Using CYGNSS Data to Map Flood Inundation during the 2021 Extreme Precipitation in Henan Province, China

Shuangcheng Zhang,Zhongmin Ma,Pengfei Zhang,Yang Nan,Hebin Zhao,Zhenhong Li,Shengwei Hu,Qi Liu,Yuxuan Feng,Jingjiang Zhang

doi:10.3390/rs13245181

Abstract

On 20 July 2021, parts of China’s Henan Province received the highest precipitation levels ever recorded in the region. Floods caused by heavy rainfall resulted in hundreds of casualties and tens of billions of dollars’ worth of property loss. Due to the highly dynamic nature of flood disasters, rapid and timely spatial monitoring is conducive for early disaster prevention, mid-term disaster relief, and post-disaster reconstruction. However, existing remote sensing satellites cannot provide high-resolution flood monitoring results. Seeing as spaceborne global navigation satellite system-reflectometry (GNSS-R) can observe the Earth’s surface with high temporal and spatial resolutions, it is expected to provide a new solution to the problem of flood hazards. Here, using the Cyclone Global Navigation Satellite System (CYGNSS) L1 data, we first counted various signal-to-noise ratios and the corresponding reflectivity to surface features in Henan Province. Subsequently, we analyzed changes in the delay-Doppler map of CYGNSS when the observed area was submerged and not submerged. Finally, we determined the submerged area affected by extreme precipitation using the threshold detection method. The results demonstrated that the flood range retrieved by CYGNSS agreed with that retrieved by the Soil Moisture Active Passive (SMAP) mission and the precipitation data retrieved and measured by the Global Precipitation Measurement mission and meteorological stations. Compared with the SMAP results, those obtained by CYGNSS have a higher spatial resolution and can monitor changes in the areas affected by the floods over a shorter period.

Highlights

IntroductionHenan Province, a provincial-level administrative region of China, is located in central
The results showed that using Cyclone Global Navigation Satellite System (CYGNSS) data, one could obtain high spatial resolution flood monitoring results (3, 6 km), and the inversion results revealed the movement of floods between cities over a short period
Based on the sensitivity of CYGNSS data to surface water, this study proposed a signal scattering mechanism and analyzed temporal and spatial changes of surface reflectivity (SR) before and after extreme precipitation in Henan Province

Summary

Introduction

Henan Province, a provincial-level administrative region of China, is located in central. China (31◦ 230 –36◦ 220 N, 110◦ 210 –116◦ 390 E). The terrain is high in the west; low in the east; and composed of plains, basins, mountains, and hills. It crosses four river basins, namely the Haihe River, Yellow River, Huaihe River, and Yangtze River, and average annual rainfall in the region is 500–900 mm [1]. In mid-to-late July 2021, the central and northern parts of Henan Province were hit by extreme precipitation. Floods and other secondary disasters caused by heavy rainfall have greatly endangered the property and safety of local residents [2,3]

Methods

Results

Discussion

Conclusion