Statistical post-processing for multi-model grand ensemble (GE) hydrologic predictions is necessary, in order to achieve more accurate and reliable probabilistic forecasts. This paper presents a case study which applies Bayesian model averaging (BMA) to statistically post-process raw GE runoff forecasts in the Fu River basin in China, at lead times ranging from 6 to 120 h. The raw forecasts were generated by running the Xinanjiang hydrologic model with ensemble forecasts (164 forecast members), using seven different “THORPEX Interactive Grand Global Ensemble” (TIGGE) weather centres as forcing inputs. Some measures, such as data transformation and high-dimensional optimization, were included in the experiment after considering the practical water regime and data conditions. The results indicate that the BMA post-processing method is capable of improving the performance of raw GE runoff forecasts, yielding more calibrated and sharp predictive probability density functions (PDFs), over a range of lead times from 24 to 120 h. The analysis of percentile forecasts in two different flood events illustrates the great potential and prospects of BMA GE probabilistic river discharge forecasts, for taking precautions against severe flooding events.

Land use changes are important aspects of global change and affect regional water cycles, environmental quality, biodiversity and terrestrial ecosystems. To understand the temporal and spatial land use change in the Jialing River Basin and its impacts on the hydrological cycle, land use change models and the variable infiltration capacity (VIC) model were applied separately to the Jialing River Basin. Real change and final change were analyzed to determine the consequences of land use changes and their hydrological consequences. Real change is defined as the total variation during a fixed period, including increases and decreases. Thus, real change is the sum of the absolute values of the decrease and the increase. Final change is defined as the difference between the beginning and end of a given period for a specific factor. Overall, the amounts of settlement and shrub land area changed significantly in the entire Jialing River (with final change rates of 20.77% and −16.07%, respectively, and real change rates of 34.2% and 30.1%, respectively, from 1985 to 1995, as well as final and real change rates of 29.37%, 12.40%, 39.9% and 32.8%, respectively, from 1995 to 2000). Compared with the final change, the real change highlighted the rate of change and the change in woodland area. The land use changes in the Lueyang (LY), Shehong (SH) and Fengtan (FT) subcatchments were more dynamic than in the other subcatchments. The economy, population and macro-policy were the main factors responsible for driving the land use changes. The decrease in woodland area in the LY subcatchment corresponded with an increase in evapotranspiration (ET) and with decreases in the other hydrological elements. Overall, the final changes in the hydrological elements in the LY, SH and FT subcatchments were not significant due to the average and compensation effects. The LY subcatchment was mainly affected by the average effect, whereas the SH and FT subcatchments were affected by the average and compensation effects. The use of real change can increase the detectability of hydrological elements changes caused by land use change in SH and FT. The results of this study provide new insights regarding the examination of the effects of land use changes on hydrological regimes. These results are useful for land use planners and water resource managers.

Melt runoff (MR) contributes significantly to the total runoff in many river basins. Knowledge of the meltwater contribution (MCR, defined as the ratio of MR to the total runoff) to the total runoff benefits water resource management and flood control. A process-based land surface model, Noah-MP, was used to investigate the spatiotemporal characteristics of MR and MCR in the Upper Changjiang River (as known as Yangtze River) Basin (UCRB) located in southwestern China. The model was first calibrated and validated using snow cover fraction (SCF), runoff, and evapotranspiration (ET) data. The calibrated model was then used to perform two numerical experiments from 1981 to 2010: control experiment that considers MR and an alternative experiment that MR is removed. The difference between two experiments was used to quantify MR and MCR. The results show that in the entire UCRB, MCR was approximately 2.0% during the study period; however, MCR exhibited notable spatiotemporal variability. Four sub-regions over the Qinghai-Tibet Plateau (QTP) showed significant annual MCR ranging from 3.9% to 6.0%, while two sub-regions in the low plain regions showed negligible annual MCR. The spatial distribution of MCR was generally consistent with the distribution of glaciers and elevation distribution. Mann-Kendall (M-K) tests of the long-term annual MCR indicated that the four sub-regions in QTP exhibited increasing trends ranging from 0.01%/year to 0.21%/year during the study period but only one displayed statistically significant trend. No trends were found for the peak time (PT) of MR and MCR, in contrast, advancing trend were observed for the center time (CT) of MR, ranging from 0.01 months/year to 0.02 months/year. These trends are related to the changes of air temperature and precipitation in the study area.

Land use scenario analysis, SWAT model, flow characteristic indices and flow variability technology were used to analyze the effect of land use quantity and location change on river flow. Results showed that river flow variation caused by land use change from forest to crop was larger than that caused by land use change from forest to grass; Land use change neither from upstream to downstream nor from downstream to upstream had little effect on annual average discharge and maximum annual average discharge. But it had obvious effect on maximum daily discharge; Land use change which occurred in upstream could lead to producing larger magnitude flood more easily; Land use change from forest to crop or grass could increase the number of large magnitude floods and their total duration. And it also could increase the number of small magnitude floods but decrease their duration.

Based on the current conditions of the joint operation of water projects in the Yangtze River Basin (as of 2023), this study aims to conduct retrospective operations using 2020 Yangtze River Basin flood events. Operations are regulated by “ 2023 Joint Operation Plan for Water Projects in the Yangtze River Basin”. The outcomes of operations are analyzed to demonstrate the effectiveness of current water engineering conditions when tacking with 2020 floods, which provide valuable references and insights for future flood operation and management