Watershed Management and Applications of AI
- Available for pre-order. Item will ship after May 17, 2021
Land use and water resources are two major environmental issues which necessitate conservation, management, and maintenance practices through the use of various engineering techniques. Water scientists and environmental engineers must address the various aspects of flood control, soil conservation, rainfall-runoff processes, and groundwater hydrology. Watershed Management and Applications of AI provides the necessary principles of hydrology to provide practical strategies useful for the planning, design, and management of watersheds. The book also synthesizes novel new approaches, such as hydrological applications of machine learning using neural networks to predict runoff and using artificial intelligence for the prediction of groundwater fluctuations.
- Presents hydrologic analysis and design along with soil conservation practices through proper watershed management techniques
- Provides analysis of land erosion and sediment transport in watersheds from small to large scale
- Includes estimations for runoff using different methodologies with systematic approaches for each
- Discusses water harvesting and development of water yield catchments
This book will be a valuable resource for students in hydrology courses, environmental consultants, water resource engineers, and researchers in related water science and engineering fields.
Table of Contents
Introduction to watershed management. Characteristics of watershed. Soil erosion and its control. Water Harvesting. Water quality management in watershed. Ground water. Flood and Drought. Sediment sampling and transport. Runoff. Application of Artificial Intelligence for prediction of ground water fluctuation. Prediction of flood using hybrid ANFIS-FFA approaches in Barak river basin. Prophecy of sediment load using hybrid AI approaches at various gauge station in Mahanadi river basin, India. Scheming of runoff using hybrid ANFIS for a watershed: Western Odisha, India. Application of hybrid neural network techniques for drought forecasting.
Sandeep Samantaray is currently a Ph.D scholar, Department of Civil engineering at National Institute of Technology Silchar, Assam, India. He has research publications and presentations on such subjects as watershed management, hydrological forecasting, hydrologic modelling and computing in developing sustainable means of managing the environment. He has published in 13 international journal and has written 5 book chapters and attended more than 23 international conferences (SCOPUS Indexing). He also holds two Indian patents. Abinash Sahoo is currently a Ph.D scholar, Department of Civil engineering at National Institute of Technology Silchar, Assam, India. He has research publications on open channel hydraulics, and flood forecasting. He has published in five international journals and 15 international conferences. He also has an Indian patent. Dillip Kumar Ghose is currently working as an Assistant professor at National Institute of Technology, Silchar. He obtained his bachelor’s degree in Civil Engineering from IGIT, Sarang, Odisha. He has published 14 research publications, 25 conference papers in national and international conferences. He also has 2 patents published along with DST project. He also is involved in many consultancy areas such as bridge design, soil investigation, water harvesting, and ground water detection.