Open Access
Issue
SHS Web Conf.
Volume 192, 2024
2024 3rd International Conference on Urban Planning and Regional Economy (UPRE 2024)
Article Number 02011
Number of page(s) 4
Section Regional Economy and Environmental Impact Analysis
DOI https://doi.org/10.1051/shsconf/202419202011
Published online 05 June 2024
  1. Ziyue Wang. Attribution and future prediction of extreme summer precipitation events in the middle and lower reaches of the Yangtze River [D]. Nanjing University of Information Science and Technology, (2023). DOI:10.27248/d.cnki.gnjqc.2023.000052. [Google Scholar]
  2. Carter E, Steinschneider S. Hydroclimatological Drivers of Extreme Floods on Lake Ontario[J]. Water Resources Research, 2018, 54(7):4461–4478. [CrossRef] [Google Scholar]
  3. Hong Wei, Yunfei Ma. On the Construction of Common Emotions of the Community of Human Destiny in Disaster Diplomacy[J]. Socialist Studies, 2021(02):163–172. [Google Scholar]
  4. Furber, A., Medema, W., Adamowski, J., Clamen, M., & Vijay, M. (2016). Conflict management in participatory approaches to water management: A case study of Lake Ontario and the St. Lawrence River Regulation. Water, 8(7), 280. https://doi.org/10.3390/w8070280. [CrossRef] [Google Scholar]
  5. Chelsea D, Xiang L, Kerry H, et al. Estimating Lake Water Volume With Regression and Machine Learning Methods#13;[J]. Frontiers in Water, 2022, 4 [Google Scholar]
  6. Gronewold, A.D., Fortin, V., Lofgren, B. et al. Coasts, water levels, and climate change: A Great Lakes perspective. Climatic Change 120, 697–711 (2013). https://doi.org/10.1007/s10584-013-0840-2 [CrossRef] [Google Scholar]
  7. Zhiyuan Y, Zhaocai W, Tunhua W, et al. A Hybrid Data-Driven Deep Learning Prediction Framework for Lake Water Level Based on Fusion of Meteorological and Hydrological Multi-source Data[J]. Natural Resources Research, 2023, 33(1):163–190. [Google Scholar]
  8. Palmer, R.N.; Cardwell, H.E.; Lorie, M.A.; Werwick, W. Disciplined planning, structured participation, and collaborative modeling—Applying Shared Vision Planning to water resources. J. Am. Water Res. Assoc. 2013, 49, 614–628. [CrossRef] [Google Scholar]
  9. Quinn, F. H. (2002). Secular changes in Great Lakes water level seasonal cycles. Journal of Great Lakes Research, 28(3), 451–465. [CrossRef] [Google Scholar]
  10. Li Y, Zhang Y, Zhang X, et al. A continuous simulation of Holocene effective moisture change represented by variability of virtual lake level in East and Central Asia[J]. Science China Earth Sciences, 2020, 63(8):1–15. [CrossRef] [Google Scholar]
  11. Li J, Xia Y, Li B, et al. A pseudo-dynamic search ant colony optimization algorithm with improved negative feedback mechanism[J]. Cognitive Systems Research, 2020, 62(pre-publish):1–9. [CrossRef] [Google Scholar]

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