Quantitative Information Fusion for Hydrological Sciences

Linda See (auth.), Xing Cai, T. -C. Jim Yeh (eds.)3540749292, 978-3-540-74929-5, 978-3-540-75383-4, 3540753834, 3540753842, 9783540753841

In a rapidly evolving world of knowledge and technology, do you ever wonder how hydrology is catching up? This book takes the angle of computational hydrology and
envisions one of the future directions, namely, 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.
Intelligent computation and information fusion are the key words. The aim is to provide both established scientists and graduate students with a summary of recent developments in this topic. The chapters of this edited volume cover some of the most important ingredients for quantitative hydrological information fusion, including data fusion techniques, interactive computational environments, and supporting mathematical and numerical methods. Real-life applications of hydrological information fusion are also addressed.

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Table of contents :
Front Matter….Pages I-IX
Data Fusion Methods for Integrating Data-driven Hydrological Models….Pages 1-18
A New Paradigm for Groundwater Modeling….Pages 19-41
Information Fusion using the Kalman Filter based on Karhunen-Loève Decomposition….Pages 43-68
Trajectory-Based Methods for Modeling and Characterization….Pages 69-103
The Role of Streamline Models for Dynamic Data Assimilation in Petroleum Engineering and Hydrogeology….Pages 105-136
Information Fusion in Regularized Inversion of Tomographic Pumping Tests….Pages 137-162
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….Pages 163-181
Integrated Methods for Urban Groundwater Management Considering Subsurface Heterogeneity….Pages 183-218