Poyang Lake is China's largest freshwater lake with a high degree of spatio-temporal variation. The lake has shrunk in size in recent years, resulting in significant hydrological, ecological and economic consequences. It remains unknown whether the shrinkage is a trend or a regime shift, which is of high importance for policymakers as it may lead to different decisions. This study constructed a four-decade record of the lake area using multi-temporal satellite images and hydrological data. The Mann-Kendall analysis revealed a decreasing trend of Poyang Lake but it was statistically insignificant. The Rodionov sequential approach disclosed an abrupt change of the lake in 2006, implying a regime shift. Basically, the lake change was a synthetic result of precipitation, evapotranspiration and outflow discharge. However, precipitation and outflow did not show any significant trend or abrupt change, and evapotranspiration had an increasing trend in addition to an abrupt change in 1998. The trigger for the recent lake declines was principally ascribed to a weakened blocking effect of the Yangtze River. The findings provide an example of hydrologic non-stationarity and are valuable for effective promotion of climate adaptation and water resource management.

Improper use of land resources may result in severe soil salinization. Timely monitoring and early warning of soil salinity is in urgent need for sustainable development. This paper addresses the possibility and potential of Advanced Land Imager (ALI) for mapping soil salinity. In situ field spectra and soil salinity data were collected in the Yellow River Delta, China. Statistical analysis demonstrated the importance of ALI blue and near infrared (NIR) bands for soil salinity. A partial least square regression (PLSR) model was established between soil salinity and ALI-convolved field spectra. The model estimated soil salinity with a R² (coefficient of determination), RPD (ratio of prediction to deviation), bias, standard deviation (SD) and root mean square error (RMSE) of 0.749, 3.584, 0.036 g∙kg⁻¹, 0.778 g∙kg⁻¹ and 0.779 g∙kg⁻¹. The model was then applied to atmospherically corrected ALI data. Soil salinity was underestimated for moderately (soil salinity within 2–4 g∙kg⁻¹) and highly saline (soil salinity >4 g∙kg⁻¹) soils. The underestimates increased with the degree of soil salinization, with a maximum value of ~4 g∙kg⁻¹. The major contribution for the underestimation (>80%) may result from data inaccuracy other than model ineffectiveness. Uncertainty analysis confirmed that improper atmospheric correction contributed to a very conservative uncertainty of 1.3 g∙kg⁻¹. Field sampling within remote sensing pixels was probably the major source responsible for the underestimation. Our study demonstrates the effectiveness of PLSR model in retrieving soil salinity from new-generation multi-spectral sensors. This is very valuable for achieving worldwide soil salinity mapping with low cost and considerable accuracy.

Spatiotemporal behaviors of meteorological droughts are basic for understanding the development and driving forces of droughts. Currently, there are a limited number of approaches mainly used to analyze the spatiotemporal evolution of large‐scale soil moisture/hydrological drought events at global or continental scales. These behavior description approaches on the spatiotemporal dynamics of drought are not perfect and should be improved further. To this end, a new approach was proposed to investigate the migration of meteorological droughts based on topological spatial relations. It was used to identify drought clusters, migration trajectories, and migration directions of meteorological droughts. In the Poyang Lake basin (24°29′ to 30°04′N, 113°34′ to 118°28′E), China, monthly precipitation data were available from 1960 to 2007. The one‐month standardized precipitation index was used to characterize meteorological droughts. The proposed approach identified a total of 77 drought events and 454 drought clusters during the study period. Their drought centroids were tracked and analyzed. The migration distances of drought events exhibited a significant linear relationship with the drought duration (R² > 0.8, slope of 165 km per month). More than 70% of drought events had a migrating displacement greater than 1° (approximately 100 km). These results indicated that the meteorological drought events traveled actively and occurred on a widespread basis in the basin. Moreover, two main patterns of drought cluster migration (northward and southward) were identified. The approach and findings can provide some important implications to investigate the migration of meteorological droughts in other regions.

Compound drought–heatwaves (CDHWs) accelerate the warming and drying of soils, triggering soil compound drought–heatwaves (SCDHWs) that jeopardize the health of soil ecosystems. Nevertheless, the behavior of these events worldwide and their responses to climatic warming are underexplored. Here, we show a global escalation in the frequency, duration, peak intensity, and severity of SCDHWs, as well as an increase in affected land area, from 1980 to 2023. The increasing trends, which are particularly prominent since the early 2000 s, and projected to persist throughout this century, are dominated by summertime SCDHWs and enhanced by El Niño. Intensive soil warming as well as climatologically lower soil temperatures compared to air temperatures lead to localized hotspots of escalating SCDHW severity in northern high latitudes, while prolonged duration causes such hotspots in northern South America. Transformation of natural ecosystems, particularly forests and wetlands, to cropland as well as forest degradation substantially enhance the strength of SCDHWs. Global SCDHWs consistently exhibit higher frequencies, longer durations, greater severities, and faster growth rates than CDHWs in all aspects from 1980 to 2023. They are undergoing a critical transition, with droughts replacing heatwaves as the primary constraint. We emphasize the significant intensification of SCDHWs in northern high latitudes as well as the prolonged duration of SCDHWs in the Southern Hemisphere, posing an underrated threat to achieving carbon neutrality and food security goals.

Context The world’s largest dam—the Three Gorges Dam (TGD)—has been in operation for more than 10 years. While the recent shrinkage of large lakes and increased severe droughts in the downstream have been subjectively ascribed to TGD, empirical support based on thorough analysis is still lacking, leaving a gap for ecologists to quantify the TGD impacts on the surrounding landscapes. Objectives This study aims to quantify the impacts of TGD water impoundment on downstream landscapes in terms of lake shrinkage and severe droughts. Methods We have incorporated the recent findings and conducted a comprehensive analysis based on long-term datasets and contrasting scenarios with and without the presence of TGD. The datasets were constructed from hydrological measurements, a hydrodynamic model, and satellite data retrieval techniques. Results Here we show that, in addition to natural variations due to climatic conditions, TGD water impoundment has indeed weakened river’s ability in preventing backflows from its connected lakes directly contributed to their shrinkage. The impoundment substantially increased the intensity and severity of droughts downstream, and may have produced a cluster of impacts on the changing landscape. Conclusions Our finding provides needed information for assessing TGD’s impacts on environmental services in the region, and raises serious concerns with the ongoing large-scale hydraulic project—China’s South-to-North Water Transfer Project—which will further reduce the flow of the Yangtze River.