The spatiotemporal changes of open-surface water bodies in the Yangtze River Basin (YRB) have profound influences on sustainable economic development, and are also closely relevant to water scarcity in China. However, long-term changes of open-surface water bodies in the YRB have remained poorly characterized. Taking advantage of the Google Earth Engine (GEE) cloud platform, this study processed 75,593 scenes of Landsat images to investigate the long-term changes of open-surface water bodies in the YRB from 1984 to 2018. In this study, we adopted the percentile-based image composite method to collect training samples and proposed a multiple index water detection rule (MIWDR) to quickly extract the open-surface water bodies. The results indicated that (1) the MIWDR is suitable for the long-term and large-scale Landsat water bodies mapping, especially in the urban regions. (2) The areas of permanent water bodies and seasonal water bodies were 29,076.70 km² and 21,526.24 km², accounting for 57.46% and 42.54% of the total open-surface water bodies in the YRB, respectively. (3) The permanent water bodies in the YRB increased along with the decreases in the seasonal water bodies from 1984 to 2018. In general, the total open-surface surface water bodies in the YRB experienced an increasing trend, with an obvious spatial heterogeneity. (4) The changes of open-surface water bodies were associated with the climate changes and intense human activities in the YRB, however, the influences varied among different regions and need to be further investigated in the future.

The eco-environment is dynamic and shows a continuous process of long-term change. It is helpful for policymakers to know the status of the regional eco-environment through accurate evaluations of the history and current situation of the regional eco-environment. The remote sensing ecological index (RSEI) model of China was established in this study by using four indexes: wetness, greenness, dryness, and heat. Knowledge granulation of the RSEIs were carried out, and a method to determine the weights of the knowledge granulation entropy of the indexes based on their characteristics was proposed. This study used Moderate Resolution Image Spectroradiometer (MODIS) data from the Google Cloud Computing Platform to study and calculate the eco-environmental quality of China from 2000–2017. The overall eco-environmental quality in China tended to improve from 2000–2017, although there were large areas of ecological degradation from 2009–2014. The eco-environment of eastern China was better than that of western China. Most of the national ecological areas were third-level ecological areas, which had moderate environmental quality. Dryness was the most important factor affecting the quality of the eco-environment, followed by greenness, which reflected the increasing environmental damage caused by human activities in China in recent years.

The quantitative assessment and spatial representation of wetland carbon storage, which play a critical role in the global carbon cycle and human production, can provide useful data and knowledge for decision-making in achieving sustainable development goals (SDGs). Currently, human activities and climate change impacts pose a challenge for the assessment of wetland carbon storage in coastal urban clusters. We proposed a "past-present-future" long time series refined wetland carbon storage assessment model using Guangxi Beibu Gulf (GBG) and Guangdong, Hong Kong, Macao and the Greater Bay Area (GBA) as the study area. The CLUE-S and InVEST models were coupled to conduct a comparative analysis of the spatial and temporal changes in wetland carbon storage and the spatial identification of damages from 1990 to 2035 and finally explore the sensitivity of wetland changes to carbon storage and quantitatively assess the SDG15.1 target. The results showed that (1) both urban clusters are characterized by many reservoirs/farming ponds, large river areas and few lakes. 1990-2035 rivers, shallow waters and mudflats have a decreasing trend to be distributed in the middle of their respective regions, mangroves are on an increasing trend, GBG is mainly distributed in the Maowei Sea and GBA is mainly distributed in Shenzhen Bay. (2) Wetland carbon storage of the two urban clusters show an overall fluctuating downward trend, with rivers, lakes and beaches all showing a downward trend. The multiyear average carbon storage of the GBG are 3.2 times higher than those of the GBA. In ecological protection scenario (EPS) policy planning, it is reasonable to help wetland carbon sequestration in coastal urban clusters. (3) The trend of wetland change from 1990 to 2020 was positive for carbon storage. The rate of recovery of wetland carbon stocks is lower in GBA than in GBG under the natural increase scenario (NIS) and the ecological protection scenario (EPS). The economic development scenario (EDS) contributes least to the realisation of SDG15.1 for the coastal urban agglomeration. The ecological protection scenario (EPS) contributes the most to the realisation of SDG15.1 for the coastal urban agglomeration.

River flooding—the world's most significant natural hazard—is likely to increase under anthropogenic climate change. Most large rivers have been regulated by damming, but the extent to which these impoundments can mitigate extreme flooding remains uncertain. Here the catastrophic 2016 flood on the Changjiang River is first analyzed to assess the effects of both the Changjiang's reservoir cascade and the Three Gorges Dam (TGD), the world's largest hydraulic engineering project on downstream flood discharge and water levels. We show that the Changjiang's reservoir cascade impounded over 30.0 × 10³ m³/s of flow at the peak of the flood on 25 July 2016, preventing the occurrence of what would otherwise have been the second largest flood ever recorded in the reach downstream of the TGD. Half of this flood water storage was retained by the TGD alone, meaning that impoundment by the TGD reduced peak water levels at the Datong hydrometric station (on 25 July) by 1.47 m, compared to pre‐TGD conditions. However, downstream morphological changes, in particular, extensive erosion of the natural floodplain, offset this reduction in water level by 0.22 m, so that the full beneficial impact of floodwater retention by the TGD was not fully realized. Our results highlight how morphological adjustments downstream of large dams may inhibit their full potential to mitigate extreme flood risk.