Due to the uneven distribution of water resources in time and space, the problem of water shortage has become increasingly serious in some areas. To optimize use of water resources, it is urgent to establish multi-objective models and apply effective optimization algorithms to guide reservoir management. This study proposed a model of multi-objective optimization for reservoir operation (MORO) with the objectives of maximizing water diversion and power generation. The multi-objective evolutionary algorithm based on decomposition with adaptive weight vector adjustment (MOEA/D-AWA) was applied to solve the MORO problem. In addition, the performance of the MOEA/D-AWA was compared with two other algorithms based on the hyper-volume index. Huangjinxia reservoir, which is located in Shaanxi, China, was selected as the case study. The results show that: (1) the proposed model is effective and reasonable in theory; (2) the optimization results obtained by MOEA/D-AWA demonstrate this algorithm can be applied to the MORO problem, providing a set of evenly distributed non-dominated solutions; and (3) water diversion and power generation are indeed contradictory objectives. The MORO strategy can be used to efficiently utilize water resources, improve the comprehensive benefits of reservoirs, and provide decision support for actual reservoir operation.

Pyromellitic dianhydride (PMDA) grafted chitosan microspheres (PMDA-GLA-CTS) were prepared, and characterized by Fourier transform infrared spectroscopy (FTIR) and x-ray photoelectron spectroscopy (XPS). Due to the presence of a large number of carboxyl groups, the adsorption capacity of the PMDA-GLA-CTS for methylene blue (MB) and neutral red (NR) showed a significant increase compared with the unmodified microspheres. The maximum adsorption capacities were 935 and 909 mg g⁻¹ for MB and NR, respectively, according to the Langmuir equation. Kinetics studies showed that the sorption rate was controlled by the chemisorption process. Sample analysis showed that the adsorbent can effectively remove the cationic dyes in printing and dyeing wastewater.

This paper proposes a feedback, rolling and adaptive operation decision-making mechanism for coupling and nesting of time scales. It is aimed at the change of time scale and the dynamics in the operation process, considering the relationship between operation period and multi-time scales. The key point is to integrate forecasting and operation in order to adapt to the multi-time scales dynamic change in the operation process. The operation process is divided into different time scales; forecasting and operation model method libraries are constructed, and the progressive updating and nesting mechanism are used to realize the process dynamic operation, according to the regulation period or operation period of the reservoir. Taking the Miyun Reservoir in Beijing, China as the research object, the operation mechanism is integrated into the operation process, and the complex forecasting operation and control mechanism are integrated, based on the integrated platform and using modern information technology. The forecasting and operation method uses classic different models, which can be selected based on different goals. The forecasting inflow is used as input, and the output is the water distribution plan, more importantly, the mechanism in the operation process is the key point. This is a rolling modification of the inflow process in the next stage, and the operation plan also changes accordingly. The feasibility, effectiveness, rationality and flexibility of the reservoir dynamic and adaptive operation are verified, so that the reservoir operation is dynamically changing and adapting to the changing demand. The proposed operation mechanism has scientific value and guiding significance to improve the reservoir operation theory, and it provides decision support for the actual reservoir operation and operation business.