Kooperativer Bibliotheksverbund

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Umfang: 1 online resource (422 pages)

ISBN: 9780128219522 , 0128219521

Inhalt: Handbook of HydroInformatics Volume III: Water Data Management Best Practices presents the latest and most updated data processing techniques that are fundamental to Water Science and Engineering disciplines. These include a wide range of the new methods that are used in hydro-modeling such as Atmospheric Teleconnection Pattern, CONUS-Scale Hydrologic Modeling, Copula Function, Decision Support System, Downscaling Methods, Dynamic System Modeling, Economic Impacts and Models, Geostatistics and Geospatial Frameworks, Hydrologic Similarity Indices, Hydropower/Renewable Energy Models, Sediment Transport Dynamics Advanced Models, Social Data Mining, and Wavelet Transforms. This volume is an example of true interdisciplinary work. The audience includes postgraduates and above interested in Water Science, Geotechnical Engineering, Soil Science, Civil Engineering, Chemical Engineering, Computer Engineering, Engineering, Applied Science, Earth and Geoscience, Atmospheric Science, Geography, Environment Science, Natural Resources, Mathematical Science, and Social Sciences. It is a fully comprehensive handbook which provides all the information needed related to the best practices for managing water data. Contributions from global experts in the fields of data management research, climate change and resilience, insufficient data problem, etc. Thorough applied examples and case studies in each chapter, providing the reader with real world scenarios for comparison. Includes a wide range of new methods that are used in hydro-modeling, with step-by-step guides on how to use them.

Anmerkung: Intro -- Handbook of HydroInformatics: Volume III: Water Data Management Best Practices -- Copyright -- Dedication -- Contents -- Contributors -- About the Editors -- Preface -- Chapter 1: Advantage of grid-free analytic element method for identification of locations and pumping rates of wells -- 1. Introduction -- 2. Limitations of the study -- 3. Methodology and formulation of the simulation-optimization model -- 3.1. AEM and FDM flow models -- 3.2. Particle swarm optimization -- 4. Model application and results -- 4.1. Physiography and topography of the area -- 5. Conclusions -- References -- Chapter 2: Application of experimental data and soft computing techniques in determining the outflow and breach character ... -- 1. Introduction -- 2. Proposed methodology -- 2.1. Failure database -- 2.2. Determination of outliers -- 2.3. Multivariate regression analysis -- 2.4. Assessment of performance indicators -- 2.5. Bayesian approach -- 2.6. Wavelet analysis -- 2.7. Gene expression programming (GEP) -- 2.8. Physical models -- 2.9. BREACH mathematical model -- 3. Landslide natural dams -- 4. Results and discussion -- 4.1. Experimental findings -- 4.2. Simulation of the breach characteristics -- 4.3. Simulation of the failure time -- 4.4. Simulations of the eroded volume of the dam -- 4.5. Simulation of the peak outflow discharge -- 4.6. Simulation of hydrograph resulting from dam failure -- 5. Conclusions -- References -- Chapter 3: Hydrological modeling of Hasdeo River Basin using HEC-HMS -- 1. Introduction -- 2. The rationale of the study -- 3. Materials and methods -- 3.1. Data collection -- 3.1.1. Topographical data -- 3.1.2. Multispectral satellite data -- 3.1.3. Soil data -- 3.1.4. Hydro-meteorological data -- 3.2. Methodology -- 3.2.1. Model development -- 3.2.2. Hydrological modeling -- 3.3. Model calibration and validation. , 3.4. Model evaluation parameter -- 4. Result and discussions -- 4.1. Calibration and validation results -- 4.1.1. For rain gauge station data -- 4.1.2. For gridded precipitation data -- 4.2. Goodness of fit curve -- 5. Limitations of the study -- 6. Conclusions -- References -- Further reading -- Chapter 4: Application of soft computing methods in turbulent storm water modeling -- 1. Introduction -- 2. Rainfall-runoff modeling between SWMM and fuzzy logic approach -- 3. Urban flood prediction using deep neural network with data augmentation -- 4. Application of expert system for storm water management modeling -- 5. Developing a flexible expert system tool -- 6. Development of ES tool ``Flext´´ -- 7. Conclusions -- References -- Chapter 5: Assessment of bed load transport for steep channels on the basis of conventional and fuzzy regression -- 1. Introduction -- 2. Bed load transport equations -- 2.1. Formula of Smart and Jaeggi -- 2.2. Formula of Meyer-Peter and Müller -- 3. Fuzzy linear regression -- 4. Application of the bed load transport formula of Smart and Jaeggi on the basis of conventional and fuzzy regression -- 5. Conclusions -- Appendix I -- Appendix II -- Appendix III -- References -- Chapter 6: Automated flood inundation mapping over Ganga basin -- 1. Introduction -- 2. Literature review -- 3. Materials and methods -- 4. Results and discussion -- 5. Conclusions -- References -- Chapter 7: Causal reasoning modeling (CRM) for rivers runoff behavior analysis and prediction -- 1. Introduction -- 2. Causal reasoning -- 3. Bayesian causal modeling (BCM) -- 3.1. Main principles -- 3.2. General methodology -- 3.3. Validation -- 4. Applications -- 4.1. Runoff temporal records analysis (runoff fractions evaluation) -- 4.2. Runoff temporal records prediction -- 4.3. Hydrological spatial records prediction -- 4.4. Spatiotemporal records prediction. , 5. Results and discussion -- 6. Conclusions -- References -- Chapter 8: Data assimilation in hydrological and hazardous forecasting -- 1. Introduction -- 2. Data assimilation for hydrological forecasting -- 3. Data assimilation for hazardous forecasting -- 4. Importance of spatial precision systems in error reduction -- 5. Discussion and future perspective -- 6. Conclusions -- References -- Chapter 9: Flood routing computations -- 1. Introduction -- 1.1. Hydrological routing models -- 1.2. Hydraulic routing models -- 2. Hydrological routing -- 2.1. Reservoir routing -- 2.2. Muskingum method -- 2.3. Modified Puls method -- 3. Hydraulic routing -- 3.1. Derivation of St. Venants equation -- 3.2. Regimes of flow -- 4. Uniform flow -- 4.1. Mannings equation -- 4.2. Uniform flow, geometries -- 5. Specific energy -- 5.1. Rectangular cross-section -- 5.2. Nonrectangular cross-section -- 6. Gradually varied flow -- 7. Conclusions -- References -- Further reading -- Chapter 10: Application of fuzzy logic in water resources engineering -- 1. Introduction -- 2. Fundamentals of fuzzy sets -- 2.1. Fuzzy set representation -- 2.2. Fuzzy set operations -- 2.2.1. Union and intersection of sets -- 2.2.2. Complementary sets -- 2.2.3. Unique operations peculiar to fuzzy sets -- 3. Fuzzy logic model -- 3.1. Fuzzification -- 3.2. Fuzzy rule base -- 3.3. Fuzzy inference engine -- 3.4. Defuzzification -- 4. Discussions -- 5. Conclusions -- References -- Chapter 11: GIS Application in floods mapping in the Ganges-Padma River basins in Bangladesh -- 1. Introduction -- 2. Objective of this study -- 3. Geographical location and physical characteristics of the study area -- 4. Data and methodology -- 5. Geographer and anthropologist view -- 6. Floods and char-land erosion and deposition in the river basins in Bangladesh. , 6.1. Impacts of floods on char-lands and changing rural livelihoods -- 6.2. Char-lands erosion and accretion pattern in the Padma River basin -- 7. Unstable settlement locations at Purba Khas Bandarkhola Mouza -- 7.1. Cyclic displacement of Basir Uddin: Case analysis 1 (1960-2008) -- 7.2. Cyclic displacement of Omar Ali: Case analysis 2 (1945-2018) -- 7.3. Discussion on dislodgment model results -- 8. Conclusions -- References -- Chapter 12: Groundwater level forecasting using hybrid soft computing techniques -- 1. Introduction -- 2. Governing equation for groundwater flow and data driven groundwater level forecasting models -- 3. Soft computing based GWL forecasting model development -- 3.1. Study area and data -- 3.1.1. Spatial variability of groundwater level -- 3.2. Machine learning algorithms and metaheuristics -- 3.2.1. Artificial neural networks -- 3.2.2. Applying metaheuristic algorithm on NN training -- Swarm intelligence on neural network -- Lion algorithm optimized long short-term memory RNN -- 3.2.3. SVR based model -- 3.2.4. Applying metaheuristic algorithm on SVR training -- 4. Results and discussion -- 4.1.1. Feedforward ANN network based GWL forecasting models -- ANN-ABC-PSO GWL forecasting system -- LSTM-RNN based GWL forecasting models -- 4.1.2. Performance evaluation of SVR based GWL forecasting model -- Lateritic terrain -- Well at Perdoor (well.ID: 80722) in lateritic terrain -- Well at Brahmavar (well.ID: 80723) in lateritic terrain -- Banded gneissic complex -- Well at Shankar Narayana (wel.ID: 80710) in BGC terrain -- Well at hiragana of Yenne hole (well.ID: 80702) in BGC terrain -- 4.1.3. Comparative analysis -- 5. Conclusions -- References -- Chapter 13: Hydroinformatics methods for groundwater simulation -- 1. Introduction -- 2. Methods -- 2.1. Time series and Markov chain methods -- 2.2. Geostatistics Methods. , 2.3. GIS and remote sensing -- 2.4. Cluster analysis -- 2.5. Soft-computing methods -- 2.6. Stochastic models -- 2.7. SOM models -- 2.8. Conceptual models -- 3. Discussion -- 4. Conclusions -- References -- Chapter 14: Hydrological-Hydraulic Modeling of floodplain inundation: A case study in Bou Saâda Wadi-Subbasin_Algeria -- 1. Introduction -- 2. Site of study -- 3. Methodology -- 4. Results and discussion -- 4.1. Peak discharge estimation -- 4.2. Delineation of Bou Saâda Wadi-Subbasin -- 4.3. Floodplain mapping for return periods -- 5. Conclusions -- References -- Chapter 15: Interoceanic waterway network system -- 1. Introduction -- 2. Notable channel systems -- 2.1. Parana and Danube -- 3. Paleohydrography and channel systems -- 4. Paleodynamics of large rivers, remote sensing -- 5. Integrated waterways systems -- 6. Integrated interoceanic channel systems -- 7. Conclusions -- References -- Further reading -- Chapter 16: Lattice Boltzmann models for hydraulic engineering problems -- 1. Introduction -- 2. Lattice Boltzmann models for closed conduit hydraulics -- 2.1. LB solutions to selected problems -- 2.2. Brief review on recent trends of pipe flows by the LB models -- 3. Lattice Boltzmann models for open channel hydraulics -- 3.1. Transcritical flow over a weir -- 3.2. Brief review of recent trends in open channel flows with the LB model -- 4. Lattice Boltzmann models for seepage flows -- 4.1. Seepage flow through an earth dam -- 4.2. Future outlook on the seepage flow modeling with the LB models -- 5. Conclusions -- References -- Chapter 17: Developments in sediment transport modeling in alluvial channels -- 1. Introduction -- 2. Approaches for predicting sediment transport -- 2.1. Empirical approaches -- 2.2. Physics-based approaches -- 2.3. Advanced approaches -- 3. Issues under considerations -- 3.1. Particle fall velocity. , 3.2. Sediment particle velocity.

Weitere Ausg.: ISBN 9780128219621

Weitere Ausg.: ISBN 0128219629

Sprache: Englisch