Jian Liu

Projecting runoff and extreme hydrological events in human-modified basins requires climate, land-use and reported water-consumption forcings to be represented within a single, traceable scenario framework. Here, the Dawen River, the largest tributary of the lower reaches of the Yellow River, was selected as the study area. We coupled a physically based model (SWAT model) with the CEEMDAN–Attention–LSTM model to forecast future social water consumption and runoff and then diagnosed extreme hydrological events and decoupled the main driving factors driving runoff dynamics using multiple remote-sensing and hydrometeorological datasets. Five global climate models (GCMs) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) were selected, and the Delta statistical downscaling method was adopted to enhance the future climate data. The GeoSOS-FLUS model was applied to simulate the future LULC distribution, and then all the climate data, the LULC data and other remote-sensing data were input into the CEEMDAN–Attention–LSTM–SWAT model. The results confirmed that the coupled model had reasonable performance in social water consumption and runoff simulation; the Nash–Sutcliffe efficiency (NSE) values for the measured and simulated runoff ranged from 0.80 to 0.84. Future runoff in all scenarios showed varying degrees of increasing trends. Future droughts display longer durations with lower severity compared to floods, while pluvial flood events are characterized by shorter durations with higher severity. The frequency of the drought–pluvial seesaw increased from upstream to downstream in the SSP126, SSP245, and SSP585 scenarios. Finally, the results of decoupling runoff dynamics revealed that the contribution of human activities showed a slight overall increasing tendency from upstream to downstream, accounting for 70% to 82% of runoff alterations, and social water consumption and the LULC factors were the dominant anthropogenic factors.

The development of low-temperature, high-efficiency catalysts for the catalytic elimination of chlorinated volatile organic compounds (CVOCs) remains a significant challenge. Investigating the influence mechanism of catalyst physicochemical properties on chlorobenzene oxidation performance and degradation pathways is particularly important. CuO/WO₃ catalysts were developed using a hydrothermal method in this work. The effects of simultaneous or separate addition of ammonium sulphate and ammonium persulphate on the catalytic performance of the CuO/WO₃ series catalysts were investigated. The results showed that the introduction of ammonium sulphate alone can facilitate the formation of CuWO₄, thereby increasing the chemisorbed oxygen concentration of the CuO/WO₃, and making the overall structure of the catalyst looser and increasing the active sites on the catalyst surface. As the optimal catalyst, CuO/WO₃-2 exhibited 55.9% of chlorobenzene conversion and 32.9% of CO₂ selectivity at 500 °C. Interestingly, although the surface acidity in this work seemed to be one of the reasons for promoting the chlorobenzene oxidation, it could be clearly found that the strong solid acidity of WO₃ was actually a key factor in inhibiting the chlorobenzene oxidation. Finally, based on in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) analysis, the primary mechanism for chlorobenzene oxidation on CuO/WO₃ catalysts proceeds through a sequential conversion: chlorobenzene was first transformed into phenolic intermediates, followed by quinone compounds, maleates, aldehydes, bidentate carbonates, and ultimately carbonate species.

Watershed water cycles undergo profound changes under changing environments. Analyses of runoff evolution characteristics are fundamental to our understanding of the evolution of water cycles under changing environments. In this study, linear regression, moving average, Mann–Kendall, Pettitt, accumulative anomaly, STARS, wavelet analysis, and CEEMDAN methods were used to analyze the trends, mutations, and periodic and intrinsic dynamic patterns of runoff evolution using long-term historical data. The intra-annual distribution of runoff in the Dawen River Basin was uneven, with an overall decreasing trend and mutations in 1975–1976. The main periods of runoff were 1.9 and 2.2 years, and the strongest oscillations in the study period occurred in 1978–1983. The runoff decomposition high-frequency term (intra-annual fluctuation term) had a stronger fluctuation frequency, with a period of 0.51–0.55 years, while the low-frequency term (interannual fluctuation term) had a period of 1.55–2.26 years. The trend term for the runoff decomposition tended to decrease throughout the monitoring period and gradually stabilized at the end of the monitoring period, while the period gradually decreased from upstream to downstream. In summary, we used multiple methods to analyze the evolutionary characteristics of runoff, which are of great relevance to the adaptive management of water resources under changing environments.