测绘通报 ›› 2026, Vol. 0 ›› Issue (3): 51-56.doi: 10.13474/j.cnki.11-2246.2026.0309

• 学术研究 • 上一篇    下一篇

青海湖沙柳河河口区刚毛藻时空分布与湖水面积及气象要素响应研究

殷万玲1,2,3, 张志军1,2,3, 张寅4, 袁帅4, 胡庆武4, 徐雯婷1,2,3, 李治君5   

  1. 1. 青海省生态环境监测中心, 青海 西宁 810007;
    2. 国家环境保护青藏高原生态环境监测与评估重点实验室, 青海 西宁 810007;
    3. 青海省生态环境监测与评估重点实验室, 青海 西宁 810007;
    4. 武汉大学遥感信息工程学院, 湖北 武汉 430079;
    5. 自然资源部信息中心, 北京 100036
  • 收稿日期:2025-08-27 出版日期:2026-03-25 发布日期:2026-04-08
  • 通讯作者: 李治君。E-mail:zjli@infomail.mnr.gov.cn
  • 作者简介:殷万玲(1989—),女,硕士,工程师,主要从事工作为生态环境遥感监测与评价。E-mail:yinwanling1989@126.com
  • 基金资助:
    2024年度青海省“昆仑英才·高端创新创业人才”项目

Study on the spatio-temporal distribution of Cladophora in the Shaliu River estuary of Qinghai Lake and its response to the lake area and meteorological elements

YIN Wanling1,2,3, ZHANG Zhijun1,2,3, ZHANG Yin4, YUAN Shuai4, HU Qingwu4, XU Wenting1,2,3, LI Zhijun5   

  1. 1. Qinghai Province Ecological and Environmental Monitoring Center, Xining 810007, China;
    2. State Environmental Protection Key Laboratory of Tibetan Plateau Eco-Environmental Monitoring and Assessment, Xining 810007, China;
    3. Qinghai Provincial Key Laboratory of Eco-Environmental Monitoring and Assessment, Xining 810007, China;
    4. School of Remote Sensing Information Engineering, Wuhan University, Wuhan 430079, China;
    5. Information Center of Ministry of Natural Resources, Beijing 100036, China
  • Received:2025-08-27 Online:2026-03-25 Published:2026-04-08

摘要: 青海湖作为我国最大内陆咸水湖,其刚毛藻分布随气候变化呈现动态变化。本文聚焦青海湖沙柳河河口区,基于GEE平台获取2022—2024年非冰期月度无云Sentinel-2影像及TerraClimate、ERA5-Land气象数据,对RGB-NDWI融合图像采用WEU-Net模型和CSI方法识别刚毛藻,分析其时空分布特征及与湖水面积、气象要素的响应关系。结果显示,刚毛藻面积与湖水面积呈显著正相关(Pearson系数为0.76),4—9月两者均增大,9月达峰后减小;刚毛藻主要分布于湖区边缘和湖湾,外边界与湖水边界一致。气象要素中,刚毛藻面积与降水、气温、湖泊混合层温度呈显著正相关,与风速呈显著负相关,相关强度从大到小依次为湖泊混合层温度、风速、气温、降水。研究揭示了水文气象要素对刚毛藻分布的协同驱动机制。

关键词: 青海湖, 刚毛藻, 湖水面积, 气象要素, Sentinel-2

Abstract: As China's largest inland saltwater lake,the distribution of Cladophora in Qinghai Lake has shown dynamic changes in response to climate change.This study selected the estuarine area of Shaliu River in Qinghai Lake to carry out detailed research.Based on the Google Earth Engine (GEE) platform,monthly cloud-free Sentinel-2 images during the non-icing period from 2022 to 2024,as well as TerraClimate and ERA5-Land meteorological data,were acquired.For the RGB-NDWI fused images,the WEU-Net model and the CSI method were used to identify Cladophora.Additionally,the spatiotemporal distribution characteristics of Cladophora and its response relationships with lake water area and meteorological factors were analyzed.The results show that there is a significant positive correlation between the area of Cladophora and the lake area,with a Pearson correlation coefficient of 0.76.Both the area of Cladophora and the lake area increase from April to September,and then decrease after reaching the peak in September.Cladophora is mainly distributed at the edge of the lake area and in the bays,and its outer boundary is consistent with the lake boundary.There are significant positive correlations between the area of Cladophora and precipitation,air temperature,and lake mixed layer temperature,and a significant negative correlation with wind speed.The order of the correlation intensity is lake mixed layer temperature,wind speed,air temperature,precipitation.This study reveals the synergistic driving mechanism of hydrometeorological factors on the distribution of Cladophora.

Key words: Qinghai Lake, Cladophora, lake water area, meteorological elements, Sentinel-2

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