Handbook of HydroInformatics
Volume III: Water Data Management Best Practices
- 1st Edition - December 6, 2022
- Imprint: Elsevier
- Editors: Saeid Eslamian, Faezeh Eslamian
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 8 2 1 9 6 2 - 1
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 2 1 9 5 2 - 2
Handbook of HydroInformatics Volume III: Water Data Management Best Practices presents the latest and most updated data processing techniques that are fundamental to Water Sc… Read more
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Request a sales quoteHandbook 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.
Post graduates and above interested in: Water Science, Geotechnique, Soil Science, Civil Engineering, Chemical Engineering, Computer Engineering, Engineering, Applied Science, Earth and Geoscience, Atmospheric Science, Geography, Environment Science, Natural Resources, Mathematical Science, Social Sciences
- Cover image
- Title page
- Table of Contents
- Copyright
- Dedication
- Contributors
- About the Editors
- Preface
- Chapter 1: Advantage of grid-free analytic element method for identification of locations and pumping rates of wells
- Abstract
- 1: Introduction
- 2: Limitations of the study
- 3: Methodology and formulation of the simulation-optimization model
- 4: Model application and results
- 5: Conclusions
- References
- Chapter 2: Application of experimental data and soft computing techniques in determining the outflow and breach characteristics in embankments and landslide dams
- Abstract
- 1: Introduction
- 2: Proposed methodology
- 3: Landslide natural dams
- 4: Results and discussion
- 5: Conclusions
- References
- Chapter 3: Hydrological modeling of Hasdeo River Basin using HEC-HMS
- Abstract
- Acknowledgment
- 1: Introduction
- 2: The rationale of the study
- 3: Materials and methods
- 4: Result and discussions
- 5: Limitations of the study
- 6: Conclusions
- References
- Further reading
- Chapter 4: Application of soft computing methods in turbulent storm water modeling
- Abstract
- 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
- Abstract
- 1: Introduction
- 2: Bed load transport equations
- 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
- Abstract
- 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
- Abstract
- Acknowledgments
- 1: Introduction
- 2: Causal reasoning
- 3: Bayesian causal modeling (BCM)
- 4: Applications
- 5: Results and discussion
- 6: Conclusions
- References
- Chapter 8: Data assimilation in hydrological and hazardous forecasting
- Abstract
- 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
- Abstract
- 1: Introduction
- 2: Hydrological routing
- 3: Hydraulic routing
- 4: Uniform flow
- 5: Specific energy
- 6: Gradually varied flow
- 7: Conclusions
- References
- Further reading
- Chapter 10: Application of fuzzy logic in water resources engineering
- Abstract
- 1: Introduction
- 2: Fundamentals of fuzzy sets
- 3: Fuzzy logic model
- 4: Discussions
- 5: Conclusions
- References
- Chapter 11: GIS Application in floods mapping in the Ganges–Padma River basins in Bangladesh
- Abstract
- Acknowledgments
- 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
- 7: Unstable settlement locations at Purba Khas Bandarkhola Mouza
- 8: Conclusions
- References
- Chapter 12: Groundwater level forecasting using hybrid soft computing techniques
- Abstract
- Acknowledgment
- 1: Introduction
- 2: Governing equation for groundwater flow and data driven groundwater level forecasting models
- 3: Soft computing based GWL forecasting model development
- 4: Results and discussion
- 5: Conclusions
- References
- Chapter 13: Hydroinformatics methods for groundwater simulation
- Abstract
- 1: Introduction
- 2: Methods
- 3: Discussion
- 4: Conclusions
- References
- Chapter 14: Hydrological-Hydraulic Modeling of floodplain inundation: A case study in Bou Saâda Wadi—Subbasin_Algeria
- Abstract
- 1: Introduction
- 2: Site of study
- 3: Methodology
- 4: Results and discussion
- 5: Conclusions
- References
- Chapter 15: Interoceanic waterway network system
- Abstract
- 1: Introduction
- 2: Notable channel systems
- 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
- Abstract
- 1: Introduction
- 2: Lattice Boltzmann models for closed conduit hydraulics
- 3: Lattice Boltzmann models for open channel hydraulics
- 4: Lattice Boltzmann models for seepage flows
- 5: Conclusions
- References
- Chapter 17: Developments in sediment transport modeling in alluvial channels
- Abstract
- 1: Introduction
- 2: Approaches for predicting sediment transport
- 3: Issues under considerations
- 4: Conclusions
- References
- Chapter 18: Modeling approaches for simulating the processes of wetland ecosystems
- Abstract
- 1: Introduction
- 2: Types of models
- 3: Discussion
- 4: Modeling of emerging contaminants
- 5: Conclusions
- References
- Chapter 19: Multivariate linear modeling for the application in the field of hydrological engineering
- Abstract
- 1: Introduction
- 2: General linear model
- 3: Hybrid causal-multivariate linear modeling (H_C-MLM)
- 4: Conclusions
- References
- Chapter 20: Ontology-based knowledge management framework: Toward CBR-supported risk response to hydrological cascading disasters
- Abstract
- Acknowledgments
- 1: Introduction
- 2: Ontology modeling for hydrological cascading disaster risk
- 3: Scenario layout with ontology base
- 4: Ontology-supported four-stage scenario reuse
- 5: Gap analysis on ontology-based CBR from a failure perspective
- 6: Conclusions
- References
- Chapter 21: Optimally pruned extreme learning machine: A new nontuned machine learning model for predicting chlorophyll concentration
- Abstract
- 1: Introduction
- 2: Study area and data
- 3: Methodology
- 4: Results and discussion
- 5: Conclusions
- References
- Chapter 22: Proposing model for water quality analysis based on hyperspectral remote sensor data
- Abstract
- 1: Introduction
- 2: Data collection and study area
- 3: Proposed model
- 4: Result analysis
- 5: Conclusions
- References
- Chapter 23: Real-time flood hydrograph predictions using rating curve and soft computing methods (GA, ANN)
- Abstract
- 1: Introduction
- 2: Flood routing methods
- 3: Soft computing methods (GA, ANN) in flood routing
- 4: Conclusions
- References
- Chapter 24: River Bathymetry acquisition techniques and its utility for river hydrodynamic modeling
- Abstract
- 1: Introduction
- 2: History
- 3: Bathymetry measurement techniques used across world
- 4: Bathymetry measurement techniques used in India
- 5: Methods of acquiring bathymetry data
- 6: Approaches for measuring bathymetry
- 7: Acoustics
- 8: Optics
- 9: Radar structure
- 10: Methods of river cross-section extraction using DEM with the application of HEC-RAS
- 11: Results and discussion
- 12: Conclusions
- References
- Chapter 25: Runoff modeling using group method of data handling and gene expression programming
- Abstract
- 1: Introduction
- 2: Study area
- 3: Data and sources
- 4: Results and discussion
- 5: Uncertainty assessment of performance of GMDH rainfall-runoff model
- 6: Conclusions
- References
- Chapter 26: Sediment transport with soft computing application for tropical rivers
- Abstract
- Acknowledgments
- 1: Introduction
- 2: Application of machine learning in sediment transport
- 3: A hybrid method by using soft computing technique
- 4: Evolutionary polynomial regression (EPR)
- 5: Multi-gene genetic programming (MGGP)
- 6: M5 tree model (M5P)
- 7: Results and discussion
- 8: Conclusions
- References
- Index
- Edition: 1
- Published: December 6, 2022
- No. of pages (Paperback): 420
- No. of pages (eBook): 420
- Imprint: Elsevier
- Language: English
- Paperback ISBN: 9780128219621
- eBook ISBN: 9780128219522
SE
Saeid Eslamian
Saeid Eslamian received his PhD in Civil and Environmental Engineering from University of New South Wales, Australia in 1998. Saeid was Visiting Professor in Princeton University and ETH Zurich in 2005 and 2008 respectively. He has contributed to more than 1K publications in journals, conferences, books. Eslamian has been appointed as 2-Percent Top Researcher by Stanford University for several years. Currently, he is full professor of Hydrology and Water Resources and Director of Excellence Center in Risk Management and Natural Hazards. Isfahan University of Technology, His scientific interests are Floods, Droughts, Water Reuse, Climate Change Adaptation, Sustainability and Resilience
Affiliations and expertise
Distinguished Full Professor, Disaster Relief: Resilient and Sustainable Water Resources, Isfahan University of Technology, IranFE
Faezeh Eslamian
Faezeh Eslamian is a PhD holder of bioresource engineering from McGill University. Her research focuses on the development of a novel lime-based product to mitigate phosphorus loss from agricultural fields. Faezeh completed her bachelor’s and master’s degrees in civil and environmental engineering from Isfahan University of Technology, Iran, where she evaluated natural and low-cost absorb bents for the removal of pollutants such as textile dyes and heavy metals. Furthermore, she has conducted research on the worldwide water quality standards and wastewater reuse guidelines. Faezeh is an experienced multidisciplinary researcher with research interests in soil and water quality, environmental remediation, water reuse, and drought management.
Affiliations and expertise
Project Manager, GHD, Quebec, CanadaRead Handbook of HydroInformatics on ScienceDirect