Flood hazards result in enormous casualties and huge economic losses every year in the Pearl River Basin (PRB), China. It is, therefore, crucial to monitor floods in PRB for a better understanding of the flooding patterns and characteristics of the PRB. Previous studies, which utilized hydrological data were not successful in identifying flooding patterns in the rural and remote regions in PRB. Such regions are the key supplier of agricultural products and water resources for the entire PRB. Thus, an analysis of the impacts of floods could provide a useful tool to support mitigation strategies. Using 66 Sentinel-1 images, this study employed Otsu’s method to investigate floods and explore flood patterns across the PRB from 2017 to 2020. The results indicated that floods are mainly located in the central West River Basin (WRB), middle reaches of the North River (NR) and middle reaches of the East River (ER). WRB is more prone to flood hazards. In 2017, 94.0% flood-impacted croplands were located in WRB; 95.0% of inundated croplands (~9480 hectares) were also in WRB. The most vulnerable areas to flooding are sections of the Yijiang, Luoqingjiang, Qianjiang, and Xunjiang tributaries and the lower reaches of Liujiang. Our results highlight the severity of flood hazards in a rural region of the PRB and emphasize the need for policy overhaul to enhance flood control in rural regions in the PRB to ensure food safety.

Monitoring and quantifying suspended sediment concentrations (SSC) in estuaries such as the Pearl River Estuary (PRE) provide crucial information for environmental processes, hydrological infrastructure, and navigation. Traditional SSC mapping based on in situ investigations lacks the spatial coverage necessitated by detailed analysis. In this study, based on in situ spectral data and SSC measurements, we developed models to quantify SSC based on Landsat TM/OLI and Sentinel-2 imagery. The models were then used to map the SSC distribution in the PRE for the period 1986–2020. The results indicated that SSC in the entire PRE displayed an overall decreasing trend over the past 35 years, but an abnormal increase was also observed in shallow waters near Hengmen. Geographically, the concentration along the west coast is higher than on the east coast, and the central part of Lingding Bay underwent a slight increase. The decreased sediment output from the Pearl River Basin is the major cause of the decreasing changes in SSC. However, the natural factors and human activities such as channel dredging and the construction of artificial facilities can also disturb the spatial distribution of SSC. Regions with a significant decrease in SSC should have special concerns about retaining the PRE’s health and sustainability.

Healthy soil is the key foundation of the world’s agriculture and an essential resource to ensure the world’s food security. Soil erosion is one of the serious forms of soil degradation and a major threat to sustainable terrestrial ecosystems. In this study, we utilized a continuous Landsat satellite image dataset to map soil erosion changes (1990–2020) based on the RUSLE model across the Pearl River Basin. The study results indicated that: (1) The multi-year area-specific soil erosion average in the Pearl River Basin is approximately 538.95 t/(km²·a) with an annual soil loss of approximately 353 million tons; (2) The overall soil erosion displayed a decreasing trend over the past 30 years with an annual decreasing rate of −13.44(±1.53) t/(km²·a); (3) Soil erosion, dominated by low- and moderate-level erosion, primarily occurred in the tributary basin of Xijiang River, especially in the areas with slopes > 15°, low vegetation coverage, or poorly managed forests; (4) the NDVI and land cover were the dominant factors regulating soil erosion dynamics versus the insignificant role of precipitation played in the erosion procedure. The study results are valuable for soil erosion management and water conservation in the Pearl River Basin.

Urbanization in China has been expanding dramatically since 1978, significantly affecting the extreme temperature changes in cities, which is a vital indicator of urban climate change. To assess urban-related effect on regional extreme-temperature changes in China, this study employed high-resolution land use data to divide meteorological stations into rural stations, suburban stations, and urban stations, and evaluated the annual and seasonal changes in extreme minimum temperature (TNN), mean temperature (Tavg) and extreme maximum temperature (TXX) at each meteorological station. The result revealed that extreme temperature indices (TNN, TXX) and Tavg increased significantly from 1960 to 2016 with varied degrees in different seasons and different regions. Extreme temperature indices in high latitudes increased more rapidly than in low latitudes; while the trends in summer are slower than in other seasons. Urbanization effects on the trends of TNN, Tavg and TXX were all statistically significant, but urbanization effects on TNN and Tavg were more significant than TXX. The urbanization effects were more significant in low altitudes, especially in North, South, Northwest and Northeast China. In North, Northwest and Northeast China, the urban-related effects on temperature increase were mainly observed in spring and winter, but in South China, the urban-related effects were more evident in summer. This study is valuable for sustainable urban planning in China.

Chlorophyll-a (Chla) is an important parameter for water quality. For remote sensing-based methods for the measurement of Chla, in-situ hyperspectral data is crucial for building retrieval models. In the Pearl River Estuary, we used 61 groups of in-situ hyperspectral data and corresponding Chla concentrations collected in July and December 2020 to build a Chla retrieval model that takes the two different seasons and the turbidity of water into consideration. The following results were obtained. (1) Based on the pre-processing techniques for hyperspectral data, it was shown that the first-derivative of 680 nm is the optimal band for the estimation of Chla in the Pearl River Estuary, with R² > 0.8 and MAPE of 26.03%. (2) To overcome the spectral resolution problem in satellite image retrieval, based on the simulated reflectance from the Sentinel-2 satellite and the shape of the discrete spectral curve, we constructed a multispectral model using the slope difference index method, which reached a R² of 0.78 and MAPE of 35.21% and can integrate the summer and winter data. (3) The slope difference method applied to the Sentinel-2 image shows better performance than the red-NIR ratio method. Therefore, the method proposed in this paper is practicable for Chla monitoring of coastal waters based on both in-situ data and images.