Comparative Analysis of Climatic Change Trend and Change-Point Analysis for Long-Term Daily Rainfall Annual Maximum Time Series Data in Four Gauging Stations in Niger Delta

The aim of this study is to establish the prevailing conditions of changing climatic trends and change point dates in four selected meteorological stations of Uyo, Benin, Port Harcourt, and Warri in the Niger Delta region of Nigeria. Using daily or 24-hourly annual maximum series (AMS) data with the Indian Meteorological Department (IMD) and the modified Chowdury Indian Meteorological Department (MCIMD) models were adopted to downscale the time series data. Mann-Kendall (MK) trend and Sen’s Slope Estimator (SSE) test showed a statistically significant trend for Uyo and Benin, while Port Harcourt and Warri showed mild trends. The Sen’s Slope magnitude and variation rate were 21.6, 10.8, 6.00 and 4.4 mm/decade, respectively. The trend change-point analysis showed the initial rainfall change-point dates as 2002, 2005, 1988, and 2000 for Uyo, Benin, Port Harcourt, and Warri, respectively. These prove positive changing climatic conditions for rainfall in the study area. Erosion and flood control facilities analysis and design in the Niger Delta will require the application of Non-stationary IDF modelling.

Spatio-Temporal Change of Dispersal Areas of Greater Kudu (Tragelaphus strepsiceros) in Lake Bogoria Landscape, Kenya

Decline in wildlife populations is manifest globally, regionally and locally. A wildlife decline of 68% has been reported in Kenya’s rangelands with Baringo County experiencing more than 85% wildlife loss in the last four decades. Greater Kudu (Tragelaphus strepsiceros) is endemic to Lake Bogoria landscape in Baringo County and constitutes a major tourist attraction for the region necessitating use of its photo on the County’s logo and thus a flagship species. Tourism plays a central role in Baringo County’s economy and is a major source of potential growth and employment creation. The study was carried out to assess spatio-temporal change of dispersal areas of Greater Kudu (GK) in Lake Bogoria landscape in the last four years for enhanced adaptive management and improved livelihoods. GK population distribution primary data collected in December 2022 and secondary data acquired from Lake Bogoria National Game Reserve (LBNGR) for 2019 and 2020 were digitized using in a Geographic Information System (GIS). Measures of dispersion and point pattern analysis (PPA) were used to analyze dispersal of GK population using GIS. Spatio-temporal change of GK dispersal in LBNR was evident thus the null hypothesis was rejected. It is recommended that anthropogenic activities contributing to GK’s habitat degradation be curbed by providing alternative livelihood sources and promoting community adoption of sustainable technologies for improved livelihoods.

Change Point Detection and Trend Analysis for Time Series

Trend analysis and change point detection in a time series are frequent analysis tools.Change point detection is the identification of abrupt variation in the process behaviour due to natural or artificial changes,whereas trend can be defined as estimation of gradual departure from past norms.We analyze the time series data in the presence of trend,using Cox-Stuart methods together with the change point algorithms.We applied the methods to the nearsurface wind speed time series for Australia as an example.The trends in near-surface wind speeds for Australia have been investigated based upon our newly developed wind speed datasets,which were constructed by blending observational data collected at various heights using local surface roughness information.The trend in wind speed at 10 m is generally increasing while at 2 m it tends to be decreasing.Significance testing,change point analysis and manual inspection of records indicate several factors may be contributing to the discrepancy,such as systematic biases accompanying instrument changes,random data errors(e.g.accumulation day error)and data sampling issues.Homogenization technique and multiple-period trend analysis based upon change point detections have thus been employed to clarify the source of the inconsistencies in wind speed trends.

Urban Wind Speed Analysis in Global Climate Change Perspective: <i>Karachi as a Case Study</i>

It is now well known that coastal urban local climate has been showing changing pattern due to global climate change. This communication attempts to explore fluctuating pattern of urban average monthly wind speed during past 50 years (1961-2010). It shows peculiar results taking Karachi (24?53'N, 67?00'E), a coastal mega-city of Pakistan, as a case study. Mann-Kendall trend test shows that March, April and October and both summer and winter seasons show positive trends for the average monthly wind speed during the whole study period (1961-2010). For the earlier 25 years data, it has been found that January, March, May, August, November and December and annual wind speed data have shown the negative trends. Only summer season has shown the positive trend for the wind speed. Similarly, for the most recent 25 years data it has been found that January, February, March, April, May, June, October, November and December and annual and both summer and winter wind speed data have shown the positive trends showing some degree of change in wind speed pattern. Probabilistic analysis reveals that average monthly wind speed data sets follow lognormal, logistic, largest extreme value, and Weibull (two-and three-parameters) probability distributions. Change point analysis has also confirmed the change in the pattern of observed average monthly wind speed data near 1992. The analysis performed reveals the effect of global warming on the local urban wind speed which appears to be temporal non-stationary.

Non-Stationary Trend Change Point Pattern Using 24-Hourly Annual Maximum Series (AMS) Precipitation Data

This paper mainly investigated the basic information about non-stationary trend change point patterns. After performing the investigation, the corresponding results show the existence of a trend, its magnitude, and change points in 24-hourly annual maximum series (AMS) extracted from monthly maximum series (MMS) data for thirty years (1986-2015) rainfall data for Uyo metropolis. Trend analysis was performed using Mann-Kendall (MK) test and Sen’s slope estimator (SSE) used to obtain the trend magnitude, while the trend change point analysis was conducted using the distribution-free cumulative sum test (CUSUM) and the sequential Mann-Kendall test (SQMK). A free CUSUM plot date of change point of rainfall trend as 2002 at 90% confidence interval was obtained from where the increasing trend started and became more pronounced in the year 2011, another change point year from the SQMK plot with the trend intensifying. The SSE gave an average rate of change in rainfall as 2.1288 and 2.16 mm/year for AMS and MMS time series data respectively. Invariably, the condition for Non-stationary concept application is met for intensity-duration-frequency modeling.

城市连续隧道交织区主线交织车辆换道点选择行为研究

基于城市连续隧道交织区分析主线交织车辆换道点选择行为,以实地采集的车行轨迹数据为基础,利用随机森林模型分析主线车辆换道点选择行为特征及影响行为决策的影响因素,而后分别采用支持向量机模型与随机森林模型进行换道点选择行为决策建模和对比分析。研究结果表明:影响主线交织车辆换道点选择的主要因素为目标车辆状态以及本车道的后车状态,且经特征筛选之后建立换道决策模型的精度更高,其中支持向量机模型可以较好的刻画换道行为,模型的预测精度不低于85%。研究成果有助于在仿真模型中更准确描述换道点选择行为,同时为城市连续隧道交织区的优化和辅助驾驶策略制定提供支撑。

1950-2007年黄河入海水沙通量变化趋势及突变特征

基于1950-2007年黄河利津站水沙数据,采用Mann-Kendall检验以及Mann-Whitney-Pettitt(MWP)与贝氏变点分析方法来分析黄河入海水沙通量变化规律,结果表明:黄河全年入海径流通量与泥沙通量分别以-8.1139亿m3/a和-0.2285亿t/a速率显著减少,汛期变化幅度大于非汛期,尤以泥沙通量为甚;全年以及汛期和非汛期入海径流通量与泥沙通量时序均存在显著转折,且各自变点出现时间不完全一致,全年入海径流通量与泥沙通量时序转折分别发生于1968年、1985年、2002年和1968年、1985年、1996年;入海水沙通量变化趋势与时序变点与流域自然因素变化与人类活动影响密切相关,部分变点出现时间与人类活动介入相吻合。

MDCPD:基于矩阵序列距离度量的数字生态变点检测

数字生态系统是一个分布式的、适应性的、开放的社会技术系统.随着大数据、物联网、云计算等技术的发展,数字生态的表现形式逐渐复杂多样,与人们的生活更加密切.数字生态受内外部激励自发性地持续演化,一些事件的发生可能会使数字生态的部分性质显著变化,偏离其正常的演化路径,进而导致生态伴随着异常不健康地发展,如果能够及时发现这些变化并定位引起变化的事件,然后加以人为干预,则可能将负面影响降到最低.动态复杂网络是一个辅助观测数字生态的有效工具,这使分析生态的演化情况成为可能,复杂网络分析领域中的变点检测是检测数字生态演化变点的主要技术手段之一.然而,目前已有的通用的变点检测方法未针对数字生态做出优化,忽视了数字生态的高度动态等特性,会导致这些方法可能无法在高度动态、持续变化的情况下检测变点,于是,已有方法在数字生态场景上的变点检测性能可能不佳.为解决上述问题,本文提出基于矩阵序列距离度量的数字生态变点检测方法(MDCPD),MDCPD是社区感知的,它从数字生态的社区视角观测数字生态的变化幅度,通过计算社区矩阵距离变化率在在连续时间动态网络建模的数字生态上高效地实现了变点检测,且变点检测和数字生态演化动因定位均是事件级别,能帮助生态的管理人员高效地进行干预和决策.为抵抗社区结构矩阵序列数据中的噪声对方法的影响,本文提出了矩阵干预策略,通过从数字生态中观测到的客观条件干预社区结构矩阵的数值,提高了社区结构矩阵序列对数字的生态结构表达能力.本文在基于合成数据的连续时间和离散时间两个场景的对比实验以及消融实验证明了MDCPD和矩阵干预策略的有效性,MDCPD的F1指标至多超过SOTA方法0.383,矩阵干预策略至多使MDCPD的F1指标提高了0.053.最后,本文在真实数字生态数据集上进行了案例分析,进一步说明了MDCPD的实践价值.

南海陆坡海底峡谷地形复杂度分析方法

地形复杂度指数是描述地形变化程度的综合指标,本文基于南海陆坡北港隆起区的水深网格数据,采用均值变点分析法确定地形起伏度的最佳统计单元,建立计算海底地形复杂度的模型,融合研究区坡度、地形起伏度、地表切割深度和高程变异系数4种地形因子,分析研究区的地形特征和地形复杂度。结果表明,研究区地形起伏度最佳分析窗口大小为19×19网格,最佳统计窗口面积为1.7689 km^(2);研究区北部及南部区域地形平坦,地形复杂程度较低,复杂度指数<2.35;中部区域存在规模不同的峡谷,地形复杂程度较高,复杂度指数平均>3.37,其中,中部偏东区域因海底峡谷最为发育,地形复杂度指数可达7.77。研究区地形复杂度的定量分析结果与海蚀作用的强弱程度呈现出较好的正相关性,这对系统开展南海海底峡谷形态特征及演化过程研究、维护海洋工程设施安全等具有重要借鉴意义。

基于浓度与流量突变的河流总磷通量估算

为进一步加深对流量与水质浓度突变特征的理解,探究浓度与流量突变点对通量模拟的影响,本研究基于Mann-Kendall突变检验法以及贝叶斯突变点模型,对潮河流域20多年来(1992—2014年)的径流量、总磷(TP)浓度以及二者之间关系进行突变分析,并结合LOADEST模型估算TP通量。结果表明:潮河流域径流、TP浓度整体均呈下降趋势,径流突变点发生于1998年,突变前后的平均流量分别为7.92 m^(3)·s^(-1)和2.86 m^(3)·s^(-1);TP浓度突变点发生于1993年和1996年,1992—1993年、1994—1996年和1997—2014年平均浓度分别为0.08、0.06 mg·L^(-1)和0.03 mg·L^(-1)。TP浓度-流量关系在2004年12月前后发生突变,前后两个阶段的流量阈值分别为2.36 m^(3)·s^(-1)和9.08 m^(3)·s^(-1)。突变点前,TP浓度与流量的关系是典型的流量驱动模式;突变点后二者关系会在高流量情况下转变为稀释主导模式。基于突变点识别的分段建模有助于改善LOADEST模型的模拟效果,而不同类型突变点各有优势。基于TP浓度突变点的分段模型的整体模拟效果最佳,使纳什系数从0.50提高到0.96;基于浓度-径流关系突变点的模型对关系突变后TP通量的模拟效果最佳,使纳什系数从-0.31提高到0.89。此外本研究讨论了降水及流域管理措施的可能影响。研究表明,进行水质建模及负荷模拟时,考虑水质浓度与流量及其关系的突变可在一定程度上提高模型的适用性。

基于极点对称模态分解的石羊河流域出山径流特征分析

随着全球气候变化加剧,石羊河流域水资源紧缺日益严重,利用合理方法研究径流的变化规律对水资源规划管理尤为重要。基于石羊河流域1956—2018年出山径流量时间序列,利用极点对称模态分解(ESMD)方法,分析石羊河出山径流序列的周期变化、突变特征和变化趋势,并利用Morlet小波分析、Mann-Kendall检验法及R/S分析法进行对比验证分析。结果表明:ESMD方法能够高效地分析处理径流数据;石羊河出山径流序列存在3.0、7.3、12.6 a的周期变化,不同时间尺度发生突变的时间不同;预测短期内石羊河出山径流量仍将持续增加,但是长期必然呈现减少趋势。

基于TFPW-DT-ICSS法的渭河水文序列方差变异识别与诊断

水文变异现象已造成许多地区的水文数据受到"污染",使得传统水文频率计算举步维艰。同时,水文变异识别方法的异法异解、隐藏效应、自相关性影响、变异信息交叉等问题也困扰着水文变异理论的发展,亟待解决。针对水文变异识别中的序列自相关性影响,提出将去趋势、预置白与ICSS检验法相结合,构建TFPW-DT-ICSS法,对渭河咸阳水文站的径流数据进行方差变异的多点识别,同时应用水文频率计算方法验证变异点的准确性。结果表明:TFPW-DT-ICSS法通过TFPW处理,可缓解序列自相关性对结果的影响;ICSS算法在方差变异检验上可获得较为准确的识别结果,适用于水文序列的方差变异诊断;ICSS算法对数据长度变化的响应不敏感,可实现多序列上的有效识别。研究成果可为变化环境下的水文计算与设计提供数据支持和技术支撑。

基于多突变点与模板匹配的用电设备在线状态监测方法

针对现阶段用电设备状态监测技术存在的处理速度较慢、准确率较低等问题,文中基于多突变点检测和模板匹配策略提出了一种用电设备在线状态监测方法。该方法在缓冲区模型和滑动窗口模型的基础上,利用多路搜索树突变点检测(Ternary Search Tree and Kolmogorov-Smirnov,TSTKS)算法形成窗口维度和缓冲区维度的特征向量,通过两种维度的模板匹配实现用电设备的运行状态匹配和状态切换时刻定位。基于家用电冰箱的仿真实验结果表明,所提方法具有检测速度快、准确率高等优点,可为用电设备状态监测领域提供参考。

基于ASTER GDEM的黑龙江省地形起伏度分析

地形起伏度是描述地貌形态的重要指标,反映了研究区域内地势起伏特征。以黑龙江省为研究区域、以30 m分辨率的ASTER GDEM(先进星载热发射和反射辐射仪全球数字高程模型)数据为基础,在ArcGIS平台上利用领域分析法分析不同窗口大小下的地形起伏度,通过均值变点法得出最佳统计单元面积为0.396 9 km^(2)。在此基础上对黑龙江省地势起伏度进行分析。结果表明黑龙江省地形起伏可分为4类,主要以台地、丘陵为主,平原占比次之。

基于多时相Landsat影像的河流边滩提取研究

河流边滩是因河流沉积作用在岸边形成的沉积物,其变化可以间接反映出河流形态及其周围环境的演变。河流边滩的动态监测对于河流生态系统研究和航道管理有着非常重要的意义。针对河流边滩与部分建筑物影像光谱相似而难以区分的问题,基于Landsat影像中边滩与河流的光谱、空间和物候等多维差异化特征,提出了一种新的河流边滩提取方法,综合利用多时相水体指数的二值变化检测方法和面向对象分析方法,成功提取了赣江中下游的河流边滩。一方面丰富了河流边滩监测的方法,为地理学研究提供新的观察视角;另一方面为赣江流域生态系统建设、环境治理和航运规划管理提供更丰富的河流边滩数据。

基于模糊聚类分析的高铁CPI稳定性判别

运营期高铁精测网复测线上CPI点的稳定性分析是关乎最终CPII成果质量的关键一环,对不稳定线上CPI点的误判或漏判都会严重影响CPI平面成果,无法为轨道精调提供可靠基准,影响列车的行车安全。点位的稳定性分析是典型的模糊问题,稳定和不稳定的界限不明显,在无法保证线上CPI成果完全无误差的情况下,难以用限差精确划分稳定与不稳定。本文针对现有判断线上CPII点稳定性的方法不足之处,结合高铁线上CPI控制点复测更新判定指标具有的模糊性,引入模糊聚类分析,对点位变化量建立模糊相似矩阵,利用动态聚类图得到分类过程,计算变形水平值确定最优分类,并结合实测数据对聚类结果进行分析,证明此种方法在线上CPI点稳定性分析中的有效性。

基于SRTM-DEM的安徽省地貌分类研究

基于分辨率为90 m的SRTM-DEM数据,采用地理信息系统(GIS)技术,提取安徽省的地貌特征要素信息,并根据均值变点分析统计方法,定量地获取研究区域内的最佳地势起伏度的统计面积。根据中国地貌类型划分标准,将安徽省地貌类型划分为11种类型,其中分布较广的主要为中起伏中山、中起伏山地、小起伏山地、低海拔丘陵、低海拔台地、低海拔平原,并分别统计各类型面积。结果表明,该文研究方法能够定量、科学地对安徽省地貌形态进行分类。

Population Spatial Distribution Based on Luojia 1-01 Nighttime Light Image:A Case Study of Beijing

With the continuous development of urbanization in China,the country’s growing population brings great challenges to urban development.By mastering the refined population spatial distribution in administrative units,the quantity and agglomeration of population distribution can be estimated and visualized.It will provide a basis for a more rational urban planning.This paper takes Beijing as the research area and uses a new Luojia1-01 nighttime light image with high resolution,land use type data,Points of Interest(POI)data,and other data to construct the population spatial index system,establishing the index weight based on the principal component analysis.The comprehensive weight value of population distribution in the study area was then used to calculate the street population distribution of Beijing in 2018.Then the population spatial distribution was visualize using GIS technology.After accuracy assessments by comparing the result with the WorldPop data,the accuracy has reached 0.74.The proposed method was validated as a qualified method to generate population spatial maps.By contrast of local areas,Luojia 1-01 data is more suitable for population distribution estimation than the NPP/VIIRS(Net Primary Productivity/Visible infrared Imaging Radiometer)nighttime light data.More geospatial big data and mathematical models can be combined to create more accurate population maps in the future.

阶跃型滑坡综合变形预测及监测预警方法研究

大型库岸滑坡的长期变形在汛期降雨作用下呈现明显的周期性“阶跃式”陡增特征。针对阶跃型滑坡的变形特征,本文提出了一种多源数据“融合-预测-预警”的三步式滑坡监测预警方法:(1)“融合”,即基于经验模态分解法将多点位移监测数据分别分解为趋势项和周期项,采用加权值法分别融合不同监测点的趋势项和周期项位移得到融合趋势项和融合周期项序列,并将两者叠加得到滑坡体的现状综合变形时间序列;(2)“预测”,即引入“一个预测周期”概念,采用滑动多项式拟合法和随机森林算法分别对融合趋势项和融合周期项进行预测并叠加得到滑坡体的预测综合变形时间序列;(3)“预警”,即基于斜率变点分析方法搜索综合变形曲线的“稳定点”和“跃迁点”,确定稳定变形和加速变形区间的斜率,建立阶跃型滑坡的四级递进式分级预警模型,基于该预警模型对滑坡现状进行预警。以向家坝水库某滑坡体自动化位移监测数据为研究对象,采用本文所提方法对该滑坡进行了综合变形预测和监测预警,结果表明:综合变形时间序列可以整体反映滑坡的变形演化规律,且预测结果可靠,根据分级预警模型判断此滑坡体当前处于稳定变形阶段(Ⅰ级预警)。

多源DEM数据在山区流域河网提取中的对比

针对何种DEM数据更适合山区流域的河网提取,选择长江上游与珠江上游的山区流域,以ALOS 12.5 m DEM、ASTER 30 m GDEM与SRTM 90 m DEM为基础数据,基于Arcpy提取研究区域河网,通过河网套合差、Arc Hydro Tools对提取结果进行修正与评价,探讨山区流域最佳集水面积阈值的选择与地形特征对数字河网提取的影响。结果表明:①分辨率为12.5 m的ALOS DEM河网套合差最小,能更真实地反映山区流域的水系发育程度;②通过Arc Hydro Tools修正DEM数据,3种DEM的河网套合差均减小,可明显提高河网的提取精度;③基于均值变点分析法确定研究区最佳集水面积阈值,ALOS DEM的最佳集水面积阈值为20000,ASTER GDEM与SRTM DEM为500;④大起伏山地有利于河网的提取,ALOS DEM提取效果最佳。因此,经过修正的ALOS DEM提取流域水系效果最佳,成果可为山区流域提取水系提供一定的参考和借鉴。