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Water Resource Modeling and Computational Technologies

Specificaties
Paperback, blz. | Engels
Elsevier Science | e druk, 2022
ISBN13: 9780323919104
Rubricering
Elsevier Science e druk, 2022 9780323919104
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Samenvatting

Water Resource Modeling and Computational Technologies, Seventh Edition provides the reader with a comprehensive overview of the applications that computational techniques have in various sectors of water resource engineering. The book explores applications of recent modeling and computational techniques in various sectors of water resource engineering, including hydroinformatics, irrigation engineering, climate change, hydrologic forecasting, floods, droughts, image processing, GIS, water quality, aquifer mapping, basin scale modeling, computational fluid dynamics, numerical modeling of surges and groundwater flow, river engineering, optimal reservoir operation, multipurpose projects, and water resource management. As such, this is a must read for hydrologists, civil engineers and water resource managers.

Specificaties

ISBN13:9780323919104
Taal:Engels
Bindwijze:Paperback

Inhoudsopgave

<p>Section I - Introduction<br>1. Artificial intelligence and machine learning in water resources engineering</p> <p>Section II - Application of Artificial Intelligence to Water Resources<br>2. Demystifying Artificial Intelligence amidst Sustainable Agricultural Water Management<br>3. Bidirectional Long Short-Term Memory Based Empirical Wavelet Transform: a New Hybrid Artificial Intelligence Model for Robust Prediction of Soil Moisture Content<br>4. Fuzzy logic modeling of groundwater potential in Marinduque, Philippines<br>5. Soft-computing approach to scour depth prediction under wall jets</p> <p>Section III – Image Processing Applications in Water Resources<br>6. Assessment of Water Resources using Remote Sensing and GIS Techniques<br>7. Establishing Spatial Relationships Between Land Use and Water Quality Influenced by Urbanization<br>8. Satellite sensors, machine learning and river channel unit types: A review<br>9. Geospatial modeling in the assessment of environmental resources for sustainable water resource management in a semi-arid region: A GIS approach<br>10. Study of morphologic changes of Arvand River in the past and predicting its future changes<br>11. Rainfall runoff modelling using GIS: a case study of Gonbad Kavous, Iran<br>12. GIS-Based Hydrological Models for a Sustainable Groundwater Management: An Overview<br>13. Development of Rainfall-Runoff Model Using ANFIS with an Integration of GIS: A Case Study<br>14. Assessing the impact of land use and land cover changes on the water balances in an urbanized peninsular region of India</p> <p>Section IV - Advances in Hydroinformatics mitigation<br>15. Random Vector Functional Link Network based On Variational Mode Decomposition for Accurate Prediction of River Water Turbidity<br>16. Water Quality Management: Development of a Fuzzy based index in Hydroinformatics platform<br>17. Appraisal Of Multi-Gene Genetic Programming For Estimating Optimal Properties Of Lined Open Channels With Circular Shapes Incorporating Constant And Variable Roughness Scenarios<br>18. Geoinformatics based assessment of gross irrigation requirement of different crops grown in the south-western region of Haryana, India</p> <p>Section V - Advances in Watershed Modelling<br>19. Theorical background and application of numerical models to surface water resources<br>20. Prophecy of groundwater fluctuation through SVM-FFA hybrid approaches in arid watershed, India<br>21. Basin-scale Subsurface Hydrology: Modelling of a stressed and data-scarce aquifer using hillslope-based approach</p> <p>Section VI - Advances in Numerical Modelling in Water Resources<br>22. Multiphysics modelling of groundwater flow on the example of a coupled thermo-hydro-mechanical model of infiltration of water warmer or cooler than the surroundings.<br>23. Hydro-Salinity Modeling of Water and Salt Dynamics in Irrigated Soil Groundwater Systems</p> <p>Section VII - Optimization Techniques and Analytical Formulations in Water Resource<br>24. Multi-objective optimization techniques for urban water management: An Agent Modeling Approach<br>25. Hybrid Extreme Learning Machine Optimized Bat Algorithm based on Ensemble Empirical Mode Decomposition for Modelling Dissolved Oxygen in River<br>26. Application of machine learning models to side-weir discharge coefficient estimations in trapezoidal and rectangular open channels</p> <p>Section VIII - Advances in Sediment Transport Modelling and River Engineering<br>27. The hole size analysis of bursting events around mid-channel bar using the conditional method approach<br>28. Magnitude Frequency Analysis of Sediment Transport: Concept, Review and Application<br>29. Last Century Evolution of Local Scour Measuring Techniques</p> <p>Section IX - Computational Intelligence in Extreme Hydrology: Flood and Droughts<br>30. Understanding trends and its variability of rainfall and temperature over Patna (Bihar)<br>31. A review of climate change trends and scenarios (2011-2021)<br>32. Climate change and trend analysis of precipitation and temperature: a case study of Gilan, Iran<br>33. Innovative Triangular Trend analysis of monthly precipitation at Shiraz station, Iran<br>34. Understanding Rainfall Variability and Trends in Arid Region of Rajasthan, India<br>35. Flash Floods and their Impact on Natural Life Using Surface Water Model and GIS Technique at Wadi Degla Natural Reserve Area, Egypt<br>36. GLOF Early Warning System – Computational Challenges and Solutions<br>37. Flood Forecasting using novel ANFIS-WOA approach in Mahanadi river basin, India</p>

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        Water Resource Modeling and Computational Technologies