Remote Sensing Retrieval of Water Transparency for Pingzhai Reservoir Based on Sentinel-2 Images

Wen Chaocheng; Zhou Zhongfa; Li Yongliu; KongJie; XieJiangting

doi:10.13961/j.cnki.stbctb.2023.01.019

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Remote Sensing Retrieval of Water Transparency for Pingzhai Reservoir Based on Sentinel-2 Images

- Remote Sensing Retrieval of Water Transparency for Pingzhai Reservoir Based on Sentinel-2 Images
- Bulletin of Soiland Water Conservation Vol. 43, Issue 1, Pages: 158-166(2023)
- 作者机构：
  
  1. 贵州师范大学地理与环境科学学院/喀斯特研究院,贵州,贵阳,550001
  2. 国家喀斯特石漠化工程技术研究中心,贵州,贵阳,550001
  3. 贵州省喀斯特山地生态环境国家重点实验室培育基地,贵州,贵阳,550001
- 作者简介：
- 基金信息：
- DOI：10.13961/j.cnki.stbctb.2023.01.019
  CLC： P461
- Published：2023
- 稿件说明：
移动端阅览
Wen Chaocheng, Zhou Zhongfa, Li Yongliu, et al. Remote Sensing Retrieval of Water Transparency for Pingzhai Reservoir Based on Sentinel-2 Images[J]. Bulletin of Soiland Water Conservation, 2023, 43(1): 158-166.
DOI：

Wen Chaocheng, Zhou Zhongfa, Li Yongliu, et al. Remote Sensing Retrieval of Water Transparency for Pingzhai Reservoir Based on Sentinel-2 Images[J]. Bulletin of Soiland Water Conservation, 2023, 43(1): 158-166. DOI： 10.13961/j.cnki.stbctb.2023.01.019.

摘要

[目的

]

研究水体透明度的变化规律及其空间分异驱动因素，为管理湖库及恢复湖库生态系统提供科学依据。[方法

]

基于2020年5月18日，8月26日，11月14日的Sentinel-2 MSI卫星影像及准同步实测透明度数据构建平寨水库透明度遥感反演模型，利用地理探测器定量分析影响透明度空间分异的驱动因素。[结果

]

①平寨水库水体透明度与Sentinel-2 MSI的B

波段最为敏感，利用波段组合B

×B

作为最佳敏感因子构建出的透明度反演模型具有较高的精度(R

=0.81，RMSE=0.11 m，MRE=16.91%)。 ②平寨水库水体透明度呈现出中心库区高而各支流上游低，近水体两岸低的空间分布趋势，且水体透明度11月＞8月＞5月。[结论

]

总悬浮物、叶绿素a及总有机碳含量是平寨水库水体透明度空间分异的主要因素。总磷、总氮、水温及风速通过影响水体中的总悬浮物、叶绿素a及总有机碳含量进而影响水体透明度空间分布。

Abstract

[Objective] The variation rule of water transparency and the driving factors of its spatial differentiation were analyzed in order to provide a scientific basis for the management of lake reservoirs and the restoration of lake reservoir ecosystems. [Methods] A remote sensing inversion model of water transparency in Pingzhai reservoir was constructed based on sentinel-2 MSI satellite images and quasi-synchronous measured transparency data collected on May 18

August 26

and November 14

2020. We quantitatively analyzed the drivers affecting spatial differentiation of water transparency using the GeoDetector package in R. [Results] ① The water transparency of Pingzhai reservoir was most sensitive to the B3 band of Sentinel-2 MSI

and the transparency inversion model constructed by using the band combination B3×B4 as the most sensitive factor had high accuracy (R2=0.81，RMSE=0.11 m，MRE=16.91%). ② The water transparency of Pingzhai reservoir showed a spatial distribution trend of high in the central reservoir area

low in the upstream region of each tributary

and low on both sides of the near water body. Water transparency was greatest in November followed by August and then May. [Conclusion] The contents of total suspended solids

chlorophyll a

and total organic carbon were the main factors affecting the spatial differentiation of water transparency in Pingzhai reservoir. Total phosphorus

total nitrogen

water temperature

and wind speed affected the spatial distribution of water transparency by affecting the content of total suspended solids

chlorophyll a

and total organic carbon in the water.

关键词

Keywords

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