Ground penetrating radar (GPR) has a broad application prospect in detecting the leakage area of water supply pipeline. In order to enhance the understanding of the response characteristics of GPR in the leakage area and improve the positioning accuracy of the leakage area, based on the finite difference time domain method, this paper simulated the response characteristics of ground penetrating radar for leakage at the bottom of metal pipes, and extracted the "three instantaneous" seismic attribution. The results show that the upper boundary signal of the leakage area is easy to be identified, and the internal signal has multiple reflections and oscillations. The reflection effect of the instantaneous amplitude attribution in the leakage area is similar to that of the original profile. The instantaneous phase attribution is obviously staggered, and the instantaneous frequency attribution is obviously attenuated. Instantaneous phase attribution and instantaneous frequency attribution can reflect the existence of leakage area and weak signal well, so the instantaneous phase attribution and instantaneous frequency attribution are preferred when analyzing the instantaneous attribution of leakage area. The research results can provide a reference for the interpretation of GPR pipeline leakage detection images and practical engineering applications.

To meet the fault prediction needs of hydro-generator units in the context of big data, combining the characteristics of the attention mechanism with good feature extraction ability and the advantages of model robustness for multi-sensor information driving, this paper proposed a fault prediction system of hydro-generating units based on the attention mechanism and multi-sensor information driving. The system was applied to on-line monitoring of unit ^#8 in August for a hydropower station in Hunan Province. The actual operation results show that the system can effectively predict the vibration trend of the hydro-generator set and realize the intelligent prediction of the hydro-generator.

Phasor measurement unit (PMU) can measure phasors directly, which provides an important technology for dynamic safety monitoring. Aiming at PMU measurements experience errors, a dynamic state estimation method for generators based on cubature Kalman filter (CKF) was proposed. In this method, the fourth order dynamic equations of generators were taken as the system function. The fading factor was introduced into CKF to keep the residual sequence orthogonal at all times, which improves the adaptability of the estimation algorithm. The adaptability of the estimation algorithm was improved, and the defect that the estimation result deviates from the real value due to the uncertain parameters of the generator model was overcome. Simulation results verified the effectiveness of the algorithm.

Goss error detecting method of monitored dam deformation data is researched based on the fully convolutional neural networks (FCN). Firstly, the method of representation learning of artificially labeled data sets by FCN model was proposed to simulate engineers’ experience. Secondly, the FCN model for gross error detection was built and artificially labeled data sets were used for model training. Finally, the trained FCN model was used for gross error detecting of monitored deformation data of a gravity dam. The results show that the gross error in monitored dam deformation data can be accurately obtained by the proposed method, which can improve efficiency of dam safety management.

It is significant to achieve safe operation of the project and strengthen the construction of the whole life cycle safety supervision system of the dam to scientifically and rationally conduct a comprehensive evaluation of the earth and rock dam seepage control treatment scheme. From the four guideline layers of engineering risk removal effect, engineering management, engineering economy and engineering construction, this study constructed the evaluation index system of earth and rock dam seepage control treatment scheme. Aiming at the evaluation of the risk attitude of decision makers in the process of seepage control program selection, the risk attitude factor was introduced to assign interval evaluation to the indicators, and the subjective and objective weights were optimized based on game theory. And then the program was analyzed and evaluated using the improved TOPSIS model. The effectiveness of the preferred system was tested by taking a reservoir anti-seepage treatment alternative as an example. The results show that the method is feasible and effective for the selection of seepage control solutions.

To fully consider the temporal volatility and randomness of runoff and associated source & load in the optimal dispatch of hydropower and reduce spillage water, a probabilistic prediction method of annual scenarios for hydropower runoff and associated source & load was proposed to simulate the typical annual temporal scenarios of average daily runoff and associated source & load and their probability of occurrence. Several typical ten-day scenarios were generated by clustering with a self-organization mapping net (SOM). Then a ten-day scenario simulation model was built based on a Markov-chain probability matrix, a multi-scenario conditional probability matrix, and the similarity principle— "the closer historical year, the larger weight." It ensures that the simulated scenarios accurately fit the statistical characteristics of actual data (randomness, seasonality, and conditional correlation) for intra-year and reflect the trend evolution year-to-year. Combined with the fluctuation checks, annual temporal scenarios were simulated by the Monte Carlo method. Finally, the k-means scenario reduction was used to obtain typical annual temporal scenarios and their probability of occurrence. The results of an actual hydropower example show that the proposed method has the advantages of high accuracy, strong adaptability, and comprehensive prediction information.

Huaxi Reservoir is a typical karst mountain reservoir and an important water source in Guiyang City. In order to find out the distribution of heavy metals in the sediment of Huaxi Reservoir, a total of 21 sets of sediment samples were collected from two cross sections. The content of Cr, Cu, Zn, As, Cd, Pb and other heavy metal elements were determined by inductively coupled plasma mass spectrometer (ICP-MS). Their distribution characteristics and content levels on the cross section were analyzed. The potential ecological risk assessment method and geo accumulation assessment method were used to evaluate the pollution risk, and systematically analyze the degree of heavy metal pollution in two different sections of the reservoir. The results show that the content of heavy metals in the section of inlet reservoir is low and lower than the background value, and its concentration sequence is Zn>Cr>Cu>As>Pb>Cd; The heavy metal content has a law of decreasing with the increase of the offshore distance, the main reason is caused by the influence of surrounding agricultural activities; The content of heavy metals in open sections is relatively low, and the concentration sequence is Zn>Cr>Cu>Pb>As>Cd; The heavy metal content increases from the left bank to the right bank, which is mainly related to river velocity and sediment particle size. The heavy metal pollution in the sediment of the reservoir is light pollution, and the pollution degree of the section near the reservoir is right bank>left bank>river center, and the pollution degree of each heavy metal in the open section gradually increases from left bank to right bank.

In order to accurately describe the water environment quality of Shiyang River Basin and clarify the main pollution factors of water quality, according to the analysis results of water quality data of typical sections of Shiyang River Basin in Gansu Province, five pollution factors including dissolved oxygen, chemical oxygen demand, ammonia nitrogen, total phosphorus and fluoride were selected as water quality evaluation indexes. A combined weighting comprehensive evaluation model based on CM-AHP and entropy weight method was established to study the main pollution factors of Shiyang River Basin. The results show that the combined weight of total phosphorus and ammonia nitrogen pollution accounted for the largest proportion, reached 0.438 and 0.296, respectively, which were the main pollution factors of Shiyang River. The water quality of Shiyang River Basin gradually deteriorated from the upstream to the middle and lower reaches.

The research on water level prediction method of Fenshui River control station in Fenshui River basin that improves the prediction accuracy is of great significance to support regional flood control decision-making. The typical historical floods of Fenshuijiang hydrology station from 2012 to 2020 were selected and classified into category Ⅰ and Ⅱ flood based on systematic cluster analysis method, with the maximum 1-day flood volume, peak discharge, peak water level and the proportion of flood initiation duration as cluster indexes. The water level classification and prediction of water level stations were carried out by flow routing and water level and flow relation conversion method. The upper and lower boundaries of the water level and flow relationship of different flood types were constructed, and a classified interval prediction method of flood level was proposed. The results show that the accuracy of flood peak water level prediction for the two types of floods is improved effectively, the width of forecast interval is obviously reduced, and the availability of forecast results is improved.

This paper selected 6 typical cape-bay sandy beaches in Wenzhou area to sort out the natural environment. The parabolic plane morphology model (MEPBAY) was used to compare the relative positions of the static simulated shoreline with the recent actual shoreline. The advancing and retreating trend of the coastline of the shaped sandy coast was analyzed. The current stability of the coastal beaches of Cape Bay in Wenzhou area was discussed. The results show that the coastline is in a stable state as a whole, and the profile of sandy beaches is mainly divided into four types: concave downward, upward convex, slope, and slope + upward convex combination. The characteristics of the interannual erosion and deposition changes of the profile are mainly divided into three modes: the upward erosion and the downward siltation, the overall erosion type and the basic stable type.