基于GIS对岩溶塌陷预测及评价的方法

根据GIS强大的数据综合处理功能及其在地质灾害预测与评价方面的应用,通过对岩溶塌陷的区域条件、影响因子、预测及评价过程的研究,建立了以GIS、RS、GPS组成的空间信息技术体系应用于对象的技术手段确定评价指标和体系,收集评价数据,结合评价信息的处理和提取,实施评价模型,划分岩溶塌陷度综合等级。此方法的思路与方法似值得借鉴。     

Review of Study on Groundwater Contamination Risk Assessment in Vadose Zone-Aquifer

The vadose zone-aquifer is an important media for water circulation and solute transport in soil, surface water and groundwater. It is a research hotspot in the field of earth science. In this paper, we took the groundwater contamination risk assessment for the vadose zone-aquifers as the review object. The groundwater contamination status of vadose zone-aquifers was pointed out. The characterization of vadose zone-aquifers, the flow and solute transport as well as the key effect parameters were systematically analyzed and the research progresses were reviewed. Finally, the existing problems in the groundwater contaminant risk assessment under the condition of different scales of vadose zone-aquifers and future research direction were pointed out from the perspective of groundwater contaminant risk assessment. In particular, more attention should be paid to the groundwater contamination risk assessment based on percolation threshold.     

Area-scale landslide hazard and risk assessment

The paper deals with a methodology for quantitative landslide hazard and risk assessments over wide-scale areas. The approach was designed to fulfil the following requirements: (1) rapid investigation of large study areas; (2) use of elementary information, in order to satisfy the first requirement and to ensure validation, repetition and real time updating of the assessments every time new data are available; (3) computation of the landslide frequency of occurrence, in order to compare objectively different hazard conditions and to minimize references to qualitative hazard attributes such as activity states. The idea of multi-temporal analysis set forth by Cardinali et al. (Nat Hazards Earth Syst Sci 2:57–72, 2002), has been stressed here to compute average recurrence time for individual landslides and to forecast their behaviour within reference time periods. The method is based on the observation of the landslide activity through aerial-photo surveys carried out in several time steps. The output is given by a landslide hazard map showing the mean return period of landslides reactivation. Assessing the hazard in a quantitative way allows for estimating quantitatively the risk as well; thus, the probability of the exposed elements (such as people and real estates) to suffer damages due to the occurrence of landslides can be calculated. The methodology here presented is illustrated with reference to a sample area in Central Italy (Umbria region), for which both the landslide hazard and risk for the human life are analysed and computed. Results show the powerful quantitative approach for assessing the exposure of human activities to the landslide threat for a best choice of the countermeasures needed to mitigate the risk.An erratum to this article can be found at     

北京平原区浅层地下水污染风险评价

本文依据北京实际情况,提出了地下水污染风险评价指标体系。以灾害风险理论为基础,提出了地下水污染风险评价方法,对北京平原区浅层地下水污染风险进行了分区评价。评价认为：北京平原区浅层地下水污染高风险区主要位于永定河冲洪积扇顶部。     

西南地区农业旱情的气象干旱指数适应性研究

利用西南地区60站1961—2011年的日平均气温、降水量资料求得半年尺度的气象干旱指数值,包括帕尔默干旱指数、标准化降水干旱指数、Z指数、降水距平百分率指数。采用超前相关、相似和技巧评分两种计算方法检测与西南地区农业灾情最适宜的气象干旱指数。基于最适宜的干旱指数,给出西南地区农业干旱灾害可能发生的风险分布。结果表明:Z指数定义的冬半年气象干旱对西南地区农业旱情的指示性较其他3种气象干旱指标更优。冬半年Z指数小于等于-0.84时引发的西南地区农业干旱灾害成灾率大于8%的风险平均达0.53,农业干旱绝收率大于5%的风险平均达0.37,风险最大地区位于贵州西北部。结论有助于深入认识气象干旱指数与农业干旱灾情的联系,对于西南地区农业干旱的检测预测有一定的应用价值。     

南昌雷电监测数据在雷击风险评估中的应用

利用由江西省闪电监测网获取的南昌地区2004—2010年雷电监测资料,计算评估对象周围5 km范围内的雷击密度,雷击主导方向、次主导方向以及雷电幅值参数。结果表明,使用监测数据计算得到的雷击大地的年平均密度值,比用雷暴日计算得到的值得更精确、更符合实际情况;分析得到评估对象所在地雷击主导方向、次主导方向,能为雷击风险评估提供真实数据;根据评估对象周围雷电流幅值概率的分布特征选择的雷电流幅值,使电涌保护器雷电流参数选取更加科学、准确。     

气候变化背景下的洪涝风险稳健决策方法评述

分析了深度不确定性内涵及其特点,包括情景不确定、决策后果不确定和决策方案不确定,指出了传统洪涝风险决策方法过于依赖于气候变化预测结果,未能充分考虑深度不确定性及提供稳健决策。给出了国际上处理深度不确定性的稳健决策方法理论基础,并介绍了被广泛应用于洪涝风险领域的鲁棒决策、信息差距及适应对策路径3种稳健决策方法。对比分析发现,鲁棒决策法有完备的适应措施定量评估体系但计算量大且不易理解;信息差距法可解决不能以概率表式的不确定性问题,而未考虑适应对策的失效情景;适应对策路径法提供可视化的决策路径,未能充分考虑社会经济的不确定性。提出未来可综合鲁棒决策和适应对策路径优点,为减少不确定性、降低洪涝灾害风险、制定适应气候变化策略提供参考。     

北京山区工程勘察风险特征与防范措施研究

北京山区工程地质条件复杂,岩土工程勘察中存在或潜在着诸多风险,能否全面查清山区工程建设场地的工程地质条件,认清风险影响因素,对工程建设的安全至关重要。识别风险源,有助于提高对勘察风险的理解和掌握。本文试对北京山区岩土勘察风险的主要影响因素进行分析,并提出对应的防范措施,希望能为北京山区工程建设安全提供一些参考和帮助。     

东北地区水稻霜冻灾害风险评估与区划

依据灾害系统理论,在综合考虑致灾因子自然属性和承灾体社会属性的基础上,建立风险评估模型,将传统的灾害研究方法与地理信息系统等现代技术手段相结合,利用1961—2010年东北地区182个气象站点逐日最低气温资料和1991—2006年172个水稻产区县（市）国土面积及社会经济资料,包括1981—2006年30个农业气象观测站水稻发育期资料,对东北地区水稻霜冻灾害风险进行评估。结果表明：东北地区可划分为高风险、次高风险、中等风险、次低风险和低风险5个水稻霜冻灾害风险区域。东北地区水稻霜冻灾害高风险区位于黑龙江省的黑河地区大部、伊春西部和吉林省的延边州西部、白山北部等地,而辽宁省的中南部等地风险较低。     

Identifying wildland fire ignition factors through sensitivity analysis of a neural network

Artificial neural networks (ANNs) show a significant ability to discover patterns in data that are too obscure to go through standard statistical methods. Data of natural phenomena usually exhibit significantly unpredictable non-linearity, but the robust behavior of a neural network makes it perfectly adaptable to environmental models such as a wildland fire danger rating system. These systems have been adopted by many developed countries that have invested in wildland fire prevention, and thus civil protection agencies are able to identify areas with high probabilities of fire ignition and resort to necessary actions. Since one of the drawbacks of ANNs is the interpretation of the final model in terms of the importance of variables, this article presents the results of sensitivity analysis performed in a back-propagation neural network (BPN) to distinguish the influence of each variable in a fire ignition risk scheme developed for Lesvos Island in Greece. Four different methods were utilized to evaluate the three fire danger indices developed within the above scheme; three of the methods are based on network’s weights after the training procedure (i.e., the percentage of influence—PI, the weight product—WP, and the partial derivatives—PD methods), and one is based on the logistic regression (LR) model between BPN inputs and observed outputs. Results showed that the occurrence of rainfall, the 10-h fuel moisture content, and the month of the year parameter are the most significant variables of the Fire Weather, Fire Hazard, and Fire Risk Indices, respectively. Relative humidity, elevation, and day of the week have a small contribution to fire ignitions in the study area. The PD method showed the best performance in ranking variables’ importance, while performance of the rest of the methods was influenced by the number of input parameters and the magnitude of their importance. The results can be used by local forest managers and other decision makers dealing with wildland fires to take the appropriate preventive measures by emphasizing on the important factors of fire occurrence.