Application of different clustering approaches to hydroclimatological catchment regionalization in mountainous regions,a case study in Utah State

With respect to the different hydrological responses of catchments, even the adjacent ones, in mountainous regions, there are a great number of motivations for classifying them into homogeneous clusters. These motivations include prediction in ungauged basins (PUB), model parameterization, understanding the potential impact of environmental changes, transferring information from gauged catchments to the ungauged ones. The present study investigated the similarity of catchments through the hydro-climatological pure time-series of a 14-year period from 2001 to 2015. Data sets encompass more than 13,000 month-station streamflow, rainfall, and temperature data obtained from 27 catchments in Utah State as one of the eight mountainous states of the USA. The identification, analysis, and interpretation of homogeneous catchments were investigated by applying the four approaches of clustering, K-means, Ward, and SOM (Self-Organized Map) and a newly proposed Wavelet-Entropy-based (WE-SOM) clustering method. By using two clustering evaluation criteria, 3, 5, and 6 clusters were determined as the best numbers of clusters, depending on the method employed, where each cluster represents different hydro-climatological behaviors. Despite the absence of geographic characteristics in input data matrix, the results indicated a regionalization in agreement with topographic characteristics. Considering the dependency of the hydrological behavior of catchments on the physiographic field aspects and characteristics, WE-SOM method demonstrated a more acceptable performance, compared to the other three conventional clustering methods, by providing more clusters. WE-SOM appears to be a promising approach in catchment clustering. It preserves the topological structure of data which can, as a result, be proofed in a greater number of clusters by dividing data into higher numbers of distinct clusters with similar altitudes of catchments in each cluster. The results showed the aptitude of wavelets to quantify the time-based variability of temperature, rainfall and streamflow, in the way contributing to the regionalization of diverse catchments.     

基于MST聚类的空间数据离群挖掘算法

空间离群是指空间邻域中属性特征值明显不同于其他对象的空间对象,空间数据离群挖掘能为人们提供很多有趣的信息,但空间数据具有复杂的拓扑关系、方位关系和度量关系等空间特征,传统的面向事务型数据库的离群挖掘算法并不适用于空间数据库。本文提出了基于MST(Minimum Spanning Tree,最小生成树)聚类的空间数据离群挖掘算法(SOM);有机结合了最小生成树理论与密度的方法,既体现了空间离群的局部特性,又体现了空间离群的孤立程度。该算法通过MST维护空间数据的基本空间结构特征,通过打断MST中最不一致的边形成MST聚类,不仅具有密度的聚类方法能够聚集非球状簇和分布不均的数据集的特点,而且聚类结果不依赖于用户参数的选择,因此,离群挖掘结果更合理。最后,通过实例数据,验证了该算法的有效性,它适用于大规模空间数据集的离群挖掘。     

遥感及再分析降水产品在缺资料干旱内陆盆地的适用性评估

山区降水较集中,但降水测站多位于山谷或人口密集区,代表性差。遥感和再分析降水产品能提供时空分布连续的数据,不受地形条件限制。柴达木盆地中心属干旱荒漠区,水是制约该区开发的首要条件,其四周属高寒山区,降水相对较多,但降水监测十分薄弱。为获取该区相对精确的降水时空分布信息,本文评估了4套高分辨率降水产品（CMADS、TRMM、GPM和MSWEP）的适用性。首先基于地面站点数据评估它们在不同时空尺度上的精度,并分析它们在柴达木盆地的空间分布和年内分配特征。然后,以盆地东南隅的无测站山区香日德河流域为研究区,利用降水产品驱动SWAT模型来评估它们的分布式水文模拟适用性。结果表明：(1) MSWEP在年、月尺度上与站点降水的吻合程度最高（R≥0.79,PBIAS=0.5%）,其次是GPM和TRMM,CMADS精度最低（R≥0.64,PBIAS=5.8%）;(2)从降水精度与站点高程的关系来看,降水产品在相对低海拔区容易高估站点降水,而在相对高海拔区常低估实际降水;(3)在香日德河流域,MSWEP(NSE=0.64)在基准期（2009—2012年）的径流模拟表现明显好于其它降水产品（NSE=0.3...     

一种逐级合并OD流向时空联合聚类算法

现有OD流向聚类多将O点和D点相分离或者将OD流向看作4维空间的数据点进行聚类处理,忽视了流向长度、方向、时间对流向聚类的影响。本文以流向作为研究对象,提出一种基于流向间相似性度的逐级合并OD流向时空联合聚类算法。首先在充分研究OD流向的空间信息和时间信息的基础上,构建合理的OD流向间时空相似性度量方法,对OD流向间的时空相似性进行量化;然后提出逐级合并OD流向聚类策略,优化类簇合并的顺序,以减少层次聚类的时间开销,实现OD流向的时空联合聚类。以成都市的滴滴出行OD数据和纽约市出租车数据为例对本文方法进行了验证,结果表明：① 本算法聚类获得的流向类簇不仅带有空间特征还具备时间特征;② 在不同参数下本方法可以得到不同时空尺度的聚类结果;③ 与现有较高水平的流向聚类算法相对比,本文方法的聚类效果更好。这体现在流向类簇内部的流向之间有着充分的相似性,以及本文方法不仅可以提取出显著的流向类簇,还可以提取出非热点区域之间的流向类簇。本算法顾及空间因素和时间因素,可以通过调整时空相似性度量方法中的时间参数和空间参数以实现不同时空尺度的流向聚类,这使得从不同时空角度研究城市居民出行模式成为可能。本文提出的OD流向时空联合聚类算法从联合时间信息和空间信息的角度获得对运动数据的新见解,有助于合理全面地研究居民的移动模式、区域之间的空间联系、已知出行结构的确定以及出行目的的探索,是后续一系列分析工作的基础。     

结合TRMM数据的区域降水高精度曲面建模研究

高精度曲面建模方法（High Accuracy Surface Modeling, HASM）,从理论上解决了传统方法在插值过程中峰值削平和边界震荡等问题。其模拟精度相对于经典插值方法有很大提高,已成功应用于人口密度、土壤属性,以及气候要素等领域的空间制图。然而,由于地面气象站点数量和分布的限制,使得HASM仅依靠站点数据难以得到高精度的空间降水估计数据,因此,本文以地貌与气候类型复杂多样的我国中西部地区2010年年降水量空间分布模拟为例,采用混合插值法进行HASM区域降水模拟。结果表明,TRMM作为背景场的HASM模拟的年降水量精度,在全局和局部明显优于IDW、Spline和Kriging等经典插值方法的结果,作为背景场的HASM模拟精度,MAE和RMSE分别为125.15 mm和155.80 mm,其他方法最好的模拟结果比其误差值分别高出53.6%和54.5%;其模拟误差在不同子区域都较小;各种方法在平原的精度都高于山区的精度。     

Probability Prediction Model for Landslide Occurrences in Xi’an,Shaanxi Province,China

Landslides are increasing since the 1980s in Xi’an, Shaanxi Province, China. This is due to the increase of the frequency and intensity of precipitation caused by complex geological structures, the presence of steep landforms, seasonal heavy rainfall, and the intensifcation of human activities. In this study, we propose a landslide prediction model based on the analysis of intraday rainfall （IR） and antecedent effective rainfall （AER）. Primarily, the number of days and degressive index of the antecedent effective rainfall which affected landslide occurrences in the areas around Qin Mountains, Li Mountains and Loess Tableland was established. Secondly, the antecedent effective rainfall and intraday rainfall were calculated from weather data which were used to construct critical thresholds for the 10%, 50% and 90% probabilities for future landslide occurrences in Qin Mountain, Li Mountain and Loess Tableland. Finally, the regions corresponding to different warning levels were identified based on the relationship between precipitation and the threshold, that is; “A” region is safe, “B” region is on watch alert, “C” region is on warning alert and “D” region is on severe warning alert. Using this model, a warning program is proposed which can predict rainfall-induced landslides by means of real-time rain gauge data and real-time geo-hazard alert and disaster response programs. Sixteen rain gauges were installed in the Xi’an region by keeping in accordance with the regional geology and landslide risks. Based on the data from gauges, this model accurately achieves the objectives of conducting real-time monitoring as well as providing early warnings of landslides in the Xi’an region.     

滇池流域降水时空变异特征分析

降水是区域水资源形成的主要影响因素,其时空变化趋势也直接影响着各种生态系统的结构、服务功能及空间分布与演变。降水时空变异分析是认识区域水资源形成与时空演变的主要手段和方法。本文利用滇池流域及周边雨量站逐月数据,采用回归分析、距平、空间相关性分析、Mann-Kendall检验、Co-kriging插值及交叉验证等方法,对1953-1987年和2007-2012年2个时序系列的时空变异特征分析结果表明：（1）1953-1987年春、秋和冬季降水量有升高趋势,夏季呈减少趋势,但各季节的增减趋势不显著,2007-2012年春、夏、冬季呈减少趋势,秋季为增加趋势,近期降水量明显有减少趋势;（2）1953-1987年流域降水量呈现增加趋势（11.12 mm/10a）,大致经历下降-上升-下降过程,2007-2012年流域降水量呈显著的锯齿状减少趋势,处于枯水期;（3）1953-1987年各时段的雨量主要呈现负相关性（不显著）,2007-2012年间呈现正相关性,通过LISA统计分析认为,空间异质性随地理位置和时间而变化;（4）年均降水量与雨季降水量的空间分布特征基本相似,出现2个降水高值区和2个低值区对顶分布态势。但在2007-2012年,降水量的高值范围有所减少,低值区范围相应有所扩大。     

近60年“雅安天漏”变化特征分析

针对雅安地区特殊的"天漏"气候特征及以往对其变化特征研究较少问题,利用雅安市1951~2010年降水资料,从降水量和雨日数出发,通过回归分析、小波分析等现代气候统计诊断方法,综合分析"雅安天漏"的变化特征。结果表明:在降水量上,雅安市年降水量总体呈显著减小趋势,20世纪90年代中期以后尤为明显;从季节尺度上来看,春、夏、秋三季降水量呈现明显减少趋势,但冬季与之相反;从逐月降水比重可以看出,极大值主要出现在7、8、9月;从量级上看,小雨、中雨、大雨的降水量均在减小,暴雨却在增加,但各量级降水所产生的降水量与全年总降水量的比值相对比较稳定。从雨日数上看,雅安市四季的雨日数均表现出减少趋势,各个强度量级的雨日数也均在波动减小。小波分析结果显示:年降水量和雨日数在年代际时间尺度均存在准周期振荡。     

基于Gabor滤波方法的居民地识别分析

图像纹理对于高分辨率遥感图像的信息提取与目标识别具有重要意义。针对"北京一号"小卫星全色遥感图像非城市区域居民地块往往呈现出比较明显的方向性纹理的特点,扩充改进Gabor滤波方法进行提取。方法主要利用Gabor滤波器的多尺度、多方向滤波的性质,提取多尺度纹理特征集,并进行特征;而后利用多特征聚类实现图像的初步分割。由于分割是对特征进行聚类完成的,其结果可能存在一个居民地块由若干个相互间存在间隔的子区域组成、存在无用小斑块、居民地内部存在大量小孔洞等缺陷。针对上述不足,利用形态学尺度空间融合方法,对居民地块通过结构元素不断增大的闭运算进行迭代融合,并选择一个具备"最长生存期限"的类别个数作为最佳类数,选择首次出现该类别数的分割结果作为最后的识别结果。对延庆地区的小卫星影像进行了居民地提取,并与共生矩阵纹理分析方法进行了实验对比。结果表明方法是有效的,并在提取精度上具有优势。     

广东阳江夏季降水的气候特征分析

为解阳江夏季降水的气候特征,进一步做好阳江气候降水预测,利用Motlet小波分析理论、Mann-Kendal检验和滑动t检验等方法对阳江单站57年（1953—2009年）6月到8月逐日降水资料进行分析,结果表明：阳江夏季降水经历了3个阶段,由降水逐渐增加时期变化到相对干旱时期,再到现阶段降水年际变化大;主要的降水周期为7—8年,1963年是降水的突变点;小雨量级降水为主要降水类型,在1980年以来阳江夏季大雨和暴雨降水日数逐渐增多,而大雨和暴雨量级降水是降水量的主要构成。     

基于自组织网络的黄河口浑浊模式研究

传统浑浊度时空变化模式研究依靠野外观测实验,需要投入大量人力物力,模型适用范围亦非常有限。本文利用自组织网络（SOM）,直接从长时序遥感影像中提取典型浑浊模式,分析浑浊度年内、年际变化特征。以黄河河口附近海域为研究区,提取出近15年的6类典型浑浊模式。典型特征显示,研究区内主要有2个浑浊区,位于渤海湾西部和南部,以及河口外和莱州湾西北部;6类模式中四类以年为周期过渡更替,冬春季浑浊度较高,夏秋季浑浊度较低;多年浑浊模式逐渐由中浑浊向清澈模式变化,整体浑浊度有降低趋势。浑浊水体分布主要受河口潮流、环流等海洋动力和风浪影响,结合研究区气象观测数据分析,海面风浪变化是造成浑浊模式更替的主要原因,黄河入海泥沙影响范围仅局限于河口口门周边。利用统计参数分析和2007年各月悬浮泥沙浓度反演结果比较,评价SOM分类效果,结果表明SOM提取的模式间具有显著差异,一定程度上能够代替经验模型反映区域浑浊特征。SOM神经网络能够从长时序遥感影像中直接提取浑浊水体典型分布模式,分析海岸带地区水体浑浊度变化的时空特征,对了解复杂水体泥沙输运及优化水资源利用具有重要应用价值。     

Adjusting precipitation measurements from the TRwS204 automatic weighing gauge in the Qilian Mountains,China

With the popularity of the automatic precipitation gauges in national weather stations, testing their performance and adjusting their measurements are top priorities. Additionally, because different climatic conditions may have different effects on the performance of the precipitation gauges, it is also necessary to test the gauges in different areas. This study mainly analyzed precipitation measurements from the single-Alter-shielded TRwS204 automatic weighing gauge (TRwS_SA) relative to the adjusted manual measurements (reference precipitation) from the Chinese standard precipitation gauge in a double-fence wind shield (CSPG_DF) in the Hulu watershed in the Qilian Mountains, China. The measurements were compared over the period from August 2014 to July 2017, and the transfer function derived from the work by Kochendorfer et al. (2017a) for correcting wind-induced losses was applied to the TRwS_SA measurements. The results show that the average loss of TRwS_SA measurements relative to the reference precipitation decreased from 0.55 mm (10.7%) to 0.51 mm (9.9%) for rainfall events, from 0.35 mm (8.5%) to 0.22 mm (5.3%) for sleet events, and from 0.49 mm (18.9%) to 0.33 mm (12.7%) for snowfall events after adjustment. The uncorrected large biases of TRwS_SA measurements are considered to be mainly caused by specific errors of TRwS_SA, different gauge orifice area and random errors. These types of errors must be considered when comparing precipitation measurements for different gauge types, especially in the mountains.     

甘东南及邻近地区地震目录的聚类分析

利用2013-01-01~2021-11-01期间甘肃甘东南及邻近地区（32°~36°N,102°~106°E）地震目录中的11 659次地震震中位置数据,使用硬聚类方法中的K-means和软聚类方法高斯混合模型GMM聚类方法对地震原始目录以及地震精定位目录的空间位置进行聚类分析。为确定最佳聚类数,使用AIC和BIC模型选择法,最终将原始目录和精定位目录分别聚类成6个和14个地震群。结果显示,精定位地震目录和GMM聚类方法结合可以更好地从地震大数据中找到具有不同空间分布特征的地震群。     

一种面向栅格的空间-属性双重约束聚类方法

针对栅格数据,传统聚类方法大都基于专题属性进行聚类,分裂了栅格对象的空间特性与专题属性,而兼顾空间与专题属性的现有空间聚类方法又存在算法复杂、参数设置多等问题,因此本文提出了一种面向栅格的空间-属性双重约束聚类算法（A Raster-oriented Clustering Method with Space-Attribute Constraints, RoCMSAC）。RoCMSAC利用栅格数据空间邻域和空间连通特性,重新定义栅格簇的相似性度量准则,通过属性均质簇生成,空间相邻栅格簇合并和空间邻近栅格簇合并3个步骤对栅格数据进行空间-属性双重约束聚类。利用太平洋海域海表温度栅格数据对算法的可行性以及有效性进行验证,并与现有算法进行对比分析。通过实例验证与对比发现：① RoCMSAC方法能够保证栅格簇空间域的邻近性和属性域的均质性;② RoCMSAC方法可发现复杂形状的栅格簇,且算法时间复杂度低,需输入参数较少。     

Ka波段雷达弱降水雨量估计方法与试验

毫米波雷达适合降水云的水凝粒子的观测,设备轻便且空间分辨率和角度分辨率较高,可用于机载或星载等对有效载荷要求苛刻且关注云雨探测的应用,因而毫米波雷达在气象科学研究中备受关注。在成都地区进行了Ka波段雷达弱降水累积雨量的观测,采用了HTI(高度时间显示)观测模式,分析了雷达测量降水的方法,联合雨量计对比了Z-R关系与衰减法计算累计降水量的效果,并通过测量误差拟合调整经验参数,减小了估测误差。     

A Modified Self-adaptive Method for Mapping Annual 30-m Land Use/Land Cover Using Google Earth Engine: A Case Study of Yangtze River Delta

Annual Land Use/Land Cover(LULC) change information at medium spatial resolution(i.e., at 30 m) is used in applications ranging from land management to achieving sustainable development goals related to food security. However, obtaining annual LULC information over large areas and long periods is challenging due to limitations on computational capabilities, training data, and workflow design. Using the Google Earth Engine(GEE), which provides a catalog of multi-source data and a cloud-based environment, we developed a novel methodology to generate a high accuracy 30-m LULC cover map collection of the Yangtze River Delta by integrating free and public LULC products with Landsat imagery. Our major contribution is a hybrid approach that includes three major components: 1) a high-quality training dataset derived from multi-source LULC products, filtered by k-means clustering analysis; 2) a yearly 39-band stack feature space, utilizing all available Landsat data and DEM data; and 3) a self-adaptive Random Forest(RF) method, introduced for LULC classification. Experimental results show that our proposed workflow achieves an average classification accuracy of 86.33% in the entire Delta. The results demonstrate the great potential of integrating multi-source LULC products for producing LULC maps of increased reliability. In addition, as the proposed workflow is based on open source data and the GEE cloud platform, it can be used anywhere by anyone in the world.     

多层次格网模型的近邻指数聚类生态区划算法与实验——以新疆北部地区区划为例

在综合考虑气候、植被、地貌等凶素的基础上,提出一种基于多层次格网模型的最近邻指数-模糊聚类生态区域划分算法(Nearest Neighbor Index Fuzzy clustering,NNI-FIC).该算法采用"自下而上"的方式,首先,利用离散格网单元之间的严格相似性形成区划的核心分区;然后,通过最近邻指数统计分...     

湖南“6.19＂暴雨过程的中尺度特征分析

针对2010年6月19～20日湖南一次大范围暴雨过程,利用常规观测资料、FY-2E卫星TBB资料、NCEP1°×1°格点资料及WRF模式输出的高分辨率资料,采用数值模拟和诊断分析相结合的方法,综合分析了此次暴雨过程.结果表明：东移短波槽及低层低涡是此次暴雨的主要影响系统;卫星资料分析显示,α中尺度对流云团前部不断有β中尺度扰动分裂和发展;WRF模式模拟结果表明,此次大范围暴雨过程是多尺度系统影响的结果,在有利的大尺度环流背景下,激发了中小尺度对流系统的活动,导致强降水带中出现了多个中尺度扰动和与此对应的中尺度雨团有组织的活动,是暴雨发生的主要原因;中尺度雨团对应着强上升气流柱、正涡度柱和低层强辐合、高层强辐散的散度结构.     

改进的最小生成树自适应空间点聚类算法

针对传统的最小生成树聚类算法存在使用全局不变阈值确定噪声边,聚类需要用户根据经验确定初始化聚类参数,如“边权值倍数容差”,“边长变化因子”等,聚类不能发现局部噪声的问题,本文提出了一种改进的最小生成树自适应空间点聚类算法。该算法在无需用户输入参数的前提下,克服主观因素的影响,根据最小生成树边长的数理统计特征定义裁剪因子。算法首先从宏观层面对最小生成树进行首轮删枝操作,消除全局环境下的噪声边,进而根据各子树的边长统计情况,自适应设定局部裁剪因子,进行第二轮删枝操作,消除局部环境下的噪声边。最后,采用1个模拟数据和1个实际应用验证算法的有效性,结果表明本文提出的改进算法在无需人为提供经验参数的环境下能够发现任意形状、不同密度的簇,能够准确的识别出空间点中的噪声数据,从而能够实现空间点数据背后隐藏信息的自动挖掘。     

Development of a region-partitioning method for debris flow susceptibility mapping

Debris flow susceptibility mapping(DFSM) has been reported in many studies, however, the irrational use of the same conditioning factor system for DFSM in regional-scale has not been thoroughly resolved. In this paper, a region-partitioning method that is based on the topographic characteristics of watershed units was developed with the objective of establishing multiple conditioning factor systems for regional-scale DFSM. First, watershed units were selected as the mapping units and created throughout the entire research area. Four topographical factors, namely, elevation, slope, aspect and relative height difference, were selected as the basis for clustering watershed units. The k-means clustering analysis was used to cluster the watershed units according to their topographic characteristics to partition the study area into several parts. Then, the information gain ratio method was used to filter out superfluous factors to establish conditioning factor systems in each region for the subsequent debris flow susceptibility modeling. Last, a debris flow susceptibility map of the whole study area was acquired by merging the maps from all parts. DFSM of Yongji County in Jilin Province, China was selected as a case study, and the analytical hierarchy process method was used to conduct a comparative analysis to evaluate the performance of the region-partitioning method. The area under curve(AUC) values showed that the partitioning of the study area into two parts improved the prediction rate from 0.812 to 0.916. The results demonstrate that the region-partitioning method on the basis of topographic characteristics of watershed units can realize more reasonable regional-scale DFSM. Hence, the developed region-partitioning method can be used as a guide for regional-scale DFSM to mitigate the imminent debris flow risk.