统计降尺度方法及其评价指标比较研究

针对目前气候变化对水资源影响研究中关注的问题,以汉江白河上游为研究对象,比较研究统计降尺度方法及其评价指标。以美国环境预报中心/美国国家大气研究中心全球再分析资料、CGCM3和HadCM3的A2情景为大尺度气候背景资料,应用SSVM和SDSM统计降尺度方法对大尺度气候因子进行尺度降解,得到降水情景序列后作为水文模型的输入,通过模拟径流比较分析统计降尺度方法的优劣。研究结果表明,由不同统计降尺度方法得到的降水作为水文模型输入,模拟径流的结果相差很大;对广泛应用于统计降尺度方法的降水模拟评价指标和径流模拟结果进行比较,发现所采用的降水评价指标侧重于考虑降水的统计分布特征,不能完整地描述降水过程特性。分析认为,径流模拟结果应该作为气候变化对径流影响研究中统计降尺度方法评价的重要参考。     

水库洪水期风险调度方法

根据风险调度原理,本文提出了水库洪水期风险调度方法。首先,根据洪水期调度过程,将洪水期划分为三个阶段;其次,针对涨水段和退水段,建立了以获得效益为主的洪水调度方法。该方法适用调节性能较差的水库,且易于操作,适应性强,获得的超额效益显著。     

基于多源遥感土壤湿度与模型数据同化的流域径流模拟

为提升径流模拟精度,以秦淮河流域为例,采用集合平均法将SMAP、SMOS、AMSR2卫星遥感土壤湿度融合并利用地形湿度指数进行空间降尺度处理,采用卡尔曼滤波算法和栅格新安江模型进行遥感融合土壤湿度同化。对2016—2018年秦淮河流域3个流量站记录的11场洪水进行模型数据同化的结果表明：日尺度率定期洪峰、径流深相对误差合格率均为71.43%,验证期洪峰、径流深相对误差合格率分别为66.67%和100%;经同化后,8场洪水径流深误差减小,平均误差降低29.01%;8场洪水确定性系数增大,范围在0.01～0.09之间,模拟精度最高可提升11.84%;同化多源遥感土壤湿度能有效改善土壤湿度估计的准确性,进而提升径流模拟精度。     

A Novel Spatiotemporal Statistical Downscaling Method for Hourly Rainfall

Finer spatiotemporal resolution rainfall data is essential for assessing hydrological impacts of climate change on medium and small basins. However, existing methods pay less attention to the inter-day correlation and diurnal cycle, which can strongly influence the hydrological cycle. To address this problem, we present a spatiotemporal downscaling method that is capable of reproducing the inter-day correlation, the diurnal cycle, and rainfall statistics on daily and hourly scales. The large-scale datasets, which we obtained from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis dataset (NNR) and general circulation model (GCM) outputs, and local rainfall data are analyzed to assess the impacts of climate change on rainfall. Our proposed method consists of two steps: spatial downscaling and temporal downscaling. We apply spatial downscaling first to obtain the relationship between large-scale datasets and daily rainfall at a site scale using a k-nearest neighbor method (KNN). Then, we conduct an hourly downscaling of daily rainfall in the second step using a genetic algorithm-based KNN (GAKNN) with the inter-day correlation and the diurnal cycle. Furthermore, we analyzed changes in rainfall statistics for the periods 2046–2065 and 2081–2100 under the A2, A1B, and B1 scenarios of the third generation Coupled Global Climate Model (CGCM3.1) and Bergen Climate Model version 2 (BCM2.0). An application of our proposed method to the Shihmen Reservoir basin (Taiwan) has shown that it could accurately reproduce local rainfall and its statistics on daily and hourly scales. Overall, the results demonstrated that the proposed spatiotemporal method is a powerful tool for downscaling hourly rainfall data from a large-scale dataset. The understanding of future changes of rainfall characteristics through our proposed method is also expected to assist the planning and management of water resources systems.     

Improvement to the Thornthwaite Method to Study the Runoff at a Basin Scale Using Temporal Remote Sensing Data

Most of the popular hydrological models are intensive data driven hence, it has become a constraint in computing runoff of river basins where the meteorological data availability is scant. Studying environmental impact assessment on runoff has also become complex in many basins due to non-availability of sufficient historic meteorological data. Directly or indirectly, major components of hydrological cycle such as evapotranspiration and soil moisture are dependent on land use pattern at basin scale. Keeping in view of this, in this paper, an attempt was made to propose modification to simple monthly water balance model by integrating potential evapotranspiration with land use coefficients that were derived from the temporal satellite remote sensing data to compute runoff at basin scale. Godavari Basin, India was selected as study basin to demonstrate the approach. Monthly land use coefficients of all land use classes were computed during the calibration process of the model by matching the computed runoff with field runoff. Runoff during the last 18 years (1990–91 to 2007–08) was computed using the developed methodology. Four years datasets were used for model calibration and the rest of the data for model validation. Spatial annual groundwater flux, reservoir flux and domestic water consumption grids were computed using the field data and integrated with the model in computing runoff. From the Nash-Sutcliffe efficiency coefficient, it is found that computed runoff is very well matching the field runoff. The demonstrated approach is found to be more accurate and simple in computing runoff at basin scale in absence of high intensity meteorological data.     

RF-SVR降尺度模型在滦河流域的适用性分析

探讨了RF-SVR统计降尺度模型用于汛期极端降雨模拟的可能性。该统计降尺度模型由降雨状态分类和降雨量预测回归两部分构成,降雨状态分类过程中采用了随机森林（RF）方法,降雨量预测回归过程采用了支持向量机回归（SVR）法。选用1961-2000年的NCEP/NCAR再分析资料及滦河流域10个雨量站点的降雨观测数据进行模型率定,并用2001-2012年数据进行了验证。将RF-SVR统计降尺度模型与SVR模型降尺度效果做了对比。结果表明：RF-SVR模型模拟的滦河流域日降雨量偏差显著减小,并可以改善流域极端降雨的模拟预测效果。     

基于ATAK的MSWEP数据空间降尺度及对降水融合的影响研究

全球性降水数据为获取大范围降水空间分布提供了新途径,但其空间分辨率不高一直是制约其应用于流域或区域尺度上的重要因素之一,因此研究全球性降水数据的空间降尺度方法具有重要的理论和实用价值。本文采用从区域到区域的Kriging（Area to Area Kriging,ATAK）和反距离权重（Inverse Distance Weighted,IDW）两种方法,不考虑地面雨量资料及影响雨量的有关辅助信息,在汉江流域将全球性降水数据MSWEP的空间分辨率由0.1°×0.1°提高至0.02°×0.02°。结果发现ATAK降尺度得到的月雨量场虽然在统计精度上与IDW无明显差异,但提高了对月降水量局部空间变异特征的描述能力,在一定程度上克服了IDW的平滑效应。进一步以ATAK、IDW降尺度处理后的MSWEP数据以及不作空间降尺度处理的原始MSWEP数据为背景场,采用GWR方法分别与雨量站网降水数据融合,发现3种情况下得到的月降水融合数据在空间基本格局上相同,精度统计结果也较为接近,但雨量场的空间连续性及细节特征仍有一定差异。在地表雨量站网密度较高的情况下,背景场差异对MSWEP和站点降水融合结果的影响不能完全消除,甚至在局部可能放大。因此,对于MSWEP等全球性降水数据与站网降水资料的融合而言,选择适当的空间降尺度方法是必要的。本文的结论和认识为全球性降水数据的空间降尺度和雨量场精细化估计提供了重要参考。     

气候变化影响下黄河上游梯级水库群未来发电量预测

为分析气候变化影响下黄河上游大型水库入库来水过程及梯级发电量的时程变化规律,以黄河上游龙羊峡刘家峡梯级水库群为例,采用Mann-Kendall 突变检验方法对唐乃亥和小川水文序列进行突变识别,在此基础上构建了考虑融雪过程的HBV 水文模型,利用统计降尺度方法对CanESM2 和GFDL_ESM2G 两种气候模式3 种气候变化情景(RCP2. 6、RCP4. 5 和RCP8. 5) 下的降水、气温数据进行空间降尺度处理,并将其驱动水文模型预测未来入库来水过程,构建黄河上游梯级联合发电调度模型分析气候变化对未来发电调度过程的影响。结果表明:黄河上游径流序列突变年份集中于20 世纪80 年代,且2000 年之后径流量显著减少;气候变化将导致未来(2021—2050年)汛期6—9 月径流增加,非汛期径流显著减少;随着时间推移,不同气候变化情景下,龙羊峡和刘家峡两库的梯级发电量变化规律不同,RCP8.5 气候变化情景下,气候模式不确定性对其影响最大。     

澜沧江流域水文气象要素变化特征分析

以澜沧江流域为对象,采用气候倾向率、MK检验、Pearson相关性分析等方法,分析1958-2015年气温和降水的空间分布、年内分配及演变趋势,揭示径流演变的驱动要素。结果表明:澜沧江流域气温空间分布不均,上游温度低降水少,下游温度高降水多;降水和径流年内分配不均,主要集中于夏秋两季,径流峰值比降水峰值滞后一个月;1958-2015年气温呈上升的趋势,降水和径流呈下降趋势;2005年为径流出现突变的年份,年径流减少21.5%;气温升高、降水量减少对径流减少有一定贡献;气温与径流的相关性较差,降水径流相关性于2005年之后变差,尤其是夏秋两季。     

梯级水电站对黑河出山口径流及洪水过程的影响

基于莺落峡水文站的月年径流量、年最大洪峰流量、洪水过程及黑河上游流域降水等资料,运用双累积曲线法、Mann-Kendall趋势检验法(简称MK检验法)、基尼系数法等方法,分析梯级水电站对黑河出山口莺落峡水文站径流及洪水过程的影响。结果表明:黑河上游梯级水电站的建设运行对年径流量变化影响不大,对径流年内分配及洪水过程有一定影响;电站联合调度运行后,坝前库区蓄放水改变了天然径流过程,对径流年内分配产生显著影响,年内分配均匀度在2001年发生转折,2017—2020年呈显著增加趋势;人为升降闸门高度,致使水位直上、直下,洪水过程拉长,峰值变大,呈陡涨直落形态,涨落率和变化频次增加。研究成果可为加强流域水电站科学调度、水生态文明建设及水能水资源可持续开发利用提供理论依据。     

基于分布式水文模型的水资源评价新方法

为解决变化环境条件下水资源评价中的"还原失真"和"还原失效"问题,本文提出基于物理参数的分布式水文模型用于变化环境下水资源评价方法的原理和假定,以及基于此原理利用上游测站流量进行模型参数率定和中游测站进行验证(简称UCMV,Up-reach for Calibration and Mid-reach for Validation)的水资源评价新方法。以永定河山区流域为实例,进行了不同时期下垫面的水资源评价。结果表明,流域1990年和2000年下垫面条件下多年平均地表水资源量分别为10.799和9.892亿m3,后者相对于前者产流能力降低了8.0%,清楚地表现出下垫面变化对流域产流能力的影响,也进一步证实了"还原失效"现象的存在以及基于物理分布式水文模型进行变化环境下的水资源评价的有效性。     

Assessment of Extreme Precipitation in Future through Time-Invariant and Time-Varying Downscaling Approaches

Skill of a time-varying downscaling approach, namely Time-Varying Downscaling Model (TVDM), against time-invariant Statistical Downscaling Model (SDSM) approach for the assessment of precipitation extremes in the future is explored. The downscaled precipitation is also compared with a Regional Climate Model (RCM) product obtained from Coordinated Regional Climate Downscaling Experiment (CORDEX). The potential of downscaling the extreme events is assessed considering Bhadra basin in India as the study area through different models (SDSM, TVDM and RCM) during historical period (calibration: 1951–2005, testing: 2006–2012). Next, the changes in precipitation extremes during future period (2006–2035) have been assessed with respect to the observed baseline period (1971–2000), for different Representative Concentration Pathway (RCP) scenarios. All the models indicate an increasing trend in the precipitation, for the monsoon months and maximum increase is noticed using RCP8.5. The annual precipitation during the future period (RCP8.5) is likely to increase by 7.6% (TVDM) and 4.2% (SDSM) in the study basin. An increase in magnitude and number of extreme events during the future period is also noticed. Such events are expected to be doubled in number in the first quarter of the year (January–March). Moreover, the time-invariant relationship (in SDSM) between causal-target variables is needed to be switched with time-varying (TVDM). This study proves that the time-varying property in TVDM is more beneficial since its performance is better than SDSM and RCM outputs in identifying the extreme events during model calibration and testing periods. Thus, the TVDM is a better tool for assessing the extreme events.

     

系统微分响应参数率定方法在建阳流域SWAT模型中的应用

利用基于系统微分响应理论的参数率定方法率定闽江建阳流域SWAT模型,通过流域1992—2000年日资料验证了该方法的实际应用效果,采用纳什效率系数(NSE)、偏差百分比(PBIAS)和相关系数r作为评价指标对率定后的SWAT模型模拟精度进行评价,并与传统利用SUFI-2方法率定得到的SWAT模型模拟结果进行对比分析。结果表明：系统微分响应方法率定的参数在建阳流域的日径流模拟中表现较好,率定期和检验期NSE均为0.65以上,径流量PBIAS在5%以内,r在0.65以上;利用系统微分响应率定参数方法率定SWAT模型参数在实际应用中可行,且效率与精度均高于传统的SUFI-2方法。     

基于CMADS驱动下SWAT模型的敖江流域径流模拟

目前针对气象、水文资料不足的小尺度流域进行径流模拟的研究相对较少。选取敖江流域为研究区,利用中国大气同化驱动数据集(CMADS)驱动SWAT模型对该流域2008—2016年进行逐月径流模拟,并使用水文比拟法结合邻近的2个传统气象站计算出模拟时段的观测数据以完成模型参数的率定与验证。结果表明:模拟结果与观测值较吻合,率定期(2010—2013年)评价指标决定系数R²和Nash-Suttcliffe系数NS分别为0.84和0.76,验证期(2014—2016年)两者分别为0.85和0.74,均达到了模型的评价要求。研究成果表明CMADS驱动下的SWAT模型适用敖江流域的径流模拟,采用水文比拟法适合在水文资料不足的地区进行径流计算,可为缺少气象与水文资料的小尺度流域进行径流模拟提供参考。     

缺资料地区产流径流时空特性分析及其关系研究——以洮河流域为例

为了解决缺资料地区的产流、径流时空特性分析问题,采用SWAT模型、多元统计分析法、相关系数法、弹性分析法等方法,研究分析缺资料地区——洮河干流分区段产流、径流的时空变化规律,揭示降雨量P、产流量Y、径流量R三者之间关系以及径流变化影响因素。结果表明：洮河流域红旗站1956-2019年径流量整体呈显著减小趋势,1987年发生突变;SWAT模型率定、验证期决定系数分别为0.78、0.79,Nash-Suttcliffe系数分别为0.78、0.77,相对误差均小于10%,模拟效果令人满意;河道径流中游占比最大(50.71%),其次为上游(37.21%),下游占比最小(12.08%),中游是径流量的主要来源;产流量由上游到下游呈减少变化,依次为214.18、179.43、81.16 mm;代桑曲子流域产流量最大,岔河、东峪沟最小;相关性排序为P与Y、Y与R、P与R,且相关性由上游到下游逐渐减弱;气候变化和人类活动对径流变化的贡献率分别为20%和80%,人类活动是主要因素。研究成果有利于揭示洮河流域各区段产水径流变化及影响机理,同时为缺资料地区产流径流时空分析提供理论支撑。     

基于改进降水输入模块的融雪径流模拟:以拉萨河为例

降水是自然界物质循环和水循环的重要组成部分,是高寒地区径流的重要来源,水文模型中降水数据的输入精度对提高高寒地区融雪径流模拟效果具有十分重要的作用。青藏高原地区气象站点较少,站点数据无法全面反映流域内降水时空分布的真实情况,传统的融雪径流模型在地形、风向和水汽等要素对降水垂直分布的影响考虑不够全面,制约了模型在山区融雪模拟以及预测中的应用,因此有必要对模型的降水输入项进行改进,以期提高半干旱高寒地区融雪径流模拟效果。本文基于改进的遥感卫星数据校正理论,开发了适用于半干旱高寒地区的降水输入模块,将其与度日因子模型进行耦合,利用高程分带将降水组合成半网格半站点的降水输入数据驱动模型,并在拉萨河流域进行试验研究。结果表明:降水输入模块能够显著提高降水卫星反演地面降水精度,改进后的融雪模型在率定期和验证期的NSE(Nash-Sutcliffe efficiency coefficient)分别为0.741和0.770,高于原融雪模型的模拟效果,表明改进后的模型能够在流域各个分区获得较为精确的降水数值,融雪径流模拟精度比原模型精度得到提高。总之,耦合降水输入模块的融雪模型可以有效提高降水输入精度,对缺资料半干旱高寒地区融雪模拟具有重要的参考价值。     

三峡库区水循环要素现状评价及预测

基于实测数据和统计资料建立三峡水库分布式水文模型,对三峡库区水循环现状进行评价, 以分析三峡库区范围内降水、径流等水循环要素的空间分布特征,并采用多个全球气候模式的集合平 均模拟结果,利用统计降尺度方法将气候模式与分布式水文模型藕合预估了未来气候变化条件下三峡 库区水循环要素的变化情况。研究结果表明:在现状条件下,除个别地区外三峡库区年降水量和年径 流量的空间分布相对较均匀,且在未来气候变化条件下,相对于历史多年平均值,预计:三峡库区年 平均温度将上升1. 3 qC,年蒸发量将增加2. 8 %,年降水量和年径流量将分别减少0. 8%和8. 2%,径 流量的减少幅度和蒸发量的增加幅度大于降水量的减少幅度,对库区未来的水资源综合管理提出了更 高的要求。     

Sewer modelling based on highly distributed calibration data sets and multi-objective auto-calibration schemes

Pollutant load modelling for sewer systems is state-of-the-art, especially for the estimation of discharged pollutant loads and development of sewer management strategies. However, conventionally obtained calibration data sets are often not exhaustive and have significant drawbacks. In the Graz West catchment area (Graz, Austria), continuous high-resolution long-term online measurements for discharge and pollutant concentration have been carried out since 2002. In this paper, the application of single- and multi-objective auto-calibration schemes based on evolution strategies for a deterministic hydrological pollutant load model will be discussed. Three approaches for pollutant load modelling are examined and compared: using a constant storm weather concentration and two build-up wash-off approaches with basic respectively extended wash-off equations. It is shown that the applied auto-calibration method leads to very satisfying results for both the calibration and the validation data set, and also for the dry and the storm weather runoff. However, until now, convective storms have not been convincingly represented. The build-up wash-off approach using the basic wash-off equation shows the best correlations between measured data and simulation results. As one of the chosen objectives for the multi-objective optimisation reacted highly sensitively to measurement errors, additional improvements can be expected after refining the criteria used in this algorithm.     

The Correlation Between Statistically Downscaled Precipitation Data and Groundwater Level Records in North-Western Turkey

Downscaling of atmospheric climate parameters is a sophisticated tool to develop statistical relationships between large-scale atmospheric variables and local-scale meteorological variables. In this study, the variables selected from the National Centre for Environmental Prediction and National Centre for Atmospheric Research (NCEP/NCAR) reanalysis data set were used as predictors for the downscaling of monthly precipitation in a watershed located in north-western Turkey where station records terminated two decades ago. An Artificial Neural Network (ANN) based approach was used to downscale global climate predictors that are positively correlated to the existing time frame of precipitation data in the basin. The downscaled precipitation information were used to extend the non-existing data from the meteorological station, which were later correlated with groundwater level data obtained from automatic pressure transducers that continuously record depth to groundwater. The results of the study showed that, among a large set of NCEP/NCAR parameters, surface precipitation data recorded at the meteorological station was strongly correlated with precipitation rate, air temperature and relative humidity at surface and air temperature at 850, 500, and 200 hPa pressure levels, and geopotential heights at 850 and 200 hPa pressure levels. The gaps in station data were then filled with the correlations obtained from NCEP/NCAR parameters and a complete precipitation data set was obtained that extended to current time line. This extended precipitation time series was later correlated with the existing groundwater level data from an alluvial plain in order to develop a general relationship that can be used in basin-wide water budget estimations. The proposed methodology is believed to serve the needs of engineers and basin planners who try to create a link between related hydrological variables under data-limited conditions.     

坡面径流阻力计算模式对比研究

坡面流是污染物迁移、土壤侵蚀、泥沙输移的主要动力因素,阻力系数是影响坡面流模拟的重要参数。为比较三种阻力计算模式(阻力系数为常数、以淹没度为变量的Lawrence模型和阻力分割模型)在裸坡、砾石覆盖坡面、植被覆盖坡面三种常见坡面上的适用程度,本文建立了坡面降雨径流模型,对不同类型坡面的产流进行了模拟。坡面径流模型采用扩散波模型,坡面降雨入渗模型采用考虑坡度影响的Green-Ampt模型,当存在植被时,考虑冠层降雨截留损失。结果表明:在裸坡上,三种阻力计算模式均适用;而在有砾石覆盖和植被覆盖的坡面上,考虑阻力系数时空变化的阻力分割模型模拟精度最高。阻力系数对坡面径流流量的影响在坡面汇流的涨水与退水阶段较大,而在稳定阶段很小。对有植被覆盖坡面,降雨强度存在阈值,大于阈值时,不同阻力模式对坡面流模拟结果影响甚微;反之,需选择合适的阻力计算模式,且坡长越长,坡度越缓,降雨强度阈值越大。