Daily Flood Monitoring Based on Spaceborne GNSS-R Data: A Case Study on Henan, China

Abstract

Flood is a kind of natural disaster that is extremely harmful and occurs frequently. To reduce losses caused by the hazards, it is urgent to monitor the disaster area timely and carry out rescue operations efficiently. However, conventional space observers cannot achieve sufficient spatiotemporal resolution. As spaceborne GNSS-R technique can observe the Earth’s surface with high temporal and spatial resolutions; and it is expected to provide a new solution to the problem of flood hazards. During 19–21 July 2021, Henan province, China, suffered a catastrophic flood and urban waterlogging. In order to test the feasibility of flood disaster monitoring on a daily basis by using GNSS-R observations, the CYGNSS (Cyclone Global Navigation Satellite System) Level 1 Science Data were processed for a few days before and after the flood to obtain surface reflectivity by correcting the analog power. Afterwards, the flood was monitored and mapped daily based on the analysis of changes in surface reflectivity from spaceborne GNSS-R mission. The results were evaluated based on the image from MODIS (Moderate Resolution Imaging Spectroradiometer) data, and compared with the observations of SMAP (Soil Moisture Active Passive) in the same period. The results show that the area with high CYGNSS reflectivity corresponds to the flooded area monitored by MODIS, and it is also in high agreement with SMAP. Moreover, CYGNSS can achieve more detailed mapping and quantification of the inundated area and the duration of the flood, respectively, in line with the specific situation of the flood. Thus, spaceborne GNSS-R technology can be used as a method to monitor floods with high temporal resolution.

Detection and Evaluation of Flood Inundation Using CYGNSS Data during Extreme Precipitation in 2022 in Guangdong Province, China

“…The CYGNSS Level 1 Version 3.0 data that were released by NASA in October 2020 were used, and can be downloaded from https://podaac-tools.jpl.nasa.gov/drive/files/ allData/CYGNSS/L1/v3.0, accessed on 10 November 2022. Compared with the data that were contained in the previous generation, V2.1, the new version reassesses the effective isotropic radiated power using the direct signal power and antenna gain that is measured with a CYGNSS delay Doppler meter, thereby reducing the uncertainty caused by the antenna pattern [5].…”

“…During floods, the Earth's surface is usually covered by clouds. Thus, traditional optical remote sensing technology cannot penetrate the clouds and monitor the progress of the floods [5]. In contrast, microwave remote sensing is almost not affected by vegetation or clouds [6,7].…”

“…Moreover, Song [28] proposed a dual-branch neural network method for flood detection based on the CYGNSS DDM and SMAP vegetation data and verified the use of the CYGNSS data for flood monitoring. In 2021, Yang and Zhang [5,7] both studied flood inundation in Henan Province during extreme precipitation events in 2020 using CYGNSS SR and the threshold method. It should be noted that Henan Province is located in the middle of mainland China, which belongs to a temperate monsoon climate with less precipitation and less moisture.…”

Assessment of Sponge City Flood Control Capacity According to Rainfall Pattern Using a Numerical Model after Muti-Source Validation

“…In 2020, heavy rain on 22 May in Guangzhou caused the suspension of the subway and great economic losses [7]. In July 2021, Zhengzhou (Henan) was affected by a severe rainstorm that killed 51 people and caused direct economic loss of $10.4 billion [8]. Urban flooding has become chronic in Chinese cities, severely restricting development.…”

Assessment of Sponge City Flood Control Capacity According to Rainfall Pattern Using a Numerical Model After Multi-source Validation

“…In 2020, heavy rain on 22 May in Guangzhou caused suspension of the subway and great economic losses [7]. In July 2021, Zhengzhou (Henan) was affected by a severe rainstorm that killed 51 people and caused direct economic loss of RMB 65.5 billion [8]. Urban flooding has become chronic in Chinese cities, severely restricting development.…”