Reanalysis datasets, such as ERA5, are essential for climate research, offering comprehensive spatiotemporal coverage. However, their accuracy needs thorough evaluation for effective regional application, particularly in areas with complex topography like the Poyang Lake Basin (PLB), China’s largest freshwater lake. This study evaluated ERA5’s accuracy in simulating near-surface air temperature and precipitation in the PLB, using data from 24 meteorological stations. Key metrics, such as the correlation coefficient (R), root mean square error (RMSE), and mean absolute error (MAE) were applied across daily, monthly, seasonal, and annual scales. The results show that ERA5 performs well for daily mean temperature, with daily R values above 0.98 and RMSEs ranging from 0.95 °C to 3.11 °C. Its highest accuracy was in February and March, with R values exceeding 0.95, and seasonal trends were best captured in spring and autumn (R > 0.99). However, ERA5’s performance for precipitation was less accurate, with daily R values between 0.578 and 0.687 and RMSEs between 8.58 mm and 11.10 mm. ERA5 consistently overestimated precipitation, particularly during 1980–2003. These findings highlight ERA5’s strengths in temperature modeling and its limitations in precipitation, providing insights for identifying climate events and improving climate simulation in the PLB.

Land-use change (LUC) is a significant contributor to the increase in atmospheric CO₂ concentrations, with previous studies demonstrating its profound impact on soil organic carbon (SOC). The conversion of primary forests to farmland has been recognized as the most significant type of LUC inducing CO₂ release from the soil. Therefore, it is critical to understand the impacts of forest LUC on SOC storage, with a particular focus on primary forest to farmland conversion. In this study, we conducted a meta-analysis of 411 observations from 41 published works and found that SOC storage decreased significantly following the conversion of primary forests to farmland. Factors such as soil depth and climate zone influenced the degree of SOC storage loss, with SOC loss being less severe in deeper soil following a conversion from primary forests to farmland. Moreover, the loss of SOC storage was more severe in temperate regions compared to tropical regions. The input and output of surface SOC, changes in soil structure, and increases in atmospheric CO₂ concentrations were significant reasons for the loss of SOC following primary forest to farmland LUC. However, improving tillage methods and implementing sustainable agricultural management strategies can help reduce SOC loss. These findings highlight the importance of sustainable land-use practices in mitigating the negative impacts of forest LUC on SOC storage and the global carbon cycle.

Runoff simulation is of fundamental importance for hydrological research. This study evaluated the applicability of multiple hydrological models and their ensembles for simulating runoff in small and medium-sized river basins of southeastern coastal China, focusing on the Xixi tributary of Jinjiang River and the Songxi and Chongyang tributaries of Minjiang River in Fujian Province. Four lumped hydrological models were selected for analysis: GR4J, IHACRES, TVGM, and MISDc-2L. The Bayesian model averaging method was utilized to compare the performance of each individual model and the multi-model ensemble in runoff simulation. Results: (1) For the calibration and validation periods of four hydrological stations, the mean values of KGE, NS, and R² for the models GR4J, IHACRES, TVGM, and MISDc-2L were all above 0.7, and the mean values of |RE| were below 8.3%, without significant simulation accuracy variations when basin size changes, demonstrating strong regional applicability for runoff simulation; (2) The multi-model ensemble simulations using Bayesian model averaging of GR4J, TVGM, and MISDc-2L exhibited higher accuracy than individual models; (3) The MISDc-2L model demonstrated strong applicability in daily runoff simulations for both small and medium-sized river basins in Fujian Province and the large-sized Dongting Lake basin, showing that it is worthy of further application in other river basins across China. The findings of this study provide a reference for the selection and application of hydrological models for runoff simulation in small and medium-sized river basins of southeastern coastal China.