Estimates of methane and nitrous oxide emission from a rice field in Central Java, Indonesia, based on the DeNitrification DeComposition model

IF 0.5 Q4 AGRONOMY Sains Tanah Pub Date : 2022-01-28 DOI:10.20961/stjssa.v19i1.56928
Umi Munawaroh, K. Komariah, D. Ariyanto, M. Zaki, K. Noda
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Abstract

Indonesia is the world’s third largest rice producer, with most rice being cultivated (estimated 3.1 million ha) in Central Java. However, one of the environmental challenges in producing rice is greenhouse gas (GHG) emissions from rice fields. Therefore, understanding the GHG emissions (methane and nitrous oxide) from the rice farming system is important for better management practices. The objective of this study is to estimate the GHG emissions supported by a satellite database, namely, the DeNitrification DeComposition (DNDC) model, at three regencies at Central Java, Indonesia, Cilacap, Karanganyar, and Pati, as well as the factors determining the emissions. The DNDC model was obtained from https://www.dndc.sr.unh.edu, which consists of three main submodels that worked together in simulating N2O and N2 emissions: (1) the soil-climate/thermal-hydraulic flux submodel, (2) the decomposition submodel, and (3) the denitrification submodel. The results showed that the N2O emissions from rice farming in Karanganyar, Cilacap, and Pati were 19.0, 18.8, and 12.8 kg N ha−1 yr−1, respectively, while they were 213.7, 270.6, and 360.6 kg C ha−1 yr−1 for CH4 emissions, respectively. Consecutive dry or high precipitation, which resulted in cumulative depleted or elevated soil moisture, respectively, along with warmer temperature likely promoted higher methane and nitrous oxide. Experimental fields for validating the model in accordance with various agricultural practices are suggested for further study. Overall, the DNDC model has successfully estimated the CH4 and N2O emissions in Central Java when incorporated with various secondary climatic and land management big data resources.
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基于反硝化分解模型对印度尼西亚中爪哇稻田甲烷和一氧化二氮排放的估计
印度尼西亚是世界第三大水稻生产国,大部分水稻种植在中爪哇(估计310万公顷)。然而,水稻生产的环境挑战之一是稻田的温室气体排放。因此,了解水稻种植系统的温室气体排放(甲烷和一氧化二氮)对于更好的管理实践非常重要。本研究的目的是利用卫星数据库,即反硝化分解(DNDC)模型,估算中爪哇、印度尼西亚、奇拉贾普、卡兰甘雅和帕蒂三个县的温室气体排放量,以及影响排放量的因素。DNDC模型由三个主要子模型组成,它们共同模拟N2O和N2排放:(1)土壤-气候/热-水力通量子模型,(2)分解子模型和(3)反硝化子模型。结果表明,卡兰干雅尔、奇拉恰普和帕蒂稻作N2O排放量分别为19.0、18.8和12.8 kg N ha−1 yr−1,CH4排放量分别为213.7、270.6和360.6 kg C ha−1 yr−1。连续的干旱或高降水,分别导致土壤水分的累积枯竭或升高,加上温度升高,可能会促进甲烷和一氧化二氮的增加。建议在不同的农业实践条件下进行实验田的验证,以供进一步研究。总体而言,DNDC模型结合各种次生气候和土地管理大数据资源,成功估算了中爪哇地区的CH4和N2O排放量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Sains Tanah
Sains Tanah Environmental Science-Pollution
CiteScore
1.90
自引率
0.00%
发文量
16
审稿时长
8 weeks
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