水力发电学报
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2024 Vol. 43, No. 7
Published: 2024-07-25

 
     
1 Reconstruction of non-stationary meteorological drought series and its spatiotemporal patterns in Yellow River basin Hot!
CHEN Shihao, MEN Baohui, PANG Jinfeng, ZHANG Teng, WANG Hongrui
DOI: 10.11660/slfdxb.20240701
Under the influence of climate change and high intensity human activities, it is difficult to accurately describe the evolution of non-stationary drought series under the traditional stationary hypothesis. This study uses the complete ensemble empirical mode decomposition with adaptive noise and the run theory to extract the reconstructed drought characteristics of the standardized precipitation evapotranspiration index (SPEI), based on monthly meteorological data from the Yellow River basin of 1960-2020. And the Pettitt method and rotating empirical orthogonal functions are combined to examine its non-stationary meteorological drought characteristics. Results indicate that its meteorological drought manifested a significant increasing trend on multiple time scales, and significant changes in SPEI occurred around 1996 on all time scales. More pronounced seasonal variations in time and more realistic distributions in space are found in the reconstructed drought characteristics when taking into account the non-stationarity. This study is of great significance in clarifying the spatiotemporal evolution patterns of meteorological drought under non-stationary conditions, and helps drought prevention and mitigation for the Yellow River basin.
2024 Vol. 43 (7): 1-13 [Abstract] ( 63 ) PDF (4160 KB)  ( 203 )
14 Generalized additive models for design annual runoff and design flood in Jialu River basin
MO Shuhong, YANG Jinlai, LIANG Weijia, ZHANG Gaofeng, LYU Jingyu
DOI: 10.11660/slfdxb.20240702
The consistency of runoff sequences is often broken due to meteorological changes and human activities, and a direct study of non-consistent hydrological sequences becomes necessary. This paper presents a new method for estimating the design annual runoff and peak flood flow of non-stationary series for the Jialu River basin in the loess plateau based on Generalized Additive Model for Location, Scale and Shape (GAMLSS), using the average design life level method (ADLL) and equivalent reliability method (ER), and selecting air temperature, precipitation and the controlling river basin area of the reservoir and dam as covariates in simulation analysis. The results show that the two hydrological sequences are non-consistent, the developed multi-covariate annual runoff model gives good fitting to the low and high quantile curves, and the flood peak model has achieved satisfactory simulation results. Application of GAMLSS and the corresponding ADLL and ER methods provides higher accuracy of design peak flood and design annual runoff in a specific return period or probability interval, and thus the method better estimates the influence of the hydrological sequence trend on the design values.
2024 Vol. 43 (7): 14-29 [Abstract] ( 53 ) PDF (4957 KB)  ( 160 )
30 Combined model for medium- and long-term runoff predictions based on Extreme-point Symmetric Mode Decomposition
LI Jiqing, LIU Yang, ZHANG Peng, CHEN Jing
DOI: 10.11660/slfdxb.20240703
Extreme-point Symmetric Mode Decomposition (ESMD) is used to predict runoff series based on a runoff forecasting model to solve two problems after runoff series decomposition-large fluctuation ranges of high frequency components and poor forecast accuracy. We use the stationary processing technique of the ESMD to decompose the runoff series, select the best prediction method by analyzing the characteristics of different frequency components, combine Particle Swarm Optimization (PSO) and Least Square Support Vector Machines (LSSVM) for the prediction of high-frequency components, and use the back-propogation (BP) neural network for the prediction of mid- and low-frequency components. A combined ESMD-PSO-LSSVM-BP forecasting model is constructed to forecast annual and monthly runoffs at three hydrological stations in the upper and middle reaches of the Xijiang River. The results show this model, using different forecasting methods for different frequency components, improves the runoff forecasting accuracy significantly.
2024 Vol. 43 (7): 30-40 [Abstract] ( 48 ) PDF (4331 KB)  ( 174 )
41 Mathematical model of random splashing by number theory classification of splashing water droplets
ZHANG Hua, YAO Yubo, ZHANG Yuchen
DOI: 10.11660/slfdxb.20240704
During flood discharge atomization, collision between the water nappes and the water body in the downstream scour pool causes numerous water droplets to splash out in random directions. This creates an initial value problem for the movement of splashing water droplets. This paper develops a concept of number theory graded water droplets, which adopts the number theory method to grade water droplets, based on the idea that this method maintains good uniformity even with a small number of selected points. Using the concept, we can simplify the high dimensional phase space to one-dimensional, and develop a mathematical model for simulation of random splashing water droplets using number theory classification. Comparison of the numerical calculations with the high-accuracy solution reveals that the error of our model is lower for a given number of droplets. As the number of droplets increases, the error decreases at a faster rate and approaches the high-precision solution more rapidly. Thus, by simulating random splashing water droplets using number theory classification, this new model not only achieves higher calculation accuracy with a smaller number of droplets, but simplifies the expression of the high dimensional initial value phase space to one-dimensional.
2024 Vol. 43 (7): 41-50 [Abstract] ( 46 ) PDF (2077 KB)  ( 134 )
51 Influence of sediment concentration on abrasion and erosion characteristics of hydraulic machinery materials
YANG Junfeng, SUN Shuzhen, SUN Shuaihui, SONG Guohua, REN Zuiyou
DOI: 10.11660/slfdxb.20240705
Hydraulic machineries running on muddy rivers suffer from sediment erosion that often causes deformation and damage to flow components, seriously threatening the safe operation of hydropower plants. This study conducts an experiment on a rotating jet facility to examine the influence of sediment concentration on the impact abrasion and erosion characteristics of hydraulic machinery materials, using the weight loss method and Scanning Electron Miscroscopy (SEM). The results show the cumulative weight loss of materials from impact abrasion and erosion takes a nearly linear increase with the rise of sediment concentration. With sediment concentration lower than 60 kg/m3, the increase in the cumulative weight loss of the tested three material is gradual; it becomes rapid at higher concentration. As the concentration increases, the impact erosion causes more severe damage to the materials, but cavitation erosion shows a weakening trend. The higher the surface hardness of the material, the better its resistance to cavitation erosion, and the lower the critical sediment concentration at which the weights of abrasion and erosion are equal. Flow cavitation affects the angle at which sand particles impact on the material surface, and it usually increases the horizontal impact load of the particles. The abrasion marks show lip edges and material accumulation, and the sand particle cutting damage dominates at higher sediment concentrations.
2024 Vol. 43 (7): 51-60 [Abstract] ( 66 ) PDF (5546 KB)  ( 139 )
61 Study on SPH method of granular flow motion and landslide fragmentation effect
LIN Chuan, LIN Yanzhe, SU Yan, PAN Yilin, GAO Xian
DOI: 10.11660/slfdxb.20240706
Landslide geological disasters, common and worldwide, feature intermittency and enormous destructive power. An effective numerical model for such disasters helps formulate the targeted prevention and control strategies of landslides. Focusing on the particle flow characteristics of landslide movement, this paper derives an expression of the dynamic friction coefficient of shallow landslides based on the μ(I) model, and constructs a corresponding framework for solutions using the Smoothed Particle Hydrodynamics (SPH) method. We examine the significant impact of particle fragmentation on landslide movement, and derive a relationship of its basal frictional force versus grain distribution to improve the model by applying the particle fragmentation law based on its potential of destruction. This model is verified against two previous studies in literature-classical three-dimensional slope model experiments, along with a sensitivity analysis on its parameters related to particle fragmentation effects, thus laying a basis for further study of landslide disaster prevention and control.
2024 Vol. 43 (7): 61-72 [Abstract] ( 57 ) PDF (5087 KB)  ( 66 )
73 Analysis of generating slip surfaces in stability analysis
JIE Yuxin, WANG Yangqiang, ZHOU Ting, XIE Qi
DOI: 10.11660/slfdxb.20240707
How to generate a slip surface is one of the key issues in slope stability analysis, and to construct a slip surface with a complex shape is quite challenging. The curve based on the integral of a Logistic function or other basis functions can take the place of the traditional slip surface generated using non-circular curves, which not only improves the smoothness of the slip surface but reduces its degree of freedom. Slip surface generating methods based on basis functions are sorted out in this paper. They are divided into the superposition method of continuous functions and the integral operation method. The characteristics of the Logistic function and its integral are examined carefully, and the influence of different parameters on the curve shape is obtained to narrow parameter ranges. This provides a basis to reduce the degree of freedom of slip surfaces. And a method is presented to determine the initial parameter values of a given slip surface. The calculations of two slope examples show our method is tolerably good in slope stability analysis.
2024 Vol. 43 (7): 73-84 [Abstract] ( 35 ) PDF (2017 KB)  ( 117 )
85 Study on intelligent predictions and analysis of earth-rock dam risk levels as well as model optimization
LI Yanlong, ZHANG Yuchun, WANG Ting, YIN Qiaogang, LIU Yunhe
DOI: 10.11660/slfdxb.20240708
Dam failure often causes an enormous loss of life and property and huge environmental damage. Accurate and fast estimation of the risk level of earth-rock dams is of great significance for controlling their failure hazards. This paper develops a fast prediction model of the earth-rock dam risk grade based on GA-LightGBM, using the K-Nearest Neighbor (KNN) algorithm to fill a large amount of missing data in the database, and adopting a Genetic Algorithm (GA) to optimize the hyperparameters of Light Gradient Boosting Machine (LightGBM). The model accuracy is verified using the receiver operating characteristic (ROC) curves, the area under the curve (AUC), and other evaluation indexes; and it is compared with the traditional machine learning model. The results show that this new model has a high accuracy of 89.95% and its AUC value is 0.977, indicating it is better in terms of applicability and accuracy. Analysis of global influencing factors and case studies using Shapley Additive Explanations (SHAP) show the frequency of inspection is one of the most important factors leading to the risk of earth-rock dams.
2024 Vol. 43 (7): 85-96 [Abstract] ( 72 ) PDF (3499 KB)  ( 130 )
97 Improved wavelet thresholding combined with optimized BiLSTM for dam deformation prediction
SHI Jiachen, YUE Chunfang, ZHU Mingyuan, PI Lilang
DOI: 10.11660/slfdxb.20240709
Deformation serves as a crucial indicator of the structural changes of dams. Enhancing the prediction accuracy of dam deformation is of paramount significance for the safety and structural control of dams, due to the nonlinear characteristics of deformation data and the underlying intricate mechanism. This paper develops a combined approach for dam deformation prediction based on the integrated modeling concept, integrating an improved wavelet threshold denoising and a Pelican Optimization Algorithm (POA) optimized Bidirectional Long Short-Term Memory (BiLSTM) network. First, the deformation measurement data sequence is processed using an improved wavelet threshold denoising method; then, POA is used to search for the optimal hyperparameter combination to optimize the BiLSTM model; finally, dam deformation prediction is conducted based on the BiLSTM with the optimal hyperparameters. Engineering case studies demonstrate that this improved wavelet threshold method produces superior denoising effects, and POA-BiLSTM gives a satisfactory accuracy for dam deformation prediction. And on the ultimate test set, it has achieved the average MAE, MAPE, RMSE, and R2 of 0.244, 0.041, 0.301, and 0.906, respectively. Compared to other methods, it exhibits higher predictive accuracy and robustness, offering valuable insight for dam deformation monitoring.
2024 Vol. 43 (7): 97-108 [Abstract] ( 50 ) PDF (675 KB)  ( 144 )
109 IT2FS-MARCOS method for risk assessment of water conservancy engineering construction
SUN Kaichang, XUE Wenli, LI Tingting, CHEN Qianqing
DOI: 10.11660/slfdxb.20240710
How to generate a slip surface is one of the key issues in slope stability analysis, and to construct a slip surface with a complex shape is quite challenging. The curve based on the integral of a Logistic function or other basis functions can take the place of the traditional slip surface generated using non-circular curves, which not only improves the smoothness of the slip surface but reduces its degree of freedom. Slip surface generating methods based on basis functions are sorted out in this paper. They are divided into the superposition method of continuous functions and the integral operation method. The characteristics of the Logistic function and its integral are examined carefully, and the influence of different parameters on the curve shape is obtained to narrow parameter ranges. This provides a basis to reduce the degree of freedom of slip surfaces. And a method is presented to determine the initial parameter values of a given slip surface. The calculations of two slope examples show our method is tolerably good in slope stability analysis.
2024 Vol. 43 (7): 109-120 [Abstract] ( 63 ) PDF (634 KB)  ( 204 )
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