玛纳斯河流域的径流与洪水特征分析

为掌握玛纳斯河流域的径流与洪水特性，更好地发挥玛纳斯河在工农业生产和防洪工作的重要作用，本文根据玛纳斯河上游肯斯瓦特水文站多年水文观测资料，对玛纳斯河的径流与洪水特征进行了阐述与分析。结果表明，冰川是玛纳斯河流域径流的主要补给源，影响该流域径流年际、年内变化的主要因素是降水和气温，其径流年内分配集中在6～8月，径流过程略滞后于气温和降水过程。     

玛纳斯河流域水文特征

本文从玛纳斯河流域所处的地理位置和自然特点出发，阐明了以夏季冰川积雪融水为主，降雨融雪混合补给型河流的水文特征。     

玛纳斯河流域绿洲区生态安全评价

探讨了玛纳斯河流域绿洲生态安全状况的问题,试图从根本上解决该流域存在的生态安全问题.根据生态安全评价因子的选取原则构建玛纳斯河流域绿洲生态安全评价指标体系.利用生态安全综合评价法对玛纳斯河流域绿洲进行生态安全评价,并用聚类分析法对评价结果进行等级划分.结论 认为:经济活动因子和荒漠化因子共同制约着玛纳斯河流域生态安全的发展程度;玛纳斯河流域绿洲生态安全状况可以划分为一级和二级水平表明该区域大部分地区的生态安全程度相仿;十户滩-安集海盐渍化防治区的盐渍化问题十分严重,应尽快实施有效的应对措施.本研究为玛纳斯河流域的管理工作提供理论基础,且对新疆的可持续发展具有重要意义.     

玛纳斯河流域信息技术的应用与实践

1流域概况玛纳斯河流域位于天山北麓中段,准噶尔盆地南缘,流域总面积为26500km2。本流域包括塔西河、玛纳斯河、宁家河、金沟河、大南沟河和巴音沟河等六条较大的内陆河流,由南向北最后流归玛纳斯湖。流域内最大河流为玛纳斯河,全长324km,多年平均径流量为13.11亿m3,属于冰川融     

堵河子流域划分及其NDVI特征分析

堵河流域是南水北调中线工程的重要水源区,对堵河流域的水文单元划分和植被覆盖特征分析,对识别流域生态环境具有重要的实际意义.文章基于SWAT分布式水文模型和ArcGIS软件,运用适度指数法和均值统计法,对堵河流域的边界提取、子流域划分及其植被盖度分布特征进行了分析.结果显示:①集水面积阈值是控制子流域提取的重要参数,通过适度指数法计算堵河流域水系提取的最佳集水面积阈值为10 000 hm~2.②堵河流域年均NDVI值约为0.636,为中高植被覆盖度,空间上表现出南岸比北岸高;中游最低,向上游和下游逐渐升高的分布特征;年均NDVI最高值在黄龙河流域,最低值在竹溪河流域,存在明显的空间异质性.③堵河流域NDVI值随海拔的上升先变快后减缓,原因是高海拔山区植被覆盖度高.④在2001—2016年间,堵河流域的12个子流域年均NDVI值表现出相似的波浪式上升趋势,体现了整个流域的植被覆盖度上升,生态环境转好.年内堵河流域各子流域的NDVI月均值变化趋势特征趋于一致,8月达到最高峰值,2月达到最低峰值.     

玛纳斯河下游绿洲土地利用变化对水资源利用的影响

为探究人类活动对干旱区玛纳斯河流域耗水规律的影响,选取玛纳斯河流域下游莫索湾绿洲为研究区域,以1990年、2000年和2007年的TM影像数据为基础,采用GIS空间分析技术计算了景观斑块的转移矩阵,分析了研究区下游土地利用的时空变化特征,并结合该流域历史水资源的利用状况分析了其土地利用变化与水资源分配之间的关系。结果表明,研究区内景观面积最大的是耕地,约占45.08%,其次为沙地和荒地,约占43.14%;各种景观在1990~2007年都发生了较大变化,其中草地的缩减最大,其次为林地,而增加最大的是荒地和沙地,其次为耕地。这表明玛纳斯河流域土地利用的变化致使其需水结构在向耗水的方向变化,因此,改善土地利用方式对提高玛纳斯河流域水资源的利用效率具有重要意义。     

玛纳斯河流域降水与径流变化及其人类活动的影响

玛纳斯河流域发源于北天山中段,消失于准噶尔盆地西缘,是天山北麓流量最大的内流河.河流贯穿于山地-绿洲-荒漠系统,地表过程复杂.其绿洲受人类活动影响较大.高山区的冰雪融水和玛纳斯河上游的降水是该流域的主要径流水源.文章根据玛纳斯河流域基本气象台站建站以来的月平均气温、降水和年平均气温、降水和流量的资料,使用概率统计时间序列方法分析了流域气温、降水和径流的年内、年际变化特点并对突变年代做了检测,就径流对气候变化的响应做进一步的探讨.结果表明：玛纳斯河流域升温趋势显著,50年温度序列Mann-Kendall方法突变检验,通过了α=0.05的置信检验,表明气温在1995年发生了由低到高的突变,气候变暖主要在冬季.降水1983年发生了由少到多的突变,降水增加主要在春季和夏季.进一步分析表明玛纳斯河流域径流变化与降水变化有密切的正相关性,与气温变化的关系较为复杂.     

洮儿河流域湿地变化对河流径流量影响研究

以洮儿河流域为研究区域,在分析了该流域湿地变化的基础上,探讨了湿地变化与流域径流量之间的关系,定量判别了湿地变化对流域径流量的影响.结果表明:1985—2010年,洮儿河流域沼泽湿地面积的消长对径流量变化具有驱动作用;流域湿地面积减少、水文调节功能下降,年均径流量不断减少,径流量年内变化显著;流域径流量突变发生在1995年,此后,湿地面积减少对径流量的影响逐渐增大,成为2000年以来流域径流量减少的主要因素.     

西辽河源头流域径流变化趋势及影响因素分析

利用1977—2008年老哈河流域与沙拉沐沦河流域水文数据,采用Mann-Kendall检验法、有序聚类分析和线性回归方法分析其降水量、径流量近32 a的年内和年际变化规律及其影响因素.结果表明:1977—2008年2个流域年降水量和径流量均呈现下降的趋势,径流量下降幅度明显高于降水量;沙拉沐沦河流域降水量下降趋势不明显,稳定的泉水补给使得径流量受降水量减少和土地利用/覆被变化影响较小;老哈河流域径流量减少幅度远远高于降水量,在雨季下游有断流现象,该流域1977—1998年降水量是径流量变化的主要影响因素,1999—2008年流域内土地利用/覆被变化和水库水坝修建、河道外取水等人类活动共同作用使得该流域径流量减少了70.3%.     

玛纳斯河流域土地利用及景观格局变化的分析

绿洲土地利用改变了内陆河流域的生态过程,影响着绿洲景观格局及其生态安全。在景观生态学理论及3S技术支持下,采用2000年、2005年和2010年遥感影像为基础数据,选取土地利用变化动态度、趋势度以及景观格局指数等指标,对玛纳斯河流域景观动态变化展开定量分析。结果显示,玛纳斯河流域景观格局变化总体上表现为耕地和建设用地的扩张趋于集中化,人工景观的规模化、连通性、优势度稳定增长,而自然景观表现为相反的生态弱化趋势;耕地和建设用地斑块的连通性增加,过渡带的开垦加大了未利用地的破碎化,水资源的高强度消耗以及人工渠道水库的建设降低了水域的连通性和优势度;玛纳斯河流域景观的破碎化程度和异质性增加,景观类型日渐丰富并伴随着斑块形态的简单化。由此可知,耕地、未利用地和草地是流域的优势景观,影响着整个流域景观格局的变化,因此耕地的高效利用、未利用地的有序开发和林草地的合理保护应得到高度重视。     

径流式梯级引水式电站防治冰，泥沙，洪水危害技术措施的探讨

1994－1998年红山咀电厂采取“抽水融冰技术”,“漏斗式全沙排沙技术”和扩建二级电站渠道枢纽泄洪工程等技术措施,在防治冰,沙,洪水危害方面取得了成功,改善了发电生产运行条件,生产技术有了很大进步,获得了显著的经济效益和社会效益。     

气侯转型对玛纳斯河流域径流的影响及其变化趋势

针对气候转型,根据近50年玛纳斯河上下游气象、水文资料,采用5年滑动平均、模比系数差积曲线、线性趋势等方法,分析了气候转型对玛纳斯河径流的影响。结果显示：玛纳斯河流域50年以来的气温呈上升趋势,平均气温增长率为0.38℃.10年-1,降水量也呈增长趋势;由于气温、降水增加趋势明显,导致1987年以后玛纳斯河径流呈增长趋势,洪水和洪灾发生的频次增加,这表明玛纳斯河流域气侯的变化已出现由暖干向暖湿转型的强劲信号,预计玛纳斯河的丰水期可能持续至2050年。     

The hydrologic cycle in deep-time climate problems

Hydrology refers to the whole panoply of effects the water molecule has on climate and on the land surface during its journey there and back again between ocean and atmosphere. On its way, it is cycled through vapour, cloud water, snow, sea ice and glacier ice, as well as acting as a catalyst for silicate-carbonate weathering reactions governing atmospheric carbon dioxide. Because carbon dioxide affects the hydrologic cycle through temperature, climate is a pas des deux between carbon dioxide and water, with important guest appearances by surface ice cover.     

A test of Snowmelt Runoff Model （SRM） for the Gongnaisi River basin in the western Tianshan Mountains, China

The Snowmelt Runoff Model (SRM) is one of a very few models in the world today that requires remote sensing derived snow cover as model input. Owing to its simple data requirements and use of remote sensing to provide snow cover information, SRM is ideal for use in data sparse regions, particularly in remote and inaccessible high mountain watersheds. In order to verify the applicability of SRM in an environment of continental climate, a test of SRM is performed for the Gongnaisi River basin in the western Tianshan Mountains, the results show that two SRM average goodness-of-fit statistics for simulations, Nash-Sutcliff coeffident (R2) and volume difference (Dv), are 0.87 and 0.90%,respectively. As compared with the application results over 80 basins in 25 different countries around the world, SRM performs well in the Gongnaisi River basin. The results also show that SRM can be a validated snowmelt runoff model capable of being applied in the western Tianshan Mountains.On the basis of snowmelt runoff simulation, together with a set of simplified hypothetical climate scenarios, SRM is also used to simulate the effects of climate change on snow cover and the consecutive snowmelt runoff. For a given hypothetical temperature increase of 4℃, the snow coverage and snowmelt season shift towards earlier dates, and the snowmelt runoff, as a result, is changed significantly at the same time. The simulation results show that the snow cover is sensitive to changes of climate, especially to the increase of temperature, the major effect of climate change will be a time shifting of snowmelt runoff to early spring months, resulting in a redistribution of seasonally runoff throughout the whole snowmelt season.     

Influence of vegetations and snow cover on sand-dust events in the west of China

THE CLIMATE SYSTEM IS HIGHLY SENSITIVE TO THE CHANGE OF LAND SURFACE FEATURE INDUCED BY NATURE OR HUMAN ACTIVITY. THE TEMPORAL-SPATIAL CHANGES OF LAND SURFACE TYPES ARE ABLE TO CAUSE AN ANISOTROPIC DISTRIBUTION OF PHYSICAL CHARACTER AT LAND SURFACE, LEADI…     

Vertical structure of recent Arctic warming

Near-surface warming in the Arctic has been almost twice as large as the global average over recent decades-a phenomenon that is known as the 'Arctic amplification'. The underlying causes of this temperature amplification remain uncertain. The reduction in snow and ice cover that has occurred over recent decades may have played a role. Climate model experiments indicate that when global temperature rises, Arctic snow and ice cover retreats, causing excessive polar warming. Reduction of the snow and ice cover causes albedo changes, and increased refreezing of sea ice during the cold season and decreases in sea-ice thickness both increase heat flux from the ocean to the atmosphere. Changes in oceanic and atmospheric circulation, as well as cloud cover, have also been proposed to cause Arctic temperature amplification. Here we examine the vertical structure of temperature change in the Arctic during the late twentieth century using reanalysis data. We find evidence for temperature amplification well above the surface. Snow and ice feedbacks cannot be the main cause of the warming aloft during the greater part of the year, because these feedbacks are expected to primarily affect temperatures in the lowermost part of the atmosphere, resulting in a pattern of warming that we only observe in spring. A significant proportion of the observed temperature amplification must therefore be explained by mechanisms that induce warming above the lowermost part of the atmosphere. We regress the Arctic temperature field on the atmospheric energy transport into the Arctic and find that, in the summer half-year, a significant proportion of the vertical structure of warming can be explained by changes in this variable. We conclude that changes in atmospheric heat transport may be an important cause of the recent Arctic temperature amplification.     

2003—2020年新疆北部积雪因子时空变化分析

积雪作为冰冻圈的活跃因子之一,对气候环境的敏感性使其能够快速反映出与气温、降水等气候因素的关系变化,并影响着全球水文变化。本文基于Google Earth Engine（GEE）云平台,对北疆地区2003年6月-2021年6月的MODIS逐日积雪数据进行去云处理,并基于像元计算了积雪覆盖比例（SCP）、积雪覆盖日数（SCD）、积雪开始时间（SOD）和积雪结束时间（SED）。实验结果如下：（1）基于GEE的去云处理方法使得积雪产品相对于气象站点数据的总精度达到91.47%,有利于提高对积雪因子的时空变化分析。（2）北疆地区SCD空间分布差异较大,SCD随海拔的升高而增加,SOD随海拔升高而提前,主要在11-12月出现;SED随海拔升高而推迟,主要在2-3月出现;夏季平均SCD最少,主要分布于天山中部以及阿尔泰山北部区域,约占3.35%,冬季平均SCD最为明显,大于60天的区域占46.3%;而SCP在1月达到最大,7、8月最小。（3）趋势变化上,SCD、SOD以及SED均无明显变化趋势,SCD整体西部呈弱上升趋势,占51.72%,东部呈弱下降趋势,占48.28%;北疆西部SOD呈提前趋势,东部SOD呈推迟趋势,SED整体呈提前趋势。（4）温度对SCD的影响大于降水量;春夏季,SCD与温度、降水量无明显相关性,仅准葛尔盆地东部春季平均SCD与温度呈强正相关;秋冬季,SCD与降水量、温度分别呈现较强的正负相关性。     

冰与混凝土坝坡间的冻结强度模拟试验

根据实际水库观测冰盖与护坡的冻结情况，在实验室内进行模拟水库冰盖与护坡局部断面的冻结试验．采用冰与混凝土板间的冻结，进行一次冻结、多次冻结、冰晶冻结、雪冰冻结等模式．分析出冰压力与冻结力的关系；在不同温度下测得各种冻结情况中的冻结强度，给出冻结强度随着温度变化的规律和数值．其结果为寒区平原水库坝坡抵抗冰推力破坏提供了设计参数．     

径流中长期预报的灰色预测方法

基于时间序列的扩维原理和灰色系统理论的关联分析，提出一种较适合于水文实测资料缺乏情况下的中长期预报方法，利用玛纳斯河水文的实测资料序列对该方法进行验证。     

Microbial community structure in major habitats above 6000 m on Mount Everest

Bacterial abundance in surface snow between 6600 and 8000 m a.s.l. on the northern slope of Mt. Ev- erest was investigated by flow cytometry. Bacterial diversity in serac ice at 6000 m a.s.l., glacier melt- water at 6350 m, and surface snow at 6600 m a.s.l. was examined by constructing a 16S rRNA gene clone library. Bacterial abundance in snow was higher than that in the Antarctic but similar to other mountain regions in the world. Bacterial abundance in surface snow increased with altitude but showed no correlation with chemical parameters. Bacteria in the cryosphere on Mt. Everest were closely related to those isolated from soil, aquatic environments, plants, animals, humans and other frozen environ- ments. Bacterial community structures in major habitats above 6000 m were variable. The Cyto- phaga-Flavobacterium-Bacteroides (CFB) group absolutely dominated in glacial meltwater, while β-Proteobacteria and the CFB group dominated in serac ice, and β-Proteobacteria and Actinobacteria dominated in surface snow. The remarkable differences among the habitats were most likely due to the bacterial post-deposition changes during acclimation processes.