Structural health monitoring is an effective method to evaluate the safety status of dams. Measurement error is an important factor which affects the accuracy of monitoring data modeling. Processing the abnormal monitoring data before data analysis is a necessary step to ensure the reliability of the analysis. In this paper, we proposed a method to process the abnormal dam displacement monitoring data on the basis of matrix manipulation and Cuckoo Search algorithm. We first generate a scatter plot of the monitoring data and exported the matrix of the image. The scatter plot of monitoring data includes isolate outliers, clusters of outliers, and clusters of normal points. The gray scales of isolated outliers are reduced using Gaussian blur. Then, the isolated outliers are eliminated using Ostu binarization. We then use the Cuckoo Search algorithm to distinguish the clusters of outliers and clusters of normal points to identify the process line. To evaluate the performance of the proposed data processing method, we also fitted the data processed by the proposed method and by the commonly used 3-$\sigma$ method using a regression model, respectively. Results indicate that the proposed method has a better performance in abnormal detection compared with the 3-$\sigma$ method.

Accurately predicting ski-jump flood discharge atomization is crucial for designing effective disaster-mitigation measures, particularly because low ambient pressure increases the risk of atomized protection in high-altitude regions. However, owing to the complex effects of low ambient pressure on strongly coupled atomized field sources, it is difficult to fully describe the comprehensive behaviour of such sources theoretically, which limits the further development of random splashing numerical models. In this paper, a refined random splashing numerical model characterized by low ambient pressure is developed based on experimental results and applied to high-altitude earth–rockfill dam projects. Compared with the reference ambient pressure condition ( P ₀ = 101.457 kPa), which corresponds to the same flood discharge flow, a decrease in ambient pressure by 0.1P ₀ leads to a maximum change rate not exceeding 10 m for the characteristic boundary of the 10 mm/h atomized rain intensity line at the QX Hydropower Station. This observation also applies to both the 40 mm/h and 10 mm/h atomized rain intensity lines at the RM Hydropower Station. For the two groups of flip bucket types designed for the RM Hydropower station, the loads associated with atomized protection are predominantly concentrated on the left bank. The maximum height of the 10 mm/h atomized rain intensity line affected by atomized rain ranges from 0.83 to 0.85 times the maximum dam height of 315 m. The distance between the farthest downstream boundary and the Spillway No. 3 outlet is between 666.80 and 692.40 metres. Since the flip bucket shape variations only slightly affect the atomization zone extent, further optimization is needed. The study can provide valuable methodological and decision-making support for safeguarding against existing and potential impacts within areas affected by flood discharge atomization from high-altitude hydropower stations.

A better understanding of the atomized rain characteristics in low ambient pressure areas is beneficial in reducing the jeopardizing effect of flood discharge atomization on high-altitude hydropower stations. A random splash experiment is designed with two measurement planes to investigate the effects of low ambient pressure on downstream atomized rain under the complicated conditions of low ambient pressure (within 0.60P₀~1.00P₀) and high waterjet velocity (at a magnitude of 10 m/s). The results demonstrate that the atomized rain (rain intensity ≥ 2 mm/h) downstream, characterized by two-dimensional distribution, can be enhanced by decreasing the ambient pressure and by increasing the inflow discharge. When the ambient pressure decreases at the same inflow discharge, both the distance of the rain intensity lines (40 mm/h, 10 mm/h, 2 mm/h) in the horizontal plane from the constricted nozzle outlet and the average rain amount in the inclined plane within the atomized source ratio of ((0~30) × 10⁻³)% appear as “linear” growth. With the ambient pressure decreasing by 0.10P₀, the range of those characteristic rain intensity lines is expanded by 0.68%~1.37%, and the average rain amount is enlarged by 11.06%~20.48%. When keeping the low ambient pressure unchanged, both the point average rain intensity reduction along the releasing centerline and the surface average rain amount growth with increased inflow discharge all follow an exponential function. The aeration reduction in the waterjet boundary and the resistance reduction in atomized water-droplets are contributing factors for the enhancement effect of low ambient pressure. This study can enable the establishment of a foundation to further predict flood discharge atomization in a high-altitude environment.

Considering the issues of water scarcity, water environment deterioration, and unreasonable allocation of water resources in the urban area of the Yellow River Basin, this paper introduces the human–water harmony theory to the allocation of regional water resources. Based on an analysis of the structural characteristics of the regional water resource system, the harmonious water resource allocation (HWRA) model—which includes three sub-systems (i.e., the water service system, ecological environmental system, and economic and social system)—is established. In addition, considering the uncertain factors in the HWRA model, the inexact fuzzy multi-objective programming (IFMOP) method is used to solve the model, aiming at achieving the minimum amount of regional water scarcity, the minimum amount of sewage discharge, and the maximum total economic benefit. A case study of water resource allocation of Binzhou, a city located in the Yellow River Basin, is conducted to validate the model. The model solution results show that the water resource system in Binzhou in 2025 and 2035 could be optimized after harmonious allocation, especially in terms of the water service and ecological environmental systems. Compared with the optimal water resource allocation (OWRA) model, the HWRA model has a more scientific water supply structure, and a smaller amount of sewage discharge. The HWRA model solves the variables using an interval number, so it can flexibly and scientifically reflect the decision-making process.

The construction and operation of high dam projects at high altitudes have led to concerns about the effectiveness of flood discharge security predictions resulting from the greater flood discharge atomized rain caused by ambient pressure reduction. In this study, self-similar characteristics and variation in atomized raindrop size distributions are analyzed to understand the phenomenon of increased atomized rain intensity under low ambient pressure from a mesoscopic scale. The monographic experiments are characterized by a low ambient pressure range (0.66P₀–1.02P₀) and a high waterjet velocity range (13.89–15.74 m/s). When the ambient pressure decreases by 0.10P₀ (P₀ = 101.325 kPa) from the reference atmospheric pressure condition as the other conditions remain fixed, the total number concentration in a two-dimensional atomized raindrop spectrum (number/(54 cm²)) and the peak value of the individual three-dimensional number concentration (number/(m³·mm) increase, which can lead to the required industry standard protective level of atomized zones increasing by one level in some cases. In addition, the spectrum trend and typical particle size ranges of the atomized raindrop size distributions present self-similarity as the ambient pressure decreases. The above studies further confirm the effects of low-ambient pressure enhancement on flood discharge atomized rain intensity, which can provide a theoretical basis for the development of random splash simulation models characterized by low pressure for high-altitude hydropower stations.

Addressing the challenges of vague ability assessment, delayed teaching adjustment, and fixed cognitive challenge levels in sustainable engineering practice courses, this study proposes a “goal elevation-matrix evaluation-dynamic regulation” tripartite coupled sustainable teaching model. The model employs a value-oriented assessment matrix as the core diagnostic tool, integrating a dual-threshold regulation mechanism and standard iteration strategy within a four-year “design-implementation-diagnosis-iteration” closed loop. Empirical evidence demonstrates that ① a three-tier diagnostic model (overall-module-indicator attainment levels) identifies structural problems of the teaching content and pinpoints the key bottleneck; ② replacing redundant high-scoring modules with basic skill modules eliminates extreme values, improves distribution gradients, and trends to class performance at 75~85%; ③ iterative standard calibration supports progressive student competence development along a “familiar problems → new challenges” pathway. This study provides an empirically validated methodological framework for systematically implementing “scientific rigor, practicality, and appropriate challenge” in engineering practice courses while fostering sustainable engineering literacy.