The long-term trends and variability of hydroclimate variables are critical for water resource management, as well as adaptation to climate change. Three popular methods were used in this study to explore the trends and variability of hydroclimate variables during last 122 years in the Songhua River (SHR), one of most important river systems in China. Results show the followings: (1) There was an obvious pattern of decadal oscillations, with three positive and three negative precipitation and streamflow anomalies. The lengths of these phases vary from 11 to 36 years. (2) Annual temperature demonstrated a statistically significant increasing trend in the last 122 years, and the trend magnitude was 0.30 °C/10 years in the last 50–60 years, being larger than that of the global surface temperature. It has increased much faster since 1970. (3) Monthly precipitation in the winter season in recent years was almost the same as that in earlier periods, but a significantly increasing monthly streamflow was observed due to snowmelt under a warming climate. (4) A statistically significant correlation between hydroclimate variables and climate indices can be determined. These results could be used to make better water resource management decisions in the SHR, especially under future climate change scenarios.

The wastewater discharged from the aquaculture and textile industries often contains toxic organic dyes, such as methylene blue (MB) and malachite green (MG), which pose significant risk to public health and ecosystem stability due to their high chemical stability, bioaccumulation potential and resistance to degradation. To address these challenges, the development of an integrated system capable of both efficient degradation and highly sensitive detection of organic dyes is essential for ecological restoration and early pollution monitoring. Herein, bifunctional Fe₃O₄-Cu₂O-Ag-GO (FCA 2-GO) nanocomposites (NCs) were developed by depositing Cu₂O, Ag nanocrystals and graphene oxide (GO) onto the surfaces of Fe₃O₄ nanocrystals. This multifunctional material acted as both a photocatalyst and a surface-enhanced Raman scattering (SERS) platform, enabling simultaneous degradation and ultrasensitive detection of organic dyes. Under simulated sunlight irradiation, FCA 2-GO NCs achieved over 98% degradation of both MB and MG within 60 min, driven by the synergistic action of reactive oxygen species (·O₂⁻ and ·OH). The degradation kinetics followed pseudo-first-order behavior, with rate constants of 0.0381 min⁻¹ (MB) and 0.0310 min⁻¹ (MG). Additionally, the FCA 2-GO NCs exhibited exceptional SERS performance, achieving detection limits as low as 10⁻¹² M for both dyes, attributed to electromagnetic–chemical dual-enhancement mechanisms. Practical applicability was demonstrated in soil matrices, showcasing robust linear correlations (R² > 0.95) between SERS signal intensity and dye concentration. This work provides a dual-functional platform that combines efficient environmental remediation with trace-level pollutant monitoring, offering a promising strategy for sustainable wastewater treatment and environmental safety.

The ability of a general circulation model (GCM) to capture the variability of El Niño–Southern Oscillation (ENSO) is not only a scientific issue of climate model performance, but also critical for climate change and variability impact studies. Here, we assess 48 CMIP5 GCMs for their skill in simulating ENSO interdecadal variability and its teleconnection with precipitation globally. The results show that (1) only 22 out of 48 GCMs display interdecadal variability that is similar to the observations; (2) the ensemble of the 48 GCMs captures the ENSO–precipitation teleconnection at the global scale; (3) no single GCM can capture the observed ENSO–precipitation teleconnection globally; and (4) a GCM that can realistically simulate ENSO variability does not necessarily capture the ENSO-precipitation teleconnection, and vice versa. The results could also be used by climate change impact studies to select suitable GCMs, especially for regions with a statistically significant teleconnection between ENSO and precipitation, as well as for the comparison of CMIP5 and CMIP6.

The higher education system has been subject to great change in the post-COVID-19 era globally. Developments in science and technology, especially in the field of information, communication and technology (ICT) have a massive influence on the higher education system. Technology in education has garnered importance and research on e-learning has become necessary to explore this new cutting edge of education. This study examines the factors affecting the adoption of e-learning within the higher education system of China. The study applied the structured survey approach to collect data from 280 faculty members of various public institutions to assess how these factors impact the integration of e-learning technologies in China. Public institute teachers are considered as they have high financial distress, anxiety and depression compared to private teachers leading to a lack of online facilities, compatibility issues and self-efficacy. The study findings revealed that a lack of ICT infrastructure and technical support, combined with a lack of e-learning knowledge among educators, are significant barriers to the effective implementation of e-learning in the higher education system of China. Social influence, perceived usefulness and ease of use also play crucial roles in shaping intent towards e-learning adoption. This study provides insights for policymakers and educational administrators seeking to enhance e-learning environments and overcome the challenges faced in the higher education sector in China.

Spatial and temporal patterns of terrestrial water storage (TWS), and their relationship with groundwater levels, were investigated with the Gravity Recovery and Climate Experiment (GRACE) satellite data, the Global Land Data Assimilation System (GLDAS) land surface model results, and climate observations for the Murray–Darling Basin (MDB). The results show that: (1) TWS displays a clear temporal variability: a negative TWS anomaly with a declining trend during 2002–2009, a positive TWS anomaly with a decreasing trend during 2010–2017, and a period of mixed positive and negative TWS anomalies being accompanied by an increasing trend from 2018 to 2025; (2) five dominant cluster patterns were identified that explain the spatial variability of temporal TWS across the MDB; (3) overall, TWS temporal variability is strongly correlated with rainfall, although it is weak at certain locations; (4) TWS is also influenced by evaporation (both actual and potential evapotranspiration, AET and PET) and runoff, and a combined model significantly improves the overall performance in explaining TWS temporal variability; and (5) TWS-derived groundwater storage changes show both similarities and differences in comparison with groundwater level observation changes, reflecting complex hydrogeological processes and the influence of human activities such as groundwater extraction. These findings provide valuable insights to support improved groundwater resource management with GRACE satellite information and land surface models.

Wetland area and quality have continued to decline worldwide due to the combined impacts of global climate change and human activities, so there is a need for a scientific and standardized framework to assess wetland degradation risk and support conservation and restoration efforts. In this study, a wetland degradation risk assessment framework integrating pressure level and degradation level was developed and applied to the western Songnen Plain, one of China’s major marsh wetland regions, using data from 2000, 2010, and 2020. The results showed that: (1) anthropogenic activity intensity and wetland area change were the most influential indicators. The degradation risk index ranged from 0.20 to 0.68, with mean values of 0.52, 0.46, and 0.46 in 2000, 2010, and 2020, respectively, indicating a slight overall decline. (2) The pressure level increased from 0.56 to 0.59 from 2000 to 2020, suggesting a growing influence of external pressures. In the same period, the degradation level decreased from 0.34 to 0.30, reflecting a reduced effect of internal environmental conditions. (3) Spatially, medium-risk areas have expanded from 47.5% to 64.1% and became the dominant area, while high-risk areas remained relatively stable at 14–16%, whereas relatively high-risk areas decreased sharply from 33.87% to 6.29%. These results provide useful guidance for regional land management for sustaining ecological systems, and the proposed framework provides a transferable assessment logic for wetland degradation risk, but its application to other regions require local calibration of indicators, weights, thresholds, and validation datasets.