Quantitative Information Fusion for Hydrological Sciences 2008

• Linda M. See:
  Data Fusion Methods for Integrating Data-driven Hydrological Models. 1-18
  
• Shu-Guang Li, Qun Liu:
  A New Paradigm for Groundwater Modeling. 19-41
  
• Zhiming Lu, Dongxiao Zhang, Yan Chen:
  Information Fusion using the Kalman Filter based on Karhunen-Loève Decomposition. 43-68
  
• D. W. Vasco:
  Trajectory-Based Methods for Modeling and Characterization. 69-103
  
• 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
  
• Geoffrey C. Bohling:
  Information Fusion in Regularized Inversion of Tomographic Pumping Tests. 137-162
  
• 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
  
• Jannis Epting, Peter Huggenberger, Christian Regli, Natalie Spoljaric, Ralph Kirchhofer:
  Integrated Methods for Urban Groundwater Management Considering Subsurface Heterogeneity. 183-218