天山西部季节性积雪密度及含水率的特性分析

利用Snow Fork雪特性分析仪采集积雪物理特性(积雪深度、积雪密度、体积含水率)数据,分析了天山积雪雪崩站稳定积雪期和非稳定积雪期雪物理特性的时间变化特征及其在垂直剖面上的廓线分布.结果表明:1)稳定期积雪深度随时间缓慢减小,体积含水率垂直廓线随积雪深度变化呈单峰曲线,峰值距雪表面约33cm,雪密度垂直廓线为中部大、积雪表层和底部较小;2)非稳定积雪期积雪迅速沉陷,体积含水率相对于雪层温度的变化有滞后效应,滞后时间约为2h,雪密度垂直廓线与稳定期相同.整个非稳定积雪期的日平均雪密度与日平均含水率、日平均温度均呈显著正相关.     

高寒流域同位素径流分割研究进展

径流分割是应用水文学中的一个基本问题,同位素径流分割则是采用同位素进行分割的方法,其应用范围已从产流理论研究拓展至地下水地表水相互作用、生态水文过程等多个领域.评述了高寒流域同位素径流分割方法原理及其应用研究进展,突出其对全球变化的指示意义.详细介绍了雪融水稳定同位素变化特征机理,以及加权平均值(VWA)、即时值(CMW)及径流校正(RunCE)等误差处理方法及其优缺点.最后,阐述了高寒流域同位素径流分割的应用前景,指出同位素径流分割可以与GIS软件等结合拓宽其研究的空间尺度、与水化学及人工试验等方法相结合拓展其研究手段,可以结合高寒流域独特地形研究山区产流机制.     

青藏高原冰雪资源的三维表面监测技术——以各拉丹东为例

本文选取青藏高原一座雪山作为研究试点,采用SPOT5卫星的HRS数据特有的立体像对采集功能,生成DEM,建立青藏高原冰雪三维监测模型,基于TIN计算雪被表面积,并结合以往研究成果估算冰雪规模,达到用尽量少的数据源对冰雪区开展调查,最大限度节省人力物力的目标。为有效管理我国冰雪资源、国家宏观水资源调控和可持续发展提供科学参考。     

近百年山西霜雪灾害时空特征

霜雪灾害对山西影响范围广、危害大, 通过对山西1901～2000年历史文献和现代气象 资料的搜集、整理和分析, 对该地区霜雪灾害的等级、阶段、周期及其成因进行研究, 旨在 探寻山西霜雪灾害发生的规律, 为该地区此类灾害的预测和防治提供科学依据。研究表明, 100年间轻度灾害占15.7%、中度占62.1%、重度占22.2%;灾害变化分为四个阶段, 1901 ～1948年为第一阶段, 1949～1964年为第二阶段, 1965～1974年为第三阶段, 1975～2000 年为第四阶段, 第一、三阶段以轻、中度灾害为主, 第二、四阶段以中、重度霜雪灾害为主; 小波分析表明, 灾害主要表现为2～3a、5～8a和25～35a的周期;山西的霜雪灾害可分为四 种成因类型;100年中发生了四次寒冷气候事件, 出现三个异常寒冷灾害年。     

中亚天山托木尔峰地区青冰滩72号冰川雪坑化学特征及其环境指示意义

基于2008年7月天山托木尔峰地区青冰滩72号冰川雪坑实测资料,探讨其冰川雪坑离子化学特征及环境指示意义。研究发现,Ca2+、Mg2+是青冰滩72号冰川雪坑中主要阳离子;雪坑中阳离子浓度顺序为:Ca2+>Mg2+>Na+>K+>NH4+,其中,Mg2+、K+和Ca2+主要反映长距离沙尘源物质传输情况;Cl-和Na+则一半以上来源于海盐;青冰滩72号冰川NO3-浓度高于天山地区含量平均值。     

Effects of land use intensity on stormwater runoff and its temporal occurrence in cold climates

The impacts of land use intensity, here defined as the degree of imperviousness, on stormwater volumes, runoff rates and their temporal occurrence were studied at three urban catchments in a cold region in southern Finland. The catchments with ‘High’ and ‘Intermediate’ land use intensity, located around the city centre, were characterized by 89% and 62% impervious surfaces, respectively. The ‘Low’ catchment was situated in a residential area of 19% imperviousness. During a 2‐year study period with divergent weather conditions, the generation of stormwater correlated positively with catchment imperviousness: The largest annual stormwater volumes and the highest runoff coefficients and number of stormwater runoff events occurred in the High catchment. Land use intensity also altered the seasonality of stormwater runoff: Most stormwater in the High catchment was generated during the warm period of the year, whereas the largest contribution to annual stormwater generation in the Low catchment took place during the cold period. In the two most urbanized catchments, spring snow melt occurred a few weeks earlier than in the Low catchment. The rate of stormwater runoff in the High and Intermediate catchments was higher in summer than during spring snow melt, and summer runoff rates in these more urbanized catchments were several times higher than in the Low catchment. Our study suggests that the effects of land use intensity on stormwater runoff are season dependent in cold climates and that cold seasons diminish the differences between land use intensities. Copyright © 2013 John Wiley & Sons, Ltd.     

Model complexity and data requirements in snow hydrology: seeking a balance in practical applications

We investigate the problem of balancing model complexity and input data requirements in snow hydrology. For this purpose, we analyze the performance of two models of different complexity in estimating variables of interest in snow hydrology applications. These are snow depth, bulk snow density, snow water equivalent and snowmelt run‐off. We quantify the differences between data and model prediction using 18 years of measurements from an experimental site in the French Alps (Col de Porte, 1325 m AMSL). The models involved in this comparison are a one‐layer temperature‐index model (HyS) and a multilayer model (Crocus). Results show that the expected loss in performance in the one‐layer temperature‐index model with respect to the multilayer model is low when considering snow depth, snow water equivalent and bulk snow density. As for run‐off, the comparison returns less clear indications for identification of a balance. In particular, differences between the models' prediction and data with an hourly resolution are higher when considering the Crocus model than the HyS model. However, Crocus is better at reproducing sub‐daily cycles in this variable. In terms of daily run‐off, the multilayer physically based model seems to be a better choice, while results in terms of cumulative run‐off are comparable. The better reproduction of daily and sub‐daily variability of run‐off suggests that use of the multilayer model may be preferable for this purpose. Variation in performance is discussed as a function of both the calibration solution chosen and the time of year. Copyright © 2016 John Wiley & Sons, Ltd.     

Uncertainty of snow water equivalent retrieved from AMSR‐E brightness temperature in northeast Asia

Accurate estimation of snow water equivalent (SWE) has been significantly recognized to improve management and analyses of water resource in specific regions. Although several studies have focused on developing SWE values based on remotely sensed brightness temperatures obtained by microwave sensor systems, it is known that there are still a number of uncertainties in SWE values retrieved from microwave radiometers. Therefore, further research for improving remotely sensed SWE values including global validation should be conducted in unexplored regions such as Northeast Asia. In this regard, we evaluated SWE through comparison of values produced by the Advanced Microwave Scanning Radiometer Earth Observing System (AMSR‐E) from December 2002 to February 2011 with in situ SWE values converted from snow‐depth observation data from four regions in the South Korea. The results from three areas showed similarities which indicated that the AMSR‐E SWE values were overestimated when compared with in situ SWE values, and their Mean Absolute Errors (MAE) by month were relatively small (1.1 to 6.5 mm). Contrariwise, the AMSR‐E SWE values of one area were significantly underestimated when compared with in situ SWE values and the MAE were much greater (4.9 to 35.2 mm). These results were closely related to AMSR‐E algorithm‐related error sources, which we analyzed with respect to topographic characteristics and snow properties. In particular, we found that snow density data used in the AMSR‐E SWE algorithm should be based on reliable in situ data as the current AMSR‐E SWE algorithm cannot reflect the spatio‐temporal variability of snow density values. Additionally, we derived better results considering saturation effect of AMSR‐E SWE. Despite the demise of AMSR‐E, this study's analysis is significant for providing a baseline for the new sensor and suggests parameters important for obtaining more reliable SWE. Copyright © 2013 John Wiley & Sons, Ltd.     

Analysis of seasonal snowmelt contribution using a distributed energy balance model for a river basin in the Altai Mountains of northwestern China

Snowmelt water is a vital freshwater resource in the Altai Mountains of northwestern China. Yet its seasonal hydrological cycle characteristics could change under a warming climate and more rapid spring snowmelt. Here, we simulated snowmelt runoff dynamics in the Kayiertesi River catchment, from 2000 to 2016, by using an improved hydrological distribution model that relied on high-resolution meteorological data acquired from the National Centers for Environmental Prediction (Fnl-NCEP) that were downscaled using the Weather Research Forecasting model. Its predictions were compared to observed runoff data, which confirmed the simulations' reliability. Our results show the model performed well, in general, given its daily validation Nash–Sutcliffe efficiency (NSE) of 0.62 (from 2013 to 2015) and a monthly NSE score of 0.68 (from 2000 to 2010) for the studied river basin of the Altai Mountains. In this river basin catchment, snowfall accounted for 64.1% of its precipitation and snow evaporation for 49.8% of its total evaporation, while snowmelt runoff constituted 29.3% of the annual runoff volume. Snowmelt's contribution to runoff in the Altai Mountains can extend into non-snow days because of the snowmelt water retained in soils. From 2000 to 2016, the snow-to-rain ratio decreased rapidly, however, the snowmelt contribution remained relatively stable in the study region. Our findings provide a sound basis for making snowmelt runoff predictions, which could be used prevent snowmelt-induced flooding, as well as a generalizable approach applicable to other remote, high-elevation locations where high-density, long-term observational data are currently lacking. How snowmelt contributes to water dynamics and resources in cold regions is garnering greater attention. Our proposed model is thus timely perhaps, enabling more comprehensive assessments of snowmelt contributions to hydrological processes in those alpine regions characterized by seasonal snow cover.     

Investigation of the snow‐cover dynamics in the Upper Euphrates Basin of Turkey using remotely sensed snow‐cover products and hydrometeorological data

The Euphrates and Tigris rivers serve as the most important water resources in the Middle East. Precipitation in this region falls mostly in the form of snow over the higher elevations of the Euphrates Basin and remains on the ground for nearly half of the year. This snow‐covered area (SCA) is a key element of the hydrological cycle, and monitoring the SCA is crucial for making accurate forecasts of snowmelt discharge, especially for energy production, flood control, irrigation, and reservoir‐operation optimization in the Upper Euphrates (Karasu) Basin. Remote sensing allows the detection of the spatio‐temporal patterns of snow cover across large areas in inaccessible terrain, such as the eastern part of Turkey, which is highly mountainous. In this study, a seasonal evaluation of the snow cover from 2000 to 2009 was performed using 8‐day snow‐cover products (MOD10C2) and the daily snow‐water equivalent (SWE) product. The values of SWE products were obtained using an assimilation process based on the Helsinki University of Technology model using equal area Special Sensor Microwave Imager (SSM/I) Earth‐gridded advanced microwave scanning radiometer—EOS daily brightness‐temperature values. In the Karasu Basin, the SCA percentage for the winter period is 80–90%. The relationship between the SCA and the runoff during the spring period is analysed for the period from 2004 to 2009. An inverse linear relationship between the normalized SCA and the normalized runoff values was obtained (r = 0·74). On the basis of the monthly mean temperature, total precipitation and snow depth observed at meteorological stations in the basin, the decrease in the peak discharges, and early occurrences of the peak discharges in 2008 and 2009 are due to the increase in the mean temperature and the decrease in the precipitation in April. Copyright © 2011 John Wiley & Sons, Ltd.