scholarly journals Quantifying methane emissions from rice fields in Tai-Lake region, China by coupling detailed soil database with biogeochemical model

2008 ◽  
Vol 5 (6) ◽  
pp. 4867-4896
Author(s):  
L. Zhang ◽  
D. Yu ◽  
X. Shi ◽  
L. Zhao ◽  
W. Ding ◽  
...  
Keyword(s):  
Paddy Rice ◽  
Rice Fields ◽  
Paddy Soils ◽  
Biogeochemical Model ◽  
Relative Deviation ◽  
Ch4 Flux ◽  
Ch4 Emissions ◽  
Soil Database ◽  
Lake Region ◽  
Tai Lake

Abstract. China's paddy rice accounts for about 22% of the world's rice fields, therefore it is crucial to accurately estimate the CH4 emissions at regional scale to gauge their contribution to global greenhouse gas effect. This paper reports an application of a biogeochemical model, DeNitrification and DeComposition or DNDC, for quantifying CH4 emissions from rice fields in Tai-Lake region of China by linking DNDC to a 1:50 000 soil database, which was derived from 1107 paddy soil profiles in the Second National Soil Survey of China in the 1980s–1990s. The modeled results estimate that the 2.34 M ha of paddy rice fields in Tai-Lake region emitted about CH4 of 5.67 Tg C for the period of 1982–2000, with the average CH4 flux ranged from 114 to 138 kg C ha−1y−1. The highest emission rate (659.24 kg C ha−1 y−1) occurred in the subgroup of "gleyed paddy soils", while the lowest (90.72 kg C ha−1y−1) were associated with the subgroup "degleyed paddy soils". The subgroup "hydromorphic paddy soils" accounted for about 52.82% of the total area of paddy soils, the largest of areas of all the soil subgroups, with the CH4 flux rate of 106.47 kg C ha−1y−1. On a sub-regional basis, the annual average CH4 flux in the Tai-Lake plain soil region and alluvial plain soil region was higher than that in low mountainous and hilly soil region and polder soil region. The model simulation was conducted with two databases using polygon or county as the basic unit. The county-based database contained soil information coarser than the polygon system built based on the 1:50 000 soil database. The modeled results with the two databases found similar spatial patterns CH4 emissions in Tai-Lake region. However, discrepancies exist between the results from the two methods, the relative deviation is −42.10% for the entire region, and the relative deviation ranged from −19.53% to 97.30% for most counties, which indicates that the more precise soil database was necessary to better simulate CH4 emissions from rice fields in Tai-Lake region using the DNDC model.

scholarly journals Quantifying methane emissions from rice fields in the Taihu Lake region, China by coupling a detailed soil database with biogeochemical model

2009 ◽  
Vol 6 (5) ◽  
pp. 739-749 ◽  
Author(s):  
L. Zhang ◽  
D. Yu ◽  
X. Shi ◽  
D. Weindorf ◽  
L. Zhao ◽  
...  
Keyword(s):  
Taihu Lake ◽  
Emission Rate ◽  
Rice Fields ◽  
Paddy Soils ◽  
Biogeochemical Model ◽  
Dndc Model ◽  
Ch4 Flux ◽  
Ch4 Emissions ◽  
Soil Database ◽  
Lake Region

Abstract. As China has approximately 22% of the world's rice paddies, the regional quantification of CH4 emissions from these paddies is important in determining their contribution to the global greenhouse gas effect. This paper reports the use of a biogeochemical model (DeNitrification and DeComposition or DNDC) for quantifying CH4 emissions from rice fields in the Taihu Lake region of China. For this application, the DNDC model was linked to a 1:50 000 soil database derived from 1107 paddy soil profiles compiled during the Second National Soil Survey of China in the 1980s–1990s. The simulated results showed that the 2.3 Mha of paddy rice fields in the Taihu Lake region emitted the equivalent of 5.7 Tg C from 1982–2000, with the average CH4 flux ranging from 114 to 138 kg C ha−1 y−1. As for soil subgroups, the highest emission rate (660 kg C ha−1 y−1) was linked to gleyed paddy soils accounting for about 4.4% of the total area of paddy soils. The lowest emission rate (91 kg C ha−1 y−1) was associated with degleyed paddy soils accounting for about 18% of the total area of paddy soils. The most common soil in the area was hydromorphic paddy soils, which accounted for about 53% of the total area of paddy soils with a CH4 flux of 106 kg C ha−1 y−1. On a regional basis, the annual averaged CH4 flux in the Taihu Lake plain soil region and alluvial plain soil region were higher than that in the low mountainous and hilly soil region and the polder soil region. The model simulation was conducted with two databases using polygons or counties as the basic units. The county-based database contained soil information coarser than the polygon system built based on the 1:50 000 soil database. The modeled results with the two databases found similar spatial patterns of CH4 emissions in the Taihu Lake region. However, discrepancies exist between the results from the two methods. The total CH4 emissions generated from the polygon-based database is 2.6 times the minimum CH4 emissions generated from the county-based database, and is 0.98 times the maximum CH4 emissions generated from the county-based database. The average value of the relative deviation ranged from −20% to 98% for most counties, which indicates that a more precise soil database is necessary to better simulate CH4 emissions from rice fields in the Taihu Lake region using the DNDC model.

Simulation of global warming potential (GWP) from rice fields in the Tai-Lake region, China by coupling 1:50,000 soil database with DNDC model

2009 ◽  
Vol 43 (17) ◽  
pp. 2737-2746 ◽  
Author(s):  
Liming Zhang ◽  
Dongsheng Yu ◽  
Xuezheng Shi ◽  
David C. Weindorf ◽  
Limin Zhao ◽  
...  
Keyword(s):  
Global Warming ◽  
Global Warming Potential ◽  
Rice Fields ◽  
Dndc Model ◽  
Soil Database ◽  
Lake Region ◽  
Tai Lake

scholarly journals How methane emission from rice paddy is affected by management practices and region?

2018 ◽  
Author(s):  
Jinyang Wang ◽  
Hiroko Akiyama ◽  
Kazuyuki Yagi ◽  
Xiaoyuan Yan
Keyword(s):  
Management Practices ◽  
Organic Amendment ◽  
Water Status ◽  
Regional Scale ◽  
Rice Fields ◽  
Ch4 Emission ◽  
Ch4 Flux ◽  
Ch4 Emissions ◽  
Flooded Rice ◽  
Previous Season

Abstract. Rice cultivation has long been known as one of the dominant anthropogenic contributors to methane (CH4) emissions, yet there is still uncertainty when estimating its emissions at the global/regional scale. An increasing number of rice field measurements have been conducted globally, which allow us to assess the major variables controlling CH4 emissions and develop the region- and country-specific emission factors (EFs). Results shown that the CH4 flux from rice fields were closely related to organic amendment, water regime during and before the rice-growing season, soil properties and climate. The average CH4 flux from fields with single and multiple drainages were 71 % and 55 % of that from continuously flooded rice fields. The CH4 flux from fields that were flooded in the previous season were 2.4 and 2.7 times that from fields previously drained for a short and long season. Contrary to the previously reported optimum soil pH of around neutrality, paddy soils with pH of 5.0–5.5 gave the maximum CH4 emission. Rice straw applied at 6 t ha−1 shortly before rice transplanting can increase CH4 emission by 3.2 times, while it increases CH4 emission by only 1.6 times when applied in the previous season. The default EF was estimated to 1.19 kg CH4 ha−1 d−1 with a 95 % confidence interval of 0.80 to 1.76 kg CH4 ha−1 d−1 for continuously flooded rice fields without organic amendment and with a preseason water status of short drainage. The default EFs at sub-regional and country levels were also estimated. We conclude that these default EFs and scaling factors can be used to develop national or regional emission inventories.

Nitrate vertical transport in the main paddy soils of Tai Lake region, China

Geoderma ◽  
2007 ◽  
Vol 142 (1-2) ◽  
pp. 136-141 ◽  
Author(s):  
Xiaomin Chen ◽  
Huashan Wu ◽  
Fei Wo
Keyword(s):  
Vertical Transport ◽  
Paddy Soils ◽  
Lake Region ◽  
Tai Lake

scholarly journals Effects of soil spatial resolution on quantifying CH4and N2O emissions from rice fields in the Tai Lake region of China by DNDC model

2011 ◽  
Vol 25 (2) ◽  
pp. n/a-n/a ◽  
Author(s):  
D. S. Yu ◽  
H. Yang ◽  
X. Z. Shi ◽  
E. D. Warner ◽  
L. M. Zhang ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Rice Fields ◽  
N2o Emissions ◽  
Dndc Model ◽  
Lake Region ◽  
Tai Lake

scholarly journals Controlling variables and emission factors of methane from global rice fields

2018 ◽  
Vol 18 (14) ◽  
pp. 10419-10431 ◽  
Author(s):  
Jinyang Wang ◽  
Hiroko Akiyama ◽  
Kazuyuki Yagi ◽  
Xiaoyuan Yan
Keyword(s):  
Water Status ◽  
Regional Scale ◽  
Organic Amendments ◽  
Emission Factors ◽  
Rice Fields ◽  
Mitigation Strategies ◽  
Ch4 Flux ◽  
Ch4 Emissions ◽  
Flooded Rice ◽  
Geographical Variations

Abstract. Rice cultivation has long been known as one of the dominant anthropogenic contributors to methane (CH4) emissions, yet there is still uncertainty when estimating its emissions at the global or regional scale. An increasing number of rice field measurements have been conducted globally, which allow us to reassess the major variables controlling CH4 emissions and develop region- and country-specific emission factors (EFs). The results of our statistical analysis show that the CH4 flux from rice fields was closely related to organic amendments, the water regime during and before the rice-growing season, soil properties and agroecological conditions. The average CH4 fluxes from fields with single and multiple drainage were 71 % and 55 % that of continuously flooded rice fields. The CH4 flux from fields that were flooded in the previous season were 2.4 and 2.7 times that of fields previously drained for a short and long season, respectively. Rice straw applied at 6 t ha−1 in the preseason can decrease CH4 emissions by half when compared to that applied shortly before rice transplanting. The global default EF was estimated to be 1.19 kg CH4 ha−1 day−1 with a 95 % confidence interval of 0.80 to 1.76 kg CH4 ha−1 day−1 for continuously flooded rice fields without organic amendment and with a preseason water status of short drainage. The lower EFs were found in countries from South Asia (0.85 kg CH4 ha−1 day−1) and North America (0.65 kg CH4 ha−1 day−1) relative to other regions, indicative of geographical variations at sub-regional and country levels. In conclusion, these findings can provide a sound basis for developing national inventories and mitigation strategies of CH4 emission from rice fields.

Emergence of Weeds in Paddy Rice Fields

1975 ◽  
Vol 20 (3) ◽  
pp. 109-113 ◽  
Author(s):  
Mitsuyoshi SUZUKI ◽  
Takahisa SUTO
Keyword(s):  
Paddy Rice ◽  
Rice Fields

scholarly journals Cloud Cover throughout All the Paddy Rice Fields in Guangdong, China: Impacts on Sentinel 2 MSI and Landsat 8 OLI Optical Observations

2021 ◽  
Vol 13 (15) ◽  
pp. 2961
Author(s):  
Rui Jiang ◽  
Arturo Sanchez-Azofeifa ◽  
Kati Laakso ◽  
Yan Xu ◽  
Zhiyan Zhou ◽  
...  
Keyword(s):  
Cloud Cover ◽  
Southern China ◽  
Vegetation Indices ◽  
Paddy Rice ◽  
Rice Fields ◽  
Optical Observations ◽  
Landsat 8 ◽  
Monthly Basis ◽  
Satellite Sensors ◽  
Sentinel 2

Cloud cover hinders the effective use of vegetation indices from optical satellite-acquired imagery in cloudy agricultural production areas, such as Guangdong, a subtropical province in southern China which supports two-season rice production. The number of cloud-free observations for the earth-orbiting optical satellite sensors must be determined to verify how much their observations are affected by clouds. This study determines the quantified wide-ranging impact of clouds on optical satellite observations by mapping the annual total observations (ATOs), annual cloud-free observations (ACFOs), monthly cloud-free observations (MCFOs) maps, and acquisition probability (AP) of ACFOs for the Sentinel 2 (2017–2019) and Landsat 8 (2014–2019) for all the paddy rice fields in Guangdong province (APRFG), China. The ATOs of Landsat 8 showed relatively stable observations compared to the Sentinel 2, and the per-field ACFOs of Sentinel 2 and Landsat 8 were unevenly distributed. The MCFOs varied on a monthly basis, but in general, the MCFOs were greater between August and December than between January and July. Additionally, the AP of usable ACFOs with 52.1% (Landsat 8) and 47.7% (Sentinel 2) indicated that these two satellite sensors provided markedly restricted observation capability for rice in the study area. Our findings are particularly important and useful in the tropics and subtropics, and the analysis has described cloud cover frequency and pervasiveness throughout different portions of the rice growing season, providing insight into how rice monitoring activities by using Sentinel 2 and Landsat 8 imagery in Guangdong would be impacted by cloud cover.

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