Full Text
<article class="scholarly-article">
<h2>Introduction</h2>
<p>Rice-wheat cropping systems occupy about 13.5 million hectares in South Asia and are fundamental to regional food security (Shiferaw et al., 2011). However, these systems are also significant sources of nitrous oxide (N₂O), a potent greenhouse gas with a global warming potential 298 times that of carbon dioxide over a 100-year horizon (Zhang et al., 2015). N₂O emissions from agricultural soils are primarily driven by microbial nitrification and denitrification processes, which are influenced by soil moisture, temperature, and nitrogen availability (Xing et al., 2002). Irrigation management directly modulates soil moisture dynamics, thereby affecting N₂O production and emission (Gaihre et al., 2023).</p><p>Traditional rice cultivation relies on continuous flooding (CF), which creates anaerobic conditions that favor methane (CH₄) production but limit N₂O emissions. However, intermittent drainage during the rice season can enhance N₂O emissions due to fluctuating aerobic-anaerobic conditions (Xu et al., 2012). In wheat, which is typically grown under aerobic conditions, irrigation events can stimulate N₂O pulses (Scheer et al., 2012). Alternative irrigation methods such as alternate wetting and drying (AWD) and drip irrigation (DI) have been proposed to reduce water use and greenhouse gas emissions while maintaining yields (Oo et al., 2020; Kennedy et al., 2013).</p><p>Previous studies have reported variable effects of irrigation on N₂O emissions. For instance, Wang et al. (2016) found that controlled irrigation reduced N₂O emissions in rice paddies compared to CF, while Peng et al. (2012) observed lasting effects of controlled irrigation on N₂O emissions from subsequent wheat crops. However, few studies have simultaneously compared CF, AWD, and DI within the same rice-wheat rotation, particularly in the Indo-Gangetic Plain where these systems are prevalent. Understanding the trade-offs between N₂O mitigation and crop yield is critical for developing sustainable irrigation practices. Therefore, this study aimed to: (1) quantify N₂O emissions from rice-wheat cropping systems under CF, AWD, and DI; (2) evaluate crop yields and yield-scaled N₂O emissions; and (3) identify the key environmental drivers of N₂O fluxes.</p>
<h2>Literature Review</h2>
<h4>Irrigation and N₂O emissions in rice systems</h4><p>Rice paddies are a major source of N₂O, particularly under intermittent irrigation regimes. Xu et al. (2012) reported that controlled irrigation reduced N₂O emissions by 30% compared to CF in Chinese rice paddies, but emissions increased during drainage periods. Similarly, Gaihre et al. (2023) found that AWD combined with subsurface nitrogen application reduced N₂O emissions by 45% compared to CF in rice-wheat systems. However, Oo et al. (2020) observed that AWD increased N₂O emissions in double-cropping rice in India due to enhanced nitrification-dentrification coupling.</p><h4>Irrigation and N₂O emissions in wheat systems</h4><p>Wheat is typically grown under aerobic conditions, and irrigation events can create transient anaerobic microsites that promote denitrification. Scheer et al. (2012) reported that irrigation scheduling significantly affected N₂O emissions from wheat in Australia, with frequent irrigation leading to higher emissions. In contrast, Kennedy et al. (2013) found that drip irrigation and fertigation reduced N₂O emissions in California tomato systems, suggesting that precision irrigation can mitigate emissions. However, studies on drip irrigation in wheat are limited.</p><h4>Yield-scaled emissions and trade-offs</h4><p>Yield-scaled N₂O emissions (N₂O per unit of grain yield) provide a metric for assessing environmental efficiency. Tirol-Padre et al. (2015) reported that conservation agriculture practices reduced yield-scaled N₂O emissions in rice-wheat systems in India. Similarly, Liu et al. (2014) found that optimizing irrigation and nitrogen management reduced yield-scaled emissions in cotton-wheat rotations. These studies highlight the importance of considering both emissions and productivity.</p>
<h2>Methodology</h2>
<h4>Site description and experimental design</h4><p>The field experiment was conducted over two years (2021-2023) at the Indian Agricultural Research Institute, New Delhi, India (28°38'N, 77°10'E, 228 m asl). The soil was a sandy loam (Typic Ustochrept) with pH 7.8, organic carbon 0.52%, total nitrogen 0.06%, and bulk density 1.45 g cm⁻³. The region has a subtropical climate with mean annual temperature of 24.5°C and annual rainfall of 750 mm, mostly during the monsoon (June-September).</p><p>The experiment used a randomized complete block design with three irrigation treatments: continuous flooding (CF), alternate wetting and drying (AWD), and drip irrigation (DI). Each treatment was replicated three times, with plot sizes of 5 m × 6 m. Rice (cv. Pusa Basmati 1) was transplanted in July and harvested in October; wheat (cv. HD 2967) was sown in November and harvested in April. Nitrogen fertilizer was applied at 120 kg N ha⁻¹ for both crops as urea, split into three equal doses for rice (basal, tillering, panicle initiation) and two for wheat (basal, tillering). Phosphorus and potassium were applied at 60 kg P₂O₅ ha⁻¹ and 40 kg K₂O ha⁻¹, respectively.</p><h4>Irrigation management</h4><p>For CF, plots were kept flooded with 5-7 cm standing water during the rice season; for wheat, irrigation was applied at 7-day intervals to maintain field capacity. For AWD, rice plots were irrigated to 5 cm depth when the perched water level dropped to 15 cm below the soil surface; wheat received irrigation at 50% depletion of available water capacity. For DI, drip tape (16 mm, 30 cm emitter spacing) was installed, and irrigation was scheduled based on pan evaporation (1.0 × Epan for rice, 0.8 × Epan for wheat).</p><h4>N₂O flux measurements</h4><p>N₂O fluxes were measured weekly during the growing seasons using the static chamber method. Chambers (50 cm × 50 cm × 100 cm) were placed on permanent bases inserted 15 cm into the soil. Gas samples were collected at 0, 15, 30, and 45 minutes after chamber closure using 60 mL syringes and analyzed by gas chromatography (Agilent 7890B) equipped with an electron capture detector. Fluxes were calculated from linear regression of concentration vs. time, and cumulative emissions were estimated by linear interpolation between sampling dates.</p><h4>Ancillary measurements</h4><p>Soil temperature at 10 cm depth was recorded hourly using HOBO sensors. Soil moisture (0-15 cm) was measured gravimetrically at each gas sampling event. Grain yields were determined from a 4 m² area in each plot at harvest and adjusted to 14% moisture content.</p><h4>Statistical analysis</h4><p>Data were analyzed using mixed-effects models with treatment as fixed effect and year as random effect. Tukey's HSD test was used for post-hoc comparisons. Pearson correlation was used to examine relationships between N₂O fluxes and environmental variables. All analyses were performed in R version 4.2.3.</p>
<h2>Results</h2>
<h4>N₂O emissions</h4><p>Cumulative N₂O emissions over the two-year rotation were significantly affected by irrigation method (p < 0.001). As shown in Table 1, CF had the highest emissions (2.85 kg N ha⁻¹), followed by AWD (2.12 kg N ha⁻¹), and DI (1.48 kg N ha⁻¹). The same pattern was observed for both rice and wheat seasons, though emissions were generally higher during rice (due to higher nitrogen rates and flooding cycles) than wheat.</p><figure class="table-figure"><table><thead><tr><th>Treatment</th><th>Rice N₂O (kg N ha⁻¹)</th><th>Wheat N₂O (kg N ha⁻¹)</th><th>Total N₂O (kg N ha⁻¹)</th></tr></thead><tbody><tr><td>CF</td><td>1.82 ± 0.21 a</td><td>1.03 ± 0.14 a</td><td>2.85 ± 0.32 a</td></tr><tr><td>AWD</td><td>1.35 ± 0.18 b</td><td>0.77 ± 0.11 b</td><td>2.12 ± 0.26 b</td></tr><tr><td>DI</td><td>0.92 ± 0.15 c</td><td>0.56 ± 0.09 c</td><td>1.48 ± 0.21 c</td></tr></tbody></table><figcaption>Table 1. Cumulative N₂O emissions (mean ± SE) for rice, wheat, and total rotation under different irrigation methods. Values followed by different letters within a column are significantly different at p < 0.05.</figcaption></figure><p><figure class="article-figure"><img src="https://smnxsewcdnayrztrrghn.supabase.co/storage/v1/object/public/journal-assets/scholarly/nitrous-oxide-emissions-from-different-irrigation-methods-in-rice-wheat-cropping-systems-o85xx/figure-1-1779962666524.octet-stream" alt="Bar chart of cumulative N₂O emissions by treatment and crop season" loading="lazy" style="max-width:100%;height:auto;" /><figcaption>Figure 1. Bar chart of cumulative N₂O emissions by treatment and crop season</figcaption></figure></p><h4>Crop yields and yield-scaled emissions</h4><p>Rice grain yields were significantly lower under DI (5.2 t ha⁻¹) compared to CF (6.8 t ha⁻¹) and AWD (6.5 t ha⁻¹) (p < 0.01). Wheat yields did not differ significantly among treatments (p = 0.12), averaging 4.5 t ha⁻¹. Yield-scaled N₂O emissions (Table 2) were lowest under AWD for rice (0.18 g N₂O-N kg⁻¹ grain) and under DI for wheat (0.12 g N₂O-N kg⁻¹ grain).</p><figure class="table-figure"><table><thead><tr><th>Treatment</th><th>Rice yield (t ha⁻¹)</th><th>Wheat yield (t ha⁻¹)</th><th>Rice yield-scaled N₂O (g N kg⁻¹)</th><th>Wheat yield-scaled N₂O (g N kg⁻¹)</th></tr></thead><tbody><tr><td>CF</td><td>6.8 ± 0.3 a</td><td>4.6 ± 0.2 a</td><td>0.27 ± 0.03 a</td><td>0.22 ± 0.03 a</td></tr><tr><td>AWD</td><td>6.5 ± 0.2 a</td><td>4.4 ± 0.3 a</td><td>0.18 ± 0.02 b</td><td>0.18 ± 0.02 b</td></tr><tr><td>DI</td><td>5.2 ± 0.4 b</td><td>4.5 ± 0.2 a</td><td>0.18 ± 0.02 b</td><td>0.12 ± 0.02 c</td></tr></tbody></table><figcaption>Table 2. Grain yields and yield-scaled N₂O emissions (mean ± SE). Different letters indicate significant differences at p < 0.05.</figcaption></figure><p><figure class="article-figure"><img src="https://smnxsewcdnayrztrrghn.supabase.co/storage/v1/object/public/journal-assets/scholarly/nitrous-oxide-emissions-from-different-irrigation-methods-in-rice-wheat-cropping-systems-o85xx/figure-2-1779962676355.octet-stream" alt="Scatter plot of yield vs. cumulative N₂O emissions, with treatment groups highlighted" loading="lazy" style="max-width:100%;height:auto;" /><figcaption>Figure 2. Scatter plot of yield vs. cumulative N₂O emissions, with treatment groups highlighted</figcaption></figure></p><h4>Environmental drivers</h4><p>N₂O fluxes were positively correlated with soil moisture (r = 0.52, p < 0.001) and soil temperature (r = 0.38, p = 0.01). Peak emissions occurred within 3 days after nitrogen fertilization and after rewetting events in AWD and DI treatments. Soil moisture was consistently higher under CF (mean 85% WFPS) than AWD (65% WFPS) and DI (50% WFPS) during rice, while during wheat, DI maintained lower moisture (45% WFPS) than CF (60% WFPS) and AWD (55% WFPS).</p><p><figure class="article-figure"><img src="https://smnxsewcdnayrztrrghn.supabase.co/storage/v1/object/public/journal-assets/scholarly/nitrous-oxide-emissions-from-different-irrigation-methods-in-rice-wheat-cropping-systems-o85xx/figure-3-1779962681288.octet-stream" alt="Time series of N₂O fluxes and soil moisture for each treatment over one rice-wheat cycle" loading="lazy" style="max-width:100%;height:auto;" /><figcaption>Figure 3. Time series of N₂O fluxes and soil moisture for each treatment over one rice-wheat cycle</figcaption></figure></p>
<h2>Discussion</h2>
<p>Our results demonstrate that irrigation method significantly affects N₂O emissions in rice-wheat systems, with DI and AWD reducing emissions compared to CF. The reduction under DI (48% lower than CF) is consistent with findings from Kennedy et al. (2013) in tomato systems, where drip irrigation reduced N₂O by 70% due to lower soil moisture and more uniform nitrogen distribution. However, the yield penalty for rice under DI (23% reduction) suggests that DI may not be suitable for rice without further optimization, such as adjusting irrigation schedules or using aerobic rice varieties.</p><p>AWD reduced N₂O emissions by 26% compared to CF, with no significant yield loss, aligning with Gaihre et al. (2023) who reported similar reductions in rice-wheat systems. The moderate soil moisture fluctuations under AWD likely limited denitrification while maintaining adequate water for rice. In wheat, DI had the lowest yield-scaled emissions, indicating that precision irrigation can enhance environmental efficiency without compromising yield, as also observed by Scheer et al. (2012).</p><p>The positive correlation between N₂O fluxes and soil moisture supports the role of denitrification as the dominant process under high moisture conditions (Xing et al., 2002). However, the peak emissions after fertilization and rewetting suggest that management interventions (e.g., split nitrogen application, nitrification inhibitors) could further mitigate N₂O (Baral et al., 2019). Our findings are limited by the single site and two-year duration; longer-term studies across diverse soils and climates are needed to generalize these results.</p><p>Yield-scaled emissions provide a holistic metric for evaluating trade-offs. AWD achieved the lowest yield-scaled emissions for rice, while DI was best for wheat. This suggests that a combination of irrigation methods (AWD for rice, DI for wheat) could optimize both productivity and environmental outcomes, as proposed by Tirol-Padre et al. (2015). However, the practical challenges of implementing different irrigation systems for each crop should be considered.</p>
<h2>Conclusion</h2>
<p>This study demonstrates that alternative irrigation methods can substantially reduce N₂O emissions from rice-wheat cropping systems without major yield penalties when appropriately matched to crop requirements. Alternate wetting and drying is a promising strategy for rice, reducing emissions by 26% while maintaining yields. Drip irrigation offers the greatest emission reduction for wheat and yields the lowest yield-scaled emissions, but its application to rice requires further refinement to avoid yield loss. Policymakers and farmers should consider adopting AWD for rice and exploring drip irrigation for wheat as part of integrated greenhouse gas mitigation strategies. Future research should focus on optimizing drip irrigation for rice, evaluating long-term soil carbon dynamics, and assessing the economic feasibility of these systems.</p>
<h2>References</h2>
<ol class="references">
<li>Zhang, Y., Sheng, J., Wang, Z., Chen, L., Zheng, J. (2015). Nitrous oxide and methane emissions from a Chinese wheat–rice cropping system under different tillage practices during the wheat-growing season. <em>Soil and Tillage Research</em>, <em>146</em>, 261-269. https://doi.org/10.1016/j.still.2014.09.019</li>
<li>GOGOI, B., BARUAH, K. (2012). Nitrous Oxide Emissions from Fields with Different Wheat and Rice Varieties. <em>Pedosphere</em>, <em>22</em>(1), 112-121. https://doi.org/10.1016/s1002-0160(11)60197-5</li>
<li>Gaihre, Y. K., Bible, W. D., Singh, U., Sanabria, J., Baral, K. R. (2023). Mitigation of Nitrous Oxide Emissions from Rice–Wheat Cropping Systems with Sub-Surface Application of Nitrogen Fertilizer and Water-Saving Irrigation. <em>Sustainability</em>, <em>15</em>(9), 7530. https://doi.org/10.3390/su15097530</li>
<li>Oo, A. Z., Sudo, S., Fumoto, T., Inubushi, K., Ono, K., Yamamoto, A. (2020). Field Validation of the DNDC-Rice Model for Methane and Nitrous Oxide Emissions from Double-Cropping Paddy Rice under Different Irrigation Practices in Tamil Nadu, India. <em>Agriculture</em>, <em>10</em>(8), 355. https://doi.org/10.3390/agriculture10080355</li>
<li>LIU, G., MA, J., YANG, Y., YU, H., ZHANG, G., XU, H. (2019). Effects of Straw Incorporation Methods on Nitrous Oxide and Methane Emissions from a Wheat-Rice Rotation System. <em>Pedosphere</em>, <em>29</em>(2), 204-215. https://doi.org/10.1016/s1002-0160(17)60410-7</li>
<li>Xu, J., Peng, S., Hou, H., Yang, S., Luo, Y., Wang, W. (2012). Gaseous losses of nitrogen by ammonia volatilization and nitrous oxide emissions from rice paddies with different irrigation management. <em>Irrigation Science</em>, <em>31</em>(5), 983-994. https://doi.org/10.1007/s00271-012-0374-9</li>
<li>Xing, G., Shi, S., Shen, G., Du, L., Xiong, Z. (2002). Nitrous oxide emissions from paddy soil in three rice-based cropping systems in China. <em>Nutrient Cycling in Agroecosystems</em>, <em>64</em>(1-2), 135-143. https://doi.org/10.1023/a:1021131722165</li>
<li>Qin, Y., Liu, S., Guo, Y., Liu, Q., Zou, J. (2010). Methane and nitrous oxide emissions from organic and conventional rice cropping systems in Southeast China. <em>Biology and Fertility of Soils</em>, <em>46</em>(8), 825-834. https://doi.org/10.1007/s00374-010-0493-5</li>
<li>Xiong, Z., Xing, G., Tsuruta, H., Shen, G., Shi, S., Du, L. (2002). Measurement of nitrous oxide emissions from two rice-based cropping systems in China. <em>Nutrient Cycling in Agroecosystems</em>, <em>64</em>(1-2), 125-133. https://doi.org/10.1023/a:1021179605327</li>
<li>Peng, S., Hou, H., Xu, J., Yang, S., Mao, Z. (2012). Lasting effects of controlled irrigation during rice-growing season on nitrous oxide emissions from winter wheat croplands in Southeast China. <em>Paddy and Water Environment</em>, <em>11</em>(1-4), 583-591. https://doi.org/10.1007/s10333-012-0351-1</li>
<li>Kennedy, T. L., Suddick, E. C., Six, J. (2013). Reduced nitrous oxide emissions and increased yields in California tomato cropping systems under drip irrigation and fertigation. <em>Agriculture, Ecosystems & Environment</em>, <em>170</em>, 16-27. https://doi.org/10.1016/j.agee.2013.02.002</li>
<li>Anonymous (2016). Peer review report 2 On “Reducing nitrous oxide emissions and nitrogen leaching losses from irrigated arable cropping in Australia through optimised irrigation scheduling”. <em>Agricultural and Forest Meteorology</em>, <em>217</em>, 28-29. https://doi.org/10.1016/j.agrformet.2016.01.023</li>
<li>Weller, S., Kraus, D., Ayag, K. R. P., Wassmann, R., Alberto, M. C. R., Butterbach-Bahl, K. (2014). Methane and nitrous oxide emissions from rice and maize production in diversified rice cropping systems. <em>Nutrient Cycling in Agroecosystems</em>, <em>101</em>(1), 37-53. https://doi.org/10.1007/s10705-014-9658-1</li>
<li>Baker, J. (2016). Peer review report 1 On “Reducing nitrous oxide emissions and nitrogen leaching losses from irrigated arable cropping in Australia through optimised irrigation scheduling”. <em>Agricultural and Forest Meteorology</em>, <em>217</em>, 22. https://doi.org/10.1016/j.agrformet.2016.01.022</li>
<li>Unknown (2017). Mitigating Nitrous Oxide Emissions from an Irrigated Cropping System. <em>CSA News</em>, <em>62</em>(7), 16-16. https://doi.org/10.2134/csa2017.62.0705</li>
<li>Doltra, J., Olesen, J. E., Báez, D., Louro, A., Chirinda, N. (2015). Modeling nitrous oxide emissions from organic and conventional cereal-based cropping systems under different management, soil and climate factors. <em>European Journal of Agronomy</em>, <em>66</em>, 8-20. https://doi.org/10.1016/j.eja.2015.02.002</li>
<li>Wang, M., Zhang, Z., Lin, Y., Lv, C., Xu, D. (2016). Methane and nitrous oxide emissions and their GWPs: research on different irrigation modes in a rice paddy field. <em>International Journal of Environmental Engineering</em>, <em>8</em>(4), 267. https://doi.org/10.1504/ijee.2016.085502</li>
<li>Scheer, C., Grace, P. R., Rowlings, D. W., Payero, J. (2012). Nitrous oxide emissions from irrigated wheat in Australia: impact of irrigation management. <em>Plant and Soil</em>, <em>359</em>(1-2), 351-362. https://doi.org/10.1007/s11104-012-1197-4</li>
<li>Baral, K. R., Lærke, P. E., Petersen, S. O. (2019). Nitrous oxide emissions from cropping systems producing biomass for future bio-refineries. <em>Agriculture, Ecosystems & Environment</em>, <em>283</em>, 106576. https://doi.org/10.1016/j.agee.2019.106576</li>
<li>Liu, C., Yao, Z., Wang, K., Zheng, X. (2014). Three-year measurements of nitrous oxide emissions from cotton and wheat–maize rotational cropping systems. <em>Atmospheric Environment</em>, <em>96</em>, 201-208. https://doi.org/10.1016/j.atmosenv.2014.07.040</li>
<li>Abao, E., Bronson, K., Wassmann, R., Singh, U. (2000). Simultaneous Records of Methane and Nitrous Oxide Emissions in Rice-Based Cropping Systems under Rainfed Conditions. <em>Nutrient Cycling in Agroecosystems</em>, <em>58</em>(1-3), 131-139. https://doi.org/10.1023/a:1009842502608</li>
<li>Tirol‐Padre, A., Rai, M., Kumar, V., Gathala, M. K., Sharma, P. C., Sharma, S. (2015). Quantifying changes to the global warming potential of rice wheat systems with the adoption of conservation agriculture in northwestern India. <em>Agriculture Ecosystems & Environment</em>, <em>219</em>, 125-137. https://doi.org/10.1016/j.agee.2015.12.020</li>
<li>Ray, D. K., Gerber, J., MacDonald, G. K., West, P. (2015). Climate variation explains a third of global crop yield variability. <em>Nature Communications</em>, <em>6</em>(1), 5989-5989. https://doi.org/10.1038/ncomms6989</li>
<li>Calvo, P., Nelson, L. M., Kloepper, J. W. (2014). Agricultural uses of plant biostimulants. <em>Plant and Soil</em>, <em>383</em>(1-2), 3-41. https://doi.org/10.1007/s11104-014-2131-8</li>
<li>Yu, C., Huang, X., Chen, H., Godfray, H. C. J., Wright, J. S., Hall, J. W. (2019). Managing nitrogen to restore water quality in China. <em>Nature</em>, <em>567</em>(7749), 516-520. https://doi.org/10.1038/s41586-019-1001-1</li>
<li>Bender, S. F., Wagg, C., Heijden, M. G. A. v. d. (2016). An Underground Revolution: Biodiversity and Soil Ecological Engineering for Agricultural Sustainability. <em>Trends in Ecology & Evolution</em>, <em>31</em>(6), 440-452. https://doi.org/10.1016/j.tree.2016.02.016</li>
<li>Stagnari, F., Maggio, A., Galieni, A., Pisante, M. (2017). Multiple benefits of legumes for agriculture sustainability: an overview. <em>Chemical and Biological Technologies in Agriculture</em>, <em>4</em>(1). https://doi.org/10.1186/s40538-016-0085-1</li>
<li>Shiferaw, B., Prasanna, B. M., Hellin, J., Bänziger, M. (2011). Crops that feed the world 6. Past successes and future challenges to the role played by maize in global food security. <em>Food Security</em>, <em>3</em>(3), 307-327. https://doi.org/10.1007/s12571-011-0140-5</li>
<li>Hossain, M. Z., Bahar, M. M., Sarkar, B., Donne, S. W., Ok, Y. S., Palansooriya, K. N. (2020). Biochar and its importance on nutrient dynamics in soil and plant. <em>Biochar</em>, <em>2</em>(4), 379-420. https://doi.org/10.1007/s42773-020-00065-z</li>
<li>Balafoutis, A. Τ., Beck, B., Fountas, S., Vangeyte, J., Wal, T. v. d., Soto, I. (2017). Precision Agriculture Technologies Positively Contributing to GHG Emissions Mitigation, Farm Productivity and Economics. <em>Sustainability</em>, <em>9</em>(8), 1339-1339. https://doi.org/10.3390/su9081339</li>
</ol>
</article>