Use of Nash's IUH and DEMs to identify the parameters of an unequal‐reservoir cascade IUH model

Under the assumption that hydrograph generation was affected by n linear reservoirs with the same value of storage coefficient k, Nash proposed the formulation of the Instantaneous Unit Hydrograph (IUH), which has been widely used in rainfall–runoff simulation and flood forecasting. However, the assumption of the parameter k having the same value in all reservoirs is obviously unphysical as it results in the estimated value of n not being integral. In this study, for parameter n integral, the different k value for each reservoir was derived using the Laplace transform and developing a general rule for the equation of the IUH of any order. The relationship between parameter k and the slope of the river channel estimated using digital elevation model (DEM) data is established, the parameter estimation procedures are given. As in most unit hydrograph studies, only isolated storm events are considered here. Seventeen flood events in three catchments were selected for the case studies. Application results show that the proposed method is slightly better than Nash's IUH with higher model efficiency and smaller absolute relative errors. This work provides a new methodology for the formulation of the IUH. Copyright © 2008 John Wiley & Sons, Ltd.     

Towards a comprehensive approach to parameter estimation in land surface parameterization schemes

In climate models, the land–atmosphere interactions are described numerically by land surface parameterization (LSP) schemes. The continuing improvement in realism in these schemes comes at the expense of the need to specify a large number of parameters that are either directly measured or estimated. Also, an emerging problem is whether the relationships used in LSPs are universal and globally applicable. One plausible approach to evaluate this is to first minimize uncertainty in model parameters by calibration. In this paper, we conduct a comprehensive analysis of some model diagnostics using a slightly modified version of the Simple Biosphere 3 model for a variety of biomes located mainly in the Amazon. First, the degree of influence of each individual parameter in simulating surface fluxes is identified. Next, we estimate parameters using a multi‐operator genetic algorithm applied in a multi‐objective context and evaluate simulations of energy and carbon fluxes against observations. Compared with the default parameter sets, these parameter estimates improve the partitioning of energy fluxes in forest and cropland sites and provide better simulations of daytime increases in assimilation of net carbon during the dry season at forest sites. Finally, a detailed assessment of the parameter estimation problem was performed by accounting for the decomposition of the mean squared error to the total model uncertainty. Analysis of the total prediction uncertainty reveals that the parameter adjustments significantly improve reproduction of the mean and variability of the flux time series at all sites and generally remove seasonality of the errors but do not improve dynamical properties. Our results demonstrate that error decomposition provides a meaningful and intuitive way to understand differences in model performance. To make further advancements in the knowledge of these models, we encourage the LSP community to adopt similar approaches in the future. Copyright © 2012 John Wiley & Sons, Ltd.     

Estimation of Nash's IUH parameters using stochastic search algorithms

In rainfall–runoff studies, it is often necessary to change the duration of a given unit hydrograph. Nash's Instantaneous Unit Hydrograph (IUH) is an ideal method that eliminates the hydrograph duration. This paper presents the results of the application of search algorithms, namely a genetic algorithm and hill climbing, to develop the IUH that minimizes the error between the observed and generated hydrographs. Also the performance of these methods has been compared with that of the classical method used for estimation of IUH, namely the method of moments. The genetic algorithm is a popular search procedure for function optimization that applies the mechanics of natural genetics and natural selection to explore a given search space. Hill climbing is an optimization technique that belongs to the family of local search and algorithms can be used to solve problems that have many solutions, with some solutions better than others. The results obtained from both the genetic algorithm and hill climbing algorithm for estimation of Nash's IUH parameters were compared with the results obtained by the method of moments for storms from two river basins that are located in different climatic regions. It was found that both the genetic algorithm and hill climbing provided improved and consistent results. Copyright © 2008 John Wiley & Sons, Ltd.     

DEPENDENCE BETWEEN FUSION TEMPERATURES AND CHEMICAL COMPONENTS OF A CERTAIN TYPE OF COAL USING CLASSICAL,NON-PARAMETRIC AND BOOTSTRAP TECHNIQUES

A statistical study of the dependence between various critical fusion temperatures of a certain kind ofcoal and its chemical components is carried out.As well as using classical dependence techniques(multiple,stepwise and PLS regression,principal components,canonical correlation,etc.)together withthe corresponding inference on the parameters of interest,non-parametric regression and bootstrapinference are also performed.     

基于最小二乘支持向量机回归的GPS高程转换模型

探讨了将最小二乘估计引入到支持向量机中,给出最小二乘支持向量机回归(LS-SVR)算法,该算法用等式约束代替传统支持向量机回归中的不等式约束,使得求解过程更为简单。将构建的LS-SVR模型应用到GPS高程转换中,提出该回归模型的实现步骤。实例表明,在有限样本情况下,LS-SVR完全可以达到与传统GPS高程拟合方法相同的精度,但实现起来更简单,而且在泛化性能方面具有理论上的保证。     

自动推算室内接入点坐标算法

随着基于位置服务的应用与发展,室外和室内定位技术都得到了飞速发展。特别是在WiFi定位技术的不断完善下,室内定位技术有了广泛的应用,但是,WiFi定位技术的两种定位方式均需预先知道室内网络接入点的精确坐标,这一要求无法满足一些紧急情况下的定位需求。因此,本文提出了一种基于M估计的自动推算室内接入点坐标算法。该算法借助在室内外交界处同时获取卫星定位信息和WiFi信号的RSSI信息,巧用分段RSSI测距算法提高长距离RSSI测距精度,结合残差绝对和最小的M估计改进距离交会定位算法,最终推算出室内接入点的三维坐标,实现自动化推算过程。试验结果表明：该方法的定位精度比常规距离交会最小二乘算法提高了50%,能够快速实时较精确地推算室内接入点的坐标,进一步完善了WiFi定位技术。     

高光谱遥感影像混合像元分解研究进展

受高光谱成像仪低空间分辨率及复杂地物的影响,高光谱遥感图像存在大量混合像元。为提高地表分类精度以及满足亚像元级目标探测的需求,混合像元分解技术一直是高光谱遥感研究热点之一。本文主要对高光谱混合像元分解技术中的核心问题:端元数目估计、端元提取算法、丰度估计算法进行综述,系统地分析了各种典型算法的原理及优缺点,进一步阐述研究过程中建立高精度遥感混合反演模型与遥感产品业务化中的混合像元分解技术难题,同时针对今后混合像元分解技术发展方向,指出在继续引入新型算法理论方法基础上,结合用户应用需求,推进高光谱混合像元分解算法业务化应用,为高光谱遥感工程化应用提供支持。