Water最新文献

{"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}

{"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}

{"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}

{"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}

{"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}

{"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}

{"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}

{"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}

{"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}

{"title":"Requirements for the Development and Operation of a Freeze-Up Ice-Jam Flood Forecasting System","authors":"Karl-Erich Lindenschmidt, Robert Briggs, Amir Ali Khan, Thomas Puestow","doi":"10.3390/w16182648","DOIUrl":"https://doi.org/10.3390/w16182648","url":null,"abstract":"This article provides a comprehensive overview of ice-jam flood forecasting methodologies applicable to rivers during freezing. It emphasizes the importance of understanding river ice processes and fluvial geomorphology for developing a freeze-up ice-jam flood forecasting system. The article showcases a stochastic modelling approach, which involves simulating a deterministic river ice model multiple times with varying parameters and boundary conditions. This approach has been applied to the Exploits River at Badger in Newfoundland, Canada, a river that has experienced several freeze-up ice-jam floods. The forecasting involves two approaches: predicting the extent of the ice cover during river freezing and using an ensemble method to determine backwater flood level elevations. Other examples of current ice-jam flood forecasting systems for the Kokemäenjoki River (Pori, Finland), Saint John River (Edmundston, NB, Canada), and Churchill River (Mud Lake, NL, Canada) that are operational are also presented. The text provides a detailed explanation of the processes involved in river freeze-up and ice-jam formation, as well as the methodologies used for freeze-up ice-jam flood forecasting. Ice-jam flood forecasting systems used for freeze-up were compared to those employed for spring breakup. Spring breakup and freeze-up ice-jam flood forecasting systems differ in their driving factors and methodologies. Spring breakup, driven by snowmelt runoff, typically relies on deterministic and probabilistic approaches to predict peak flows. Freeze-up, driven by cold temperatures, focuses on the complex interactions between atmospheric conditions, river flow, and ice dynamics. Both systems require air temperature forecasts, but snowpack data are more crucial for spring breakup forecasting. To account for uncertainty, both approaches may employ ensemble forecasting techniques, generating multiple forecasts using slightly different initial conditions or model parameters. The objective of this review is to provide an overview of the current state-of-the-art in ice-jam flood forecasting systems and to identify gaps and areas for improvement in existing ice-jam flood forecasting approaches, with a focus on enhancing their accuracy, reliability, and decision-making potential. In conclusion, an effective freeze-up ice-jam flood forecasting system requires real-time data collection and analysis, historical data analysis, ice jam modeling, user interface design, alert systems, and integration with other relevant systems. This combination allows operators to better understand ice jam behavior and make informed decisions about potential risks or mitigation measures to protect people and property along rivers. The key findings of this review are as follows: (i) Ice-jam flood forecasting systems are often based on simple, empirical models that rely heavily on historical data and limited real-time monitoring information. (ii) There is a need for more sophisticated modeling tech","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":"142254616","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}