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1.
利用政府间气候变化专门委员会第四次评估报告的22个新一代全球气候模式基准期(1961～1990年)模拟结果,从时空尺度分别讨论了与观测过程的差异,评估了模式对长江流域气温和降水的模拟性能。结果表明22个气候模式对长江流域具有一定的模拟能力,地面气温的模拟值都偏低,部分降水的模拟值局部偏高。不同的气候模式的模拟能力差异显著,大部分模式对长江流域的模拟精度有待进一步改进,只有少数几个模式（降水有6个模式,气温有5个模式）的年变化趋势与实况基本一致。综合比较,UKMO_HadCM3和NCAR_PCM两个模式基本能再现长江流域降水和气温的年变化特征。长江流域降水和气温未来情景预估表明各个模式和情景结果虽然存在差异,但对未来90年气候变化的模拟趋势基本一致,将持续增温、降水出现区域性增加,并着重讨论了UKMO_HadCM3模式在2020s（2010～2039年）、2050s（2040～2069年）和2080s（2070～2099年）3个时段的降水和气温时空变化特征,研究结果表明3个时段气温和降水在不同情景下都是逐渐增加的,A2情景下未来降水增幅最显著,B1情景增幅最小。 相似文献
2.
为评估IPCC第四次评估报告中的15个全球气候模式对碧流河水库流域气温和降水的模拟效果,通过LARS-WG降尺度方法,选取了HADCM3等3种气候模式,分析其在A2、A1B和B1三种排放情景下未来期(2011~2040年)碧流河水库流域气温和降水的变化,进而结合ABCD月尺度水文模型,预估未来气候变化下碧流河水库流域的径流变化特征,为流域水资源规划和管理提供依据。结果表明:CNCM3、HADCM3和IPCM4三个模式对碧流河水库流域模拟效果较好;与基准期相比,未来期多年平均降水变幅为-6.4%~3.7%,多年平均温度升高0.8℃~1.2℃,实际蒸发增幅为2.4%~4.4%;多年平均年径流量变化范围为4.8~6.2(108m3),三种排放情景下各模式平均径流量均呈减少趋势,较基准期减幅为-4.7%~-27.1%,未来水资源利用将会面临更大挑战。 相似文献
3.
人类活动和气候变化严重改变了黄河水文情势和生态径流,分析未来气候变化对河流生态的影响对流域水资源管理和长期规划意义重大。本文对第六次国际耦合模式比较计划（CMIP6）的13个全球气候模式数据进行偏差订正,驱动水文模型进行径流模拟,应用流量历时曲线方法分析SSP1-2.6、SSP2-4.5、SSP5-8.5情景下2026年至21世纪末年、季节尺度的花园口生态径流变化。结果表明:订正能明显降低降水、气温模拟偏差;人类活动严重影响了1986-2010年花园口生态径流;2026-2100年年均气温和年降水量增加趋势显著,低排放情景增速慢,高排放情景增速快;气候变化可在一定程度上缓解水库调控、水土保持等人类活动对生态径流的负面影响,SSP5-8.5情景缓解程度最高,冬季缓解程度最高,夏、秋季最低。 相似文献
4.
西部高寒河源区因冰川积雪冻土等特殊的地理环境,其径流过程的模拟与预测一直是水文学研究的难点和热点问题之一,全球气候变暖为这一地区的水文模拟提出了新的挑战。以雅鲁藏布江拉孜以上流域为研究区域,基于可考虑冰川积雪融水的SWAT分布式水文模型对拉孜站径流过程进行模拟,评估SWAT模型在高寒河源区的适用性。基于未来气候变化情景,统计分析了未来研究区降水、气温的变化趋势,预估了气候变化对区域径流过程的影响。结果表明:SWAT模型在拉孜以上流域径流过程模拟中具有较好的适用性,模型在率定期和验证期月尺度NS系数分别达到了0.78和0.84;未来研究区降水、气温均呈现出增加趋势,且随着排放情景的上升,气温、降水增加幅度有变大趋势;未来研究区不同时段径流量也呈现出不同的增加趋势,在2020～2049年的RCP2.6、RCP4.5和RCP8.5情景下,相较于基准期径流分别增加了约11.8%、14.0%、16.5%,为下游水资源可持续开发利用带来了更大的挑战。 相似文献
5.
基于CMIP6气候模式的新疆积雪深度时空格局研究 总被引：1，自引：0，他引：1
积雪深度的变化对地表水热平衡起着至关重要的作用。选用了国际耦合模式比较计划第六阶段（CMIP6）中目前情景比较齐全的五个全球气候模式,通过对比新疆地区1979—2014年积雪深度长时间序列数据集,评估了气候模式在新疆地区模拟积雪深度的模拟能力,接着预估了未来不同SSPs-RCPs情景下新疆地区在2021—2040年（近期）、2041—2060年（中期）、2081—2100年（末期）相对于基准期（1995—2014年）的积雪深度变化。气温和降水对积雪深度变化有着重要的影响,因此还分析了新疆地区到21世纪末期气温和降水的变化趋势。结果表明：订正后的气候模式模拟的积雪深度数据与观测数据的相关系数均达到0.8以上,其中1月至3月与观测数据的结果更为吻合。气候模式基本上能够反映积雪深度年内变化的基本特征,气候模式模拟的积雪深度空间分布和观测数据具有相似的特征。气温和降水在未来不同情景下均会波动上升,其中气温的增幅相对比较明显,达0.43 ℃·（10a）-1,而降水的增幅为0.63 mm·（10a）-1,新疆未来的气候总体上呈现出变暖变湿的趋势。新疆地区的平均积雪深度在未来不同时期相对基准期均呈增加的趋势。SSP1-1.9情景下,21世纪近期、中期和末期北部大部分地区的积雪深度将会有所增加;SSP1-2.6情景下,北部阿尔泰山地区的积雪深度在21世纪近期有所减小,但中期和末期将会有所增加;SSP2-4.5情景下,21世纪不同时期东部地区的积雪深度将会有所增加,北部和中部大部分地区在不同时期积雪深度将会变小;SSP3-7.0情景下,21世纪不同时期北部和西南地区的积雪深度将会普遍变小,东部地区的积雪深度将普遍增加;SSP4-3.4和SSP4-6.0情景下,21世纪不同时期西南昆仑山地区的积雪深度将会普遍变小,东部地区的积雪深度将普遍增加;SSP5-8.5情景下,北部阿尔泰山地区和东部地区的积雪深度将普遍增加。 相似文献
6.
CMIP5多模式集合对南亚印度河流域气候变化的模拟与预估 总被引：1，自引：0，他引：1
利用印度河流域CRU、APHRODITE和CMIP5多模式逐月气温、降水格点数据集, 评估了CMIP5模式集合对印度河流域气候变化的模拟能力; 对多模式集合数据进行了偏差订正, 并对流域2046-2065年和2081-2100年气候变化进行了预估. 结果表明: 气候模式对流域年平均气温时间变化和空间分布特征有着较强的模拟能力, 时间空间相关系数均达到了0.01的显著性水平, 尤其对夏季气温的模拟要优于其他季节; 模式对降水的季节性波动也有着较好的模拟能力. 偏差订正后的预估结果表明, RCP2.6、4.5、8.5情景下, 相对于基准期(1986-2005年), 21世纪中期(2046-2065年)和末期(2081-2100年)整个流域年平均气温都有一定上升, 且流域上游增幅较大; 除RCP4.5情景下21世纪中期流域有弱减少趋势外, 年降水量都将有一定增长. 未来夏季持续升温将引起源区冰川的进一步消融, 春季降水对于中高海拔地区水资源的贡献将减弱; 流域北部高海拔区域冬季降水的增加有助冰川累积和上游水资源的增加, 东部高海拔区域冬季降水的减少会减少上游水资源. 两时期夏季降水都有一定的增长, 洪涝的发生风险加大; 流域暖事件和强降水事件也将可能增多. 相似文献
7.
气候变化对地表水资源的影响 总被引：7，自引：0，他引：7
总结了气候变化对水文水资源影响方面的研究方法, 分析了气候变化条件下水文水资源变化的研究现状和存在问题.并以山西省和黄河源区为研究对象, 以分布式水文模型为工具、GCMs输出的气候情景为输入条件, 针对不同的下垫面特征建立不同的分布式水文模型, 分别采用气候情景趋势分析结果和直接利用GCMs输出结果两类方法确定气候变化的数据源, 对研究区域未来的地表径流过程和地表水资源可能的变化趋势进行了研究.从气候情景的预测结果来看, 未来50年山西省的气温和降水都呈增加趋势, 但由于各自对水资源带来的影响不同, 将使山西省水资源呈现先增加后减少的趋势; 且由于冬季气温和降水的增幅比夏季大, 使得未来山西省的水资源年内分布有略微平缓的趋势.对黄河源区而言, 虽然未来100年内的降水和气温都呈增加趋势, 但由于降水增长引起的地表水资源的增加不足以抵消气温升高带来的影响, 因此将导致径流量不断降低的总体趋势, 并使径流年内分布略趋平缓, 而年际分布将越来越不均匀, 旱涝威胁日趋严峻. 相似文献
8.
气候变化对黄河流域水资源系统影响研究进展 总被引：1，自引：0，他引：1
1 目前的研究现状气候变化对黄河流域水资源系统的影响研究 ,主要是通过研究气候变化引起的流域气温、降水、蒸发等变化来预测径流可能的增减趋势及对其流域供水影响。主要研究方法有 :①假定气候情景法。此法直接假定气候变化的某些情景组合 ,结合水文模型推算在这些情景下的径流变化 ,如假定未来降水变幅为 0 ,± 2 5 %,± 5 0 %,± 75 %和± 10 0 %;未来气温变幅为 0 ,± 1℃ ,± 2℃ ,两两组合成未来气候变化的 45种气候情景 ,先后结合黄河月水文模型和基于ＧＩＳ技术的黄河流域分布式水文模型 ,分析流域水资源对气候变化的敏感性 (王… 相似文献
9.
利用通用气候系统模式(Community Climate System Model,简称CCSM)全新世和21世纪气候模拟试验数据,对比分析了全新世暖期鼎盛期和RCP4.5(Representative Concentration Pathway 4.5,简称RCP4.5)未来变暖情景下东亚地区夏季地表气温和降水的空间分布特征,并探讨了两个暖期夏季气候变化的成因机制。结果表明:1)全新世东亚地区最暖的夏季出现在9 ka B.P.前后,这与地球轨道参数有关;2)RCP4.5温室气体排放情景下21世纪整个东亚地区的夏季平均地表气温均呈上升趋势,而在全新世暖期鼎盛期东亚地区的夏季地表气温呈现同心圆状分布;3)全新世暖期鼎盛期和未来变暖情景下东亚地区夏季降水的空间分布有明显差异,前者东亚地区的夏季降水呈现"南负北正"的偶极子分布形态,而后者呈三极子形势;前者东亚夏季降水的变化幅度明显强于后者;4)全新世暖期鼎盛期副高偏强,中国东部偏南气流较强;而在RCP4.5未来变暖情景下副高偏弱。 相似文献
10.
全球变暖下我国气候响应的研究对进一步预估我国未来气候变化相关风险及制定适应和减缓政策具有重要意义。利用第六次耦合模式比较计划中25个全球气候模式的模拟结果,评估比较了各种可靠性集合加权方案对中国区域气候的模拟性能,基于表现最好的可靠性集合平均方案预估了SSP2-4.5和SSP5-8.5情景下中国极端气候指数在全球增暖1.5和2.0℃下的未来变化。结果表明,改进的可靠性集合方案模拟中国气候指数表现最好,与观测的偏差最小。未来中国区域温度明显增加,极端温度的增幅强于平均温度,极端降水整体也增加,且SSP5-8.5情景下增幅略强于SSP2-4.5情景。SSP5-8.5情景下,中国区域平均温度、最高温和最低温在全球增暖1.5(2.0℃)下较1995—2014年分别增加了1.11、1.18和1.31℃(1.88、1.98和2.14℃),总降水和强降水分别增加了5.6%和14.4%(10.5%和25.7%)。中国北方和青藏高原部分区域为增温的大值区,中国西部为降水增加的大值区。额外0.5℃增暖对中国地区产生显著影响,几乎整个中国地区温度指数的增幅都将超过全球平均。极端降水也将进一步增加,SSP5-... 相似文献
11.
Understanding the impacts of climate change on water quality and stream flow is important for management of water resources and environment. Miyun Reservoir is the only surface drinking water source in Beijing, which is currently experiencing a serious water shortage. Therefore, it is vital to identify the impacts of climate change on water quality and quantity of the Miyun Reservoir watershed. Based on long-time-series data of meteorological observation, future climate change scenarios for this study area were predicted using global climate models (GCMs), the statistical downscaling model (SDSM), and the National Climate Centre/Gothenburg University—Weather Generator (NWG). Future trends of nonpoint source pollution load were estimated and the response of nonpoint pollution to climate change was determined using the Soil and Water Assessment Tool (SWAT) model. Results showed that the simulation results of SWAT model were reasonable in this study area. The comparative analysis of precipitation and air temperature simulated using the SDSM and NWG separately showed that both tools have similar results, but the former had a larger variability of simulation results than the latter. With respect to simulation variance, the NWG has certain advantages in the numerical simulation of precipitation, but the SDSM is superior in simulating precipitation and air temperature changes. The changes in future precipitation and air temperature under different climate scenarios occur basically in the same way, that is, an overall increase is estimated. Particularly, future precipitation will increase significantly as predicted. Due to the influence of climate change, discharge, total nitrogen (TN) and total phosphorus (TP) loads from the study area will increase over the next 30 years by model evaluation. Compared to average value of 1961?~?1990, discharge will experience the highest increase (15%), whereas TN and TP loads will experience a smaller increase with a greater range of annual fluctuations of 2021 ~ 2050. 相似文献
12.
大兴安岭区域未来气候变化趋势及其对湿地的影响 总被引：2，自引：1，他引：1
基于未来2种排放情景下的RCM-PRECIS输出的大兴安岭区域气温与降水量预测数据,采用Mann-Kendall(简称M-K)非参数检验法和线性倾向率法,分析大兴安岭区域2015-2050年气候变化趋势及其对湿地的影响.结果表明,在未来2种情景下,2015-2050年的年平均气温升高显著,A2情景的增温速率(0.54℃·(10a)-1)高于B2情景(0.41℃·(10a)-1),与东北地区增温速率(0.56℃·(10a)-1)一致,B2情景增温速率低于东北地区增温速率;大兴安岭区域自2032年气温开始出现增暖突变现象,增温幅度显著增大.2种情景下季节平均气温的增温速率大小依次为夏季、冬季、春季和秋季,A2情景夏、冬、春、秋季分别为0.59、0.56、0.56、0.52℃·(10a)-1,B2情景分别为0.48、0.47、0.42、0.37℃·(10a)-1;各季突变增温时间点和增温趋势显著时段存在差异.2种情景下2015-2050年的年降水量有微弱的减少趋势,M-K检测基本无显著变化;季节降水总体而言,大兴安岭区域未来36a降水量仍以夏季为主,占全年降水量的60%左右;春季和秋季次之,各占全年降水量的18%~19%.未来大兴安岭区域气候呈现暖干化趋势,其中21世纪20、40年代大兴安岭湿地受到气候暖干化的胁迫相应较强,未来气候暖干化趋势是大兴安岭湿地生态系统萎缩和退化的主要诱因之一,未来大兴安岭湿地生态系统仍将受到气候暖干化趋势的巨大威胁,面临萎缩和严重退化趋势. 相似文献
13.
气候变化对玛纳斯河的径流量影响预测模拟分析 总被引：1，自引：0，他引：1
山区积雪和冰川融水径流是内陆干旱区的重要水资源, 研究全球变暖情景下温度对融雪径流的影响具有重要意义. 以典型的内陆河玛纳斯流域上游为例, 利用基于度-日因子算法的SRM(Snowmelt Runoff Model)融雪径流模型, 根据当前变化趋势和年内分配模拟出20种假定来模拟未来气候情景(气温上升1 ℃、 2 ℃、 3 ℃、 4 ℃和降水变化率为0、 ±10%、 ±20%的随机组合情况)下的河道径流量, 从而计算出径流量的变化率, 分析了温度和降水变化对径流量的影响. 结果表明: 对于以雪冰融水为主要补给的玛纳斯河, 随着温度和降水的增加, 径流量也会增加, 并会使融雪径流提前. 假定降水量不发生大的变化, 温度增高1 ℃, 径流量增大13%~16%; 在气温一定时, 降雨量增加10%, 径流量增加2%左右, 说明气温和降水都对干旱区内陆河山区径流形成具有重要影响. 该研究对制定气候变化情景下的水资源适应对策具有重要指导意义. 相似文献
14.
Based on NEX-BCC_CGM1.1 global daily statistics downscaling climate data set, the latest release by American National Aeronautics and Space Administration (NASA), which has representative concentration path, by using linear fitting and empirical orthogonal function (EOF) analysis methods, the simulation capacity on precipitation and temperature in Qinling and its surrounding areas of this data sets was estimated and the possible changes of the precipitation, daily maximum and minimum temperature in the next stage under the two scenarios of Rcp4.5 and Rcp8.5 were analyzed. Results showed that: ①The inter-annual trend of average daily precipitation, maximum temperature, minimum temperature is simulated well by NEX-BCC_CGM1.1. The spatial distribution was in accordance with the observations. The deficiency is that the elements value and extreme frequency have systemic bias compared with the observations. ②Average daily precipitation will have increasing trend in the future in Qinling and its surrounding areas under the two scenarios of Rcp4.5 and Rcp8.5. For different level precipitation frequency, light rains will reduce and rainstorms will increase in the future. The spatial modes of precipitation in the future are shown as the variation of the uniform increase in the whole region (EOF1) and anti-phase change in northern and southern Qinling (EOF2). EOF1 will be positive phase in medium-term in the Mid-21st century, where there will be significantly more means precipitation. ③Under the two scenarios, temperature warming trend is obvious, daily maximum temperature increasing trend is greater than minimum temperature, and the amplitude of temperature increase under Rcp8.5 is higher than Rcp4.5. The frequency of daily maximum temperatures greater than 36 ℃ will increase and low temperature less than -15 ℃ will reduce in the future, at the same time, high temperature (low temperature) increase (decrease) rate is more pronounced under Rcp8.5. Average daily maximum and minimum temperatures are shown uniform warming in the whole region (EOF1) and anti-phase change in northern and southern Qinling under two scenarios, but the spatial distribution has great difference. 相似文献
15.
Simulating climate change impact on soil carbon sequestration in agro-ecosystem of mid-Himalayan landscape using CENTURY model 总被引：1，自引：0，他引：1
Soils play significant roles in global carbon cycle. The increase in atmospheric CO2 due to climate change may have a significant impact on both soil organic carbon storage and management practices to sequester organic carbon in agricultural areas. The aim of the study was to simulate climate change impact on soil carbon sequestration using CENTURY model. The statistical downscaling model (SDSM) was used to downscale the climate variables (temperature and rainfall) under two scenarios A2 and B2 for three periods: 2020 (2011–2040), 2050 (2041–2070) and 2080 (2071–2099). Downscaling was better in case of temperature than precipitation, which was evident from coefficient of correlation for temperature (r 2 = 0.91–0.99) and precipitation (r 2 = 0.71–0.80). Downscaling of climate data revealed that the temperature may increase for the years 2020, 2050 and 2080 periods, whereas precipitation may increase till 2020 and then it may reduce in 2050 and 2080 as compared to 2020 in the study area. For CENTURY model, the input parameters were obtained through soil sampling and interviewing the farmers as well, whereas the climatic variables (maximum temperature, minimum temperature and precipitation) were taken from the SDSM output. The historical data of soils were collected from the literature, and six agricultural sites were selected for estimating soil carbon sequestration. After soil sampling of the same sites, it was found that the organic carbon had increased two times than historical data might be due to the addition of high organic matter in the form of farm yard manure. Therefore, the model was calibrated, considering more organic carbon in the area, and was validated using random points in the study area. Determination coefficient (r 2 = 0.95) and RMSE (538 g c/m2) were computed to assess the accuracy of the model. The organic carbon was predicted from 2011 to 2099 and was compared with the 2011 predicted data. The study revealed that the amount of soil organic carbon in Bhaitan, Kanatal, Kotdwar, Malas, Pata and Thangdhar sites may reduce by 11.6, 15.8, 17.19, 13.54, 19.2 and 12.7%, respectively, for A2 scenario and by 9.62, 15.6, 15.72, 11.45, 16.96 and 13.36% for B2 scenario up to 2099. The study provides comprehensive possible future scenarios of soil carbon sequestration in the mid-Himalaya for scientists and policy makers. 相似文献
16.
Impact of climate change on waterlogging and salinity distributions in Huai Khamrian subwatershed, NE Thailand 总被引：1，自引：0，他引：1
Phayom Saraphirom Wanpen Wirojanagud Kriengsak Srisuk 《Environmental Earth Sciences》2013,70(2):887-900
Regional climate models project significant changes in temperature and rainfall over the Greater Mekong Subregion over the twenty-first century. The potential impacts of climate change on areas affected by waterlogging and shallow saline groundwater in Northeast Thailand was investigated using the variable density groundwater model SEAWAT supported with recharge estimates derived from the hydrologic model HELP3. The focal area is the 154 km2 Huai Kamrian subwatershed. Changes in groundwater salinity and waterlogging areas at the middle and end of this century were predicted using the calibrated model. These predictions used the dynamically downscaled PRECIS regional climate change scenarios generated by ECHAM4 GCM A2 and B2 scenarios. Recharge rates are predicted to increase as a result of the higher intensity of rainfall. Shallow watertable areas are projected to increase by approximately 23 % from existing conditions during the middle of the century and up to 25 % by the end of this century. Although the precise rate and timing of climate change impacts are uncertain, all of the scenarios clearly point towards an extension in the area of waterlogging and area affected by shallow saline groundwater areas. Given that areas affected by shallow saline watertables are predicted to expand for both climate change scenarios as well as for the base case, it is concluded that climate change will have a significant impact on the area affected by salinity and waterlogging areas for both climate change scenarios. Evaluation of management options that explore the adaptation to saline environments and to means to reduce salt affected areas are required. 相似文献
17.
选择长江中下游单季中稻为研究对象,结合45个气象站1961~2010年逐日气象资料,基于统计降尺度模型(SDSM),生成HadCM3气候模式A2和B2两种情景下各站点参考作物腾发量和降水数据。基于联合国粮食及农业组织(FAO)推荐的作物系数法,并考虑有效性降雨和不同地区深层渗漏量,分析历史和未来的水稻灌溉需水时空变化特征。结果表明:过去50年,除了太湖流域以外的长江中下游大部分区域的参考作物腾发量和水稻需水量都呈显著下降趋势,而显著下降的水稻灌溉需水量主要位于鄱阳湖流域;未来两种情景下,参考作物腾发量、水稻需水量和水稻灌溉需水量均值都呈下降趋势,但水稻灌溉需水量降幅最小;水稻需水量和水稻灌溉需水量在长江中下游地区的变化趋势具有明显的空间异质性,水稻需水量大幅减少的区域由太湖流域向汉江和洞庭湖流域扩展。未来水稻灌溉需水量减少的区域主要分布在太湖流域、汉江流域东部和洞庭湖流域北部,并随时间推移呈扩大趋势。 相似文献
18.
Climate change, particularly due to the changed precipitation trend, can have a severe impact on soil erosion. The effect is more pronounced on the higher slopes of the Himalayan region. The goal of this study was to estimate the impact of climate change on soil erosion in a watershed of the Himalayan region using RUSLE model. The GCM (general circulation model) derived emission scenarios (HadCM3 A2a and B2a SRES) were used for climate projection. The statistical downscaling model (SDSM) was used to downscale the precipitation for three future periods, 2011–2040, 2041–2070, and 2071–2099, at large scale. Rainfall erosivity (R) was calculated for future periods using the SDSM downscaled precipitation data. ASTER digital elevation model (DEM) and Indian Remote Sensing data – IRS LISS IV satellite data were used to generate the spatial input parameters required by RUSLE model. A digital soil-landscape map was prepared to generate spatially distributed soil erodibility (K) factor map of the watershed. Topographic factors, slope length (L) and steepness (S) were derived from DEM. Normalised difference vegetation index (NDVI) derived from the satellite data was used to represent spatial variation vegetation density and condition under various land use/land cover. This variation was used to represent spatial vegetation cover factor. Analysis revealed that the average annual soil loss may increase by 28.38, 25.64 and 20.33% in the 2020s, 2050s and 2080s, respectively under A2 scenario, while under B2 scenario, it may increase by 27.06, 25.31 and 23.38% in the 2020s, 2050s and 2080s, respectively, from the base period (1985–2013). The study provides a comprehensive understanding of the possible future scenario of soil erosion in the mid-Himalaya for scientists and policy makers. 相似文献
19.
全球变暖情景下黑河山区水循环要素变化研究 总被引：4，自引：0，他引：4
利用有关水文气象台站的观测资料,对近50年来黑河上游山区流域降水、气温与径流深等水循环要素的变化进行了分析,结果表明：该区域的平均气温变化总体上呈上升的趋势,且其升温幅度高于全球过去50年的升温幅度;降水与径流的变化均呈增加的趋势,但增幅不是十分显著,且径流增长的增幅要大于降水量,这意味着径流的增长并不完全依赖降水的增加,气温上升导致的冰川和高山积雪及地下冻土层融水增加也是影响黑河上游山区流域径流变化的重要原因。根据降水和气温未来的变化趋势,预计在未来50年中, 除非遭遇到特别极端的气候组合,黑河山区径流仍将维持过去50年来缓慢增加的趋势,但增幅非常有限,最大变幅基本在目前多年均值的±5%左右。 相似文献
20.
《地学前缘(英文版)》2017,8(5):941-949
There are serious concerns of rise in temperatures over snowy and glacierized Himalayan region that may eventually affect future river flows of Indus river system. It is therefore necessary to predict snow and glacier melt runoff to manage future water resource of Upper Indus Basin(UIB). The snowmelt runoff model(SRM) coupled with MODIS remote sensing data was employed in this study to predict daily discharges of Gilgit River in the Karakoram Range. The SRM was calibrated successfully and then simulation was made over four years i.e. 2007, 2008, 2009 and 2010 achieving coefficient of model efficiency of 0.96, 0.86, 0.9 and 0.94 respectively. The scenarios of precipitation and mean temperature developed from regional climate model PRECIS were used in SRM model to predict future flows of Gilgit River. The increase of 3 C in mean annual temperature by the end of 21 th century may result in increase of 35-40% in Gilgit River flows. The expected increase in the surface runoff from the snow and glacier melt demands better water conservation and management for irrigation and hydel-power generation in the Indus basin in future. 相似文献