Commensurability-based flood forecasting in northeastern China

• Autorzy: Peng Z. , Zhang L. , Yin J. , Wang H.
• Języki publikacji: EN

Abstrakty

EN

Northeastern China is one of the largest industrial and agricultural bases in China, but frequent flooding brings huge losses to the people and country. To forecast floods in northeastern China, we used commensurability forecasting techniques and ordered a network structure chart and butterfly structure diagram. The prediction selected extraordinary flooding years that have occurred in the region since 1856, and it used ternary, quinary, and septenary commensurability calculation models for forecasting. It verified the inevitability of flooding in 2013 and showed that northeastern China would be highly prone to flooding in 2017. The specific locations of flooding would be the second Songhua River or Liaohe River. The ordered network structure and butterfly structure diagram are the extension of commensurability, both of which showed perfect symmetry neatly and orderly, and indicated the great possibility of flooding in northeastern China in 2017. Because of spatial distribution in the region, we also picked up four representative sites in the region to subsidiarily forecast the runoff qualitatively. Except for a site that did not have a significant year, the other three sites showed that the runoff in the second Songhua River would be wet in 2017. The idea of this paper is good in the data-starved area and helpful for improving judgment regarding flood trends.

• Wydawca: -
• Czasopismo: Polish Journal of Environmental Studies
• Rocznik: 2017
• Tom: 26
• Numer: 6
• Opis fizyczny: p.2689-2702,fig,ref.

Twórcy

autor

Peng Z.

• College of Environmental Science and Engineering, Donghua University, Shanghai 200051, China

autor

Zhang L.

• China Institute of Water Resources and Hydropower Research, Beijing 100044, China

autor

Yin J.

• China Institute of Water Resources and Hydropower Research, Beijing 100044, China

autor

Wang H.

• China Institute of Water Resources and Hydropower Research, Beijing 100044, China

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Identyfikatory

DOI

10.15244/pjoes/73859