贝叶斯概率水文预报系统在中长期径流预报中的应用

采用贝叶斯概率水文预报理论制订水电站水库中长期径流预报模型,以概率分布的形式定量地描述水文预报的不确定度,探索概率水文预报理论及其应用价值。采用气象因子灰关联预报模型处理输入因子的不确定度,将实时气象信息和历史水文资料有效结合,突破传统确定性预报方法在信息利用和样本学习方面的局限性,以提高水文预报的精确度。以丰满水电厂水库为例对所建模型进行检验,模拟计算结果表明,该模型与确定性径流预报方法相比,不仅有利于决策人员定量考虑不确定性,而且在期望意义上提高了径流预报精度,具有较高的应用价值。     

贝叶斯概率水文预报简介

基于贝叶斯理论的概率水文预报，在于应用贝叶斯理论的优点：它能综合考虑各方面的不确定性，并以分布函数形式描述水文预报的不确定度。从而，能较好地满足优化决策的需要。     

水文集合预报试验及其研究进展

水文集合预报是一种既可以给出确定性预报值,又能提供预报值的不确定性信息的概率预报方法。简述了水文集合预报试验(Hydrologic Ensemble Prediction Experiment,HEPEX)国际计划的主要研究内容,回顾了HEPEX研究进展,分析了对水文预报发展有重要意义的3个HEPEX前沿研究:降尺度研究、集合预报系统研究以及不确定性研究。研究表明,动力-统计降尺度法和高分辨率"单一"模式及低分辨率集合相结合是HEPEX未来研究的方向。     

考虑降水预报的三峡入库洪水集合概率预报方法比较

为了考虑预见期内降水预报的不确定性对洪水预报的影响,采用中国气象局、美国环境预测中心和欧洲中期天气预报中心的TIGGE(THORPEX Interactive Grand Global Ensemble)降水预报数据驱动GR4J水文模型,开展三峡入库洪水集合概率预报,分析比较BMA、Copula-BMA、EMOS、M-BMA 4种统计后处理方法的有效性。结果表明:4种统计后处理方法均能提供一个合理可靠的预报置信区间;其期望值预报精度相较于确定性预报有所提高,尤其是水量误差显著减小;M-BMA方法概率预报效果最佳,它能够考虑预报分布的异方差性,不需要进行正态变换,结构简单,应用灵活。     

基于贝叶斯理论的水文不确定性分析研究进展

水文过程受众多自然和人为因素影响,决定了其变化的极端复杂性,表现为确定性的动态规律与不确定性的统计规律共存。水文不确定性分析的理论和方法在认识水文规律中发挥着重要作用,其中贝叶斯作为一种主要理论方法在水文水资源相关问题的研究中得到了较广泛的应用。本文评述了贝叶斯理论在水文频率分析、水文预报、确定性和不确定性方法耦合等研究中的进展,对基于贝叶斯理论的水文不确定性重点研究内容进行了展望。     

基于IBUNE方法的水文模型不确定性分析

在贝叶斯理论框架下,根据一种可结合多个水文模型给出模拟或预报结果的IBUNE方法探讨了水文模型的输入、参数以及结构的不确定性问题。将SCEM-UA算法和EM算法嵌入新安江和TOPMODEL水文模型用于参数优化和模型平均,进而将输入与参数的综合不确定性处理后得到的预报量后验分布进行多模型综合,据此对水文模型的不确定性及其对水文模拟结果的影响进行评价。以湖南洣水流域龙家山水文站以上集水区域为例进行了应用研究,结果表明,IBUNE方法能够有效估计水文模型的不确定性,并能给出合理的概率预报区间。     

确定性水文预报模型的实时校正

近二十年来,确定性水文预报模型发展很快,并且已经具备了一定的实用水平。然而,随着水文自动测报系统的建立,已经能够使人们在作业预报中源源不断地获得最新的信息。因此,在洪水预报中也应当充分利用这一新的有利条件,借助于必要数学手段,在现有确定性模型的基础上,使模型具备实时校正能力,这就是我们开展这项研究工作的问题所在。现就实时校正模型的建立及应用等分别介绍如下。在研究工作中,选用了三水源新安江模     

不同分布式水文模型在大凌河中游对比运用研究

不同水文模型在不同流域都具有一定的适用性,为对比分布式水文模型SWAT模型和VIC模型在大凌河中游的适用性及模拟精度,以大凌河中游大城子水文站以上流域为研究区域,基于大城子水文站2000-2010年水文数据,对比分析两种分布式水文模型在大凌河中游的适用性及模拟精度。研究成果表明:SWAT模型更适合于大凌河中游的水量模拟,SWAT模型模拟相对误差均值为5.21%,低于VIC模型模拟的相对误差(相对误差均值为8.01%),且SWAT模型模拟的确定性系数均值为0.74,优于VIC模型模拟的确定系数(确定系数均值为0.68)。研究成果对于大凌河中游水文模拟及流域水文预报预警提供参考价值。     

电感耦合等离子体光谱法测定农业地质调查土壤样品中铈的不确定度评定

采用《测量不确定度评定与表示指南》，以等离子体发射光谱法测定土壤中的稀土元素铈为例，对测定结果进行不确定度评定。分析了不确定度的重要来源，包括溶液制备过程中引入的不确定度、样品称量引入的不确定度、标准物质外标法测量不确定度及仪器重复测定的不确定度。提供了引入不确定度各参数的采集和计算方法，对各不确定度分量进行分析计算，最后合成标准不确定度，通过乘以95％概率下的扩展因子2，获得测量结果的扩展不确定度。     

概化的Tank模型及其在龙羊峡水库汛期旬平均入库流量预报中的应用

Tank模型（又称为水箱模型），是一种用于流域径流预报的确定性水文模型，根据龙羊峡水库入库主要产流区－－黄河上游唐乃亥水文站以上流域下垫面条件下产汇流特性，将其概化为以降雨量为输入，径流量为输出的单孔出流的线性水箱，工用于该水库汛期旬平均入库流量的预报，经对历史资料进行拟合和试验预报的 结果表明，该模型具有较高的预报精度，现已应用于黄河上游龙羊峡水库汛期旬平均入库来水量的中期预报中，取得了十分显著的经济效益。     

Efficient Monte Carlo Simulation of parameter sensitivity in probabilistic slope stability analysis

Monte Carlo Simulation (MCS) method has been widely used in probabilistic analysis of slope stability, and it provides a robust and simple way to assess failure probability. However, MCS method does not offer insight into the relative contributions of various uncertainties (e.g., inherent spatial variability of soil properties and subsurface stratigraphy) to the failure probability and suffers from a lack of resolution and efficiency at small probability levels. This paper develop a probabilistic failure analysis approach that makes use of the failure samples generated in the MCS and analyzes these failure samples to assess the effects of various uncertainties on slope failure probability. The approach contains two major components: hypothesis tests for prioritizing effects of various uncertainties and Bayesian analysis for further quantifying their effects. Equations are derived for the hypothesis tests and Bayesian analysis. The probabilistic failure analysis requires a large number of failure samples in MCS, and an advanced Monte Carlo Simulation called Subset Simulation is employed to improve efficiency of generating failure samples in MCS. As an illustration, the proposed probabilistic failure analysis approach is applied to study a design scenario of James Bay Dyke. The hypothesis tests show that the uncertainty of undrained shear strength of lacustrine clay has the most significant effect on the slope failure probability, while the uncertainty of the clay crust thickness contributes the least. The effect of the former is then further quantified by a Bayesian analysis. Both hypothesis test results and Bayesian analysis results are validated against independent sensitivity studies. It is shown that probabilistic failure analysis provides results that are equivalent to those from additional sensitivity studies, but it has the advantage of avoiding additional computational times and efforts for repeated runs of MCS in sensitivity studies.     

Stochastic prediction in geomorphology using Bayesian inference models

Bayesian inference modeling may be applied to empirical stochastic prediction in geomorphology where outcomes of geomorphic processes can be expressed by probability density functions. Natural variations in process outputs are accommodated by the probability model. Uncertainty in the values of model parameters is reduced by considering statistically independent prior information on long-term, parameter behavior. Formal combination of model and parameter information yields a Bayesian probability distribution that accounts for parameter uncertainty, but not for model uncertainty or systematic error which is ignored herein. Prior information is determined by ordinary objective or subjective methods of geomorphic investigation. Examples involving simple stochastic models are given, as applied to the prediction of shifts in river courses, alpine rock avalanches, and fluctuating river bed levels. Bayesian inference models may be applied spatially and temporally as well as to functions of a random variable. They provide technically superior forecasts, for a given shortterm data set, to those of extrapolation or stochastic simulation models. In applications the contribution of the field geomorphologist is of fundamental quantitative importance.     

水文模型参数区域化研究进展

参数区域化方法是解决资料缺乏地区水文模拟和预报的有效手段,主要包括回归法、空间邻近法和属性相似法三类方法,可将有资料流域的水文模型参数移用到资料缺乏流域。首先回顾了区域化方法的基本原理和应用方法,并分析了三类主要区域化方法的适用性。从流域特征因子、水文模型及参数、不确定性探讨三个方面综述了区域化方法的研究进展。分析发现,当前区域化方法缺乏完善的理论基础,流域特征因子选择存在主观性,水文模型及参数的适用性方面研究不足。最后展望了未来的研究重点：（1）多维度适用性比较;（2）水文过程和参数的空间分布规律;（3）参数的尺度问题;（4）参数区域化的不确定性问题。     

Probabilistic multi-model ensemble prediction of Indian summer monsoon rainfall using general circulation models: A non-parametric approach

Probabilistic prediction has the ability to convey the intrinsic uncertainty of forecast that helps the decision makers to manage the climate risk more efficiently than deterministic forecasts. In recent times, probabilistic predictions obtained from the products from General Circulation Models (GCMs) have gained considerable attention. The probabilistic forecast can be generated in parametric (assuming Gaussian distribution) as well as non-parametric (counting method) ways. The present study deals with the non-parametric approach that requires no assumption about the form of the forecast distribution for the prediction of Indian summer monsoon rainfall (ISMR) based on the hindcast run of seven general circulation models from 1982 to 2008. Probabilistic prediction from each of the GCM products has been generated by non-parametric methods for tercile categories (viz. below normal (BN), near-normal (NN), and above normal (AN)) and evaluation of their skill is assessed against observed data. Five different types of PMME schemes have been used for combining probabilities from each GCM to improve the forecast skill as compared to the individual GCMs. These schemes are different in nature of assigning the weights for combining probabilities. After a rigorous analysis through Rank Probability Skill Score (RPSS) and relative operating characteristic (ROC) curve, the superiority of PMME has been established over climatological probability. It is also found that, the performances of PMME1 and PMME3 are better than all the other methods whereas PMME3 has showed more improvement over PMME1.     

跨流域引水受水水库最优调度决策的理论分析

针对跨流域调水工程的实时调度决策问题,考虑受水水库的供水效益与引水成本,建立受水水库实时调度的理论分析框架,制定最优引、供水决策,分析预报不确定性对调度决策的影响,提出预报信息可利用准则。辽宁省大伙房应急入连工程的应用表明:若受水水库可用水量较少,引水后水库当前时段供水效益与时段末蓄水效益均增加,最优决策满足引水边际成本、供水边际效益与蓄水边际效益三者相等;随受水水库可用水量增多,水库按需供水,引水仅提升蓄水效益,最优决策使引水边际成本等于蓄水边际效益。若水库期望蓄水量较小,水库缺水概率较大,预报信息可利用性取决于可接受缺水风险;反之,水库弃水概率较大,预报信息可利用性取决于可接受弃水风险。     

长江上游干支流洪水遭遇分析

目前洪水遭遇研究仅限于简单的实测资料统计分析,尚缺系统有效的理论方法.基于多维Copula函数分别建立金沙江屏山站、岷江高场站、嘉陵江北碚站以及长江宜昌站的洪水发生时间和量级的联合分布.以此方法估计干支流洪水发生时间和量级的遭遇可能性及条件概率,并与实测资料的统计结果进行比较.结果表明,模型计算结果与实测相吻合,说明该...