Christian Herrera, Javier Urrutia, Linda Godfrey, Jorge Jódar, Mario Pereira, Constanza Villarroel, Camila Durán, Ivan Soto, Elizabeth J. Lam, Luis Gómez
A hydrogeological study of the shallowest part of the halite nucleus of the Salar de Atacama is presented, focusing on the isotopic variability in δ18O and δ2H (SMOW) in the brine. It is observed that intensive brine extraction has induced upward vertical flows from the lower aquifer, which presents with a lighter isotopic composition (δ18O: −0.87‰ to −2.49‰; δ2H: −26.04‰ to −33.25‰), toward the upper aquifer, which has more variable and enriched isotopic values. Among the possible explanations for the lighter isotopic composition of the lower aquifer waters is the influence of paleolakes formed during the wetter periods of the Late Pleistocene and Holocene that recharged the underlying aquifers. The geological structure of the Salar, including faults and the distribution of low-permeability layers, has played a determining role in the system’s hydrodynamics. This study emphasizes the need for continuous and detailed monitoring of the isotopic composition to assess the sustainability of the water resource in response to brine extraction and future climate changes. Additionally, it suggests applying this methodology to other salt flats in the region for a better understanding of hydrogeological processes in arid zones. The research provides an integrative view of the relationship between resource extraction, water management, and ecosystem conservation in one of the most important salars in the world.
{"title":"An Evaluation of the Brine Flow in the Upper Part of the Halite Nucleus of the Salar de Atacama (Chile) through an Isotopic Study of δ18O and δ2H","authors":"Christian Herrera, Javier Urrutia, Linda Godfrey, Jorge Jódar, Mario Pereira, Constanza Villarroel, Camila Durán, Ivan Soto, Elizabeth J. Lam, Luis Gómez","doi":"10.3390/w16182651","DOIUrl":"https://doi.org/10.3390/w16182651","url":null,"abstract":"A hydrogeological study of the shallowest part of the halite nucleus of the Salar de Atacama is presented, focusing on the isotopic variability in δ18O and δ2H (SMOW) in the brine. It is observed that intensive brine extraction has induced upward vertical flows from the lower aquifer, which presents with a lighter isotopic composition (δ18O: −0.87‰ to −2.49‰; δ2H: −26.04‰ to −33.25‰), toward the upper aquifer, which has more variable and enriched isotopic values. Among the possible explanations for the lighter isotopic composition of the lower aquifer waters is the influence of paleolakes formed during the wetter periods of the Late Pleistocene and Holocene that recharged the underlying aquifers. The geological structure of the Salar, including faults and the distribution of low-permeability layers, has played a determining role in the system’s hydrodynamics. This study emphasizes the need for continuous and detailed monitoring of the isotopic composition to assess the sustainability of the water resource in response to brine extraction and future climate changes. Additionally, it suggests applying this methodology to other salt flats in the region for a better understanding of hydrogeological processes in arid zones. The research provides an integrative view of the relationship between resource extraction, water management, and ecosystem conservation in one of the most important salars in the world.","PeriodicalId":23788,"journal":{"name":"Water","volume":"12 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142254622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Swimming pools are key assets in the hotel industry. With climate change and water stress, more sustainable pools are needed in tourist areas. The study examines the relationship between hotel categories and the consumption of water in swimming pools in a Mediterranean coastal region facing water scarcity. The study focuses on the Costa Brava, with a focus on Lloret de Mar, a popular tourist destination. The research employs a combination of data analysis and the utilisation of evaporation models in order to estimate the consumption of water by swimming pools. The findings indicate that hotels in the higher categories, particularly those with three or four stars, contribute a notable proportion of the total water consumption due to their larger pool sizes and higher guest numbers. The study underscores the necessity for the implementation of sustainable water management strategies, particularly in the context of climate change. It recommends the utilisation of pool water-saving technologies as potential solutions. Furthermore, the paper highlights the broader environmental impact of tourism infrastructure on water resources and suggests policy measures to mitigate these effects. The research aligns with global sustainability goals such as the European Green Deal and the 2030 Agenda.
游泳池是酒店业的重要资产。随着气候变化和水资源紧张，旅游区需要更具可持续性的游泳池。本研究探讨了在缺水的地中海沿岸地区，酒店类别与游泳池耗水量之间的关系。研究以布拉瓦海岸为重点，关注热门旅游目的地 Lloret de Mar。研究采用了数据分析和蒸发模型相结合的方法来估算游泳池的耗水量。研究结果表明，高等级酒店，尤其是三星级或四星级酒店，由于泳池面积较大、入住人数较多，其耗水量在总耗水量中占很大比例。研究强调了实施可持续水资源管理战略的必要性，尤其是在气候变化的背景下。研究建议利用泳池节水技术作为潜在的解决方案。此外，论文还强调了旅游基础设施对水资源的广泛环境影响，并提出了减轻这些影响的政策措施。该研究与欧洲绿色协议和 2030 年议程等全球可持续发展目标相一致。
{"title":"Evaluating the Impact of Hotel Classification on Pool Water Consumption: A Case Study from Costa Brava (Spain)","authors":"Núria Arimany-Serrat, Juan-Jose Gomez-Guillen","doi":"10.3390/w16182658","DOIUrl":"https://doi.org/10.3390/w16182658","url":null,"abstract":"Swimming pools are key assets in the hotel industry. With climate change and water stress, more sustainable pools are needed in tourist areas. The study examines the relationship between hotel categories and the consumption of water in swimming pools in a Mediterranean coastal region facing water scarcity. The study focuses on the Costa Brava, with a focus on Lloret de Mar, a popular tourist destination. The research employs a combination of data analysis and the utilisation of evaporation models in order to estimate the consumption of water by swimming pools. The findings indicate that hotels in the higher categories, particularly those with three or four stars, contribute a notable proportion of the total water consumption due to their larger pool sizes and higher guest numbers. The study underscores the necessity for the implementation of sustainable water management strategies, particularly in the context of climate change. It recommends the utilisation of pool water-saving technologies as potential solutions. Furthermore, the paper highlights the broader environmental impact of tourism infrastructure on water resources and suggests policy measures to mitigate these effects. The research aligns with global sustainability goals such as the European Green Deal and the 2030 Agenda.","PeriodicalId":23788,"journal":{"name":"Water","volume":"16 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142254649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rongbin Zhang, Jingming Hou, Jingsi Li, Tian Wang, Muhammad Imran
Large-scale urban water distribution network simulation plays a critical role in the construction, monitoring, and maintenance of urban water distribution systems. However, during the simulation process, matrix inversion calculations generate a large amount of computational data and consume significant amounts of time, posing challenges for practical applications. To address this issue, this paper proposes a parallel gradient calculation algorithm based on GPU hardware and the CUDA Toolkit library and compares it with the EPANET model and a model based on CPU hardware and the Armadillo library. The results show that the GPU-based model not only achieves a precision level very close to the EPANET model, reaching 99% accuracy, but also significantly outperforms the CPU-based model. Furthermore, during the simulation, the GPU architecture is able to efficiently handle large-scale data and achieve faster convergence, significantly reducing the overall simulation time. Particularly in handling larger-scale water distribution networks, the GPU architecture can improve computational efficiency by up to 13 times. Further analysis reveals that different GPU models exhibit significant differences in computational efficiency, with memory capacity being a key factor affecting performance. GPU devices with larger memory capacity demonstrate higher computational efficiency when processing large-scale water distribution networks. This study demonstrates the advantages of GPU acceleration technology in the simulation of large-scale urban water distribution networks and provides important theoretical and technical support for practical applications in this field. By carefully selecting and configuring GPU devices, the computational efficiency of large-scale water distribution networks can be significantly improved, providing more efficient solutions for future urban water resource management and planning.
大规模城市配水管网模拟在城市配水系统的建设、监测和维护中发挥着至关重要的作用。然而，在仿真过程中，矩阵反演计算会产生大量计算数据并消耗大量时间，这给实际应用带来了挑战。为解决这一问题，本文提出了一种基于 GPU 硬件和 CUDA 工具包库的并行梯度计算算法，并将其与 EPANET 模型以及基于 CPU 硬件和 Armadillo 库的模型进行了比较。结果表明，基于 GPU 的模型不仅达到了与 EPANET 模型非常接近的精度水平，准确率达到 99%，而且明显优于基于 CPU 的模型。此外，在仿真过程中，GPU 架构能够有效地处理大规模数据并实现更快的收敛，从而大大缩短了整体仿真时间。特别是在处理更大规模的配水管网时，GPU 架构可将计算效率提高 13 倍。进一步的分析表明，不同的 GPU 模型在计算效率方面存在显著差异，而内存容量是影响性能的关键因素。内存容量较大的 GPU 设备在处理大规模配水管网时表现出更高的计算效率。这项研究证明了 GPU 加速技术在大规模城市配水管网仿真中的优势，并为该领域的实际应用提供了重要的理论和技术支持。通过精心选择和配置 GPU 设备，可以显著提高大规模配水管网的计算效率，为未来城市水资源管理和规划提供更高效的解决方案。
{"title":"Study on Large-Scale Urban Water Distribution Network Computation Method Based on a GPU Framework","authors":"Rongbin Zhang, Jingming Hou, Jingsi Li, Tian Wang, Muhammad Imran","doi":"10.3390/w16182642","DOIUrl":"https://doi.org/10.3390/w16182642","url":null,"abstract":"Large-scale urban water distribution network simulation plays a critical role in the construction, monitoring, and maintenance of urban water distribution systems. However, during the simulation process, matrix inversion calculations generate a large amount of computational data and consume significant amounts of time, posing challenges for practical applications. To address this issue, this paper proposes a parallel gradient calculation algorithm based on GPU hardware and the CUDA Toolkit library and compares it with the EPANET model and a model based on CPU hardware and the Armadillo library. The results show that the GPU-based model not only achieves a precision level very close to the EPANET model, reaching 99% accuracy, but also significantly outperforms the CPU-based model. Furthermore, during the simulation, the GPU architecture is able to efficiently handle large-scale data and achieve faster convergence, significantly reducing the overall simulation time. Particularly in handling larger-scale water distribution networks, the GPU architecture can improve computational efficiency by up to 13 times. Further analysis reveals that different GPU models exhibit significant differences in computational efficiency, with memory capacity being a key factor affecting performance. GPU devices with larger memory capacity demonstrate higher computational efficiency when processing large-scale water distribution networks. This study demonstrates the advantages of GPU acceleration technology in the simulation of large-scale urban water distribution networks and provides important theoretical and technical support for practical applications in this field. By carefully selecting and configuring GPU devices, the computational efficiency of large-scale water distribution networks can be significantly improved, providing more efficient solutions for future urban water resource management and planning.","PeriodicalId":23788,"journal":{"name":"Water","volume":"201 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142254563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Víctor Pocco, Arleth Mendoza, Samuel Chucuya, Pablo Franco-León, Germán Huayna, Eusebio Ingol-Blanco, Edwin Pino-Vargas
Natural aquifers used for human consumption are among the most important resources in the world. The Locumba basin faces significant challenges due to its limited water availability for the local population. In this way, the search for possible aquifer recharge zones is crucial work for urban development in areas that have water scarcity. To evaluate this problem, this research proposes the use of the hybrid Fuzzy AHP methodology in conjunction with the TOPSIS algorithm to obtain a potential aquifer recharge map. Ten factors that influence productivity and capacity in an aquifer were implemented, which were subjected to Fuzzy AHP to obtain their weighting. Using the TOPSIS algorithm, the delineation of the most favorable areas with high recharge potential was established. The result shows that the most influential factors for recharge are precipitation, permeability, and slopes, which obtained the highest weights of 0.22, 0.19, and 0.17, respectively. In parallel, the TOPSIS result highlights the potential recharge zones distributed in the Locumba basin, which were classified into five categories: very high (13%), high (28%), moderate (15%), low (28%), and very low (16%). The adapted methodology in this research seeks to be the first step toward effective water resource management in the study area.
{"title":"Assessment of Potential Aquifer Recharge Zones in the Locumba Basin, Arid Region of the Atacama Desert Using Integration of Two MCDM Methods: Fuzzy AHP and TOPSIS","authors":"Víctor Pocco, Arleth Mendoza, Samuel Chucuya, Pablo Franco-León, Germán Huayna, Eusebio Ingol-Blanco, Edwin Pino-Vargas","doi":"10.3390/w16182643","DOIUrl":"https://doi.org/10.3390/w16182643","url":null,"abstract":"Natural aquifers used for human consumption are among the most important resources in the world. The Locumba basin faces significant challenges due to its limited water availability for the local population. In this way, the search for possible aquifer recharge zones is crucial work for urban development in areas that have water scarcity. To evaluate this problem, this research proposes the use of the hybrid Fuzzy AHP methodology in conjunction with the TOPSIS algorithm to obtain a potential aquifer recharge map. Ten factors that influence productivity and capacity in an aquifer were implemented, which were subjected to Fuzzy AHP to obtain their weighting. Using the TOPSIS algorithm, the delineation of the most favorable areas with high recharge potential was established. The result shows that the most influential factors for recharge are precipitation, permeability, and slopes, which obtained the highest weights of 0.22, 0.19, and 0.17, respectively. In parallel, the TOPSIS result highlights the potential recharge zones distributed in the Locumba basin, which were classified into five categories: very high (13%), high (28%), moderate (15%), low (28%), and very low (16%). The adapted methodology in this research seeks to be the first step toward effective water resource management in the study area.","PeriodicalId":23788,"journal":{"name":"Water","volume":"15 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142254615","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Bharat Manna, Emma Jay, Wensi Zhang, Xueyang Zhou, Boyu Lyu, Gevargis Muramthookil Thomas, Naresh Singhal
Climate change threatens freshwater ecosystems, potentially intensifying cyanobacterial blooms and antibiotic resistance. We investigated these risks in Cosseys Reservoir, New Zealand, using short-term warming simulations (22 °C, 24 °C, and 27 °C) with additional oxidative stress treatments. A metagenomic analysis revealed significant community shifts under warming. The cyanobacterial abundance increased from 6.11% to 20.53% at 24 °C, with Microcystaceae and Nostocaceae proliferating considerably. The microcystin synthesis gene (mcy) cluster showed a strong association with cyanobacterial abundance. Cyanobacteria exhibited enhanced nutrient acquisition (pstS gene) and an upregulated nitrogen metabolism under warming. Concurrently, antibiotic resistance genes (ARGs) increased, particularly multidrug resistance genes (50.82% of total ARGs). A co-association network analysis identified the key antibiotic-resistant bacteria (e.g., Streptococcus pneumoniae and Acinetobacter baylyi) and ARGs (e.g., acrB, MexK, rpoB2, and bacA) central to resistance dissemination under warming conditions. Oxidative stress exacerbated both cyanobacterial growth and ARGs’ proliferation, especially efflux pump genes (e.g., acrB, adeJ, ceoB, emrB, MexK, and muxB). This study demonstrated that even modest warming (2–5 °C) could promote both toxic cyanobacteria and antibiotic resistance. These findings underscore the synergistic effects of temperature and oxidative stress posed by climate change on water quality and public health, emphasizing the need for targeted management strategies in freshwater ecosystems. Future research should focus on long-term impacts and potential mitigation measures.
{"title":"Short-Term Warming Induces Cyanobacterial Blooms and Antibiotic Resistance in Freshwater Lake, as Revealed by Metagenomics Analysis","authors":"Bharat Manna, Emma Jay, Wensi Zhang, Xueyang Zhou, Boyu Lyu, Gevargis Muramthookil Thomas, Naresh Singhal","doi":"10.3390/w16182655","DOIUrl":"https://doi.org/10.3390/w16182655","url":null,"abstract":"Climate change threatens freshwater ecosystems, potentially intensifying cyanobacterial blooms and antibiotic resistance. We investigated these risks in Cosseys Reservoir, New Zealand, using short-term warming simulations (22 °C, 24 °C, and 27 °C) with additional oxidative stress treatments. A metagenomic analysis revealed significant community shifts under warming. The cyanobacterial abundance increased from 6.11% to 20.53% at 24 °C, with Microcystaceae and Nostocaceae proliferating considerably. The microcystin synthesis gene (mcy) cluster showed a strong association with cyanobacterial abundance. Cyanobacteria exhibited enhanced nutrient acquisition (pstS gene) and an upregulated nitrogen metabolism under warming. Concurrently, antibiotic resistance genes (ARGs) increased, particularly multidrug resistance genes (50.82% of total ARGs). A co-association network analysis identified the key antibiotic-resistant bacteria (e.g., Streptococcus pneumoniae and Acinetobacter baylyi) and ARGs (e.g., acrB, MexK, rpoB2, and bacA) central to resistance dissemination under warming conditions. Oxidative stress exacerbated both cyanobacterial growth and ARGs’ proliferation, especially efflux pump genes (e.g., acrB, adeJ, ceoB, emrB, MexK, and muxB). This study demonstrated that even modest warming (2–5 °C) could promote both toxic cyanobacteria and antibiotic resistance. These findings underscore the synergistic effects of temperature and oxidative stress posed by climate change on water quality and public health, emphasizing the need for targeted management strategies in freshwater ecosystems. Future research should focus on long-term impacts and potential mitigation measures.","PeriodicalId":23788,"journal":{"name":"Water","volume":"27 15 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142254623","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The water supply pipeline is regarded as the “lifeline” of the city. In recent years, pipeline accidents caused by aging and other factors are common and have caused large economic losses. Therefore, in order to avoid large economic losses, it is necessary to analyze the failure prediction of pipelines so that the pipelines that are going to fail can be replaced in a timely manner. In this paper, we propose a method for predicting the failure pressure of pipelines, i.e., a genetic algorithm was used to optimize the weights and thresholds of a BP neural network. The first step was to determine the topology of the neural network and the number of input and output variables. The second step was to optimize the weights and thresholds initially set for the back propagation neural network using a genetic algorithm. Finally, the optimized back-propagation neural network was used to simulate and predict pipeline failures. It was proved by examples that compared with the separate back propagation neural network model and the optimized and trained genetic algorithm-back propagation neural network, the model performed better in simulation prediction, and the prediction accuracy could reach up to 91%, whereas the unoptimized back propagation neural network model could only reach 85%. It is feasible to apply this model for fault prediction of pipelines.
供水管道被视为城市的 "生命线"。近年来，由于老化等因素造成的管道事故屡见不鲜，并造成了较大的经济损失。因此，为了避免较大的经济损失，有必要对管道的失效预测进行分析，以便及时更换即将失效的管道。本文提出了一种预测管道失效压力的方法，即利用遗传算法优化 BP 神经网络的权值和阈值。第一步是确定神经网络的拓扑结构以及输入和输出变量的数量。第二步是利用遗传算法优化反向传播神经网络最初设定的权重和阈值。最后，利用优化后的反向传播神经网络来模拟和预测管道故障。实例证明，与单独的反向传播神经网络模型和经过优化和训练的遗传算法反向传播神经网络相比，该模型在模拟预测方面表现更好，预测准确率可达 91%，而未经优化的反向传播神经网络模型只能达到 85%。将该模型应用于管道故障预测是可行的。
{"title":"Research on Failure Pressure Prediction of Water Supply Pipe Based on GA-BP Neural Network","authors":"Qingfu Li, Zeyi Li","doi":"10.3390/w16182659","DOIUrl":"https://doi.org/10.3390/w16182659","url":null,"abstract":"The water supply pipeline is regarded as the “lifeline” of the city. In recent years, pipeline accidents caused by aging and other factors are common and have caused large economic losses. Therefore, in order to avoid large economic losses, it is necessary to analyze the failure prediction of pipelines so that the pipelines that are going to fail can be replaced in a timely manner. In this paper, we propose a method for predicting the failure pressure of pipelines, i.e., a genetic algorithm was used to optimize the weights and thresholds of a BP neural network. The first step was to determine the topology of the neural network and the number of input and output variables. The second step was to optimize the weights and thresholds initially set for the back propagation neural network using a genetic algorithm. Finally, the optimized back-propagation neural network was used to simulate and predict pipeline failures. It was proved by examples that compared with the separate back propagation neural network model and the optimized and trained genetic algorithm-back propagation neural network, the model performed better in simulation prediction, and the prediction accuracy could reach up to 91%, whereas the unoptimized back propagation neural network model could only reach 85%. It is feasible to apply this model for fault prediction of pipelines.","PeriodicalId":23788,"journal":{"name":"Water","volume":"42 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142254648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nikolay Aniskin, Andrey Stupivtsev, Stanislav Sergeev, Ilia Bokov
This article addresses the reliability and safety of an earth dam in the case of a change in the reservoir water level. The water level must often be reduced to remove water or as a response to an emergency situation in the process of operation of a hydraulic structure. Lower water levels change seepage conditions, such as the surface of depression, values and directions of seepage gradients, seepage rates, and volumetric hydrodynamic loading. Practical hydraulic engineering shows that these changes can have a number of negative consequences. Higher seepage gradients can lead to seepage-triggered deformations in the vicinity of the upstream slope of a structure. Hydrodynamic loads, arising during drawdown, reduce the stability of an upstream slope of a dam and cause its failure. Potential consequences of a drawdown can be evaluated by solving the problem of drawdown seepage for the dam body and base. A numerical solution to this problem is based on the finite element method applied using the PLAXIS 2D software package. Results thus obtained are compared with those obtained using the finite element method in the locally variational formulation. A numerical experiment was conducted to analyze factors affecting the value of the maximum seepage gradient and stability of the earth dam slope. Recommendations were formulated to limit the drawdown parameters and to ensure the safe operation of a structure.
{"title":"The Drawdown of a Reservoir: Its Effect on Seepage Conditions and Stability of Earth Dams","authors":"Nikolay Aniskin, Andrey Stupivtsev, Stanislav Sergeev, Ilia Bokov","doi":"10.3390/w16182660","DOIUrl":"https://doi.org/10.3390/w16182660","url":null,"abstract":"This article addresses the reliability and safety of an earth dam in the case of a change in the reservoir water level. The water level must often be reduced to remove water or as a response to an emergency situation in the process of operation of a hydraulic structure. Lower water levels change seepage conditions, such as the surface of depression, values and directions of seepage gradients, seepage rates, and volumetric hydrodynamic loading. Practical hydraulic engineering shows that these changes can have a number of negative consequences. Higher seepage gradients can lead to seepage-triggered deformations in the vicinity of the upstream slope of a structure. Hydrodynamic loads, arising during drawdown, reduce the stability of an upstream slope of a dam and cause its failure. Potential consequences of a drawdown can be evaluated by solving the problem of drawdown seepage for the dam body and base. A numerical solution to this problem is based on the finite element method applied using the PLAXIS 2D software package. Results thus obtained are compared with those obtained using the finite element method in the locally variational formulation. A numerical experiment was conducted to analyze factors affecting the value of the maximum seepage gradient and stability of the earth dam slope. Recommendations were formulated to limit the drawdown parameters and to ensure the safe operation of a structure.","PeriodicalId":23788,"journal":{"name":"Water","volume":"15 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142254650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Aldona Dobrzycka-Krahel, Michał E. Skóra, Michał Raczyński, Katarzyna Magdoń
Various biological traits support the invasive success of different organisms. The osmoregulatory capacity and food preferences of the signal crayfish Pacifastacus leniusculus were experimentally tested to determine if they contribute to its invasive success. The osmotic concentrations of haemolymph were determined after acclimation of the crustaceans to seven salinities from 0 to 20 PSU. Food preferences were tested using Canadian pondweed Elodea canadensis, and rainbow trout Oncorhynchus mykiss. The results showed that the signal crayfish exhibits a hyper-hypoosmotic regulation pattern in the salinity range from 0 to 20 PSU, enabling them to inhabit both freshwater and brackish environments. Furthermore, the study found signal crayfish to have non-specific food preferences, although fish muscle tissue is more beneficial as a source of energy. Both features, osmoregulatory ability and food preferences, can increase the invasive success of this species as it expands into new areas. The ability to survive in higher salinities compared to the coastal waters of the Baltic Sea along the Polish coastline should be considered in targeted management strategies to control the spread of this invasive species.
{"title":"Osmoregulatory Capacity and Non-Specific Food Preferences as Strengths Contributing to the Invasive Success of the Signal Crayfish Pacifastacus leniusculus: Management Implications","authors":"Aldona Dobrzycka-Krahel, Michał E. Skóra, Michał Raczyński, Katarzyna Magdoń","doi":"10.3390/w16182657","DOIUrl":"https://doi.org/10.3390/w16182657","url":null,"abstract":"Various biological traits support the invasive success of different organisms. The osmoregulatory capacity and food preferences of the signal crayfish Pacifastacus leniusculus were experimentally tested to determine if they contribute to its invasive success. The osmotic concentrations of haemolymph were determined after acclimation of the crustaceans to seven salinities from 0 to 20 PSU. Food preferences were tested using Canadian pondweed Elodea canadensis, and rainbow trout Oncorhynchus mykiss. The results showed that the signal crayfish exhibits a hyper-hypoosmotic regulation pattern in the salinity range from 0 to 20 PSU, enabling them to inhabit both freshwater and brackish environments. Furthermore, the study found signal crayfish to have non-specific food preferences, although fish muscle tissue is more beneficial as a source of energy. Both features, osmoregulatory ability and food preferences, can increase the invasive success of this species as it expands into new areas. The ability to survive in higher salinities compared to the coastal waters of the Baltic Sea along the Polish coastline should be considered in targeted management strategies to control the spread of this invasive species.","PeriodicalId":23788,"journal":{"name":"Water","volume":"69 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142254647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Floods are normal components of many river regimes and, as such, they exert a significant influence at the ecosystem level. In recent decades, however, climate change has increased the frequency and intensity of floods, with serious consequences for lotic biota, particularly benthic macroinvertebrates, due to their limited mobility and sensitivity to disturbance. The impact of floods varies according to different biological parameters including the characteristics of the macrobenthic communities (taxonomic composition, morphology, behaviour, and life history traits) on one hand and various nonbiological parameters such as flood intensity, artificialisation of the river bed, the presence of dams, and many other factors on the other. Understanding these dynamics is pivotal to improve the effective management and conservation of aquatic ecosystems in the context of current climate change. The aim of this short communication is to evaluate the impact of a catastrophic flood on the macroinvertebrate community of a low-order Appennine stream (NW Italy). This will provide data regarding the varying impacts on different taxa and the recovery pattern of this significant component of the ecosystem.
{"title":"The Impact of Catastrophic Floods on Macroinvertebrate Communities in Low-Order Streams: A Study from the Apennines (Northwest Italy)","authors":"Anna Marino, Stefano Fenoglio, Tiziano Bo","doi":"10.3390/w16182646","DOIUrl":"https://doi.org/10.3390/w16182646","url":null,"abstract":"Floods are normal components of many river regimes and, as such, they exert a significant influence at the ecosystem level. In recent decades, however, climate change has increased the frequency and intensity of floods, with serious consequences for lotic biota, particularly benthic macroinvertebrates, due to their limited mobility and sensitivity to disturbance. The impact of floods varies according to different biological parameters including the characteristics of the macrobenthic communities (taxonomic composition, morphology, behaviour, and life history traits) on one hand and various nonbiological parameters such as flood intensity, artificialisation of the river bed, the presence of dams, and many other factors on the other. Understanding these dynamics is pivotal to improve the effective management and conservation of aquatic ecosystems in the context of current climate change. The aim of this short communication is to evaluate the impact of a catastrophic flood on the macroinvertebrate community of a low-order Appennine stream (NW Italy). This will provide data regarding the varying impacts on different taxa and the recovery pattern of this significant component of the ecosystem.","PeriodicalId":23788,"journal":{"name":"Water","volume":"42 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142254567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nari Kim, Soo-Jin Lee, Eunha Sohn, Mija Kim, Seonkyeong Seong, Seung Hee Kim, Yangwon Lee
Soil moisture is a critical parameter that significantly impacts the global energy balance, including the hydrologic cycle, land–atmosphere interactions, soil evaporation, and plant growth. Currently, soil moisture is typically measured by installing sensors in the ground or through satellite remote sensing, with data retrieval facilitated by reanalysis models such as the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5 (ERA5) and the Global Land Data Assimilation System (GLDAS). However, the suitability of these methods for capturing local-scale variabilities is insufficiently validated, particularly in regions like South Korea, where land surfaces are highly complex and heterogeneous. In contrast, artificial intelligence (AI) approaches have shown promising potential for soil moisture retrieval at the local scale but have rarely demonstrated substantial products for spatially continuous grids. This paper presents the retrieval of daily soil moisture (SM) over a 500 m grid for croplands in South Korea using random forest (RF) and automated machine learning (AutoML) models, leveraging satellite images and meteorological data. In a blind test conducted for the years 2013–2019, the AutoML-based SM model demonstrated optimal performance, achieving a root mean square error of 2.713% and a correlation coefficient of 0.940. Furthermore, the performance of the AutoML model remained consistent across all the years and months, as well as under extreme weather conditions, indicating its reliability and stability. Comparing the soil moisture data derived from our AutoML model with the reanalysis data from sources such as the European Space Agency Climate Change Initiative (ESA CCI), GLDAS, the Local Data Assimilation and Prediction System (LDAPS), and ERA5 for the South Korea region reveals that our AutoML model provides a much better representation. These experiments confirm the feasibility of AutoML-based SM retrieval, particularly for local agrometeorological applications in regions with heterogeneous land surfaces like South Korea.
{"title":"An Automated Machine Learning Approach to the Retrieval of Daily Soil Moisture in South Korea Using Satellite Images, Meteorological Data, and Digital Elevation Model","authors":"Nari Kim, Soo-Jin Lee, Eunha Sohn, Mija Kim, Seonkyeong Seong, Seung Hee Kim, Yangwon Lee","doi":"10.3390/w16182661","DOIUrl":"https://doi.org/10.3390/w16182661","url":null,"abstract":"Soil moisture is a critical parameter that significantly impacts the global energy balance, including the hydrologic cycle, land–atmosphere interactions, soil evaporation, and plant growth. Currently, soil moisture is typically measured by installing sensors in the ground or through satellite remote sensing, with data retrieval facilitated by reanalysis models such as the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5 (ERA5) and the Global Land Data Assimilation System (GLDAS). However, the suitability of these methods for capturing local-scale variabilities is insufficiently validated, particularly in regions like South Korea, where land surfaces are highly complex and heterogeneous. In contrast, artificial intelligence (AI) approaches have shown promising potential for soil moisture retrieval at the local scale but have rarely demonstrated substantial products for spatially continuous grids. This paper presents the retrieval of daily soil moisture (SM) over a 500 m grid for croplands in South Korea using random forest (RF) and automated machine learning (AutoML) models, leveraging satellite images and meteorological data. In a blind test conducted for the years 2013–2019, the AutoML-based SM model demonstrated optimal performance, achieving a root mean square error of 2.713% and a correlation coefficient of 0.940. Furthermore, the performance of the AutoML model remained consistent across all the years and months, as well as under extreme weather conditions, indicating its reliability and stability. Comparing the soil moisture data derived from our AutoML model with the reanalysis data from sources such as the European Space Agency Climate Change Initiative (ESA CCI), GLDAS, the Local Data Assimilation and Prediction System (LDAPS), and ERA5 for the South Korea region reveals that our AutoML model provides a much better representation. These experiments confirm the feasibility of AutoML-based SM retrieval, particularly for local agrometeorological applications in regions with heterogeneous land surfaces like South Korea.","PeriodicalId":23788,"journal":{"name":"Water","volume":"11 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142254651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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