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Reciprocity is a fundamental principle of wave physics related to time-reversal symmetry. Nonreciprocal wave behaviors have been pursued for decades because of their great scientific significance and tremendous potential applications. However, nonreciprocity devices have been based on manipulation of non-topological charge (TC) in most studies to date. Here, we introduce the rotational Doppler effect (RDE) into the acoustic system to achieve nonreciprocal control of the TC beam. We use the metasurface to generate a vortex beam with a defined TC. By rotating the metasurface with specific angular velocity, the wave vector of the transmitted wave obtains positive and negative transition flexibly due to the RDE. As a result, isolated and propagating states of the vortex beam can be realized by controlling the rotation direction, representing nonreciprocal propagation. Our work also provides an alternative method for the application of TC beams and the realization of nonreciprocity.

An in-fiber Michelson interferometric sensor was presented by fabricating a concavity on the end face of a single mode fiber using a single CO

In this study, a new method is developed to generate multi-site streamflow series. First, a correlated sampling method based on spectral decomposition is employed to simulate a large number of individual years of multi-site streamflow series. Then, combined with historical design flood data, flood characteristic series considering historical floods are generated. Finally, a subset of the streamflow series corresponding to these flood characteristics is selected from the pool of multi-site simulated streamflow series. The proposed model is applied to multi-site streamflow simulations in the upper Yangtze River basin. Experimental results show that the simulated data not only ensure the fundamental statistical characteristics of the observed data, but also provide good preservation of high order self-dependent, cross-dependent at finer and coarser time scales with any marginal distributions and any correlation structures. In addition, the simulated extreme situations are more reliable for risk and vulnerability analysis of multi-reservoir joint operation systems due to the consideration of the historical design flood data.

We propose an ultrasensitive displacement measurement scheme to overcome the standard quantum limit (SQL) in the unresolved sideband cavity optomechanical system with nonlinear optomechanical coupling and squeezed light injection. By introducing the optimized quantum correlation, which is enabled by suitable choices of the squeezing angle, squeezing level, power of the probe light, and measurement angle of homodyne detection, the off-resonant displacement sensitivity reaches 6 dB below the SQL in linear optomechanical coupling. In contrast, displacement sensitivities with a coherent probe plus variational readout and squeezed probe plus fixed measurement angle (phase quadrature) are 2.6 dB and 4.6 dB below the SQL, respectively. By combining linear and quadratic optomechanical coupling, we show that the displacement sensitivity can be further improved to 9.6 dB below the SQL. Our results have potential applications in gravitational-wave detectors, quantum metrology, and the search for dark matter.

Multireservoir joint flood control operation is an important nonstructural measure for flood control in some basins. Owing to the existence of uncertainties in flood control operation, various degrees of risk can be shown in flood control operation systems. Examining these uncertainties and the resulting risk of failure in multireservoir operation systems is extremely beneficial and indispensable for basin flood mitigation. In this study, different stochastic simulation methods were employed to generate streamflow series at multiple stations and other uncertainties such as the flood forecast errors, discharge capacity, and reservoir storage. Then, the Monte Carlo framework was established based on the simulation sequence to estimate the risk of a failure of each flood control unit in the flood control system. Furthermore, a comprehensive risk assessment indicator was proposed to consider the failure probability and failure consequences at the same time. The Xiluodu‐Xiangjiaba‐Three Gorges cascade reservoirs were selected as a case study. Results show that the applied probabilistic simulation methods could simulate various uncertainties in a multireservoir flood control system effectively, and the proposed risk analysis method could comprehensively evaluate the risks of reservoir overtopping, flood flows exceeding a standard, and flood diversion from the perspective of overall watershed security.

The integration of the digital twin with the water industry is a new generation of information technology and communication technology in the integrated application of the water industry, is an important implementation path to promote the new stage of high-quality water development. The current level of wisdom in the water conservancy industry is still low, and there is relatively little research and application for the digital twin. For this reason, the basic connotation and development concept of the digital twin is discussed in depth, and research is conducted focusing on the problems that may be faced in the construction process of the digital twin in the flood storage space. The study gives a general scheme of flood storage space construction with data base construction, digital scene construction, intelligent simulation and accurate decision support construction as the main axes. The related results can provide constructive planning ideas for future smart river basin construction.

Joint operation of reservoir group is an important method for flood mitigation. Most of the existing flood control operation methods only focus on a single reservoir and a single object, which cannot take into account the coordination and complementarity of different reservoirs, and it is difficult to comprehensively consider the safety of multiple flood control objectives in the upstream and downstream of the basin. In this context, this paper proposed a multi-objective modeling and optimization method for flood control operation of large-scale reservoir groups based on different pre-set frameworks. 12 large reservoirs in the Yangtze River Basin were selected as a case. The results show that the proposed method can reasonably and effectively deal with the complex optimization problem of large-scale reservoir group operation scheme, and can further improve the intelligent level of multi-reservoir joint flood control operation.

During flood control reservoir operation, uncertainties occur in flood forecasting, hydrograph shape, streamflow simulation, reservoir storage, water level, and discharge outflow. It is therefore important to analyze flood control risk due to these uncertainties. This study proposes a stochastic simulation method, comprising a copula-based simulation method accounting for flood forecasting uncertainty, a copula-based single site daily streamflow simulation method for uncertainty in flood hydrograph, and the Latin hypercube sampling (LHS) method for uncertainty in storage, water level, and outflow discharge. Using the Three Gorges Reservoir (TGR) as a case study, the flood control risk, defined by traditional statistical and entropy methods, was calculated and compared. The proposed method satisfactorily preserved the statistical characteristics of the original streamflow series. Results from the TGR case study showed that the entropy method was effective for assessing flood risk due to different uncertainties. Thus, this study provides gives a comprehensive evaluation of flood risk during flood control reservoir operation.

The risk inevitably exists in the process of flood control operation and decision-making of reservoir group, due to the hydrologic and hydraulic uncertain factors. In this study different stochastic simulation methods were applied to simulate these uncertainties in multi-reservoir flood control operation, and the risk caused by different uncertainties was evaluated from the mean value, extreme value and discrete degree of reservoir occupied storage capacity under uncertain conditions. In order to solve the conflict between risk assessment indexes and evaluate the comprehensive risk of different reservoirs in flood control operation schemes, the subjective weight and objective weight were used to construct the comprehensive risk assessment index, and the improved Mahalanobis distance TOPSIS method was used to select the optimal flood control operation scheme. The proposed method was applied to the flood control operation system in the mainstream and its tributaries of upper reaches of the Yangtze River basin, and 14 cascade reservoirs were selected as a case study. The results indicate that proposed method can evaluate the risk of multi-reservoir flood control operation from all perspectives and provide a new method for multi-criteria decision-making of reservoir flood control operation, and it breaks the limitation of the traditional risk analysis method which only evaluated by risk rate and cannot evaluate the risk of the multi-reservoir flood control operation system.

Flood disasters are the most frequent and most severe natural disasters in most countries around the world. Reservoir flood operation is an important method to reduce flood losses. When there are multiple reservoirs and flood control points in the basin, it is difficult to use reservoirs separately to fully realize their flood control potential. However, the multi-reservoir joint flood control operation is a multi-objective, multi-constrained, multi-dimensional, nonlinear, and strong-transition feature decision-making problem, and these characteristics make modeling and solving very difficult. Therefore, a large-scale reservoirs flood control operation modeling method is innovatively proposed, and Dynamic Programming (DP) combined with the Progressive Optimality Algorithm (POA) and Particle Swarm Optimization (PSO) methods, DP-POA-PSO, are designed to efficiently solve the optimal operation model. The middle and upper Yangtze River was chosen as a case study. Six key reservoirs in the basin were considered, including Xiluodu (XLD), Xiangjiaba (XJB), Pubugou (PBG), Tingzikou (TZK), Goupitan (GPT), and Three Gorges (TG). Studies have shown that DP-POA-PSO can effectively solve the optimal operation model. Compared with the current operation method, the joint flood control optimal operation makes the flood control point reach the flood control standard, moreover, in the event of the flood with a return period of 1000 years, Jingjiang, the most critical flood control point of the Yangtze River, does not require flood diversion, and the volume of flood diversion in Chenglingji is also greatly reduced.

With the reservoir construction gradually completed, joint operation of reservoir groups is an important measure to realize reservoir flood control potential,but when the river basin is large, the flood channel routing and time-lag cannot be simplified, in addition, the curse of dimensionality is very difficult for model solving With the expansion of the number of reservoirs. These factors restrict the application of joint operation of large scale mixed reservoirs.In this study, The DP-POA cyclic iterative algorithm which is based on large scale system decomposed-coordinating method was proposed to solve the optimal problem considering the flood routing and time-lag.The upper Yangtze River is selected as a case study. 6 reservoirs, including the Three Gorges Reservoir(TGR)、Xiangjiaba Reservoir(XJB)、Xiluodu Reservoir (XLD)、 Pubugou Reservoir (PBG)、Goupitan Reservoir (GPT) and Tingzikou Reservoir (TZK)are taken into accounts.Compared with current operation of reservoirs independent,results demonstrate that the method can effectively reduce the maximum operating water level of TGR and flood diversion in the lower reaches of the TGR. Therefore, the safety of the flood control points along the river has been largely improved based on the proposed method.