Aqua Water Infrastructure, Ecosystems and Society

ABSTRACT The deep tunnel storage system, mainly consisting of underground tunnels and dropshafts, is effective for dealing with urban waterlogging. A stepped dropshaft is suitable for the system to safely transport water to underground tunnels and efficiently release air carried by water. In this study, the air inflow discharge, air vent discharge, and air discharge into the underground tunnel are investigated experimentally. As the dimensionless water flow discharge increases to 0.56, the water flow successively forms the nappe flow, transition flow, and skimming flow regimes, the relative air inflow discharge decreases from 0.97 to 0.32, the relative air vent discharge decreases from 0.85 to 0.22, and the relative air discharge into the underground tunnel fluctuates below 0.20. The exhaust capacity (the ratio of the air vent discharge to the air inflow discharge) reaches a maximum of 0.87 at the threshold between the nappe flow and the transition flow. Influences of flow discharge, step height, step rotation angle, outlet diameter of the central exhaust pipe, and underground tunnel blockage on airflow characteristics are revealed. The prediction formulas for air inflow discharge, air vent discharge, and exhaust capacity are obtained with accuracies over 80%, providing a guide to the practical design and operation of stepped dropshafts.

Jingkang Sun

Zhaodan Fei

Shangtuo Qian

Jiangang Feng

Hui Xu

Jiachun Liu

Rui Zhang

AQUA - Water Infrastructure Ecosystems and Society

Airflow characteristics of the stepped dropshaft in the deep tunnel storage system

深隧储水系统中阶梯式跌水井的气流特性

Abstract Population growth and economic development, coupled with water pollution and the frequent occurrence of extreme weather, have led to a growing contradiction between water supply and demand in some regions. To address this challenge, rational and optimal allocation of regional water resources has emerged as a crucial approach. This study focuses on creating a comprehensive model for optimizing regional water resource allocation, taking into account social, economic, and ecological factors. In addition, three innovative modifications are introduced to the firefly algorithm (FA), resulting in the development of the improved firefly algorithm (IFA). The effectiveness of IFA is validated through experiments involving nine benchmark functions. The results highlight the improved search efficiency and convergence achieved by IFA compared to other intelligent algorithms. Moreover, the application of IFA in solving the water resource allocation challenge in Shannxi Province, China, for 2020 and 2021 demonstrates a reduction in the overall water shortage rate to 4.69 and 1.72%, at a 75% guarantee rate. This reduction in water shortages contributes to addressing future scarcities. The proposed allocation scheme offers comprehensive benefits and provides crucial technical support for water resource management. Ultimately, this study offers valuable insights and guidance for addressing the issue of water supply–demand disparities.

Zhiling Yang

Zhaocai Wang

Zhiyuan Yao

Xiaoguang Bao

Optimal allocation planning of regional water resources with multiple objectives using improved firefly algorithm

基于改进萤火虫算法的多目标区域水资源优化配置规划

Gemma Carr

Stacy Langsdale

Building trust with stakeholders in water supply management

在水供应管理中与利益相关者建立信任

ABSTRACT This study evaluates and enhances machine learning models for predicting pan evaporation under diverse climatic conditions. Five fundamental machine learning models were employed and tested across four different stations. Subsequent comparisons were made with advanced techniques, including long short-term memory (LSTM) networks. An innovative approach was introduced, combining LSTM with Binary Al-Biruni Earth Radius (BER–LSTM). This hybrid method was benchmarked against other optimization techniques. The BER–LSTM model consistently outperformed other models across all stations and time scales, achieving up to a 97.54% improvement in root mean square error (RMSE) compared to standard LSTM on daily time scales. Compared to simpler models like Multilayer Perceptron and Support Vector Regressor, BER–LSTM showed even more substantial improvements, with up to a 99.03% reduction in RMSE. The BER–LSTM model demonstrates superior predictive capabilities for pan evaporation across varied climatic conditions, offering significant improvements over both traditional and advanced machine learning techniques. This approach shows promise for enhancing evaporation forecasting in diverse environmental contexts.

Bilel Zerouali

Nadjem Bailek

Kada Bouchouich

Guermoui Mawloud

Alban Kuriqi

Doaa Sami Khafaga

Amal H. Alharbi

El-Sayed M. El-kenawy

Enhancing water security through advanced modeling: integrating deep learning and a novel metaheuristic optimization algorithm for accurate pan evaporation prediction

通过先进建模提升水安全：结合深度学习和新型元启发式优化算法实现精确的蒸发皿蒸发预测

ABSTRACT Multi-objective operation optimization of water distribution systems (WDSs) in large metropolitan areas is essential; however, it is complex and time-consuming. Effective and reliable scheduling of WDSs can significantly enhance the efficiency and reliability of urban water resources management, which requires further research. This paper develops an optimization method combining genetic algorithm and multiple criteria analysis that coordinates energy conservation, hydraulic condition improvement, and water age optimization in WDSs. Results showed that the optimal scheduling method could achieve a 23.0, 16.7, and 2.5% decrease in energy consumption, and water supply volume with unsatisfied pressure, and average water age, respectively. To achieve optimal results, this study indicated that it is crucial to properly allocate water supply volume and pressure across multiple drinking water treatment plants. This finding provides important guidance for water utilities in scheduling. Furthermore, the emergency scenario analysis shows that the newly proposed method can significantly enhance the social and economic sustainability of WDSs through the coordinated optimization of energy consumption, hydraulic conditions, and water age.

Yifan Xie

Yipeng Wu

Ye Jin

Yuxian Li

Bei Zhao

Xiangyi Li

Zhuoran Ba

Shuming Liu

Energy-efficient and reliable coordinated scheduling for water distribution systems: enhancing hydraulic conditions and water quality

水分配系统的节能可靠协同调度：提升水力条件与水质

ABSTRACT The detection of small side branches within underground water pipe networks can be challenging since they are usually subject to many unknown uncertainties. A transient-based method was proposed to detect multi-branching pipes in pipeline systems having uncertainties associated with unknown abnormalities. To isolate the uncertainty signal from the original pressure signal, a polynomial transient model was developed that can address nonlinear transient introduction. Through the superimposition of different pressure signals, the uncertainty signal was delineated to obtain the processed signal for multi-branch prediction. Pipeline systems with two branching pipes were tested under various uncertainties to detect multi-branching pipes. In this study, two transient generation conditions were used: an instant valve closure and a pressure injection. Under several uncertainty conditions, hydraulic pressure damping can be obtained for the detection of two branching pipes under both transient generation conditions. It is possible to predict the locations of multi-branching pipes with a prediction error of less than 10% by using proper signal processing and manipulation for two distinct transient generation methods in a pilot-scale pipeline system with several uncertainties. This study demonstrates the potential for detecting multi-branching pipes in a pipeline system, even with unknown uncertainties for a pipeline system.

Dongwon Ko

Jeongseob Lee

Kwangju Kim

Sanghyun Kim

Detection of multi-branching pipes using transients in a pilot-scale pipeline system with uncertainties

利用瞬变检测中试规模管道系统中不确定性的多分支管道

ABSTRACT Interrill erosion is a major contributor to land degradation, prompting a focus on the interplay between slope, rainfall intensity, and erosion. Our investigation combines two slope types – interrill and artificially created rills – to scrutinize their impact on soil erosion characteristics. Experiments conducted in the LEGHYD laboratory utilized a 1 m2 soil plot with a triangular cross-section channel simulating rills using agricultural soil. Slope values of 3 and 5% were applied to the soil plot, and 15 and 22.5% for the interrill soil. Six artificial rainfall intensities ranging from 101.94 to 31.40 mm·h−1 were utilized. Hydraulic parameters of overland flow for both slopes were assessed concerning sediment concentration. Results indicate insignificant slope effects on flow velocity parameters within the rill but substantial impacts on rainfall-related parameters such as intensity and overland flow power. This underscores the importance of slope characteristics in modulating interrill erosion under simulated rainfall conditions.

Aziz Maaliou

Abderzak Moussouni

Dalila Ziani

Investigation of hydraulic parameters influencing interrill erosion under simulated rainfall conditions

模拟降雨条件下影响细沟间侵蚀的水动力参数研究

短名
Journal Impact	1.95
国际分区	WATER RESOURCES(Q3)
期刊索引	SCI Q3中科院 4 区

ISSN	2709-8028, 2709-8036
h-index	58
国内分区	环境科学与生态学(4区)环境科学与生态学工程土木(4区)环境科学与生态学水资源(4区)

涉及主题	watereutrophicationinfrastructureecosystemssocietysustainability
出版信息	出版商: IWA Publishing，出版周期: ，期刊类型: journal，开源期刊: 是
基本数据	创刊年份: 2021，原创研究文献占比: 95.70%，自引率:14.30%， Gold OA占比: 96.57%
平均审稿周期	20 weeks

Aqua Water Infrastructure, Ecosystems and Society

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Airflow characteristics of the stepped dropshaft in the deep tunnel storage system

Optimal allocation planning of regional water resources with multiple objectives using improved firefly algorithm

Building trust with stakeholders in water supply management

Enhancing water security through advanced modeling: integrating deep learning and a novel metaheuristic optimization algorithm for accurate pan evaporation prediction

Energy-efficient and reliable coordinated scheduling for water distribution systems: enhancing hydraulic conditions and water quality

Building trust with stakeholders in water supply management

Enhancing water security through advanced modeling: integrating deep learning and a novel metaheuristic optimization algorithm for accurate pan evaporation prediction

Airflow characteristics of the stepped dropshaft in the deep tunnel storage system

Detection of multi-branching pipes using transients in a pilot-scale pipeline system with uncertainties

Investigation of hydraulic parameters influencing interrill erosion under simulated rainfall conditions