窟野河流域水文特性分析

依据水文实测资料和水质监测资料,对窟野河流域降水、径流、泥沙、蒸发、冰情、水质等水文水质因子进行了分析,给出其年内、年际、地域方面的时空变化规律。通过水文水质数据的统计、计算、分析,对窟野河流域水文特性做了论述。     

沙河源水文特性分析

文章采用沙河源头控制站中汤(三)水文站及其控制流域内6个雨量站1970-2016年实测水文资料,分析了近年沙河源头地区天然降水、河道天然径流等水文特性,为进一步研究该流域水文特性变化趋势、水旱灾害预警预报等提供数据支撑。     

影响黄土丘陵区次降水泥沙输移比的水文要素

以桥沟小流域为研究对象,利用该流域不同地貌部位的野外径流场及沟道水文站网观测资料,计算了不同场次降水的泥沙输移比,较为系统地研究了影响桥沟流域次降水泥沙输移比的水文要素。结果表明:土壤前期含水量、流域的降水过程特征、洪峰流量、径流量、水流含沙量是影响次降水泥沙输移比的主要水文要素;提出了表示降水、径流、泥沙对泥沙输移比影响的表征参数,即降水峰现系数、径流侵蚀力和泥沙相对容重。     

西汉水流域水文特性分析

通过对西汉水流域降水、径流、泥沙等水文数据进行统计,分析了西汉水流域水文情势的基本特征和水文要素的地域分布特征。     

漠阳江流域水文特性分析

从降水、蒸发、径流、泥沙、地下水和水环境等方面分析了漠阳江流域的水文特性,可为该流域水资源的开发利用和规划、水环境保护等工作提供参考。     

变化环境下气象水文预报研究进展

随着全球气候变化、下垫面改变及高强度人类活动的不断加剧,流域降水、蒸发、径流等气象水文要素都受到直接性的影响,水文序列的一致性假设不复存在。在变化环境下,传统径流预报方法适用性逐步变差,从而对气象水文的精准预报带来挑战。本文分别从气象水文预报的各个环节——多源降水数据融合、数值天气预报、流域水文模型、参数率定、数据同化、集合预报等方面综述了变化环境下的气象水文预报的研究进展。可以看到,国内外学者围绕上述技术都开展了大量研究,并取得了大量成果。未来针对变化环境下气象水文预报研究,将主要围绕以下方向开展:(1)落地和预报降水精度及时空分辨率的进一步提高;(2)水文模型结构的改进及不确定性分析;(3)水文预报误差的描述方法及其可靠性。     

漠阳江流域水文特性探讨

采用漠阳江流域水文站（陂面站、荆山站、双捷站）和阳春水位站历年的水文资料，进行统计分析，探讨了漠阳江流域的降水、水位、径流、泥沙和蒸发等水文特征的变化规律，为合理开发漠阳江流域水力资源及其治理提供基本的水文资料。     

TRMM卫星降水数据在黄河源区的适用性研究

具有较高时空分辨率的卫星降水数据为研究缺乏地面实测站点流域的水文循环过程提供了有力的支撑.以黄河源区为研究对象,在对比分析2002—2015年TRMM 3B42卫星降水数据与站点实测降水数据的基础上,利用VIC分布式水文模型验证了TRMM降水数据在我国资料稀缺的高寒流域径流模拟的适用性.结果表明,TRMM卫星测雨数据与...     

沙河流域王快水库上游水文要素特性分析

根据沙河流域王快水库上游测站多年的水文资料统计,从流域概况、降水、蒸发、径流、泥沙、水质等方面对该流域的水文要素进行特性分析,研究其水文要素的变化规律。     

叶尔羌河流域水资源及水文特性

介绍了叶尔羌河流域基本情况,根据流域内主要控制站的多年水文资料,从气温、降水、冰川、蒸发、径流、洪水等方面对流域的水文特性进行了分析。     

无测站流域径流预测区域化方法研究进展

无测站流域径流预测是地表水文研究的难题与挑战,而区域化方法,即将水文信息从有测站流域移植至无测站或缺测站流域估算径流量的过程,则为该问题提供了有效的解决办法。由于不同流域地文属性及气候特征各不相同,目前并无通用的方法,回归法、空间近似法及物理相似法是径流预测区域化研究中最常用的三种方法。基于此,本文阐明了三种方法的基本理论,综述了其研究进展、适用性及局限性,分析了区域化研究中常用水文模型及流域特征因子遴选的依据,总结了误差检验及不确定性分析的方法,并展望了径流预测区域化研究的未来发展方向。本文可为无测站流域区域化方法的选择提供基本依据与科学参考。     

资料短缺地区径流模拟研究

以柬埔寨洞里萨湖流域为对象,基于多源降水信息分析、水文模型构建及适应性分析、参数移植研究及检验等,探讨了资料短缺地区的径流模拟问题。结果表明:气候再分析资料集Ag MERRA在洞里萨湖地区的精度较高,VIC模型在该区域的适应性较好,可以用来进行水文模拟;水文模型参数与流域气候和下垫面因子的相关性较好,拟合优度R2都在0. 65以上,移植的可信度较高;在3个验证流域的实测径流过程对比分析表明,基于参数移植方案构建的水文模型能较好地模拟资料短缺地区的流域水文过程。     

Classification of Drainage Basins Based on Readily Available Information

Classification of drainage basins into groups with similar response to meteorological forcing can be very helpful in cases of transfer of hydrological information in space such as in streamflow prediction in ungauged basins. It is also critical for the implementation of the Water Framework Directive and related legislative tools of the EU such as the Flood Directive. The focus is testing the ability to classify drainage basins using climate-based variables and geomorphometric characteristics as predictors. Precipitation is selected as the climate-based variable, since this is commonly measured in the majority of basins. Geomorphometric characteristics include, among others, the average ground slope and drainage density; these are derived from a Digital Terrain Model. The employed methodology involves two steps. In the first step we perform unsupervised classification through using the fuzzy c-means method to identify basin classes that serve as the reference classes in the second step of analysis. A set of hydrological signatures is used in the first step, which includes the runoff ratio, the baseflow index, the slope of the flow duration curve, and the snow day ratio. In the second step we perform supervised classification through using the k-Nearest Neighbour method which maps predictors to basin classes. Last, the success rate of the obtained classification is assessed through using jack-knife re-sampling. Twenty-four gauged basins in mainland Greece are used, which are classified into four classes. The employed methodology proved to be successful in more than 95 % of cases of recognition of the class for an ungauged basin.     

改进的SCS模型在流域径流模拟中的应用

介绍了改进的通用SCS日模型,应用该模型对汉江牧马河等8个流域进行长系列水文模拟,结果表明:模型对于较大径流系数的流域模拟效果较好,而较小径流系数的流域则不够理想;模型不仅仅可用于小流域径流计算,对于较大流域也一样可以取得满意的结果。结合M OD IS遥感数据确定模型参数,为开展无资料地区的水文预报进行了一定的尝试。     

Improvement of Multi-Satellite Real-Time Precipitation Products for Ensemble Streamflow Simulation in a Middle Latitude Basin in South China

The real-time availability of several satellite-based precipitation products has recently provided hydrologists with an unprecedented opportunity to improve current hydrologic prediction capability for vast river basins, particularly for ungauged regions. However, the accuracy of real-time satellite precipitation data remains uncertain. This study aims to use three widely used real-time satellite precipitation products, namely, TRMM Multi satellite Precipitation Analysis real-time precipitation product 3B42 (TMPA 3B42RT), Precipitation Estimation from Remote Sensing Information using Artificial Neural Network (PERSIAN), and NOAA/Climate Precipitation Center Morphing Technique (CMORPH), for ensemble stream flow simulation with the gridded xinanjiang (XAJ) model and shuffled complex evolution metropolis (SCEM-UA) algorithm in the middle-latitude Mishui basin in South China. To account the bias of the satellite precipitation data and consider the input uncertainty, two different methods, i.e. a precipitation error multiplier and a precipitation error model were introduced. For each precipitation input model, the posterior probability distribution of the parameters and their associated uncertainty were calibrated using the SCEM-UA algorithm, and 15,000 ensemble stream flow simulations were conducted. The simulations of the satellite precipitation data were then optimally merged using the Bayseian model averaging (BMA) method. The result shows that in Mishui basin, the three sets of real-time satellite precipitation data largely underestimated rainfall. Streamflow simulation performed poorly when the raw satellite precipitation data were taken as input and the model parameters were calibrated with gauged data. By implementing the precipitation error multiplier and the precipitation error model and then recalibrating the model, the behavior of the simulated stream flow and calculated uncertainty boundary were significantly improved. Furthermore, the BMA combination of the simulations from the three datasets resulted in a significantly better prediction with a remarkably reliable uncertainty boundary and was comparable with the simulation using the post-real-time bias-corrected research quality TMPA 3B42V7. The proposed methodology of bias adjustment, uncertainty analysis, and BMA combination collectively facilitates the application of the current three real-time satellite data to hydrological prediction and water resource management over many under-gauged basins. This research is also an investigation on the hydrological utility of multi-satellite precipitation data ensembles, which can potentially integrate additional more satellite products when the Global Precipitation Measuring mission with 9-satellite constellation is anticipated in 2014.     

GRACE反演近年青藏高原及雅鲁藏布江流域陆地水储量变化

利用2005年至2010年6年的GRACE(Gravity Recovery and Climate Experiment)数据反演,研究了青藏高原地区以及雅鲁藏布江流域的季节及年陆地水储量的变化情况.结果显示:在研究区,伴随着显著地季节性波动,年水储量均有明显的下降趋势.同时,流域GRACE数据反演结果和国际上几种模式的水文模拟结果比较表明,GRACE在两个流域上的反演结果与CPC水文模型模拟结果变化趋势较为一致,但水储量年、季变化幅度偏大,而与GLDAS发布的CLM与VIC模型的结果则相差甚远,主要原因归结为青藏高原地区气候条件复杂导致模型的不确定性及误差较大,而大多水文模型缺乏对地下水变化的模拟能力所致.     

几种典型流域水文模型类比分析

流域水文模型是研究水文自然规律和解决水文实际问题的重要理论基础。按照流域水文模型的基本分类,简单总结分析了国内外几种典型流域水文模型的基本建模思路、适用范围及其优缺点等。在此基础上,以模型效果评价指标为准则,通过对同一流域上不同模型、以及同一模型在不同流域上的应用效果进行类比和分析,提出了在特定流域应该选取比较适用的水文模型以及几种典型水文模型的最佳适用流域。     

Effect of calibration data series length on performance and optimal parameters of hydrological model

In order to assess the effects of calibration data series length on the performance and optimal parameter values of a hydrological model in ungauged or data-limited catchments (data are non-continuous and fragmental in some catchments), we used non-continuous calibration periods for more independent streamflow data for SIMHYD (simple hydrology) model calibration. Nash-Sutcliffe efficiency and percentage water balance error were used as performance measures. The particle swarm optimization (PSO) method was used to calibrate the rainfall-runoff models. Different lengths of data series ranging from one year to ten years, randomly sampled, were used to study the impact of calibration data series length. Fifty-five relatively unimpaired catchments located all over Australia with daily precipitation, potential evapotranspiration, and streamflow data were tested to obtain more general conclusions. The results show that longer calibration data series do not necessarily result in better model performance. In general, eight years of data are sufficient to obtain steady estimates of model performance and parameters for the SIMHYD model. It is also shown that most humid catchments require fewer calibration data to obtain a good performance and stable parameter values. The model performs better in humid and semi-humid catchments than in arid catchments. Our results may have useful and interesting implications for the efficiency of using limited observation data for hydrological model calibration in different climates.     

基于LH-OAT分布式水文模型参数敏感性分析

为了有效进行分布式水文模型参数的优选,消除模型计算过程中的不确定性,更好地理解参数对水文模拟的影响,开展了模型参数敏感性分析。使用LH-OAT方法,对比分析了3个不同的流域中多个目标函数下的分布式物理水文模型——流溪河模型的参数敏感性,将其参数敏感性归为：极敏感,敏感,一般敏感和不敏感4类。研究表明,模型参数的敏感性并不是一成不变的,在不同流域,不同评价目标下,会发生一定程度的改变。     

淮北平原分布式除涝水文模型及应用

针对目前淮北平原除涝水文计算采用的经验排模公式仅考虑了设计净雨和排水面积两个因素,对于下垫面情况复杂的流域不能很好地反映峰量关系的情况,应用GIS技术根据DEM进行流域划分、水流方向确定等处理,并结合流域水文地质图、土壤分布图等建立GIS图层,进而构建淮北分布式水文模型。结果表明,该模型可用于无资料地区的排涝水文计算,应用历史数据对模型参数进行调试,模拟计算精度可达GB/T 22482-2008《水文情报预报规范》的甲级标准。