[1] Large-scale assessments of the potential for food production and its impact on biogeochemical cycling require the best possible information on the distribution of cropland. This information can come from ground-based agricultural census data sets and/ or spaceborne remote sensing products, both with strengths and weaknesses. Official cropland statistics for China contain much information on the distribution of crop types, but are known to significantly underestimate total cropland areas and are generally at coarse spatial resolution. Remote sensing products can provide moderate to fine spatial resolution estimates of cropland location and extent, but supply little information on crop type or management. We combined county-scale agricultural census statistics on total cropland area and sown area of 17 major crops in 1990 with a fine-resolution land-cover map derived from 1995-1996 optical remote sensing (Landsat) data to generate 0.5°r esolution maps of the distribution of rice agriculture in mainland China. Agricultural census data were used to determine the fraction of crop area in each 0.5°grid cell that was in single rice and each of 10 different multicrop paddy rice rotations (e.g., winter wheat/ rice), while the remote sensing land-cover product was used to determine the spatial distribution and extent of total cropland in China. We estimate that there were 0.30 million km 2 of paddy rice cropland; 75% of this paddy land was multicropped, and 56% had two rice plantings per year. Total sown area for paddy rice was 0.47 million km 2 . Paddy rice agriculture occurred on 23% of all cultivated land in China.
[1] Since the early 1980s, water management of rice paddies in China has changed substantially, with midseason drainage gradually replacing continuous flooding. This has provided an opportunity to estimate how a management alternative impacts greenhouse gas emissions at a large regional scale. We integrated a process-based model, DNDC, with a GIS database of paddy area, soil properties, and management factors. We simulated soil carbon sequestration (or net CO 2 emission) and CH 4 and N 2 O emissions from China's rice paddies (30 million ha), based on 1990 climate and management conditions, with two water management scenarios: continuous flooding and midseason drainage. The results indicated that this change in water management has reduced aggregate CH 4 emissions about 40%, or 5 Tg CH 4 yr À1 , roughly 5-10% of total global methane emissions from rice paddies. The mitigating effect of midseason drainage on CH 4 flux was highly uneven across the country; the highest flux reductions (>200 kg CH 4 -C ha À1 yr À1 ) were in Hainan, Sichuan, Hubei, and Guangdong provinces, with warmer weather and multiple-cropping rice systems. The smallest flux reductions (<25 kg CH 4 -C ha À1 yr À1 ) occurred in Tianjin, Hebei, Ningxia, Liaoning, and Gansu Provinces, with relatively cool weather and single cropping systems. Shifting water management from continuous flooding to midseason drainage increased N 2 O emissions from Chinese rice paddies by 0.15 Tg N yr À1 ($50% increase). This offset a large fraction of the greenhouse gas radiative forcing benefit gained by the decrease in CH 4 emissions. Midseason drainage-induced N 2 O fluxes were high (>8.0 kg N/ha) in Jilin, Liaoning, Heilongjiang, and Xinjiang provinces, where the paddy soils contained relatively high organic matter. Shifting water management from continuous flooding to midseason drainage reduced total net CO 2 emissions by 0.65 Tg CO 2 -C yr À1 , which made a relatively small contribution to the net climate impact due to the low radiative potential of CO 2 . The change in water management had very different effects on net greenhouse gas mitigation when implemented across climatic zones, soil types, or cropping systems. Maximum CH 4 reductions and minimum N 2 O increases were obtained when the mid-season draining was applied to rice paddies with warm weather, high soil clay content, and low soil organic matter content, for example, Sichuan, Hubei, Hunan, Guangdong, Guangxi, Anhui, and Jiangsu provinces, which have 60% of China's rice paddies and produce 65% of China's rice harvest.
[1] Decreased methane emissions from paddy rice may have contributed to the decline in the rate of increase of global atmospheric methane (CH 4 ) concentration over the last 20 years. In China, midseason paddy drainage, which reduces growing season CH 4 fluxes, was first implemented in the early 1980s, and has gradually replaced continuous flooding in much of the paddy area. We constructed a regional prediction for China's rice paddy methane emissions using the DNDC biogeochemical model. Results of continuous flooding and midseason drainage simulations for all paddy fields in China were combined with regional scenarios for the timing of the transition from continuous flooding to predominantly mid-season drainage to generate estimates of total methane flux for 1980 -2000. CH 4 emissions from China's paddy fields were reduced over that period by $5 Tg CH 4 yr À1 .
Grassland biomass is essential for maintaining grassland ecosystems. Moreover, biomass is an important characteristic of grassland. In this study, we combined field sampling with remote sensing data and calculated five vegetation indices (VIs). Using this combined information, we quantified a remote sensing estimation model and estimated biomass in a temperate grassland of northern China. We also explored the dynamic spatio-temporal variation of biomass from 2006 to 2012. Our results indicated that all VIs investigated in the study were strongly correlated with biomass (α < 0.01). The precision of the model for estimating biomass based on ground data and remote sensing was greater than 73%. Additionally, the results of our analysis indicated that the annual average biomass was 11.86 million tons and that the average yield was 604.5 kg/ha. The distribution of biomass exhibited substantial spatial heterogeneity, and the biomass decreased from the eastern portion of the study area to the western portion. The highest coefficient of variation was found for the desert steppe, followed by the typical steppe and the meadow steppe.
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