Characterisation of hydroclimatological trends and variability in the Lake Naivasha basin,Kenya

Recent hydro‐climatological trends and variability characteristics were investigated for the Lake Naivasha basin with the aim of understanding the changes in water balance components and their evolution over the past 50 years. Using a Bayesian change point analysis and modified Mann–Kendall tests, time series of annual mean, maximum, minimum, and seasonal precipitation and flow, as well as annual mean lake volumes, were analysed for the period 1960–2010 to uncover possible abrupt shifts and gradual trends. Double cumulative curve analysis was used to investigate the changes in hydrological response attributable to either human influence or climatic variability. The results indicate a significant decline in lake volumes at a mean rate of 9.35 × 10⁶ m³ year^?1. Most of the river gauging stations showed no evidence of trends in the annual mean and maximum flows as well as seasonal flows. Annual minimum flows, however, showed abrupt shifts and significant (upward/downward) trends at the main outlet stations. Precipitation in the basin showed no evidence of abrupt shifts, but a few stations showed gradual decline. The observed changes in precipitation could not explain the decline in both minimum flows and lake volumes. The findings show no evidence of any impact of climate change for the Lake Naivasha basin over the past 50 years. This implies that other factors, such as changes in land cover and infrastructure development, have been responsible for the observed changes in streamflow and lake volumes. Copyright © 2015 John Wiley & Sons, Ltd.     

Assessing the ‘two water worlds’ hypothesis and water sources for native and exotic evergreen species in south‐central Chile

Recent studies using water‐stable isotopes (δ¹⁸O and δ²H) have suggested an ecohydrological separation of water flowing to streams or recharging groundwater and water used by trees, known as the ‘two water worlds’ (TWW) hypothesis. In this study, we measured water isotopic composition in precipitation [open field and throughfall, i.e. local meteoric water line (LMWL)] and the mobile water compartment (i.e. stream and soil solution), bulk soil water and xylem water over a period of 1.5 years in two headwater catchments: NF, covered with old growth native evergreen forest (Aetoxicon punctatum, Laureliopsis philippiana and Eucriphya cordifolia), and EP, covered with 4 and 16‐year‐old Eucalyptus nitens stands. Our results show that precipitation, stream and soil solution plot approximately along the LMWL, while xylem waters from all studied tree species plot below the LMWL, supporting the TWW hypothesis. However, we also found evidence of ecohydrological connectivity during the wet season, likely controlled by the amount of antecedent precipitation. These observations hold for all investigated tree species. On both sites, a different precipitation source for stream and xylem water was observed. However, in EP, bulk soil showed a similar precipitation source as xylem water from both E. nitens stands. This suggests that E. nitens may use water that is recharging the bulk soil compartment. We conclude that under a rainy temperate climate, the TWW hypothesis is temporal and does not apply during wet seasons. Copyright © 2016 John Wiley & Sons, Ltd.     

Parallelized combined finite-discrete element (FDEM) procedure using multi-GPU with CUDA

This paper focuses on the efficiency of finite discrete element method (FDEM) algorithmic procedures in massive computers and analyzes the time-consuming part of contact detection and interaction computations in the numerical solution. A detailed operable GPU parallel procedure was designed for the element node force calculation, contact detection, and contact interaction with thread allocation and data access based on the CUDA computing. The emphasis is on the parallel optimization of time-consuming contact detection based on load balance and GPU architecture. A CUDA FDEM parallel program was developed with the overall speedup ratio over 53 times after the fracture from the efficiency and fidelity performance test of models of in situ stress, UCS, and BD simulations in Intel i7-7700K CPU and the NVIDIA TITAN Z GPU. The CUDA FDEM parallel computing improves the computational efficiency significantly compared with the CPU-based ones with the same reliability, providing conditions for achieving larger-scale simulations of fracture.     

基于决策树分类的大屯矿区地物信息提取及矿区污染分析

本文在对国内外遥感图像分类方法充分研究分析的基础上,选择决策树分类法对大屯矿区的Landsat 8遥感图像进行分类研究。选取样本提取并分析研究区典型地类光谱特征曲线,依据光谱曲线特征和归一化植被指数建立了土地利用分类决策树模型,通过反复试验和修正,筛选出适宜大屯矿区地物分类的决策树最优阈值,对研究区进行分类和精度评价,最后通过分类结果对研究区的水体污染状况进行简要分析。     

北斗系统周跳探测与修复方法探究

北斗卫星导航系统是中国自行研制的继美国GPS和俄罗斯GLONASS之后第3个成熟的卫星导航系统。进行GNSS相位数据处理的过程中,由于某种原因,载波相位观测值突然出现整周数的跳变的现象称为周跳。周跳现象的发生将会严重影响后续的数据处理,因此,有必要在解算前完成周跳探测与修复工作。本文就北斗系统周跳探测与修复课题进行了较为全面的探究,先后介绍了高次差法、多普勒法、伪距载波相位组合法、电离层残差法、三频数据组合探测法等一系列周跳探测与修复方法,可分别应用于不同频段接收机、不同观测环境、不同数据处理模式。     

L1范数与IQR统计量组合的GNSS坐标序列粗差探测算法

GNSS坐标时间序列中不可避免地含有粗差,未剔除的粗差将会导致参数估计有偏。因此,粗差探测与剔除是GNSS坐标序列分析中一项重要的数据预处理工作。针对GNSS坐标时间序列特点,提出了一种将L1范数(L1-norm)估计与四分位距统计量IQR(interquartile range)组合的移动开窗粗差探测算法,称之为L1_Mod IQR。该方法的主要思想是,首先利用L1范数估计得到较"真实"的残差,然后再对残差采用IQR统计量进行粗差探测。将L1_Mod IQR法与"3σ"法、基于最小二乘的τ检验法等粗差探测算法进行了模拟计算与对比,验证了该算法的有效性。进一步采用L1_Mod IQR算法对中国区域10个IGS站的高程时间序列进行了分析,结果表明中国区域IGS站高程序列的粗差剔除率最小为0.1%,最大为2.6%。并且以WUHN站为例与SOPAC提供的结果进行了对比,结果表明SOPAC提供的"Clean"数据仍含有大量的粗差,而L1_Mod IQR算法能够有效地剔除粗差。     

风暴分类识别技术在人工防雹中的应用

利用新一代多普勒天气雷达资料,在风暴跟踪识别算法的基础上,发展了风暴分类技术,以提高人工防雹作业指挥的效率。首先以SCIT算法为基础,结合风暴的结构特征,综合利用雷达、探空资料,自动提取风暴结构特征指数;其次采用基于决策树模型的风暴自动分类技术,将风暴按强度分为雷雨云、单体风暴、多单体风暴和强风暴;最后根据风暴强度、高度和位置等属性,对有可能产生冰雹的单体,结合GIS,自动对下游方向或附近作业点进行预警或输出作业参数。通过对2006—2014年期间重庆、辽宁大连和河南三门峡三地发生的较为典型的31次冰雹天气过程、182站次冰雹样本的检验来看:该方法通过对风暴按强度、垂直结构等综合属性进行分类,能有效提高冰雹识别的命中率、降低空报率,其中强风暴的命中率能达到100%,空报率仅为11.4%。能有效提高人工防雹作业的自动化程度,对防雹作业的科学决策有着重要参考作用。     

ZQZ TF型风传感器冻结故障自动检测装置设计

近年来我国大部分地区在冬、春两季多遭受冻雨灾害,自动气象站的风向风速传感器容易因冻结而无法正常工作。针对冻结故障的实时检测问题,本文设计了一种基于ZQZ-TF型风传感器的故障自动检测装置。该装置通过检测风传感器的工作电压和工作电流,实现对传感器实时状态的监控。同时,结合具体的故障诊断算法,能够快速判断风传感器是否被冻结。系统的核心硬件电路、软件算法可分别集成在自动气象站风向风速数据采集电路和嵌入式软件中,具有结构紧凑、操作简单的特点。经验证,该装置能够实时检测风传感器冻结故障,且工作稳定,检测精度高。     

Retrieval of effective leaf area index (LAIe) and leaf area density (LAD) profile at individual tree level using high density multi-return airborne LiDAR

As an important canopy structure indicator, leaf area index (LAI) proved to be of considerable implications for forest ecosystem and ecological studies, and efficient techniques for accurate LAI acquisitions have long been highlighted. Airborne light detection and ranging (LiDAR), often termed as airborne laser scanning (ALS), once was extensively investigated for this task but showed limited performance due to its low sampling density. Now, ALS systems exhibit more competing capacities such as high density and multi-return sampling, and hence, people began to ask the questions like—“can ALS now work better on the task of LAI prediction?” As a re-examination, this study investigated the feasibility of LAI retrievals at the individual tree level based on high density and multi-return ALS, by directly considering the vertical distributions of laser points lying within each tree crown instead of by proposing feature variables such as quantiles involving laser point distribution modes at the plot level. The examination was operated in the case of four tree species (i.e. Picea abies, Pinus sylvestris, Populus tremula and Quercus robur) in a mixed forest, with their LAI-related reference data collected by using static terrestrial laser scanning (TLS). In light of the differences between ALS- and TLS-based LAI characterizations, the methods of voxelization of 3D scattered laser points, effective LAI (LAIe) that does not distinguish branches from canopies and unified cumulative LAI (ucLAI) that is often used to characterize the vertical profiles of crown leaf area densities (LADs) was used; then, the relationships between the ALS- and TLS-derived LAIes were determined, and so did ucLAIs. Tests indicated that the tree-level LAIes for the four tree species can be estimated based on the used airborne LiDAR (R² = 0.07, 0.26, 0.43 and 0.21, respectively) and their ucLAIs can also be derived. Overall, this study has validated the usage of the contemporary high density multi-return airborne LiDARs for LAIe and LAD profile retrievals at the individual tree level, and the contribution are of high potential for advancing forest ecosystem modeling and ecological understanding.