西藏那曲牧区雪灾区域危险度的模糊综合评价研究

在野外调查和分析的基础上，选取10月至次年5月的平均气温和平均降水，以及稳定的积雪日数、平均积雪深度、草场现有载畜量、冷季草地超载比例、冬储草量等7个因子为那曲地区雪灾区域危险度的评价因子，将模糊综合评价的数学模型应用于雪灾区域危险度的评判。以西藏那曲地区的5个县为例，具体介绍了雪灾区域危险度模糊综合评价的方法和步骤。     

杭州地区城区降雪中全氟化合物的污染特征

通过调查杭州降雪中16种全氟化合物(PFCs)的质量浓度,考察了杭州地区大气中PFCs的污染状况.2016年1月20~22日,在杭州市城区及主要郊县建成区共计11个采样点采集降雪样品,应用固相萃取净化、富集与超高效液相色谱-串联质谱联用相结合的方法,测定样品中PFCs质量浓度.所有采样点降雪均有不同浓度的PFCs检出,全部样品共检出包括C_4和C_8全氟烷基磺酸以及C_4~C_6、C_8和C_9全氟烷基羧酸等7种中短链PFCs.ΣPFCs质量浓度范围为2.85~35.1 ng·L~(-1),其中全氟辛酸(PFOA)质量浓度范围2.15~23.0 ng·L~(-1),为主要污染因子,全氟辛烷磺酸(PFOS)检出浓度较低,为0~0.46 ng·L~(-1).与国内外其它地区相比杭州降雪中PFOA含量居于中等水平,PFOS含量则处于相对较低水平.污染物空间分布城区略高于郊县,其中富阳最高,建德和淳安较低.本次调查,在研究区域降雪中普遍检出以PFOA为主较高浓度的PFCs,表明湿沉降已经成为杭州地区土壤、地表水和地下水等生态系统PFCs污染一个不可忽视的污染源,需要有关部门引起足够的重视.研究结果揭示了杭州地区大气中广泛存在以PFOA为主的PFCs污染,大气因素可能已成为当地人群和生态环境暴露PFCs的重要途径之一.     

新疆雪豹种群密度监测方法探讨

2004-2010年间,前后累计270多天,新疆雪豹研究小组在新疆北塔山、阿尔泰山、昆仑山、天山东部和托木尔峰地区20多个地点(山谷),对雪豹(Uncia uncia)的痕迹进行了全面调查,共计完成150多条样线,总长度接近190 km,痕迹数平均为1～3个·km-1.记录到的痕迹有粪团、嗅痕(气味标记)、足迹链、刨痕(刨坑)、爪痕、卧迹、毛发、尿迹、血迹、剩余食物(动物尸体)和吼声等.通过痕迹学的分析,初步掌握雪豹的领域范围、分布规律和相对密度.之后开展了红外相机拍摄、雪豹食物资源普查、市场毛皮调查、贸易通道调查、杀戮案件搜集、民间问卷调查、非政府组织(NGO)社区服务与牧业冲突调研等工作.同期布设红外相机36台,约2094个照相日,计50 256 h,回收胶卷71个,回收清晰雪豹照片32张,平均拍摄率或"捕获率"(capture rate)达1.53%.确定在托木尔峰250 km2范围内有5～8只雪豹活动,密度为2.0～3.2只·(100 km2)-1.在比较分析各种监测结果的基础上,讨论了新疆雪豹种群密度不同监测方法的优点与局限性.     

Vulnerability Assessment of Snow Disaster Based on Traffic System： A Case Study of Chenzhou City in Hunan Province, China

The article establishes the patterns of urban snow disaster system and disaster chain based on the theory of regional disaster system. The patterns indicate that urban snow disaster is exacerbated mainly through the traffic system. In addition, the paper sets up the vulnerability assessment index system and synthetically vulnerability assessment model of urban snow disaster which are mainly based on traffic system, and applies them in Chenzhou City. The results of assessment indicate that obvious geographical differences exist in the vulnerability of snow disaster bearing bodies： vulnerability of Chenzhou section of the Beijing-Zhuhai expressway is the highest in Chenzhou City, and the southeastern counties are more vulnerable than the northwest region. Furthermore, according to the snow disaster vulnerability dynamic process analysis, the vulnerability of Chenzhou City obviously increased in 2008 winter compared with that in 2007. Finally, the paper presents some suggestions for the locations of the emergency commands and the reserves of relief materials based on the evaluation results, and points out that disaster monitoring and relevant technical level should be strengthened for the minimization of traffic system＇s vulnerability.     

Relationships between dissolved and particulate carbohydrate temporal patterns and mucilaginous aggregates formation: evidences from time series analysis and biochemical composition of aggregates

A 3-year monitoring of dissolved and particulate carbohydrate concentrations in four transects located in the Adriatic and Tyrrhenian Seas was performed in order to get information on the role played by carbohydrates in the mucilage formation in these areas. The application of time series analysis pointed out that the concentration of dissolved carbohydrates does not vary significantly in coincidence of the mucilage appearance showing an almost constant state with respect to time. In contrast, wider temporal variations of carbohydrate amounts, either increase or decrease, were observed when mucilages were lacking or reduced. This almost constant state of carbohydrate amounts observed in presence of mucilages that we define 'steady state' could be associated to an alteration of the complex chemical equilibrium between synthesis and degradation (either hydrolysis or oxidation) reactions of the organic polymers which are typical of the humification processes in the marine environment. The results of this study suggest that the monitoring of carbohydrates can represent an useful tool for the comprehension of the most relevant phenomena of mucilage appearance in the Northern Adriatic Sea.     

新疆干旱区季节性积雪中黑碳气溶胶研究

利用中分辨率成像光谱仪（MODIS）遥感数据与2018年1月野外实测的28个雪样,综合分析新疆干旱区季节性积雪中黑碳气溶胶浓度（BC）分布特征与气溶胶光学厚度（AOD）等.利用HYSPLIT-4后向轨迹模式获取釆样点逐日的后向轨迹,分析BC的可能传输路径.结果表明：①北疆地区积雪覆盖率从11月份到次年1月份逐渐增加,冬季积雪覆盖率可达到97.5%,冬季AOD平均值为0.173,高值出现在天山北坡经济带区域与东部区域（0.2~0.35）,低值区域主要在阿勒泰地区（0.06~0.1）.②表层积雪的BC浓度范围为44.08~1949.9ng/g,平均值为536.71ng/g,BC浓度分布特征为：天山北坡经济带BC浓度（913.24ng/g） > 艾比湖东南部区域（816.56ng/g） > 艾比湖北部区域（421.94ng/g） > 艾比湖西部区域（407.97ng/g） > 克拉玛依区域（162.28ng/g） > 古尔班通古特沙漠区域（124.89ng/g） > 阿勒泰地区（98.51ng/g）.随着海拔升高积雪中BC浓度有微弱上升,相关系数R²为0.03,随着纬度增加积雪中BC浓度均呈下降趋势,R²为0.255.③艾比湖流域后向轨迹中以博乐-精河-艾比湖向东北方向输送路径为主,对采样点的BC浓度影响较大;天山北坡经济带区域主要以精河-石河子-乌鲁木齐的天山北坡城市群向东北输送路径为主,局地污染较为严重;阿勒泰地区的后向轨迹以俄罗斯南部-哈萨克斯坦北部-东哈萨克斯坦输送路径为主,局地污染贡献较少;克拉玛依区域主要来自哈萨克斯坦东部和西部向东方向的输送,局地污染不明显;沙漠区域主要以西南方向输送路径为主.     

基于GIS的路面积雪灾害风险分析与区划研究

以宁夏高速公路为对象,利用1981—2018年25个常规气象站观测资料及交通相关数据资料,基于GIS、AHP等方法,从致灾因子的危险性、孕灾环境的敏感性、承灾体的易损性三方面进行高速公路路面积雪灾害风险分析与区划研究。结果表明:全区年平均积雪日数在6.5~86.7d,年平均降雪日数在10.3~64.5d,最大积雪深度在8~35cm,自南向北减少(浅),南部山区明显多(深)于北部地区。路面积雪灾害主要出现在冬季、初春和晚秋,大到暴雪级的路面积雪主要出现在秋冬转换的10~11月和冬春交替的3~4月。风险分析与区划研究结果表明,高风险区位于福银高速(G70)、青兰高速(G22)六盘山区东南麓区段;较高风险区位于福银高速(G70)固原市原州区段、青兰高速(G22)固原市隆德西段段、固西高速、彭青高速路段;同心以北的银川市、石嘴山市、吴忠市各路段风险总体较低。     

藏北高原土壤温度异常变化及其与雪灾关系初析

通过对ＧＡＭＥ－Ｔｉｂｅｔ野外工作期间所得藏北高原一个年周期的土壤温度资料的初步分析,发现藏北高原１９９７￣１９９８年冬半年土壤日温差的分布存在明显的异常现象;指出了这种异常现象的发生可能与藏北高原１９９７年冬天的特大雪灾有关。从浅层土壤日温差的异常变化,定性地说明了藏北高原１９９７￣１９９８年冬半年不同地点雪灾的严重程度,但由于受资料的限制,目前尚无法进行定量的评估。     

Groundwater Level Trends and Drivers in Two Northern New England Glacial Aquifers

We evaluated long‐term trends and predictors of groundwater levels by month from two well‐studied northern New England forested headwater glacial aquifers: Sleepers River, Vermont, 44 wells, 1992‐2013; and Hubbard Brook, New Hampshire, 15 wells, 1979‐2004. Based on Kendall Tau tests with Sen slope determination, a surprising number of well‐month combinations had negative trends (decreasing water levels) over the respective periods. Sleepers River had slightly more positive than negative trends overall, but among the significant trends (p < 0.1), negative trends dominated 67 to 40. At Hubbard Brook, negative trends outnumbered positive trends by a nearly 2:1 margin and all seven of the significant trends were negative. The negative trends occurred despite generally increasing trends in monthly and annual precipitation. This counterintuitive pattern may be a result of increased precipitation intensity causing higher runoff at the expense of recharge, such that evapotranspiration demand draws down groundwater storage. We evaluated predictors of month‐end water levels by multiple regression of 18 variables related to climate, streamflow, snowpack, and prior month water level. Monthly flow and prior month water level were the two strongest predictors for most months at both sites. The predictive power and ready availability of streamflow data can be exploited as a proxy to extend limited groundwater level records over longer time periods.     

Spatiotemporal Variability of Snow Depletion Curves Derived from SNODAS for the Conterminous United States, 2004‐2013

Assessment of water resources at a national scale is critical for understanding their vulnerability to future change in policy and climate. Representation of the spatiotemporal variability in snowmelt processes in continental‐scale hydrologic models is critical for assessment of water resource response to continued climate change. Continental‐extent hydrologic models such as the U.S. Geological Survey National Hydrologic Model (NHM) represent snowmelt processes through the application of snow depletion curves (SDCs). SDCs relate normalized snow water equivalent (SWE) to normalized snow covered area (SCA) over a snowmelt season for a given modeling unit. SDCs were derived using output from the operational Snow Data Assimilation System (SNODAS) snow model as daily 1‐km gridded SWE over the conterminous United States. Daily SNODAS output were aggregated to a predefined watershed‐scale geospatial fabric and used to also calculate SCA from October 1, 2004 to September 30, 2013. The spatiotemporal variability in SNODAS output at the watershed scale was evaluated through the spatial distribution of the median and standard deviation for the time period. Representative SDCs for each watershed‐scale modeling unit over the conterminous United States (n = 54,104) were selected using a consistent methodology and used to create categories of snowmelt based on SDC shape. The relation of SDC categories to the topographic and climatic variables allow for national‐scale categorization of snowmelt processes.