Quantitative Information Fusion for Hydrological Sciences 2008
Xing Cai, T.-C. Jim Yeh (Eds.):
Quantitative Information Fusion for Hydrological Sciences.
Studies in Computational Intelligence Vol. 79 Springer 2008, ISBN 978-3-540-75383-4 BibTeX
- Linda M. See:
Data Fusion Methods for Integrating Data-driven Hydrological Models.
1-18
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- Shu-Guang Li, Qun Liu:
A New Paradigm for Groundwater Modeling.
19-41
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- Zhiming Lu, Dongxiao Zhang, Yan Chen:
Information Fusion using the Kalman Filter based on Karhunen-Loève Decomposition.
43-68
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- D. W. Vasco:
Trajectory-Based Methods for Modeling and Characterization.
69-103
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- Akhil Datta-Gupta, Deepak Devegowda, Dayo Oyerinde, Hao Cheng:
The Role of Streamline Models for Dynamic Data Assimilation in Petroleum Engineering and Hydrogeology.
105-136
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- Geoffrey C. Bohling:
Information Fusion in Regularized Inversion of Tomographic Pumping Tests.
137-162
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- Faisal Hossain, Nitin Katiyar:
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.
163-181
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- Jannis Epting, Peter Huggenberger, Christian Regli, Natalie Spoljaric, Ralph Kirchhofer:
Integrated Methods for Urban Groundwater Management Considering Subsurface Heterogeneity.
183-218
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Copyright © Sat May 16 22:55:07 2009
by Michael Ley (ley@uni-trier.de)