融雪径流模型及其在黄河唐乃亥站的应用

针对冰雪地区的产流特点，在充分考虑融雪径流形成机制的情况下，提出了以特征温度估算流域积雪及积雪面积分布，建立融雪径流模型。并应用该模型对黄河上游唐乃亥站的月径流过程进行了模拟，在此基础上，进一步探讨了气候变化对该地区径流量的影响。     

融雪径流模型及其在黄河唐乃亥站的应用

针对冰雪地区的产流特点，在充分考虑融雪径流形成机制的情况下，提出了以特征温度估算流域积雪及积雪面积分布，建立融雪径流模型，并应用该模型对黄河上游唐乃亥站的月径流过程进行了模拟，在此基础上，进一步探讨了气候变化对该地区径流量的影响。     

新安江模型在唐乃亥站洪水预报中的应用

基于黄河上游玛曲-唐乃亥站流域降雨及洪水特性,筛选玛曲站和唐乃亥站1998-2014年共9场洪水资料,玛曲、军功、玛沁、河南、唐乃亥5站的时段雨量资料,以及军功水文站蒸发资料,利用泰森多边形法计算各站所占面积权重,运用新安江模型建立洪水预报方案。结果表明:次洪率定所得参数对检验期洪水模拟效果良好,率定参数适合该流域洪水预报;检验期洪水确定性系数均在0.9以上且合格率达到100%,故新安江模型可以作为唐乃亥站降雨径流预报的一个可靠手段,预报结果可用于正式预报。     

气候变化和土地利用变化对黄河源区径流变化的累积影响评估

径流变化归因是理解水文循环过程的关键科学问题，传统的Budyko框架多着眼于2个时段的比较，缺乏对影响因素累积影响的刻画。以黄河源区重点水文站点为例，基于时变参数的Budyko框架深入分析了1960—2016年气候变化和土地利用变化对源区径流变化的累积影响，揭示了径流演变的内在机制，结果表明：黄河源区吉迈站年径流无显著变化，玛曲和唐乃亥年径流显著减少。气候变化对3个站点控制流域径流的影响存在时间波动，气候变化在1973—1990、2004年之后增加了径流，而1991—2003年减少了径流，其累积影响值在1990年附近达到最大(15 mm以上),在2003年达到最小(3个站点分别为-10.85、-20.91、-21.66 mm);除吉迈站部分时段外土地利用变化均减少了径流，对3个站点的最终累积影响值分别为-9.17、-32.09、-31.65 mm。气候变化对吉迈站径流变化起了重要作用，而土地利用变化对玛曲和唐乃亥站的累积影响更大。     

三江源区径流演变规律分析

通过线性回归、滑动平均、Mann-Kendall检验、累积距平、滑动t检验和Morlet小波分析等方法分析了三江源区1956—2012年的年径流量演变规律。结果表明: 57 a来直门达、吉迈和香达站的年径流量呈上升趋势,唐乃亥站的年径流量呈下降趋势,直门达站的年径流量通过显著性检验;直门达和吉迈站均在2004年发生显著性均值突变,其余站点突变不显著;三江源区年径流量均存在6~8 a和23 a左右的主周期,以23 a左右时间尺度上的信号最强,周期相位变化均存在3个偏多期和2个偏少期。研究结果可为我国中下游的水资源保护与管理提供参考依据。     

基于Elman网络的黄河源区径流评估模型

黄河源区来水量对黄河上游乃至整个流域供水有重要影响,研究黄河源区汛期径流变化规律和来水趋势,对黄河流域水量持续利用和优化配置有重要作用.针对黄河唐乃亥水文站近48 a(1959～2006年)径流流量及年降雨情况,利用反馈Elman网络,尝试建立了黄河源区汛期径流评估模型.并利用matlab7所提供的神经网络工具箱对其进行了仿真实验.预报结果表明,该模型能较好地反映唐乃亥水文站汛期径流量的规律.     

基于Elman网络的黄河源区枯季径流预报研究

采用反馈Elman网络对黄河唐乃亥及玛曲两站1959～2003年年降水量及径流量进行了分析,建立了基于反馈神经网络的黄河源区枯季径流预报模型.利用matlab7神经网络工具箱对黄河源区唐乃亥站枯季径流量进行了预报.结果表明,所建立的ANN(7,7,15,7)模型预报结果精度高,容错能力强,是枯季径流预报的有效手段.     

1950-2011年黄河干流水沙关系变化研究

采用黄河干流主要控制水文站唐乃亥、兰州、头道拐、龙门、潼关、花园口、高村、艾山和利津站的实测径流量和输沙量资料,借助Mann-Kendall趋势检验法、双累积曲线法和Pearson相关分析等方法,探讨50余年来黄河流域不同时段、不同河段水沙关系的变化特征。结果表明:唐乃亥站径流量和输沙量无长期变化趋势,黄河干流自兰州以下各站年径流量和年输沙量均表现出显著下降趋势。借助花园口站实测径流量与输沙量双累积曲线知,2000-2011年无降水影响时的累积减沙量为61.602亿t。径流量和输沙量呈正相关关系,沿程各站相关系数r∈(0.512,0.664),不同年代水沙关联性有较大差别。黄河上中下游之间径流量、输沙量均呈现显著正相关,其相关系数分别为r∈(0.725,0.904)、r∈(0.887,0.918)。不同年代中游来水来沙量对下游径流量和输沙量的贡献率存在较大差异,在2000-2009年达到最小值。     

黄河上游龙羊峡以上大型水电站工程可能最大洪水估算初探

在分析黄河龙羊峡以上河段及邻近地区的大暴雨和气象资料的基础上,采用在龙羊峡水电站工程可能最大洪水(PMF)估算中使用的简化方法,即利用历史大洪水反推PMF的设计方法,先估算黄河上游玛曲水文站、唐乃亥水文站以上流域PMF,然后以玛曲站和唐乃亥站为依据站,取面积为权数进行线性内插,推求黄河上游龙羊峡以上大型水电站工程PMF。经与黄河上游已建大型水电站工程PMF成果比较,经合理性分析最终确定黄河龙羊峡以上大型水电站工程PMF成果。     

基于IHA的黄河源区水文情势及环境流变化

基于黄河源区唐乃亥及玛曲两个水文站1961—2008年的逐日径流数据,利用IHA软件,从河流水文指标、环境流组成以及生物多样性方面分析了黄河源区水文情势和环境流变化情况。结果表明:(1)受干扰后,唐乃亥及玛曲站分别有17、14个水文指标发生了中度改变,分别占指标总数的53.1%、43.8%;(2)两站环境流中大洪水事件逐渐消失,流量结构组成趋于单一化,并逐步向以高流量脉冲及枯水流量事件为主发展;(3)受干扰后黄河源区生物多样性呈下降趋势,两站的生物多样性指数均值均减少到10。     

1975－2015年洪泽湖水沙变化趋势及成因分析

淮河流域洪涝灾害频繁,洪泽湖对其防洪除涝起关键性作用。掌握洪泽湖水沙变化趋势及突变点对流域水资源管理、水沙调节有重要的现实意义。利用入、出洪泽湖各支流代表水文站1975-2015年实测年径流量和年输沙量数据,分析入、出洪泽湖水量和沙量分布特征。通过Mann-Kendall(M-K)秩相关检验法和Pettitt突变点识别法研究入湖、出湖水沙量年际变化趋势和突变点。在此基础上,从流域降雨、水资源开发利用和水库滞沙三个方面分析了洪泽湖水沙变化的主要影响因素。研究表明:洪泽湖入湖、出湖水量年际变化趋势一致,无明显减小趋势,且无显著突变点。入湖沙量有小幅减小趋势,出湖沙量M-K统计值超过95%显著性水平,有明显减小趋势。入湖、出湖沙量发生突变的年份为1991年。对影响因素的分析得到:降雨量变化是水量变化的重要影响因素。1993-2015年,入湖水量呈不明显减小趋势则与流域用水量明显增加、水资源开发利用程度不断提高有关。上游水库建设是导致洪泽湖沙量有明显减小趋势的主要原因,1991年治淮工程的实施,水库复建和水土保持等措施是沙量突变的主要原因。     

Impact of Climate Change on Water Resources in the Tarim River Basin

The plausible association between climate change and the variability of water resources in the Tarim River basin, west China is investigated in this study. The long-term trend of the hydrological time series including temperature, precipitation, and streamflow are detected by using both parametric and nonparametric techniques. The possible association between the El Niño/Southern Oscillation (ENSO) and these three kinds of time series are tested. This study enhances the knowledge of the climate change impact on water resources in the Tarim River basin. The conclusion obtained in this investigation shows that the temperature experienced a significant monotonic increase at the 5% level of significance during the past 50 yr, and precipitation also exhibited an upward tendency during the past several decades. A significant jump is also detected for both time series around 1986. This may be resulted from the possible impact of climate change, although the interior climate mechanism needs further investigation. Although precipitation and the streamflow from the headwater of the Tarim River exhibited significant increase, decreasing trend has been detected in the streamflow along the mainstream of the river. It implies that anthropogenic activities instead of the climate change dominated the streamflow cessation and the drying-up of the river. Results also showed that no significant association exists between the ENSO and the temperature, precipitation and streamflow in the study area. This conclusion shows that the water curtailment, river desiccation, and ecosystem deterioration in the Tarim River basin may be mainly resulted from the impact of human activities.     

Identification of Streamflow Response to Climate Change and Human Activities in the Wei River Basin,China

In this study, the calibration and validation period with stable underlying surface conditions was determined by using a statistically significant change point of the annual streamflow in several catchments of the Wei River basin (WRB). The effects of climate changes and human activities on streamflow were estimated by using the sensitivity-based method and the dynamic water balance model, respectively. The contributions of climate effects and human activities effects on streamflow were also investigated. The results showed that almost all the catchments exhibited significant decreasing trend of streamflow in the early 1990s. The streamflow was more sensitive to changes in precipitation than changes in potential evapotranspiration (PET). Effects of climate due to changes in precipitation and PET are weak in Linjiacun, Weijiabao and Xianyang catchments, while it is strong in the catchments controlled by other hydrological stations, accounting for more than 40 % of streamflow reduction. Effects of human activities on streamflow in Linjiacun, Weijiabao, Xianyang and Zhangjiashan catchments accounted for more than 50 % of the streamflow reduction. The study provides scientific foundation to understand the causes of water resources scarcity and useful information for the planning and management of water resources in the ecological fragile arid area.     

Improving Annual Streamflow Prediction by Extracting Information from High-frequency Components of Streamflow

Annual streamflow prediction is of great significance to the sustainable utilization of water resources, and predicting it accurately is challenging due to changes in streamflow have strong nonlinearity and uncertainty. To improve the prediction accuracy of annual streamflow, this study proposes a new hybrid prediction model based on extracting information from high-frequency components of streamflow. In the proposed model, the original streamflow data is decomposed by ensemble empirical mode decomposition (EEMD) into several intrinsic mode functions (IMFs) with different frequencies. Then, the dominant component and residual component are identified from the high-frequency components IMF1 and IMF2 using singular spectrum analysis (SSA), and the residual components are accumulated as a new component. Finally, all the components, including the new component that is not noise, are modelled by support vector machine (SVM), and the SVM is optimized by grey wolf optimizer (GWO). To analyse and verify the proposed model, the annual streamflow data are collected from the Liyuan River and Taolai River in the Heihe River Basin, and six models, autoregressive integrated moving average (ARIMA), cross validation (CV)-SVM, GWO-SVM, EEMD-ARIMA, EEMD-GWO-SVM and modified EEMD-GWO-SVM are considered as comparison models. The results indicate that the prediction performance of the proposed model is obviously better than that of other reference models, and extracting valuable information from high-frequency components can effectively improve annual streamflow prediction. Thus, the high-frequency components contained in the original streamflow series have an important impact on obtaining accurate streamflow prediction, and the proposed model makes full use of the high-frequency components and provides a reliable method for streamflow prediction.

     

Vulnerability Analysis of Future Public Water Supply Under Changing Climate Conditions: A Study of the Moy Catchment,Western Ireland

An application of the Water Evaluation and Planning tool Version 21 (WEAP21) is developed to analyse the vulnerability of the future public water supply in the River Moy catchment, western Ireland. The River Moy’s future hydrology is modelled using the WEAP21 integrated rainfall runoff module and an ensemble of statistically downscaled future climate series. This approach facilitates the identification of the most vulnerable future public water supplies without being constrained by the availability of historically observed streamflow records. The model is calibrated by linking the model-independent parameter estimation tool (PEST) with the hydrological model and verified by reproducing observed streamflow records. This research suggests an emerging vulnerability to water stress of the public water supply sector under the four modelled scenarios, for areas which currently have plenty of water available. These results present a basis for future planning and management of the Moy catchment and its water resources.     

North Atlantic Oscillation as a Cause of the Hydrological Changes in the Mediterranean (Júcar River,Spain)

Significant changes in the Júcar River Basin District’s hydrology in the Mediterranean side of Spain, have been observed during last decades. A statistical change-point in the year 1980 was detected in the basins’ hydrological series in the main upper river, Júcar and Túria basins. In the study scope are, the North Atlantic Oscillation (NAO) is linked with the winter precipitations in the Upper Basins, which are here responsible for the major part of streamflow. So changes in the rainfall has an important effect in the natural river flows. The statistical analysis detected a change at NAO’s seasonal pattern, what means a considerable reduction of winter rainfalls in the Upper River basins located in the inland zone which is simultaneously the water collection and reservoirs area (a???40% of water resources availability since 1980). Hydro-meteorological data and a Water Balance Model, Patrical, have been used to assess these water resources’ reduction. Results points out to the change in the Basin’s precipitation pattern in the inland areas (upper basins), associated to Atlantic weather patterns, as the main cause, while it has not been detected in the coastal areas. All these changes implies water stress for water resources planning, management and allocation, where more than 5.2 million people and irrigation of 390,000 ha are served, joint to the time variability, an important territorial imbalance exists between resources and demands. Thus, in the main upper basins, with the biggest streamflow’s reductions, locate the largest reservoirs in terms of water resources collection and reserves.     

Artificial neural network model for synthetic streamflow generation

Time series of streamflow plays an important role in planning, design and management of water resources system. In the event of non availability of a long series of historical streamflow record, generation of the data series is of utmost importance. Although a number of models exist, they may not always produce satisfactory result in respect of statistics of the historical data. In such event, artificial neural network (ANN) model can be a potential alternative to the conventional models. Streamflow series, which is a stochastic phenomenon, can be suitably modeled by ANN for its strong capability to perform non-linear mapping. An ANN model developed for generating synthetic streamflow series of the Pagladia River, a major north bank tributary of the river Brahmaputra, is presented in this paper along with its comparison with other existing models. The comparison carried out in respect of five different statistics of the historical data and synthetically generated data has shown that among the different models, viz., autoregressive moving average (ARMA) model, Thomas-Fiering model and ANN model, the ANN based model has performed better in generating synthetic streamflow series for the Pagladia River.     

Detection of Streamflow Change in the Susquehanna River Basin

Streamflow statistics are commonly used for purposes of planning and managing water resources in the Susquehanna River Basin. For accurately estimating streamflow statistics, it is important to identify whether there are increasing or decreasing changes during the period of records and whether the change is gradual or abrupt. This study employs repeated monotonic trend tests with varying beginning and ending time for detecting changes in streamflow in tributaries within the Susquehanna River Basin. The method is employed to analyze long-term streamflow trends and detect change for annual minimum, median, and maximum daily streamflow for eight unregulated watersheds within the basin. Monthly baseflow and storm runoff are investigated. The results show a considerable increase in annual minimum flow for most of the examined watersheds and a noticeable increase in annual median flow for about half of the examined watersheds. Both these streamflow increases were abrupt, with only a few years of transition centered around 1970. The abrupt change in annual minimum and median flows appears to occur in the summer and fall seasons. The abrupt change in annual minimum and median flows is due to increased flows in the summer and fall seasons. The results also indicate there is no long-term significant increasing or decreasing change in annual maximum flow in the examined watersheds.     

Assessment of global warming impacts on water resources and ecology of a river basin in Japan

Global warming may cause serious problems in the world. However, the influence of water-related factors, such as water resources and basin ecology, due to global warming has not been comprehensively investigated. In this study, a distributed hydrological and environmental model is applied to assess the impacts of global warming on water resources and ecology of the Nagara River in Japan. With GCM outputs for the two periods, 1979 to 2000 and 2079 to 2100, the model simulation mainly reveals four aspects of the influences of global warming: (i) precipitation and streamflow discharge increase in summer; (ii) air temperature and water temperature rise; (iii) fish habitats are improved, except in summer; and (iv) the boundaries of the crop and vegetation move to higher elevations.     

1959-2011年北洛河上游流域径流量及其组分变化趋势和时间分配特征

以实测水文数据为基础,分析了区域水土保持措施实施和植被恢复背景下北洛河上游黄土丘陵沟壑区流域1959-2011年间径流和基流数量变化、时间分配规律和阶段特征,对流域水土保持和生态平衡、水资源保护和利用具有指导和借鉴意义。结果表明:志丹、吴起、刘家河3个水文站的年均径流深分别为37.6、27.1、31.8 mm。年均地表径流量和基流量所占比例3站平均为63.8%和36.2%。3站的年径流量和地表径流量全部表现为极显著减少趋势(P<0.001),而且地表径流量决定了总径流量的变化程度。3站基流量呈增加(P<0.01)(吴起站、刘家河站)或稳定态势(志丹站)。径流量及其组分年内分配均表现为"双峰型"。随时间推移,径流量月内分配不均匀性减弱,夏、汛期径流量占年径流量的比例急剧降低。3站冬、春季枯水期基流量均为显著增加态势,而夏、秋季稳定。1959-2011年在水土保持措施的实施和生态恢复背景下,流域径流及其组分的数量和时间分配发生了很大变化,流域水循环要素比例趋于合理。