A cascade approach to continuous rainfall data generation at point locations

High-resolution temporal rainfall data sequences serve as inputs for a range of applications in planning, design and management of small (especially urban) water resources systems, including continuous flow simulation and evaluation of alternate policies for environmental impact assessment. However, such data are often not available, since their measurements are costly and time-consuming. One alternative to obtain high-resolution data is to try to derive them from available low-resolution information through a disaggregation procedure. This study evaluates a random cascade approach for generation of high-resolution rainfall data at a point location. The approach is based on the concept of scaling in rainfall, or, relating the properties associated with the rainfall process at one temporal scale to a finer-resolution scale. The procedure involves two steps: (1) identification of the presence of scaling behavior in the rainfall process; and (2) generation of synthetic data possessing same/similar scaling properties of the observed rainfall data. The scaling identification is made using a statistical moment scaling function, and the log–Poisson distribution is assumed to generate the synthetic rainfall data. The effectiveness of the approach is tested on the rainfall data observed at the Sydney Observatory Hill, Sydney, Australia. Rainfall data corresponding to four different successively doubled resolutions (daily, 12, 6, and 3 h) are studied, and disaggregation of data is attempted only between these successively doubled resolutions. The results indicate the presence of multi-scaling behavior in the rainfall data. The synthetic data generated using the log–Poisson distribution are found to exhibit scaling behaviors that match very well with that for the observed data. However, the results also indicate that fitting the scaling function alone does not necessarily mean reproducing the broader attributes that characterize the data. This observation clearly points out the extreme caution needed in the application of the existing methods for identification of scaling in rainfall, especially since such methods are also prevalent in studies of the emerging satellite observations and thus in the broader spectrum of hydrologic modeling.     

梯级水库优化调度的有后效性动态规划模型及应用

建立了梯级水库在洪水期间发电调度的优化模型,由于含有河道洪水演进方程,该模型成为一类有后效性的动态规划模型.提出了两种新的解法——多维动态规划近似解法与有后效性动态规划逐次逼近算法.实例研究表明:这两种解法可行,结果合理,特别是逐次逼近算法计算更快速,是求解这类问题的有效的方法.     

人工免疫系统在梯级水库群短期优化调度中的应用

免疫起源于抗感染的研究,是一种机体识别和排斥抗原性异物的生理功能。现代仿生技术将免疫应用到解决非线性优化问题中,形成了独特的人工免疫系统(AIS),AIS用抗体代表问题的可行解,用抗原代表问题的约束条件和目标函数,采用期望繁殖率来定义父体选择的概率进行随机搜索全局最优解。将AIS应用到梯级水库群短期(日)优化调度的研究中,经过对某梯级水库群的仿真计算,认为其结果是合理和可实际应用的。     

水电站水库群模糊优化调度模型与目标协调－模糊规划法

利用大系统和模糊数学规划理论与方法,分析和探讨了水电站水库群模糊优化调度问题,建立了水电站水库群模糊优化调度模型,提出一种目标协调-模糊规划(IB-FP)法.理论分析和实例计算表明,所建立的模糊优化调度模型和提出的IB-FP法是可行和有效的.     

Numerical Physical Mechanism and Model of Turbulent Cascades in a Barotropic Atmosphere

In a barotropic atmosphere, new Reynolds mean momentum equauons including turbulent viscosit,dispersion, and instability are used not only to derive the KdV-Burgers-Kuramoto equation but also to analyze the physical mechanism of the cascades of energy and enstrophy. It shows that it is the effects of dispersion and instability that result in the inverse cascade. Then based on the conservation laws of the energy and enstrophy, a cascade model is put forward and the processes of the cascades are described.     

梯级水库设计洪水最可能地区组成法计算通式

利用Copula函数建立各分区洪水的联合分布,基于联合概率密度最大原则,推导得到最可能地区组成法的计算通式,并用来推求梯级水库下游断面的设计洪水。选择清江流域水布垭-隔河岩-高坝洲梯级水库为例,开展了验证和方法比较研究。结果表明:最可能地区组成法计算得到的设计洪水值位于同频率地区组成法多方案计算结果的区间之内;受清江梯级水库调洪的影响,宜都断面设计洪水的削峰率十分显著,最可能地区组成法推求100年一遇设计洪水的削峰率达到30.2%。该法具有较强的统计基础,组成方案唯一,结果合理可行,为复杂梯级水库设计洪水的计算提供了一种新途径。     

澜沧江—湄公河水电梯级开发的生态影响

针对次澜沦江－湄公河区域快速增长的能源需求,以及国际社会对该流域水电开发的经济、生态和社会问题的关注,集中分析了流域干流水电梯级开发对生态环境的综合影响,提出了能满足各流域国对能源、防洪、灌溉、水生生态保护和减轻海水倒灌等多方面需求的对策措施。     

梯级水电开发对生态地质环境影响评价的思路与方法初探

笔者在充分调研和综合分析研究金沙江、雅砻江、大渡河水电工程区岸坡生态地质环境条件和主要生态环境地质问题及其环境演化效应的基础上.按照分类评价思想和原理.初步探讨了流域梯级水电工程开发对生态地质环境影响评价的思路与方法,初步提出以斜坡(岸坡)稳定性评价子系统、水土流失与水库淤积评价子系统、生态环境演化评价子系统和社会经济发展影响子系统等四大类子系统为主干的梯级水电开发对生态地质环境影响评价系统.初步建立了四大类评价指标体系,讨论了评价方法与成果表达方式,供大家讨论。     

应对干旱的黄河干流梯级水库群协同调度

科学控制梯级水库蓄泄过程是减少旱灾损失的重要手段。以减少干旱年份流域缺水量和优化缺水时空分布为目标,构建应对干旱的梯级水库群多时空尺度协同优化调度模型。采用交互式与改进粒子群优化方法,外层寻求多年调节水库旱限水位最优控制,内层优化梯级水库群年内蓄泄过程,实现流域水资源年际调控、年内优化、库群协同、空间协调。以2014年的黄河流域重旱为例,通过模型优化提出2012—2014年龙羊峡水库旱限水位及梯级水库群年内蓄泄过程,结果表明:通过龙羊峡水库旱限水位控制实现跨年度补水,控制各年度缺水率在4.9%~5.7%之间,通过水库群出库过程优化控制不同区域各时段缺水均匀分布,将农业缺水率控制在7.0%~11.0%之间,显著减轻了旱灾损失。     

Estimation for partially observed Markov processes

Many stochastic process models for environmental data sets assume a process of relatively simple structure which is in some sense partially observed. That is, there is an underlying process (X_n, n 0) or (X_t, t 0) for which the parameters are of interest and physically meaningful, and an observable process (Y_n, n 0) or (Y_t, t 0) which depends on the X process but not otherwise on those parameters. Examples are wide ranging: the Y process may be the X process with missing observations; the Y process may be the X process observed with a noise component; the X process might constitute a random environment for the Y process, as with hidden Markov models; the Y process might be a lower dimensional function or reduction of the X process. In principle, maximum likelihood estimation for the X process parameters can be carried out by some form of the EM algorithm applied to the Y process data. In the paper we review some current methods for exact and approximate maximum likelihood estimation. We illustrate some of the issues by considering how to estimate the parameters of a stochastic Nash cascade model for runoff. In the case of k reservoirs, the outputs of these reservoirs form a k dimensional vector Markov process, of which only the kth coordinate process is observed, usually at a discrete sample of time points.