Rice is a water-guzzling crop cultivated mostly through inefficient irrigation methods which leads to low water use efficiency and many environmental problems. Additionally, the export of virtual water through rice trading and the looming water crisis poses significant threats to the sustainability of rice production and food security. There are several alternative rice production methods to improve water use efficiency. These include aerobic rice, direct-seeded rice (DSR), alternate wetting and drying (AWD), saturated soil culture (SSC), drip-irrigated rice, a system of rice intensification (SRI), and smart irrigation with sensors and the Internet of Things (IoT). However, each method has its own advantages and disadvantages. For example, drip-irrigated rice and IoT-based automated irrigation are not feasible for poor farmers due to the high production costs associated with specialized machinery and tools. Similarly, aerobic rice, drip-irrigated rice, and the SRI are labor-intensive, making them unsuitable for areas with a shortage of labor. On the other hand, DSR is suitable for labor-scarce areas, provided herbicides are used to control weeds. In this article, the suitability of different water-saving rice production methods is reviewed based on factors such as climate, soil type, labor, energy, and greenhouse gas emissions, and their prospects and challenges are evaluated. Additionally, the article examines how cultural practices, such as seed treatment, weed control, and nutrition management, contribute to enhancing water use efficiency in rice production.

Synthetic aperture radar (SAR) imagery, notably Sentinel-1A’s C-band, VV, and VH polarized SAR, has emerged as a crucial tool for mapping rice fields, especially in regions where cloud cover hinders optical imagery. Employing multi-temporal characteristics, SAR data were regularly collected and parameterized using MAPscape-Rice software, which integrates a fully automated processing chain to convert the data into terrain-geocoded σ° values. This facilitated the generation of rice area maps through a rule-based classifier approach, with classification accuracies ranging from 88.5 to 91.5 and 87.5 percent in 2017, 2018, and 2022, respectively. To estimate methane emissions, IPCC (37.13 kg/ha/season, 42.10 kg/ha/season, 43.19 kg/ha/season) and LST (36.05 kg/ha/season, 41.44 kg/ha/season, 38.07 kg/ha/season) factors were utilized in 2017, 2018 and 2022. Total methane emissions were recorded as 19.813 Gg, 20.661 Gg, and 25.72 Gg using IPCC and 19.155 Gg, 20.373 Gg, and 22.76 Gg using LST factors in 2017, 2018 and 2022. Overall accuracy in methane emission estimation, assessed against field observations, ranged from (IPCC) 85.71, 91.32, and 80.25 percent to (LST) 83.69, 91.43, and 84.69 percent for the years 2017, 2018 and 2022, respectively, confirming the efficacy of remote sensing in greenhouse gas monitoring and its potential for evaluating the impact of large-scale water management strategies on methane emissions and carbon credit-based ecosystem services at regional or national levels.

Field experiments were conducted during Rabi 2014, at Paddy Breeding Station, Tamil Nadu Agricultural University, Coimbatore to study the effect of pre-emergence / early post emergence herbicides along with hand weeding options on weed control in transplanted rice. The soil of the experimental field was clay loam in texture with pH 8.23. The performance of different pre-emergence application of butachlor 50% EC 1.5 kg a.i. ha-1, flucetosulfuron 10% WG in two doses at 20 g a.i ha-1 and 25 g a.i ha-1, pyrazosulfuron-ethyl 10% WB 75 g a.i ha-1, early post emergence application of penoxsulam + cyhalofop-butyl in two doses at 120 g a.i ha-1 and 135 g a.i. ha-1, bispyribac sodium 10% SC 35 g a.i ha-1 were evaluated along with pre-emergence application of pretilachlor 50% EC 1.0 kg a.i ha-1 + HW at 45 DAT, butachlor 50% EC 1.0 kg a.i ha-1 + HW at 45 DAT in comparison with hand weeding twice at 20 and 40 DAT, unweeded control and weed free check. The test variety used in this experiment was Co (R) 50. The experimental results revealed that weed free check had 100% weed control efficiency (WCE) in all the stages of crop growth. Among the various treatments tested, At 90 DAT, weed control efficiency (WCE) was maximum with early post emergence application of penoxsulam + cyhalofop-butyl135 g a.i. ha-1 (T5 ) recorded the maximum weed control efficiency of 85.78%. The number of productive tillers m-2 recorded ranged between 441 in T5 and 295 in unweeded control (T11). Grain yield ranged between 7717 kg ha-1 in weed free check (T12) and 5194 kg ha-1 in unweeded control (T11). The maximum straw yield of 9277 kg ha-1 was recorded in weed free check (T12). This was on par with early post emergence application of penoxsulam+ cyhalofop-butyl 135 g a.i. ha-1 (T5 ) and hand weeding twice at 20 and 40 DAT (T10) with 9206 kg ha-1 and 9019 kg ha-1.