Currently, wetland stability is under threat due to the joint effects of global climate change and human activity, especially in lakes. Hence, it is necessary to evaluate the health status of wetland ecosystems such as lakes, identify the variables causing the wetland degradation and work to protect the wetlands from the identified variables in the future. Based on fourteen high-resolution autumn remote sensing images from 1989–2013, the classification characteristics and spatial distribution patterns of wetland landscapes in Poyang Lake were studied through quantitative interpretation technology. An established health assessment index system named the EHCI (Ecological Health Comprehensive Index) was used to assess the health status of Poyang Lake. Additionally, the relationship between water regime and health status of wetland landscape distribution of Poyang Lake were investigated by multivariate statistical analysis. The results demonstrated: (1) The total area of three first level (or six second level) types of wetland landscapes showed a stable status, which was long-term maintaining at about 3026 km² from 1989–2013. (2) The water area shows a downward trend, while the areas of vegetation and land-water transition zone show upward trends. (3) The proposed EHCI of the Poyang Lake wetland presented a downward trend. According to the EHCI results from 1989–2013, the health status of Poyang Lake wetland was healthy for two years, unhealthy for four years and sub-healthy for eight years. (4) The water level fluctuation greatly affected the EHCI, and the effect became greater as the water level increased. These results contribute to the understanding of specific effects of hydrological process on the health status of the Poyang Lake wetland. In addition they provide a scientific reference for the maintenance of stable ecosystem functions of the seasonal freshwater lake. These results contribute to the understanding of specific effects of hydrological process on the health status of the Poyang Lake. In addition they provide a scientific reference for the maintenance of stable ecosystem functions of the seasonal freshwater lake.

Understanding the effects of climate and catchment properties’ changes on water yield is a challenging component in assessments of future water resources. Here, we spatially applied the water-energy balance equation, based on the widely-used Budyko framework, to quantify the temporal and spatial differences of the climate elasticity of runoff in the Poyang Lake Basin (PYLB), highlighting the influence of the catchment properties’ parameter n variation on the climate elasticity and runoff prediction. By using Sen’s slope and the Mann–Kendall method, we found that, for the whole study period (1960–2010), annual temperature in PYLB significantly increased at a rate of 1.44% per decade. Basin-wide wind speed and net radiation had been declining at 0.17 m/s and 46.30 MJ/m² per decade. No significant trend was detected in precipitation and relative humidity. The moving average method was applied to evaluate the temporal pattern of n. The results showed that the calibrated catchment properties’ parameter and the derived elasticities were not constant during the past 50 years. We found that in most sub-basins, the n values increased during 1970–1980, followed by a decreasing trend in the period from 1980 to 1990, whereas the n value in Fuhe sub-basin kept increasing for the almost the whole study period. In addition, the climate elasticity is highly correlated with the n value, indicating that the catchment properties’ parameter was the dominant factor influencing climate elasticity in PYLB in the past 50 years. We also attempted to predict the runoff trend with the consideration of trends in n. However, in some sub-basins, there were still considerable differences between the predicted runoff trend and the observed one. The method used here to evaluate the temporal pattern of n should be an extension of the existing literature and will provide a better understanding of elasticity in the regional hydrological cycle.

Water regime was one of the most important driving factors in the formation of wetland landscape and the growth and distribution pattern of wetland vegetation. Currently, research on the relationship between wetland landscape and water regime was mostly focused in autumns and winters in Poyang Lake, and lack of research in springs. Based on the nine high-resolution spring remote sensing images during 2000–2010, the classification characteristics of wetland landscape and spatial distribution pattern of vegetation and their succession trends in Poyang Lake were studied through quantitative interpretation technology and multivariate statistical analysis. Combined with water level fluctuations characteristics of the five monitoring hydrological stations (i.e., Hukou, Xingzi, Duzhan, Tangyin and Kangshan) at the Poyang Lake, the inter-annual and intra-annual water level variations of Poyang Lake were analyzed. The study was aimed to investigate the quantitative effects of water regime on the spring wetland landscape and spatial distribution pattern of vegetation and their succession trends in Poyang Lake. The results showed that: (1) the maximum scope of water levels of the five monitoring stations varied from 8.5 m to 13.57 m, and the water level of Poyang lake showed a downward trend, declining at an average rate of 0.16 m per year during 2000–2010; (2) the total area of the 10 types of the landscapes did not change significantly, which was always maintained at about 3026 km $2^{}$ and the total area of vegetation coverage showed increasing trend during 2000–2010 in Poyang Lake, with a maximum area in 2008 and a minimum area in 2010; (3) The water level change was consistent with the area of the lake water, and was inconsistent with the areas of the mudflat, vegetation and land-water transition zone. The highest linear fitting degree with water level was the area of the land-water transition zone, followed by the lake water and vegetation. The results were helpful to further explore the eco-hydrology process and its trend at Poyang Lake wetland, a scientific reference for the maintenance of stable ecosystem functions of the seasonal freshwater lake wetland.

Developing a comprehensive research framework that integrates the water–energy–carbon (WEC) system with economic development is crucial to fostering sustainable development. However, common evaluation indicators for sustainable development fail to cover the most up-to-date climate objectives and policies comprehensively and also lack a decoupling analysis between various subsystems and economic development. By incorporating the Tapio model and the coupling coordination degree model (CCDM), we introduce a novel water–energy–carbon–economy (WECE) framework to evaluate the sustainability of regional resources and the environment. Taking the Yangtze River Economic Belt (YREB) as an example, we have constructed a comprehensive water–energy–carbon (WEC) indicator system that aligns with China’s sustainable development objectives and its most recent carbon emission reduction strategies. Employing the indicator system, we conducted an assessment of the sustainable development within the YREB from 2010 to 2019. The results reveal that the YREB has yet to achieve full decoupling between water use, energy consumption, carbon emissions, and economic development, with a prevailing trend towards weak decoupling (WD). The WEC system within the YREB exhibited coordination from 2010 to 2019. Notably, only the WEC system in Sichuan attained good coordination in 2019, indicating the imperative for more extensive initiatives in resource and environmental development to realize sustainable objectives. Finally, we delve into the driving mechanism of the coupling coordination degree (CCD) of the WEC system. Our findings suggest that, from the perspective of system collaborative management, the integrated approach of the WEC system offers superior benefits compared to individual management components. Consequently, it is imperative to bolster collaboration and institute a comprehensive set of policies to ensure sustainable development within the region.

The implementation of differentiated governance for agricultural water pollution (AWP) plays a significant role in alleviating the pressure on agricultural water resources. However, research that comprehensively assesses AWP and its influencing factors from a multidimensional perspective remains relatively limited. This study utilized the grey water footprint (GWF) model to quantify the agricultural grey water footprint (AGWF), agricultural grey water footprint efficiency (AGWFE), agricultural grey water footprint intensity (AGWFI), and agricultural water pollution level (AWPL) in Zhejiang from 2010 to 2020. Subsequently, we applied the standard deviational ellipse (SDE), the kernel density estimation (KDE), and the Dagum Gini coefficient to delve into the dynamic evolution and regional disparities of these indicators. Ultimately, we leveraged both the random forest model and the panel regression model to identify and examine the key factors shaping AGWF-related indicators. The results show that: (1) From 2010 to 2020, in Zhejiang, both AGWF and AGWFI exhibit a trend of first increasing and then decreasing, peaking in 2012. In contrast, AGWFE has consistently increased over the years, reaching an increase of 54.56 CNY/m³ by 2020. Meanwhile, despite fluctuations, AWPL in Zhejiang shows an overall gradual decline. (2) The centroids of relevant indicators for AWP in Zhejiang are primarily located in Jinhua (for AGWF and AGWFI), Shaoxing (for AWPL), and in the area where AGWFE converge. (3) Compared to 2010, the regional disparities in AGWF and AWPL have shrunk significantly in 2020, whereas the regional differences in AGWFE and AGWFI have increased to some extent. In most years, the regional disparities in AGWF, AGWFI, and AWPL are more pronounced in Northeastern Zhejiang compared to the southwestern part. (4) The influencing factors of AGWF, AGWFE, and AGWFI exhibit significant regional heterogeneity. In Northeastern Zhejiang, the primary factors influencing them are technological innovation, resource endowment, and crop-cultivation methods. Conversely, in the southwestern region, the primary factors exerting the same influence are the application intensities of fertilizers, pesticides, and agricultural film application. The primary drivers of AWPL in Zhejiang are grain yield, water resource availability, and crop-planting structure. Notably, these factors do not exhibit regional heterogeneity. The paper proposes AWP control policies from both a comprehensive and multi-dimensional perspective.