sedimentation basin is one of the important water conservancy facilities to reduce the sand content of water flow in agricultural irrigation projects, which plays an important role in reducing the sand content of water flow and improving the utilization rate of water flow. In order to improve the efficiency of sand sedimentation basin discharge, a linear sand collection culvert structure was designed based on the S-type structure of the sedimentation basin in the Weigan River dry canal. The hydraulic characteristics of the S-type and linear sand collection culvert water flow were clarified by combining the experimental results of prototype observation with physical model tests and numerical simulations. The experimental results show that Fluent software can effectively simulate the operation process of local sand traps; Due to the low flow velocity at the end of the S-type sand trap, the sediment accumulation in the sand trap is caused, while the linear structure effectively increases the overall flow velocity in the sand trap, and the flow velocity in the corridor at the end of the sand trap is increased from 0 m/s to 0.4 m/s-0.7 m/s, thus improving the sand discharge efficiency of the sand trap. This study can provide scientific basis and technical support for optimizing the structure of the sand sink and improving the sand discharge efficiency of the sedimentation basin.

In recent years, it causes disasters increasingly by too much or too little precipitation. Therefore, accurate prediction of precipitation is of great significance and practical application value to human life and social development. Based on the monthly precipitation data of Zhengzhou from 1990 to 2019, monthly precipitation was forecasted from 2020 to 2021 by utilizing SARIMA, Prophet and LSTM model, respectively. In order to improve the prediction accuracy of the model for monthly precipitation, two combined models of the SARIMA-EMD-LSTM and Prophet-EMD-LSTM were proposed. Empirical analysis shows that the proposed two combined models have higher prediction accuracy and decrease the root mean square error significantly. Furthermore, Prophet-EMD-LSTM model has comparatively better prediction effect. The monthly precipitations in Zhengzhou from April to December, 2022 were forecasted with higher precision.

To deal with the problems such as grouting pipe blocking and uneven diffusion of grout-enriched roller compacted concrete, the rheology, fluidity, stability, strength and time-varying properties of slurry containing micro-silica powder were studied. The entropy weight ideal point method was used to determine the optimal mix proportion by considering the working characteristics of the slurry and economic cost. The results show that adding micro-silica powder can reduce the bleeding rate and improve the compressive strength. When W/B=0.4, micro-silica powder reduces the yield stress and fluidity, and increases the plastic viscosity. When W/B =0.5-0.7, the yield stress and plastic viscosity increase with the addition of micro-silica powder. The rheology of slurry is related to the thickness of water film. With the increase of water-binder ratio, the effect of micro-silica powder on slurry’s performance gradually weakens. The yield stress increases linearly with time, and the plastic viscosity increases exponentially with time. Based on entropy weight ideal point method, the optimal mixture ratio of different schemes with fixed water-binder ratio can be obtained.

In order to enhance the efficiency and rationality of water resources allocation in Minjiang River, a water allocation index system including the monitoring rate of water intake, the rate of water quality of control sections meeting the standards and the early warning of discharge was established from the perspective of water resources management and assessment effectiveness. And then the quantitative calculation of the water intake of each water-taking city and the importance of each index were carried out by the comprehensive weighting method which combines the subjective and objective factors. The results show that the results of water intake distribution are consistent with the actual of water diversion, and the demand of water resources in Chengdu, Meishan and other cities in the middle reaches of Minjiang River is large, which can provide a basis for water resources regulation and water rights trading in Minjiang River. The supervision rate of water intake and the rate of water quality of control section are of great weight among the 6 new indexes, which provides an idea for constructing a new index system of water allocation. The results of water diversion take into account both the health of rivers and the requirements of water environment, and try to directly link the benefits of water resources management with water diversion, which can provide reference for actual water diversion, and urges each area to have the emphasis to continue to do well the water resources management and the appraisal related work.

Accurate load forecasting is of great significance for improving the level of grid planning and accurately guiding investment. In view of the shortcoming of over-fitting in the combined forecasting model of empirical risk minimization, a combined forecasting model based on social learning multi-objective particle swarm optimization algorithm was proposed in term of partial least squares regression model, support vector regression model and grey prediction GM (1, 1) model. The uncertainty function information entropy of weight was introduced to represent the expected risk, and the empirical risk and expected risk were comprehensively considered in the model. The simulation results show that the proposed method has higher prediction accuracy than the single forecasting model and the other two combined forecasting models, and the social learning multi-objective particle swarm optimization algorithm has stronger global search ability and optimization performance.

In light of the difficulty of traditional single runoff prediction models to describe future variation in runoff, a monthly runoff prediction model named AVMD-GPR-CK based on adaptive variational modal decomposition (AVMD) and Gaussian process regression (GPR-CK) with physically composite kernel was proposed. In the proposed model, the runoff series was decomposed into several subseries using AVMD. Then subseries were separately modeled according to their own characteristics, and the final prediction result was the superposition of the subsequence prediction results. The AVMD-GPR-CK was applied to forecast the future 1-12 months runoff at Xiangjiaba station in the Jinsha River basin. The results show that the deterministic coefficient of the AVMD-GPR-CK model is greater than 0.94, and the mean absolute percentage error (M_MAPE) is within ±17% for all leading times, and the M_MAPE is inside ±10% for leading times within 10 months. Furthermore, the accuracy of the AVMD-GPR-CK is significantly better than those of the commonly used BP, GRNN, RBF, and RELM models.

In order to study the effects of plants on the migration and accumulation of nitrogen in the biological retention system, and promote the vegetation construction of rainwater biological retention system in loess distribution area, 5 groups of biological retention system simulation devices were constructed by selecting Iris, Hemerocallis, Sedum, Ophiopogon and non-plants. The migration of nitrogen in fillers and the accumulation of nitrogen in each medium under different plant treatments were investigated. The results show that there was a close relationship between plant nitrogen accumulation and plant biomass increase during the experiment, which was as follows: Sedum> Iris>Hemerocallis> Ophiopogon. The nitrogen absorbed by plants was mainly accumulated in the upper structure of plants. The distribution difference of in the five groups of biological retention system fillers is not significant and the content of is low. is mainly removed in the upper part of the packing layer by adsorption, and each system has a good removal effect on . Plants have a significant effect on the distribution of in the packing and the migration of in the system. Compared with the non-plant group, the system with plants can reduce content in the filler, and the lower the content in the filler before influent, the lower the effluent concentration. The average TN removal rates of 5 treatments were as follows: Iris (50.59%)> Sedum (43.99%)> Hemerocallis (37.85%) Ophiopogon > (30.51%)> non-plant (26.09%).

At present, most of the domestic parallel pump groups adopt a single-objective control model, and only pay attention to the energy efficiency optimization of operating conditions and operating costs in the process of use, and cannot adjust the operation strategy under the real-time working conditions of the pump group according to the comprehensive energy efficiency state of the pump group in the whole life cycle. A multi-objective pump group energy efficiency optimization control model can be independently adjusted according to the energy efficiency state of the current pump set in the whole life cycle. The weight coefficients of three objective functions can be autonomously adjusted, which improves the energy efficiency of the pump set throughout its life cycle and extends the life of the pump set. The objective function was determined by the ideal point value and distance deviation method. The multi-objective ideal point model was solved by LINGO. The optimal solution with the highest total system efficiency, the lowest pump group specific energy consumption and the highest system reliability was obtained. Experimental results show that the improved multi-objective ideal point model can adjust the target weight combination according to the real-time state of the pump group, so as to adjust the real-time control strategy of the pump group.

In order to scientifically evaluate vulnerability of heavy rainfall and waterlogging in subway Stations, determine the sensitivity index as well as improve the management level of the heavy rainfall and waterlogging in subway stations, an evaluation method based on IOWA-VAC was proposed. Firstly, an evaluation index system was constructed based on Pressure-State-Response (PSR) theory. Then, the index data was reordered in ascending order by using the IOWA operator, and the final weight of the new data was obtained by introducing coefficients θ to dynamically adjust the interval boundary weights. The Vector Angle Cosine (VAC) was introduced to test the closeness of the consistency between the target score vector to be evaluated and the ideal target vector, so as to realize the transformation from algebraic thinking to spatial geometry thinking, and the target grade to be evaluated was obtained. Single factor sensitivity analysis was used to determine the sensitivity index. The practicability of the evaluation model was verified by taking the Yansi station of Zhengzhou Metro Line 5 construction projects as examples. The results show that the vulnerability level of the Yansi station of Zhengzhou Metro Line 5 is Ⅳ, with high risk. Thus, it provides feasible suggestion for vulnerability management of heavy rainfall and waterlogging in subway stations.

In order to realize the remote mobile monitoring of the dam, the automatic identification of important defects and the measurement of key monitoring equipment, the research on the intelligent mobile inspection technology of dam safety based on image recognition technology and track robot was carried out. Firstly, an intelligent mobile inspection system for dam safety was constructed based on the orbital robot. On this basis, the automatic identification of typical dam defects and the measurement of key monitoring equipment were realized based on image recognition technology. It had been applied in a dam with good results. The remote and large-scale inspection of dam safety was realized, which can significantly reduce the workload of manual inspection, replace manual inspection under extreme natural conditions, and timely grasp the operation of hydraulic structures such as dams. The research results can provide important reference and technical support for the safety monitoring of dams.