Quantitative Information Fusion for Hydrological Sciences

著者

    • Cai, Xing
    • Yeh, T.-C. Jim

書誌事項

Quantitative Information Fusion for Hydrological Sciences

Xing Cai and T.-C. Jim Yeh (Eds.)

(Studies in computational intelligence, v79)

Springer, c2008

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注記

with 81 Figures and 7 Tables

内容説明・目次

内容説明

In this rapidly evolving world of knowledge and technology, do you ever wonder how hydrology is catching up? Here, two highly qualified scientists edit a volume that takes the angle of computational hydrology and envision one of the science's future directions - namely, the quantitative integration of high-quality hydrologic field data with geologic, hydrologic, chemical, atmospheric, and biological information to characterize and predict natural systems in hydrological sciences.

目次

Data Fusion Methods for Integrating Data-driven Hydrological Models.- A New Paradigm for Groundwater Modeling.- Information Fusion using the Kalman Filter based on Karhunen-Loeve Decomposition.- Trajectory-Based Methods for Modeling and Characterization.- The Role of Streamline Models for Dynamic Data Assimilation in Petroleum Engineering and Hydrogeology.- Information Fusion in Regularized Inversion of Tomographic Pumping Tests.- Advancing the Use of Satellite Rainfall Datasets for Flood Prediction in Ungauged Basins: The Role of Scale, Hydrologic Process Controls and the Global Precipitation Measurement Mission.- Integrated Methods for Urban Groundwater Management Considering Subsurface Heterogeneity.

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詳細情報

  • NII書誌ID(NCID)
    BA86267325
  • ISBN
    • 9783540753834
  • タイトル言語コード
    eng
  • 本文言語コード
    eng
  • 出版地
    Berlin ; Heidelberg
  • ページ数/冊数
    viii, 218 p.
  • 大きさ
    24 cm
  • 親書誌ID
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