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Full Description
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.
Features:
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.
Contents
Introduction to Watershed Management. Characteristics of Watershed. Soil Erosion and Its Control. Water Harvesting. Water Quality Management in Watershed. Groundwater. 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.
