Researchers and environmental managers need big datasets spanning long time periods to accurately assess current and historical water quality conditions in fresh and estuarine waters. Using remote sensing data, we can survey many water bodies simultaneously and evaluate water quality conditions with greater frequency. The combination of existing and historical water quality data with remote sensing imagery into a unified database allows researchers to improve remote sensing algorithms and improves understanding of mechanisms causing blooms. We report on the development of a water quality database "EstuarySAT" which combines data from the Sentinel-2 multi-spectral instrument (MSI) remote sensing platform and water quality data throughout the coastal USA. EstuarySAT builds upon an existing database and set of methods developed by the creators of AquaSat, whose region of interest is primarily larger freshwater lakes in the USA. Following the same basic methods, EstuarySAT utilizes open-source tools: R v. 3.24+ (statistical software), Python (dynamic programming environment), and Google Earth Engine (GEE) to develop a combined water quality data and remote sensing imagery database (EstuarySAT) for smaller coastal estuarine and freshwater tidal riverine systems. EstuarySAT fills a data gap that exists between freshwater and estuarine water bodies. We are able to evaluate smaller systems due to the higher spatial resolution of Sentinel-2 (10 m pixel image resolution) vs. the Landsat platform used by AquaSat (30 m pixel resolution). Sentinel-2 also has a more frequent revisit (overpass) schedule of every 5 to 10 days vs. Landsat 7 which is every 17 days. EstuarySAT incorporates publicly available water quality data from 23 individual water quality data sources spanning 1984-2021 and spatially matches them with Sentinel-2 imagery from 2015-2021. EstuarySAT currently contains 299,851 matched observations distributed across the coastal USA. EstuarySAT's primary focus is on collecting chlorophyll data; however, it also contains other ancillary water quality data, including temperature, salinity, pH, dissolved oxygen, dissolved organic carbon, and turbidity (where available). As compared to other ocean color databases used for developing predictive chlorophyll algorithms, this coastal database contains spectral profiles more typical of CDOM-dominated systems. This database can assist researchers and managers in evaluating algal bloom causes and predicting the occurrence of future blooms.
{"title":"EstuarySAT Database Development of Harmonized Remote Sensing and Water Quality Data for Tidal and Estuarine Systems.","authors":"Steven A Rego, Naomi E Detenbeck, Xiao Shen","doi":"10.3390/w16192721","DOIUrl":"10.3390/w16192721","url":null,"abstract":"<p><p>Researchers and environmental managers need big datasets spanning long time periods to accurately assess current and historical water quality conditions in fresh and estuarine waters. Using remote sensing data, we can survey many water bodies simultaneously and evaluate water quality conditions with greater frequency. The combination of existing and historical water quality data with remote sensing imagery into a unified database allows researchers to improve remote sensing algorithms and improves understanding of mechanisms causing blooms. We report on the development of a water quality database \"EstuarySAT\" which combines data from the Sentinel-2 multi-spectral instrument (MSI) remote sensing platform and water quality data throughout the coastal USA. EstuarySAT builds upon an existing database and set of methods developed by the creators of AquaSat, whose region of interest is primarily larger freshwater lakes in the USA. Following the same basic methods, EstuarySAT utilizes open-source tools: R v. 3.24+ (statistical software), Python (dynamic programming environment), and Google Earth Engine (GEE) to develop a combined water quality data and remote sensing imagery database (EstuarySAT) for smaller coastal estuarine and freshwater tidal riverine systems. EstuarySAT fills a data gap that exists between freshwater and estuarine water bodies. We are able to evaluate smaller systems due to the higher spatial resolution of Sentinel-2 (10 m pixel image resolution) vs. the Landsat platform used by AquaSat (30 m pixel resolution). Sentinel-2 also has a more frequent revisit (overpass) schedule of every 5 to 10 days vs. Landsat 7 which is every 17 days. EstuarySAT incorporates publicly available water quality data from 23 individual water quality data sources spanning 1984-2021 and spatially matches them with Sentinel-2 imagery from 2015-2021. EstuarySAT currently contains 299,851 matched observations distributed across the coastal USA. EstuarySAT's primary focus is on collecting chlorophyll data; however, it also contains other ancillary water quality data, including temperature, salinity, pH, dissolved oxygen, dissolved organic carbon, and turbidity (where available). As compared to other ocean color databases used for developing predictive chlorophyll algorithms, this coastal database contains spectral profiles more typical of CDOM-dominated systems. This database can assist researchers and managers in evaluating algal bloom causes and predicting the occurrence of future blooms.</p>","PeriodicalId":23788,"journal":{"name":"Water","volume":"16 19","pages":"2721"},"PeriodicalIF":3.0,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11534012/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142583740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pulwansha Amandi Thilakarathna, Fazla Fareed, Madhubhashini Makehelwala, Sujithra K. Weragoda, Ruchika Fernando, Thejani Premachandra, Mangala Rajapakse, Yuansong Wei, Min Yang, S. H. P. Parakrama Karunaratne
Exploration of the pollution status of river-based water sources is important to ensure quality and safe drinking water supply for the public. The present study investigated physicochemical parameters of surface water in the upper segment of River Mahaweli, which provides drinking water to the Nuwara Eliya and Kandy districts of Sri Lanka. River surface water from 15 intakes and treated water from 14 Water Treatment Plants (WTPs) were tested for pH, water temperature, turbidity, EC, COD, 6 anions, 21 cations, 3 pesticides, and 30 antibiotics once every 3 months from June 2022 to July 2023. Except for turbidity and iron concentrations, all other parameters were within the permissible range as per the Sri Lanka Standard Specification for Potable Water (SLS 614:2013). The uppermost Kotagala WTP raw water had a high concentration of iron due to runoff from areas with abundant iron-bearing minerals. Turbidity increased as the river flowed downstream, reaching its highest value of 13.43 NTU at the lowermost Haragama. Four intakes had raw surface water suitable for drinking as per the Water Quality Index (WQI). Pollution increased gradually towards downstream mainly due to agricultural runoff, industrial effluents, and urbanization. Poor water quality at the upstream Thalawakale-Nanuoya intake was due to highly contaminated effluent water coming from Lake Gregory in Nuwara Eliya. Cluster analysis categorized WTP locations in the river segment into 3 clusters as low, moderate, and high based on contaminations. Principal component analysis revealed that the significance of the 41.56% variance of the raw water was due to the pH and the presence of heavy metals V, Cr, Ni, Rb, Co, Sr, and As. All treated water from 15 WTPs had very good to excellent quality. In general, heavy metal contamination was low as indicated by the heavy metal pollution index (HPI) and heavy metal evaluation index (HEI). The treatment process could remove up to 94.7% of the turbidity. This is the first attempt to cluster the river catchment of the Mahaweli River based on physicochemical parameters of river water. We present here the land-use pattern-based pollution of the river and efficacy of the water treatment process using the Mahaweli River Basin as a case study. Regular monitoring and treatment adjustments at identified points are recommended to maintain the delivery of safe drinking water.
{"title":"Land-Use Pattern-Based Spatial Variation of Physicochemical Parameters and Efficacy of Safe Drinking Water Supply along the Mahaweli River, Sri Lanka","authors":"Pulwansha Amandi Thilakarathna, Fazla Fareed, Madhubhashini Makehelwala, Sujithra K. Weragoda, Ruchika Fernando, Thejani Premachandra, Mangala Rajapakse, Yuansong Wei, Min Yang, S. H. P. Parakrama Karunaratne","doi":"10.3390/w16182644","DOIUrl":"https://doi.org/10.3390/w16182644","url":null,"abstract":"Exploration of the pollution status of river-based water sources is important to ensure quality and safe drinking water supply for the public. The present study investigated physicochemical parameters of surface water in the upper segment of River Mahaweli, which provides drinking water to the Nuwara Eliya and Kandy districts of Sri Lanka. River surface water from 15 intakes and treated water from 14 Water Treatment Plants (WTPs) were tested for pH, water temperature, turbidity, EC, COD, 6 anions, 21 cations, 3 pesticides, and 30 antibiotics once every 3 months from June 2022 to July 2023. Except for turbidity and iron concentrations, all other parameters were within the permissible range as per the Sri Lanka Standard Specification for Potable Water (SLS 614:2013). The uppermost Kotagala WTP raw water had a high concentration of iron due to runoff from areas with abundant iron-bearing minerals. Turbidity increased as the river flowed downstream, reaching its highest value of 13.43 NTU at the lowermost Haragama. Four intakes had raw surface water suitable for drinking as per the Water Quality Index (WQI). Pollution increased gradually towards downstream mainly due to agricultural runoff, industrial effluents, and urbanization. Poor water quality at the upstream Thalawakale-Nanuoya intake was due to highly contaminated effluent water coming from Lake Gregory in Nuwara Eliya. Cluster analysis categorized WTP locations in the river segment into 3 clusters as low, moderate, and high based on contaminations. Principal component analysis revealed that the significance of the 41.56% variance of the raw water was due to the pH and the presence of heavy metals V, Cr, Ni, Rb, Co, Sr, and As. All treated water from 15 WTPs had very good to excellent quality. In general, heavy metal contamination was low as indicated by the heavy metal pollution index (HPI) and heavy metal evaluation index (HEI). The treatment process could remove up to 94.7% of the turbidity. This is the first attempt to cluster the river catchment of the Mahaweli River based on physicochemical parameters of river water. We present here the land-use pattern-based pollution of the river and efficacy of the water treatment process using the Mahaweli River Basin as a case study. Regular monitoring and treatment adjustments at identified points are recommended to maintain the delivery of safe drinking water.","PeriodicalId":23788,"journal":{"name":"Water","volume":"117 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142254565","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}
China’s southwestern region boasts abundant hydropower resources. However, the area is prone to frequent strong earthquakes. The areas surrounding dam sites typically have deep overburden, and the liquefaction of saturated sand foundations by earthquakes poses significant safety risks to the construction of high dams in the southwest. The effects of liquefaction and reinforcing measures on the foundations of rockfill dams on liquefiable overburden under seismic action are currently the subject of somewhat unsystematic investigations. The paper utilizes the total stress and effective stress methods, based on the equivalent linear model, to perform numerical simulations on the overburden foundations of rockfill dams. The study explores how factors such as dam height, overburden thickness, liquefiable layer depth, liquefiable layer thickness, ground motion intensity, and seismic wave characteristics affect the liquefaction of the overburden foundations. Additionally, it examines how rockfill dams impact the dynamic response, considering the liquefaction effects in the overburden. The results show that although the total stress method, which ignores the cumulative evolution of pore pressure during liquefaction, can reveal the basic response trend of the dam, its results in predicting the acceleration response are significantly biased compared to those of the effective stress method, which comprehensively considers the cumulative changes in liquefaction pore pressure. Specifically, when the effect of soil liquefaction is considered, the predicted acceleration response is reduced compared to that when liquefaction is not considered, with the reduction ranging from 4% to 30%; with increases in the thickness and burial depth of the liquefiable layer, the effective stress method considering liquefaction significantly reduces the predicted peak acceleration; the effect of liquefiable soil on the attenuation of the speed response is more sensitive to the low-frequency portion of the seismic wave. The study’s findings are a significant source of reference for the planning and building of rockfill dams on liquefiable overburden.
{"title":"Study on the Effect of Liquefiable Overburden Foundations of Rockfill Dams Based on a Pore Pressure Model","authors":"Zhuxin Li, Hao Zou, Shengqi Jian, Zhongxu Li, Hengxing Lin, Xiang Yu, Minghao Li","doi":"10.3390/w16182649","DOIUrl":"https://doi.org/10.3390/w16182649","url":null,"abstract":"China’s southwestern region boasts abundant hydropower resources. However, the area is prone to frequent strong earthquakes. The areas surrounding dam sites typically have deep overburden, and the liquefaction of saturated sand foundations by earthquakes poses significant safety risks to the construction of high dams in the southwest. The effects of liquefaction and reinforcing measures on the foundations of rockfill dams on liquefiable overburden under seismic action are currently the subject of somewhat unsystematic investigations. The paper utilizes the total stress and effective stress methods, based on the equivalent linear model, to perform numerical simulations on the overburden foundations of rockfill dams. The study explores how factors such as dam height, overburden thickness, liquefiable layer depth, liquefiable layer thickness, ground motion intensity, and seismic wave characteristics affect the liquefaction of the overburden foundations. Additionally, it examines how rockfill dams impact the dynamic response, considering the liquefaction effects in the overburden. The results show that although the total stress method, which ignores the cumulative evolution of pore pressure during liquefaction, can reveal the basic response trend of the dam, its results in predicting the acceleration response are significantly biased compared to those of the effective stress method, which comprehensively considers the cumulative changes in liquefaction pore pressure. Specifically, when the effect of soil liquefaction is considered, the predicted acceleration response is reduced compared to that when liquefaction is not considered, with the reduction ranging from 4% to 30%; with increases in the thickness and burial depth of the liquefiable layer, the effective stress method considering liquefaction significantly reduces the predicted peak acceleration; the effect of liquefiable soil on the attenuation of the speed response is more sensitive to the low-frequency portion of the seismic wave. The study’s findings are a significant source of reference for the planning and building of rockfill dams on liquefiable overburden.","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":"142254618","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}
Soil erosion (SE) is a critical threat to the sustainable development of ecosystem stability, agricultural productivity, and human society in the context of global environmental and climate change. Particularly in tropical island regions, due to the expansion of human activities and land use/cover changes (LUCCs), the risk of SE has been exacerbated. Combining the RUSLE with machine learning methods, SE spatial patterns, their driving forces and the mechanisms of how LUCCs affect SE, were illustrated. Additionally, the potential impacts of future LUCCs on SE were simulated by using the PLUS model. The main results are as follows: (1) Due to LUCCs, the average soil erosion modulus (SEM) decreased significantly from 108.09 t/(km2·a) in 2000 to 106.75 t/(km2·a) in 2020, a reduction of 1.34 t/(km2·a), mainly due to the transformation of cropland to forest and urban land. (2) The dominant factor affecting the spatial pattern of SE is the LS factor (with relative contributions of 43.9% and 45.17%), followed by land use/cover (LUC) (the relative contribution is 28.46% and 34.89%) in 2000 and 2020, respectively. (3) Three kinds of future scenarios simulation results indicate that the average SEM will decrease by 2.40 t/(km2·a) under the natural development scenario and by 1.86 t/(km2·a) under the ecological protection scenario by 2060. However, under the cropland protection scenario, there is a slight increase in SEM, with an increase of 0.08 t/(km2·a). Sloping cropland erosion control remains a primary issue for Hainan Island in the future.
在全球环境和气候变化的背景下，土壤侵蚀（SE）对生态系统的稳定性、农业生产力和人类社会的可持续发展构成了严重威胁。特别是在热带岛屿地区，由于人类活动的扩张和土地利用/覆盖变化（LUCCs），水土流失的风险更加严重。结合 RUSLE 和机器学习方法，说明了 SE 空间模式、其驱动力以及 LUCCs 如何影响 SE 的机制。此外，还利用 PLUS 模型模拟了未来 LUCC 对 SE 的潜在影响。主要结果如下(1）由于 LUCCs，平均土壤侵蚀模数（SEM）从 2000 年的 108.09 吨/（km2-a）显著下降到 2020 年的 106.75 吨/（km2-a），减少了 1.34 吨/（km2-a），这主要是由于耕地向林地和城市用地的转变。(2) 2000 年和 2020 年，影响 SE 空间格局的主导因素是 LS 因素（相对贡献率分别为 43.9% 和 45.17%），其次是土地利用/覆盖（LUC）（相对贡献率分别为 28.46% 和 34.89%）。(3）三种未来情景模拟结果表明，到 2060 年，在自然发展情景下，平均 SEM 将减少 2.40 吨/（km2-a），在生态保护情景下，平均 SEM 将减少 1.86 吨/（km2-a）。然而，在耕地保护情景下，SEM 会略有增加，增加 0.08 吨/（平方公里-a）。坡耕地水土流失控制仍是海南岛未来的首要问题。
{"title":"Impact of Land Use/Cover Change on Soil Erosion and Future Simulations in Hainan Island, China","authors":"Jianchao Guo, Jiadong Chen, Shi Qi","doi":"10.3390/w16182654","DOIUrl":"https://doi.org/10.3390/w16182654","url":null,"abstract":"Soil erosion (SE) is a critical threat to the sustainable development of ecosystem stability, agricultural productivity, and human society in the context of global environmental and climate change. Particularly in tropical island regions, due to the expansion of human activities and land use/cover changes (LUCCs), the risk of SE has been exacerbated. Combining the RUSLE with machine learning methods, SE spatial patterns, their driving forces and the mechanisms of how LUCCs affect SE, were illustrated. Additionally, the potential impacts of future LUCCs on SE were simulated by using the PLUS model. The main results are as follows: (1) Due to LUCCs, the average soil erosion modulus (SEM) decreased significantly from 108.09 t/(km2·a) in 2000 to 106.75 t/(km2·a) in 2020, a reduction of 1.34 t/(km2·a), mainly due to the transformation of cropland to forest and urban land. (2) The dominant factor affecting the spatial pattern of SE is the LS factor (with relative contributions of 43.9% and 45.17%), followed by land use/cover (LUC) (the relative contribution is 28.46% and 34.89%) in 2000 and 2020, respectively. (3) Three kinds of future scenarios simulation results indicate that the average SEM will decrease by 2.40 t/(km2·a) under the natural development scenario and by 1.86 t/(km2·a) under the ecological protection scenario by 2060. However, under the cropland protection scenario, there is a slight increase in SEM, with an increase of 0.08 t/(km2·a). Sloping cropland erosion control remains a primary issue for Hainan Island in the future.","PeriodicalId":23788,"journal":{"name":"Water","volume":"3 1","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142254621","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}
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}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号