基于AVHRR遥感数据和气象观测数据,将地表能量平衡系统(surface energy balance system,SEBS)模型应用于赣江上游流域,在不同气象条件下对日蒸散发量进行估算。结果表明,SEBS模型对日蒸散发量的估算满足一定的精度,可以应用于此流域。...基于AVHRR遥感数据和气象观测数据,将地表能量平衡系统(surface energy balance system,SEBS)模型应用于赣江上游流域,在不同气象条件下对日蒸散发量进行估算。结果表明,SEBS模型对日蒸散发量的估算满足一定的精度,可以应用于此流域。通过遥感反演分析发现,赣江上游实际日蒸散发量受到净辐射、植被覆盖率、地表温度等因素的影响;反演参数与土地利用在空间上有良好的相关性和一致性,且在时间上有明显的年内分布规律。展开更多
This paper explores the methodology for compiling the torrent hazard and risk zonation map by means of GIS technique for the Red River Basin in Yunnan province of China, where is prone to torrent. Based on a 1：250,00...This paper explores the methodology for compiling the torrent hazard and risk zonation map by means of GIS technique for the Red River Basin in Yunnan province of China, where is prone to torrent. Based on a 1：250,000 scale digital map, six factors including slope angle, rainstorm days, buffer of river channels, maximum runoff discharge of standard area, debris flow distribution density and flood disaster history were analyzed and superimposed to create the torrent risk evaluation map. Population density, farmland percentage, house property, and GDP as indexes accounting for torrent hazards were analyzed in terms of vulnerability mapping. Torrent risk zonation by means of GIS was overlaid on the two data layers of hazard and vulnerability. Then each grid unit with a resolution of 500 m- 500 m was divided into four categories of the risk： extremely high, high, moderate and low. Finally the same level risk was combined into a confirmed zone, which represents torrent risk of the study area. The risk evaluation result in the upper Red River Basin shows that the extremely high risk area of 13,150 km^2 takes up 17.9% of the total inundated area, the high risk area of 33,783 km^2 is 45.9%, the moderate risk area of 18,563 km^2 is 25.2% and the low risk area of 8115 km^2 is 11.0%.展开更多
文摘基于AVHRR遥感数据和气象观测数据,将地表能量平衡系统(surface energy balance system,SEBS)模型应用于赣江上游流域,在不同气象条件下对日蒸散发量进行估算。结果表明,SEBS模型对日蒸散发量的估算满足一定的精度,可以应用于此流域。通过遥感反演分析发现,赣江上游实际日蒸散发量受到净辐射、植被覆盖率、地表温度等因素的影响;反演参数与土地利用在空间上有良好的相关性和一致性,且在时间上有明显的年内分布规律。
基金National Natural Science Foundation of China, No.40371018
文摘This paper explores the methodology for compiling the torrent hazard and risk zonation map by means of GIS technique for the Red River Basin in Yunnan province of China, where is prone to torrent. Based on a 1：250,000 scale digital map, six factors including slope angle, rainstorm days, buffer of river channels, maximum runoff discharge of standard area, debris flow distribution density and flood disaster history were analyzed and superimposed to create the torrent risk evaluation map. Population density, farmland percentage, house property, and GDP as indexes accounting for torrent hazards were analyzed in terms of vulnerability mapping. Torrent risk zonation by means of GIS was overlaid on the two data layers of hazard and vulnerability. Then each grid unit with a resolution of 500 m- 500 m was divided into four categories of the risk： extremely high, high, moderate and low. Finally the same level risk was combined into a confirmed zone, which represents torrent risk of the study area. The risk evaluation result in the upper Red River Basin shows that the extremely high risk area of 13,150 km^2 takes up 17.9% of the total inundated area, the high risk area of 33,783 km^2 is 45.9%, the moderate risk area of 18,563 km^2 is 25.2% and the low risk area of 8115 km^2 is 11.0%.
