摘要
通天河是长江源头重要的干流,探讨其植被生长状况及其与气候因子的响应对三江源区生态系统稳定性研究具有重要意义。本文以通天河流域为研究区,采用了广义回归神经网络(General regression neural network,GRNN)计算模型来反演叶面积指数(Leaf area index,LAI)和植被覆盖度(Fractional vegetation cover,FVC)数据,分析LAI和FVC的变化特征及其对气候因子的响应。分析结果表明:通天河流域植被总体呈显著波动增长趋势,LAI,FVC增长速率分别为(1.2×10^(-3))·a^(-1)和(0.9×10^(-3))·a^(-1);流域内植被明显改善区分布在海拔较低水热条件较好的沟谷地带,但下游人类活动频繁的曲麻莱县和治多县周边地区植被退化明显;流域内植被主要生长在海拔4000 m以上地区,超过5200 m植被生长差,覆盖类型以低覆盖为主,中-高覆盖集中在河流下游地区;相较于气温而言,降水是影响该流域植被的主导因素,与植被LAI和FVC呈显著正相关。
Tongtian River is an important main stream of the source area of the Yangtze River.It is of great significance to study the vegetation growth and its response to climate factors in the source area of the Sanjiangyuan area.This paper focused the Tongtian River Basin by using the General regression neural network(GRNN)calculation model to invert the Leaf area index(LAI)and Fractional vegetation cover(FVC)data on the variation characteristics of LAI and FVC and their responses to climate factors.The results show:the vegetation in the Tongtian River Basin showed a significant fluctuating growth trend overall,with the growth rates of LAI and FVC being(1.2×10)^(-3)·a^(-1)and(0.9×10)^(-3)·a^(-1)respectively.The vegetation improvement areas in the basin are distributed in the valleys with lower altitude and better hydrothermal conditions,but the vegetation around Qumalai County and Zhiduo County with frequent human activities in the lower reaches of the river was degraded significantly.Vegetation in the basin mainly grew in the area above 4000 m above sea level,and the vegetation growth was poor where the area locates at more than 5200 m above sea level.The low vegetation coverage type existed the most area of that basin,and the medium to high coverage was concentrated in the lower reaches of the river.Compared with air temperature,precipitation was the dominant factor affecting vegetation coverage in the basin,and was significantly positively correlated with vegetation LAI and FVC.
作者
张浔浔
段阳海
吴淑莹
谭昌海
赵阳刚
杨斌
文浪
肖志强
孙建
ZHANG Xun-xun;DUAN Yang-hai;WU Shu-ying;TAN Chang-hai;ZHAO Yang-gang;YANG Bin;WEN Lang;XIAO Zhi-qiang;SUN Jian(Research Center of Applied Geology of China Geological Survey,Chengdu,Sichuan Province 610036,China;Key Laboratory of Coupling Process and Effect of Natural Resources Elements,Ministry of Natural Resources,Bejing 100055,China;Sichuan Hua Di Building Engineering Co.,Ltd,Chengdu,Sichuan Province 610081,China;Chengdu center of hydrogeology and engineering geology of Sichuan provincial geology and mineral resources bureau,Chengdu,Sichuan Province 610081,China;State Key Laboratory of Remote Sensing Science,School of Geography,Beijing Normal University,Beijing 100875,China;State Key Laboratory of Tibetan Plateau earth system science,Institute of Tibetan Plateau Research,Chinese Academy of Sciences,Beijing 100101,China)
出处
《草地学报》
CAS
CSCD
北大核心
2023年第2期479-488,共10页
Acta Agrestia Sinica
基金
青藏高寒区资源与环境调查监测与评价(ZD20220138)
长江源沱沱河地区生态环境调查评价(ZD20220222)
气候变化背景下基于氢氧同位素和水化学方法的青藏高原沱沱河地区径流分割研究(2021490711)资助。
关键词
通天河流域
三江源
广义回归神经网络
叶面积指数
植被覆盖度
General regression neural network
Tongtian River Basin
Sanjiangyuan national Nature Reserve
Leaf area index
Fractional vegetation cover
