Anurag M. Bhargav

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.

This book is a collection of current viewpoints on how to create productive, resilient and environmentally sustainable agricultural and food systems. It reflects on the potential of climate-smart practices and sustainable cropping systems, as well as natural farming, digital agriculture, crop monitoring, and decision-support technologies in helping to maintain farm productivity while simultaneously protecting natural resources. Special focus is dedicated to resources, including soil and water; using inputs efficiently; adapting to shifts in climate change; and managing farming through smart technologies to make better decisions.It also takes care of the process of agriculture to food processing and value addition. The chapters address the progresses in the field of food processing, process modelling, food quality and safety issues, shelf-life extension approaches, intelligent packages, biodegradable packages, and circular usage of agricultural by-products. These topics collectively emphasize the need to bridge the gap between resilient production and efficient processing, minimize losses, and achieve more sustainable food systems.This edited book provides an interdisciplinary perspective on concepts, practices, and technologies for current-day agriculture to scientists, students, educationalists, farming practitioners, and everyone interested in sustainable development in agriculture. We hope it will spur more research, collaboration, and practical innovation in the area of climate resilience and sustainable resource use and more sustainable agricultural future. Table of Content Section I - Sustainable Agriculture and Climate-Smart Production1 Introduction to Sustainable Agricultural and Food SystemsNiraj Kumar, Dhiraj Kumar, Pritam Das, A. M. Bhargav and Samir Sen 2 Climate-Smart Agricultural Practices and TechnologiesSarju Thokchom 3 Climate-Resilient Cropping Systems and Sustainable ProductionKamendra, Hirak Jyoti Sarmah, Sanjay H. Parmar and Daksh Vadalia, N. H. Gohel 4 Natural Farming and Ecological Approaches to Crop ProductionGopi J. Ram, Rohit V. Bharadava, Jigna N. Rathod Section II - Digital Agriculture, Crop Monitoring and Risk Management5 Crop Monitoring and Decision Support for Climate-Resilient AgricultureWashim Sarkar, Tarun Agarwal, Sabyasachi Murmu and Pritam Das 6 Digital Agriculture and Smart Farm ManagementSumanpriya Sorokhaibam, Avanija Rathore, Nitin Koumary and Dhiraj Kumar 7 Risk Management and Adaptation Strategies in Agricultural ProductionBivek Chakma, Akhilesh Kumar, Sagar Debbarma Section III - Food Processing, Quality, Preservation and Sustainable Technologies8 The Sensor-Based Multi-Crop Thresher for Indian FarmersNitin Kumar, Prof. S. Karmakar, N. H. Gohel, S. R. Makvana 9 Novel Food Processing Technologies for Sustainable Food SystemsDhananjay Kumar, Deepali Bharti and Chaman Kumar 10 Process Modelling, Optimization and Scale-Up in Food ProcessingVaidehi Verma 11 Emerging Processing Technologies for Climate-Resilient Food SystemsV. A. Jhala, Bimal Prachi, Khushboo Kumari, Samir Sen 12 Food Quality and Safety in Agricultural Value ChainsBimal Prachi 13 Shelf-Life Extension and Preservation of Food ProductsSandeep Yadav and Joyita Mali 14 Intelligent, Active and Biodegradable Food PackagingSudhanshu Kannaujia 15 Sustainable Food Processing and Circular Utilization of Agricultural By-ProductsA.R. Mevada, S.H. Sankaliya and Sushant Patel

Agriculture, a cornerstone of national prosperity, is evolving through innovative technologies like the Internet of Things (IoT). These advancements enhance farming productivity by enabling real‐time monitoring, automation, and precise resource management. IoT applications in agriculture integrate sensors and connectivity to optimize processes such as soil analysis, crop health assessment, and irrigation management. Meanwhile, the emergence of 5G connectivity revolutionizes smart farming with ultralow latency, high‐speed data transfer, and seamless communication among devices. These capabilities support the development of autonomous machinery, drones, and data‐driven decision‐making tools that streamline operations and improve yields. 5G technology enables rapid transmission of large datasets from IoT sensors, supporting applications such as machine learning for pest and disease detection, autonomous vehicle navigation, and environmental monitoring. Integration of 5G in precision farming facilitates intelligent resource allocation, minimizing waste while maximizing outputs. Challenges persist, including data security, interoperability, and infrastructure costs. However, the synergy between 5G and IoT holds transformative potential for sustainable agricultural practices. This paper explores the advancements in IoT and enabling 5G technologies within agriculture, focusing on their applications, benefits, and challenges. It highlights case studies and research insights, showcasing how these innovations contribute to more efficient, scalable, and sustainable farming. The findings underscore the critical role of digital technologies in addressing global food security and fostering resilience against climate change.

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.

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.

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.

This research bears significant implications for river management, flood forecasting, and ecosystem preservation in the Lower Narmada Basin. A more precise estimation of Manning’s Roughness Coefficeint (n) will enhance the accuracy of hydraulic models and facilitate informed decision-making regarding flood risk management, water resource allocation, and environmental conservation efforts. Ultimately, this study aspires to contribute to the sustainable management of perennial river systems in India and beyond by offering a robust methodology for optimizing Manning’s n tailored to the complex hydrological dynamics of the Lower Narmada Basin. Through a synthesis of empirical evidence and computational modelling, it seeks to empower stakeholders with actionable insights toward preserving and enhancing these invaluable natural resources. Using the new HEC-RAS v 6.0, a one-dimensional hydrodynamic model was developed to predict overbank discharge at different points along the basin. The study analyzes water levels, stream discharges, and river stage, optimizing Manning’s n and required flood risk management. The model predicted a strong output agreement with R², NSE, and RMSE for the 2020 event as 0.83, 0.81, and 0.36, respectively, with an optimum Manning’s n of 0.03. The lower Narmada Basin part near the coastal zone (validation point) appears inundated frequently. The paper aims to provide insights into optimizing Manning’s coefficient, which can ultimately lead to better water flow predictions and more efficient water management in the region.