000 03458nam a22005295i 4500
001 978-3-540-75384-1
003 DE-He213
005 20170628034802.0
007 cr nn 008mamaa
008 100301s2008 gw | s |||| 0|eng d
020 _a9783540753841
_9978-3-540-75384-1
024 7 _a10.1007/978-3-540-75384-1
_2doi
050 4 _aTA329-348
050 4 _aTA640-643
072 7 _aTBJ
_2bicssc
072 7 _aMAT003000
_2bisacsh
082 0 4 _a519
_223
100 1 _aCai, Xing.
_eeditor.
245 1 0 _aQuantitative Information Fusion for Hydrological Sciences
_h[electronic resource] /
_cedited by Xing Cai, T. -C. Jim Yeh.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2008.
300 _aIX, 218 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Computational Intelligence,
_x1860-949X ;
_v79
505 0 _aData 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.
520 _aIn 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.
650 0 _aEngineering.
650 0 _aHydraulic engineering.
650 0 _aEngineering geology.
650 0 _aArtificial intelligence.
650 0 _aEngineering mathematics.
650 1 4 _aEngineering.
650 2 4 _aAppl.Mathematics/Computational Methods of Engineering.
650 2 4 _aHydrogeology.
650 2 4 _aGeotechnical Engineering.
650 2 4 _aArtificial Intelligence (incl. Robotics).
700 1 _aYeh, T. -C. Jim.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783540753834
830 0 _aStudies in Computational Intelligence,
_x1860-949X ;
_v79
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-540-75384-1
912 _aZDB-2-ENG
999 _c21511
_d21511