With the rapid development of meteorological models, numerical weather prediction is increasingly used in flood forecasting and reservoir regulation, but its forecasting ability is limited by the large amount of uncertainty from meteorological systems. In this paper, a new, hybrid framework is developed to improve numerical precipitation forecasting by combining the multimodel ensemble and probabilistic postprocessing methods. The results show that the multimodel ensemble method used in this paper is an efficient way to reduce prediction errors, especially missing alarm errors. In a comparison of the probabilistic postprocessors based the generalized Bayesian model (GBM) and bivariate probabilistic model (BPM), the GBM shows better performance from the aspects of indicators and is more suitable for real-time applications. Meanwhile, the assessment of probabilistic results shows that the skill of probabilistic precipitation forecasts is related to the quality of their inputs. According to these results, a new hybrid framework is proposed by taking the results from multimodel ensemble as the input of probabilistic postprocessor. Compared to using the raw numerical in GBM, the hybrid framework improves the accuracy, sharpness, reliability, and resolution ability from different lead times by 2–13%, 1–22%, and 0–12% respectively, especially when the lead time is less than 4 d, the improvement can reach 9–13%, 10–22%, and 5–12% respectively. In conclusion, the hybrid two-step framework can provide a more skillful precipitation forecast, which can be useful for flood forecasting and reservoir regulation.

In recent years, flash droughts with a rapid onset and strong intensity have attracted extensive attention due to their impact on agriculture and ecosystems. However, there is still no feasible method for flash drought forecasting and early warning. This paper employs the thresholds of several meteorological variables to identify flash droughts in Zhejiang Province, China, and build a probabilistic flash drought forecasting model through numeric weather forecast (NWF) and the generalized Bayesian model (GBM). The results show that the northern part of Zhejiang Province has the highest risk of flash drought. The NWF is a viable method to provide future information for flash drought forecasting and early warning, but its forecasting accuracy tends to decline with the increase in the lead time and is very limited when the lead time is over 5 days, especially for the precipitation forecast. Due to the low performance of the NWF, the flash drought forecast based on the raw NWF may be unreliable when the lead time is over 5 days. To solve this problem, probabilistic forecasting based on GBM is employed to quantify the uncertainty in the NWF and is tested through an example analysis. In the example analysis, it was found that the probability of a flash drought exceeds 30% from the probabilistic forecasting when the lead time is 12 days, while the deterministic forecasting via the raw NWF cannot identify a flash drought when the lead time is over 5 days. In conclusion, probabilistic forecasting can identify a potential flash drought earlier and can be used to evaluate the risk of a flash drought, which is conducive for the early warning of flash droughts and the development of response measures.

The treatment of rural domestic sewage is essential for the comprehensive improvement of the rural environment. At present, the rate of resource utilization of rural domestic sewage is generally low in China, which fits with the actual situation of rural areas, and low cost is becoming the requirement for the development of rural sewage treatment technologies. Adopting a tailored approach based on local conditions for utilising sewage resources is the best option for rural sewage management. Therefore, it is very important and urgent to explore and evaluate the mode of rural domestic sewage resource utilisation. This paper analyzes the current status of sewage resource utilization in rural China. It researches and explores sewage treatment technology and resource utilization models based on 10 study sites in Yongkang City, Zhejiang Province. At the same time, this article evaluates pollution control effectiveness and environmental emission reduction benefits. The results show that the effluent quality of the treated wastewater by the skid-mounted resource utilization equipment met the reuse requirements and maintained stable water quality. The project can save 251,900 tons of high-quality water resources annually, reducing COD by 78.51 tons, reducing NH3-N and TP by 5.62 tons and 0.39 tons, respectively, and reducing carbon emissions by more than 134 tons. The project has achieved significant comprehensive benefits in water conservation, pollution reduction, and carbon reduction.

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