Assessment of future climate change impacts on hydrological behavior of Richmond River Catchment

This study evaluated the impacts of future climate change on the hydrological response of the Richmond River Catchment in New South Wales (NSW), Australia, using the conceptual rainfall-runoff modeling approach (the Hydrologiska Byrans Vattenbalansavdelning (HBV) model). Daily observations of rainfall, temperature, and streamflow and long-term monthly mean potential evapotranspiration from the meteorological and hydrological stations within the catchment for the period of 1972–2014 were used to run, calibrate, and validate the HBV model prior to the streamflow prediction. Future climate signals of rainfall and temperature were extracted from a multi-model ensemble of seven global climate models (GCMs) of the Coupled Model Intercomparison Project Phase 3 (CMIP3) with three regional climate scenarios, A2, A1B, and B1. The calibrated HBV model was then forced with the ensemble mean of the downscaled daily rainfall and temperature to simulate daily future runoff at the catchment outlet for the early part (2016–2043), middle part (2044–2071), and late part (2072–2099) of the 21st century. All scenarios during the future periods present decreasing tendencies in the annual mean streamflow ranging between 1% and 24.3% as compared with the observed period. For the maximum and minimum flows, all scenarios during the early, middle, and late parts of the century revealed significant declining tendencies in the annual mean maximum and minimum streamflows, ranging between 30% and 44.4% relative to the observed period. These findings can assist the water managers and the community of the Richmond River Catchment in managing the usage of future water resources in a more sustainable way.     

Assessment of future snowfall regimes within the Italian Alps using general circulation models

General Circulation Models GCMs are widely adopted tools to achieve future climate projections. However, one needs to assess their accuracy, which is only possible by comparison of GCMs’ control runs against past observed data. Here, we investigate the accuracy of two GCMs models delivering snowfall that are included within the IPCC panel's inventory (HadCM3, CCSM3), by comparison against a comprehensive ground data base (ca. 400 daily snow gauging stations) located in the Italian Alps, during 1990-2009. The GCMs simulations are objectively compared to snowfall volume by regionally evaluated statistical indicators. The CCSM3 model provides slightly better results than the HadCM3, possibly in view of its finer computational grid, but yet the performance of both models is rather poor. We evaluate the bias between models and observations, and we use it as a bulk correction for the GCMs' snowfall simulations for the purpose of future snowfall projection. We carry out stationarity analysis via linear regression and Mann Kendall tests upon the observed and simulated snowfall volumes for the control run period, providing contrasting results. We then use the bias adjusted GCMs output for future snowfall projections from the IPCC-A2 scenario. The two analyzed models provide contrasting results about projected snowfall during the 21st century (until 2099). Our approach provides a first order assessment of the expected accuracy of GCM models in depicting past and future snowfall upon the (Italian) Alps. Overall, given the poor depiction of snowfall by the GCMs here tested, we suggest that care should be taken when using their outputs for predictive purposes.     

赣江流域非一致性条件下设计洪水估计

赣江流域年最大日径流量在过去60a呈现出显著的变异特征,以此为样本序列,选用广义极值(GEV)分布来对其进行拟合,并基于五种气候模式输出结果对未来设计洪水的变化情况进行分析。所选协变量包括时间t、洪水前N日降水量和下垫面信息。相关关系分析表明,N=10时降水与洪水关系最为密切,但流域内土地利用类型仅呈现出微弱的变化趋势。模拟结果表明,洪水序列服从Weibull分布,其中形状参数ξ=-0.169、尺度参数σ=2 078.9、位置参数μ=65.1c+437.1。非一致性条件下的设计洪水值与传统方法计算的设计值存在很大区别,设计洪水值在1994年要偏大4 000m~3/s以上,其面临的洪水风险要远超普通年份。未来的设计洪水在低、中、高三种排放情景下均呈现出上升趋势,峰值出现于2040年前后,较1994年估计值偏大1 000～2500 m~3/s。     

气候变化对汉江上游蒸发量的影响

根据汉江上游1961～2000年的月降水和月气温的实测资料,利用GCMs模型输出的气候背景为输入条件,采用气候情景趋势分析结果和直接利用GCMs模型的输出结果两类方法确定气候变化的数据源,分析了未来降水和气温变化对蒸发量的影响。分析结果表明：未来气候变化情况下蒸发量年内分配与多年平均年内分配一致,没有明显的变化。降水量变化对蒸发量的影响枯水期大于汛期,降水减少对蒸发量的影响大于降水增加的影响。气温变化对蒸发量的影响枯水期大于汛期,气温减少对蒸发量的影响大于温度增加的影响。降水对蒸发量的影响大于气温。     

气候变化情景下丹江口水库径流模拟预测

气候变化和异常对水资源影响的评价方法有很多种,本项研究采用概念性水文模型模拟和假定气候情景推算径流变化法,分析气候变化对丹江口水库径流的影响,即利用不同的GCMs模型模拟丹江口水库上游的月降水和气温序列,并通过Delta变化作为汉江流域半分布式两参数月水量平衡模型的输入,用以模拟和预测2021～2050年的丹江口水库径流量.结果表明,对于2021-2050年降水和气温年变化的情景,未来年平均径流将相应升高8.18%(HadCM3)、7.78%(CSRIO)和2.14%(CCSRINES),敏感度分析结果显示,径流量对降水变化的敏感度较径流对气温变化的敏感度要大.     

乌江中上游地区极端降水特征及未来预估

选取乌江中上游地区1961-2019年的逐日降水数据,采用趋势分析、EOF、小波分析等方法,研究极端降水在时空上的变化特征,同时为了使研究具有整体性,利用CMIP6中5个GCMs下的3种情景数据(SSP126、SSP245、SSP585),在降尺度处理后预估未来(2020-2100年)极端降水的变化。结果表明：1961-2019年整个流域地区极端降水事件虽然有增有减,但无显著性变化;在变化周期上,信号强烈的周期主要在23～30 a的时间尺度上,且贯穿整个时序;5个极端降水指数的第1模态表明其在空间变化上具有一致性,第2模态则有差异;未来极端降水事件整体上随SSPs情景的升高而愈发显著,且多以正趋势为主。研究结果可为乌江流域地区水安全管控、规划建设、防灾减灾等提供参考。     

基于熵权的 TOPSIS 综合评价法 在大气环流模式优选中的应用

大气环流模式(GCMs)是定量评估气候变化及其影响效应的有效工具,GCMs的优选是使用该工具时不可缺少的重要环节。将TOPSIS综合评价法引入到GCMs的优选中,并结合熵权的概念对各项评价指标进行赋权,采用加权TOPSIS综合评价法对CMIP5中18个GCMs对黑河流域上游降水模拟方面的适用性进行评价;并通过传统Rank Score(RS)方法和降水预估精度两方面对该方法的结果进行验证。结果表明,对研究区1960-2005年降水模拟效果最好的是CSIRO-Mk3.6.0模式,模拟效果最差的是BNU-ESM模式;1960-2005年模拟性能优良和模拟性能较差的GCMs排序与传统RS方法得到的结果基本一致,与2006-2015年GCMs的排序也基本一致,这说明基于加权TOPSIS综合评价法对GCMs进行优选的结论具有很强的可靠性。因此该方法适用于多方案、多目标的GCMs优选,并由于其计算简单、计算过程中没有信息损失等优势而具有广阔的应用前景。     

GCMs降尺度及其在讨赖河上游径流预报中的应用

在气候变化和人类活动影响下,内陆河流域出山径流变异程度提升,研究径流预测及其对气候变化响应具有理论和实践的双重意义。以讨赖河流域上游为研究区,采用Delta降尺度及权重集成方法对14种GCMs在3种RCP情景下的气温和降水进行优化,预测分析了该区未来径流变化和水资源供需平衡。结果表明:由气候-生态联合驱动的径流预测模式在讨赖河流域适用性良好,气温对出山径流总体呈负减效应,降水和NDVI表现为正增效应。未来气温和降水呈增加趋势,增温主要发生在河谷地带,降水增加在分水岭周边更为显著。流域出山径流总体增加,不同子区径流变幅从小到大依次为OL06＜OL04＜OL05＜OL01＜OL03＜OL02。尽管未来出山径流有所增加,但从水资源满足度来看,平、枯水年讨赖河流域仍存在水资源短缺问题。     

基于Delta方法的淮河流域气候变化预测分析

为了预测气候变化对区域水文要素变化的影响,以淮河流域蚌埠以上区域为例,利用全球气候模式CSIRO和HadCM3,分别预测了同一情景下,淮河流域3个未来时段的降雨和温度变化。通过Delta变换对未来3个阶段的数据进行降尺度处理,运用曲线拟合的方法提出了蒸发函数模型。将预测出的气温作为蒸发函数模型的输入因子,模拟了淮河流域未来的蒸发过程。结果表明, 该区域未来时段的降雨、气温和蒸发量均比历史观测值有所上升。