The upper Huanghe(Yellow) River basin is situated in the northeast of the Qinghai Xizang(Tibet)Plateau of China. The melt water from the snow cover is main water supply for the rivers in the region during springtime a...The upper Huanghe(Yellow) River basin is situated in the northeast of the Qinghai Xizang(Tibet)Plateau of China. The melt water from the snow cover is main water supply for the rivers in the region during springtime and other arid regions of the northwestern China, and the hydrological conditions of the rivers are directly controlled by the snowmelt water in spring. So snowmelt runoff forecast has importance for hydropower, flood prevention and water resources utilization. The application of remote sensing and Geographic Information System (GIS) techniques in snow cover monitoring and snowmelt runoff calculation in the upper Huanghe River basin are introduced amply in this paper. The key parameter-snow cover area can be computed by satellite images from multi platform, multi temporal and multi spectral. A cluster of snow cover data can be yielded by means of the classification filter method. Meanwhile GIS will provide relevant information for obtaining the parameters and also for zoning. According to the typical samples extracting snow covered mountainous region, the snowmelt runoff calculation models in the upper Huanghe River basin are presented and they are mentioned in detail also. The runoff snowmelt models based on the snow cover data from NOAA images and observation data of runoff, precipitation and air temperature have been satisfactorily used for predicting the inflow to the Longyangxia Reservoir , which is located at lower end of snow cover region and is one of the largest reservoirs on the upper Huanghe River, during late March to early June. The result shows that remote sensing techniques combined with the ground meteorological and hydrological observation is of great potential in snowmelt runoff forecasting for a large river basin. With the development of remote sensing technique and the progress of the interpretation method, the forecast accuracy of snowmelt runoff will be improved in the near future. Large scale extent and few stations are two objective reality situations in China, so they should be considered in simulation and forecast. Apart from dividing, the derivation of snow cover area from satellite images would decide the results of calculating runoff. Field investigation for selection of the learning samples of different snow patterns is basis for the classification.展开更多
This paper proposes an applicable approach for snow information abstraction in northern Xinjiang Basin using MODIS data. Linear spectral mixture analysis （LSMA） was used to calculate snow cover fractions （SF） with...This paper proposes an applicable approach for snow information abstraction in northern Xinjiang Basin using MODIS data. Linear spectral mixture analysis （LSMA） was used to calculate snow cover fractions （SF） within a pixel, which was used to establish a regression function with NDSI. In addition, 80 snow depths samples were collected in the study region. The correlation between image spectra reflectance and snow depth as well as the comparison between measured snow spectra and image spectra was analyzed. An algorithm was developed for snow depth inversion on the basis of the correlation between snow depth and snow spectra in the region. The results indicated that the model of SF had a high accuracy with the mean absolute error 0.06 tested by 26 true measured values and the validation for snow depth model using another dataset with 50 sampling sites showed an RMSE of 1.63. Our study showed that MODIS data provide an alternative method for snow information abstraction through development of algorithms suitable for local application.展开更多
文摘The upper Huanghe(Yellow) River basin is situated in the northeast of the Qinghai Xizang(Tibet)Plateau of China. The melt water from the snow cover is main water supply for the rivers in the region during springtime and other arid regions of the northwestern China, and the hydrological conditions of the rivers are directly controlled by the snowmelt water in spring. So snowmelt runoff forecast has importance for hydropower, flood prevention and water resources utilization. The application of remote sensing and Geographic Information System (GIS) techniques in snow cover monitoring and snowmelt runoff calculation in the upper Huanghe River basin are introduced amply in this paper. The key parameter-snow cover area can be computed by satellite images from multi platform, multi temporal and multi spectral. A cluster of snow cover data can be yielded by means of the classification filter method. Meanwhile GIS will provide relevant information for obtaining the parameters and also for zoning. According to the typical samples extracting snow covered mountainous region, the snowmelt runoff calculation models in the upper Huanghe River basin are presented and they are mentioned in detail also. The runoff snowmelt models based on the snow cover data from NOAA images and observation data of runoff, precipitation and air temperature have been satisfactorily used for predicting the inflow to the Longyangxia Reservoir , which is located at lower end of snow cover region and is one of the largest reservoirs on the upper Huanghe River, during late March to early June. The result shows that remote sensing techniques combined with the ground meteorological and hydrological observation is of great potential in snowmelt runoff forecasting for a large river basin. With the development of remote sensing technique and the progress of the interpretation method, the forecast accuracy of snowmelt runoff will be improved in the near future. Large scale extent and few stations are two objective reality situations in China, so they should be considered in simulation and forecast. Apart from dividing, the derivation of snow cover area from satellite images would decide the results of calculating runoff. Field investigation for selection of the learning samples of different snow patterns is basis for the classification.
基金Supported by the National Natural Science Foundation of China （No.70361001）.
文摘This paper proposes an applicable approach for snow information abstraction in northern Xinjiang Basin using MODIS data. Linear spectral mixture analysis （LSMA） was used to calculate snow cover fractions （SF） within a pixel, which was used to establish a regression function with NDSI. In addition, 80 snow depths samples were collected in the study region. The correlation between image spectra reflectance and snow depth as well as the comparison between measured snow spectra and image spectra was analyzed. An algorithm was developed for snow depth inversion on the basis of the correlation between snow depth and snow spectra in the region. The results indicated that the model of SF had a high accuracy with the mean absolute error 0.06 tested by 26 true measured values and the validation for snow depth model using another dataset with 50 sampling sites showed an RMSE of 1.63. Our study showed that MODIS data provide an alternative method for snow information abstraction through development of algorithms suitable for local application.
