The study develops a 2D hydrodynamic model using HEC-RAS to assess flood hazards and generate inundation maps for the lower Narmada basin in Gujarat, India. The model effectively simulates flood dynamics by integrating data, i.e. digital elevation models, stream gauge data, and land use and land cover information. Results indicate strong model performance, with R² and root mean square error (RMSE) values of 0.92 and 0.12 for calibration and 0.77 and 0.08 for validation. Approximately 326.45 km² of the basin is severely inundated during major flood events, with agriculture being most affected. The model's outputs, including depth maps, velocity maps, and water arrival time predictions, provide critical insights for flood management. Floodwaters take 110 h to reach nearby areas and 361 h to reach validation points from upstream dam releases, offering an 8-h window to alert residents of potential overflow conditions. This information is vital for early warning systems and evacuation planning.

Plastic film mulching (PF) was extensively used to improve maize yields, but its continuous application with ridge-furrow practices led to a significant depletion of soil organic carbon (SOC) and soil water storage (SWS). A study conducted during the 2018–19 rabi season on sandy loam soils evaluated the impact of different mulching techniques—Reflective Silver Plastic Mulch (RSPM), Rice Straw Mulch (RSM), Biodegradable Mulch (BM), and control without mulching (CK)—under irrigation regimes defined by IW/CPE ratios of 0.6, 0.8, and 1.0. The highest grain yields were achieved with an IW/CPE ratio of 1.0, with Reflective Silver Plastic Mulch significantly outperforming other treatments in grain yield (7086.57 kg/ha) and water use efficiency (WUE), followed by Biodegradable Mulch and Rice Straw Mulch. Reflective Silver Plastic Mulch also enhanced all major yield attributes, particularly when combined with the highest irrigation level, while the lowest values were observed under minimal irrigation and no mulch. The study concluded that irrigation at an IW/CPE ratio of 1.0 combined with Reflective Silver Plastic Mulch optimized maize yield, water use efficiency, and economic returns under drip irrigation.

Floods rank among the most devastating natural disasters, causing extensive damage to property and severe impacts on communities. Effective management and mitigation of flood risks necessitate reliable data regarding flood depth, discharge, and extent. The Karjan River Basin’s low-lying regions experienced significant flooding in 2020. This research utilizes the latest new HEC-RAS version for one-dimensional hydrodynamic flood modelling for the Karjan River in low-lying areas and the merging point of the Karjan River Basin in Narmada River, emphasizing geospatial techniques. The study showcases the analytical process of the new HEC-RAS v6 in spatial analysis. River features like bank lines and cross-sections were derived from ALOS Palsar for flood modeling. An unsteady flow simulation was conducted to model water dynamics, yielding water depth results viewable in the HEC-RAS geospatial RAS mapper. Flood depth maps created for 2020 reveal that areas low lying area i.e. Dhamncha, bhadam, Juna Rundh and surrounding area near the merging point of Karjan River are prone to floods when river discharge surpasses 8836 cubic meters per second. Model accuracy was verified by comparing simulated outcomes with historical data from the mentioned events, demonstrating the model’s precision and reliability.

This book offers the fundamental concepts, state-of-the-art research and practical applications for soil and water resource management in agriculture. It underscores the need for integrated and resource efficient management practices, and draws attention to key challenges in agriculture including ill health of soils, water scarcity, sub-optimal irrigation practices, and climate uncertainty. This book covers water resource management, agricultural water requirements, irrigation scheduling, micro-irrigations and soil health and conservation. Moreover, it explores novel technologies such as Artificial Intelligence, Machine Learning, Remote sensing, GIS, Google Earth Engine, and DSS related to drought monitoring, irrigation planning, hydroclimatic modelling and agricultural resources evaluation. These disciplines collectively offer opportunities to enhance climatic resilience, water-use efficiency and support sustainable agricultural production.Researchers, academics, students, agricultural engineers and irrigation specialists are the target audience for this edited volume. Our special thanks to all of the contributing writers, colleagues and institutions for their inestimable help and assistance. We hope this book will encourage further research and technical development to encourage sustainable agricultural development in the use of soil and water resources.