Raingauge network optimization in a tropical urban area by coupling cross-validation with the geostatistical technique

An adequate and reliable raingauge network is essential for observing rainfall data in hydrology and water resource applications. A raingauge network developed for a catchment area is commonly extended periodically to increase data accuracy. Due to financial constraints, the network is reviewed for the optimal number of stations. A new optimization approach is developed in this study by coupling a cross-validation technique with a geostatistical method for raingauge network optimization to prioritize raingauge stations. The spatial interpolation error of the spatial rainfall distribution, measured as the root mean square error (E_rms) optimization criterion is applied to a raingauge network in a tropical urban area. The results indicate that this method can successfully optimize the number of rainfall stations in an existing raingauge network, as the stations are prioritized based on their importance in the network.     

一种改进的InSAR城市地面沉降监测精度评价方法

针对InSAR沉降监测精度评定方法的单一性,综合考虑建筑物自身沉降和时空基准难以统一的问题,构建了改进的反距离权重插值模型。以宁波东部新城某沉降区域的PS-InSAR监测结果为试验数据,在统一时空基准的前提下,利用改进IDW插值模型对监测结果进行精度评定,并以交叉验证的方式验证了该插值方法的准确性。试验证明：通过对比两个实测水准点,使用改进的IDW插值获取的InSAR监测结果误差为0.3和0.8,相比于普通IDW和Kriging方法提高了大约1.1 mm。     

基于GA-SVR的地铁隧道沉降预测

利用支持向量回归(SVR)和遗传算法(GA)参数寻优,建立了基于GA-SVR的地铁隧道沉降预测模型,可提高地铁隧道沉降预测的精度。利用长期实测的地铁结构监测数据对SVR模型进行训练,并通过GA优化SVR模型的3个参数;利用训练模型均方误差结合留一交叉验证的方法确定GA的适应度。基于南京地铁2号线隧道结构沉降实测数据,将预测值与实测值进行了对比分析。结果表明,该模型预测的地铁隧道沉降预测值准确、可靠,其精度能满足工程实际要求。     

附有病态约束反演问题的岭估计法

提出了处理附有病态约束矩阵的等式约束反演问题的岭估计解法,推导了相应的求解公式及均方误差评定精度的方法,给出了确定附有病态约束矩阵的等式约束反演中岭参数的岭迹法、广义交叉核实法和L曲线法。算例比较了三种确定岭参数的方法在处理附有病态约束矩阵的等式约束反演问题中的优缺点,并与截断SVD法进行了对比分析。     

一种基于交叉证认技术的自适应小波变换及其在削减GPS多路径误差中的应用

多路径效应影响是目前限制GPS定位精度进一步提高的瓶颈。提出用交叉证认技术自动识别小波分解的信号层,再通过小波重构实现降噪和信号提取,并将该方法应用于GPS多路径误差的削减中。对模拟数据和实际GPS观测资料的分析表明,该方法能合理分离不同噪声水平下资料序列中的信号和噪声;当噪声水平小于信号振幅的一半时,能成功分离资料序列中的高频信号。同时,运用该方法得到的多路径改正模型和GPS多路径效应的重复性,可有效地削弱多路径效应的影响,提高GPS定位精度。     

Assessment of radar-based locally varying anisotropy on daily rainfall interpolation

ABSTRACT

Spatial variability of rainfall has been recognised as an important factor controlling the hydrological response of catchments. However, gauged daily rainfall data are often available at scattered locations over the catchments. This paper looks into how to capitalise on the spatial structure of radar rainfall data for improving kriging interpolation of limited gauge data over catchments at the 1-km² grid scale, using for the case study 117 gauged stations within the 128 km × 128 km region of the Mt Stapylton weather radar field (near Brisbane, Australia). Correlograms were developed using a Fast Fourier Transform method on the Gaussianised radar and gauged data. It is observed that the correlograms vary from day to day and display significant anisotropy. For the radar data, locally varying anisotropy (LVA) was examined by developing the correlogram centred on each pixel and for different radial distances. Cross-validation was carried out using the empirical correlogram tables, as well as different fitting strategies of a two-dimensional exponential distribution for both the gauged and the radar data. The results indicate that the correlograms based on the radar data outperform the gauged ones as judged by statistical measures including root mean square error, mean bias, mean absolute bias, mean standard deviation and mean inter-quartile range. While the radar data display significant LVA, it was observed that LVA did not significantly improve the estimates compared with the global anisotropy. This was also confirmed by conditional simulation of 120 rainfields using different options of correlogram development.

EDITOR M.C. Acreman; ASSOCIATE EDITOR Q. Zhang     

Field survey and modelling of irrigation water quality indices in a Mediterranean island catchment: a comparison between spatial interpolation methods

ABSTRACT

A biannual survey of physico-chemical quality indices of 104 irrigation-water wells located in a cultivated plain of a Mediterranean island catchment was conducted using a multi-parameter probe. The campaign was planned so as to differentiate between the dry and wet seasons. The acquired data constituted the test bed for evaluating the results and the features of four spatial interpolation methods, i.e. ordinary kriging, universal kriging, inverse distance weighted and nearest neighbours, against those of the recently introduced bilinear surface smoothing (BSS). In several cases, BSS outperformed the other interpolation methods, especially during the two-fold cross-validation procedure. The study emphasizes the fact that both in situ measurements and good mathematical techniques for studying the spatial distribution of water quality indices are pivotal to agricultural practice management. In the specific case studied, the spatio-temporal variability of water quality parameters and the need for monitoring were evident, as low irrigation water quality was encountered throughout the study area.     

采样点数目对反距离加权插值结果的敏感性分析

为了研究采样点数目对反距离加权插值结果的影响,以面积为2.076×105km2的白俄罗斯为研究区域,采用数目逐渐变化的采样点作为实验数据,通过交叉验证方法,得到了采样点数目与插值精度之间的关系。结果表明:随着采样点数目减少,插值误差呈现先缓慢上升后迅速上升再缓慢上升的趋势。就本组数据而言,当采样点逐渐减少到约为总采样点数目的 70%左右,插值的质量会发生突变。计算采样点的密度,得出每100 km2采0.9～1.3个点(即每76～109 km2采集1个点)的情况下,插值精度变化不大。鉴于研究所得,在实际的生产生活中,可供大区域插值时,采样方案设计参考。     

支持向量机在大气污染预报中的应用研究

支持向量机是基于统计学习理论的新一代机器学习技术，其非线性回归预测性能优越于传统统计方法。利用前一天该污染物的日均浓度、前一天地面平均风速等7个预报因子建立了基于RBF核函数支持向量回归法的大气污染预报模型，并利用十重交叉验证和网格搜索法寻找模型最优参数。乌鲁木齐大气预报实例表明：支持向量机显示出小样本时预报精度较高和训练速度快的独特优势，为空气质量预报提供一种全新的模式。