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Research on Similar Basin Recognition Method Based on Time-varying Feature Matrix
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Ke LI1, 2, 3, Guang-yuan KAN1, 2, 3, Xiao-yan HE1, 2, 3, Bing-jie ZHU4
Water Resources and Power | 2023, 41(6) : 13 - 16
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Water Resources and Power | 2023, 41(6): 13-16
HYDROLOGY, WATER RESOURCES AND ENVIRONMENT
Research on Similar Basin Recognition Method Based on Time-varying Feature Matrix
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Ke LI1, 2, 3, Guang-yuan KAN1, 2, 3, Xiao-yan HE1, 2, 3, Bing-jie ZHU4
Affiliations
  • 1.State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, Beijing 100038, China
  • 2.China Institute of Water Resources and Hydropower Research, Beijing 100038, China
  • 3.Research Center on Flood and Drought Disaster Reduction of the Ministry of Water Resources, Beijing 100038, China
  • 4.Henan Bureau of Hydrology and Water Resources, Zhengzhou 450003, China
Published: 2023-06-25 doi: 10.20040/j.cnki.1000-7709.2023.20221474
Outline
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A similar basin identification method was proposed to improve the reliability of similar basin identification for hydrological forecasting in ungauged basin. The method introduced the basin time-varying feature information and constructed a time-varying feature matrix (TVFM). A dimension reduction method for the TVFM was proposed to obtain the basin feature vector. The classical K-means clustering method was adopted to implement the identification of the similar basins. Seventeen natural catchments in Jiangxi Province were selected and the Xin'anjiang model was applied in this research. A series of studies were carried out which includes feature vector and feature matrix construction, similar basin identification, parameter transfer, and comparison & analysis of hydrological forecasting results. The following conclusions can be drawn. The proposed TVFM can achieve better forecasting results in ungauged basins. Compared with the traditional similar basin identification method based on time-invariant underlying surface information, the prediction accuracy is improved. The similar basin identification based on time-varying comprehensive features generates the best predictions, and the prediction accuracy based on time-varying meteorological features is better than that based only on time-invariant underlying surface features. Comparison with the single factor methods, the directional problem of the parameter transfer can be partially solved by the proposed comprehensive method. Unfortunately, the directional problem cannot be completely overcame until recently.

similar basins  /  time-varying feature matrix  /  ungauged basin  /  parameter transfer  /  Xin'anjing model
Ke LI, Guang-yuan KAN, Xiao-yan HE, Bing-jie ZHU. Research on Similar Basin Recognition Method Based on Time-varying Feature Matrix[J]. Water Resources and Power, 2023 , 41 (6) : 13 -16 . DOI: 10.20040/j.cnki.1000-7709.2023.20221474
Year 2023 volume 41 Issue 6
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Article Info
doi: 10.20040/j.cnki.1000-7709.2023.20221474
  • Receive Date:2022-07-18
  • Online Date:2026-01-28
  • Published:2023-06-25
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History
  • Received:2022-07-18
  • Revised:2022-08-19
Funding
Affiliations
    1.State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, Beijing 100038, China
    2.China Institute of Water Resources and Hydropower Research, Beijing 100038, China
    3.Research Center on Flood and Drought Disaster Reduction of the Ministry of Water Resources, Beijing 100038, China
    4.Henan Bureau of Hydrology and Water Resources, Zhengzhou 450003, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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