新疆开孔河流域地下水依赖型植被生态系统的遥感识别
Mapping groundwater dependent vegetation ecosystems by remote sensing in Kaidu-Kongque River Basin,Xinjiang
张燕 1尹立河 2王旭升 1王浪 3王璐晨 4张俊 2李福杰 3张鹏伟3
作者信息
- 1. 中国地质大学(北京)水资源与环境学院,北京 100083
- 2. 中国地质调查局西安地质调查中心,陕西 西安 710054
- 3. 中国地质调查局乌鲁木齐自然资源综合调查中心,新疆 乌鲁木齐 830057
- 4. 中国地质大学(北京)水资源与环境学院,北京 100083;中国地质调查局西安地质调查中心,陕西 西安 710054
- 折叠
摘要
在干旱-半干旱地区,识别地下水依赖型植被生态系统(GDVEs)的位置和范围,对水资源和生态环境保护至关重要.针对传统识别方法的不足,以新疆开孔河流域为研究区,探索基于遥感技术的GDVEs识别方法.选取相对干旱年为研究期,基于植被指数、土壤湿度和潜在蒸散发,利用叠加分析和自然间断点分级法,确定开孔河流域GDVEs的空间分布,利用湿地分布、河流影响带及野外实地调查数据对识别结果进行验证.结果表明:开孔河流域GDVEs较高和高潜力区主要位于博斯腾湖周围和孔雀河下游荒漠平原区,主要为湿地生态系统和荒漠河岸林植被生态系统,约占天然植被区面积的10.3％;验证表明,本文提出的GDVEs识别方法可在西北干旱内陆河流域推广.
Abstract
In arid and semi-arid areas,mapping location and extent of groundwater dependent vegetation eco-systems(GDVEs)is critical for water resources and ecological environment protection.Targeting the shortcomings of traditional mapping methods,this study takes the Kaidu-Kongque River Basin in Xinjiang as the study area to explore the GDVEs mapping method based on remote sensing technology.For a rela-tively dry year,the study used overlay analysis and natural breaking classification method to determine the spatial distribution of GDVEs based on NDVI,soil moisture and potential evapotranspiration,and then used wetlands,river influence areas and field survey data to validate the results.The result shows that the high and very high potential areas of GDVEs are mainly located in the surrounding areas of the Bosten Lake and desert areas in the middle and lower reach of the Kongque River,which are mainly wetland and riparian fo-rest ecosystems,accounting for about 10.3％of the natural vegetation area;and the verification shows that the proposed method is applicable in other arid inland river basins in NW China.
关键词
生态水文学/地下水依赖型植被生态系统(GDVEs)/识别方法/遥感数据/塔里木河流域Key words
ecohydrology/groundwater dependent vegetation ecosystems(GDVEs)/mapping method/re-mote sensing data/Tarim River Basin引用本文复制引用
基金项目
新疆维吾尔自治区"天池英才"引进计划()
陕西省自然科学基础研究计划项目(2022JQ-271)
陕西省创新能力支撑计划项目(2019TD-040)
出版年
2024
国家科技期刊平台
NSTL
万方数据