“冰冻灾害”过程中长途汽车司机心理安全感与应付方式的初步调查

“春季冰灾”的严重后果无疑是“京珠高速”的瘫痪,而长时间滞留其中的长途汽车司机既是灾害当事人,也是灾害见证人。在灾害持续过程中了解当事人心理活动及其变化过程,在灾害心理学上无疑具有理论意义与实践价值。调查结果表明,灾害持续时间（车辆滞留时间）与当事人的心理活动有着密切的关系,灾害持续一周后,当事人的心理安全感显著下降,应付方式开始从成熟型应对向不成熟型应对退化。看来,灾害持续不仅消解心理健康,而且瓦解应变能力。     

沈阳市降雪中PFOS和PFOA污染现状调查

通过调查降雪中PFOS和PFOA的浓度,阐明了沈阳市大气中PFOS和PFOA的污染状况和污染规律.2006-02-06采集沈阳市区和郊区共计36个采样点的降雪样品,2006-02-25在其中5个采样点再次采集降雪样品.固相萃取融雪水中的PFOS和PFOA,利用LC-MS-SIM法测定样品中PFOS和PFOA浓度.全部样品中均检出PFOS和PFOA.2006-02-06降雪中PFOS和PFOA的浓度几何平均值分别为2.0 ng·L^-1（范围：0.4～46.2 ng·L^-1）和3.6 ng·L^-1（范围：1.6～22.4 ng·L^-1）,95%置信区间分别为1.5～2.8 ng·L^-1和3.1～4.2 ng·L^-1.PFOS和PFOA的最高浓度同时出现在郊区采样点朱尔屯,市中心区2种物质的浓度呈显著正相关.2006-02-25的5个采样点降雪中PFOS和PFOA的浓度几何平均值均为2.2 ng·L^-1.2次降雪中PFOS浓度差异不显著,2006-02-25降雪中PFOA浓度高于2006-02-06.结果表明,沈阳市区和郊区降雪中广泛存在PFOS和PFOA污染,局部区域可能存在共同的PFOS和PFOA污染来源;沈阳地区有较稳定的PFOS来源持续向大气中输送该类物质;PFOS和PFOA的环境行为可能不同.     

重大冰雪灾害应急管理能力评价体系研究

深入分析了重大冰雪灾害应急管理能力评价体系的构建依据,提出了评价体系结构.首先根据全过程管理理论及系统论中的层次分析法,构造了重大冰雪灾害应急管理能力集,在此基础上结合冰雪灾害的特点提出了能力因素集.其次调研湖南省30位政府部门应急管理专家,根据专家意见最后确立重大冰雪灾害应急管理能力评价体系结构,为能力评价研究打下基...     

Defining the Diurnal Pattern of Snowmelt Using a Beta Distribution Function

Snow is an important component of the hydrologic cycle for many regions worldwide. In addition to vital water resources, snowmelt can be important for forest ecosystem dynamics and flood risk. However, standard design events in the United States lack a design snowmelt event, including only precipitation events, though snowmelt has been shown to be larger than rainfall. In this article, we present a method using hourly snow water equivalent data to develop and test a function for representing the diurnal pattern of snowmelt. A two‐parameter beta distribution function is modified for the purposes of this study and found to fit the pattern of snowmelt well with a root mean squared error of 0.008. Soil moisture sensors were additionally utilized to assess the timing of the snowmelt water outflow from the base of the snowpack that supports the shape of the function, but suggests that the timing of losses recorded on snow pillows lag as much as 3 h. Further testing of the function showed the shape of the function to be accurate. The methods developed and tested in this paper can be applied for design purposes comparing snowmelt and rainfall events or to improve hydrological models investigating processes such as streamflow or groundwater recharge.     

Local and regional variability in snow conditions in northern Finland: A reindeer herding perspective

Weather station measurements were used to force the SNOWPACK snow model and combined with reindeer herders’ experiences to study the local and regional variations in snow conditions in a Finnish reindeer herding area for the 1981–2010 period. Winter conditions varied significantly between the four selected herding districts and between open and forest environments within the districts. The highest snow depths and densities, the thicknesses of ground ice, and the lengths of snow cover period were generally found in the northernmost districts. The snow depths showed the strongest regional coherence, whereas the thicknesses of ground ice were weakly correlated among the districts. The local variation in snow depths was higher than the regional variation and limits for rare or exceptional events varied notably between different districts and environments. The results highlight that forests diversify snow and foraging conditions, e.g., ground ice rarely forms simultaneously in different environments. Sufficient and diverse forest pastures are important during the critical winter season if reindeer herding is pursued on natural grazing grounds also in the future.     

Does Including Soil Moisture Observations Improve Operational Streamflow Forecasts in Snow‐Dominated Watersheds?

Changing climate and growing water demand are increasing the need for robust streamflow forecasts. Historically, operational streamflow forecasts made by the Natural Resources Conservation Service have relied on precipitation and snow water equivalent observations from Snow Telemetry (SNOTEL) sites. We investigate whether also including SNOTEL soil moisture observations improve April‐July streamflow volume forecast accuracy at 0, 1, 2, and 3‐month lead times at 12 watersheds in Utah and California. We found statistically significant improvement in 0 and 3‐month lead time accuracy in 8 of 12 watersheds and 10 of 12 watersheds for 1 and 2‐month lead times. Surprisingly, these improvements were insensitive to soil moisture metrics derived from soil physical properties. Forecasts were made with volumetric water content (VWC) averaged from October 1 to the forecast date. By including VWC at the 0‐month lead time the forecasts explained 7.3% more variability and increased the streamflow volume accuracy by 8.4% on average compared to standard forecasts that already explained an average 77% of the variability. At 1 to 3‐month lead times, the inclusion of soil moisture explained 12.3‐26.3% more variability than the standard forecast on average. Our findings indicate including soil moisture observations increased statistical streamflow forecast accuracy and thus, could potentially improve water supply reliability in regions affected by changing snowpacks.     

Testing and Improving Temperature Thresholds for Snow and Rain Prediction in the Western United States

The phase of precipitation at the land surface is critical to determine the timing and amount of water available for hydrological and ecological systems. However, there are few techniques to directly observe the precipitation phase and many prediction tools apply a single temperature threshold (e.g., 0°C) to determine phase. In this paper, we asked two questions: (1) what is the accuracy of default and station optimized daily temperature thresholds for predicting precipitation phase and (2) what are the regions and conditions in which typical temperature‐based precipitation phase predictions are most suited. We developed a ground truth dataset of rain vs. snow using an expert decision‐making system based on precipitation, snow depth, and snow water equivalent observations. This dataset was used to evaluate the accuracy of three temperature‐threshold‐based techniques of phase classification. Optimizing the temperature threshold improved the prediction of precipitation phase by 34% compared to using 0°C threshold. Developing a temperature threshold based on station elevation improved the error by 12% compared with using the 0°C temperature threshold. We also found the probability of snow as a function of temperature differed among ecoregions, which suggests a varied response to future climate change. These results highlight a current weakness in our ability to predict the effects of regional warming that could have uneven impacts on water and ecological resources.     

干旱区城市昌吉降雪及积雪中PGEs含量分布及其影响因素

选择干旱区中小城市昌吉市,对其降雪及积雪中铂族元素(PGEs)含量分布及影响因素进行研究.运用ICP-MS对样品进行分析测定.结果表明,降雪中Rh、Pd、Pt平均含量分别为0.43 ng·L-1(未检出～2.24 ng·L-1)、60.07 ng·L-1(46.66～84.25 ng·L-1)和4.54 ng·L-1(3.02～6.38 ng·L-1).不同场次降雪中PGEs含量存在差异,随雪前干燥期天数加长,降雪中PGEs含量趋于增大;降雪量对PGEs含量也有一定影响,降雪量越小,雪中PGEs含量越高.积雪中Rh、Pd、Pt的平均含量分别为6.65 ng·L-1(2.50～18.80 ng·L-1)、83.45 ng·L-1(46.83～199.20 ng·L-1)和8.17 ng·L-1(4.27～13.78 ng·L-1).积雪中PGEs含量远高于降雪,降雪中PGEs仅来自于单场次降雪对大气PGEs的淋洗,而积雪中PGEs不仅来自于多场次降雪中PGEs的累积,且由于积雪长时间暴露,还源源不断接受了大气干沉降带来的PGEs.各采样点积雪PGEs含量表现出交通区>居民文教区>公园广场区>郊区农田,随功能区不同,积雪中PGEs输入途径与输入量有显著差异,这是造成各功能区积雪PGEs含量不同且具有一定规律性的主要原因.     

基于SARIMA模型的黑龙江省冰雪旅游国际需求预测

选取黑龙江省1990-2011年冰雪旅游入境人次的月度时间序列为研究样本，建立SARIMA模型对黑龙江省冰雪旅游国际需求进行分析预测。结果表明，SARIMA（4，1，4）（1，1，1）。模型的拟合度和短期预测效果都较好。通过应用SARIMA模型进行冰雪旅游预测，以期对黑龙江省旅游企业的冰雪旅游国际客源市场开发及政府部门制定冰雪旅游发展战略和政策调整提供重要的理论依据。     

陕南地区清代霜雪灾害及分形特征研究

通过对陕南清代历史文献资料的搜集、整理和分析,研究了清代(1644-1911年)陕南霜雪灾害等级、阶段变化及不同等级灾害周期性等。统计分析显示,陕南清代发生霜雪灾害28次,平均每9.57年发生一次;霜雪灾害可划分为轻度、中度、重度三级,各占灾害总频次的21%,72%和7%;清代霜雪灾害可分为4个阶段,其中1644-1668年和1819-1868年的第1、第3阶段为灾害多发期,而1669-1818年和1869-1911年的第2、第4阶段为灾害少发期。霜雪灾害的自相似性揭示了灾害的分形性,分形结果显示陕南地区清代各等级灾害呈周期变化,且这些灾害的集中性非常强。陕南清代轻度、中度和重度霜雪灾害发生分别存在着16～18 a,7～8 a和46 a振荡周期。该地区霜雪灾害的发生主要是偏暖月的持续性降雪、积雪或由寒流引起的气温骤降造成的。初步确定陕南清代发生了两次霜雪灾害气候事件,时间在公元1649-1663年和1817-1842年。