In order to understand the water quality of Wuliangsu Lake, an inversion method of total suspended matter concentration based on M-GA-BP was proposed. Using Sentinel-2 remote sensing satellite images as the data source and considering the spatial and temporal characteristics existing in the study area, the monthly data was considered as a feature for the inversion of TSM concentration. The GA-BP model was built by optimizing the weights and thresholds of the BP neural network using genetic algorithm (GA), and comparing with the traditional BP neural network model. The results show that the introduction of the monthly feature model effectively reduces the model complexity and improves the model inversion accuracy, among which the M-GA-BP model has the highest inversion accuracy with the coefficients of determination of 0.916 and 0.903 for the training and test sets, respectively, and the root mean square errors of 0.049 μg/L and 0.057 μg/L for the training and test sets, respectively. The study can provide a new idea for the inversion of TSM concentration in the Wuliangsu Lake.

The health status assessment of hydraulic turbines is a necessary task for achieving health management of hydraulic turbines, and is a key step in achieving condition based maintenance of hydraulic turbines. Considering the uncertainty and fuzziness of the obtained representation information of the health status of hydraulic turbines, a combination of qualitative and quantitative indicator systems was constructed. The health status of hydraulic turbines was defined as 5 states and transformed into cloud droplets using language scale functions. The evaluation of the health status of hydraulic turbines was achieved through cloud distance. The effectiveness of the health status evaluation model was verified using a certain type of hydraulic turbine as an example, which provides a solid foundation for equipment health management of hydraulic turbine.

Limited by hydrometeorological data, flood forecasting in ungauged basins still faces challenges. Parameter regionalization is a common method to solve this problem. The machine learning model has the characteristics of simple modeling and convenient use compared with the traditional flood forecasting model. Taking the West Plain of Nansihu Lake in Shandong Province as the research area, referencing the idea of hydrological regional synthesis, this paper synthesizes the data of 40 floods in 8 watersheds from 2010 to 2021, and builds a regionalized flood forecasting model based on Long Short-Term Memory (LSTM). The results show that the regionalized flood forecasting model can simulate the actual flood process well, the relative error of flood peak in both the training set and the testing set are less than 10%, and the Nash-Sutcliffe efficiency coefficients are all greater than 0.9; In the 15 h forecast period, the regionalized flood forecasting model has higher forecasting accuracy, and when the forecast period is more than 15 h, the forecast accuracy of the model decreases.

A study was performed on the stress characteristics of the urban emergency flood-control box—a new equipment made of polymer material. The finite element analysis method was used to study the stress, strain and deformation characteristics of the flood control box under different water retaining heights. The results show that the stress concentration area of the box is mainly appeared at the water retaining surface and the two sides; With the increase of the water retaining height, the difference of water level between inside and outside of box as well as the maximum stress and the deformation are gradually smaller. Compared with the ABS, LLDPE, HDPE and PP materials, the deformation of the flood control box with ABS material is relatively smaller under the same conditions. An optimization study was carried out on the scheme of the flood-control box. And the stress, strain and deformation of the optimization scheme under the same conditions are greatly improved. The maximum stress decreases from 16.09 MPa in the original form to 7.31 MPa in the optimized form, and the maximum deformation decreases from 0.78 cm to 0.13 cm. The mechanical characteristics of the box structure are obviously improved.

Taking the section of Hunan in Xiangjiang River Basin (XRB) as an example, bases on the land use and evapotranspiration data in 2000, 2010 and 2020, this study discusses the characteristics of land use type, area change and mutual conversion in the XRB by using the methods of land use transfer matrix, integrated and single dynamic attitude model and GIS spatial analysis. The effects of land use type, area and conversion on evapotranspiration in the study area were revealed. The results show that the area, proportion and spatial pattern of land use types in the XRB have undergone great changes, especially the frequent conversion among land use types. However, in the past 20 years, the order of main land use areas in the XRB remained stable: forest > farmland > grassland > construction land > water area. The order of theoretical annual evapotranspiration based on land use type in the XRB is forest > grassland > farmland > construction land, which is different from the order of actual annual total evapotranspiration based on land use area: forest > farmland > grassland > construction land. Therefore, the land use type and land use area to evapotranspiration in the study area should be considered comprehensively. The conversion of different land use types in the XRB caused the change of evapotranspiration in different trends and degrees. The conversion between construction land and other land use types has a relatively large impact on evapotranspiration in the study area, while the conversion of other land use types has a small impact on regional evapotranspiration. The research results can provide scientific reference for land use planning and water resources management in the basin.

Flexible Mattress is the main beach guarding structure in the middle and lower reaches of the Yangtze River. The water flow scouring is likely to cause the deformation of the flexible mattress, affecting the guarding effect. Aiming at its deformation monitoring difficulties, this paper explores the feasibility of using optical fiber sensing to monitor the deformation of the flexible mattress through the indoor experiment. The results of the study show that at the initial stage of tensile deformation (less than 20 mm), the measured strain value deviates less from the actual value. When the tensile length is greater than 20 mm, the error rate of each measurement point is exponentially increasing, and the fixing effect of the optical fiber cable and the flexible mattress at the fixed point determines the monitoring accuracy of tensile deformation. The positioning accuracy of optical fiber sensing to measure bending deformation is 3 times fixed-points interval. For the concentrated stress areas (such as the edge of scour pits), positive strain is mainly generated. Optical fiber sensing has the feasibility of monitoring the tensile deformation of flexible beach protection structures. When applying this technology, it is necessary to consider the coupling of the sensing fiber and the deformation of the flexible structure, the destruction of sinking the mattress and the complexity of the construction process. The results can be reference for the research and development of monitoring and assessment technology of the in-service condition of the flexible mattress.

Based on the ground radiation observation data of Hubei Huashi photovoltaic power station from April to September in 2022, the forecast accuracy of the ground radiation products of Wind Energy and Solar Energy Forecasting System of China Meteorological Administration (CMA-WSP) was evaluated. Overall, the correlation coefficient between ground solar radiation and observation in the next 5 days predicted by CMA-WSP is between 0.85 and 0.91, and the forecast effect on the first day is the best. With the increase of forecast time, the forecast accuracy gradually decreases. From the perspective of month-by-month effect, the CMA-WSP has the best effect on ground radiation forecasting in August and September, and the forecast accuracy rate in May and June is relatively low. In terms of daily changes, the CMAWSP has a relatively poor forecasting effect on ground radiation at 10:00~16:00, and is better in other periods. The prediction of ground radiation by CMA-WSP has strong seasonality. The forecast results of different times in spring are quite different, and are relatively stable in summer. The forecast effect in autumn is the most stable, and the correlation coefficient between the prediction results and observation can reach 0.92. In general, the CMA-WSP has a good effect on the ground radiation forecasting in Hubei Province, which can provide good support for the short-term forecasting of photovoltaic resources in Hubei Province.

For the pump-stopping water hammer prevention of the floating pumping station water-conveying system, in addition to ensuring the safety of the pump unit and the pipeline, the impact of the water hammer pressure on the movable rocker pipe and the floating boat should be considered to ensure the stability of the floating boat. The numerical simulation of the pump-stopping transient of a floating pumping station water-conveying system under large range variable water source level was conducted. The results show that the lowest inlet water level is the most unfavorable condition for water hammer prevention. Under the condition that the pump outlet valve refuses to close, if the unit’s reverse speed exceeds the standard and the maximum reverse flow is reached within 3 s after the pump-stopping. The axial-flow check valve is recommended for the pump outlet valve considering the valve driving capacity requirements, the unit reverse speed and water hammer pressure. In the water hammer protection scheme of "pump outlet axial-flow check valve + air chamber on shore + intermediate check valve + hammer-prevention air valve", the axial-flow check valve ensures that the pump unit does not reverse, the air chamber and air valve reduce the maximum water hammer pressure and improve the negative pressure condition in the pipeline, and the intermediate check valve reduces the pressure oscillation amplitude and oscillation time in the pump outlet and rocker pipe. Therefore, the water hammer prevention problem in the floating pumping station water-conveying system is effectively solved.

An accurate hydrological model with strong adaptability is crucial for predicting floods and preventing disasters. The antecedent soil moisture and rain intensity factors are considered to improve the SCS-CN runoff generation model. Then the new SCS-CN hydrological model is developed by adding the watershed concentration module. From the perspectives of different climate zones and magnitude floods, the new model is applied in four basins to flow simulation, which include semiarid basins of Hancun and Macun, and humid basins of Shenglihe and Gongcheng. The results demonstrate that new SCS-CN hydrological model has good applicability in both semi-arid and humid basins, with better performance in semi-arid basins. Generally, the model shows better accuracy in simulating floods of different magnitudes, especially for small and medium floods.

Photovoltaic power generation is affected by the chaotic characteristics of meteorology, and its stochastic, volatile and intermittent characteristics affect the operation of power systems seriously. Aiming at the problem of large dimension of original PV power generation data and the vulnerability of power generation to weather conditions, a data processing method based on Principal Component Analysis (PCA) and BRICH clustering was proposed to reduce the dimensionality of model input variables and facilitate statistical modeling. Secondly, a Copula-Monte Carlo-based probabilistic PV power probabilistic prediction model was constructed to calculate the probabilistic interval prediction of PV power output given the future point prediction values. The model was evaluated based on interval coverage and average width of prediction interval. Finally, the summer data of the actual photovoltaic power station were taken as an example for verification analysis. The results show that the Copula-Monte Carlo method can intuitively show the fluctuation range and expected value of photovoltaic power generation, and is superior to other power prediction models.