Spatio-temporal variations of soil organic matter and nutrient losses resulted from wind erosion in northern China from 1980 to 2015
Received date: 2018-12-26
Request revised date: 2019-05-25
Online published: 2019-12-02
Copyright
The arid and semi-arid region in northern China is one of the major dust source areas and a major contributor to global dust emissions in the world. The area affected by wind erosion in China accounts for approximately 30% of the national territory, which is a primary contributor to atmospheric dust aerosols in East Asia and frequently transported over long distances to North Pacific Ocean, North America, and even Europe. Dust emissions resulted from wind erosion could generate a large amount of soil organic matter (SOM) and cause nutrient losses. Dust transportation and deposition processes of the wind erosion can redistribute the losses of SOM and nutrient, which can profoundly impact air quality, climate change, plant growth and productivity as well as ecosystem carbon (C) cycling and sequestration in China. However, how dust emissions affect SOM and nutrient losses in this region are poorly understood. In this paper, the WRF/Chem (Weather Research Forecasting model coupled with Chemistry) v3.7.1 atmospheric chemical transport model was adopted to simulate the spatio-temporal variations of dust emissions in northern China from 1980 to 2015. The spatio-temporal variations of losses of SOM, total nitrogen (TN), and total phosphorus (TP) resulted from wind erosion were calculated by the combination of simulated dust emissions and the spatial distribution of SOM, TN, and TP in the research region. Results showed that: (1) the annual dust emission was around 66.59 Tg (< 20 μm) over the past 40 years in northern China; (2) dust emissions showed large spatial and temporal disparities, and the dust source areas are mainly concentrated in regions such as eastern Xinjiang, the Badain Jaran Desert, and the Tengger Desert; (3) spatial patterns of SOM, TN, and TP losses were consistent with those of dust emission rates over the research region; (4) the annual losses of SOM, TN, and TP due to wind erosion are around 0.07 Tg, 0.004 Tg, and 0.005 Tg, respectively; (5) there were no obvious trends but large inter-annual fluctuations in dust emissions and the losses of SOM, TN, and TP resulted from wind erosion during 1980-2015 at the regional scale. Although numerous impacting factors can cause potential uncertainty in the estimation of SOM and nutrient losses by wind erosion, very little is known concerning the linkages between dust processes and the productivity and biogeochemical cycles of terrestrial ecosystems. Losses of SOM and nutrients by wind erosion should be included in projecting plant growth and ecosystem productivity, especially in dust storm-prone areas. It is critical to reduce the uncertainties in simulating regional biogeochemical cycling. This study is of great significance for the impacts of wind erosion on carbon cycle and nutrient cycling, as well as a deep understanding of the mechanism of land degradation in northern China.
ZHAO Haipeng , SONG Hongquan , LIU Pengfei , LI Xiaoyang , WANG Tuanhui . Spatio-temporal variations of soil organic matter and nutrient losses resulted from wind erosion in northern China from 1980 to 2015[J]. GEOGRAPHICAL RESEARCH, 2019 , 38(11) : 2778 -2789 . DOI: 10.11821/dlyj020181424
表1 模式参数化方案Tab. 1 Configurations of WRF/Chem options |
| 模型参数 | 参数设置 |
|---|---|
| 长波辐射模型 | RRTM长波辐射 |
| 短波辐射模型 | RRTM短波辐射 |
| 近地面层 | Revised MM5 MO |
| 微物理方案 | Morrison 2-mom |
| 陆面参数 | Noah LSM |
| 积云 | Multi-scale Kain-Fritsch |
| 边界层 | Noah LSM |
表2 WRF/Chem气象参数模拟结果评估Tab. 2 Evaluation of meteorological parameters simulated by WRF/Chem |
| 气象参数(单位) | 季节 | 平均观测值 | 平均模拟值 | MB | NMB(%) | NME(%) | RMSE | R |
|---|---|---|---|---|---|---|---|---|
| T2 (℃) | 冬季 | -0.8 | -1.9 | -1.1 | -0.5 | 2.6 | 3.5 | 0.9 |
| 春季 | 6.1 | 5.2 | -0.9 | -15.1 | 37.9 | 3.4 | 0.9 | |
| 夏季 | 21.9 | 21.7 | -0.2 | -0.1 | 8.9 | 3.3 | 0.9 | |
| 秋季 | 18.7 | 17.8 | -0.9 | -4.6 | 9.3 | 3.1 | 0.9 | |
| WSP10 (m/s) | 冬季 | 1.9 | 3.2 | 1.3 | 69.0 | 76.1 | 1.7 | 0.4 |
| 春季 | 2.5 | 3.5 | 1.0 | 43.0 | 51.1 | 1.5 | 0.5 | |
| 夏季 | 2.2 | 3.2 | 1.0 | 42.1 | 49.8 | 1.3 | 0.5 | |
| 秋季 | 1.9 | 2.9 | 1.0 | 49.4 | 56.4 | 1.3 | 0.5 | |
| WDR10(°) | 冬季 | 210.5 | 190.1 | -20.4 | -12.7 | 46.9 | 189.0 | 0.2 |
| 春季 | 206.4 | 185.2 | -21.3 | -13.4 | 47.3 | 165.2 | 0.2 | |
| 夏季 | 201.5 | 167.3 | -34.2 | -15.6 | 47.3 | 194.7 | 0.2 | |
| 秋季 | 211.4 | 172.7 | -38.7 | -16.3 | 48.6 | 192.7 | 0.2 | |
| PCP(mm/d) | 冬季 | 0.9 | 0.7 | -0.2 | -10.6 | 107.3 | 6.4 | 0.5 |
| 春季 | 2.8 | 2.4 | -0.4 | -17.2 | 97.8 | 9.5 | 0.4 | |
| 夏季 | 3.5 | 4.3 | 0.8 | 12.2 | 139.7 | 7.3 | 0.5 | |
| 秋季 | 1.8 | 2.1 | 0.3 | 7.2 | 123.6 | 8.5 | 0.3 |
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