Assessment of Sustainable Development Goal (SDG6) for water resources on Hainan Island based on Big Earth Data

  • role: First author第一作者
  • Affiliation:

    Key Laboratory of Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

    International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China

    University of Chinese Academy of Sciences, Beijing 100049, China

  • Email:hanzhiting21@mails.ucas.ac.cn
  • Introduction: E-mail hanzhiting21@mails.ucas.ac.cn
HAN Zhiting123,  
  • role: Corresponding author通信作者
  • Affiliation:

    Key Laboratory of Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

    International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China

  • Email:liaojj@aircas.ac.cn
  • Introduction: E-mail liaojj@aircas.ac.cn
LIAO Jingjuan12*,  
  • Affiliation:

    Key Laboratory of Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

    International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China

ZHANG Li12

ملخص

أهداف التنمية المستدامة للمياه SDG 6 (Sustainable Development Goal 6) هي الأساس لتحقيق أهداف الأمم المتحدة الأخرى في التنمية المستدامة. تقع جزيرة هاينان في منطقة استوائية وتمتلك موارد مائية بحرية غنية، لكن بيئة موارد المياه العذبة هشة. يستند هذا البحث إلى نظام تقييم الأمم المتحدة للتنمية المستدامة، مع مراعاة الوضع الفعلي في جزيرة هاينان، لتحديد مؤشرات هدف التنمية المستدامة رقم 6 محلياً، وجمع البيانات الإحصائية والبيانات عن بعد من المدن والمقاطعات، ودمج مؤشر أثر الخدمات البيئية في نموذج خدمات النظام الإيكولوجي Co$ting Nature (NFWQ) للحصول على جودة المياه الطبيعية، وبناء إطار تقييم أكثر استكمالاً للتنمية المستدامة، وتقييم SDG 6 في مدينة ومقاطعة جزيرة هاينان من سنة 2015 إلى 2021. تُظهر النتائج: (1) أن درجة مؤشر SDG 6 (0-100 نقطة) تشير إلى أن مستوى التنمية المستدامة لجزيرة هاينان قد تحسن بشكل ملحوظ، حيث كانت درجة SDG 6 لمعظم مدن مقاطعات جزيرة هاينان تشهد ارتفاعاً متدرجاً من عام 2015 حتى عام 2021. (2) من بين 18 مدينة ومقاطعة، كانت العاصمة هايكو ومدينة السياحة سانيا لديهما أعلى درجة إجمالية لمؤشر SDG 6. حيث حلت مقاطعة تونغتشانغ ومدينة ووزيشان ومقاطعة تشيونغ في المرتبة الأولى من حيث سرعة النمو، وبلغت نسبها على التوالي: 91.4% و 74.2% و 73%. (3) يوضح توزيع مستوى تطوير الهدف 6 في جزيرة هاينان أنه غير متساو، ويُظهر نمطاً مكانياً بارزاً بين الأجزاء الشرقية والوسطى والجنوبية والشمالية والغربية. إذاً، توفير مؤشرات خدمات النظام الإيكولوجي ونظام تقييم التأقيس المحلي لمدن ومقاطعات جزيرة هاينان التي تم اقتراحها في هذا البحث، يمكنها دعم إقامة مقاطعة هاينان لتنفيذ الخطة الوطنية الخامسة عشرة والفوز في حرب السيطرة على المياه الست.

مفهوم

remote sensing;SDG 6;Natural Footprint on Water Quality (NFWQ);water resource management and assessment;Co$ting nature ecosystem service model;Hainan Island

References

  1. 1.
    Allen C, Nejdawi R, El-Baba J, Hamati K, Metternicht G and Wiedmann T. 2017. Indicator-based assessments of progress towards the sustainable development goals (SDGs): a case study from the Arab region. Sustainability Science, 12(6): 975-989
  2. 2.
    Bhaduri A, Bogardi J, Siddiqi A, Voigt H, Vörösmarty C, Pahl-Wostl C, Bunn S E, Shrivastava P, Lawford R, Foster S, Kremer H, Renaud F G, Bruns A and Osuna V R. 2016. Achieving sustainable development goals from a water perspective. Frontiers in Environmental Science, 4: 64.
  3. 3.
    Chen C, Zhao Y H and Hao C X. 2021. Analysis on 2020 global environmental performance index report and suggestions. Environmental Protection, 49(2): 69-74
  4. 4.
    陈晨, 赵元浩, 郝春旭. 2021. 2020年可持续发展目标生态环境领域指标分析与建议. 环境保护, 49(2): 69-74
  5. 5.
    Chen J D, Gao M, Ma K and Song M L. 2020. Different effects of technological progress on China’s carbon emissions based on sustainable development. Business Strategy and the Environment, 29(2): 481-492
  6. 6.
    Choi H A, Song C, Lee W K, Jeon S and Gu J H. 2018. Integrated approaches for national ecosystem assessment in South Korea. KSCE Journal of Civil Engineering, 22(5): 1634-1641
  7. 7.
    Feng X M, Liu Q L, Yin L C, Fu B J and Chen Y Z. 2018. Linking water research with the sustainability of the human-natural system. Current Opinion in Environmental Sustainability, 33: 99-103
  8. 8.
    Gao B, Xu Y P, Wang Q, Yang J, Shen S Z and Xu X. 2017. Effects of land use changes on water quality of the plain area in Taihu Basin. Journal of Agro-Environment Science, 36(6): 1186-1191
  9. 9.
    高斌, 许有鹏, 王强, 杨洁, 沈顺忠, 徐兴. 2017. 太湖平原地区不同土地利用类型对水质的影响. 农业环境科学学报, 36(6): 1186-1191
  10. 10.
    Garrick D E, Hall J W, Dobson A, Damania R, Grafton R Q, Hope R, Hepburn C, Bark R, Boltz F, De Stefano L, O'Donnell E, Matthews N and Money A. 2017. Valuing water for sustainable development. Science, 358(6366): 1003-1005
  11. 11.
    Green P A, Vörösmarty C J, Harrison I, Farrell T, Sáenz L and Fekete B M. 2015. Freshwater ecosystem services supporting humans: pivoting from water crisis to water solutions. Global Environmental Change, 34: 108-118
  12. 12.
    Hainan Academy of Environmental Sciences. 2023. Spatial distribution dataset of ecosystem types in Hainan, 2000—2019. 海南省环境科学研究院. 2023. 2000年—2019年海南生态系统类型空间分布数据集). https://data.casearth.cn/thematic/hainan/259). [2023-05-01]
  13. 13.
    Hainan Provincial Bureau of Statistics. 2022. Hainan Statistical Yearbook. Beijing: China Statistics Press
  14. 14.
    海南省统计局. 2022. 海南统计年鉴. 北京: 中国统计出版社
  15. 15.
    Hao J. 2021. Study on the spatial differentiation pattern and influencing factors of the level of human sustainable development in China. Changchun: Jilin University
  16. 16.
    郝辑. 2021. 中国人类可持续发展水平的空间分异格局与影响因素研究. 长春: 吉林大学
  17. 17.
    Harrison I J, Green P A, Farrell T A, Juffe-bignoli D, Sáenz L and Vörösmarty C J. 2016. Protected areas and freshwater provisioning: a global assessment of freshwater provision, threats and management strategies to support human water security. Aquatic Conservation: Marine and Freshwater Ecosystems, 26(S1): 103-120
  18. 18.
    Hemati T, Pourebrahim S, Monavari M and Baghvand A. 2020. Species-specific nature conservation prioritization (a combination of MaxEnt, Co$ting Nature and DINAMICA EGO modeling approaches). Ecological Modelling, 429: 109093
  19. 19.
    Herrera D, Ellis A, Fisher B, Golden C D, Johnson K, Mulligan M, Pfaff A, Treuer T and Ricketts T H. 2017. Upstream watershed condition predicts rural children’s health across 35 developing countries. Nature Communications, 8(1): 811
  20. 20.
    Ionescu G H, Jianu E, Patrichi I C, Ghiocel F, Țenea L and Iancu D. 2021. Assessment of Sustainable Development Goals (SDG) implementation in Bulgaria and future developments. Sustainability, 13(21): 12000
  21. 21.
    Li J S and Wang S L. 2022. 10m datasets of remote sensing monitoring in Hainan Island inland water ecology from 2019 to 2021 (FUI, Transparency, Trophic status).
  22. 22.
    李俊生, 王胜蕾. 2022. 2019-2021年海南岛10 m内陆水生态遥感监测数据集(FUI、透明度、营养状态). https://data.casearth.cn/thematic/hainan/233).[2023-05-01]
  23. 23.
    Li L B. 2019. Estimation of available quantity of water resources in Hainan Island. Water Resources Informatization, (6): 38-44
  24. 24.
    李龙兵. 2019. 海南岛水资源可利用量估算. 水利信息化, (6): 38-44
  25. 25.
    Liu M J, Graham N, Wang W Y, Zhao R Z, Lu Y L, Elimelech M and Yu W Z. 2022. Spatial assessment of tap-water safety in China. Nature Sustainability, 5(8): 689-698
  26. 26.
    Lu S L, Jia L, Jiang Y Z, Wang Z M, Duan H T, Shen M, Tian Y and Lu J. 2021. Progress and prospect on monitoring and evaluation of United Nations SDG 6 (clean water and sanitation) target. Bulletin of Chinese Academy of Sciences, 36(8): 904-913
  27. 27.
    卢善龙, 贾立, 蒋云钟, 王宗明, 段洪涛, 沈明, 田雨, 卢静. 2021. 联合国可持续发展目标6(清洁饮水与卫生设施)监测评估: 进展与展望. 中国科学院院刊, 36(8): 904-913
  28. 28.
    Mulligan M. 2009. The human water quality footprint: agricultural, industrial, and urban impacts on the quality of available water globally and in the Andean region//Proceedings of the International Conference on Integrated Water Resource Management and Climate Change. Cali, CO.: 11. .[2023-05-01]
  29. 29.
    Mulligan M. 2022. The problem with water footprints outside of irrigated drylands. Water International, 47(7): 1085-1107
  30. 30.
    Mulligan M, van Soesbergen A, Hole D G, Brooks T M, Burke S and Hutton J. 2020. Mapping nature’s contribution to SDG 6 and implications for other SDGs at policy relevant scales. Remote Sensing of Environment, 239: 111671
  31. 31.
    Peng S Z. 2022. 1-km monthly potential evapotranspiration dataset for China (1901-2023). National Tibetan Plateau / Third Pole Environment Data Center.
  32. 32.
    彭守璋. 2022. 中国1km逐月潜在蒸散发数据集(1901—2023). 国家青藏高原数据中心). https://data.tpdc.ac.cn/zh-hans/data/8b11da09-1a40-4014-bd3d-2b86e6dccad4 [2023-04-15]
  33. 33.
    Rosenstock T S, Lamanna C, Chesterman S, Hammond J, Kadiyala S, Luedeling E, Shepherd K, DeRenzi B and Van Wijk M T. 2017. When less is more: innovations for tracking progress toward global targets. Current Opinion in Environmental Sustainability, 26-27: 54-61
  34. 34.
    Sachs J D, Kroll C, Lafortune G, Fuller G and Woelm F. 2022. Sustainable Development Report 2022. Cambridge: Cambridge University Press
  35. 35.
    Tang G A. 2019. Digital elevation model of China (1KM). National Tibetan Plateau / Third Pole Environment Data Center[EB/OL].
  36. 36.
    汤国安. 2019. 中国数字高程图(1KM). 国家青藏高原数据中心) [EB/OL]. [2023-04-17]
  37. 37.
    UNESCO. 2023. The United Nations World Water Development Report 2023: Partnerships and Cooperation for Water[EB/OL]. Paris: UNESCO. . [2023-04-15]
  38. 38.
    UN-Water. 2021. The United Nations World Water Development Report 2021: Valuing Water[EB/OL]. YorkNew, NY, USA: United Nations. https://www.unwater.org/publications/un-world-water-development-report-2021. [2023-03-15]
  39. 39.
    Wang Q. 2021. Progress of environmental remote sensing monitoring technology in China and some related frontier issues. National Remote Sensing Bulletin, 25(1):25-36
  40. 40.
    王桥.2021.中国环境遥感监测技术进展及若干前沿问题.遥感学报,25(1): 25-36
  41. 41.
    WorldPop. 2023. The spatial distribution of population density in 2020, China. Southampton: University of Southampton. https://www.worldpop.org. [2023-01-16]
  42. 42.
    Wu B F, Zeng Y, Yan N N, Zeng H W, Zhao D, Zhang M. 2020. Remote sensing for ecosystem:Definition and prospects. Journal of Remote Sensing (in Chinese), 24(6): 609-617
  43. 43.
    吴炳方, 曾源, 闫娜娜, 曾红伟, 赵旦, 张淼. 2020. 生态系统遥感:内涵与挑战. 遥感学报, 24(6): 609-617
  44. 44.
    Xiang X M. 2007. An analysis of main characteristics and factors on the sustainable development of water resources in Hainan. Journal of Hainan Normal University (Natural Science), 20(1): 80-83
  45. 45.
    向晓明. 2007. 海南岛水资源基本特点及影响可持续发展的主要因素初探. 海南师范大学学报(自然科学版), 20(1): 80-83
  46. 46.
    Xiao R B, Ouyang Z Y, Han Y S, Wang X K, Li Z X and Zhao T Q. 2004. Ecological security assessment of Hainan Island. Journal of Natural Resources, 19(6): 769-775
  47. 47.
    肖荣波, 欧阳志云, 韩艺师, 王效科, 李振新, 赵同谦. 2004. 海南岛生态安全评价. 自然资源学报, 19(6): 769-775
  48. 48.
    Xu L L, Liu H Q, Jin Y, Hou Y Y and Zhao Y L. 2017. Characteristics of and problems from development and utilization of water resources in Hainan Province. Chinese Journal of Tropical Agriculture, 37(9): 120-127
  49. 49.
    徐磊磊, 刘海清, 金琰, 侯媛媛, 赵云龙. 2017. 海南省水资源开发利用特点及主要水资源问题. 热带农业科学, 37(9): 120-127
  50. 50.
    Xu Z C, Chau S N, Chen X Z, Zhang J, Li Y J, Dietz T, Wang J Y, Winkler J A, Fan F, Huang B R, Li S X, Wu S H, Herzberger A, Tang Y, Hong D Q, Li Y K and Liu J G. 2020. Assessing progress towards sustainable development over space and time. Nature, 577(7788): 74-78
  51. 51.
    Zhang C, Sun Z C, Xing Q, Sun J L, Xia T Y and Yu H. 2021a. Localizing Indicators of SDG11 for an integrated assessment of urban sustainability—a case study of Hainan Province. Sustainability, 13(19): 11092
  52. 52.
    Zhang J J. 2017. Comprehensive evaluation of resources and environment carrying capacity in Hainan Island. Wuhan: China University of Geosciences (张晶晶. 2017. 海南岛资源环境承载力评价. 武汉: 中国地质大学)
  53. 53.
    Zhang L, Li G Q, Zhu L W, Guo H D. 2019. Construction and service demonstration of Hainan remote sensing big data platform. Journal of Remote Sensing (in Chinese), 23(2): 327-335
  54. 54.
    张丽, 李国庆, 朱岚巍, 郭华东. 2019. 海南省遥感大数据服务平台建设与应用示范. 遥感学报, 23(2): 327-335
  55. 55.
    Zhang X, Liu L Y, Chen X D, Gao Y, Xie S and Mi J. 2021b. GLC_FCS30: Global land-cover product with fine classification system at 30 m using time-series Landsat imagery. Earth System Science Data, 13(6): 2753-2776
  56. 56.
    Zheng C L, Jia L and Hu G C. 2022. ETMonitor global actual evapotranspiration dataset with 1resolution-km. National Tibetan Plateau / Third Pole Environment Data Center. https://data.tpdc.ac.cn/zh-hans/data/c284bd88-7694-4577-9cbb-02684bd940ff/ (郑超磊, 贾立, 胡光成. 2022.
  57. 57.
    ETMonitor全球1公里分辨率地表实际蒸散发数据集. 国家青藏高原科学数据中心). https://data.tpdc.ac.cn/zh-hans/data/c284bd88-7694-4577-9cbb-02684bd940ff/[2023-01-16]

قراءة النص الكامل

The above content is generated by Large Model Translation. The translated content is for reference only. We do not assume any commercial or legal responsibilty for any consequences arising from the use of our website