Predicting quantiles of water quality from catchment characteristics

Water quality is often highly variable both in space and time, which poses challenges for modelling the more extreme concentrations. This study developed an alternative approach to predicting water quality quantiles at individual locations. We focused on river water quality data that were collected over 25 years, at 102 catchments across the State of Victoria, Australia. We analysed and modelled spatial patterns of the 10th, 25th, 50th, 75th and 90th percentiles of the concentrations of sediments, nutrients and salt, with six common constituents: total suspended solids (TSS), total phosphorus (TP), filterable reactive phosphorus (FRP), total Kjeldahl nitrogen (TKN), nitrate-nitrite (NO_x), and electrical conductivity (EC). To predict the spatial variation of each quantile for each constituent, we developed statistical regression models and exhaustively searched through 50 catchment characteristics to identify the best set of predictors for that quantile. The models predict the spatial variation in individual quantiles of TSS, TKN and EC well (66%–96% spatial variation explained), while those for TP, FRP and NO_x have lower performance (37%–73% spatial variation explained). The most common factors that influence the spatial variations of the different constituents and quantiles are: annual temperature, percentage of cropping land area in catchment and channel slope. The statistical models developed can be used to predict how low- and high-concentration quantiles change with landscape characteristics, and thus provide a useful tool for catchment managers to inform planning and policy making with changing climate and land use conditions.     

基于F-范数的不确定性平差模型的解算方法

为提高基于F-范数的不确定性平差模型的解算效率，给出直接迭代算法进行参数估计。该算法无需SVD，解算过程简单且易于编程计算，同时给出迭代不收敛时的SVD-解方程算法。二元线性拟合及沉降观测AR模型的算例结果表明，这2种算法正确可行，与SVD-迭代算法具有等价性。当迭代收敛时，宜使用直接迭代算法，收敛速度更快，解算效率更高；当迭代不收敛时，可釆用SVD-解方程算法。     

Study of irregular wave run-up over fringing reefs based on a shock-capturing Boussinesq model

This paper presents the results of a parametric study of irregular wave run-up over fringing reefs using the shock-capturing Boussinesq wave model Funwave-TVD to better understand the role of fringing reefs in the mitigation of wave-driven flooding. Laboratory experiments were newly performed with a typical fringing reef profile and typical hydrodynamic conditions to validate the model. Experimental data shows irregular wave run-ups are dominated by the low-frequency motions and confirms the run-up resonant phenomenon over the back-reef slope, which has been revealed in previous numerical studies. It is demonstrated that irregular wave evolution and run-up over fringing reefs are reasonably reproduced by the present model with a proper grid size. However, the infragravity run-up height and highest 2% run-up height over the back-reef slope are under-predicted due to the underestimation of the infragravity wave height over the reef flat. The validated model was then utilized to model irregular wave transformations and run-ups under different conditions. Through a series of numerical experiments, the effects of key hydrodynamic and reef geometry parameters, including the reef flat width, water depth over the reef flat, fore-reef slope angle and back-reef slope angle, on the irregular wave run-up were investigated. Variations of spectral components of irregular wave run-ups were examined to better understand the physical process underlying the effect of each parameter.     

Lidar-aided analysis of boreal forest backscatter at Ku band

This paper analyzes the backscatter of the microwave signal in a boreal forest environment based on a Ku -band airborne Frequency-Modulated Continuous Waveform (FMCW) profiling radar—Tomoradar. We selected a half-managed boreal forest in the southern part of Finland for a field test. By decomposing the waveform collected by the Tomoradar, the vertical canopy structure was achieved. Based on the amplitude of the waveform, the Backscattered Energy Ratio of Canopy-to-Total (BERCT) was calculated. Meanwhile, the canopy fraction was derived from the corresponding point cloud recorded by a Velodyne VLP-16 LiDAR mounted on the same platform. Lidar-derived canopy fraction was obtained by counting the number of the first/ the strongest returns versus the total amount of returns. Qualitative and quantitative analysis of radar-derived BERCT on lidar-derived canopy fraction and canopy height are investigated. A fitted model is derived to describe the Ku-band microwave backscatter in the boreal forest to numerically analyze the proportion contributed by four factors: lidar-derived canopy fraction, radar-derived canopy height, the radar-derived distance between trees and radar sensor and other factors, from co-polarization Tomoradar measurements. The Root Mean Squared Error (RMSE) of the proposed model was 0.0958, and the coefficient of determination R2 was 0.912. The fitted model reveals that the correlation coefficient between radar-derived BERCT and lidar-derived canopy fraction is 0.84, which illustrates that lidar surface reflection explains the majority of the profiling /waveform radar response. Thus, vertical canopy structure derived from lidar can be used for the benefit of radar analysis.     

Parallelization of the flow-path network model using a particle-set strategy

High-performance simulation of flow dynamics remains a major challenge in the use of physical-based, fully distributed hydrologic models. Parallel computing has been widely used to overcome efficiency limitation by partitioning a basin into sub-basins and executing calculations among multiple processors. However, existing partition-based parallelization strategies are still hampered by the dependency between inter-connected sub-basins. This study proposed a particle-set strategy to parallelize the flow-path network (FPN) model for achieving higher performance in the simulation of flow dynamics. The FPN model replaced the hydrological calculations on sub-basins with the movements of water packages along the upstream and downstream flow paths. Unlike previous partition-based task decomposition approaches, the proposed particle-set strategy decomposes the computational workload by randomly allocating runoff particles to concurrent computing processors. Simulation experiments of the flow routing process were undertaken to validate the developed particle-set FPN model. The outcomes of hourly outlet discharges were compared with field gauged records, and up to 128 computing processors were tested to explore its speedup capability in parallel computing. The experimental results showed that the proposed framework can achieve similar prediction accuracy and parallel efficiency to that of the Triangulated Irregular Network (TIN)-based Real-Time Integrated Basin Simulator (tRIBS).     

An evaluation of Guided Regularized Random Forest for classification and regression tasks in remote sensing

New Earth observation missions and technologies are delivering large amounts of data. Processing this data requires developing and evaluating novel dimensionality reduction approaches to identify the most informative features for classification and regression tasks. Here we present an exhaustive evaluation of Guided Regularized Random Forest (GRRF), a feature selection method based on Random Forest. GRRF does not require fixing a priori the number of features to be selected or setting a threshold of the feature importance. Moreover, the use of regularization ensures that features selected by GRRF are non-redundant and representative. Our experiments based on various kinds of remote sensing images, show that GRRF selected features provides similar results to those obtained when using all the available features. However, the comparison between GRRF and standard random forest features shows substantial differences: in classification, the mean overall accuracy increases by almost 6% and, in regression, the decrease in RMSE almost reaches 2%. These results demonstrate the potential of GRRF for remote sensing image classification and regression. Especially in the context of increasingly large geodatabases that challenge the application of traditional methods.     

基于高斯烟羽模型的船舶尾气扩散研究

为有效对港区大气污染进行治理、分析船舶尾气,本文详细介绍了一种基于高斯烟羽模型,通过MATLAB模拟仿真模型,其包括实验仿真过程、技术原理及理论模型对船舶尾气扩散进行的研究。该模型是在传统的高斯烟羽模型的基础上,通过对实源像源进行加权选择输入参数;通过矢量合成确定了气体扩散的方向,利用合成后的"风速"进行计算仿真,有效模拟了船舶尾气在港区或者海洋环境中的气体扩散模型。其模型简单且可以有效模拟船舶尾气扩散。并且进一步对后续模型的精确优化进行分析。     

利用超快速精密星历约束的北斗卫星实时精密定轨

以广播星历为起算轨道的北斗卫星实时滤波精密定轨往往需要较长收敛时间，针对此，提出利用超快速精密星历约束的实时精密定轨方法。通过MGEX跟踪网全球分布的51个测站连续7 d的实测数据，利用平方根信息滤波对北斗卫星实时精密轨道进行确定，并以3 d解事后轨道作为参考，评估北斗卫星实时滤波轨道精度。结果表明，利用广播星历作起算轨道时，北斗实时滤波轨道平均需要经过15 h收敛才能达到稳定，而新方法在这段时间内轨道变化较为平稳，未出现明显的收敛现象，并且7 d时间内GEO卫星在切向、法向和径向上RMS分别优于2.5 m、20 cm和30 cm，IGSO和MEO卫星在3个方向上分别优于30 cm、15 cm和10 cm。
     

基于高斯两步移动搜寻法的村镇避难场所可达性研究

避难场所可达性是指避难场所与受灾居民之间的通达性,即灾害发生时,避难人员通过避难疏散通道到达避难场所的难易程度,是评价避难场所布局合理性的重要指标。本研究结合高斯两步移动搜寻法和网络分析法,从供需双向出发对村镇地区避难场所进行可达性分析。2种方法的结合,既充分考虑了需求点与设施点的相互作用,又充分考虑了设施点的吸引力随距离的衰减关系,并基于实际道路,以步行疏散时间作为搜索半径,降低了传统研究中因忽略供需间相互作用及实际距离而引起的可达性结果的误差。最后,以神农架松柏镇区为例,验证该方法的实际应用价值。结果表明,该方法能够有效测定村镇地区避难场所的空间可达性,同时,基于GIS软件可以直观地揭示研究区域内避难场所可达性空间分布差异。该方法可为制定科学的村镇防灾减灾规划提供方法支持。     

Bearing capacity of offshore umbrella suction anchor foundation in silty soil under varying loading modes

Considering the current disadvantages of present offshore wind turbine foundations, a novel anchor foundation with skirt and branches is proposed, called offshore umbrella suction anchor foundation (USAF). A series of experiments and numerical simulations were performed to explore the bearing capacity of the USAF under various kinds of loading modes. The bearing characteristics and the anchor–soil interactions are described in detail for horizontal static loading, horizontal cyclic loading, and an antidrawing (pullout) test in silty soil. In the static loading test, the load–deflection of the anchor under step loading was analyzed and the normalized curve of the load–deflection was obtained to determine the ultimate horizontal bearing capacity of the anchor under normal working conditions. Under horizontal cyclic loading, the relationship between the plastic cumulative deformation and cyclic number was determined. In addition, the responses of USAF were investigated for a low wave frequency and storm surges. In the drawing test, it was found that a “segmentation phenomenon” occurred during the test. Moreover, a method to identify the maximum antidrawing load of USAF was provided based on dynamic mechanics. The numerical results show that the use of anchor branches and skirt can enhance the bearing performance of USAF to a certain degree. However, the anchor branch has a slight positive influence on the bearing performance improvement. The USAF is not only similar to a stiff short pile, but a rotation occurs. The failure envelope under composite loading (V-M) was obtained and the changes associated with changes in the aspect ratio of the internal compartment were clarified.