Presentation Information
[U15-P08]A preliminary study on an optimal placement of water level sensors for a flood depth estimation system
*Akihiro Nagao1, Hideaki Kitauchi1, Masato Nakamura1 (1.MRI Research Associates, Inc.)
Keywords:
DEM,flood depth estimation system
For local governments, it is crucial to accurately and promptly grasp urban damage conditions—such as residential flooding caused by heavy rainfall from typhoons or linear precipitation bands—in order to make decisions regarding evacuation orders and requests for emergency assistance. However, for some local governments, it is difficult to allocate sufficient personnel to conduct on-site inspections of disaster areas or to operate complex systems, creating a demand for systems that allow the current situation to be easily understood.
In this study, assuming use under conditions of limited personnel during disaster response, we aim to develop a flood-inundation area estimation system capable of meeting practical needs in disaster prevention operations. To this end, we examine optimal sensor placement—while also considering the prediction of inundation conditions—by using actual flood-related measurement data (such as camera images and low-cost inundation sensors[1], hereinafter referred to as “inundation sensors”), along with a digital elevation model (DEM)[2] and flood inundation assumption area information[3]. This research contributes to the development of a system that enables the assessment of flood damage during disaster response.
In this study, assuming use under conditions of limited personnel during disaster response, we aim to develop a flood-inundation area estimation system capable of meeting practical needs in disaster prevention operations. To this end, we examine optimal sensor placement—while also considering the prediction of inundation conditions—by using actual flood-related measurement data (such as camera images and low-cost inundation sensors[1], hereinafter referred to as “inundation sensors”), along with a digital elevation model (DEM)[2] and flood inundation assumption area information[3]. This research contributes to the development of a system that enables the assessment of flood damage during disaster response.