Global risk assessment of river pollution stress based on nighttime light remote sensing data

Abstract

Rivers play a crucial role in the development of human civilization, and river pollution is a significant environmental issue that accompanies with intensified human activity. However, the evaluation of river pollution at a global scale is difficult because of the limitations of long-term pollution-related datasets. As human activities are the main factor causing river pollution, nighttime light (NTL) remote sensing data can be used as an alternative indicator of the risk of river pollution stress(RPS), which is closely related to human activities and refers to the amount of pollutants within the confluence range of river reaches. In this study, we propose a river pollution pressure index (PI) to indicate risk of RPS by considering the accumulation effect of water flow. Then we calculated PI of over 0.67 million reaches global with annual total flow >100 million m3/s from 2000 to 2022, which was validated using water quality data of >2000 river sections in China. The results show that, from 2000 to 2022, the spatial variations of the risk of RPS are uneven, with a migration trend from west to east. The risk of RPS continues to increase globally, especially rapidly after 2010. Central Asia, Southeast Asia, East Asia, and eastern China are the regions with the fastest growth rates. In most developed countries, developing countries, and underdeveloped countries, the risk of RPS is high and increasing slowly, moderate and increasing rapidly, and low and increasing slowly, respectively. However, in some special cases, such as Japan, the risk of RPS continues to decrease. These spatiotemporal variations of the risk of RPS correlate with global events, such as quantitative easing of global economy after 2008, China's “Belt and Road Initiative”, and COVID-19. This study demonstrates that NTL data can be applied to evaluate the global risk of RPS.