Climate-sensitive ice-covered reservoirs are critical components of methane (CH₄) release. To reveal the spatial characteristics of CH₄ concentrations, diffusive fluxes and bubble fluxes during the ice-covered and ice-free periods in northern reservoirs, and in order to clarify the critical influences on their variations. We selected Dongfeng Reservoir, a large reservoir in Northeast China, and conducted six field investigations of CH₄ concentrations and emissions in deep and shallow waters during the ice-covered (January 2022 and January 2023) and ice-free (July 2022, October 2022, March 2023, and September 2023) periods. The results showed that spatially, surface CH₄ concentration and diffusive flux were significantly higher in shallow water than those in deep water. CH₄ bubble flux had the largest range of variation in shallow water, while there was no obvious spatial difference in the proportion of CH₄ in bubbles. Temporally, surface CH₄ concentration, diffusive flux, bubble flux, and the proportion of CH₄ in bubbles were generally high in summer and low in autumn. The surface CH₄ concentration had the largest range of variation in winter, and the CH₄ concentration under the ice was significantly higher in shallow water than those in deep water. Water depth determines the release of CH₄ bubbles from sediments and is the basis for determining deep and shallow water based on bubbles. Ice cover leads to significant differences in CH₄ production and transport compared with ice-free periods by indirectly changing the water environment and directly altering the CH₄ release. CH₄ accumulated under the ice and in the ice will greatly increase the CH₄ release potential during the spring ice-melt period. Overall, this study improves the understanding of CH₄ emissions from reservoirs characterized by ice-covered periods and provides theoretical basis for comprehensive estimation of CH₄ emissions from reservoirs.

Accurate simulation and forecast for soil processes has always been a challenge for river management and environmental conservation. However, the sediment modeling technique remains insufficient for catchments characterized by special soil erosion conditions, especially for the steep area of the upper Yangtze River basin. This study presents a framework that incorporates soil erosion and transport calculation modules into a distributed hydrological model, and customized modifications are applied to fit the catchment conditions. In addition, to accurately describe the topography (e.g., slope length and steepness) and to account for its impact on soil process simulation, the sub-basin with high sediment yield is discretized with a higher spatial resolution. The presented is validated in Heishuihe River basin in southwestern China. And the results show that the modified version of the DDRM model (i.e., DDRM-SED) model show a good simulation performance in terms of flow and sediment processes. In addition, the DDRM-SED model with multi-spatial resolution show a better simulation performance than the model with constant spatial resolution.