been the result of a personal commitment by steering group members that has leveraged the total Federal funding by contributions from the States and Federal Agencies at a ratio of over six matching dollars to every NTHMP dollar. Twice yearly meetings of the steering group promote communication between scientists and emergency managers, and among the State and Federal agencies. From its initiation NTHMP has been based on the needs of coastal communities and emergency managers and has been results driven because of the cycle of year-to-year funding for the first 5 years. A major impact of the program occurred on 17 November 2003, when an Alaskan tsunami warning was canceled because real-time, deep ocean tsunami data indicated the tsunami would be non-damaging. Canceling this warning averted an evacuation in Hawaii, avoiding a loss in productivity valued at $68M.     

基于ANUSPLIN软件的逐日气象要素插值方法应用与评估

气象要素是资源、环境、灾害以及全球变化等领域研究的数据基础,格点化数据在未来研究应用中显得日益重要。本文基于中国境内667个基本和基准地面气象观测站点的基本气象资料,使用ANUSPLIN专用气候插值软件对1961-2006年逐日气温、降水进行插值,并利用未参与插值的全国1667个加密站点对插值结果的准确性进行检验,同时与反向距离权重法和普通克吕格法等插值方法的结果进行对比。结果表明,利用667个站点使用ANUSPLIN软件进行逐日平均气温插值有92.0%的误差在2.0℃以内,75.0%的误差在1.0℃以内,0.9%的误差在5.0℃以上,平均绝对误差为0.8℃;对逐日降水进行插值,75.0%的误差小于5.0mm,85%的误差小于10.0mm,平均绝对误差为6.4mm,误差大小与降水量呈现出正相关性,对局地强降水的插值效果不好,这可能与参与局部拟合插值的样本数太少有关;同时,夏季的温度插值误差小于冬季,而冬季的降水误差小于夏季。将ANUSPLIN的局部薄盘样条插值结果分别与反向距离权重法和普通克吕格法的插值结果进行对比,显示ANUSPLIN软件的插值误差最小。结果同样表明,适当增加站点数量和提高DEM精度可进一步提高ANUSPLIN软件的插值精度。     

An Agricultural Land Resource Assessment Study Based on GIS—An Example from Guiyang City

This paper assesses the agricultural land resources of Guiyang City by means of GIS,on the basis of the pressure-state-response model in which soil heavy metal contamination is selected as a pressure indicatror.he results suggest that most of the agricultural land resources are of good quality,However,there are 17.11km^2 dry land and paddy field,which belong to the region of serious heavy metal contamination and are not fit for planting crops.At the same time,the high quality plowland,which is suitable for cultivation,has decreased nearly by 1/3 due to soil heavy metal contamination.These findings may improve our understanding that it is very important to prevent and cure heavy metal contamination of Guiyang City.     

Seismic risk assessment of interdependent critical infrastructure systems: The case of European gas and electricity networks

We study the seismic vulnerability of the interdependent European gas and electricity transmission networks from a topological point of view, whereby the electricity network depends on the gas network through gas‐fired power plants. First, we assessed the seismic response for each independent network; then we analyzed the increased vulnerability due to their interdependency. We implemented a probabilistic reliability model that encompasses the spatial distribution of both network structures and their seismic hazard exposure using a Geographic Information System. We characterized the network interdependency using the strength of coupling of the interconnections, together with the seismic response of the independent—gas—network. We calculated the network fragility curves of the independent and dependent networks in terms of various performance measures (connectivity loss, power loss, and impact on the population) and found that the gas network is more seismically vulnerable than the electricity network. The interdependency introduces an extra vulnerability to the electricity network response that decreases with the extensiveness of the networks' damage states. Damage was also evaluated at a local level in order to identify the most vulnerable parts of the network, where it was found that the potential for the highest power loss is located in southeast Europe. Copyright © 2011 John Wiley & Sons, Ltd.     

融合降水实况分析产品在四川地区的适用性评估

利用四川省地面自动站2018年6月—2019年5月的逐小时降水观测资料,在邻近插值和双线性插值对比分析的基础上,从晴雨准确率、降水时空特征、降水分量级检验等多个方面,对国家气象信息中心研制的融合降水实况分析产品在四川地区的适用性进行评估分析.评估结果表明:(1)邻近插值和双线性插值对评估结果影响小.(2)融合降水实况分...     

A workflow for Sustainable Development Goals indicators assessment based on high-resolution satellite data

ABSTRACT

For evaluating the progresses towards achieving the Sustainable Development Goals (SDGs), a global indicator framework was developed by the UN Inter-Agency and Expert Group on Sustainable Development Goals Indicators. In this paper, we propose an improved methodology and a set of workflows for calculating SDGs indicators. The main improvements consist of using moderate and high spatial resolution satellite data and state-of-the-art deep learning methodology for land cover classification and for assessing land productivity. Within the European Network for Observing our Changing Planet (ERA-PLANET), three SDGs indicators are calculated. In this research, harmonized Landsat and Sentinel-2 data are analyzed and used for land productivity analysis and yield assessment, as well as Landsat 8, Sentinel-2 and Sentinel-1 time series are utilized for crop mapping. We calculate for the whole territory of Ukraine SDG indicators: 15.1.1 – ‘Forest area as proportion of total land area’; 15.3.1 – ‘Proportion of land that is degraded over total land area’; and 2.4.1 – ‘Proportion of agricultural area under productive and sustainable agriculture’. Workflows for calculating these indicators were implemented in a Virtual Laboratory Platform. We conclude that newly available high-resolution remote sensing products can significantly improve our capacity to assess several SDGs indicators through dedicated workflows.