Climate change poses significant challenges to global agriculture, necessitating sustainable practices to ensure food security and mitigate environmental impacts. Climate-smart agriculture (CSA) is a technique that aims to boost agricultural productivity, improve adaptive ability, and reduce greenhouse gas emissions. It includes practices like crop management, sustainable farming, agroforestry, precision farming, and climate-resilient crop varieties. CSA improves soil health, water use efficiency, erosion, carbon sequestration, biodiversity conservation, and resource utilization. Precision agriculture tools like remote sensing and data analytics enable site-specific management decisions. Climate-resilient crop types, such as drought-tolerant, heat-tolerant, and disease-resistant, are crucial for food production under changing climatic conditions. Encouraging laws, institutional frameworks, and financial incentives are essential for CSA implementation. However, more research and collaboration are needed to promote widespread adoption of CSA practices.

The agricultural sector faces considerable challenges as a result of climate change requiring the implementation of new and sustainable methods. This chapter delves into climate-smart agriculture (CSA), an all-encompassing strategy for boosting agricultural resilience and profitability that incorporates environmental, economic, and social considerations. Various agricultural settings are taken into account with topics including soil, water, crop, livestock, forest, and fisheries management. Precision farming, reforestation, and animal husbandry are all examples of CSA methods. Increased productivity, stable food supplies, lessened vulnerability, and lower expenses are just some of the ways it boosts economic benefits. The results of successful CSA programs can be learned from case studies. Challenges and future prospects are discussed in the latter section of the chapter, along with calls for further study, technical advancements, and policy changes.

Drought is a complex natural disaster with significant implications for agriculture, water resources, and socioeconomic development. Accurate and timely assessment of meteorological drought is crucial for effective management and mitigation strategies. Climate change has led to a rise in climatic anomalies, such as droughts, floods, heatwaves, and cold snaps, which have severe impacts on human well-being and societal patterns. Droughts, which are prolonged periods of limited or absent rainfall, pose significant challenges for sectors like agriculture, energy, and enterprises, especially in economically reliant countries with inadequate water management infrastructure. Drought indicators are essential in meteorology, agriculture, and hydrology for monitoring drought conditions. Accurate drought assessment relies on quantitative index-based comprehensive drought indices, such as India’s Aridity Anomaly Index (AAI), Deciles Index, Percent of Normal Index, Reconnaissance Drought Index (RDI), and the Palmer Drought Severity Index (PDSI). Drought management involves analyzing risk components and using analytical tools for decision making. A decision support system includes institutional, methodological, public, and operational components. Long-term actions include demand reduction through economic incentives, while short-term actions include increasing water supply through wastewater reutilization, inter-basin water conveyance, reservoir construction, and agricultural ponds. Impact minimization is achieved through educational initiatives, reallocating water resources, early warning systems, and insurance programs. Challenges include developing technologies to integrate data sources and create unified indicators, and geospatial decision-support systems facilitate hazard mapping and strategic drought management plans.

Precision irrigation is a water management strategy that applies water to crops based on their specific needs. It is a sustainable practice that can help to increase crop yields, reduce water use, improve fertilizer use efficiency, and reduce environmental impact. This chapter offers a detailed overview of precision irrigation for sustainable agricultural productivity. It defines precision irrigation and discusses its benefits, types, components, design, implementation, management, applications, and economic and environmental benefits. The chapter also discusses the role of precision irrigation in sustainable agriculture, challenges and opportunities for adoption, and the future of precision irrigation. It is intended to be a valuable resource for farmers, researchers, policymakers, and other stakeholders interested in learning more about precision irrigation's role in sustainable agriculture.

This chapter explores the connection between sustainable agriculture and the Sustainable Development Goals (SDGs). It discusses various practices like conservation agriculture, organic farming, agroforestry, and precision agriculture, and how they contribute to various SDGs. It focuses on SDG 2 (Zero Hunger), SDG 6 (Clean Water and Sanitation), SDG 15 (Biodiversity Preservation), and SDG 1 and 8 (Rural Development). The chapter also discusses barriers to widespread adoption, including economic, technological, and sociocultural factors. It uses case studies to illustrate successful models and offers policy recommendations, emphasizing national policies aligning with sustainable agriculture, fostering international cooperation, and investing in education and capacity building. The chapter provides valuable insights for policymakers, researchers, and practitioners in agriculture, sustainability, and development.

Climate change poses a significant threat to global food security and environmental sustainability. Traditional agricultural practices often struggle to adapt to increasing weather variability and extreme events. This chapter explores the potential of AI and GIS technologies to build climate-resilient agriculture and promote environmental sustainability. AI algorithms can analyze vast datasets, including weather patterns, soil characteristics, and crop productivity data, to identify vulnerabilities and recommend strategies for farmers to adapt to changing conditions. Some applications that can help improve agricultural production are mapping climate risk, predicting drought, and finding the best places to put different crops. The chapter explores the context-specific solutions that combine technological innovation with traditional practices, fostering collaboration among farmers, researchers, developers, and business leaders to optimize resource use, enhance crop yields, and mitigate environmental impacts despite challenges like data availability and equitable access.