Five-day biochemical oxygen demand (BOD5) is a vital wastewater contamination strength indicator. The process of measuring BOD5 is to measure the mass of molecular oxygen consumed in 1 L of water at 20 °C over 5-day incubation period. It is a time-consuming process and often too late for water management agencies to make a timely reaction if the result of measurement shows a water body is seriously polluted. Biosensors can simplify the process of BOD5 measurement; however, the measurement results often deviate significantly from the measured BOD5 values. The main aim of this research is to identify a machine learning model, which could predict BOD5 value from historical data and make it easier to detect water pollution in advance and timely adopt treatment measures. Three machine learning techniques, linear regression, support vector regression (SVR) and multi-layer perceptron (MLP) and two optimization processes have been studied in this research. Four main steps, preprocessing (one-time only), model training, model evaluation (testing) and analysis have been implemented in the experiments. With three feature selection strategies, the results of the experiment showed that SVR with genetic algorithm (GA) optimizer achieved the best performance with R2 of 0.694 and the lowest MAE of 0.109.
{"title":"Prediction of biochemical oxygen demand with genetic algorithm-based support vector regression","authors":"Y. Liu, Zhiyuan Chen","doi":"10.2166/wqrj.2023.015","DOIUrl":"https://doi.org/10.2166/wqrj.2023.015","url":null,"abstract":"\u0000 Five-day biochemical oxygen demand (BOD5) is a vital wastewater contamination strength indicator. The process of measuring BOD5 is to measure the mass of molecular oxygen consumed in 1 L of water at 20 °C over 5-day incubation period. It is a time-consuming process and often too late for water management agencies to make a timely reaction if the result of measurement shows a water body is seriously polluted. Biosensors can simplify the process of BOD5 measurement; however, the measurement results often deviate significantly from the measured BOD5 values. The main aim of this research is to identify a machine learning model, which could predict BOD5 value from historical data and make it easier to detect water pollution in advance and timely adopt treatment measures. Three machine learning techniques, linear regression, support vector regression (SVR) and multi-layer perceptron (MLP) and two optimization processes have been studied in this research. Four main steps, preprocessing (one-time only), model training, model evaluation (testing) and analysis have been implemented in the experiments. With three feature selection strategies, the results of the experiment showed that SVR with genetic algorithm (GA) optimizer achieved the best performance with R2 of 0.694 and the lowest MAE of 0.109.","PeriodicalId":23720,"journal":{"name":"Water Quality Research Journal","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43726316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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}
E. Soyer, Halûk Bayram, Nalan Canıgeniş, Onur Eren
We consider the problem of determining water withdrawal depth in water supply reservoirs with multilevel intakes in an effective and systematic manner. In the traditional way, operators decide which intake port to use based on their own experience and water samples taken from various depths. Our goal is to provide assistance to operators in the decision-making process and establish a systematic approach for determining the appropriate water withdrawal level in a stratified reservoir. To achieve this, we propose an algorithmic approach as a decision support system for estimating the water withdrawal level. We validate our approach using long-term data collected from a water supply reservoir and compare the results with those of the operator's decisions. The results reveal that when the depth tolerance is set to 10 m, the approach and operator's decisions match at an 80% rate. However, when the depth tolerance is increased to 15 m, the matching percentage improves to over 90%.
{"title":"Decision support system for selective withdrawal in water supply reservoirs: an approach based on thermal stratification","authors":"E. Soyer, Halûk Bayram, Nalan Canıgeniş, Onur Eren","doi":"10.2166/wqrj.2023.030","DOIUrl":"https://doi.org/10.2166/wqrj.2023.030","url":null,"abstract":"\u0000 We consider the problem of determining water withdrawal depth in water supply reservoirs with multilevel intakes in an effective and systematic manner. In the traditional way, operators decide which intake port to use based on their own experience and water samples taken from various depths. Our goal is to provide assistance to operators in the decision-making process and establish a systematic approach for determining the appropriate water withdrawal level in a stratified reservoir. To achieve this, we propose an algorithmic approach as a decision support system for estimating the water withdrawal level. We validate our approach using long-term data collected from a water supply reservoir and compare the results with those of the operator's decisions. The results reveal that when the depth tolerance is set to 10 m, the approach and operator's decisions match at an 80% rate. However, when the depth tolerance is increased to 15 m, the matching percentage improves to over 90%.","PeriodicalId":23720,"journal":{"name":"Water Quality Research Journal","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47141318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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}
R. Ammeri, S. Kloula, G. Simeone, I. Mehri, Wafa Hassan, A. Hassen
The work was focused on the effect of the bioaugmentation process on STWW contaminated by pentachlorophenol (PCP: 100 mg L−1) by Pseudomonas putida AE015451. The monitoring of bioaugmentation treatments was assessed by chloride content determination via high-performance liquid chromatography (HPLC), optical density (OD) for microbial biomass determination, and pyoverdine and biofilm production. The process of bioaugmentation by a PGPR Pseudomonas strain showed a high-efficiency removal rate of PCP (100 mg L−1). The contaminant decreased up to 92% after 168 h. The production of pyoverdine and the formation of bacterial biofilm by the strain Ps. putida AE015451 showed an important role in tolerating the toxicity of PCP by using it as a carbon source. The obtained result proved that the pyoverdine production and biofilm formation help the Pseudomonas bacteria to tolerate to the stressed condition as pesticide. Moreover, the co-existence of the iron and PCP molecule ameliorate its biodegradation.
{"title":"Pesticide removal by the bioaugmentation process in secondary treated wastewater","authors":"R. Ammeri, S. Kloula, G. Simeone, I. Mehri, Wafa Hassan, A. Hassen","doi":"10.2166/wqrj.2023.001","DOIUrl":"https://doi.org/10.2166/wqrj.2023.001","url":null,"abstract":"\u0000 The work was focused on the effect of the bioaugmentation process on STWW contaminated by pentachlorophenol (PCP: 100 mg L−1) by Pseudomonas putida AE015451. The monitoring of bioaugmentation treatments was assessed by chloride content determination via high-performance liquid chromatography (HPLC), optical density (OD) for microbial biomass determination, and pyoverdine and biofilm production. The process of bioaugmentation by a PGPR Pseudomonas strain showed a high-efficiency removal rate of PCP (100 mg L−1). The contaminant decreased up to 92% after 168 h. The production of pyoverdine and the formation of bacterial biofilm by the strain Ps. putida AE015451 showed an important role in tolerating the toxicity of PCP by using it as a carbon source. The obtained result proved that the pyoverdine production and biofilm formation help the Pseudomonas bacteria to tolerate to the stressed condition as pesticide. Moreover, the co-existence of the iron and PCP molecule ameliorate its biodegradation.","PeriodicalId":23720,"journal":{"name":"Water Quality Research Journal","volume":"1 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2023-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41530669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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}
Hang Zhang, R. Zhao, Ying Yang, Yinyin Liu, Linchen Han
Excessive nitrate in surface waters poses a great threat to the health of human beings. Traditional measuring tools require either hazardous chemicals or organic matter compensation. In this work, we proposed an online microfluidic device incorporated with a miniaturized capacitive deionization cell that separates organic matter and nitrate ions before the measurement and afterwards determines the nitrate concentration with a 235-nm LED. The optimal operational parameter setting, which is a combination of 600-s charging duration and 0.5-V cell potential, was also obtained in order to achieve the maximum fractionation of nitrate ions. Promising results were obtained by our new approach, revealing that this device could serve as a functional and effective tool for the determination of nitrate concentration in surface water.
{"title":"Measuring nitrate concentration in surface waters with a microfluidic device facilitated by a miniaturized capacitive deionization cell","authors":"Hang Zhang, R. Zhao, Ying Yang, Yinyin Liu, Linchen Han","doi":"10.2166/wqrj.2023.010","DOIUrl":"https://doi.org/10.2166/wqrj.2023.010","url":null,"abstract":"\u0000 Excessive nitrate in surface waters poses a great threat to the health of human beings. Traditional measuring tools require either hazardous chemicals or organic matter compensation. In this work, we proposed an online microfluidic device incorporated with a miniaturized capacitive deionization cell that separates organic matter and nitrate ions before the measurement and afterwards determines the nitrate concentration with a 235-nm LED. The optimal operational parameter setting, which is a combination of 600-s charging duration and 0.5-V cell potential, was also obtained in order to achieve the maximum fractionation of nitrate ions. Promising results were obtained by our new approach, revealing that this device could serve as a functional and effective tool for the determination of nitrate concentration in surface water.","PeriodicalId":23720,"journal":{"name":"Water Quality Research Journal","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2023-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47463974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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}
S. A. Abu Amr, M. Abujazar, M. Alazaiza, A. Albahnasawi, M. Bashir, D. Nassani
Microalgae cultivation has received much interest in foods and biofuel production and provides a significant potential option for cleaning the soil, water, and environment from several contaminants. Accordingly, microalgae harvesting becomes essential to separate the solid–liquid microalgae suspension for other green technologies and sustainable processes. Although several physical, chemical, and physiochemical methods have been widely used for microalgae harvesting, their cost, non-environmental residues, and harvesting efficiencies are still questionable. This review summarized and evaluated the performance of different natural coagulants used for harvesting cultivated microalgae. The operational factors and their effect on harvesting efficiency were discussed. Moreover, the current challenges in utilizing several natural coagulants in microalgae harvesting were considered.
{"title":"The potential use of natural coagulants for microalgae harvesting: a review","authors":"S. A. Abu Amr, M. Abujazar, M. Alazaiza, A. Albahnasawi, M. Bashir, D. Nassani","doi":"10.2166/wqrj.2022.026","DOIUrl":"https://doi.org/10.2166/wqrj.2022.026","url":null,"abstract":"\u0000 Microalgae cultivation has received much interest in foods and biofuel production and provides a significant potential option for cleaning the soil, water, and environment from several contaminants. Accordingly, microalgae harvesting becomes essential to separate the solid–liquid microalgae suspension for other green technologies and sustainable processes. Although several physical, chemical, and physiochemical methods have been widely used for microalgae harvesting, their cost, non-environmental residues, and harvesting efficiencies are still questionable. This review summarized and evaluated the performance of different natural coagulants used for harvesting cultivated microalgae. The operational factors and their effect on harvesting efficiency were discussed. Moreover, the current challenges in utilizing several natural coagulants in microalgae harvesting were considered.","PeriodicalId":23720,"journal":{"name":"Water Quality Research Journal","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46650286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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}
Zhenlin Wang, Zhengkui Ge, Ying Wang, Qi Wang, Xiaoxiao Han, Ming Li
Water-level changes in the water-level fluctuating zone (WLFZ) promoted soil and plants to release nutrients into the water, threatening the water health in the reservoir. Plant restoration in the WLFZ is also an important way to reduce the nutrient release in order to select plants that can effectively reduce the release of soil nutrients under changing water levels. This study conducted a flooding experiment to reveal the difference in the change in soil physico-chemical properties and microbial communities planted with various plants under different water-level conditions. The flooding experiment began at the end of September 2020 and was planted with three dominant plants common to reservoirs, namely Cynodon dactylon, Alternanthera philoxeroides, and Acorus calamus. Our study found the three common dominant plants along the reservoir, and C. dactylon had a good adsorption capacity for nitrogen and phosphorus when it was flooded with shallow water, decreasing soil nutrients during the drying period. After a wetting–drying cycle, there was an obvious and significant (p < 0.05) divergence among soil microbial community structures between N0 and D1, D2, and D3, respectively. This study could provide sufficient reference information for plant selection and the assessment of nutrient release of WLFZ in restoration work.
{"title":"Different tolerance of three typical riparian plants (Cynodon dactylon, Alternanthera philoxeroides, and Acorus calamus) to different depths of waterlogging caused variations in soil nutrient release and microbial diversity","authors":"Zhenlin Wang, Zhengkui Ge, Ying Wang, Qi Wang, Xiaoxiao Han, Ming Li","doi":"10.2166/wqrj.2022.125","DOIUrl":"https://doi.org/10.2166/wqrj.2022.125","url":null,"abstract":"\u0000 Water-level changes in the water-level fluctuating zone (WLFZ) promoted soil and plants to release nutrients into the water, threatening the water health in the reservoir. Plant restoration in the WLFZ is also an important way to reduce the nutrient release in order to select plants that can effectively reduce the release of soil nutrients under changing water levels. This study conducted a flooding experiment to reveal the difference in the change in soil physico-chemical properties and microbial communities planted with various plants under different water-level conditions. The flooding experiment began at the end of September 2020 and was planted with three dominant plants common to reservoirs, namely Cynodon dactylon, Alternanthera philoxeroides, and Acorus calamus. Our study found the three common dominant plants along the reservoir, and C. dactylon had a good adsorption capacity for nitrogen and phosphorus when it was flooded with shallow water, decreasing soil nutrients during the drying period. After a wetting–drying cycle, there was an obvious and significant (p < 0.05) divergence among soil microbial community structures between N0 and D1, D2, and D3, respectively. This study could provide sufficient reference information for plant selection and the assessment of nutrient release of WLFZ in restoration work.","PeriodicalId":23720,"journal":{"name":"Water Quality Research Journal","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46446024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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}
Conventionally, impermeable weirs are employed for retaining, measuring, and regulating the water in the river. Still now, alternative devices are more predominantly in vogue, which are made of locally available materials called gabion weirs chosen because the latter can better fulfill ecological needs due to their porous nature. Dissolved oxygen (D.O.) is one of the significant determinants for assessing the character of water bodies. This study mainly focuses on improving the estimation of the gabion oxygen transfer efficiency (OTE20) to enhance its efficacy. The backpropagation neural network (BPNN), adaptive neuro-fuzzy inference system (ANFIS), and multi-variant linear and nonlinear regression (MVLR and MVNLR) are developed with experimental data to estimate the OTE20 and their results are compared. In terms of statistical metrics, the BPNN has proved to be the best-performing model. At the same time, triangular membership function (mf)-based ANFIS is the second-best performing model. Nevertheless, other applied mf-based ANFIS, MVLR, and MVNLR are giving a comparable performance. Input variable discharge per unit width (q) is the most crucial parameter in the computation of the OTE20, followed by the gabion mean size (d50). Major challenges are found in computing porosity of the gabion materials and optimal parameters of proposed data mining techniques.
{"title":"Estimating gabion weir oxygen transfer with data mining","authors":"N. K. Tiwari, Kumari Luxmi, S. Ranjan","doi":"10.2166/wqrj.2022.023","DOIUrl":"https://doi.org/10.2166/wqrj.2022.023","url":null,"abstract":"\u0000 Conventionally, impermeable weirs are employed for retaining, measuring, and regulating the water in the river. Still now, alternative devices are more predominantly in vogue, which are made of locally available materials called gabion weirs chosen because the latter can better fulfill ecological needs due to their porous nature. Dissolved oxygen (D.O.) is one of the significant determinants for assessing the character of water bodies. This study mainly focuses on improving the estimation of the gabion oxygen transfer efficiency (OTE20) to enhance its efficacy. The backpropagation neural network (BPNN), adaptive neuro-fuzzy inference system (ANFIS), and multi-variant linear and nonlinear regression (MVLR and MVNLR) are developed with experimental data to estimate the OTE20 and their results are compared. In terms of statistical metrics, the BPNN has proved to be the best-performing model. At the same time, triangular membership function (mf)-based ANFIS is the second-best performing model. Nevertheless, other applied mf-based ANFIS, MVLR, and MVNLR are giving a comparable performance. Input variable discharge per unit width (q) is the most crucial parameter in the computation of the OTE20, followed by the gabion mean size (d50). Major challenges are found in computing porosity of the gabion materials and optimal parameters of proposed data mining techniques.","PeriodicalId":23720,"journal":{"name":"Water Quality Research Journal","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45678293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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}
Ivan D. Medel, M. Gabriel, Greta M Wengert, M. Filigenzi, D. Clifford
Several studies have documented the use of pesticides in cannabis cultivation. In northern California, one of the top cannabis production regions, several studies have identified cannabis-related impacts on multiple terrestrial wildlife species. To date, research has not focused on the potential for cannabis-related pesticides to contaminate downstream waterways and aquatic species. We conducted a two-part multi-scale study utilizing polar organic chemical integrative samplers (POCIS) to monitor pesticide contamination (1) immediately downstream and upstream of illegal public land cannabis cultivation complexes in low-order tributaries and (2) below a gradient of private land cannabis cultivation operations within higher-order streams. Diazinon and carbofuran were confirmed within sensitive headwater streams downstream of illegal public land cultivation sites in remote settings within four National Forests. Diazinon demonstrated higher downstream transport potential, with overland and in-stream flow distances totaling up to 186 m downstream of cultivation areas. While carbofuran displayed greater temporal longevity, being detected over 490 days after the last estimated pesticide application, no positive detections were identified within POCIS deployed within higher-order catchments. The utility of targeted POCIS deployed within low-order catchments is validated and confirms downstream cannabis-related water contamination on National Forest lands.
{"title":"Passive monitoring of soluble pesticides linked to cannabis cultivation: a multi-scale analysis","authors":"Ivan D. Medel, M. Gabriel, Greta M Wengert, M. Filigenzi, D. Clifford","doi":"10.2166/wqrj.2022.101","DOIUrl":"https://doi.org/10.2166/wqrj.2022.101","url":null,"abstract":"\u0000 Several studies have documented the use of pesticides in cannabis cultivation. In northern California, one of the top cannabis production regions, several studies have identified cannabis-related impacts on multiple terrestrial wildlife species. To date, research has not focused on the potential for cannabis-related pesticides to contaminate downstream waterways and aquatic species. We conducted a two-part multi-scale study utilizing polar organic chemical integrative samplers (POCIS) to monitor pesticide contamination (1) immediately downstream and upstream of illegal public land cannabis cultivation complexes in low-order tributaries and (2) below a gradient of private land cannabis cultivation operations within higher-order streams. Diazinon and carbofuran were confirmed within sensitive headwater streams downstream of illegal public land cultivation sites in remote settings within four National Forests. Diazinon demonstrated higher downstream transport potential, with overland and in-stream flow distances totaling up to 186 m downstream of cultivation areas. While carbofuran displayed greater temporal longevity, being detected over 490 days after the last estimated pesticide application, no positive detections were identified within POCIS deployed within higher-order catchments. The utility of targeted POCIS deployed within low-order catchments is validated and confirms downstream cannabis-related water contamination on National Forest lands.","PeriodicalId":23720,"journal":{"name":"Water Quality Research Journal","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45770584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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}
Diffuse groundwater pollution by agricultural land-use practices is a major international problem. The evolution of the problem in two similar areas of Northern Europe, highly dependent on groundwater for public water supply and arable agriculture for economic production, is reviewed over decades through reference to some exceptionally long-term monitoring data. In Denmark, the greatest concern has been with excessive concentrations of pesticides and their metabolites but significant nitrate problems have also been experienced in some areas. In Eastern England, rising groundwater nitrate concentrations constituted the greater problem but pesticide issues also had to be confronted. An in-depth assessment of the approaches available to water utilities for addressing the problem is provided, contrasting treatment solutions, which have major implications for carbon footprint, with land-use controls, to eliminate or reduce nitrate and pesticide leaching, in groundwater source catchment areas.
{"title":"Diffuse agricultural pollution of groundwater: addressing impacts in Denmark and Eastern England","authors":"S. Foster, T. Bjerre","doi":"10.2166/wqrj.2022.022","DOIUrl":"https://doi.org/10.2166/wqrj.2022.022","url":null,"abstract":"\u0000 Diffuse groundwater pollution by agricultural land-use practices is a major international problem. The evolution of the problem in two similar areas of Northern Europe, highly dependent on groundwater for public water supply and arable agriculture for economic production, is reviewed over decades through reference to some exceptionally long-term monitoring data. In Denmark, the greatest concern has been with excessive concentrations of pesticides and their metabolites but significant nitrate problems have also been experienced in some areas. In Eastern England, rising groundwater nitrate concentrations constituted the greater problem but pesticide issues also had to be confronted. An in-depth assessment of the approaches available to water utilities for addressing the problem is provided, contrasting treatment solutions, which have major implications for carbon footprint, with land-use controls, to eliminate or reduce nitrate and pesticide leaching, in groundwater source catchment areas.","PeriodicalId":23720,"journal":{"name":"Water Quality Research Journal","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48324130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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}
Thermal pollution is an environmental impact of large dams altering the natural temperature regime of downstream river ecosystems. The present study proposes a simulation–optimization framework to reduce thermal pollution downstream from reservoirs and tests it on a real-world case study. This framework attempts to simultaneously minimize the environmental impacts as well as losses to reservoir objectives for water supply. A hybrid machine-learning model is applied to simulate water temperature downstream of the reservoir under various operation scenarios. This model is shown to be robust and achieves acceptable predictive accuracy. The results of simulation–optimization indicate that the reservoir could be operated in such a way that the natural temperature regime is reasonably preserved to protect downstream habitats. Doing so, however, would result in significant trade-offs for reservoir storage and water supply objectives. Such trade-offs can undermine the benefits of reservoirs and need to be carefully considered in reservoir design and operation.
{"title":"A simulation–optimization framework for reducing thermal pollution downstream of reservoirs","authors":"M. Sedighkia, B. Datta, S. Razavi","doi":"10.2166/wqrj.2022.018","DOIUrl":"https://doi.org/10.2166/wqrj.2022.018","url":null,"abstract":"\u0000 Thermal pollution is an environmental impact of large dams altering the natural temperature regime of downstream river ecosystems. The present study proposes a simulation–optimization framework to reduce thermal pollution downstream from reservoirs and tests it on a real-world case study. This framework attempts to simultaneously minimize the environmental impacts as well as losses to reservoir objectives for water supply. A hybrid machine-learning model is applied to simulate water temperature downstream of the reservoir under various operation scenarios. This model is shown to be robust and achieves acceptable predictive accuracy. The results of simulation–optimization indicate that the reservoir could be operated in such a way that the natural temperature regime is reasonably preserved to protect downstream habitats. Doing so, however, would result in significant trade-offs for reservoir storage and water supply objectives. Such trade-offs can undermine the benefits of reservoirs and need to be carefully considered in reservoir design and operation.","PeriodicalId":23720,"journal":{"name":"Water Quality Research Journal","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42910977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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