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降水是地表淡水资源的主要来源,降水分布强烈的时空异质性给陆地水循环研究带来了较大不确定性,因此降水的空间异质性及其影响因子研究一直是水循环研究的重点。选取观测资料丰富的华东地区,采用351个气象台站降水观测数据,通过一般线性回归模型、地理加权回归模型和多尺度地理加权回归模型的拟合结果,研究了典型地形因子对降水空间分布的影响及其影响尺度。结果表明,传统的一般线性回归模型不能表征降水分布的空间异质性,而地理加权回归模型和多尺度地理加权回归模型均较好地拟合出了降水在空间上的非均匀分布（R2>0.7）。此外,多尺度地理加权回归模型的带宽数还反映了各地形因子对降水空间分布的影响尺度。一般说来,带宽数较小的局地影响因子对降水的空间异质性影响较强。对于年降水量,地形高程和地形起伏度是影响降水空间异质性的主要地形因子,而地形坡度和主风向系数对降水的影响不显著。在不同季节,各地形因子对降水空间分布的影响程度不同。地形高程对夏季降水影响较大;离海岸线距离对春、秋季南部山区降水影响较大;地形起伏度对冬季降水有重要影响。厘清我国不同季节降水与地形因子间的关系,有助于理解各季节复杂地形因子对降水的贡献,为... 相似文献
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选择了5种机器学习模型,即k最近邻方法（KNN）、多元自回归样条方法（MARS）、支持向量机（SVM）、多项对数线性模型（MLM）和人工神经网络（ANN）,利用海拔、相对湿度、坡向、植被、风速、气温和坡度等因子订正ITPCAS和CMORPH两种常用的青藏高原日降水数据集。五折交叉验证表明,KNN的订正精度最高。在三个验证站点（唐古拉、西大滩和五道梁）的误差分析,以及对青藏高原年降水量的空间分析均表明,KNN对CMORPH的订正效果显著,对ITPCAS在局部区域有一定订正效果,ITPCAS及其订正值的降水空间分布准确度高于CMORPH的订正值。主成分分析法表明降水订正是气象和环境因子综合作用的结果。 相似文献
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识别地质灾害聚集的热点区及驱动力对于区域灾害预警具有重要意义。以甘肃定西地区为研究区,选取坡度、坡向、土地利用等7个评价因子,利用确定系数与逻辑回归耦合模型、空间自相关方法分析地质灾害的空间集聚特征及驱动因素。结果表明:定西地区地质灾害危险性呈现中部高,南北两侧低的特征,其主要受降水、坡向、工程岩组等因子的影响;地质灾害与降水、坡向和工程岩组的空间关系为高高聚集;地质灾害危险性存在较强的空间自相关性,在3 km的空间尺度上呈显著正相关,且随距离阈值增加而降低;距离阈值为5 km时,正相关高高聚集与低低聚集以团块的形式存在,而高低聚集与低高聚集多以零星状分布。研究可为区域地质灾害监测与防控提供参考。 相似文献
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助地理信息系统空间分析技术和CF法,对该县滑坡各致灾因子进行敏感性分析,获得各因子的敏感性区段。分析表明,岩性、坡度、坡向、起伏度、与河流距离和与主要道路距离是影响该县滑坡发育的主要因子。根据各致灾因子的CF值建立的回归模型进行研究,结果表明所建模型可解释百分之八十的已发滑坡。 相似文献
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为了研究中国天山山区降水空间分布规律及其形成机理,基于研究区DEM及气象站点数据资料,运用偏最小二乘法和GIS技术建立了山区降水估算模型,并分析其降水成因。结果表明:天山山区年降水具有明显的经度和纬度地带性,西段多于东段,北坡(迎风坡)多于南坡(背风坡);研究区降水在海拔4 000 m以下呈线性增加特征,随后显著减少,在5 500 m左右出现第二极大值带;坡度小于50°时降水与坡度呈显著正相关。在地形抬升条件下,随气温下降和相对湿度上升使降水增加,这也是山区降水形成的必要条件。总体来看,偏最小二乘法可以有效解决降水及各因子间多重相关性问题,模型回归效果较显著,在模拟山区降水方面具有一定适用性。 相似文献
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根据SLM模型对辽西4个区域的降水径流非线性扰动响应进行模拟分析,结果表明:70年代至今,辽西4个典型干旱半干旱区域降水径流非线性显著,降水变化率在-3.3%~14.2%,径流变化率在-15.1%^-65.8%,径流的非线性变化逐年增强。线性模型下各典型区域NSE和R2的评估值均低于0.6,故采用非线性模型对辽西干旱半干旱区域降水径流进行模拟。 相似文献
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采用高分辨率的3"数字高程模型及青藏高原东部102个常规气象观测站5～9月份的降水量资料,根据降水随高度分布将站点分为三类,再采用多元逐步回归的方法,建立了青藏高原40年(1961-2000年)逐年雨季降水量与经度、纬度、海拔、坡度、坡向、开放度等6个地理、地形因子关系模型,并以此为基础,分析了三类区域在丰枯水年里的因子系数的变化规律.结果表明,此法建立的关于高原降水量与诸因子之间方程的相关性显著,相对误差20%,平均相对误差4.4%,估算模型的相关系数均通过0.05的显著性检验;海拔低于1 400 m的第一类区域,主要受地形高度和开放度等局地地形的影响,来改变旱涝年的降水分布特征,海拔高度大于3 600 m的第三类区域,主要受开放度和坡度的影响,其他区域主要受地形的海拔、经度和开放度等局地地形的影响;高原季风是影响第三类区域水汽分布的主要因素,在季风加强时,开放度和经度的影响也随着加强,而坡度和海拔的影响减弱,从而使得水汽的局地性分布特征增强,东西分布差异加大,相应地局地降水分布特征加强,东西差异加大.地理地形因子影响大气的水汽输送和大气的垂直运动,从而导致其对空间降水分配的差异. 相似文献
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反映流域整体降水情势的面雨量一直是水文模型的重要输入参数之一,在泰森多边形雨量法的基础上考虑地理空间要素对降雨空间分布的影响,采用面向对象的遥感信息聚类方法提取出雅砻江流域2项形状因子(周长、面积)和5项地形因子(平均高程、平均坡度、平均坡向、高程差周长比和高程差面积比)。降雨—径流相关性分析结果表明:地形因子雨量法在月尺度上的降雨估算精度高于年尺度,且在月尺度上能更好地反映流域不同区段的降雨空间分布特征;在月、年际降雨变化趋势分析方面,年尺度上的降雨与径流一阶差分后平均相关系数为0. 903,高于月尺度的0. 629,主要由于水电站调蓄过程对流域径流异质性的影响,且影响度随着时间尺度缩小而放大。 相似文献
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借助地理信息系统(GIS)空间分析技术和基于贡献率的敏感性分析方法,分析地形地貌因子与滑坡敏感性之间的关系,研究大关县坡度坡向对滑坡的影响程度的大小。将坡度和坡向因子细分区间,计算每一区间对滑坡的贡献率,定量地分析坡度、坡向区间变化与滑坡发育的关系。研究结果表明,坡度15°~25°区间的区域为滑坡最敏感的区域,坡向带270°~315°区间是滑坡灾害最敏感的区域,但坡向带每一区域的贡献率差别不大,说明坡向对滑坡发生的作用效果不显著。 相似文献
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西藏林芝市泥石流灾害频发,亟需建立泥石流灾害预警模型,预测林芝市泥石流灾害可能发生的区域,减少泥石流灾害导致的损失。文章提出了一种基于栅格径流汇流的林芝市泥石流灾害预警模型,从栅格像元尺度上模拟流域各位置上的水深,以提高泥石流预警的空间针对性。该模型将泥石流致灾因子分为背景因子和激发因子。通过林芝市裸岩率、河床纵比降等因子的逻辑回归,获取林芝市泥石流灾害概率,作为泥石流预警模型的背景因子;引入栅格径流汇流模型,以站点降水和雪水当量为模型的水量输入,模拟预警时段内的流域各位置上的模型水深,作为泥石流预警模型的激发因子。利用二元逻辑回归的方法计算背景因子和激发因子的权重,建立泥石流预警模型。利用2011—2020年18次历史灾害对模型进行验证,落入预警区内的灾害点占比64.4%,预警精度较高,对于林芝市泥石流灾害预警具有一定的指导意义。 相似文献
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Manifestation of remote sensing data and GIS on landslide hazard analysis using spatial-based statistical models 总被引：15，自引：10，他引：5
This paper presents landslide hazard analysis at Cameron area, Malaysia, using a geographic information system (GIS) and remote sensing data. Landslide locations were identified from interpretation of aerial photographs and field surveys. Topographical and geological data and satellite images were collected, processed, and constructed into a spatial database using GIS and image processing. The factors chosen that influence landslide occurrence are topographic slope, topographic aspect, topographic curvature, and distance to rivers, all from the topographic database; lithology and distance to faults were taken from the geologic database; land cover from TM satellite image; the vegetation index value was taken from Landsat images; and precipitation distribution from meteorological data. Landslide hazard area was analyzed and mapped using the landslide occurrence factors by frequency ratio and bivariate logistic regression models. The results of the analysis were verified using the landslide location data and compared with the probabilistic models. The validation results showed that the frequency ratio model (accuracy is 89.25%) is better in prediction of landslide than bivariate logistic regression (accuracy is 85.73%) model. 相似文献
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Bivariate and multivariate statistical analyses were used to predict the spatial distribution of landslides in the Cuyahoga River watershed, northeastern Ohio, U.S.A. The relationship between landslides and various instability factors contributing to their occurrence was evaluated using a Geographic Information System (GIS) based investigation. A landslide inventory map was prepared using landslide locations identified from aerial photographs, field checks, and existing literature. Instability factors such as slope angle, soil type, soil erodibility, soil liquidity index, landcover pattern, precipitation, and proximity to stream, responsible for the occurrence of landslides, were imported as raster data layers in ArcGIS, and ranked using a numerical scale corresponding to the physical conditions of the region. In order to investigate the role of each instability factor in controlling the spatial distribution of landslides, both bivariate and multivariate models were used to analyze the digital dataset. The logistic regression approach was used in the multivariate model analysis. Both models helped produce landslide susceptibility maps and the suitability of each model was evaluated by the area under the curve method, and by comparing the maps with the known landslide locations. The multivariate logistic regression model was found to be the better model in predicting landslide susceptibility of this area. The logistic regression model produced a landslide susceptibility map at a scale of 1:24,000 that classified susceptibility into four categories: low, moderate, high, and very high. The results also indicated that slope angle, proximity to stream, soil erodibility, and soil type were statistically significant in controlling the slope movement. 相似文献
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Statistical models are one of the most preferred methods among many landslide susceptibility assessment methods. As landslide
occurrences and influencing factors have spatial variations, global models like neural network or logistic regression (LR)
ignore spatial dependence or autocorrelation characteristics of data between the observations in susceptibility assessment.
However, to assess the probability of landslide within a specified period of time and within a given area, it is important
to understand the spatial correlation between landslide occurrences and influencing factors. By including these relations,
the predictive ability of the developed model increases. In this respect, spatial regression (SR) and geographically weighted
regression (GWR) techniques, which consider spatial variability in the parameters, are proposed in this study for landslide
hazard assessment to provide better realistic representations of landslide susceptibility. The proposed model was implemented
to a case study area from More and Romsdal region of Norway. Topographic (morphometric) parameters (slope angle, slope aspect,
curvature, plan, and profile curvatures), geological parameters (geological formations, tectonic uplift, and lineaments),
land cover parameter (vegetation coverage), and triggering factor (precipitation) were considered as landslide influencing
factors. These influencing factors together with past rock avalanche inventory in the study region were considered to obtain
landslide susceptibility maps by using SR and LR models. The comparisons of susceptibility maps obtained from SR and LR show
that SR models have higher predictive performance. In addition, the performances of SR and LR models at the local scale were
investigated by finding the differences between GWR and SR and GWR and LR maps. These maps which can be named as comparison
maps help to understand how the models estimate the coefficients at local scale. In this way, the regions where SR and LR
models over or under estimate the landslide hazard potential were identified. 相似文献
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Landslide hazard mapping at Selangor, Malaysia using frequency ratio and logistic regression models 总被引：28，自引：9，他引：28
The aim of this study is to evaluate the landslide hazards at Selangor area, Malaysia, using Geographic Information System
(GIS) and Remote Sensing. Landslide locations of the study area were identified from aerial photograph interpretation and
field survey. Topographical maps, geological data, and satellite images were collected, processed, and constructed into a
spatial database in a GIS platform. The factors chosen that influence landslide occurrence were: slope, aspect, curvature,
distance from drainage, lithology, distance from lineaments, land cover, vegetation index, and precipitation distribution.
Landslide hazardous areas were analyzed and mapped using the landslide-occurrence factors by frequency ratio and logistic
regression models. The results of the analysis were verified using the landslide location data and compared with probability
model. The comparison results showed that the frequency ratio model (accuracy is 93.04%) is better in prediction than logistic
regression (accuracy is 90.34%) model. 相似文献
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堆石非线性强度特性对高土石坝稳定性的影响 总被引：4，自引：1，他引：3
抗剪强度指标的选择对大坝坝坡稳定性评价有着十分重要的影响。堆石料抗剪强度具有明显的非线性,在高坝中这一特点更为显著。因此,计算堆石坝坝坡稳定安全系数时应采用非线性指标,而不是传统的线性指标。讨论了不同的堆石料抗剪强度模型、计算参数取值标准、非线性指标的稳定分析方法以及允许安全标准问题。统计分析了171组822个三轴试验结果发现,邓肯非线性指标对堆石料抗剪强度的模拟误差要小于线性指标和德迈洛非线性指标。采用不同的抗剪强度指标计算261.5 m高的云南糯扎渡大坝坝坡的稳定性。结果表明：各种工况下线性有咬合力、邓肯非线性指标与德迈洛非线性指标3种方法得到的安全系数和滑裂面位置都十分接近,非线性指标计算的结果并不比线性指标高。因此,进行非线性分析时,现有规范规定的基于线性指标的允许安全系数标准无需改变。 相似文献
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基于非线性Mohr-Coulomb破坏准则,结合极限分析上限法和拟静力分析法,建立功能方程,推导了地震效应下裂缝边坡的安全系数计算方程。采用数学规划方法,计算了不同参数组合条件下的边坡安全系数值,详细分析了非线性条件下一系列参数对边坡稳定性的影响。研究表明,边坡安全系数随非线性参数和地震效应的增大而减小。对比分析可知,在非线性破坏准则下,裂缝深度较大时,裂缝对边坡稳定性影响显著,且边坡越陡影响越大;当裂缝深度超过某个值后,临界破坏面起始端可能不穿过裂缝最底端,而是从裂缝中间某部位穿过。在地震效应作用下,非线性抗剪强度参数对安全系数影响显著。研究成果进一步完善了裂缝边坡稳定性分析内容,所列图表为边坡的设计与施工提供有益参考。 相似文献
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基于多元线性回归模型的冻土强度影响因素 显著性分析 总被引：1，自引：0，他引：1
为定量分析土质、含水率、温度和应变速率等因素对冻土强度的影响,本文根据公开发表的试验数据,应用多元线性回归模型对冻土强度影响因素进行了显著性分析。分析结果表明,在仅考虑线性影响条件下,温度和土性是影响冻土强度的主要因素,影响强度分别为0.632和0.193,含水率对冻土强度也有显著性影响,影响强度为-0.577。为探明各影响因素对冻土强度的非线性作用,在保留强度Taylor展开二次项的条件下,通过变量代换,将非线性项进行线性化,并利用多元线性回归模型进行了进一步分析。分析结果表明含水率与温度对冻土强度的影响包含线性、非线性和交叉影响项三项,应变率对冻土强度的影响仅包含非线性和交叉影响项。各因素对冻土强度的影响程度可用偏回归系数定量描述。 相似文献