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.

Soil-testing formula fertilization technology is a powerful tool for preserving arable land and ensuring food security. The purpose of this study was to investigate farmers’ acceptance intentions and behavioral responses to soil-testing formula fertilization technology. Based on the theory of planned behavior, this paper adopts the partial least squares structural equation modeling (PLS-SEM) method, with 295 farmers in the high-standard farmland project area of Shaanxi Province as samples. The research results show that attitude (ATT), subjective norms (SN), and perceived behavioral control (PBC) all had a significant positive influence on farmers’ behavioral intentions. The order of impact effects from large to small is ATT > SN > PBC. The ecological rationality of farmers, communication and demonstration between neighbors, and effective technical training, as well as consulting and guidance services, can better enhance farmers’ intentions to apply soil-testing formula fertilization technology. This study could help to provide references for policymaking to improve the adoption of soil-testing formula fertilization technology.