Coastal subsidence detection and characterization caused by brine mining over the Yellow River Delta using time series InSAR and PCA

Abstract

Extensive coastal deltas in the world are subsiding due to natural or anthropogenic activities. As the widest and youngest river delta in the world, serious coastal subsidence in the Yellow River Delta (YRD) has exacerbated the relative sea level rise (RSLR) and increased the risk of soil salinization and coastal flooding. However, there are rarely relevant studies that quantitatively separate the contributions from different driving factors to subsidence. In this work, we aim to provide a detailed and comprehensive analysis of coastal subsidence related to coastal brine pumping activities in YRD. We investigate the land deformation of the entire YRD by time series InSAR analysis (TS-InSAR) of Sentinel-1 images acquired between 2016 and 2021. The results reveal that fast subsiding funnels larger than 50 mm/yr are mainly distributed in the coastal brine mining clusters. We further used Principal Component Analysis (PCA) to extract the principal components and temporal patterns from the deformation time series. Taking geological data, precipitation, temperature, and human activities into consideration, we quantitatively separate the driving factors of coastal subsidence in sub-areas. We find that underground brine mining contributes to more than 94 % of the coastal subsidence of the YRD. In addition, precipitation is the most important natural factor that can affect the process of land subsidence in YRD, whereas other driving factors from soil consolidation, oil extraction and other activities are not noticeable. This study is expected to offer a cost-effective method for detecting and characterizing coastal subsidence in global sinking deltas, which will contribute to more accurate dynamic monitoring of coastal subsidence and a better understanding of land subsidence responses to anthropogenic activities.

Keywords

• Yellow River Delta
• Coastal subsidence
• Brine mining
• Time series InSAR
• Driving factors
• Principal component analysis