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1.
?????人????????????????GPS?????????????о??????仯????λ??????????????????????????t????????????渺???????????????????????????仯???????????????????????????????????λ????????????????3??????????????????λ?????????????????90%??75%??????????????????????LaD??GLDAS??????????????????????????仯?????????????????????????????????????????????  相似文献   

2.
μ����ص��α������о�   总被引:2,自引:1,他引:1  
?????л???????????α????GPS????????????2001??2008??μ??????????????仯??????????????????????λ???????о????????????????????????????????????????????????????2004??????μ??????3??仯???????????????????????????仯?????????????????  相似文献   

3.
????InSAR?????????????????????? ??GPS???????????????λ?????????????????????????????????????????????????μ?????Ms8.1?????????????????????????????λ????????????????С???????????????????????????????????????λ???????GPS???????????????????????????????????????????????????Ms8.1?????????λ????????仯??  相似文献   

4.
??10???????FG5-112?????????????й???????????????????о?????嶯??????????????????????68??????????ι????????????С??2??10 -8 ms -2???????????????????????С?????????????;????????????????????????????????????仯?????1??10 -8 ms -2 /a??????????λ???????-0.38 cm/a;??????????λ?仯??????????????????????????????  相似文献   

5.
�Ž�-���5.7������������Դ���ƽ�   总被引:1,自引:0,他引:1  
???????????е???λ?????????????????????? ??????????-???5.7???????112??ML??1.5????????????????????????????????????1?????-???5.7???????????????????????????NNW??NEE?????50??60??,??????-60??-100??2??????????????????????λ???EW?????????????????λ??NS???????????????????????????????  相似文献   

6.
???????????48??IGS?2009-2011??????????????????ZTD?????????????EGNOS???????ZTD???????????????????????1??????????????????IGS?????ZTD??EGNOS???????ZTD???????????????-0.18 cm??5.98 cm?????й?????????0.81 cm??6.13 cm??2????????????????????????仯????????????????^??С??????????????????????С??3????????????????γ?????仯???????????????????????????γ????????????????????????????????γ????????????????????仯????С??4:???????????γ?????????????????????????????????仯?????  相似文献   

7.
???????GPS????????????????????λ?????????????????о??????????????????С????α??????????????????????仯???????????繤?????????????????????????????????????????????????£??????????????????????????????????????仯??????????????λ????????????????????????????????е????????????С???????????????????С?????α?????й?????????????????????????????????????????й??????????С?????α????????????С????????????????????????????????????????????2006??2009??????????????????????????????????????????????????С???,?????????????????????????????????????????????????????仯???????????????????????????  相似文献   

8.
????????????λ?????λ?仯??????λ?????????????????????????????????????????????????????λ???????????????????????????????????裬???????????????????????????????????????????????????????????????о??λ?仯???????????????????????????÷????о????????????????????·????????????????λ??????????????????????????λ?????????????????????????????????????????в?????·??????6??????????5?????????4??  相似文献   

9.
????3?????1996??2006?????????????????????о????????????????????????????????? ?о??????????????仯?????????????????????????й????仯?????????????????????й???????????????????仯??????????????????????????仯??????????????????????仯??  相似文献   

10.
????COSMIC??????????????????????о???2006??11??15????????Ms8.0?????2007??2??25????????Ms5.3??????????????????????????????仯,?????K???(???)?????????????????仯??????????????? ?о????????GPS???????????????????????????????????????????????仯,?????仯???п????????????????  相似文献   

11.
In order to reach the designated final water level of 175 m, there were three impoundment stages in the Three Gorges Reservoir, with water levels of 135 m, 156 m and 175 m. Baishuihe landslide in the Reservoir was chosen to analyze its displacement characteristics and displacement variability at the different stages. Based on monitoring data, the landslide displacement was mainly influenced by rainfall and drawdown of the reservoir water level. However, the magnitude of the rise and drawdown of the water level after the reservoir water level reached 175 m did not accelerate landslide displacement. The prediction of landslide displacement for active landslides is very important for landslide risk management. The time series of cumulative displacement was divided into a trend term and a periodic term using the Hodrick-Prescott(HP) filter method. The polynomial model was used to predict the trend term. The extreme learning machine(ELM) and least squares support vector machine(LS-SVM) were chosen to predict theperiodic term. In the prediction model for the periodic term, input variables based on the effects of rainfall and reservoir water level in landslide displacement were selected using grey relational analysis. Based on the results, the prediction precision of ELM is better than that of LS-SVM for predicting landslide displacement. The method for predicting landslide displacement could be applied by relevant authorities in making landslide emergency plans in the future.  相似文献   

12.
通过对蓄水前后三峡库首区构造应力场进行三维数值模拟发现,相对于蓄水前,蓄水至135 m水位时,官渡口断裂-马鹿池断裂-牛口断裂围限区、秭归地理中心和九湾溪断裂带,出现了4个主应力下降区和共轭的主应力增长区,形成了差应力场;175 m水位与135 m水位相比,局部差应力场呈现逆向变化,即形成了加载效应与卸载效应的交替过程。这一过程,可能是水库诱发地震的诱震(或触震)因素。  相似文献   

13.
利用Jason-1数据监测呼伦湖水位变化   总被引:8,自引:2,他引:6  
卫星测高为内陆水域水位变化的实时和连续监测提供了一种高效的技术工具.但是这种应用受到数据点覆盖稀疏的限制。利用Jason-13年(2002-2004)GDRs测高数据作简单的数据编辑,并进行必要的地球物理改正.最后得到内蒙古地区呼伦湖水位变化的时间序列。呼伦湖地区由于近年来持续干旱,水位呈现明显的下降趋势.年平均下降约0.3~0.5m。在一般的内陆水域.水位变化主要取决于降雨量和蒸发量,所以,根据卫星测高所得的水位变化信息.可以为区域气候变化的研究提供一种全新的技术与方法。  相似文献   

14.
Extreme water levels are related to astronomical tides and storm surges.Eleven typhoon systems,which have caused extreme water level rises,were selected based on 60-yr water level data from the Xiamen tide gauge station.In these 11 typhoon systems,the astronomical tide component accounts for 71%-95%of the total water level.The Gumbel distribution of extreme water level rise was estimated,and the impact of typhoon surges on water levels during the return period was analyzed.The ex-treme tide levels caused by typhoons Herb(1996)and Dujuan(2015)are much higher than those of other typhoons and correspond to the return period of 76 yr and 71 yr,respectively.The differences of sea levels in the presence and absence of these two typhoons in the 10-100 yr return period are 5.8-11.1 cm.For the 100-yr return period,the total risks within 10,25,50,and 100 yr increase by 94.3%,85.4%,72.9%,and 54.4%,respectively,if the Herb and Dujuan are not considered.Assuming that typhoon Herb(1996)occurred during the highest astronomical tide,it will produce a water level higher than that of the 1000-yr return period.Sea level rise has an important influence on the water level return period,and the contribution of nonlinear sea level rise in the next 100 yr is estimated to be 10.34%.  相似文献   

15.
������ˮλ���봨������Ӧ�����Ӧ   总被引:3,自引:3,他引:0  
???λ????????????????????????????????峱????????????????????λ???????????????????λ??????????·?????????????????????????????????M2???????????????λ?????????????????????????????????????????λ?????????????Ms8.0????????????????????????????沨??????????沨???????????λ????????????????????λ??????????????????????????????????????????????????????沨?????????????????λ???????????1??????????  相似文献   

16.
Land creation projects have been implemented in China to expand urban space in mountainous areas. In addition to the predictable settlement brought about by filling construction,varying degrees of land subsidence and engineering failures have a demonstrated relationship to groundwater level fluctuation induced by land creation engineering. In this work, we adopted a typical large-scale land creation project, Yan'an New City in Shaanxi province, West China, as our study area. Prior to conducting the main experiment,preliminary field investigation and groundwater level monitoring were conducted to determine the groundwater fluctuation trend induced by land creation engineering. Although a blind drainage system was implemented, the depth aspect of groundwater level changes after large-scale land creation still needed to be addressed. To study the degree of impact and the settlement mechanism induced by the rising groundwater level, we conducted a Water Immersion Test(WIT) in a typical land creation site for 107 days. The rising groundwater level was simulated by injecting water from the bottom of the filling foundation. During the WIT, the soil water content, surface subsidence, and internal settlement of soil at different depths were obtained. Surface subsidence development could be categorized into four stages during the water level increase. The second stage, which is defined as the point when the groundwater level rises to 10 m,marked the critical point in the process. Furthermore,it was ascertained that the local settlement in regions that were originally composed of steep slopes is larger than that in originally flat areas. In addition, ground cracks and sinkholes in the study area were inspected;and it was determined that they would become new channels that would accelerate water infiltration and exacerbate the settlement. Based on the results from our field investigation and testing, several suggestions are proposed for land creation projects to mitigate issues associated with construction-induced groundwater level rising.  相似文献   

17.
三峡二期工程蓄水后的垂直形变场   总被引:16,自引:12,他引:4  
根据三峡地区的数字高程模型(DEM),模拟三峡二期工程蓄水位达到135m后的水体负载,利用Farrell提出的质量负荷产生的地球形变理论,推算三峡水库水位达到135m后整个库区的垂直形变,与三峡库区GPS形变监测网获得的蓄水前后的垂直形变图像进行对比分析,结果显示:在三斗坪-巴东库段,两者中都出现了3个相同的、明显的垂直形变集中区。在三峡大坝附近,模拟结果比观测结果大8~15mm,说明坝址附近的花岗岩具有较强的刚性;而在香溪,模拟结果比观测结果要小23mm,且GPS观测到长江两岸的垂直变化差异达到22mm,说明该段地质构造的特殊性和复杂性。综合分析表明,三峡大坝坝址所在地的地质构造和地壳是稳定的。  相似文献   

18.
Based on the simulation with the Ocean-Atmosphere Coupled Model CCSM and Ocean Model POP under the greenhouse gas emission scenario of the IPCC SRES A2 (IPCC, 2001), and on the earth crust subsidence and glacier melting data, the relative sea level change is obtained along the coast of China in the 21st century. Using the SRTM elevation data the submergence of coastal low land is calculated under the extreme water level with a 100-year return period. The total flooding areas are 98.3×103 and 104.9×103 km2 for 2050 and 2080, respectively. For the three regions most vulnerable to extreme sea level rise, i.e., the coast of Bohai Bay, the Yangtze River Delta together with neighboring Jiangsu Province and northern Zhejiang Province, and the Pearl River Delta, the flooded areas are 5.0×103, 64.1×103 and 15.3×103 km2 in 2050 and 5.2×103, 67.8×103 and 17.2×103 km2 in 2080, respectively.  相似文献   

19.
丹江口水库诱发地震研究   总被引:2,自引:0,他引:2  
丹江口水库由汉江、丹江两个库段组成。在丹库的峡谷灰岩地带 ,断裂、节理发育 ,利于水的渗透和循环。 196 7年 11月蓄水后 ,随水位的增加 ,地震活动增加 ,且震级由Ms<2 .5上升到Ms =4.7,并在丹库的峡谷附近形成北北西方向延伸的 3个地震密集区。地震频度、强度与水位 (库容 )变化有一定的相关性。预测二期工程蓄水后 ,仍将产生诱发地震 ,其最大强度为Ms≤ 5 .0。  相似文献   

20.
评价土地覆被数据质量是正确、合理使用数据的前提和保障,有助于遥感制图方法的改进。本文以1:10万土地利用数据为参考数据,选取2010年RapidEye_5 m、FROM_GLC(30 m)、MODIS_V005(500 m),以及2009年GlobCover 2009(300 m)土地覆被数据,以湖南省桃源县为例对4种不同分辨率的遥感土地覆被数据质量,引入窗口的分类类别统计方法,进行了综合评价,并分析了其误差和空间分布。结果表明:(1)RapidEye_5 m数据总体精度最高,MODIS_V005和FROM_GLC次之,GlobCover 2009数据相对最低。高分辨率土地覆被数据对于居民地、交通用地、水体等精细地物分类较好,具有一定优越性,各数据在一级类上的面积相关性和一致性总体高于二级类;(2)各数据在建筑用地和其他未利用地类型上的生产者精度均较低,FROM_GLC和MODIS_V005数据,在灌木草地上的空间一致性较差,4种数据在以耕地为主的平坦地区空间一致性较好,混淆主要发生在灌木草地、乔木林地和耕地之间;(3)随着土地覆被数据分辨率的提高,分出较多地物类型数的面积比例也随之增加,较高分辨率的RapidEye_5 m和FROM_GLC分出的类别数集中在7-16种较高水平上,低分辨率数据集中在1-5种较低水平上,在丘陵山区差异显著,而高分辨率数据对地物区分更好,集中于11-16种地物。  相似文献   

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