非平稳条件下北京市最大月降水量频率特征分析   总被引：1，自引：1，他引：0  

韩丽  黄俊雄  周娜  李超 《水文》2021,41(2):32-37,108

为探究气候变化下极端降水的频率变化特征,基于北京市22个雨量站实测月降水量数据,以时间为协变量构建平稳和非平稳GEV模型,对北京市最大月降水量序列(极值降水序列)进行模拟和频率分析,并采用Bootstrap方法对频率分析结果的不确定性进行评价.结果表明:所有极值降水序列的最优概率分布模型均为非平稳GEV模型,该模型能够...  相似文献   

收缩城市建设用地利用效率时空分异及影响机制——以黑龙江省伊春市为例   总被引：1，自引：1，他引：0  

徐惠孝  刘艳军 《地理科学进展》2021,40(6):937-947

建设用地是城镇经济社会活动的空间载体,其利用效率是调控建设用地扩张和配置的重要基础.论文以收缩型城市——黑龙江省伊春市为例,利用DEA模型测算了1995-2015年伊春市建设用地利用效率分析其时空演变规律,并运用地理探测器模型探究伊春市建设用地利用效率空间分异的影响机制,结论如下:①1995-2015年伊春市建设用地利...  相似文献   

基于熵权综合评价模型的福建省雷灾风险划分     

陈琳  陈彩珠  胡雅君  杨秀敏  朱亚飞 《气象研究与应用》2021,42(2):46-52

利用福建省2012-2017年闪电定位资料和雷灾资料,采用熵权综合评价模型,对福建省68个县市区域雷灾进行评价.结果表明,福建省闪电密度高值区域主要集中在闽中东部,各区域年平均密度值大部分在4次·km-2·a-1次以下,少部分地区高达8次·km-2·a-1次以上;闪电发生时间集中在6-8月;闪电强度区域分布均衡,强度值...  相似文献   

2012年8月6日谷城倒塔事故与暴雨洪涝影响调查分析     

史天如  周月华  叶丽梅  李兰 《湖北气象》2021,40(2):182-189

利用现场调查方法,对2012年8月6日谷城500 KV十樊一回#170倒塔事故的现场损害状况、洪水淹没范围等进行调查梳理;使用资料调查方法,对灾害发生时段的水文、气象以及发生区域内的水库、河道工况、自然地理等进行调查整理.最后,运用数理统计方法对水位、流量及降水等要素极值进行推算,并利用二维水动力模型模拟洪水路径及淹没...  相似文献   

收缩情境下城市用地结构时空格局演变及动力机制——以中国东北地区为例   总被引：3，自引：1，他引：2  

宋洋  朱道林  YEUNG Godfrey  徐阳  张立新 《地理研究》2021,40(5):1387-1403

构建城市用地结构时空格局演变分析框架,引入信息熵和偏移份额模型定量剖析2000-2017年中国东北地区城市用地结构时空格局演变特征,通过计量经济模型分阶段对比分析收缩情境下东北地区城市用地结构演变的动力机制.结果表明:东北地区城市用地总面积持续增长,用地结构信息熵整体呈现先上升、后下降的趋势.2011年以后,城市用地结...  相似文献   

基于气象站资料的中国地区太阳日辐射量算法研究   总被引：2，自引：0，他引：2  

孙睿  梁璐  杨玲 《气象与环境科学》2007,30(1):24-27

现行计算水平面太阳日辐射主要有两种方式:一种是利用影响辐射的相关要素建立模型,另一种是依据实测资料进行空间插值.但后一种方法若要保证精度则需有足够多的样本.针对上述问题,利用我国不同区域67个站点的数据,在VP-RAD模型的基础上,建立了一个适用于中国地区的逐日太阳辐射算法CNR,该算法仅需要输入站点基本信息、最高最低温度和降水量.模拟结果与实际观测结果比较吻合.  相似文献   

不同草地类型净初级生产力(NPP)模拟及其敏感性分析     

张美玲  陈全功  蒋文兰 《干旱区地理》2021,44(2):369-378

气候变化问题作为人类社会可持续发展面临的重大挑战,受到国际社会越来越强烈的关注.全球气候变化深刻影响着草地生态系统,定量评估区域和不同类型草地生态系统的生产力,研究其对气候变化的敏感性可以为草地生态系统适应未来气候变化提供基础数据和理论依据.草原综合顺序分类系统(CSCS)将天然草原分为42类(其中中国包含41类),并...  相似文献   

基于小波神经网络耦合模型对云南星云湖富营养化气象驱动因子的分析     

潘佳敏  冯禹昊  谢平  方精云 《湖泊科学》2021,33(2):428-438

气象因子是影响湖泊富营养化的重要因素,而湖泊富营养化对人群健康、生态系统和社会经济等均有负面影响.本文基于统计资料及遥感数据,结合Morlet小波分析和BP多层前馈神经网络(BP神经网络)构建了不同时间尺度下的小波神经网络耦合模型,分析了19862011年云南星云湖水华强度变化与月降雨量、月平均气温、月平均风速、月日照...  相似文献   

Evaluation of Inference Adequacy in Cumulative Logistic Regression Models: An Empirical Validation of ISWRidge Relationships     

Cheng-Wu CHEN  Hsien-Chueh Peter YANG  Chen-Yuan CHEN  Alex Kung-Hsiung CHANG  Tsung-Hao CHEN   《中国海洋工程》2008,22(1):43-56

Internal solitary wave propagation over a submarine ridge results in energy dissipation, in which the hydrodynamic interaction between a wave and ridge affects marine environment. This study analyzes the effects of ridge height and potential energy during wave-ridge interaction with a binary and cumulative logistic regression model. In testing the Global Null Hypothesis, all values are p 〈0.001, with three statistical methods, such as Likelihood Ratio, Score, and Wald. While comparing with two kinds of models, tests values obtained by cumulative logistic regression models are better than those by binary logistic regression models. Although this study employed cumulative logistic regression model, three probability functions p^1, p^2 and p^3, are utilized for investigating the weighted influence of factors on wave reflection. Deviance and Pearson tests are applied to cheek the goodness-of-fit of the proposed model. The analytical results demonstrated that both ridge height （X1 ） and potential energy （X2 ） significantly impact （p 〈 0. 0001 ） the amplitude-based refleeted rate; the P-values for the deviance and Pearson are all 〉 0.05 （0.2839, 0.3438, respectively）. That is, the goodness-of-fit between ridge height （ X1 ） and potential energy （X2） can further predict parameters under the scenario of the best parsimonious model. Investigation of 6 predictive powers （ R2, Max-rescaled R^2, Sorners＇ D, Gamma, Tau-a, and c, respectively） indicate that these predictive estimates of the proposed model have better predictive ability than ridge height alone, and are very similar to the interaction of ridge height and potential energy. It can be concluded that the goodness-of-fit and prediction ability of the cumulative logistic regression model are better than that of the binary logistic regression model.  相似文献   

Evaluation of Inference Adequacy in Cumulative Logistic Regression Models： An Empirical Validation of ISW-Ridge Relationships   总被引：3，自引：0，他引：3  

Hsien-Chueh Peter YANG  Alex Kung-Hsiung CHANG  Tsung-Hao CHEN 《中国海洋工程》2008,22(1)

Internal solitary wave propagation over a submarine ridge results in energy dissipation, in which the hydrodynamic interaction between a wave and ridge affects marine environment. This study analyzes the effects of ridge height and potential energy during wave-ridge interaction with a binary and cumulative logistic regression model. In testing the Global Null Hypothesis, all values are p<0.001, with three statistical methods, such as Likelihood Ratio, Score, and Wald. While comparing with two kinds of models, tests values obtained by cumulative logistic regression models are better than those by binary logistic regression models. Although this study employed cumulative logistic regression model, three probability functions p^1, p^2 and p^3, are utilized for investigating the weighted influence of factors on wave reflection. Deviance and Pearson tests are applied to check the goodness-of-fit of the proposed model. The analytical results demonstrated that both ridge height (X1) and potential energy (X2) significantly impact (p<0.0001) the amplitude-based reflected rate; the P-values for the deviance and Pearson are all >0.05 (0.2839, 0.3438, respectively). That is, the goodness-of-fit between ridge height (X1) and potential energy (X2) can further predict parameters under the scenario of the best parsimonious model.Investigation of 6 predictive powers (R2, Max-rescaled R2, Somers'D, Gamma, Tau-a, and c, respectively) indicate that these predictive estimates of the proposed model have better predictive ability than ridge height alone, and are very similar to the interaction of ridge height and potential energy. It can be concluded that the goodness-of-fit and prediction ability of the cumulative logistic regression model are better than that of the binary logistic regression model.  相似文献