Water level observations from unmanned aerial vehicles for improving estimates of surface water–groundwater interaction

Integrated hydrological models are usually calibrated against observations of river discharge and piezometric head in groundwater aquifers. Calibration of such models against spatially distributed observations of river water level can potentially improve their reliability and predictive skill. However, traditional river gauging stations are normally spaced too far apart to capture spatial patterns in the water surface, whereas spaceborne observations have limited spatial and temporal resolution. Unmanned aerial vehicles can retrieve river water level measurements, providing (a) high spatial resolution; (b) spatially continuous profiles along or across the water body, and (c) flexible timing of sampling. A semisynthetic study was conducted to analyse the value of the new unmanned aerial vehicle‐borne datatype for improving hydrological models, in particular estimates of groundwater–surface water (GW–SW) interaction. Mølleåen River (Denmark) and its catchment were simulated using an integrated hydrological model (MIKE 11–MIKE SHE). Calibration against distributed surface water levels using the Differential Evolution Adaptive Metropolis algorithm demonstrated a significant improvement in estimating spatial patterns and time series of GW–SW interaction. After water level calibration, the sharpness of the estimates of GW–SW time series improves by ~50% and root mean square error decreases by ~75% compared with those of a model calibrated against discharge only.     

区域-时间-长度算法在青海地区的应用研究

应用检测地震活动水平相对变化的区域-时间-长度算法（RTL算法）,分析研究了青海地区有相对较完备小震资料的14次6级以上震例。结果表明,该区6级以上地震发生前在源区或近源区大约120km半径的空间尺度内,‰值能检测到明显的1年内和2年内时间尺度的中期地震活动异常,地震活动增强的“上升型”异常和地震活动平静的“下降型”异常各占一半。     

基于ArcObjects的公路动态分段数据的组织与实现

介绍了ArcObjects处理空间数据的相关层次结构,在动态分段思想的基础上设计了公路分段数据存储结构,提出了公路分段数据处理过程中的组织方法,并对数据合并方法进行了改进,最后设计出了数据生产过程模型和相应的数据生产软件。     

海浪外观波数谱与谱宽度最优确定

本文将外频谱转化为外观波数谱并设计了计算处理格式,提出了一种谱宽度参量的优化方法,为进一步研究海浪特征资料提取谱值和应用奠定基础。数值试验验证了此方法的可行性,但在高海况下风浪过程复杂,优化出的谱宽度偏大,外观谱解析形式需进一步改进     

ANN在海洋预报中的应用

人工神经网络通过神经元之间的相互作用来完成整个网络的信息处理,具有自学习和自适应等一系列优点,因而用它来进行海洋预报是可行的。针对海洋预报问题,初步建立了基于神经网络的预报分析系统,给出了应用实例。     

两类双结构矩阵的标准型及其应用

给出2类双结构矩阵的标准型。作为应用,还利用新得出的标准型对这2类双结构矩阵特征值问题发展了结构算法,其中对第一类双结构矩阵特征值问题发展了只用实运算的结构算法。     

Mooring optimization of floating platforms using a genetic algorithm

This paper presents a new procedure for the optimization of the mooring design of floating platforms, in which an automatic design sequence is also established. Regarding the optimization philosophy, the following aspects are dealt with:

• The optimization of the platform heading and its mooring pattern, taking into account the environmental force spreading;

• optimum line length or line tension for each mooring line, associated to the optimization of the mooring line materials and sizes.

Basically, the main goal of this paper is to introduce a new method, which will provide the quickest way to find the best mooring system, defined here as that which minimizes platform responses.A genetic algorithm (GA) is applied in this contribution, and this paper describes exactly the procedure of developing a GA code directed toward the solution of mooring design optimization problems. In order to prove the efficiency and the vast potential of the proposed algorithm as a design tool, sample moorings are analyzed for different environmental conditions and the final results, including the time required to run them, are presented.     

对称模式下的CHAMP弯曲角掩星数据同化

简单介绍了无线电掩星技术探测行星大气的发展史,列举了该技术中存在的若干问题。从 Eyre提出的统计学的最优估计反演方法,比较了用相位、弯曲角和折射率作为同化因子时出现的问题和各自的优缺点。对弯曲角同化因子,以欧洲中期天气预报中心(ECMWF)资料为背景场,运用一维变分技术,进行CHAMP掩星观测资料变分同化反演,从而获得水汽和温度剖面。将反演获得的气象剖面与非同化的剖面作比较,并且采用相应的探空气球资料作为验证,可以看出变分同化技术比传统的标准反演技术反演误差小。证实掩星数据资料的一维变分同化技术可以改进目前的数值天气预报模式。     

海底地形测量波束角效应改进模型

在海洋测深过程中,回声测深仪波束角效应使记录的测深图像失真。现有波束角效应模型应用分段解析几何的方法将其划分为三个作用过程：测深值平移效应、双曲线增伪效应、深度丢失效应。在此基础上,应用微分几何的原理对波束角效应的空间结构及其数学原理描述进行理论分析,提出了波束角效应的改进模型及其改正算法。改进模型的优越之处在于提出决定波束角效应发生作用的是海底地形的线性特征而不是形状特征,由此提高了改正算法的自动化程度。     

基于阈值区间的海洋锋面提取模型

A model （Bayesian oceanic front detection, BOFD） of sea surface temperature （SST） front detection in satel- lite-derived SST images based on a threshold interval is presented, to be used in different applications such as climatic and environmental studies or fisheries. The model first computes the SST gradient by using a Sobel algorithm template. On the basis of the gradient value, the threshold interval is determined by a gradi- ent cumulative histogram. According to this threshold interval, front candidates can be acquired and prior probability and likelihood can be calculated. Whether or not the candidates are front points can be deter- mined by using the Bayesian decision theory. The model is evaluated on the Advanced Very High-Resolution Radiometer images of part of the Kuroshio front region. Results are compared with those obtained by using several SST front detection methods proposed in the literature. This comparison shows that the BOFD not only suppresses noise and small-scale fronts, but also retains continuous fronts.