Quantitative Information Fusion for Hydrological Sciences
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,...
Kaydedildi:
| Yazar: | |
|---|---|
| Diğer Yazarlar: | |
| Materyal Türü: | Livre numérique |
| Dil: | Anglais |
| Baskı/Yayın Bilgisi: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Edisyon: | 1st ed. 2008. |
| Seri Bilgileri: | Studies in Computational Intelligence
79 |
| Online Erişim: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Not: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Quantitative information fusion for hydrological sciences, Xing Cai, T.-C. Jim Yeh (eds.), Berlin, Springer, 2008, 1 vol. (VIII-218 p.), Studies in computational intelligence, 978-3-540-75383-4 |
İçindekiler:
- Data Fusion Methods for Integrating Data-driven Hydrological Models A New Paradigm for Groundwater Modeling Information Fusion using the Kalman Filter based on Karhunen-Loève 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