Snow Monitoring And Early Warning Of Snow Disaster In Pastoral Area Of Qinghai Province

Seasonal snow cover has an important meaning for hydrological process and climate change. The dynamic change of snow cover area influences aquatic system, energy cycle, social economy and ecological system significantly. In addition, snowmelt is primary water source for arid and semiarid ecological system. Winter-spring snowfall is an important restrictive factor of animal husbandry development. Snow cover has some harmful effects, for example, burying forage, shortage of forage. Moreover, snow cover maybe cause snow disaster, because of freezing a large number of livestock to death in the pastoral area which have no or lack of forage storage. In this research, the study area is Qinghai, holding a large rangeland with 3647×104 ha and available pasture with 3161×104 ha, which made the pasture of Qinghai be one of the five six largest pastures in China. Snow disaster is the main natural hazards. In the period from October to April of the next year, because of the series snowfall and low temperature, heavy snow cover and freezing and starving of the livestock to death always happen in Yushu, Guoluo, the south part of Huangnan and Qilianshan, which make local herdsmen lost a lot property or even life.Snow cover area monitor and snow depth inversion have important implications for snow hazard monitor and evaluation in the pasture. In this study, the combination of MODIS daily images for snow product (with the resolution of 500m) and passive microwave images (AMSR-E SWE) which are not affected by clouds are combined into user-defined daily snow images with higher resolution firstly. Then, based on the passive microwave daily images (AMSR-E TB) and climate data, snow depth of Qinghai is inverted. Finally, using the combination of snow cover area and depth which is obtained in format researches, grazing capacity of the pasture and some other databases, the snow disast early warming and risk evaluation models were built. This study provided a scientifical basis for snow cover and snow disaster monitoring and estimation.The results of this study indicated that:1) As the study area of Qinghai Province, the cloud cover of the combined image (MOYD10A1) of the MODIS/Terra and MODIS/Aqua daily image for snow product is about 14 percent less than that of MOD10A1 image or MYD10A1 image. For all the climate, the classification accuracy of the user-defined images (MOYD10A1) is 43.7%, compared with that of MOD10A1 (43.5%) and that of MYD10A1 (27.7%). The snow classification accuracy of MA10A1, composited by MOYD10A and AMSR-E SWE, is 54.5%, and the land classification accuracy and overall classification accuracy is 89.2% and 85.5%, respectively.2) The factors which affect the snow depth inversion is analyzed base on the AMSR-E 18 and 36 GHz data during the snow seasons (October to March, from 2003 to 2008) and the sampling data (including snow depth and daily maximum temperature) of 43 meteorological stations. The result shows that the factors like snowmelt, large water body and especially deep frost layer influence the building of snow depth model seriously. According to the 639 pairs data excluding the unreasonable records, the snow depth inversion model (SD= 0.43(Tb18V-Tb36V)+ 2.06) was built based on the regressional analysis of various brightness temperature difference data and snow depth samples. Then the 104 pairs data (the snow depth is over 3cm) from October to March in 2002-2003 was used to evaluate the linear regression model. The result of this evaluation reveals that the obtained inversion model can be used to monitor snow depth of the study area Based on MODIS-EVI and aboveground biomass samples of August 2006 and August 2007 in the south part of Qinghai, the aboveground biomass inversion model (y= 297.15e4.9492x, R2=0.5626, N=396) was built. According to the aboveground biomass samples of 2008, average error of the model is 21.06%. Based on the key pasture theory, the aboveground biomass, total consuming forage, theoretical capacity, winter-spring pasture capacity and summer-autumn capacity of 14 counties are calculated and analylized through 2006 to 2008 in the southern pasture of Qinghai.4) Based on remote sensing, GIS, statistics of the study area and the results of chapter 2, chapter 3 and chapter 4, the relationship among snow cover, rangeland and livestock was analyzed. And the snow disaster warning grade index was put forward. Finally, the snow disaster warning model and the risk assessment model were built based on monitoring the anti-calamity ability of pasture and livestock.