• Title/Summary/Keyword: desert sand

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Vegetation on Basic, Alkaloid, Arid Land of the Whole Area of Baicheng City, Jilin Province, China (중국(中國) 길림성(吉林省) 백성시(白城市) 일대의 염성(鹽性), 알칼리성 건조지(乾操地) 식생(植生)에 관한 연구)

  • Ahn, Young-Hee;Wang, Bai-Cheng;Jin, Ying-Hua;Choe, Chang-Young;Xuan, Yong-Nan;Song, Dong-Ok
    • Korean Journal of Environment and Ecology
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    • v.23 no.1
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    • pp.90-98
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    • 2009
  • Every spring, Korea is always plagued by sandy dust from the western region of China and Mongolia. Yellow sand is causing an environmental problem to Japan and far into the American continent, let alone Korea. At present, the western region of China is going under desertification at a great speed due to climatic change and humans' damaging activities. To cope with this, each country including China is considering ecological restoration of deserts through planting. Accordingly, this research conducted a vegetation survey on Baicheng district which is a representative dry land of western China to obtain a basic data for ecological restoration of a desert. The survey revealed that Setaria viridis which invaded an arid land made a succession into Setaria viridis-Cannabis sativa var. fruderalis community together with Artemisia mongolica-Setaria viridis community due to the increase in salt concentration and alkalization subsequent to dryness. It was also found out that there finally formed Artemisia mongolica community on a flat intense in harsh wind and dryness with the continuous worsening of environmental conditions. There appeared a different type of vegetation on hilly districts where sporadic shade could come into being because the air humidity could be available relatively there. Frequently, typically appearing at the whole survey area, the Tributlus terrestris community was found to make succession into Tribulus terrestris-Cleisrogenes squarrosa community due to the aggravation of soil environment. In addition, with the worsening of the environment at hilly districts, there formed Clesirogenes squarrosa community resistant to dryness, salinity in soil and strong alkalinity. Further, there appeared higher plant life totalling to 62 taxa comprising 58 species and 4 varieties with 27 families and 49 genuses at the whole survey area. Among these, Compositae plants excellent in resistance to environment was surveyed the most, accounting for 27%.

The Character of Distribution of Solar Radiation in Mongolia based on Meteorological Satellite Data (위성자료를 이용한 몽골의 일사량 분포 특성)

  • Jee, Joon-Bum;Jeon, Sang-Hee;Choi, Young-Jean;Lee, Seung-Woo;Park, Young-San;Lee, Kyu-Tae
    • Journal of the Korean earth science society
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    • v.33 no.2
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    • pp.139-147
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    • 2012
  • Mongolia's solar-meteorological resources map has been developed using satellite data and reanalysis data. Solar radiation was calculated using solar radiation model, in which the input data were satellite data from SRTM, TERA, AQUA, AURA and MTSAT-1R satellites and the reanalysis data from NCEP/NCAR. The calculated results are validated by the DSWRF (Downward Short-Wave Radiation Flux) from NCEP/NCAR reanalysis. Mongolia is composed of mountainous region in the western area and desert or semi-arid region in middle and southern parts of the country. South-central area comprises inside the continent with a clear day and less rainfall, and irradiation is higher than other regions on the same latitude. The western mountain region is reached a lot of solar energy due to high elevation but the area is covered with snow (high albedo) throughout the year. The snow cover is a cause of false detection from the cloud detection algorithm of satellite data. Eventually clearness index and solar radiation are underestimated. And southern region has high total precipitable water and aerosol optical depth, but high solar radiation reaches the surface as it is located on the relatively lower latitude. When calculated solar radiation is validated by DSWRF from NCEP/NCAR reanalysis, monthly mean solar radiation is 547.59 MJ which is approximately 2.89 MJ higher than DSWRF. The correlation coefficient between calculation and reanalysis data is 0.99 and the RMSE (Root Mean Square Error) is 6.17 MJ. It turned out to be highest correlation (r=0.94) in October, and lowest correlation (r=0.62) in March considering the error of cloud detection with melting and yellow sand.