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Assessment of an Extreme Rainfall Detection System for Flood Prediction over Queensland (Australia)

机译:昆士兰州洪水预测极端降雨检测系统评估(澳大利亚)

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摘要

Flood events represent some of the most catastrophic natural disasters, especially in localities where appropriate measurement instruments and early warning systems are not available. Remotely sensed data can often help to obtain near real-time rainfall information with a global spatial coverage without the limitations that characterize other instruments. In order to achieve this goal, a freely accessible Extreme Rainfall Detection System (ERDS—erds.ithacaweb.org) was developed and implemented by ITHACA with the aim of monitoring and forecasting exceptional rainfall events and providing information in an understandable way for researchers as well as non-specialized users. The near real-time rainfall monitoring is performed by taking advantage of NASA GPM (Global Precipitation Measurement) IMERG (Integrated Multi-satellite Retrievals for GPM) half-hourly data (one of the most advanced rainfall measurements provided by satellite). This study aims to evaluate ERDS performance in the detection of the extreme rainfall that led to a massive flood event in Queensland (Australia) between January and February 2019. Due to the impressive amount of rainfall that affected the area, Flinders River (one of the longest Australian rivers) overflowed, expanding to a width of tens of kilometers. Several cities were also partially affected and Copernicus Emergency Management Service was activated with the aim of providing an assessment of the impact of the event. In this research, ERDS outputs were validated using both in situ and open source remotely sensed data. Specifically, taking advantage of both NASA MODIS (Moderate-resolution Imaging Spectroradiometer) and Copernicus Sentinel datasets, it was possible to gain a clear look at the full extent of the flood event. GPM data proved to be a reliable source of rainfall information for the evaluation of areas affected by heavy rainfall. By merging these data, it was possible to recreate the dynamics of the event.
机译:洪水事件代表了一些最灾难性的自然灾害,特别是在不可用的适当测量仪器和预警系统的地方。远程感测的数据通常可以有助于在具有全局空间覆盖范围内获得近实时降雨信息,而无需其他仪器的限制。为了实现这一目标,由Ithaca开发并实施了自由无障碍的极端降雨检测系统(ERDS-ERDS.ITHACAWEB.ORG),目的是监测和预测卓越的降雨事件,并为研究人员提供可理解的方式提供信息作为非专业用户。通过利用NASA GPM(全球降水测量)IMERG(GPM集成的多卫星检索)半小时数据(卫星提供的最先进的降雨测量之一)来进行近实时降雨监测。本研究旨在评估检测到极端降雨中的ERDS性能,导致昆士兰州(澳大利亚)在2019年1月至2月之间的大规模洪水活动。由于影响该地区的降雨量令人印象深刻,弗林德斯河(其中一个)最长的澳大利亚河流)溢出,扩大到几十公里的宽度。几个城市也是部分受影响的,并激活了Copernicus紧急管理服务,目的是提供对事件的影响的评估。在本研究中,使用遥感数据两者验证ERDS输出。具体而言,利用NASA MODIS(适度分辨率成像光谱分辨率计)和Copernicus Sentinel数据集,可以在洪水事件的全部范围内获得清晰的外观。 GPM数据被证明是评估受重降雨影响影响的地区的可靠降雨信息来源。通过合并这些数据,可以重新创建事件的动态。

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