The construction and operation of cascade reservoirs has changed the natural hydrological cycle in the Yalong River Basin, and reduced the accuracy of hydrological forecasting. The impact of cascade reservoir operation on the runoff of the Yalong River Basin is assessed, providing a theoretical reference for the construction and joint operation of reservoirs. In this paper, eight scenarios were set up, by changing the reservoir capacity, operating location, and relative location in the case of two reservoirs. The aim of this study is to explore the impact of the capacity and location of a single reservoir on runoff processes, and the effect of the relative location in the case of joint operation of reservoirs. The results show that: (1) the reservoir has a delay and reduction effect on the flood during the flood season, and has a replenishment effect on the runoff during the dry season; (2) the impact of the reservoir on runoff processes and changes in runoff distribution during the year increases with the reservoir capacity; (3) the mitigation of flooding is more obvious at the river basin outlet control station when the reservoir is further downstream; (4) an arrangement with the smaller reservoir located upstream and the larger reservoir located downstream can maximize the benefits of the reservoirs in flood control.

The Yellow River Basin is a typical arid and semi-arid area, which is very sensitive to climate change. In recent years, it has become the area with the greatest shortage of water resources in China. In this study, a new two-way coupling model of land surface and hydrology has been explored to analyze the impacts of climate change and human activities on the runoff. It is of great theoretical and practical significance for making better management countermeasures and strategies to cope with climate change in the Yellow River Basin. The results showed that: (1) the annual average precipitation in the basin was 470.1 mm, which was higher in the lower reaches than in the middle and upper reaches. The annual average temperature is 5.8 °C. The entire basin showed a remarkable warming speed. The annual average pan evaporation is 1067.3 mm showing a downward trend throughout the basin; (2) from 1987 to 2009, the contribution rate of climate change to runoff change has not fluctuated by more than 5%. Since 2010, the precipitation caused by climate factors has increased runoff by 12~15%. The impact of land use change on runoff has been increasing annually. The influence of projects on runoff change was the leading factor of runoff reduction in the Yellow River Basin, with the contribution rate around 50%; and (3) for every 10% decrease in precipitation, the runoff decreases by 13~15.7%. When the temperature rises by 1.0 °C, the runoff decreases by 2.1~4.2%. The runoff in the upper reaches of the Yellow River was most sensitive to precipitation and temperature changes. This showed that the runoff in the plateau and mountainous areas were highly sensitive to climate change.

The Yangtze River Basin experiences frequent extreme heatwaves and prolonged droughts, resulting in a tight supply demand balance of electricity and negatively impacting socioeconomic production. Meanwhile, ongoing inter-basin water diversion projects are planned that will divert approximately 25.263 billion cubic meters of water from the Yangtze River Basin annually, which may further affect the power supply in the region. In this study, the CLHMS-LSTM model, a land-surface hydrological model coupled with a long short-term memory (LSTM)-based reservoir operation simulation model, is used to investigate the impact of water diversions on the power generation of the Yangtze River mainstream reservoirs under extreme drought conditions. Two different water diversion schemes are adopted in this study, namely the minimum water deficit scheme (Scheme 1) and minimum construction cost scheme (Scheme 2). The results show that the land surface–hydrological model was able to well characterize the hydrological characteristics of the Yangtze River mainstem, with a daily scale determination coefficient greater than 0.85. The LSTM reservoir operation simulation model was able to simulate the reservoir releases well, with the determination coefficient greater than 0.93. The operation of the water diversion projects will result in a reduction in the power generation of the Yangtze River mainstem by 14.97 billion kilowatt-hours. As compared to the minimum construction cost scheme (Scheme 2), the minimum water deficit scheme (Scheme 1) reduces the loss of power generation by 1.38 billion kilowatt-hours. The research results provide new ideas for the decision-making process for the inter-basin water diversion project and the formulation of water diversion plans, which has implications for ensuring the security of the power supply in the water diversion area.

With the widespread use of Underwater Acoustic Sensor Networks (UASNs) in marine monitoring, disaster prevention and other fields. In recent years, researchers have gradually paid more attention to the security issues of UASNs. Because of the development environment is inaccessible and severely hostile, UASNs are vulnerable to various security threats, such as selective forwarding attacks and DoS attacks [1]. In recent years, the trust model has been recognized as an effective way to defend against the internal attacks in the terrestrial networks. However, it is not feasible to apply these trust models directly in UASNs, because the underwater environment has the characteristics that signal attenuation and the communication quality of channel will change with the environment. The communication quality of the underwater link is unstable, and the poor quality of the link will have a negative impact on the trust value of the nodes. In this paper, we propose a new trust model for stable and accurate node trust evaluation in UASNs. A fast link quality assessment method which is suitable for UASNs with limited node energy and computing ability was adopted. Based on the analysis of the effects of various internal attacks, three types of trust evidence were selected to accurately calculate the trust value of nodes.

Assessing the impacts of land use and cover (LUCC) change and climate change on discharge and sediment load is beneficial for the regional management of water resources and the water environment. The Mann-Kendall test and soil and water assessment tool (SWAT) model were applied to analyze the change trends of meteorological and hydrological variables and to quantitatively assess the response of discharge and sediment load to LUCC and climate change, respectively, in the Hunhe River Basin (HRB). The results showed that LUCC changed little during 1980–2009, mainly from forestland (−0.36%) to other land use types, such as urban land (+0.13%) and grassland (+0.13%). Temperature increased significantly (p < 0.01), and precipitation showed a non-significant decreasing trend. Discharge showed a non-significant decreasing trend, and sediment load significantly (p < 0.05) decreased. The Nash–Sutcliffe efficiency (NSE), coefficient of determination (R²), and percent bias (PBIAS) during the calibration and validation periods indicated that good performance was achieved for the discharge simulation (NSE: 0.77–0.79; R²: 0.79–0.84; PBIAS: −9.61–1.48%) and satisfactory performance for the sediment load simulation (NSE: 0.65–0.77; R²: 0.65–0.78; PBIAS: −2.56–8.31%). The calibrated SWAT model was successfully utilized to assess the impacts of LUCC and climate change on discharge and sediment load, finding that the combined impact of LUCC and climate change decreased the annual discharge and sediment load by 22.65% and 31.51%, respectively. Minor changes in annual discharge (+0.08%) and sediment load (−1.33%) were caused by LUCC, and climate change led to a pronounced decrease in annual discharge (−22.69%) and sediment load (−30.61%). These findings indicate that climate change rather than LUCC dominated the hydrological alterations in the HRB. This study provides important information for decision makers to identify the reasons for changes in hydrological alterations and to design adaptive measures.

To alleviate regional disparities in water resource distribution and consequent scarcity, China has initiated and planned a series of inter-basin water transfer projects using the Yangtze River Basin as the source. These projects are expected to divert approximately 33.4 billion cubic meters of water annually from the Yangtze River Basin. The implementation of these water transfer projects will inevitably alter the hydrological conditions in the upper reaches of the Yangtze River, impacting the reservoir storage strategies of cascading hydroelectric stations under current end-of-flood-season operational plans. This study quantitatively assesses the impact of water transfer projects on end-of-flood-season reservoir storage in cascading systems using the reservoir fullness ratio as an indicator. Employing reservoir storage analysis models, optimization techniques, and flood risk assessment methods, we simulated reservoir storage processes to evaluate associated flood risks and derive an optimized timing strategy for cascading reservoir storage. The results indicate that advancing the reservoir filling schedule by five days for both the Baihetan and Three Gorges dams can offset the adverse impacts of water transfer projects on reservoir storage efficiency. This adjustment restores the reservoir fullness ratio to levels observed in scenarios without water transfers while still meeting flood control requirements. After optimizing the timing of reservoir filling, the electricity generation capacity for the Baihetan and Three Gorges dams increased by 1.357 and 3.183 billion kWh, respectively, under non-transfer scenarios. In water transfer scenarios, the electricity generation for the Baihetan and Three Gorges dams increased by 1.48 and 2.759 billion kWh, respectively. By optimizing reservoir filling schedules, we not only improved the reservoir fullness ratio but also enhanced the electricity generation efficiency of the cascading systems, offering valuable insights for future reservoir operation optimization.