предыдущий|следующий

Spatial distribution and dynamics of lakes in China： Progress in remote sensing monitoring at national scale and new inventory of the maximum lake extent and change trajectory

  • role： First author第一作者
  • Affiliation：

    Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China

    School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China

  • Email：wensong_z@outlook.com
  • Introduction：张闻松，1998年生，男，硕士研究生，研究方向为水文遥感。E-mail： wensong_z@outlook.com
ZHANG Wensong12,  
  • role： Corresponding author通信作者
  • Affiliation：

    Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China

  • Email：cqsong@niglas.ac.cn
  • Introduction：宋春桥，1986年生，男，研究员，研究方向为水文遥感。E-mail： cqsong@niglas.ac.cn
SONG Chunqiao1*

реферат

Lakes play an important role in supplying water resources and sustaining human living. The broad geographical extent and complex environment of China result in the different changing patterns and complicated driving factors of lakes. The two-epoch national lake surveys provide the groundbreaking knowledge of lake distribution and change characteristics in China. Thus, an increasing number of researchers have conducted the national-scale remote sensing monitoring of lake changes with the rapid development of satellite techniques in recent years. However, evident discrepancies exist in the results and conclusions among these prior studies due to differences in level of manual quality control, lake mapping method, and the acquisition time (year and month) of used remote sensing images. Thus, comprehensively investigating their differences and causes and producing an updated lake inventory are required.We reviewed and compared the data sources, methods, and results of the existing works on national-scale remotely sensed lake changes and analyzed the causes of such differences. We also produced a new national lake inventory by interpreting the maximum water inundation area (1980—2010), which can minimize the differences of manual interpretation and lake mapping in different time periods. With the spatial constrain of maximum water extent for each lake from the new inventory, this study developed a novel approach, namely, the Probability Equivalent Area method, to detect the long-term change trajectory of China’s lakes during 1980—2010.A total of 3741 lakes in China had a maximum area exceeding 1 km2 in the past 30 years. The Qinghai-Tibet Plateau lake zone accounted for approximately one-third in count and half in area of the inventoried lakes in China. The total area of China’s lakes showed an overall upward trend, but it had strong spatial heterogeneity. The Qinghai-Tibet Plateau and Xinjiang lake zones significantly increased lake areas, while the Eastern Plain, Inner Mongolia Plateau, and Yunnan-Guizhou Plateau lake zones significantly decreased lake areas. The area changes in the Northeast Plain and Mountain lake zone were statistically insignificant.This study suggested that the main causes of different results in previous remote sensing research of China’s lakes include inconsistent timing of satellite imagery, the manual interpretation standards for lakes and reservoirs, and quality assurance procedures. To produce a more accurate estimation of lake area, a new inventory dataset, which minimized interpretation differences and provided a unified spatiotemporal constraint, was proposed on the basis of our findings. A statistics-based method named the Probability Equivalent Area, which eliminated differences in satellite imagery selection, was also proposed. The lake area changing patterns and distribution of lake water resources in different lake zones are obviously imbalanced in China. China’s sparsely populated areas are generally experiencing a dramatic increase in lake area. However, the densely populated areas are experiencing a significant decline in lake area. This situation may further increase the imbalance of water resources per capita in China. Effective measures should be taken to slow down this trajectory.

ключеви́че слова́

lake remote sensing;Water Area;remote sensing monitoring;China;National Scale;global change

References

  1. 1.
    Cai Y, Ke C Q, Yao G H and Shen X Y. 2020. MODIS-observed variations of lake ice phenology in Xinjiang, China. Climatic Change, 158(3/4): 575-592
  2. 2.
    Duan H T, Ma R H, Xu X F, Kong F X, Zhang S X, Kong W J, Hao J Y and Shang L L. 2009. Two-decade reconstruction of algal blooms in China’s Lake Taihu. Environmental Science and Technology, 43(10): 3522-3528
  3. 3.
    Feng L, Hu C M, Chen X L, Cai X B, Tian L Q and Gan W X. 2012. Assessment of inundation changes of Poyang Lake using MODIS observations between 2000 and 2010. Remote Sensing of Environment, 121: 80-92
  4. 4.
    Feng S L, Liu S G, Huang Z H, Jing L, Zhao M F, Peng X, Yan W D, Wu Y P, Lv Y H, Smith A R, Mcdonald M A, Patil S D, Sarkissian A J, Shi Z H, Xia J and Ogbodo U S. 2019. Inland water bodies in China: Features discovered in the long-term satellite data. Proceedings of the National Academy of Sciences of the United States of America, 116(51): 25491-25496
  5. 5.
    Huang S F, Li J G and Xu M. 2012. Water surface variations monitoring and flood hazard analysis in Dongting Lake area using long-term Terra/MODIS data time series. Natural Hazards, 62(1): 93-100
  6. 6.
    Jiang G J, Ma R H, Loiselle S A and Duan H T. 2012. Optical approaches to examining the dynamics of dissolved organic carbon in optically complex inland waters. Environmental Research Letters, 7(3): 034014
  7. 7.
    Jiang L G, Nielsen K, Andersen O B and Bauer-Gottwein P. 2017. Monitoring recent lake level variations on the Tibetan Plateau using CryoSat-2 SARIn mode data. Journal of Hydrology, 544: 109-124
  8. 8.
    Li J L and Sheng Y W. 2012. An automated scheme for glacial lake dynamics mapping using Landsat imagery and digital elevation models: a case study in the Himalayas. International Journal of Remote Sensing, 33(16): 5194-5213
  9. 9.
    Liu D, Duan H T, Loiselle S, Hu C M, Zhang G Q, Li J L, Yang H, Thompson J R, Cao Z G, Shen M, Ma R H, Zhang M and Han W X. 2020. Observations of water transparency in China’s lakes from space. International Journal of Applied Earth Observation and Geoinformation, 92: 102187
  10. 10.
    Liu J N, Yao Y B and Shi C. 2001. Theoretic research on robustified least squares estimator based on equivalent variance-covariance. Geo-Spatial Information Science, 4(4): 1-8
  11. 11.
    Ma R H, Duan H T, Hu C M, Feng X Z, Li A N, Ju W M, Jiang J H and Yang G S. 2010. A half-century of changes in China’s lakes: Global warming or human influence? Geophysical Research Letters, 37(24): L24106
  12. 12.
    Ma R H, Yang G S, Duan H T, Jiang J H, Wang S M, Feng X Z, Li A N, Kong F X, Xue B, Wu J L and Li S J. 2011. China’s lakes at present: Number, area and spatial distribution. Science China Earth Sciences, 54(2): 283-9
  13. 13.
    Otsu N. 1979. A threshold selection method from gray-level histograms. IEEE Transactions on Systems, Man, and Cybernetics, 9(1): 62-66
  14. 14.
    Pekel J F, Cottam A, Gorelick N and Belward A S. 2016. High-resolution mapping of global surface water and its long-term changes. Nature, 540(7633): 418-422
  15. 15.
    Shi K, Zhang Y L, Song K S, Liu M L, Zhou Y Q, Zhang Y B, Li Y, Zhu G W and Qin B Q. 2019a. A semi-analytical approach for remote sensing of trophic state in inland waters: Bio-optical mechanism and application. Remote Sensing of Environment, 232: 111349
  16. 16.
    Shi K, Zhang Y L, Zhang Y B, Li N, Qin B Q, Zhu G W and Zhou Y Q. 2019b. Phenology of phytoplankton blooms in a trophic lake observed from long-term MODIS data. Environmental Science and Technology, 53(5): 2324-2331
  17. 17.
    Song C Q, Huang B and Ke L H. 2013. Modeling and analysis of lake water storage changes on the Tibetan Plateau using multi-mission satellite data. Remote Sensing of Environment, 135: 25-35
  18. 18.
    Song C Q, Huang B, Ke L H and Richards K S. 2014. Seasonal and abrupt changes in the water level of closed lakes on the Tibetan Plateau and implications for climate impacts. Journal of Hydrology, 514(1): 131-144
  19. 19.
    Song C Q, Zhan P F and Ma R H. 2020. Progress in remote sensing study on lake hydrologic regime. Journal of Lake Sciences, 32(5): 1406-1420
  20. 20.
    Song K S, Wen Z D, Shang Y X, Yang H, Lyu L L, Liu G, Fang C, Du J and Zhao Y. 2018. Quantification of dissolved organic carbon (DOC) storage in lakes and reservoirs of mainland China. Journal of Environmental Management, 217: 391-402
  21. 21.
    Tao S L, Fang J Y, Ma S H, Cai Q, Xiong X Y, Tian D, Zhao X, Fang L Q, Zhang H, Zhu J L and Zhao S Q. 2020. Changes in China’s lakes: climate and human impacts. National Science Review, 7(1): 132-140
  22. 22.
    Wang S L, Li J S, Zhang B, Spyrakos E, Tyler A N, Shen Q, Zhang F F, Kuster T, Lehmann M K, Wu Y H and Peng D L. 2018. Trophic state assessment of global inland waters using a MODIS-derived Forel-Ule index. Remote Sensing of Environment, 217: 444-460
  23. 23.
    Wang S M and Dou H S. 1998. Chinese Lake Catalogue. Beijing: Science Press
  24. 24.
    Wang Y, Feng L, Liu J G, Hou X J and Chen D L. 2020. Changes of inundation area and water turbidity of Tonle Sap Lake: responses to climate changes or upstream dam construction? Environmental Research Letters, 15(9): 0940a1
  25. 25.
    Wu F C, Meng W, Song Y H, Liu Z T, Jin X C, Zheng B H, Wang Y Y, Wang S R, Jiang X, Lu S Y, Chu Z S, Chen Y Q, Wang C, Hua Z L, Wang P F, Yu Z Q and Fu J M. 2008. Research progress in lake water quality criteria in China. Acta Scientiae Circumstantiae, 28(12): 2385-2393
  26. 26.
    Wu Y H, Li M R, Guo L N, Zheng H X and Zhang H Y. 2019. Investigating water variation of lakes in Tibetan Plateau using remote sensed data over the past 20 years. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12(7): 2557-2564
  27. 27.
    Xie C, Huang X and Li J Y. 2018. Assessing China’s lake changes and associated driving forces during 1985-2015. Photogrammetric Engineering and Remote Sensing, 84(10): 657-666
  28. 28.
    Yang G S, Ma R H, Zhang L, Jiang J H, Yao S C, Zhang M and Zeng H A. 2010. Lake status, major problems and protection strategy in China. Journal of Lake Sciences, 22(6): 799-810
  29. 29.
    Zhang G Q, Yao T D, Chen W F, Zheng G X, Shum C K, Yang K, Piao S L, Sheng Y W, Yi S, Li J L, O’Reilly C M, Qi S H, Shen S S P, Zhang H B and Jia Y Y. 2019. Regional differences of lake evolution across China during 1960s—2015 and its natural and anthropogenic causes. Remote Sensing of Environment, 221: 386-404
  30. 30.
    Zhou Q, Wang J R, Tian L Q, Feng L, Li J and Xing Q G. 2021. Remotely sensed water turbidity dynamics and its potential driving factors in Wuhan, an urbanizing city of China. Journal of Hydrology, 593: 125893

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