|
|||||
|
|
| 祁连山区黑河流域季节冻土时空变化研究 | |
| 引用本文： | 彭小清,张廷军,潘小多,王庆峰,钟歆钥,王康,牟翠翠.祁连山区黑河流域季节冻土时空变化研究[J].地球科学进展,2013,28(4):497-508. |
| 作者姓名： | 彭小清 张廷军 潘小多 王庆峰 钟歆钥 王康 牟翠翠 |
| 作者单位： | 1. 中国科学院寒区旱区环境与工程研究所,冻土工程国家重点实验室,甘肃兰州730000 2. 兰州大学资源环境学院,甘肃 兰州730000;美国科罗拉多大学国家冰雪数据中心,科罗拉多 博尔德80309 3. 兰州大学资源环境学院,甘肃 兰州,730000 |
| 基金项目： | 国家自然科学基金重大研究计划"黑河流域冻土特征及其对生态—水文过程的影响"，冻土工程国家重点实验室自主项目"中国西部山地冻土研究——以黑河地区为例" |
| 摘 要： | 季节冻土的时空变化对地—气水热交换、地表能量平衡、地表水文过程、生态系统及碳循环等有着非常重要的影响.利用黑河流域11个气象站40多年的气温数据和5 cm深度处的土壤温度数据,建立了月平均气温与土壤冻结天数之间的关系.同时应用月平均气温与冻结天数的相关关系和5 km网格化月平均气温及30 m分辨率的DEM数据,编制了黑河流域逐月季节冻土分布图,并按其空间分布特征,将逐月地表冻融状态划分为:完全冻结、不完全冻结和不冻结3种.系统研究了黑河流域2000-2009年逐月季节冻土分布及冻结概率的时空变化特征.在季节分配上,黑河流域完全冻结面积最大值出现在1月；不完全冻结面积最大值在11月；而不冻结面积最大值在6月和7月.在年际变化上,完全冻结状态的离差值在冷季变化大,暖季变化小；不完全冻结状态在一年的回暖期和降温初期,年际变化较大；不冻结状态分别在4月和10月变化较大.冻结概率在1月达到最大值,6月和7月降低到最小值.在空间分布上,黑河流域季节冻土的逐月分布与变化和冻结概率主要受海拔高度控制,纬度的影响次之. |
| 关 键 词： | 黑河流域 季节冻土 冻融变化 冻融天数 冻结概率 |
Spatial and Temporal Variations of Seasonally Frozen Ground over the Heihe River Basin of Qilian Mountain in Western China |
|
| Peng Xiaoqing,Zhang Tingjun,Pan Xiaoduo,Wang Qingfeng,Zhong Xinyue,Wang Kang,Mu Cuicui.Spatial and Temporal Variations of Seasonally Frozen Ground over the Heihe River Basin of Qilian Mountain in Western China[J].Advance in Earth Sciences,2013,28(4):497-508. | |
| Authors: | Peng Xiaoqing Zhang Tingjun Pan Xiaoduo Wang Qingfeng Zhong Xinyue Wang Kang Mu Cuicui |
| Institution: | 1.State Key Laboratory of Frozen Soil Engineering, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou730000, China;; 2.College of Earth and Environmental Sciences, Lanzhou University, Lanzhou730000, China;; 3. National Snow and Ice Data Center, Cooperative Institute for Research in Environmental Sciences University of Colorado, Boulder, 80309, USA |
| Abstract: | Spatial and temporal variations of seasonally frozen ground extent have important impacts on carbon exchange between the atmosphere and the land surface, surface energy balance, hydrologic cycle, and ecosystems as a whole. By using air temperature and soil temperature at 5 cm depth from 11 meteorological stations for more than 40 years, we established a relationship between mean monthly air temperature and numbers of frozen days within the month. Based on this relationship, grid air temperature data with a resolution of 5 kilometers, and 30m-DEM data, we mapped the monthly seasonally frozen ground distribution over the Heihe River Basin, and three different types of freezing/thawing status can be divided by using the spatial characteristics : complete frozen, incomplete frozen, and not frozen. The results indicate that the maximum area of three different types of soil freeze thaw status occur in January, November, and June or July respectively. Over the study period from 2000 through 2009, interannual variations of the complete frozen area extent is large in cold season, vice versa in warm season; there is a huge change in the warmer and catathermal period for incomplete frozen area extent; not frozen area extent has a huge variation in April and October. The maximum of freezing probability occurs in January, while the minimum of probability occurs between June and July. To the spatial perspective, distribution and variation of monthly seasonally frozen ground and freezing probability are mainly controlled by elevation, following by latitude over the Heihe River Basin. |
| Keywords: | Heihe River Basin Seasonally frozen ground Variation of freezing/thawing Numbers of freezing/thawing days Freezing probability |
| 本文献已被 万方数据 等数据库收录！ | |
| 点击此处可从《地球科学进展》浏览原始摘要信息 | |
| 点击此处可从《地球科学进展》下载免费的PDF全文 | |