确定的概率的风险评价(PRA ) 使用概率论一个事件的出现的概率。在这研究， PRA 为过量氮(N) 的分泌物被进行从一农业(Jiulong 河) 在东南中国的分水岭。用差错树分析， PRA 的一种类型， N 在一个流量事件期间解除进河的过量的出现的...确定的概率的风险评价(PRA ) 使用概率论一个事件的出现的概率。在这研究， PRA 为过量氮(N) 的分泌物被进行从一农业(Jiulong 河) 在东南中国的分水岭。用差错树分析， PRA 的一种类型， N 在一个流量事件期间解除进河的过量的出现的概率被评估品质上和份量上。土地利用地图，土壤图，化肥使用记录，和专家意见被用来在差错树以内决定单个事件的可能性并且推测过量 N 的全面概率在一个流量事件期间排出。质的分析证明过量 N 分泌物的风险在分水岭主要与庄稼和家畜惯例有关。耕种，化肥，和粪肥的合适的管理是必要的控制 N 版本。量的评价结果显示那种选择练习沿着 Jiulong 河包括授精，在猪农场附近的植物的长带缓冲区的安装，和更河边的缓冲区的安装的减小能减少 N 的可能性通过流量的分泌物。展开更多
Flash flood is a dangers natural disaster causes lots of structure damage, traffic collapse, economic defects and human life loss. An efficient way to reduce its effects is preparing flash flood mapping to identify zo...Flash flood is a dangers natural disaster causes lots of structure damage, traffic collapse, economic defects and human life loss. An efficient way to reduce its effects is preparing flash flood mapping to identify zones at risk due to flood. Flash flood mapping is a powerful tool for urban planners, traffic and infrastructure engineers, emergency and rescue services. This article proposes an approach utilizes remote sensing (RS) and geographic information system (GIS) to prepare flood risk code (FRC) map for Jeddah city, Saudi Arabia. The proposed approach applied the Curve Number (CN) method of flood modelling and uses runoff depth, land use, soil hydrological parameters, surface slope, and longest flow path to generate FRC. SPOT satellite image of the study area was classified to generate land use map, Digital Elevation Model (DEM) was used for generating slope map and for hydrology analysis using HEC-GeoHMS tool, and soil properties were generated from scanned soil maps. All data were integrated in ArcGIS 10.4.1 to prepare the final flood risk map. The results show that a precipitation of 106.3 mm will generate 136.5 million m3 of flood water. The results according to the developed flood risk code show that due to this amount of precipitation, about 1 million people live in Jeddah are prone to extreme flood risk and about 2 million of population are at major risk, the rest of population (about 0.5 million) are vulnerable to moderate to minor fold risk. The approach was verified using ground truth data and proofed precision.展开更多
基金the Department of Science and Technology of Fujian Province,China (No.2002H009).
文摘确定的概率的风险评价(PRA ) 使用概率论一个事件的出现的概率。在这研究， PRA 为过量氮(N) 的分泌物被进行从一农业(Jiulong 河) 在东南中国的分水岭。用差错树分析， PRA 的一种类型， N 在一个流量事件期间解除进河的过量的出现的概率被评估品质上和份量上。土地利用地图，土壤图，化肥使用记录，和专家意见被用来在差错树以内决定单个事件的可能性并且推测过量 N 的全面概率在一个流量事件期间排出。质的分析证明过量 N 分泌物的风险在分水岭主要与庄稼和家畜惯例有关。耕种，化肥，和粪肥的合适的管理是必要的控制 N 版本。量的评价结果显示那种选择练习沿着 Jiulong 河包括授精，在猪农场附近的植物的长带缓冲区的安装，和更河边的缓冲区的安装的减小能减少 N 的可能性通过流量的分泌物。
文摘Flash flood is a dangers natural disaster causes lots of structure damage, traffic collapse, economic defects and human life loss. An efficient way to reduce its effects is preparing flash flood mapping to identify zones at risk due to flood. Flash flood mapping is a powerful tool for urban planners, traffic and infrastructure engineers, emergency and rescue services. This article proposes an approach utilizes remote sensing (RS) and geographic information system (GIS) to prepare flood risk code (FRC) map for Jeddah city, Saudi Arabia. The proposed approach applied the Curve Number (CN) method of flood modelling and uses runoff depth, land use, soil hydrological parameters, surface slope, and longest flow path to generate FRC. SPOT satellite image of the study area was classified to generate land use map, Digital Elevation Model (DEM) was used for generating slope map and for hydrology analysis using HEC-GeoHMS tool, and soil properties were generated from scanned soil maps. All data were integrated in ArcGIS 10.4.1 to prepare the final flood risk map. The results show that a precipitation of 106.3 mm will generate 136.5 million m3 of flood water. The results according to the developed flood risk code show that due to this amount of precipitation, about 1 million people live in Jeddah are prone to extreme flood risk and about 2 million of population are at major risk, the rest of population (about 0.5 million) are vulnerable to moderate to minor fold risk. The approach was verified using ground truth data and proofed precision.
