Inadequate water quality can mean that water is unsuitable for a variety of human uses, thus exacerbating freshwater scarcity. Previous large-scale water scarcity assessments mostly focused on the availability of sufficient freshwater quantity for providing supplies, but neglected the quality constraints on water usability. Here we report a comprehensive nationwide water scarcity assessment in China, which explicitly includes quality requirements for human water uses. We highlight the necessity of incorporating water scarcity assessment at multiple temporal and geographic scales. Our results show that inadequate water quality exacerbates China’s water scarcity, which is unevenly distributed across the country. North China often suffers water scarcity throughout the year, whereas South China, despite sufficient quantities, experiences seasonal water scarcity due to inadequate quality. Over half of the population are affected by water scarcity, pointing to an urgent need for improving freshwater quantity and quality management to cope with water scarcity.

Every year typhoons severely disrupt the normal rhythms of human activities and pose serious threats to China’s coast. Previous studies have shown that the impact extent and degree of a typhoon can be inferred from various geolocation datasets. However, it remains a challenge to unravel how dwellers respond to a typhoon disaster and what they concern most in the places with significant human activity changes. In this study, we integrated the geotagged microblogs with the Tencent’s location request data to advance our understanding of dweller’s collective response to typhoon Hato and the changes in their concerns over the typhoon process. Our results show that Hato induces both negative and positive anomalies in humans’ location request activities and such anomalies could be utilized to characterize the impacts of wind and rainfall brought by Hato to our study area, respectively. Topic analysis of Hato-related geotagged microblogs reveals that the negative location request anomalies are closely related to damage-related topics, whereas the positive anomalies to traffic-related topics. The negative anomalies are significantly correlated with economic loss and population affected at city level as suggested by an over 0.7 adjusted R². The changes in the anomalies can be used to portray the response and recovery processes of the cities impacted.

The daily nighttime lights (NTL) and the amount of location-service requests (NLR) data have been widely used as a proxy for measures of disaster-induced power outages and geo-tagged human activity dynamics. However, the association between the two datasets is not well understood. In this study, we investigated how the NTL signals and geo-tagged human activities changed in response to Typhoon Mangkhut. The confusion matrix is constructed to quantify the changes of the NLR in response to Typhoon Mangkhut, as well as the changes of the NTL signals at the grid level. Geographically-weighted regression and quantile regression were used to examine the associations between the changes of the NTL and the NLR at both grid and county levels. The quantile regressions were also used to quantify the relationships between the dimmed NTL signals and the change of the NLR in disaster damage estimates at the county level. Results show that the percent of the grids with anomalous human activities is significantly correlated with the nearby air pressure and wind speed. Geo-tagged human activities varied in response to the evolution of Mangkhut with significant areal differentiation. Over 69.3% of the grids with significant human activity change is also characterized by declined NTL brightness, which is closely associated with abnormal human activities. Significant log-linear and moderate positive correlations were found between the changes of the NTL and NLR at both the grid and county levels, as well as between the county-level changes of NLR/NTL and the damage estimates. This study shows the geo-tagged human activities are closely associated with the changes of the daily NTL signals in response to Typhoon Mangkhut. The two datasets are complimentary in sensing the typhoon-induced losses and damages.