The impact of climate change on methane (CH₄) emissions from rice production systems in the Coimbatore region (Tamil Nadu, India) was studied by leveraging field experiments across two main treatments and four sub-treatments in a split-plot design. Utilizing the closed-chamber method for gas collection and gas chromatography analysis, this study identified significant differences in CH₄ emissions between conventional cultivation methods and the system of rice intensification (henceforth SRI). Over two growing seasons, conventional cultivation methods reported higher CH₄ emissions (range: from 36.9 to 59.3 kg CH₄ ha⁻¹ season⁻¹) compared with SRI (range: from 2.2 to 12.8 kg CH₄ ha⁻¹ season⁻¹). Experimental data were subsequently used to guide parametrization and validation of the DeNitrification–DeComposition (DNDC) model. The validation of the model showed good agreement between the measured and modeled data, as denoted by the statistical tests performed, which included CRM (0.09), D-index (0.99), RMSE (7.16), EF (0.96), and R² (0.92). The validated model was then used to develop future CH₄ emissions projections under various shared socio-economic pathways (henceforth SSPs) for the mid- (2021–2050) and late (2051–2080) century. The analysis revealed a potential increase in CH₄ emissions for the simulated scenarios, which was dependent on specific soil and irrigation management practices. Conventional cultivation produced the highest CH₄ emissions, but it was shown that they could be reduced if the current practice was replaced by minimal flooding or through irrigation with alternating wetting and drying cycles. Emissions were predicted to rise until SSP 370, with a marginal increase in SSP 585 thereafter. The findings of this work underscored an urgency to develop climate-smart location-specific mitigation strategies focused on simultaneously improving current water and nutrient management practices. The use of methanotrophs to reduce CH₄ production from rice systems should be considered in future work. This research also highlighted the critical interaction that exists between agricultural practices and climate change, and emphasized the need to implement adaptive crop management strategies that can sustain productivity and mitigate the environmental impacts of rice-based systems in southern India.

Regenerative Agriculture is a promising concept that aims to address the challenges posed by conventional farming methods, which often lead to soil degradation and reduced productivity over time. The ultimate goal of regenerative agriculture is to revitalize the soil and landscape while offering environmental, economic and social advantages to communities. Prioritizing soil health and carbon sequestration are the key principles of regenerative agriculture. These principles include maintaining soil cover, minimizing disturbance, sustaining living roots year-round, fostering species diversity, incorporating livestock, and reducing synthetic inputs such as herbicides and fertilizers. The implementation of crop diversification and rotation techniques is a key strategy in regenerative agriculture. These techniques promote the cycling of nutrients into the soil and enhance the diversity of soil microorganisms such as bacteria. Agroforestry, another component of regenerative agriculture, contributes to carbon sequestration by utilizing stable deep-rooted systems and storing carbon within plant biomass. However, the overall efficacy of these methods may vary in different environments. Potential limitations include the upper thresholds for carbon sequestration and increased nitrogen demand. Although there are challenges to be addressed, regenerative agriculture shows promise in improving soil quality, crop productivity, and overall farm economics. This represents a shift towards more sustainable and resilient farming practices that could benefit the environment and communities.

Evapotranspiration is a crucial component of the hydrological cycle and is profoundly influenced by climate change. Assessing regional evapotranspiration changes is essential for effective water resource management. The study investigated the dynamics of reference evapotranspiration in the Lower Bhavani Basin, a region with diverse landscapes increasingly vulnerable to climatic variability. Reference evapotranspiration data from the Food and Agriculture Organization using the AgERA5 dataset was analyzed to assess annual and seasonal trends from 2000 to 2022. The result showed that the mean yearly reference evapotranspiration in the basin is 1672.87 mm, with a significant decline of 3.53 mm per year. Seasonal analysis revealed a consistent decreasing trend across all seasons, with the southwest monsoon season showing the most significant reduction in evapotranspiration rates. The notable shift in the annual evapotranspiration rate was observed in 2016, highlighting the impact of climate change. Further, temperature, solar radiation and relative humidity were identified as the dominant factors influencing evapotranspiration rates in the basin. The relative moisture index indicated prevalent dry conditions, making the region susceptible to water stress. The findings provide critical insights for regional water resources management and accentuate the need for sustainable water management strategies to mitigate the impacts of climate change.

Over the decade, rapid climatic changes threaten agroecosystem stability and food security. The rapid transition from natural vegetation to agricultural land results to alteration of surface energy balance. Numerous interactions occur within the agroecosystem among its diverse components. Properly understanding these interactions helps mitigate environmental impact through modern climate-smart technologies and sustainable crop water management based on unique needs. Smart water management paves the pathway, particularly in water crises phase through the use of numerous contemporary artificial intelligences, machine learning tools, agrometeorological models and Internet of Things based modern watering devices aid in the efficient use of resources both on and off farm to improve agricultural output and quality. The study's objective is reviewing core technologies including advanced sensors, internet of things, remote sensing and agrometeorological models. The highlights of this study to investigate SWM systems. A comparative analysis of existing technologies identifies challenges such as high cost, data privacy concerns and policy gap. To address these gaps, this study proposes an integrated approach that combines artificial intelligence, remote sensing and IoT framework as most effective approach, enabling real time monitoring, precise irrigation scheduling and adaptive response to climate variability. Advancing these technologies with suitable, cost effective solutions, and policy interventions is crucial for ensuring climate resilient, increasing the efficiency of the smart management system and sustainable agricultural water management.

This study investigates the water requirements, evapotranspiration dynamics and water productivity of cotton (CO 17) under semi-arid climatic conditions across three cropping seasons (2023-2025) at Agricultural Research Station, Bhavanisagar. Field experiments were conducted on sandy loam soils with continuous monitoring of weather, soil moisture and crop parameters. The standardized FAO Penman-Monteith equation was used to compute daily reference evapotranspiration (ETo), while actual crop evapotranspiration (ETc) was estimated using both locally developed and FAO-based crop coefficient (Kc) curves derived as functions of thermal units. Seasonal ETc ranged from 386 to 607 mm and irrigation applied varied between 170 and 336 mm. Seed cotton yield ranged from 1997 to 2237 kg/ha and lint yield from 678.8 to 761.7 kg/ha, with corresponding water use efficiency (WUE) values between 0.107 and 0.155 kg/m³ and water productivity (WP) from 0.32 to 0.46 kg/m³. Statistical analyses, including paired t-tests and regression, confirmed no significant difference (p > 0.05) between local and FAO-based ETc estimates, while a strong linear relationship (R² = 0.93) was observed between adjusted ETc and irrigation applied. The locally calibrated Kc improved ETc estimation by better representing canopy development and climatic variability. Precisely scheduled irrigation and site-specific Kc calibration enhanced yield, water productivity and resource-use efficiency, emphasizing the importance of ET-based irrigation management for sustainable cotton production in water-limited environments.

Rice production is essential for global food security and socio-economic development, as it is a staple food for many people. However, low water-use efficiency/water productivity is noticed due to the high water input in the traditional transplanted rice ecosystem with stagnant water. On the other hand, climate change affects the hydrological cycle through precipitation, causing increasing water demand and major threats to the sustainability of rice cultivation and food security for the growing population. A significant need is to find out the balance between water conservation practices and their influence on greenhouse (GHG) emissions, mainly methane. This review gives insight into a comprehensive analysis of sustainable rice production systems that improve water productivity while reducing GHG emissions, a crucial gap in existing research. To overcome this, we evaluate key strategies like aerobic rice, alternate wetting and drying (AWD), direct-seeded rice (DSR), drip-irrigated rice, a system of rice intensification (SRI) and Internet of Things (IoT) based smart irrigation, highlighting the potential water use efficiency and reducing carbon footprints. Notably, we spotlight low methane-emitting rice cultivars and drought resistance right cultivars as promising low-emission rice cultivation solutions. Additionally, this article underscores the adoption of simulation models on water productivity and seasonal GHG emissions in rice. This review provides valuable insight for policymakers and researchers to optimize rice production under changing climatic conditions. This review underscores the need for effective water management practices to enhance food security while reducing environmental impacts.