自适应GA-BP优化方法进行高分辨率反演

本文提出了一种高精度的神经网络学习方法．由于BP神经网络受初值的影响较大,而遗传算法可以很快达到全局最优解附近．本文结合遗传神经网络和BP神经网络各自的优点,将两种算法混合．使得神经网络的收敛速度得到加快,精度得到提高,并对传统的混合方法作了一点改进．通过对波阻抗进行反演的实践,表明这种方法可以达到提高分辨率的效果。     

Missing precipitation data estimation using optimal proximity metric-based imputation,nearest-neighbour classification and cluster-based interpolation methods

Abstract

New optimal proximity-based imputation, K-nearest neighbour (K-NN) classification and K-means clustering methods are proposed and developed for estimation of missing daily precipitation records. Mathematical programming formulations are developed to optimize the weighting, classification and clustering schemes used in these methods. Ten different binary and real-valued distance metrics are used as proximity measures. Two climatic regions, Kentucky and Florida, (temperate and tropical) in the USA, with different gauge density and network structure, are used as case studies to evaluate the new methods. A comprehensive exercise is undertaken to compare the performances of the new methods with those of several deterministic and stochastic spatial interpolation methods. The results from these comparisons indicate that the proposed methods performed better than existing methods. Use of optimal proximity metrics as weights, spatial clustering of observation sites and classification of precipitation data resulted in improvement of missing data estimates.

Editor D. Koutsoyiannis; Associate editor C. Onof     

Multi-objective autocalibration of SWAT model for improved low flow performance for a small snowfed catchment

ABSTRACT

A reliable modelling framework needs to ensure that the model is simulating reality with limited uncertainty, thus enhancing its predictive ability. In the literature, hydrological model assessment using one or more metrics is reported to be inadequate when the river flow regime is required to be reproduced comprehensively. This research is aimed to: (a) calibrate the Soil and Water Assessment Tool (SWAT) based on the concept of multi-objective optimization by applying the Borg multi-objective evolutionary algorithm (MOEA); (b) apply hydrological signatures as objective functions; and (c) adopt a multi-metric approach for model evaluation. The SWAT model was coupled with a relatively newer and powerful Borg MOEA. The inclusion of hydrological signatures as objective functions along with the conventional statistical functions assisted in improving the performance for low flows by 135% in terms of volume efficiency and 65% for flow time series simulation.     

The interrill erosion for a sandy loam soil

This paper resumes a laboratory experience on a slope adjustable plot with the aim of examining the role of rainfall intensity and slope gradient for a sandy loam soil, typical of Southern Italy, with particular initial moisture content. The results of the simulations performed show that a rainfall reduction causes a corresponding percentage reduction of sediment output. A similar behaviour can be attributed to slope gradient, while runoff moderately increases with rainfall intensity but it is not sensitive to slope gradient. Data also highlight that the degree of saturation can affect runoff and soil loss values.     

山东及邻区地震重新定位及其与活动构造的关系

Earthquakes taking place from 1975 to 2010 in and around Shandong Province are relocated using double-difference （HypoDD） and Hypoinvers 2000 （Hypo2000） methods, after correction of the onset times of seismic phases. The results show that the relocated seismicity is clearly associated with regional tectonics in space, and is also in agreement with the existence of deep faults imaged by wide-angle and deep seismic reflection profiling ; most of the focal depths are in the range of 5 - 25km, and there are clearly two predominant depths： 10km and 16km, which are inferred to be on the bottom of the upper crust and in the middle crust, respectively. The pattern of seismic activity indicates that moderate and strong earthquakes are likely to occur in the brittle-ductile transition zone between the upper and the lower crust, as the outcome of the deep tectonic dynamic process and the movement and deformation of faults in the upper and shallow crust under the regional stress field.     

Sediment fingerprinting in fluvial systems： review of tracers,sediment sources and mixing models

Suspended sediments in fluvial systems originate from a myriad of diffuse and point sources, with the relative contribution from each source varying over time and space. The process of sediment fingerprinting focuses on developing methods that enable discrete sediment sources to be identified from a composite sample of suspended material. This review identifies existing methodological steps for sediment fingerprinting including fluvial and source sampling, and critically compares biogeochemical and physical tracers used in fingerprinting studies. Implications of applying different mixing models to the same source data are explored using data from 41 catchments across Europe, Africa, Australia, Asia, and North and South America. The application of seven commonly used mixing models to two case studies from the US （North Fork Broad River watershed） and France （Bldone watershed） with local and global （genetic algorithm） optimization methods identified all outputs remained in the acceptable range of error defined by the original authors. We propose future sediment fingerprinting studies use models that combine the best explanatory parameters provided by the modified Collins （using correction factors） and Hughes （relying on iterations involving all data, and not only their mean values） models with optimization using genetic algorithms to best predict the relative contribution of sediment sources to fluvial systems.     

Stochastic subspace identification for output‐only modal analysis: application to super high‐rise tower under abnormal loading condition

The objective of this paper is to develop an online system parameter estimation technique from the response measurements through using the recursive covariance‐driven stochastic subspace identification (SSI‐COV) approach. In developing the recursive SSI‐COV, to avoid time‐consumption of singular value decomposition in recursive SSI, the extended instrumental variable version of the projection approximation subspace tracking method is used in SSI‐COV. Besides, to reduce the effect of noise on the results of identification, the preprocessing of data using recursive singular spectrum analysis technique is also presented to remove the noise contaminant measurements to enhance the stability of data analysis. On the basis of the proposed method, both the ambient vibration and seismic response data of a tower (Canton Tower) are used to observe the time‐varying system natural frequencies of a tower from its operating condition. Results from using off‐line SSI‐COV method under normal operating condition are also presented. Comparison on the identified time‐varying dynamic characteristics of the tower under normal operating condition and earthquake response of distanced earthquake event is discussed. Copyright © 2012 John Wiley & Sons, Ltd.     

Variability of volume strain in bounded heterogeneous media

The deformation of the solid matrix affects the fluid pore pressure and flow by altering the pore volume. Such interaction in turn affects the storage of groundwater in the void space. Obviously, this subject is of interest in groundwater hydrology. This paper describes an investigation of the effect of aquifer heterogeneity on the variability of the fluid pressure head and solid's volume strain, where the assumption of a constant vertical total stress leads to a relatively simple relationship between changes in solid's volume strain and fluid pressure head. To solve the problem analytically, focus is placed on the one‐dimensional models. It is found from our closed‐form solutions that the variance and correlation length of the log hydraulic conductivity are important in increasing the variability of pressure head and solid's volume strain. It is hoped that our findings will provide a basic framework for understanding and quantifying field‐scale volume strain processes and be useful in stimulating further research in this area. Copyright © 2011 John Wiley & Sons, Ltd.     

A) A. I. H. S. / A) A. I. H. S.

Abstract

A new method is presented to generate stationary multi-site hydrological time series. The proposed method can handle flexible time-step length, and it can be applied to both continuous and intermittent input series. The algorithm is a departure from standard decomposition models and the Box-Jenkins approach. It relies instead on the recent advances in statistical science that deal with generation of correlated random variables with arbitrary statistical distribution functions. The proposed method has been tested on 11 historic weekly input series, of which the first seven contain flow data and the last four have precipitation data. The article contains an extensive review of the results.

Editor D. Koutsoyiannis

Citation Ilich, N., 2014. An effective three-step algorithm for multi-site generation of stochastic weekly hydrological time series. Hydrological Sciences Journal, 59 (1), 85–98.     

冬小麦农田裸温与气温差异分析及其应用

以矮秆代表作物冬小麦为研究对象,利用郑州农业气象试验站2010年10月15日—2011年6月2日农田小气候观测的各层裸温、气温、总辐射和覆盖度资料,采用对比差值、温度垂直梯度等方法统计分析,并对温度对比差值和总辐射曝辐量相关关系和温度的垂直梯度分布特征进行了研究,结果表明:25cm、150cm和300cm高度的日平均裸温和气温变化趋势基本一致,其对比差值呈由小变大趋势;各层裸温和气温的日分布符合温度日变化分布的一般规律,垂直梯度变化比较明显;各层对比差值呈单峰分布,峰值出现在正午12时左右;裸温和气温的对比差值与总辐射曝辐量呈线性相关。裸温与气温的垂直梯度变化有很好的一致性,可利用裸温不同层次间垂直梯度变化特征确定气温传感器合理的安装高度;根据麦田裸温垂直梯度变化特征,考虑到温度防辐射罩高度限制,矮秆作物田间小气候气温应在距离地表面25cm、50cm和150cm高度附近分别设置观测层次。