Handbook of HydroInformatics

Volume III: Water Data Management Best Practices

Saeid Eslamian, Faezeh Eslamian

• Publisher: Elsevier
• Year: 2022
• Print ISBN: 9780128219621
• eBook ISBN: 9780128219522
• Topic: Biological Sciences
• Subtopic: Business Intelligence
• Index: Biological Sciences

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.

Table of contents

• Cover
• Front Matter
• Table of Contents
• Copyright
• Dedication
• Contributors
• About the Editors
• Preface
• List of Illustrations
• List of Tables
• Chapter 1 : Advantage of grid-free analytic element method for identification of locations and pumping rates of wells
• Chapter 2 : Application of experimental data and soft computing techniques in determining the outflow and breach characteristics in embankments and landslide dams
• Chapter 3 : Hydrological modeling of Hasdeo River Basin using HEC-HMS
• Chapter 4 : Application of soft computing methods in turbulent storm water modeling
• Chapter 5 : Assessment of bed load transport for steep channels on the basis of conventional and fuzzy regression
• Chapter 6 : Automated flood inundation mapping over Ganga basin
• Chapter 7 : Causal reasoning modeling (CRM) for rivers’ runoff behavior analysis and prediction
• Chapter 8 : Data assimilation in hydrological and hazardous forecasting
• Chapter 9 : Flood routing computations
• Chapter 10 : Application of fuzzy logic in water resources engineering
• Chapter 11 : GIS Application in floods mapping in the Ganges–Padma River basins in Bangladesh
• Chapter 12 : Groundwater level forecasting using hybrid soft computing techniques
• Chapter 13 : Hydroinformatics methods for groundwater simulation
• Chapter 14 : Hydrological-Hydraulic Modeling of floodplain inundation: A case study in Bou Saâda Wadi—Subbasin_Algeria
• Chapter 15 : Interoceanic waterway network system
• Chapter 16 : Lattice Boltzmann models for hydraulic engineering problems
• Chapter 17 : Developments in sediment transport modeling in alluvial channels
• Chapter 18 : Modeling approaches for simulating the processes of wetland ecosystems
• Chapter 19 : Multivariate linear modeling for the application in the field of hydrological engineering
• Chapter 20 : Ontology-based knowledge management framework: Toward CBR-supported risk response to hydrological cascading disasters
• Chapter 21 : Optimally pruned extreme learning machine: A new nontuned machine learning model for predicting chlorophyll concentration
• Chapter 22 : Proposing model for water quality analysis based on hyperspectral remote sensor data
• Chapter 23 : Real-time flood hydrograph predictions using rating curve and soft computing methods (GA, ANN)
• Chapter 24 : River Bathymetry acquisition techniques and its utility for river hydrodynamic modeling
• Chapter 25 : Runoff modeling using group method of data handling and gene expression programming
• Chapter 26 : Sediment transport with soft computing application for tropical rivers
• Index
• A