托木尔型冰川融水对气候变化敏感性的模型分析

以度日因子模型为基础,建立了一个简单的分布式模型,评估不同气候条件下托木尔型冰川融水径流的变化。模型分别考虑了冰雪、表碛、冰崖等复杂冰川下垫面的产流过程,并利用线性水库原理对冰川汇流进行参数化。结果显示,模型能够较好地对冰川融水径流进行模拟。敏感性分析表明,平均气温的变化对于融水径流有重要影响:当平均气温升高1℃时,融水径流将增加22.5%;而当气温升高2℃时,径流的增加幅度将达到45.0%。相反,当气温降低1℃和2℃时,融水径流分别减小20.6%和37.6%。比较而言,降水的变化对冰川融水径流的影响较小。     

未来气候变化对黄河流域水文过程的影响

使用NASA/NCAR有限区域大气环流模型FvGCM结果驱动高分辨率区域气候模式RegCM3 (20 km),进行1961～1990年当代气候模拟(控制试验)和2071～2100年IPCC A2排放情景下未来气候模拟(A2情景模拟试验)。将RegCM3径流模拟结果同大尺度汇流模型LRM [分辨率0.25°(纬度)×0.25°(经度)]相连接,模拟预估未来气候变化对我国黄河流域水文过程的影响。结果表明:相对于当代气候,未来黄河流域呈现气温升高、降水增加(夏季7～8月降水减少)和蒸发增大的趋势,且空间分布极不均匀,造成河川径流在5～10月减少,加剧流域夏季的水资源短缺;未来气温升高使得融雪径流增加,可能导致更早和更大的春季径流,使径流过程发生季节性迁移,引起黄河流域水资源年内分配发生变化。     

博斯腾湖流域气候变化及其对径流的影响

利用博斯腾湖流域开都河、黄水沟和清水河的出山口水文站月径流量和气象站月平均数据，开展变化特征分析和径流变化对气候因子的响应研究。结果表明，博斯腾湖流域年际气候变化以气温上升为主，降水量增加趋势不显著；域内主要河流径流量持续上升。突变检验发现，三条入湖河流90年代之前径流量增加主要是域内降水量增加的结果，随后受气温上升导致冰雪消融加快也对径流量的增加有贡献。相关分析结果显示，博斯腾湖三条入湖河流年径流量变化主要受4月和7月降水因子影响。此外，开都河的径流变化还表现出对8月气温和降水的显著响应，同时开都河流域集水区冰川的面积和占比均大于黄水沟和清水河流域，这表明冰川融水补给对开都河径流的影响大于黄水沟和清水河。所建立的气候因子-径流量多元线性回归模型，能够很好的模拟开都河、黄水沟和清水河的径流变化过程，证明了博斯腾湖流域水文变化受气候因子的显著影响。     

南疆开都河流域夏季径流量的变化及其特征分析

利用RegCM3模式对开都河流域2000-2006年夏季气候进行模拟,结果表明:模式对于流域夏季月降水总量和月平均气温的空间分布有较好的模拟能力。结合站点海拔高度值、实测值以及模拟量分别对降水、气温进行修正,并由此计算流域的面雨量和平均温度;结果表明开都河流域夏季面雨量与开都河同期实测径流量有较好的一致性,R~2达到0.97。对开都河流域夏季平均气温、面雨量以及径流量的分析表明,降水是影响流域夏季径流量的主要影响因子;而气温对于径流呈现负贡献的原因可能由于对温度敏感的小冰川大大减少,致使径流量随着温度增加而增加的关系减弱。此外,气温升高导致流域蒸散量的提高,可能是气温呈现负贡献的又一原因。     

黄河上中游径流对气候变化的敏感性分析

利用月水文模型, 采取假定气候方案, 分析了黄河上中游径流对气候变化的敏感性。 结果表明, 径流对降水变化的响应敏感, 对气温变化的响应相对较弱, 如气温不变, 降水增加 10 %时, 径流量约增加 17%。 如降水不变, 气温升高 1 ℃, 则径流减少 5 %左右。 在区域上分布, 中游较上游对气候变化更为敏感。     

RCP情景下内蒙古黄河流域径流预估及其对水资源的影响

根据内蒙古黄河流域内72个国家气象站观测的1961—2005年和区域气候模式CCLM模拟的1961—2100年的气温和降水数据,采用BP人工神经网络模型,预估分析3种RCP情景下头道拐水文站2011—2100年流量变化,评估未来气候变化对流域水资源的可能影响。结果表明:①2011—2100年内蒙古黄河流域气温升高,降水变化不明显,年平均流量呈减少趋势,RCP2.6、RCP4.5和RCP8.5情景分别减少3.6%、2.7%和23.4%。②未来春季流量以增加为主;夏季在不同情景的变化趋势不一致;秋季在21世纪50年代前以增加为主,之后以减少为主;冬季则以减少为主。③未来流域可利用水资源呈减少趋势,尤其夏季水资源的供需矛盾加剧,以及径流季节分配发生变化,可能产生更大的春季径流。     

阿克苏河流域春季径流变化及气候成因分析

采用数理统计方法,分析了35年来阿克苏河流域春季径流的变化及其与冬、春季气温、降水等气候因子的响应关系.研究表明,流域内春季径流在增加,冬、春季均有增暖变湿的趋势,影响阿克苏河春季径流的主导气候因子是前冬降雪和春季温度,春季径流对前冬降雪、春季温度具有正相关关系.春季流域以融雪径流为主,4月中下旬开始出现融雪径流,5月中下旬融雪作用明显.近年来阿克苏河损耗径流增加,主要由于其两支流汇流前流域农业灌溉用水增多所致.同时分析了35年来春季阿克苏河径流典型丰、枯水年当年春季及前冬的500 hPa位势高度环流场的距平特征.     

用耦合模型模拟青弋江流域水文对气候变化的响应

用陆面模式SSiB与动态植被模型TRIFFID以及流域地形指数水文模型的耦合模型SSiB4T/TRIFFID模拟了长江下游的青弋江流域植被和水量平衡的动态过程,分析了气温和降水变化对流域径流和蒸发的影响。结果表明：（1）流域气温上升10C,径流减小6.7-9.7%;气温上升20C,径流减小11.7-17.4%;（2）降水增加5%,径流增加9.2-11.6%,降水减小5%,径流减小8.6-11.6%;（3）温度不变仅降水变化对流域蒸发影响很小,温度增加20C,流域总蒸发3-10月份增加8.0-10.7mm,其余月份增加5.4-7.1mm,1月和12月蒸发对温度增加最敏感;（4）气温上升20C,叶面积指数1月和12月增加,5-10月略有减小。降水和气温变化对青弋江流域径流影响明显且与植被类型有关,流域蒸发的变化主要受温度变化的控制。     

近40 a青海湖流域逐日降水和气温变化特征

利用青海湖流域内刚察气象站1958～2001年的逐日降水和气温资料,分析了流域内的气候变化特征.结果表明,日降水量P≤5 mm的降水总量以9 mm/10 a的速率显著减少,已从1960s的130.8 mm/a减少为1990s的116.2 mm/a,而P≥20 mm的降水总量以9 mm/10 a的速率显著增加,已从29.7 mm/a增加为36.9 mm/a;连续无降水最长天数由1960s的32 d/a增加为1990s的45 d/a,至少10 d连续无降水总天数由103 d/a增加为145 d/a.逐年平均温度40 a来明显升高,已从1960s的-0.7℃升至1990s的0.1℃,且与逐年极端低温升高有较好相关性.1990s与1960s的同日平均气温相比,已有261 d变暖(占年天数的71.2%),且主要发生在冬季.这种气候变化特征对流域内的青海湖水位和河川径流有重要影响.     

气候变化对长江上游径流影响预估

利用第五次国际耦合模式比较计划(CMIP5)中5个气候模式在3种典型浓度路径(RCPs)下的预估结果驱动SWAT水文模型,预估了21世纪气候变化对长江上游年径流量、季节分配以及极端径流的影响。结果表明：预估的长江上游平均气温呈显著上升趋势,21世纪末较当前(1986—2005年)升高1.5~5.5℃,降水总体呈增加趋势,在21世纪30年代后高于当前气候平均值,21世纪末相对于当前增加5%~15%。流域内气候变化存在明显空间差异,金沙江和岷沱江流域气温升高和降水增加幅度均大于流域平均值。预估的长江上游年径流量及各月平均径流均有增加趋势,在21世纪30年代后高于当前多年平均值,21世纪中期增加4%~8%,21世纪末增加10%~15%。预估的径流年内分布的均匀性有所增加,但年际变化明显增大,极端旱涝事件的频率和强度明显增加。预估的各子流域径流变化对气候变化的响应也存在差异,金沙江和岷沱江流域年径流量、年际变化和年内分布变化小,对气候变化的响应表现为低敏感;嘉陵江流域、乌江流域和长江上游干流径流增加幅度大,同时极端丰枯出现的频率和程度增加显著,是气候变化响应的敏感区域。     

气侯变化背景下黑河上游春季融雪洪水预估研究

气候变暖将导致高山区冰冻圈加剧融化,一方面融水资源时空分布的不确定性增大;另一方面,融水洪水灾害发生的频度和强度也将发生改变。基于气象、水文数据和MODIS积雪覆盖数据,利用融雪径流模型(SRM),对1990—2012年共23年祁连山黑河札马什克控制区融雪期径流进行模拟与验证。结果表明：SRM在该流域具有较高的模拟精度（纳什系数为0.91),可用于分析和预估控制区径流强度变化。为此,采用黑河流域气温、降水降尺度数据,预估了未来气候变化背景下积雪范围变化及不同重现期洪水变化趋势。结果显示,与基准期相比,在RCP2.6、RCP4.5和RCP8.5情景下,最大积雪范围可减小3%~7%,且随着海拔升高,变化愈剧烈。RCP2.6情景下因气温和降水变化幅度较小,到21世纪末各重现期洪水强度保持在10%以内波动;RCP4.5情景下,各重现期洪水强度最高增大约20%;在RCP8.5情景下,各重现期洪水强度最高可增大超30%。相关分析结果显示,不同重现期洪水径流与气温和降水均具有较强相关性：重现期越长,洪峰与气温的相关性越大;重现期越短,洪峰与降水的相关性越大。通过预估气候变化背景下的融雪性洪水事件强度及重现期变化,有助于有效开展区域洪水风险管理、提高洪水资源的利用价值。     

气候与植被覆盖变化对中国西南亚高山区流域碳水循环的影响模拟

正确认识气候变化对流域森林植被和水文的影响对于林业经营管理与流域生态修复具有重要意义。为了揭示气候与植被覆盖变化对西南亚高山区流域碳水循环过程的影响,用生物物理/动态植被模型SSiB4/TRIFFID（Simplified Simple Biosphere model version 4, coupled with the Top-down Representation of Interactive Foliage and Flora Including Dynamics model）与流域地形指数水文模型TOPMODEL（Topographic Index Model）的耦合模型（以下记为SSiB4T/TRIFFID）模拟了不同气候情景下西南亚高山区的梭磨河流域植被演替和碳水循环过程。结果表明,所有试验流域植被经历了从C3到苔原灌木最后到森林的变化;控制试验流域蒸散在流域植被主要为苔原灌木时达到最大而径流深最小;增温5 ℃并且增雨40%试验[记为T+5, (1+40%) P试验]流域蒸散在流域为森林覆盖时达到最大而径流深最小。随着温度增加,森林蒸腾、冠层截留蒸发和蒸散的增加幅度明显大于草和苔原灌木,导致森林从控制试验的增加径流量变为减小径流量。从控制试验到T+5, (1+40%) P试验,温度增加使森林净初级生产力有所增加,但对草和苔原灌木的净初级生产力影响很小;植被水分利用效率随温度增加明显减小。西南山区随着海拔高度降低（温度升高）,森林从增加径流量转变为减少径流量,植被水分利用效率也相应明显减小。西南山区气候的垂直地带性对森林—径流关系和水分利用效率的空间变化有着重要的影响。     

土地利用变化对长江流域气候及水文过程影响的敏感性研究

使用区域气候模式(RegCM3)和大尺度汇流模型(LRM), 研究土地利用/植被覆盖变化对长江流域气候及水文过程的影响。RegCM3嵌套于欧洲数值预报中心 (ECMWF) 再分析资料ERA40, 分别进行了中国区域在实际植被和理想植被分布情况下两个各15年 (1987～2001年) 时间长度的积分试验。随后, RegCM3 两个试验的输出径流结果分别用来驱动LRM, 研究土地利用/植被覆盖变化对长江流域河川径流的影响。研究结果指出, 中国当代土地利用变化对长江流域降水、蒸散发、径流深及河川径流等水文气候要素的改变较大, 对气温的改变并不明显。土地利用变化引起长江干流河川径流量在夏季(6～8月)有所增加, 并且越向下游增加幅度越大, 其中大通站径流量增加接近15%。总体而言, 土地利用改变加剧了长江流域夏季水循环过程, 使得夏季长江中下游地区降水增多, 径流增大。     

Modelling spatially distributed snowmelt and meltwater runoff in a small Arctic catchment with a hydrology land‐surface scheme (WATCLASS)

Abstract

The fully distributed hydrology land‐surface scheme WATCLASS is used to simulate spring snowmelt runoff in a small Arctic basin, Trail Valley Creek, dominated by open tundra and shrub tundra vegetation. The model calculates snowmelt rates from a full surface energy balance, and a three‐layer soil model is used to simulate the infiltration into and the exchange of heat and moisture within the ground. The generated meltwater is delivered to the stream channel network by overland flow, interflow, and baseflow and subsequently routed out of the catchment. Subgrid spatial variability is handled by the model through the use of grouped response units (GRUs). The GRUs in WATCLASS are chosen according to vegetation land cover.

Five spring snowmelt periods with a variety of initial end‐of‐winter snow cover and melt conditions were simulated and compared with observed runoff data. In a second step, the model's ability to simulate spatially variable snow covered area (SCA) within the basin was tested by comparing model predictions to remotely sensed SCA. WATCLASS was able to predict runoff volumes (on average within 15% over five years of modelling) as well as timing of snowmelt and meltwater runoff for open tundra fairly accurately. However, the model underestimated melt in the energetically more complex shrub tundra areas of the basin. Furthermore, the observed high spatial variability of the SCA at a 1‐km resolution was not captured well by the model.

Several recommendations are made to improve model performance in Arctic basins, including a more realistic implementation of the gradual deepening of the thawed layer during the spring, and the use of topographic information in the definition of land cover classes for the GRU approach.     

气候变化条件下雅砻江流域未来径流变化趋势研究

雅砻江为我国重要的水电基地,未来气候变化条件下流域径流变化将直接影响雅砻江梯级水库群运行安全和发电调度,因此研究气候变化对雅砻江流域径流的影响十分必要。首先建立了流域月尺度的SWAT模型,然后使用统计降尺度模型（SDSM）模拟未来2006—2100年流域内各站点的气象数据,最后使用流域SWAT模型对未来2006—2100年月径流进行模拟。结果表明,未来雅砻江流域径流呈上升趋势,且增幅随着辐射强迫的增加同步增大,RCP2.6、RCP4.5、RCP8.5这3种典型浓度路径下年平均径流增幅分别为8.9%、12.5%、16.7%,且2020S（2006—2035年)、2050S（2036—2065年)、2080S（2066—2100年）这3个时期年径流量呈现不同的变化趋势,其中RCP2.6浓度路径下为先逐步增加达到峰值后略有减少,RCP4.5浓度路径下为先逐步增加达到峰值后趋于稳定,RCP8.5浓度路径下为持续增加。流域径流年内分配方面,3种典型浓度路径下汛期径流占全年比例在2020S、2050S、2080S这3个时期均为先降后升趋势,整个预测期总体为降低趋势,RCP2.6、RCP4.5及RCP8.5这3种浓度路径下整个预测期的均值分别由基准期的75.9%降低为72.9%、72.0%、71.2%。径流增加会对流域洪水特性产生较大影响,为此应该修正流域设计洪水计算结果和调整防洪调度方案,以降低雅砻江流域梯级水库群因气候变化而产生的运行风险,并提高发电调度效率。     

River discharge and freshwater runoff to the Barents Sea under present and future climate conditions

River discharge forms a major freshwater input into the Arctic Ocean, and as such it has the potential to influence the oceanic circulation. As the hydrology of Arctic river basins is dominated by cryospheric processes such as snow accumulation and snowmelt, it may also be highly sensitive to a change in climate. Estimating the water balance of these river basins is therefore important, but it is complicated by the sparseness of observations and the large uncertainties related to the measurement of snowfalls. This study aims at simulating the water balance of the Barents Sea drainage basin in Northern Europe under present and future climate conditions. We used a regional climate model to drive a large-scale hydrological model of the area. Using simulated precipitation derived from a climate model led to an overestimation of the annual discharge in most river basins, but not in all. Under the B2 scenario of climate change, the model simulated a 25% increase in freshwater runoff, which is proportionally larger than the projected precipitation increase. As the snow season is 30–50 day shorter, the spring discharge peak is shifted by about 2–3 weeks, but the hydrological regime of the rivers remains dominated by snowmelt.     

21世纪天山南坡台兰河流域径流变化情景预估

基于台兰水文站2003—2005年观测的水文气象数据,通过参数率定和验证获得了适用于台兰河流域的HBV水文模型优化参数。应用RegCM3气候模式在IPCC SRES A1B情景下的预估数据,经Delta降尺度方法生成流域未来气候数据,并结合流域冰川退缩情景预估台兰河流域径流在21世纪中期(2041—2060年)和末期(2081—2100年)可能发生的变化。结果表明:在21世纪中期和末期,台兰河流域气温将显著上升,而降水变化不大;21世纪中期冰川3种可能退缩比例为15%、20%和25%,末期分别为20%、30%和40%;无论冰川处于哪一种退缩情景,21世纪径流较基准期(1981—2000年)都呈增加趋势,中期和末期最小增幅将分别为17.3%和18.6%;最大增幅可达45.9%和66.0%;耦合RegCM3气候模式预估增幅为28.9%和41.5%;台兰河流域未来径流年内分布与基准期大体相同,但又呈现出一定的差异性,具体表现为,在21世纪中期5月份径流增加很快,径流峰值出现在7月份,而到21世纪末期径流峰值出现在8月份。     

Hydrological response to climate change in a glacierized catchment in the Himalayas

The analysis of climate change impact on the hydrology of high altitude glacierized catchments in the Himalayas is complex due to the high variability in climate, lack of data, large uncertainties in climate change projection and uncertainty about the response of glaciers. Therefore a high resolution combined cryospheric hydrological model was developed and calibrated that explicitly simulates glacier evolution and all major hydrological processes. The model was used to assess the future development of the glaciers and the runoff using an ensemble of downscaled climate model data in the Langtang catchment in Nepal. The analysis shows that both temperature and precipitation are projected to increase which results in a steady decline of the glacier area. The river flow is projected to increase significantly due to the increased precipitation and ice melt and the transition towards a rain river. Rain runoff and base flow will increase at the expense of glacier runoff. However, as the melt water peak coincides with the monsoon peak, no shifts in the hydrograph are expected.     

Implications of 21st century climate change for the hydrology of Washington State

Pacific Northwest (PNW) hydrology is particularly sensitive to changes in climate because snowmelt dominates seasonal runoff, and temperature changes impact the rain/snow balance. Based on results from the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4), we updated previous studies of implications of climate change on PNW hydrology. PNW 21st century hydrology was simulated using 20 Global Climate Models (GCMs) and 2 greenhouse gas emissions scenarios over Washington and the greater Columbia River watershed, with additional focus on the Yakima River watershed and the Puget Sound which are particularly sensitive to climate change. We evaluated projected changes in snow water equivalent (SWE), soil moisture, runoff, and streamflow for A1B and B1 emissions scenarios for the 2020s, 2040s, and 2080s. April 1 SWE is projected to decrease by approximately 38–46% by the 2040s (compared with the mean over water years 1917–2006), based on composite scenarios of B1 and A1B, respectively, which represent average effects of all climate models. In three relatively warm transient watersheds west of the Cascade crest, April 1 SWE is projected to almost completely disappear by the 2080s. By the 2080s, seasonal streamflow timing will shift significantly in both snowmelt dominant and rain–snow mixed watersheds. Annual runoff across the State is projected to increase by 2–3% by the 2040s; these changes are mainly driven by projected increases in winter precipitation.     

Explaining the hydroclimatic variability and change in the Salmon River basin

Climate change in the Pacific Northwest and in particular, the Salmon River Basin (SRB), is expected to bring about 3–5 °C rise in temperatures and an 8 % increase in precipitation. In order to assess the impacts due to these changes at the basin scale, this study employed an improved version of Variable Infiltration Capacity (VIC) model, which includes a parallel version of VIC combined with a comprehensive parameter estimation technique, Shuffled Complex Evolution (SCE) to estimate the streamflow and other water balance components. Our calibration (1955–1975) and validation (1976–1999) of the model at the outlet of the basin, White Bird, resulted in an r² value of 0.94 which was considered satisfactory. Subsequent center of timing analysis showed that a gradual advancement of snowmelt induced-peak flow advancing by about 10 days in the future. Historically, the flows have shown a general decline in the basin, and in the future while the magnitudes might not be greatly affected, decreasing runoff of about 3 % over the next 90 years could be expected and timing of peak flow would shift by approximately 10 days. Also, a significant reduction of snow water equivalent up to 25 %, increased evapotranspiration up to 14 %, and decreased soil moisture storages of about 2 % is predicted by the model. A steady decline in SWE/P from the majority of climate model projections for the basin was also evident. Thus, the earlier snowmelt, decreasing soil moisture and increased evapotranspiration collectively implied the potential to trigger drought in the basin and could affect the quality of aquatic habitats and their spawning and a detailed investigation on these impacts is warranted.