Valuating service loss of snow cover in Irtysh River Basin

Snow cover provides essential resources and services for human well-being and socioeconomic development in arid areas. With the change in snow cover resulting from climate change that causes concerns about its consequences, there is a pressing need to analyze and understand its impact on the benefits that people has been enjoying from snow cover. These can be derived from the variation in economic value of snow services, that are demanded to meet socioeconomic activities. Based on the average decline mass of snow cover from 1979 to 2016 in Irtysh River Basin, we use the approach by applying economic evaluation to estimate the annual value loss of snow services. Considering the decreasing trend of snow cover mass at rates of 10.2 Mt per year (p < 0.05) or 0.3% per year, the annual service loss in Irtysh River Basin is currently worth up to CN 196 million. Within it, the service loss of climate regulation contributes the most, or about CN 84.7 million. The loss of freshwater service contributes only about 19%, implying that there would be a significant underestimation of service loss if only water supply would be considered. This may cause biased decision-making when we are facing the challenges of declining services as a result of climate change, impacting on the balancing of socioeconomic development and environment conservation for the sustainability over a long term.

Spatiotemporal variation of snow cover and its relationship with temperature and precipitation in the Yarlung Tsangpo-Brahmaputra River Basin

The snow cover over the Qinghai-Tibet Plateau(QTP)and its surrounding areas is very sensitive to climate changes.Due to the complexity of geographical environment in this large region,the response of snow cover to climate change should exhibit spatiotemporal differences.In this study,the spatiotemporal variations of snow cover from 2002-2015 in the Yarlung Tsangpo-Brahmaputra River Basin(YBRB)were analyzed using an optimized fractional snow cover(FSC)product derived from Moderate Resolution Imaging Spectroradiometer(MODIS).Additionally,the effects of temperature and precipitation on the variability of snow cover were also investigated.The results showed that:(1)The snow cover exhibited large spatial and temporal heterogeneity in the YBRB.High FSC was observed in the northeast of the basin and the south slope of Himalaya,while the lowest was concentrated in the broad valley of the upstream of YBRB.The FSC value reached its highest in winter and dropped to its lowest in summer,but the monthly change processes were different between upstream and downstream regions.(2)A slightly increasing tendency(3.76%/10 a)of snow cover was observed on basin-wide,but the changes varied through time and space.The FSC increased significantly in the source and midstream regions during winter to spring(10.5%-18.0%/10 a),while it changed slightly in summer over all parts of the basin(-0.4%-4.3%/10 a).(3)The study area generally became warm and wet,and the change trend of temperature was more significant than that of precipitation.Snow cover changes were weakly correlated with temperature in winter and precipitation in summer.But in spring and autumn,both precipitation and temperature were significantly related to snow cover change in most regions of the basin.(4)The dominant factor driving the changes of snow cover varied in seasons.The area dominated by temperature was slightly larger than that dominated by precipitation in spring,except that precipitation significantly dominated the snow cover changes in the source region;In summer and autumn,temperature contributed more to the snow cover change in most areas of the basin;However,in winter,precipitation played a leading role in the variations of snow cover.These findings help to understand the different performance of the snow cover in the QTP and its surrounding areas under future climate change.

Snowline and Snow Cover Monitoring at High Spatial Resolution in a Mountainous River Basin Based on a Timelapse Camera at a Daily Scale

Snowline change and snow cover distribution patterns are still poorly understood in steep alpine basins of the Qilian Mountainous region because fast changes in snow cover cannot be observed by current sensing methods due to their short time scale. To address this issue of daily snowline and snow cover observations, a ground- based EOS 7D camera and four infrared digital hunting video cameras （LTL5210A） were installed around the Hulugou river basin （HRB） in the Qilian Mountains along northeastern margin of the Tibetan Plateau （38°15′54″N, 99°52′53″E） in September 2011. Pictures taken with the EOS 7D camera were georeferenced and the data from four LIL521oA cameras and snow depth sensors were used to assist snow cover estimation. The results showed that the time-lapse photography can be very useful and precise for monitoring snowline and snow cover in mountainous regions. The snowline and snow cover evolution at this basin can be precisely captured at daily scale. In HRB snow cover is mainly established after October, and the maximum snow cover appeared during February and March. The consistent rise of the snowline and decrease in snow cover appeared after middle part of March. This melt process is strongly associated with air temperature increase.

Monitoring and analysis of snow cover change in an alpine mountainous area in the Tianshan Mountains,China

Estimating the snow cover change in alpine mountainous areas(in which meteorological stations are typically lacking)is crucial for managing local water resources and constitutes the first step in evaluating the contribution of snowmelt to runoff and the water cycle.In this paper,taking the Jingou River Basin on the northern slope of the Tianshan Mountains,China as an example,we combined a new moderate-resolution imaging spectroradiometer(MODIS)snow cover extent product over China spanning from 2000 to 2020 with digital elevation model(DEM)data to study the change in snow cover and the hydrological response of runoff to snow cover change in the Jingou River Basin under the background of climate change through trend analysis,sensitivity analysis and other methods.The results indicate that from 2000 to 2020,the annual average temperature and annual precipitation in the study area increased and snow cover fraction(SCF)showed obvious signs of periodicity.Furthermore,there were significant regional differences in the spatial distribution of snow cover days(SCDs),which were numerous in the south of the basin and sparse in the central of the basin.Factors affecting the change in snow cover mainly included temperature,precipitation,elevation,slope and aspect.Compared to precipitation,temperature had a greater impact on SCF.The annual variation in SCF was limited above the elevation of 4200 m,but it fluctuated greatly below the elevation of 4200 m.These results can be used to establish prediction models of snowmelt and runoff for alpine mountainous areas with limited hydrological data,which can provide a scientific basis for the management and protection of water resources in alpine mountainous areas.

Uncertainties of snow cover extraction caused by the nature of topography and underlying surface

Manas River,the largest inland river to the north of the Tianshan Mountains,provides important water resources for human production and living.The seasonal snow cover and snowmelt play essential roles in the regulation of spring runoff in the Manas River Basin（MRB）.Snow cover is one of the most significant input parameters for obtaining accurate simulations and predictions of spring runoff.Therefore,it is especially important to extract snow-covered area correctly in the MRB.In this study,we qualitatively and quantitatively analyzed the uncertainties of snow cover extraction caused by the terrain factors and land cover types using TM and DEM data,along with the Per（the ratio of the difference between snow-covered area extracted by the Normalized Difference Snow Index（NDSI） method and visual interpretation method to the actual snow-covered area） and roughness.The results indicated that the difference of snow-covered area extracted by the two methods was primarily reflected in the snow boundary and shadowy areas.The value of Per varied significantly in different elevation zones.That is,the value generally presented a normal distribution with the increase of elevation.The peak value of Per occurred in the elevation zone of 3,700–4,200 m.Aspects caused the uncertainties of snow cover extraction with the order of sunny slope〉semi-shady and semi-sunny slope〉shady slope,due to the differences in solar radiation received by each aspect.Regarding the influences of various land cover types on snow cover extraction in the study area,bare rock was more influential on snow cover extraction than grassland.Moreover,shrub had the weakest impact on snow cover extraction.

近20 a塔里木河流域山区NDSI对气候变化的响应

NDSI(归一化差异积雪指数)是一种评估地表积雪覆盖程度的指数,对研究山区积雪变化有重要作用。本研究基于2001—2022年遥感数据和再分析数据,采用趋势分析法、多元线性回归法等,分析了近20 a来塔里木河流域山区NDSI时空变化及其归因。结果表明:塔里木河流域山区2001—2022年NDSI均呈下降趋势,具有显著的空间异质性。北部和西部山区,NDSI值的季节变化相同,NDSI平均值从高到低为:冬季>春季>秋季>夏季,而南部山区的NDSI平均值夏季高于秋季。塔里木河流域山区年均实际蒸散发均呈上升趋势。北部山区的降水呈略微下降的趋势,而西部和南部山区表现为上升趋势。所有山区的饱和水汽压差均呈上升趋势。下行地表太阳辐射呈下降趋势。北部和西部山区的最低气温呈上升趋势,南部山区略呈下降趋势,而所有区域最高气温均呈上升趋势。众多变量中,气温和饱和水汽压对NDSI的影响较大。本研究可为政策决策提供科学依据。

基于积雪数据的HBV模型改进及应用

大渡河流域内站点分布较少,历史观测数据不足,给该地区的融雪径流预报带来困难。基于欧洲中期天气预报中心提供的最新一代高分辨率陆面再分析数据集ERA5-Land,将积雪覆盖率和积雪平均深度引入度日因子雪量计算公式中,对HBV模型的积融雪模块进行改进,以提升融雪径流计算的可靠性。以大渡河上游为研究对象,选取1961—2018年的水文气象资料对模型进行率定和验证,并以2019年为例进行试预报研究。结果表明,通过引入ERA5-Land再分析数据,以及对积融雪模块进行改进,发挥了其在模拟积融雪上的优势,有效提升了融雪径流预报精度,对大渡河流域具有适用性。研究成果可为稀缺资料地区融雪径流模拟预报提供经验。

额尔齐斯河源区森林对春季融雪过程的影响评估

春季积雪融水是额尔齐斯河河源区最重要的水资源.为探索森林对春季融雪过程的影响,于2014年融雪期在额尔齐斯河河源区的卡依尔特斯河流域,选择草地、林中空地和林下三种不同地貌条件,分别观测积雪消融过程.结果显示:积雪消融过程中,积雪深度和雪水当量的变化并不是同步的;积雪深度的减小是持续发生的,是新雪密实化作用的结果;而雪水当量仅在日均空气温度高于0℃时才出现快速的下降.森林具有显著调节空气温度的功能,三种类型观测点1.5 m处的日平均空气温度表现为草地>林下>林中空地,其中,消融期内草地的平均空气温度(-2.5℃)远高于林下(-5.4℃)和林中空地(-6.1℃);森林的存在显著减小了空气温度的日较差.草地、林中空地和林下积雪消融持续期分别为20 d、43 d和35 d,消融期平均积雪消融速率分别为2.1 mm·d-1、1.5 mm·d-1和1.2 mm·d-1,即:草地>林中空地>林下.另外,单棵树对积雪的消融速率有极其重要的影响:树冠外一定距离内积雪的消融速率约为树冠下积雪消融速率的2倍以上;但由于树冠超过70%的降雪截留效应,树冠正下方的积雪消融结束时间仍提前树冠外侧约10 d.积雪的消融由空气温度和辐射强度共同决定:当日平均空气温度<0℃时,辐射强度对积雪消融影响较大,消融过程可由空气温度和辐射强度共同描述;当温度>0℃时,单独的空气温度可直接反映消融速率的变化.研究还发现,该流域内积雪的消融主要发生在每天的14:00-19:00,该时段内积雪消融量约占全天消融总量的50%以上,这对流域内积雪洪水预报和水资源利用及管理具有重要的指导意义.

45a来塔里木河流域气温、降水变化及其对积雪面积的影响

对塔里木河流域19个台站45a（1958—2002年）的气温、降水序列进行非参数检验，查明其变化趋势及特征，在此基础上，对近20a（1982—2001年）流域的积雪面积（SCA，％）变化进行趋势与相关分析．结果表明：流域的气温和降水均在20世纪80年代中期发生了阶段式的跳跃增长，气温和降水增加的主要季节分别为冬季和夏季．流域总体的积雪面积呈缓慢增加态势，其中北区和西区增加较为稳定，而南区相对不稳定．在垂直方向上，海拔〈2500m的区域积雪面积表现缓慢增加，而海拔≥2500m的区域则减少．相比较，低海拔区域更易受降水影响，而高海拔区域更易受气温影响．海拔2500～5000m的高度带是对气候变化较为敏感的区域．20世纪90年代与80年代相比，降雪和融雪的速度都更快．积雪与冷季降水呈正相关，但与冷季气温没有明显的相关关系．

基于MODIS数据的新疆叶尔羌河流域山区积雪特征分析

科学监测新疆叶尔羌河流域山区积雪面积及其变化特征对该区域的气候研究、雪水资源开发利用、环境灾害预报和生态环境保护等方面有重要意义.利用2000-2012年近13 a的MOD10A2积雪产品提取研究区域内积雪,结合DEM数据分析研究区内积雪面积的动态变化特征.结果显示:新疆叶尔羌河流域山区的积雪面积的年际变化幅度较大,其中,2005年和2009年积雪面积较大,2007年则为典型少雪年;年内变化差异显著,总体上呈现"M"型的特点,12月和3月处于高位,2月和8月处于低谷.叶尔羌河流域山区积雪覆盖率随着海拔的上升逐渐增大,稳定积雪主要分布在海拔5 000 m以上的地区;不同坡向的积雪覆盖率差异比较明显,西北坡、东坡、东北坡的积雪覆盖率比北坡、东南坡、西坡、南坡的积雪覆盖率高,西北坡高达52.8%,南坡仅为20%.叶尔羌河流域山区的积雪面积与气温呈负相关,与降水量呈正相关,积雪面积变化对气温因素更为敏感.

基于ETM+的积雪提取方法研究——以新疆玛纳斯河流域为例

为了高精度地提取积雪信息,消除森林覆盖区以及结冰河流水体对于积雪信息提取的影响,以Landsat ETM+为数据源,分析了玛纳斯河流域积雪信息提取的归一化差值积雪指数阈值,并建立积雪信息提取方法.对研究区进行了积雪信息提取,并与国际数据服务平台所得的积雪信息提取结果进行了比较.结果表明:基于Landsat数据利用归一化差值积雪指数提取积雪信息时,其合理阈值应为0.37;通过总体精度以及Kappa相关系数在结冰水体区域以及森林覆盖区域的提取结果进行对比,认定所使用的提取方法更加准确可靠.

长江源区典型流域积雪年变化及其与气温、降水的关系

对长江源区冬克玛底河流域2005年1月-2006年9月积雪空间分布特征、雪盖变化进行了分析，探讨了2005年暖季（5～9月）积雪覆盖与同期气温和降水量之间的关系．结果表明：积雪主要分布在河谷两侧的山坡、山顶、冰川前沿和冰川上，宽广平坦的河谷积雪很少；在暖季，流域降水多、气温较高，积雪主要分布在冰川区．作为一种特殊的下垫面，沼泽化草甸和冻土丘对积雪分布也有较大的影响．从两年的积雪覆盖率变化来看，在降雪少而气温低的1～4月积雪覆盖率变化剧烈；5月份降雪增多，但由于气温也在逐步回升，使得积雪覆盖率还是变化剧烈；10～11月降雪较多而且气温较低使得积雪覆盖率保持在80％以上的覆盖水平；6～8月因气温和地温较高，尽管降水多以固态形式降落，但在地面保留的时间极短，故积雪覆盖面积较小．在暖季（5～9月）降水对积雪覆盖的影响微弱，而温度是流域积雪覆盖变化的主要影响因素．

乌鲁木齐河流域季节积雪的基本特征

乌鲁木齐河流域的季节积雪受气温、降水量、水汽来向、山坡朝向、海拔和下垫面性质所控制和影响,具有明显的空间变化规律。按积雪期的长短,可划分为瞬时积雪、不稳定积雪、稳定积雪和永久积雪。气温低、雪层薄、雪层内温度梯度大,积雪密度小,雪面蒸发强是其特征。

黑河上游不同流域融雪过程的SRM模拟

利用SRM模型对黑河上游三个水文站点控制区2000年的融雪过程进行了模拟,在此基础上探讨高山地区不同水文区域对SRM模型模拟精度的影响.模型以MODIS积雪产品和气象台站数据为输入,结合退水系数进行融雪过程模拟,重点研究不同水文站点控制区域下的模拟精度.结果表明:在气象观测数据相对丰富的莺落峡控制区,模拟的精度较高,拟合优度确定系数R^2=0.795,积差D_v=-2.346%;在气象观测资料稀缺的祁连站和扎马什克站控制区,其模拟精度较差,其中祁连站R^2=-0.233,D_v=-3.277%,扎马什克站R^2=0.517,D_v=-11.128%.此外,地形的复杂程度和植被覆盖类型也会对模型的模拟精度产生影响.

SRM融雪径流模型在黑河流域上游的模拟研究

以黑河流域上游作为典型干旱区流域,探讨了SRM(Snowmelt Runoff Model)融雪径流模型的可操作性.在论述模型结构、参数意义的基础上,重点研究以MODIS雪产品为基础的积雪面积衰减曲线的获取方法,细化了退水系数的获取,并分析了其中存在的问题.通过利用WinSRM1.10版本对黑河上游2004年融雪期进行径流量模拟,结果表明:SRM模型在以融雪水为主要补给的黑河流域上游有着较好的径流量模拟精度,拟合优度确定系数R2为0.020,体积差Dv为7.124%.在实际应用中应最大限度利用已有的气象水文资料,以更为准确地描述融雪径流过程.针对数据稀缺的问题,需要加强小流域的观测,改进SRM模型以更适用于以融雪为主的我国西北山区流域.

玛纳斯河流域积雪变化特征及其与气温、降水的关系

利用MODIS积雪资料以及同期气象资料,分析了2000—2009年玛纳斯河流域积雪面积年内、年际变化及其与同期气温和降水的关系,结果表明:玛纳斯河流域积雪面积在4个不同分带上随季节变化各不相同,其中,带1变化最剧烈,受气候影响最为显著;带2、带3积雪的增加和减少都比较平缓;带4受气候影响最小。从年际波动来看,带1积雪面积随季节变化更为明显,带4在四季变化中均较平稳。对整个流域积雪面积与气候资料的相关分析表明:冬季,流域积雪变化对降水更敏感;而春季,气温是影响流域积雪面积变化的更主要的因素。

新疆玛纳斯河流域卫星雪盖信息提取的影响因素分析

卫星雪盖信息的准确提取受到很多因素的影响,本文选用11幅玛纳斯河流域Landsat ETM+影像,应用归一化差值积雪指数NDSI区分积雪与其他地物,分析传感器增益、大气因素、地形效应对雪盖信息提取造成影响的原因,并定量计算各因素影响程度的大小。研究结果表明,成像过程传感器高低增益对卫星雪盖信息提取的影响非常大,大气因素的影响相对较小,NDSI对地形不具有适应性,尤其在阴影区进行积雪判读不适用。

1977-2013年玛河流域山区冰雪覆被消融态势分析

对1977年MSS,1990年、2000年和2013年TM影像采用监督分类最大似然法区分冰雪与其他地物,探测冰雪面积及储量变化趋势,结合梯度、坡度、坡向等分析其分布规律.结果表明：（1）时间上：1977-2013年玛河流域山区冰雪面积从3 125.63 km2减少到745.81 km2,总退缩面积为2 379.82 km2,占1977年冰雪总面积76.14％.其中1977-1990年,年均变化率为1.6％,1990-2000年为2.9％,近13a为2.0％,总体上呈＆quot;小 大小＆quot;趋势退缩;玛河流域山区冰雪储量减少明显,减少量为1 446.75 km3.（2）空间上：海拔≤2 700 m的梯度冰雪消减最快,速率达到25.55 km/a,其次是海拔2 700～3 600 m,消减速率达到23.44 km/a,最后是海拔3 600～5 242 m的消减速率,仅为17.11 km/a;坡向上,冰雪分布阴坡大于阳坡,北坡、东北、西北坡分布最多,东坡、西坡次之,南坡、东南坡、西南坡最少,但不同坡向分布的冰雪百分比没有明显变化;坡度上,冰雪主要分布在坡度0＆#176;～50＆#176;,所占比例超过95％,≥50＆#176;雪盖分布较少.（3）控制冰雪变化的主要两个因素是夏季均温和年降水量,其中夏季气温对冰川的消融量起决定作用,年降水则影响冰川的积累量,冰雪覆被消融态势随自然因素和人类活动影响进一步加剧.

乌鲁木齐河流域积雪状况及其对公路的影响

乌鲁木齐河流域的季节积雪分布状况受冷期内连续降水过程的降雪量和气温所控制。水汽来向、山坡朝向、海拔高度和下垫面性质是影响积雪的主要因素。一般有瞬时积雪,不稳定积雪,稳定积雪和永久积雪之分。季节积雪的分布界限,在秋末冬初随海拔高度的降低而逐渐下移,春末夏初则随海拔高度增加而逐渐上移。到7月下旬或8月初移至海拔4000—4200m的雪线附近。由于风的再搬运作用,使本来不厚的自然积雪在公路的局部地段形成影响车辆通行的雪阻现象。

寒冷地区流域水污染防治问题

我国寒冷地区河流冰封期最长可达180天,其间水体自净功能差,加之城镇污水处理水平低于全国平均水平,工业点源污染负荷沉重,流域水污染问题显得格外突出,水环境压力巨大。因此,有针对性地解决寒冷地区流域水环境问题已经成为协调资源供求、经济发展与环境保护的核心问题。通过分析寒冷地区流域水污染特点及成因,提出了建立流域水污染防治法制体系、提高地方排放标准和推广低温污水处理技术的对策。