As one of China's nine border provinces, Jilin Province is an important window for China's “Belt and Road” to open up to the north, and an important channel for China's foreign trade and foreign exchanges. Therefore, understanding hydrogeochemical characteristics is very important for effective water resources management in Jilin Province. A total of 64 groundwater samples were collected from 32 monitoring Wells in Jilin Province. Use of hydrogeochemical analysis techniques, WQI index and human health risk index methods to assess hydrogeochemical processes and groundwater quality, including the determination of hydrogeochemical parameters, conventional ions, trace elements and stable isotopes (δD and δ18O). The results show that the groundwater is slightly alkaline, the cations are mainly Na+, Ca2+, Mg2+, and K+, and the anions are mainly HCO3-, Cl−, and SO42-. Most of the groundwater samples belong to Ca-HCO3 and Na-HCO3 types, which are formed by the dissolution of calcite, dolomite, gypsum, silicates and carbonates. Stable isotope analysis shows that groundwater recharge in Jilin mainly comes from atmospheric precipitation at an altitude of 1,430~2,348 m. The strong correlation between trace elements indicates a common source. Most of the groundwater quality index (WQI) in the study area is Class I to Class III, and hazard quotient (HQ) and hazard index (HI) are both below 1. This indicates excellent water quality and minimal health risks associated with human consumption. It is worth noting that trace elements are enriched in the Tanlu fault zone. It provides scientific guidance for the utilization and allocation of groundwater resources in Jilin Province.
{"title":"Hydrogeochemical characteristics and evaluation of groundwater resources of Jilin Province, China","authors":"Zhaojun Zeng, Yueju Cui, Xiaocheng Zhou, Xiaodong Pan, Fengxia Sun, Yinan Liu, Jiao Tian, Miao He, Yongxian Zhang, Yucong Yan, Zhenyu Zou, Yuwen Wang, Bingyu Yao, Gaoyuan Xing, Shihan Cui","doi":"10.3389/frwa.2023.1315805","DOIUrl":"https://doi.org/10.3389/frwa.2023.1315805","url":null,"abstract":"As one of China's nine border provinces, Jilin Province is an important window for China's “Belt and Road” to open up to the north, and an important channel for China's foreign trade and foreign exchanges. Therefore, understanding hydrogeochemical characteristics is very important for effective water resources management in Jilin Province. A total of 64 groundwater samples were collected from 32 monitoring Wells in Jilin Province. Use of hydrogeochemical analysis techniques, WQI index and human health risk index methods to assess hydrogeochemical processes and groundwater quality, including the determination of hydrogeochemical parameters, conventional ions, trace elements and stable isotopes (δD and δ18O). The results show that the groundwater is slightly alkaline, the cations are mainly Na+, Ca2+, Mg2+, and K+, and the anions are mainly HCO3-, Cl−, and SO42-. Most of the groundwater samples belong to Ca-HCO3 and Na-HCO3 types, which are formed by the dissolution of calcite, dolomite, gypsum, silicates and carbonates. Stable isotope analysis shows that groundwater recharge in Jilin mainly comes from atmospheric precipitation at an altitude of 1,430~2,348 m. The strong correlation between trace elements indicates a common source. Most of the groundwater quality index (WQI) in the study area is Class I to Class III, and hazard quotient (HQ) and hazard index (HI) are both below 1. This indicates excellent water quality and minimal health risks associated with human consumption. It is worth noting that trace elements are enriched in the Tanlu fault zone. It provides scientific guidance for the utilization and allocation of groundwater resources in Jilin Province.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":"120 29","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138958997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-19DOI: 10.3389/frwa.2023.1247322
Fernando Miralles-Wilhelm
This paper presents a synthesis of evidence and implementation gaps in the application of nature-based solutions (NbS) in agricultural landscapes that contribute to reduce trade-offs between food production, climate change and conservation objectives. The literature and data surveyed relies primarily in peer-reviewed sources and is organized around an overview of NbS science and applications in agricultural landscapes in major biomes. To date, the focus of NbS applications in food production has been predominantly for carbon sequestration, water quality, and disaster-risk management objectives while documented examples of NbS benefits in agricultural production are sparse. Conservation applications of NbS appear to show evidence of effectiveness across multiple objectives in biodiversity, land, soil and water. Evidence and analysis of NbS to meet climate change mitigation targets has surged in recent years driven by global community efforts. Overall, considerable scientific work remains to refine and reduce the uncertainty of NbS benefit estimates across production, climate and conservation objectives, and resilience implications. However, delaying implementation of NbS in agricultural landscapes would likely increase the costs to meet agricultural production, climate, conservation and other societally beneficial goals, while degrading the capacity of natural systems to continue to provide these and other ecosystem services.
{"title":"Nature-based solutions in agricultural landscapes for reducing tradeoffs between food production, climate change, and conservation objectives","authors":"Fernando Miralles-Wilhelm","doi":"10.3389/frwa.2023.1247322","DOIUrl":"https://doi.org/10.3389/frwa.2023.1247322","url":null,"abstract":"This paper presents a synthesis of evidence and implementation gaps in the application of nature-based solutions (NbS) in agricultural landscapes that contribute to reduce trade-offs between food production, climate change and conservation objectives. The literature and data surveyed relies primarily in peer-reviewed sources and is organized around an overview of NbS science and applications in agricultural landscapes in major biomes. To date, the focus of NbS applications in food production has been predominantly for carbon sequestration, water quality, and disaster-risk management objectives while documented examples of NbS benefits in agricultural production are sparse. Conservation applications of NbS appear to show evidence of effectiveness across multiple objectives in biodiversity, land, soil and water. Evidence and analysis of NbS to meet climate change mitigation targets has surged in recent years driven by global community efforts. Overall, considerable scientific work remains to refine and reduce the uncertainty of NbS benefit estimates across production, climate and conservation objectives, and resilience implications. However, delaying implementation of NbS in agricultural landscapes would likely increase the costs to meet agricultural production, climate, conservation and other societally beneficial goals, while degrading the capacity of natural systems to continue to provide these and other ecosystem services.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":" 7","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138961965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-19DOI: 10.3389/frwa.2023.1256249
S. Dhaubanjar, A. Lutz, W. Smolenaars, S. Khanal, M. K. Jamil, H. Biemans, Fulco Ludwig, Arun Bhakta Shrestha, W. Immerzeel
Despite ambitious plans to quadruple hydropower generation in the Indus basin, a quantitative assessment of the impact of climate change on hydropower availability in the basin is missing. To address this gap, we combine downscaled CMIP6 projections with the Hydropower Potential Exploration (HyPE) model to quantify future hydropower potential available in the upper Indus basin.HyPE uses a spatial cost-minimization framework to evaluate four classes of hydropower potential, namely theoretical, technical, financial and sustainable, considering various constraints on the siting and sizing of two run-of-river hydropower plant configurations.Under future discharge projections, all classes of potential increase while subbasin changes align with the spatial patterns projected in hydro-climatology. Theoretical potential changes by 3.9–56 %, technical potential by −2.3–46.8 %, financial potential by −8.8–50.4 % and sustainable potential by −6.1–49.7 %. A small decline is observed in the northwestern subbasins where increase in potential is lower than in the southeast. In contrast, with increasing variability in the Indian Summer Monsoon in the future, the southeastern subbasins have the strongest increase in sustainable potential accompanied by higher increase in plant size, decrease in costs and higher variability. The southeastern Satluj subbasin is the hotspot where sustainable potential has the highest increase of up to 145 %. The northwestern Kabul subbasin has the highest decrease of up to −27 %. The Swat subbasin has the lowest variability in sustainable potential while the Jhelum and Indus main subbasins remain the subbasins with the cheapest potential into the future. The performance of future sustainable portfolios differ from the performance of historical portfolios by −11.1–39.9 %.Hence, considering future climate in the present-day planning of hydropower will lead to improved performance under a majority of scenarios. The sufficiency of hydropower potential to fulfill energy security depends on future population growth. Energy availability is projected to decline in the northwest as population increases faster than hydropower potential. The per capita sustainable potential In the Kabul subbasin reduces to a third of the historical value. A socio-hydrological approach is necessary to address the complexity of achieving sustainable and equitable hydropower development in the Indus basin under such spatial mismatch between hydropower availability and energy demand in a resource-limited world.
{"title":"Quantification of run-of-river hydropower potential in the Upper Indus basin under climate change","authors":"S. Dhaubanjar, A. Lutz, W. Smolenaars, S. Khanal, M. K. Jamil, H. Biemans, Fulco Ludwig, Arun Bhakta Shrestha, W. Immerzeel","doi":"10.3389/frwa.2023.1256249","DOIUrl":"https://doi.org/10.3389/frwa.2023.1256249","url":null,"abstract":"Despite ambitious plans to quadruple hydropower generation in the Indus basin, a quantitative assessment of the impact of climate change on hydropower availability in the basin is missing. To address this gap, we combine downscaled CMIP6 projections with the Hydropower Potential Exploration (HyPE) model to quantify future hydropower potential available in the upper Indus basin.HyPE uses a spatial cost-minimization framework to evaluate four classes of hydropower potential, namely theoretical, technical, financial and sustainable, considering various constraints on the siting and sizing of two run-of-river hydropower plant configurations.Under future discharge projections, all classes of potential increase while subbasin changes align with the spatial patterns projected in hydro-climatology. Theoretical potential changes by 3.9–56 %, technical potential by −2.3–46.8 %, financial potential by −8.8–50.4 % and sustainable potential by −6.1–49.7 %. A small decline is observed in the northwestern subbasins where increase in potential is lower than in the southeast. In contrast, with increasing variability in the Indian Summer Monsoon in the future, the southeastern subbasins have the strongest increase in sustainable potential accompanied by higher increase in plant size, decrease in costs and higher variability. The southeastern Satluj subbasin is the hotspot where sustainable potential has the highest increase of up to 145 %. The northwestern Kabul subbasin has the highest decrease of up to −27 %. The Swat subbasin has the lowest variability in sustainable potential while the Jhelum and Indus main subbasins remain the subbasins with the cheapest potential into the future. The performance of future sustainable portfolios differ from the performance of historical portfolios by −11.1–39.9 %.Hence, considering future climate in the present-day planning of hydropower will lead to improved performance under a majority of scenarios. The sufficiency of hydropower potential to fulfill energy security depends on future population growth. Energy availability is projected to decline in the northwest as population increases faster than hydropower potential. The per capita sustainable potential In the Kabul subbasin reduces to a third of the historical value. A socio-hydrological approach is necessary to address the complexity of achieving sustainable and equitable hydropower development in the Indus basin under such spatial mismatch between hydropower availability and energy demand in a resource-limited world.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":"134 ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138962898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-18DOI: 10.3389/frwa.2023.1333165
H. Schoenfuss, A. Kolok
Contaminants of Emerging Concern (CECs) have been documented across the seven continents, including Antarctica, and are likely an impediment to the sustainable management of natural resources. Most studies to date have relied on sweeping chemistry surveys, reliant upon sophisticated instrumentation. This approach is expensive, relies on limited laboratory capacity, and generates results that are spatially and temporally constrained. Here we review existing approaches that can overcome these limitations by focusing on effects-based monitoring. Passive samplers can generate long-term records regarding the occurrence of CECs. As samples are concentrated, their analysis can be achieved using equipment that will be more common and less expensive. A second approach involves rapid test methods for single compounds, including test strips, ELISA assays, and mobile phone-based analytic tools. These can provide inexpensive CEC presence data for many field sites and can be used to stratify sampling and thereby reduce cost. Identifying the presence of a single compound can often shed light on the likely presence of entire groups of chemicals. Pairing these chemistry-derived approaches with geospatial modeling to predict CEC presence and concentrations across watersheds has already been applied in several large watersheds. Utilizing available ecotoxicological knowledge bases provides an opportunity to link modeled CEC occurrence and concentrations with likely adverse biological responses. Finally, confirmatory on-site exposure experiments can corroborate the presence or absence of biological effects hypothesized from the above chain of evidence to provide natural resource managers with information to make conservation decisions.
{"title":"An ecotoxicologically relevant approach to water quality monitoring for contaminants of emerging concern","authors":"H. Schoenfuss, A. Kolok","doi":"10.3389/frwa.2023.1333165","DOIUrl":"https://doi.org/10.3389/frwa.2023.1333165","url":null,"abstract":"Contaminants of Emerging Concern (CECs) have been documented across the seven continents, including Antarctica, and are likely an impediment to the sustainable management of natural resources. Most studies to date have relied on sweeping chemistry surveys, reliant upon sophisticated instrumentation. This approach is expensive, relies on limited laboratory capacity, and generates results that are spatially and temporally constrained. Here we review existing approaches that can overcome these limitations by focusing on effects-based monitoring. Passive samplers can generate long-term records regarding the occurrence of CECs. As samples are concentrated, their analysis can be achieved using equipment that will be more common and less expensive. A second approach involves rapid test methods for single compounds, including test strips, ELISA assays, and mobile phone-based analytic tools. These can provide inexpensive CEC presence data for many field sites and can be used to stratify sampling and thereby reduce cost. Identifying the presence of a single compound can often shed light on the likely presence of entire groups of chemicals. Pairing these chemistry-derived approaches with geospatial modeling to predict CEC presence and concentrations across watersheds has already been applied in several large watersheds. Utilizing available ecotoxicological knowledge bases provides an opportunity to link modeled CEC occurrence and concentrations with likely adverse biological responses. Finally, confirmatory on-site exposure experiments can corroborate the presence or absence of biological effects hypothesized from the above chain of evidence to provide natural resource managers with information to make conservation decisions.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":"54 s266","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138965376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-14DOI: 10.3389/frwa.2023.1305373
Cuthbert Taguta, L. Nhamo, Zolo Kiala, Tsitsi Bangira, T. L. Dirwai, A. Senzanje, Hodson Makurira, Graham P. W. Jewitt, S. Mpandeli, T. Mabhaudhi
The water-energy-food (WEF) nexus has evolved into an important transformative approach for facilitating the timely identification of trade-offs and synergies between interlinked sectors for informed intervention and decision-making. However, there is a growing need for a WEF nexus tool to support decision-making on integrated resources management toward sustainable development.This study developed a geospatial web-based integrative analytical tool for the WEF nexus (the iWEF) to support integrated assessment of WEF resources to support resilience building and adaptation initiatives and strategies. The tool uses the Analytic Hierarchy Process (AHP) to establish numerical correlations among WEF nexus indicators and pillars, mainly availability, productivity, accessibility, and sufficiency. The tool was calibrated and validated with existing tools and data at varying spatio-temporal scales.The results indicate the applicability of the tool at any spatial scale, highlighting the moderate sustainability in the management of WEF resources at various scales. The developed iWEF tool has improved the existing integrative WEF nexus analytical tool in terms of processing time and providing geospatial capabilities.The iWEF tool is a digital platform that automatically guides policy and decision-making in managing risk from trade-offs and enhancing synergies holistically. It is developed to support policy and decision-making on timely interventions in priority areas that could be showing signs of stress.
{"title":"A geospatial web-based integrative analytical tool for the water-energy-food nexus: the iWEF 1.0","authors":"Cuthbert Taguta, L. Nhamo, Zolo Kiala, Tsitsi Bangira, T. L. Dirwai, A. Senzanje, Hodson Makurira, Graham P. W. Jewitt, S. Mpandeli, T. Mabhaudhi","doi":"10.3389/frwa.2023.1305373","DOIUrl":"https://doi.org/10.3389/frwa.2023.1305373","url":null,"abstract":"The water-energy-food (WEF) nexus has evolved into an important transformative approach for facilitating the timely identification of trade-offs and synergies between interlinked sectors for informed intervention and decision-making. However, there is a growing need for a WEF nexus tool to support decision-making on integrated resources management toward sustainable development.This study developed a geospatial web-based integrative analytical tool for the WEF nexus (the iWEF) to support integrated assessment of WEF resources to support resilience building and adaptation initiatives and strategies. The tool uses the Analytic Hierarchy Process (AHP) to establish numerical correlations among WEF nexus indicators and pillars, mainly availability, productivity, accessibility, and sufficiency. The tool was calibrated and validated with existing tools and data at varying spatio-temporal scales.The results indicate the applicability of the tool at any spatial scale, highlighting the moderate sustainability in the management of WEF resources at various scales. The developed iWEF tool has improved the existing integrative WEF nexus analytical tool in terms of processing time and providing geospatial capabilities.The iWEF tool is a digital platform that automatically guides policy and decision-making in managing risk from trade-offs and enhancing synergies holistically. It is developed to support policy and decision-making on timely interventions in priority areas that could be showing signs of stress.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":"7 2","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139002630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-14DOI: 10.3389/frwa.2023.1286128
Joshua Matanzima, Teboho Mosuoe-Tsietsi
This article calls for social justice within the transition from dam building to decommissioning. Dam decommissioning is escalating in the global north, and sooner than later, the tied will spread to the global south. Though dam removal is an essential strategy for riverine landscape restoration, it may yield negative social outcomes for communities living along dams. Ecological restoration must not be achieved at the expense of local communities. Decisions on dam removal are predominantly made by experts and government agencies, often to the exclusion of local communities. For this reason, the decisions to remove several dams in the global north have been opposed by local communities leading to suspension or, in worst-case scenarios, reversal of such decisions. By referring to cases from Europe, USA, and Canada where dam removals have been opposed, this article argues for better incorporation of local communities in decision-making. Community consultations and consent are key in achieving successful decommissioning with minimal harm on communities. Yet, they have not received sufficient attention in dam removal conversations. The socio-economic issues are also not sufficiently interrogated in the literature on dam removal. We underscore this gap and provides recommendations for best social performance in dam removals.
{"title":"Dam removal blind spots: debating the importance of community engagement in dam decommissioning projects","authors":"Joshua Matanzima, Teboho Mosuoe-Tsietsi","doi":"10.3389/frwa.2023.1286128","DOIUrl":"https://doi.org/10.3389/frwa.2023.1286128","url":null,"abstract":"This article calls for social justice within the transition from dam building to decommissioning. Dam decommissioning is escalating in the global north, and sooner than later, the tied will spread to the global south. Though dam removal is an essential strategy for riverine landscape restoration, it may yield negative social outcomes for communities living along dams. Ecological restoration must not be achieved at the expense of local communities. Decisions on dam removal are predominantly made by experts and government agencies, often to the exclusion of local communities. For this reason, the decisions to remove several dams in the global north have been opposed by local communities leading to suspension or, in worst-case scenarios, reversal of such decisions. By referring to cases from Europe, USA, and Canada where dam removals have been opposed, this article argues for better incorporation of local communities in decision-making. Community consultations and consent are key in achieving successful decommissioning with minimal harm on communities. Yet, they have not received sufficient attention in dam removal conversations. The socio-economic issues are also not sufficiently interrogated in the literature on dam removal. We underscore this gap and provides recommendations for best social performance in dam removals.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":"8 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138972774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-14DOI: 10.3389/frwa.2023.1305347
Jawaher S. Al-Marri, Aisha B. Abouedwan, Mohammad I. Ahmad, N. Bensalah
Electrocoagulation is a water treatment technology capable to remove a variety of organic pollutants from water. It is advantageous compared to chemical coagulation due to the controlled dissolution of coagulants by regulating the current density and pH. In this work, the removal of kinetic hydrate inhibitor (KHI) (polyvinyl pyrrolidone, PVP) from water by electrocoagulation using Al electrodes was investigated. The effects of several experimental conditions including the nature of the supporting electrolyte, the current density, and the initial pH value on the electrochemical dissolution of aluminum was evaluated. The findings of the experiments revealed that both chemical and electrochemical dissolution play important roles in the generation of hydroxo-aluminum species. Corrosion studies demonstrated that the presence of chloride ions in water promotes aluminum dissolving via pitting corrosion, whereas the presence of phosphate ions inhibits aluminum corrosion by the deposition of a thick passive layer of aluminum hydroxide/phosphate on the metal surface. The theoretical and experimental amounts of aluminum, increase linearly with increasing specific electrical charge for Q< 2.5 Ah/L, which correlates well with Faraday's Law. The removal of KHI from 0.1M NaCl aqueous solutions by electrocoagulation using aluminum electrodes achieved high removal efficiency in terms of total organic carbon (TOC) up to 95%. TOC decay during galvanostatic electrolysis confirmed the removal of KHI molecules by Al-electrocoagulation at different current densities and pH conditions. The primary mechanism involved in eliminating KHI from water by electrocoagulation using Al electrodes includes mainly the adsorption of PVP molecules on the surface of Al(OH)3 flocs and their enmeshment inside the solid coagulants.
电凝是一种能够去除水中各种有机污染物的水处理技术。与化学混凝法相比，电凝法的优势在于通过调节电流密度和 pH 值来控制混凝剂的溶解。在这项工作中，研究了使用铝电极通过电凝去除水中的动力学水合物抑制剂（KHI）（聚乙烯吡咯烷酮，PVP）。评估了多种实验条件（包括支撑电解质的性质、电流密度和初始 pH 值）对铝电化学溶解的影响。实验结果表明，化学溶解和电化学溶解在氢氧基铝物种的生成过程中都发挥了重要作用。腐蚀研究表明，水中氯离子的存在会通过点腐蚀促进铝的溶解，而磷酸盐离子的存在则会在金属表面沉积一层厚厚的氢氧化铝/磷酸盐被动层，从而抑制铝的腐蚀。当 Q< 2.5 Ah/L 时，铝的理论值和实验值随着比电荷的增加而线性增加，这与法拉第定律十分吻合。使用铝电极电凝去除 0.1M NaCl 水溶液中的 KHI 时，总有机碳（TOC）的去除率高达 95%。在不同的电流密度和 pH 值条件下，静电电解过程中的 TOC 衰减证实了铝电凝对 KHI 分子的去除效果。使用铝电极电凝消除水中 KHI 的主要机制包括 PVP 分子在 Al(OH)3 絮凝体表面的吸附及其在固体混凝剂内部的啮合。
{"title":"Electrocoagulation using aluminum electrodes as a sustainable and economic method for the removal of kinetic hydrate inhibitor (polyvinyl pyrrolidone) from produced wastewaters","authors":"Jawaher S. Al-Marri, Aisha B. Abouedwan, Mohammad I. Ahmad, N. Bensalah","doi":"10.3389/frwa.2023.1305347","DOIUrl":"https://doi.org/10.3389/frwa.2023.1305347","url":null,"abstract":"Electrocoagulation is a water treatment technology capable to remove a variety of organic pollutants from water. It is advantageous compared to chemical coagulation due to the controlled dissolution of coagulants by regulating the current density and pH. In this work, the removal of kinetic hydrate inhibitor (KHI) (polyvinyl pyrrolidone, PVP) from water by electrocoagulation using Al electrodes was investigated. The effects of several experimental conditions including the nature of the supporting electrolyte, the current density, and the initial pH value on the electrochemical dissolution of aluminum was evaluated. The findings of the experiments revealed that both chemical and electrochemical dissolution play important roles in the generation of hydroxo-aluminum species. Corrosion studies demonstrated that the presence of chloride ions in water promotes aluminum dissolving via pitting corrosion, whereas the presence of phosphate ions inhibits aluminum corrosion by the deposition of a thick passive layer of aluminum hydroxide/phosphate on the metal surface. The theoretical and experimental amounts of aluminum, increase linearly with increasing specific electrical charge for Q< 2.5 Ah/L, which correlates well with Faraday's Law. The removal of KHI from 0.1M NaCl aqueous solutions by electrocoagulation using aluminum electrodes achieved high removal efficiency in terms of total organic carbon (TOC) up to 95%. TOC decay during galvanostatic electrolysis confirmed the removal of KHI molecules by Al-electrocoagulation at different current densities and pH conditions. The primary mechanism involved in eliminating KHI from water by electrocoagulation using Al electrodes includes mainly the adsorption of PVP molecules on the surface of Al(OH)3 flocs and their enmeshment inside the solid coagulants.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":"30 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138973296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-13DOI: 10.3389/frwa.2023.1305998
Abdessamad Jari, E. Bachaoui, Soufiane Hajaj, Achraf Khaddari, Younes Khandouch, Abderrazak El Harti, Amine Jellouli, Mustapha Namous
Groundwater resource management in arid regions has a critical importance for sustaining human activities and ecological systems. Accurate mapping of groundwater potential plays a vital role in effective water resource planning. This study investigates the effectiveness of machine learning models, including Random Forest (RF), Adaboost, K-Nearest Neighbors (KNN), and Gaussian Process in groundwater potential mapping (GWPM) in the Tan-Tan arid region, Morocco. Fourteen groundwater conditional factors were considered following multicollinearity test, including topographical, hydrological, climatic, and geological factors. Additionally, point data with 174 sites indicative of groundwater occurrences were incorporated. The groundwater inventory data underwent random partitioning into training and testing datasets at three different ratios: 55/45%, 65/35%, and 75/25%. Ultimately, a comprehensive ranking of the 13 models, encompassing both individual and ensemble models, was determined using the prioritization rank technique. The results revealed that ensemble learning (EL) models, particularly RF and Adaboost (RF-Adaboost), outperformed individual models in groundwater potential mapping. Based on accuracy assessment using the validation dataset, the RF-Adaboost EL results yielded an Area Under the Receiver Operating characteristic Curve (AUROC) and Overall Accuracy (OA) of 94.02 and 94%, respectively. Ensemble models have been effectively applied to integrate 14 factors, capturing their intricate interrelationships, and thereby enhancing the accuracy and robustness of groundwater prediction in the Tan-Tan water-scarce region. Among the natural factors, the current study identified lithology, structural elements (such as faults and tectonic lineaments), and land use as significant contributors to groundwater potential. However, the critical characteristics of the study area showing a coastal position as well as a low background in groundwater prospectivity (low borehole points) are challenging in GWPM. The findings highlight the importance of the significant factors in assessing and managing groundwater resources in arid regions. Moreover, this study makes a contribution to the management of groundwater resources by demonstrating the effectiveness of ensemble learning algorithms in the groundwater potential mapping (GWPM) in arid regions.
{"title":"Investigating machine learning and ensemble learning models in groundwater potential mapping in arid region: case study from Tan-Tan water-scarce region, Morocco","authors":"Abdessamad Jari, E. Bachaoui, Soufiane Hajaj, Achraf Khaddari, Younes Khandouch, Abderrazak El Harti, Amine Jellouli, Mustapha Namous","doi":"10.3389/frwa.2023.1305998","DOIUrl":"https://doi.org/10.3389/frwa.2023.1305998","url":null,"abstract":"Groundwater resource management in arid regions has a critical importance for sustaining human activities and ecological systems. Accurate mapping of groundwater potential plays a vital role in effective water resource planning. This study investigates the effectiveness of machine learning models, including Random Forest (RF), Adaboost, K-Nearest Neighbors (KNN), and Gaussian Process in groundwater potential mapping (GWPM) in the Tan-Tan arid region, Morocco. Fourteen groundwater conditional factors were considered following multicollinearity test, including topographical, hydrological, climatic, and geological factors. Additionally, point data with 174 sites indicative of groundwater occurrences were incorporated. The groundwater inventory data underwent random partitioning into training and testing datasets at three different ratios: 55/45%, 65/35%, and 75/25%. Ultimately, a comprehensive ranking of the 13 models, encompassing both individual and ensemble models, was determined using the prioritization rank technique. The results revealed that ensemble learning (EL) models, particularly RF and Adaboost (RF-Adaboost), outperformed individual models in groundwater potential mapping. Based on accuracy assessment using the validation dataset, the RF-Adaboost EL results yielded an Area Under the Receiver Operating characteristic Curve (AUROC) and Overall Accuracy (OA) of 94.02 and 94%, respectively. Ensemble models have been effectively applied to integrate 14 factors, capturing their intricate interrelationships, and thereby enhancing the accuracy and robustness of groundwater prediction in the Tan-Tan water-scarce region. Among the natural factors, the current study identified lithology, structural elements (such as faults and tectonic lineaments), and land use as significant contributors to groundwater potential. However, the critical characteristics of the study area showing a coastal position as well as a low background in groundwater prospectivity (low borehole points) are challenging in GWPM. The findings highlight the importance of the significant factors in assessing and managing groundwater resources in arid regions. Moreover, this study makes a contribution to the management of groundwater resources by demonstrating the effectiveness of ensemble learning algorithms in the groundwater potential mapping (GWPM) in arid regions.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":"253 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139003795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-06DOI: 10.3389/frwa.2023.1298465
Tianlong Jia, Andre Jehan Vallendar, Rinze de Vries, Z. Kapelan, R. Taormina
Supervised Deep Learning (DL) methods have shown promise in monitoring the floating litter in rivers and urban canals but further advancements are hard to obtain due to the limited availability of relevant labeled data. To address this challenge, researchers often utilize techniques such as transfer learning (TL) and data augmentation (DA). However, there is no study currently reporting a rigorous evaluation of the effectiveness of these approaches for floating litter detection and their effects on the models' generalization capability. To overcome the problem of limited data availability, this work introduces the “TU Delft—Green Village” dataset, a novel labeled dataset of 9,473 camera and phone images of floating macroplastic litter and other litter items, captured using experiments in a drainage canal of TU Delft. We use the new dataset to conduct a thorough evaluation of the detection performance of five DL architectures for multi-class image classification. We focus the analysis on a systematic evaluation of the benefits of TL and DA on model performances. Moreover, we evaluate the generalization capability of these models for unseen litter items and new device settings, such as increasing the cameras' height and tilting them to 45°. The results obtained show that, for the specific problem of floating litter detection, fine-tuning all layers is more effective than the common approach of fine-tuning the classifier alone. Among the tested DA techniques, we find that simple image flipping boosts model accuracy the most, while other methods have little impact on the performance. The SqueezeNet and DenseNet121 architectures perform the best, achieving an overall accuracy of 89.6 and 91.7%, respectively. We also observe that both models retain good generalization capability which drops significantly only for the most complex scenario tested, but the overall accuracy raises significantly to around 75% when adding a limited amount of images to training data, combined with flipping augmentation. The detailed analyses conducted here and the released open source dataset offer valuable insights and serve as a precious resource for future research.
{"title":"Advancing deep learning-based detection of floating litter using a novel open dataset","authors":"Tianlong Jia, Andre Jehan Vallendar, Rinze de Vries, Z. Kapelan, R. Taormina","doi":"10.3389/frwa.2023.1298465","DOIUrl":"https://doi.org/10.3389/frwa.2023.1298465","url":null,"abstract":"Supervised Deep Learning (DL) methods have shown promise in monitoring the floating litter in rivers and urban canals but further advancements are hard to obtain due to the limited availability of relevant labeled data. To address this challenge, researchers often utilize techniques such as transfer learning (TL) and data augmentation (DA). However, there is no study currently reporting a rigorous evaluation of the effectiveness of these approaches for floating litter detection and their effects on the models' generalization capability. To overcome the problem of limited data availability, this work introduces the “TU Delft—Green Village” dataset, a novel labeled dataset of 9,473 camera and phone images of floating macroplastic litter and other litter items, captured using experiments in a drainage canal of TU Delft. We use the new dataset to conduct a thorough evaluation of the detection performance of five DL architectures for multi-class image classification. We focus the analysis on a systematic evaluation of the benefits of TL and DA on model performances. Moreover, we evaluate the generalization capability of these models for unseen litter items and new device settings, such as increasing the cameras' height and tilting them to 45°. The results obtained show that, for the specific problem of floating litter detection, fine-tuning all layers is more effective than the common approach of fine-tuning the classifier alone. Among the tested DA techniques, we find that simple image flipping boosts model accuracy the most, while other methods have little impact on the performance. The SqueezeNet and DenseNet121 architectures perform the best, achieving an overall accuracy of 89.6 and 91.7%, respectively. We also observe that both models retain good generalization capability which drops significantly only for the most complex scenario tested, but the overall accuracy raises significantly to around 75% when adding a limited amount of images to training data, combined with flipping augmentation. The detailed analyses conducted here and the released open source dataset offer valuable insights and serve as a precious resource for future research.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":"59 8","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138595249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-06DOI: 10.3389/frwa.2023.1254225
Bisesh Joshi, Eva Bacmeister, Erin K. Peck, M. Peipoch, Jinjun Kan, Shreeram Inamdar
Nitrogen (N) pollution in riverine ecosystems has substantial environmental, economic, and policy consequences. Various riverine N removal processes include permanent dissimilatory sinks such as denitrification (Uden) and temporary assimilatory sink such as microbial N uptake (Uassim). Both processes have been extensively evaluated in benthic sediments but only sparsely in the water column, particularly for storm flows producing high suspended sediment (SS) concentrations. Stormflows also increase the sediment bound N (Sed-N) export, and in turn, the overall N exports from watersheds. The balance between N removal by Uden and Uassim vs. Sed-N export has not been studied and is a key knowledge gap. We assessed the magnitude of Uden and Uassim against stormflow Sed-N exports for multiple storm events of varying magnitude and across two drainage areas (750 ha and 15,330 ha) in a mixed landuse mid-Atlantic US watershed. We asked: How do the Uden and Uassim sinks compare with Sed-N exports and how do these N fluxes vary across the drainage areas for sampled storms on the rising and falling limbs of the discharge hydrograph? Mean Uden and Uassim as % of the Sed-N exports ranged between 0.1–40% and 0.6–22%, respectively. Storm event Uassim fluxes were generally slightly lower than the corresponding Uden fluxes. Similarly, comparable but slightly higher Uden fluxes were observed for the second order vs. the fourth order stream, while Uassim fluxes were slightly higher in the fourth-order stream. Both of these N sinks were higher on the falling vs. rising limbs of the hydrograph. This suggests that while the N sinks are not trivial, sediment bound N exports during large stormflows will likely overshadow any gains in N removal by SS associated denitrification. Understanding these N source-sink dynamics for storm events is critical for accurate watershed nutrient modeling and for better pollution mitigation strategies for downstream aquatic ecosystems. These results are especially important within the context of climate change as extreme hydrological events including storms are becoming more and more frequent.
{"title":"Sediment-Nitrogen (N) connectivity: suspended sediments in streams as N exporters and reactors for denitrification and assimilatory N uptake during storms","authors":"Bisesh Joshi, Eva Bacmeister, Erin K. Peck, M. Peipoch, Jinjun Kan, Shreeram Inamdar","doi":"10.3389/frwa.2023.1254225","DOIUrl":"https://doi.org/10.3389/frwa.2023.1254225","url":null,"abstract":"Nitrogen (N) pollution in riverine ecosystems has substantial environmental, economic, and policy consequences. Various riverine N removal processes include permanent dissimilatory sinks such as denitrification (Uden) and temporary assimilatory sink such as microbial N uptake (Uassim). Both processes have been extensively evaluated in benthic sediments but only sparsely in the water column, particularly for storm flows producing high suspended sediment (SS) concentrations. Stormflows also increase the sediment bound N (Sed-N) export, and in turn, the overall N exports from watersheds. The balance between N removal by Uden and Uassim vs. Sed-N export has not been studied and is a key knowledge gap. We assessed the magnitude of Uden and Uassim against stormflow Sed-N exports for multiple storm events of varying magnitude and across two drainage areas (750 ha and 15,330 ha) in a mixed landuse mid-Atlantic US watershed. We asked: How do the Uden and Uassim sinks compare with Sed-N exports and how do these N fluxes vary across the drainage areas for sampled storms on the rising and falling limbs of the discharge hydrograph? Mean Uden and Uassim as % of the Sed-N exports ranged between 0.1–40% and 0.6–22%, respectively. Storm event Uassim fluxes were generally slightly lower than the corresponding Uden fluxes. Similarly, comparable but slightly higher Uden fluxes were observed for the second order vs. the fourth order stream, while Uassim fluxes were slightly higher in the fourth-order stream. Both of these N sinks were higher on the falling vs. rising limbs of the hydrograph. This suggests that while the N sinks are not trivial, sediment bound N exports during large stormflows will likely overshadow any gains in N removal by SS associated denitrification. Understanding these N source-sink dynamics for storm events is critical for accurate watershed nutrient modeling and for better pollution mitigation strategies for downstream aquatic ecosystems. These results are especially important within the context of climate change as extreme hydrological events including storms are becoming more and more frequent.","PeriodicalId":33801,"journal":{"name":"Frontiers in Water","volume":"41 25","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138597641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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