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The enormous energy carried by discharged water poses a serious threat to the Piano Key Weir (PKW) and its downstream hydraulic structures. However, previous research on energy dissipation in PKWs has mainly focused downstream effects, and the research methods have been largely limited to physical model experiments. To deeply investigate the discharge capacity and hydraulic characteristics of PKW, this study established a PKW model with universally applicable geometric parameters. By combining physical model experiments and numerical simulations, the flow pattern of the PKW, the discharge at the overflow edges, and the variation in the energy dissipation were revealed for different water heads. The results showed that the discharge of the side wall constitutes the majority of the total discharge at low water heads, resulting in a relatively high overall discharge efficiency. As the water head increases, the proportion of discharge from the inlet and outlet keys increases, while the proportion from the side wall decreases. This change results in less discharge from the side wall and a consequent reduction in the overall discharge efficiency. The PKW exhibits superior energy dissipation efficiency under low water heads. However, this efficiency exhibits an inverse relationship with an increasing water head. The overall energy dissipation efficiency can reach 40% to 70%. Additionally, the collision of the water flows inside the outlet chamber and the mixing of the overflow jet play a primary role in energy dissipation. The findings of this study have significant implications for hydraulic engineering construction and PKW operational safety. [ABSTRACT FROM AUTHOR]

Manning's roughness coefficient(n) is considered a key parameter in a one-dimensional (1D) hydrodynamic model. However, it is highly variable and time- and site- dependent. Further, identifying proper n values is not easy, especially in plain looped river network areas. Therefore, a more systematic approach is needed. This study proposes a coupled optimization-simulation model to systematically estimate the spatial distribution of n values. The particle swarm optimization (PSO) algorithm and InfoWorks Integrated Catchment Modelling (ICM) software were integrated to solve the objective function and hydraulic process, respectively. Crisscrossing rivers were partitioned into river reaches that were each assumed to have a uniform and constant Manning's roughness coefficient according to their network topology and cross-section variation. In addition, a sensitivity analysis was implemented to determine the weights of measured data from different gauging stations, and a large difference in the spatial distribution of the sensitivity index illustrated the importance of identifying the weights of multiple stations. Then, a systematic approach was applied to estimate the n values in the Changshu Grand Polder Area (CGPA), which is crisscrossed by 150 rivers, under the water diversion stage. The calculation statistics and efficiency indicated that the proposed method performs well for model calibration. [ABSTRACT FROM AUTHOR]

River water temperature (RWT) forecasting is important for the management of stream ecology. In this paper, a new method based on coupling of wavelet transformation (WT) and artificial intelligence (AI) techniques, including multilayer perceptron neural network (MLPNN) and adaptive neural-fuzzy inference system (ANFIS) for RWT prediction is proposed. The performances of the hybrid models are compared with regular MLPNN and ANFIS models and multiple linear regression (MLR) models for RWT forecasting in two river stations in the Drava River, Croatia. Model performance was evaluated using the coefficient of correlation (R), the Willmott index of agreement (d), the root mean squared error (RMSE), and the mean absolute error (MAE). Results indicate that the combination of WT and AI models (WTMLPNN and WTANFIS) yield better models than the conventional forecasting models for RWT simulation for both regular periods and heatwave events. The MLPNN and ANFIS models outperform the MLR models for RWT simulation for the studied river stations. RMSE values of WTMLPNN2 and WTANFIS2 models range from 1.127 to 1.286 °C, and 1.216 to 1.491 °C for the Botovo and Donji Miholjac stations respectively. Additionally, modeling results further confirm the importance of the day of year (DOY) on the thermal dynamics of the river. The results of this study indicate the potential of coupling of WT and MLPNN, ANFIS models in forecasting RWT. [ABSTRACT FROM AUTHOR]

The centrifugal model test system is utilized to reappear the breaching process of a tailings dam. The results show that there are significant differences in breaching processes between tailings dams and earth-rockfill dams. Influenced by the special physical and mechanical properties of tailings, the breaching processes of tailings dams are of short duration, and the flood flow through the breach increase rapidly. Based on the centrifugal test results, considering the special physical and mechanical properties of tailings, a mathematical model for tailings dam breaching is established. In the model, the vertical undercutting and horizontal expansion are simulated utilizing the erosion rate formula which is derived from shear stress principle of water flow; limit equilibrium method is used to analyze the breach slope stability. In addition, the model adopts iterative calculation method to simulate the whole breaching process. The analysis results show that, the proposed model is applicable in modeling the dam breaching process for tailings dam due to overtopping. [ABSTRACT FROM AUTHOR]