Improving river medium–high flow estimation by CM Hierarchical Classification (CMHC) method using Sentinel-2 imagery

Abstract

River discharge monitoring is one of the most important parts of water resources management. However, due to hydrological stations' high operating and maintenance costs, discharge monitoring data has gradually become scarce. Remote sensing technology has great potential to supplement observations in this field. The close relationship between the reflectance ratio of dry (C) and wet (M) pixels around the river in the near-infrared (NIR) band and river discharge has been effectively proved, and many CM-based methods have also achieved good results, but often underestimate medium–high flow in rivers. However, medium–high flow usually occurs during the rainy season or flood-prone periods, and their underestimation not only affects the risk assessment of possible or already occurred floods but may also cause damage to people's lives, property, and social assets. To improve this phenomenon, we proposed a new CM method called CM Hierarchical Classification (CMHC) based on the Sentinel-2 dataset and Google Earth Engine (GEE) cloud platform to monitor the river discharge at different classes and achieve high-precision discharge estimation at medium–high flow. The study was conducted at four stations along the Po River in Italy, where measured discharge data were used to derive the calibration curve and evaluate the performance of the estimated results. The Nash-Sutcliffe efficiency (NS) values for the estimates reached an average of 0.84 and up to 0.89, indicating the excellent performance of the method. Compared with existing methods, our method substantially improves the monitoring accuracy of medium–high flow of the river. Furthermore, additional experiments in the Han River in China also confirmed the applicability of the CMHC method, implying that this method can be used to improve the ability of Sentinel-2 to estimate river discharge, especially for medium–high flow, and provide support for river discharge monitoring on a global scale.