Future variation in mountainous discharge in arid northwestern China: A basin case study

To better understand the variation in mountainous discharge(MD) in the future, a basin case study was conducted in the upstream Taolai River Basin(UTRB) in arid northwestern China. The Blaney-Criddle(B-C) equation, Budyko framework, and water balance method were coupled for MD calculations. The outputs of 10 global climate models(GCMs) are synthesized to confirm the future changes in air temperature and precipitation under 3 selected Representative Concentration Pathway(RCP) scenarios. The climate elasticity(CE) method was used to determine the variation in MD, and the influence of climate factors on that was quantitatively analyzed. The results reveal that the coupling framework of the three methods is suitable for MD determination in the UTRB. The weight-based synthesis of the 10 GCM outputs shows overall increases in temperature(T) and precipitation(P) under the 3 scenarios during most of the time until 2099. The above climate change leads to an increase in MD. According to CE analysis, the positive effectiveness of precipitation is greater than the negative effectiveness of temperature on MD variation, and the increase in precipitation would induce more MD in the UTRB. Uncertainty analysis reveals that GCM outputs dominate in predicting precipitation, while the RCP scenarios influence temperature more. Overall, under the background of climate change, the risk of extreme floods during wet years might increase, and a water deficit will still occur during normal and dry years. The study provides a case example for better understanding MD responses to climate change in the upper reaches of inland river basins. Findings are helpful for reasonable water resource development and utilization in the middle and lower reaches of these basins in the future. As in the Taolai River Basin, considering the future water demand across the whole basin, the development of watersaving technologies and reasonable industrial structures is crucial for a sustainable future.     

昆仑山提孜那甫河流域雨雪分离的温度条件分析

气候变暖背景下高海拔山区融雪（冰）以及强降水引发的洪水愈加难以预测,通过山区雨雪分离可判定引发洪水的温度条件,从而为山洪准确预报提供简单而科学的参考依据。本研究以昆仑山提孜那甫河流域为例,基于流域内不同海拔气象站2012-2016年的降水以及温度数据,结合MOD10A2积雪数据,采用温度积分法和概率统计方法,利用研究期内的平均温度,确定出不同降水形态对应的温度条件,以达到雨雪分离的目的。研究结果表明,莫木克站最大温和积温分别达到20.91 ℃和51.82 ℃时,降水可判定为降雨,最大温和积温分别低于18.13 ℃,43.69 ℃时,降水可判定为降雪;库地站最大温和积温分别达到14.51 ℃,33.17 ℃时,降水可判定为降雨,最大温和积温分别低于13.57 ℃,31.68 ℃时,降水可判定为降雪;西合休站最大温和积温分别达到9.43 ℃,19.53 ℃时,降水可判定为降雨,最大温和积温分别低于8.22 ℃,19.4 ℃时,降水可判定为降雪。利用流域内气象站点附近乡镇的气象统计数据对温度条件及分离结果进行验证,在海拔2000 m以下、2000~3000 m以及3000 m以上不同海拔地区的准确率分别为92.86%、79.49%以及88.3%。本研究可为判别洪水类型和洪水预报提供科学参考。     

Implications of climate change on streamflow of a snow-fed river system of the Northwest Himalaya

Air temperature and snow cover variability are sensitive indicators of climate change. This study was undertaken to forecast and quantify the potential streamflow response to climate change in the Jhelum River basin. The implications of air temperature trends (+0.11°C/decade) reported for the entire north-west Himalaya for past century and the regional warming (+0.7°C/decade) trends of three observatories analyzed between last two decades were used for future projection of snow cover depletion and stream flow. The streamflow was simulated and validated for the year 2007-2008 using snowmelt runoff model (SRM) based on in-situ temperature and precipitation with remotely sensed snow cover area. The simulation was repeated using higher values of temperature and modified snow cover depletion curves according to the assumed future climate. Early snow cover depletion was observed in the basin in response to warmer climate. The results show that with the increase in air temperature, streamflow pattern of Jhelum will be severely affected. Significant redistribution of streamflow was observed in both the scenarios. Higher discharge was observed during spring-summer months due to early snowmelt contribution with water deficit during monsoon months. Discharge increased by 5% 40% during the months of March to May in 2030 and 2050. The magnitude of impact of air temperature is higher in the scenario-2 based on regional warming. The inferences pertaining to change in future streamflow pattern can facilitate long term decisions and planning concerning hydro-power potential, waterresource management and flood hazard mapping in the region.     

土地利用和气候变化对海河流域蒸散发时空变化的影响

蒸散发（ET）是水文能量循环和气候系统的关键环节,研究ET的时空变化特征及其响应土地利用和气候变化的驱动机制对于理清流域水资源和气候变化的关系具有重要的意义。本文基于MOD16/ET数据集定量分析了海河流域2000-2014年ET的时空变化特征,并结合时序气温降水数据和土地利用数据,采用相关分析方法定量探索了ET与气候因子的驱动力关系。结果表明：① 海河流域2000-2014年ET表现为较为显著的空间分布格局,呈现出北部和南部高、西北部和中东部低的分布特性。不同土地利用类型的多年ET呈林地>草地>耕地>其他类型的特征;② 2000-2014年海河流域年均ET波动范围为371.96~441.29 mm/a,多年ET的均值为398.69 mm/a,平均相对变化率为-0.41%,整体呈下降趋势;③ 多年月ET与气温和降水均呈单峰型周期性变化趋势,年内月ET呈单峰变化趋势;④ 春秋两季的ET与降水和气温的相关性明显高于其他季节,ET与气温和降水的平均相关系数是-0.17和0.37,表明降水对于ET的响应程度强于气温;⑤ 驱动分区结果表明海河流域ET受气候因子驱动的主要类型是降水驱动型和降水、气温共同驱动型;⑥ 海河流域耕地ET变化气候因子驱动模式主要是降水、气温共同驱动型;林地、草地的驱动模式主要气温驱动型和降水驱动型,其他土地利用类型的驱动模式主要是受其他因素驱动。该研究将对海河流域水资源开发管理和区域气候调节起到科学指导作用。     

2002-2012年青藏高原积雪物候变化及其对气候的响应

积雪是地表最活跃的自然要素之一,其动态变化对气候、环境以及人类生活都产生了重要影响。本文利用MODIS积雪产品和IMS雪冰产品,首先通过Terra、Aqua双星合成和临近日合成去除MODIS积雪产品中的部分云像元,再与IMS融合,获取了青藏高原2002-2012年逐日无云积雪覆盖产品,并逐像元计算每个水文年的积雪覆盖日数（SCD）、积雪开始期（SCS）和积雪结束期（SCE）,分析了不同生态分区积雪的时空变化特征,以及积雪开始期和结束期与温度、降水的关系。结果表明：青藏高原积雪分布存在明显的空间差异,南部喜马拉雅山脉和念青唐古拉山地区以及西部帕米尔高原和喀喇昆仑山脉为SCD的2个高值区,年均积雪日数在200 d以上。18.1%的区域SCS表现出明显的提前趋势,主要集中在青藏高原中东部;羌塘高原南部、念青唐古拉山西段以及川西地区有显著推迟趋势,占高原面积的8.5%。23.2%的区域SCE显著推迟,主要集中在果洛那曲高寒区、昆仑山区和念青唐古拉山地区;而仅有6.9%的区域表现出提前趋势,主要分布在高原西南部。总体上,不同生态单元内积雪开始与结束期受温度、降水的影响差异很大,表现出不同的空间格局与演变趋势。     

Recent snow cover variation in the Upper Indus Basin of Gilgit Baltistan,Hindukush Karakoram Himalaya

Mountainous basins like the Upper Indus Basin(UIB) of Gilgit Baltistan(GB) are dependent on seasonal snowmelt and glacier melt. Monitoring of the snow-covered area(SCA) is not only vital for the overall hydrology of the Indus basin but also important to the sustainable agriculture and hydropower system. The snow-covered area in the UIB of GB was investigated for changes over the last 18 years using the Moderate Resolution Imaging Spectroradiometer(MODIS) snow product. The study area was divided into five elevation zones ranging from 877-8564 meters above sea level(m ASL). In contrast to the global cryosphere related studies, SCA in the UIB is slightly increasing. Elevation based SCA analysis also indicated that SCA is slightly increasing in each elevation zone. However, a significant amount of snow is concentrated in areas above 5000 m ASL. Due to the strong correlation between SCA and precipitation, the precipitation data also follow a similar trend. Analysis of the climatic data suggests a statistically significant increase in total monthly precipitation and relative humidity, a slight decrease in mean monthly temperature and a significant upward tendency in monthly solar irradiance data. All these trends in combination with the increasing trend in global precipitation, winter westerly disturbances and orographic precipitation are the important factors behind the slightly increasing SCA in the study area. Our results though constrained by short observation period mainly contribute to the understanding of advancing snow cover and glaciers in Hindukush Karakoram.     

An artificial neural network-based snow cover predictive modeling in the higher Himalayas

With trends indicating increase in temperature and decrease in winter precipitation, a significant negative trend in snow-covered areas has been identified in the last decade in the Himalayas. This requires a quantitative analysis of the snow cover in the higher Himalayas. In this study, a nonlinear autoregressive exogenous model, an artificial neural network （ANN）, was deployed to predict the snow cover in the Kaligandaki river basin for the next 30 years. Observed climatic data, and snow covered area was used to train and test the model that captures the gross features of snow under the current climate scenario. The range of the likely effects of climate change on seasonal snow was assessed in the Himalayas using downscaled temperature and precipitation change projection from - HadCM3, a global circulation model to project future climate scenario, under the AIB emission scenario, which describes a future world of very rapid economic growth with balance use between fossil and non-fossil energy sources. The results show that there is a reduction of 9% to 46% of snow cover in different elevation zones during the considered time period, i.e., 2Oll to 2040. The 4700 m to 52oo m elevation zone is the most affected area and the area higher than 5200 m is the least affected. Overall, however, it is clear from the analysis that seasonal snow in the Kaligandaki basin is likely to be subject to substantialchanges due to the impact of climate change.     

Runoff responses to climate change in arid region of northwestern China during 1960–2010

Based on runoff, air temperature, and precipitation data from 1960 to 2010, the effects of climate change on water resources in the arid region of the northwestern China were investigated. The long-term trends of hydroclimatic variables were studied by using both Mann-Kendall test and distributed-free cumulative sum (CUSUM) chart test. Results indicate that the mean annual air temperature increases significantly from 1960 to 2010. The annual precipitation exhibits an increasing trend, especially in the south slope of the Tianshan Mountains and the North Uygur Autonomous Region of Xinjiang in the study period. Step changes occur in 1988 in the mean annual air temperature time series and in 1991 in the precipitation time series. The runoff in different basins shows different trends, i.e., significantly increasing in the Kaidu River, the Aksu River and the Shule River, and decreasing in the Shiyang River. Correlation analysis reveals that the runoff in the North Xinjiang (i.e., the Weigan River, the Heihe River, and the Shiyang River) has a strong positive relationship with rainfall, while that in the south slope of the Tianshan Mountains, the middle section of the north slope of the Tianshan Mountains and the Shule River has a strong positive relationship with air temperature. The trends of runoff have strong negative correlations with glacier coverage and the proportion of glacier water in runoff. From the late 1980s, the climate has become warm and wet in the arid region of the northwestern China. The change in runoff is interacted with air temperature, precipitation and glacier coverage. The results show that streamflow in the arid region of the northwestern China is sensitive to climate change, which can be used as a reference for regional water resource assessment and management.     

遥感及再分析降水产品在缺资料干旱内陆盆地的适用性评估

山区降水较集中,但降水测站多位于山谷或人口密集区,代表性差。遥感和再分析降水产品能提供时空分布连续的数据,不受地形条件限制。柴达木盆地中心属干旱荒漠区,水是制约该区开发的首要条件,其四周属高寒山区,降水相对较多,但降水监测十分薄弱。为获取该区相对精确的降水时空分布信息,本文评估了4套高分辨率降水产品（CMADS、TRMM、GPM和MSWEP）的适用性。首先基于地面站点数据评估它们在不同时空尺度上的精度,并分析它们在柴达木盆地的空间分布和年内分配特征。然后,以盆地东南隅的无测站山区香日德河流域为研究区,利用降水产品驱动SWAT模型来评估它们的分布式水文模拟适用性。结果表明：① MSWEP在年、月尺度上与站点降水的吻合程度最高（R ≥ 0.79,PBIAS = 0.5%）,其次是GPM和TRMM,CMADS精度最低（R ≥ 0.64,PBIAS = 5.8%）;② 从降水精度与站点高程的关系来看,降水产品在相对低海拔区容易高估站点降水,而在相对高海拔区常低估实际降水;③ 在香日德河流域,MSWEP（NSE = 0.64）在基准期（2009—2012年）的径流模拟表现明显好于其它降水产品（NSE = 0.36~0.59）,变化期（2013—2016年）表现最好的是CMADS（NSE = 0.75,其余产品NSE = 0.53~0.68）。本研究可为缺资料干旱山区获取精确的降水时空信息和后续水资源的科学管理与规划提供重要支撑。     

Projection of future streamflow of the Hunza River Basin,Karakoram Range (Pakistan) using HBV hydrological model

Hydrologiska Byrans Vattenbalansavdeling(HBV) Light model was used to evaluate the performance of the model in response to climate change in the snowy and glaciated catchment area of Hunza River Basin. The study aimed to understand the temporal variation of streamflow of Hunza River and its contribution to Indus River System(IRS). HBV model performed fairly well both during calibration(R2=0.87, Reff=0.85, PBIAS=-0.36) and validation(R2=0.86, Reff=0.83, PBIAS=-13.58) periods on daily time scale in the Hunza River Basin. Model performed better on monthly time scale with slightly underestimated low flows period during bothcalibration(R2=0.94, Reff=0.88, PBIAS=0.47) and validation(R2=0.92, Reff=0.85, PBIAS=15.83) periods. Simulated streamflow analysis from 1995-2010 unveiled that the average percentage contribution of snow, rain and glacier melt to the streamflow of Hunza River is about 16.5%, 19.4% and 64% respectively. In addition, the HBV-Light model performance was also evaluated for prediction of future streamflow in the Hunza River using future projected data of three General Circulation Model(GCMs) i.e. BCC-CSM1.1, CanESM2, and MIROCESM under RCP2.6, 4.5 and 8.5 and predictions were made over three time periods, 2010-2039, 2040-2069 and 2070-2099, using 1980-2010 as the control period. Overall projected climate results reveal that temperature and precipitation are the most sensitiveparameters to the streamflow of Hunza River. MIROC-ESM predicted the highest increase in the future streamflow of the Hunza River due to increase in temperature and precipitation under RCP4.5 and 8.5 scenarios from 2010-2099 while predicted slight increase in the streamflow under RCP2.6 during the start and end of the 21 th century. However, BCCCSM1.1 predicted decrease in the streamflow under RCP8.5 due to decrease in temperature and precipitation from 2010-2099. However, Can ESM2 predicted 22%-88% increase in the streamflow under RCP4.5 from 2010-2099. The results of this study could be useful for decision making and effective future strategic plans for water management and their sustainability in the region.     

基于GEE的黄河流域植被时空变化及其地形效应研究

黄河流域作为中国东部平原的生态屏障,研讨其植被覆盖的时空变化有助于生态环境治理。本文利用GEE平台,基于Landsat数据通过像元二分模型反演了1990—2020年黄河流域植被覆盖度（FVC）,并通过Theil-Sen Median趋势分析和 Mann-Kendall检验方法剖析FVC的时空变化趋势,挖掘出FVC趋势变化与海拔、坡度、坡向等地形因子之间的响应关系。结果表明：① 黄河流域FVC整体呈现西北低东南高的空间分布趋势,其中低等FVC占整个流域面积的45%,主要集中于西北部干旱半干旱地区;② 流域中部植被覆盖改善明显,占整个流域的57.07%,西北部和东南部退化程度相对较高;③ 植被覆盖受地形效应影响较为显著,在坡度大于40°及高程（-31~637 m）时高等级FVC占比较高,坡度8~18°及高程1852~2414 m范围内植被改善效果相对较好。结果可以为黄河流域生态环境保护及高质量发展提供科学支撑。     

Response of snow hydrological processes to a changing climate during 1961 to 2016 in the headwater of Irtysh River Basin,Chinese Altai Mountains

With changing climatic conditions and snow cover regime, regional hydrological cycle for a snowy basin will change and further available surface water resources will be redistributed. Assessing snow meltwater effect on runoff is the key to water safety, under climate warming and fast social-economic developing status. In this study, stable isotopic technology was utilized to analyze the snow meltwater effect on regional hydrological processes, and to declare the response of snow hydrology to climate change and snow cover regime, together with longterm meteorological and hydrological observations, in the headwater of Irtysh River, Chinese Altai Mountains during 1961-2015. The average δ~(18) O values of rainfall, snowfall, meltwater, groundwater and river water for 2014–2015 hydrological year were-10.9‰,-22.3‰,-21.7‰,-15.7‰ and-16.0‰, respectively.The results from stable isotopes, snow melting observation and remote sensing indicated that the meltwater effect on hydrological processes in Kayiertesi River Basin mainly occurred during snowmelt supplying period from April to June. The contribution of meltwater to runoff reached 58.1% during this period, but rainfall, meltwater and groundwater supplied 49.1%, 36.9% and 14.0% of water resource to annual runoff, respectively. With rising air temperature and increasing snowfall in cold season, the snow water equivalent(SWE) had an increasing trend but the snow cover duration declined by about one month including 13-day delay of the first day and 17-day advancement of the end day during 1961–2016. Increase in SWE provided more available water resource. However, variations in snow cover timing had resulted in redistribution of surface water resource, represented by an increase of discharge percentage in April and May, and a decline in Juneand July. This trend of snow hydrology will render a deficit of water resource in June and July when the water resource demand is high for agricultural irrigation and industrial manufacture.     

Glacier changes since the early 1960s,eastern Pamir,China

Glaciers in the eastern Pamir are important for water resources and the social and economic development of the region.In the last 50 years,these glaciers have shrunk and lost ice mass due to climate change.In order to understand recent glacier dynamics in the region,a new inventory was compiled from Landsat TM/ETM+ images acquired in2009,free of clouds and with minimal snow cover on the glacierized mountains.The first glacier inventory of the area was also updated by digitizing glacier outlines from topographical maps that had been modified and verified using aerial photographs.Total glacier area decreased by 10.8%±1.1%,mainly attributed to an increase in air temperature,although precipitation,glacier size and topographic features also combined to affect the general shrinkage of the glaciers.The 19.3–21.4 km~3 estimated glacier mass loss has contributed to an increase in river runoff and water resources.     

SNOW COVER MONITORING BY REMOTE SENSING AND SNOWMELT RUNOFF CALCULATION IN THE UPPER HUANGHE RIVER BASIN

The upper Huanghe(Yellow) River basin is situated in the northeast of the Qinghai-Xizang(Tibet)Plateau of China.The melt-water from the snow-cover is main water supply for the rivers in the region during springtime and other arid regions of the northwestern China, and the hydrological conditions of the rivers are directly controlled by the snowmelt water in spring .So snowmelt runoff forecast has importance for hydropower,flood prevention and water resources utilize-tion.The application of remote sensing and Geographic Information System(GIS) techniques in snow cover monitoring and snowmelt runoff calculation in the upper Huanghe River basin are introduced amply in this paper.The key parame-ter-snow cover area can be computed by satellite images from multi-platform,multi-templral and multi-spectral.A clus-ter of snow-cover data can be yielded by means of the classification filter method.Meanwhile GIS will provide relevant information for obtaining the parameters and also for zoning .According to the typical samples extracting snow covered moun-tained in detail also.The runoff snowmelt models based on the snow-cover data from NOAA images and observation data of runoff,precipitation and air temperature have been satisfactorily used for predicting the inflow to the Longyangxia Reser-voir,which is located at lower end of snow cover region and is one of the largest reservoirs on the upper Huanghe River, during late March to early June.The result shows that remote sensing techniques combined with the ground meteorological and hydrological observation is of great potential in snowmelt runoff forecasting for a large river basin.With the develop-ment of remote sensing technique and the progress of the interpretation method,the forecast accuracy of snowmelt runoff will be improved in the near future .Large scale extent and few stations are two objective reality situations in Chian,so they should be considered in simulation and forecast.Apart from dividing ,the derivation of snow cover area from satellite images would decide the results of calculating runoff.Field investigation for selection of the learning samples of different snow patterns is basis for the classification.     

Sensitivity of penman-monteith reference crop evapotranspiration in Tao’er River Basin of northeastern China

A non-dimensional relative sensitivity coefficient was employed to predict the responses of reference crop evapotranspiration （ET0） to perturbation of four climate variables in Tao＇er River Basin of the northeastern China. Mean monthly ET0 and yearly ET0 from 1961 to 2005 were estimated with the FAO-56 Penman-Monteith Equation. A 45-year historical dataset of average monthly maximum/minimum air temperature, mean air temperature, wind speed, sunshine hours and relative humidity from 15 meteorological stations was used in the analysis. Results show that： 1） Sensitivity coefficients of wind speed, air temperature and sunshine hours were positive except for those of air temperature of Arxan Meteorological Station, while those of relative humidity were all negative. Relative humidity was the most sensitive variable in general for the Tao＇er River Basin, followed by sunshine hours, wind speed and air temperature. 2） Similar to climate variable, monthly sensitivity coefficients exhibit large annual fluctuations. 3） Sensitivity coefficients for four climate variables all showed significant trends in seasonal/yearly series. Also, sensitivity coefficients of air temperature, sunshine hours and wind speed all showed significant trends in spring. 4） Among all sensitivity coefficients, the average yearly sensitivity coefficient of relative humidity was highest throughout the basin and showed largest spatial variability. Longitudinal distribution of sensitivity coefficients for air temperature, relative humidity and sunshine hours was also found, which was similar to the distribution of the three climate variables.     

Land use and land cover change within the Koshi River Basin of the central Himalayas since 1990

Land change is a cause and consequence of global environmental change.Land use and land cover have changed considerably due to increasing human activities and climate change,which has become the core issue of major international research projects.This study interprets land use and land cover status and the changes within the Koshi River Basin(KRB)using Landsat remote sensing(RS)image data,and employs logistic regression model to analyze the influence of natural and socioeconomic driving forces on major land cover changes.The results showed that the areas of built-up land,bare land and forest in KRB increased from 1990 to 2015,including the largest increases in forest and the highest growth rate in construction land.Areas of glacier,grassland,sparse vegetation,shrub land,cropland,and wetland all decreased over the study period.From the perspective of driving analysis,the role of human activities in land use and land cover change is significant than climate factors.Cropland expansion is the reclamation of cropland by farmers,mainly from early deforestation.However,labor force separation,geological disasters and drought are the main factors of cropland shrinkage.The increase of forest area in India and Nepal was attributed to the government’s forest protection policies,such as Nepal’s community forestry has achieved remarkable results.The expansion and contraction of grassland were both dominated by climatic factors.The probability of grassland expansion increases with temperature and precipitation,while the probability of grassland contraction decreases with temperature and precipitation.     

Vegetation cover variation in the Qilian Mountains and its response to climate change in 2000–2011

An understanding 0f variati0ns in vegetati0n c0ver in resp0nse t0 climate change is critical f0r predicting and managing future terrestrial ec0system dynamics. Because scientists anticipate that m0untain ec0systems will be m0re sensitive t0 future climate change c0mpared t0 0thers, 0ur 0bjectives were t0 investigate the impacts 0f climate change 0n variati0n in vegetati0n c0ver in the Qilian M0untains （QLM）, China, between 2000 and 2011. T0 acc0mplish this, we used linear regressi0n techniques 0n 250-m MODIS N0rmalized Difference Vegetati0n Index （NDVI） datasets and mete0r0l0gical rec0rds t0 determine spati0temp0ral variability in vegetati0n c0ver and climatic fact0rs （i.e. temperature and precipitati0n）. Our results sh0wed that temperatures and precipitati0n have increased in this regi0n during 0ur study peri0d. In additi0n, we f0und that gr0wing seas0n mean NDVI was mainly distributed in the vertical z0ne fr0m 2,700 m t0 3,600 m in elevati0n. In the study regi0n, we 0bserved significant p0sitive and negative trends in vegetati0n c0ver in 26.71% and 2.27% 0f the vegetated areas. C0rrelati0n analyses indicated that rising precipitati0n fr0m May t0 August was resp0nsible f0r increased vegetati0n c0ver in areas with p0sitive trends in gr0wing seas0n mean NDVI. H0wever, there was n0 similar significant c0rrelati0n between gr0wing seas0n mean NDVI and precipitati0n in regi0ns where vegetati0n c0ver declined thr0ugh0ut 0ur study peri0d. Using spatial statistics, we f0und that veeetati0n c0ver freauentlvdeclined in areas within the 2,500-3,100 m vertical z0ne, where it has steep sl0pe, and is 0n the sunny side 0f m0untains. Here, the p0sitive influences 0f increasing precipitati0n c0uld n0t 0ffset the drier c0nditi0ns that 0ccurred thr0ugh warming trends. In c0ntrast, in higher elevati0n z0nes （3,900-4,500 m） 0n the shaded side 0f the m0untains, rising temperatures and increasing precipitati0n impr0ved c0nditi0ns f0r vegetati0n gr0wth. Increased precipitati0n als0 facilitated vegetati0n gr0wth in areas experiencing warming trends at l0wer elevati0ns （2,000-2,400 m） and 0n l0wer sl0pes where water was m0re easily c0nserved. We suggest that spatial differences in variati0n in vegetati0n as the result 0f climate change depend 0n l0cal m0isture and thermal c0nditi0ns, which are mainly c0ntr0lled by t0p0graphy （e.g. elevati0n, aspect, and sl0pe）, and 0ther fact0rs, such as l0cal hydr0l0gy.     

Spatial distribution of snow depth based on geographically weighted regression kriging in the Bayanbulak Basin of the Tianshan Mountains,China

Snow depth is a general input variable in many models of agriculture,hydrology,climate and ecology.This study makes use of observational data of snow depth and explanatory variables to compare the accuracy and effect of geographically weighted regression kriging(GWRK)and regression kriging(RK)in a spatial interpolation of regional snow depth.The auxiliary variables are analyzed using correlation coefficients and the variance inflation factor(VIF).Three variables,Height,topographic ruggedness index(TRI),and land surface temperature(LST),are used as explanatory variables to establish a regression model for snow depth.The estimated spatial distribution of snow depth in the Bayanbulak Basin of the Tianshan Mountains in China with a spatial resolution of 1 km is obtained.The results indicate that 1)the result of GWRK's accuracy is slightly higher than that of RK(R~2=0.55 vs.R~2=0.50,RMSE(root mean square error)=0.102 m vs.RMSE=0.077 m);2)for the subareas,GWRK and RK exhibit similar estimation results of snow depth.Areas in the Bayanbulak Basin with a snow depth greater than 0.15m are mainly distributed in an elevation range of 2632.00–3269.00 m and the snow in this area comprises 45.00–46.00% of the total amount of snow in this basin.However,the GWRK resulted in more detailed information on snow depth distribution than the RK.The final conclusion is that GWRK is better suited for estimating regional snow depth distribution.     

基于GridMet模型的浙江省温湿指数空间分布及地形影响分析

温湿指数是气候舒适度评价模型之一,通过温度与湿度的组合反映人体与周围环境的热量交换,本文利用2003-2018年浙江省及其周边71个气象站点月平均气温、地面水汽压数据,以及MODIS水汽产品,基于GridMet模型模拟了浙江省各月温湿指数空间分布（100 m×100 m）,分析了浙江省温湿指数随地形因子（海拔、坡度、坡向）变化的特征;讨论了各地形因子对温湿指数空间分布的影响程度。结果表明：① 海拔、坡度、坡向3个地形因子中,1月温湿指数随坡向的变化最大,7月最小;② 同坡向上,坡度变化对1月温湿指数影响较大,而海拔变化则是对7月影响最大;③ 南坡1月温湿指数随海拔和坡度增加均略为增加,南坡其他月份及北坡各月均为随海拔和坡度增加温湿指数减小;④ 北坡相对于南坡而言,海拔和坡度对温湿指数的影响更为明显。浙江大部分山区由于地形影响,夏季较为“舒适”,适宜建立避暑消夏的旅游项目。     

光学与微波遥感的新疆积雪覆盖变化分析

利用2002-2013年冬季的MODIS光学遥感数据,以及AMSR-E、AMSR2与MWRI被动微波遥感数据,建立了新疆地区冬季每日积雪分布遥感反演模型。首先,将Terra与Aqua双星MODIS的积雪产品融合,初步去云并最大化积雪信息;然后,利用AMSR-E/AMSR2和MWRI被动微波数据进行每日雪盖提取;最后,利用被动微波遥感数据反演得到的每日雪盖结果对双星融合后依然有云的像元进行替换,得到每日积雪分布情况。据此模型提取了11年间冬季的积雪天数信息,结合气象台站观测数据,分析了新疆冬季积雪的年内和年际变化规律。结果表明,新疆地区积雪主要分布在北部新疆,积雪天数与地形关系密切,山区积雪天数较多,盆地及城市区积雪天数较少;积雪天数年内变化是从11月到次年1月随温度降低逐渐增加,从1月到3月积雪天数则逐渐减少。新疆地区积雪天数在这11年中存在一定的波动,积雪天数与该年的平均气温,以及月低于0℃的天数存在显著相关性,与降雪量关系不明显。新疆地区近年来积雪天数重心有向西向南移动的趋势,这可能与全球气候变暖导致多年积雪融化有关。