In this paper, the elephant in the room is the issue of projected longer-term population growths and declines in a finite world, while the Greek goddess Panacea is the opportunity to non-disruptively attain populations that live sustainably and solve some of the world’s most pressing problems. Particularly addressed in this paper is the potential of water systems models and modeling to facilitate a transition to planning for long-term sustainable lives of sustained quality. Anent “longer term”, for simplicity we consider both a typical period of family memory, for instance from 1880 to 2100, or 220 years, about seven or eight generations, as well as the anthropocene millenia. After setting down background definitions and introducing the underlying issues, we review key population and well-being trends, attitudes, and impacts, citing acknowledged experts. How, where, and when population and economic decline will occur is not covered; the paper rather suggests implications for water resources engineering and for water management modeling, even if the transition will be patchy in space and time. Confronting imminent degrowth, significant revisions of current water modeling practice are suggested: planned, phased, orderly removal of projected and existing urban development and drainage infrastructure and, for instance and where applicable, systematic restoration of keystone ecology and natural hydrology. Whether the imminent degrowth era will persist is uncertain, evidently. Also alluded to is degrowth’s countervailing assurance of improved well-being, providing more time for individuals to further their personal interests. The original PowerPoint presentation is at Robillynians.org and also at the CHI website (James 2023). Questions raised and the answers given at the presentation are included in the appendix to this paper.
{"title":"The Elephant and the Goddess: How Water Systems Models Could Help Preserve Civil Life","authors":"William James","doi":"10.14796/jwmm.c507","DOIUrl":"https://doi.org/10.14796/jwmm.c507","url":null,"abstract":"In this paper, the elephant in the room is the issue of projected longer-term population growths and declines in a finite world, while the Greek goddess Panacea is the opportunity to non-disruptively attain populations that live sustainably and solve some of the world’s most pressing problems. Particularly addressed in this paper is the potential of water systems models and modeling to facilitate a transition to planning for long-term sustainable lives of sustained quality. Anent “longer term”, for simplicity we consider both a typical period of family memory, for instance from 1880 to 2100, or 220 years, about seven or eight generations, as well as the anthropocene millenia. After setting down background definitions and introducing the underlying issues, we review key population and well-being trends, attitudes, and impacts, citing acknowledged experts. How, where, and when population and economic decline will occur is not covered; the paper rather suggests implications for water resources engineering and for water management modeling, even if the transition will be patchy in space and time. Confronting imminent degrowth, significant revisions of current water modeling practice are suggested: planned, phased, orderly removal of projected and existing urban development and drainage infrastructure and, for instance and where applicable, systematic restoration of keystone ecology and natural hydrology. Whether the imminent degrowth era will persist is uncertain, evidently. Also alluded to is degrowth’s countervailing assurance of improved well-being, providing more time for individuals to further their personal interests. The original PowerPoint presentation is at Robillynians.org and also at the CHI website (James 2023). Questions raised and the answers given at the presentation are included in the appendix to this paper.","PeriodicalId":43297,"journal":{"name":"Journal of Water Management Modeling","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135318848","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}
In the hydrological cycle, runoff precipitation is one of the most significant and complex phenomena. In order to develop and improve predictive models, different perspectives have been presented in its modeling. Hydrological processes can be confidently modeled with the help of artificial intelligence techniques. In this study, the runoff of the Leilanchai watershed was simulated using artificial neural networks (ANNs) and M5 model tree methods and their hybrid with wavelet transform. Seventy percent of the data used in the train state and thirty percent in the test state were collected in this watershed from 2000 to 2021. In addition to daily and monthly scales, simulated and observed results were compared within each scale. Initially, the rainfall and runoff time series were divided into multiple sub-series using the wavelet transform to combat instability. The resultant subheadings were then utilized as input for an ANN and M5 model tree. The results demonstrated that hybrid models with wavelet improved the ANN model's daily accuracy by 4% and its monthly accuracy by 26%. It also improved the M5 model tree's daily and monthly accuracy by 4% and 41%. The wavelet-M5 model's accuracy does not diminish to the same degree as the wavelet-ANN (WANN) model as the forecast horizon lengthens. Consequently, the Leilanchai watershed has a relatively stable behavior pattern. Finally, hybrid models, in conjunction with the wavelet transform, improve forecast accuracy.
{"title":"Investigating the Accuracy of Hybrid Models with Wavelet Transform in the Forecast of Watershed Runoff","authors":"Mohammad Javad Saravani, Sahar Kashef, Mahdi Farmahini, Mahdi Kashefi, Mahdi Zohreh","doi":"10.14796/jwmm.c499","DOIUrl":"https://doi.org/10.14796/jwmm.c499","url":null,"abstract":"In the hydrological cycle, runoff precipitation is one of the most significant and complex phenomena. In order to develop and improve predictive models, different perspectives have been presented in its modeling. Hydrological processes can be confidently modeled with the help of artificial intelligence techniques. In this study, the runoff of the Leilanchai watershed was simulated using artificial neural networks (ANNs) and M5 model tree methods and their hybrid with wavelet transform. Seventy percent of the data used in the train state and thirty percent in the test state were collected in this watershed from 2000 to 2021. In addition to daily and monthly scales, simulated and observed results were compared within each scale. Initially, the rainfall and runoff time series were divided into multiple sub-series using the wavelet transform to combat instability. The resultant subheadings were then utilized as input for an ANN and M5 model tree. The results demonstrated that hybrid models with wavelet improved the ANN model's daily accuracy by 4% and its monthly accuracy by 26%. It also improved the M5 model tree's daily and monthly accuracy by 4% and 41%. The wavelet-M5 model's accuracy does not diminish to the same degree as the wavelet-ANN (WANN) model as the forecast horizon lengthens. Consequently, the Leilanchai watershed has a relatively stable behavior pattern. Finally, hybrid models, in conjunction with the wavelet transform, improve forecast accuracy.","PeriodicalId":43297,"journal":{"name":"Journal of Water Management Modeling","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135685807","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}
This article discusses challenges encountered in implementing Information Communication Technology tools in water and sanitation services management in South Africa. This qualitative study used a Human Capital Development framework. The study area has had limited consultation on Information Communication Technology tools, low Information Communication Technology usage, and skills gap. Attention is paid to the effective use of Information Communication Technology tools, for example, mobile phones and their application to address the challenges faced. This promotes proper water and sanitation services management by implementing relevant tools to increase the knowledge and skills of service providers. South Africa needs to address and eliminate challenges experienced in implementing Information Communication Technology tools, inequalities, and human-made challenges to ensure availability of services and sustainable water and sanitation services management.
{"title":"Challenges in Implementing ICT Tools in Water and Sanitation Services Management in South Africa","authors":"Tafadzwa Jaquline Mukasi, Olabanji Oni","doi":"10.14796/jwmm.c506","DOIUrl":"https://doi.org/10.14796/jwmm.c506","url":null,"abstract":"This article discusses challenges encountered in implementing Information Communication Technology tools in water and sanitation services management in South Africa. This qualitative study used a Human Capital Development framework. The study area has had limited consultation on Information Communication Technology tools, low Information Communication Technology usage, and skills gap. Attention is paid to the effective use of Information Communication Technology tools, for example, mobile phones and their application to address the challenges faced. This promotes proper water and sanitation services management by implementing relevant tools to increase the knowledge and skills of service providers. South Africa needs to address and eliminate challenges experienced in implementing Information Communication Technology tools, inequalities, and human-made challenges to ensure availability of services and sustainable water and sanitation services management.","PeriodicalId":43297,"journal":{"name":"Journal of Water Management Modeling","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135057673","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}
Ali M. Sulaiman, Kotayba T. Al-Youzbakey, Daad A. Ismael
Wadi Bandawaya, which is 40 km north of Mosul in Iraq, pierces Mount Dahqan and creates a small valley that is ideal for the construction of a dam for harvesting rainwater. Water quality is evaluated for domestic and agricultural uses using chemical analyses of the main cations (Ca2+, Mg2+, Na+, K+), anions (HCO3-, SO42-, Cl-, NO3-), as well as measurements of the acidity function (pH), electrical conductivity (Ec), concentration of total dissolved salts (TDS), and total hardness (TH). The valley water is considered to be within the limits permitted for drinking by the World Health Organization. If held inside the water harvesting project of the Bandawaya dam, the water of Bandawaya Valley is freshwater, suitable for drinking and domestic applications, according to the water quality index (WQI). It is also suitable for irrigation of agricultural lands adjacent to the valley in accordance with standards of the percentage of sodium (SSP), the rate of sodium adsorption (Sodium Adsorption Ratio, SAR), the quantity of residual sodium carbonate (Residual Sodium Bicarbonate, RSBC), and the percentage of magnesium (MAR). When there is little rain, the harvested water will be used for irrigation, as well as for supplemental irrigation techniques.
{"title":"The Variation of Water Parameters along the Bandawaya Valley, Northern Iraq","authors":"Ali M. Sulaiman, Kotayba T. Al-Youzbakey, Daad A. Ismael","doi":"10.14796/jwmm.c504","DOIUrl":"https://doi.org/10.14796/jwmm.c504","url":null,"abstract":"Wadi Bandawaya, which is 40 km north of Mosul in Iraq, pierces Mount Dahqan and creates a small valley that is ideal for the construction of a dam for harvesting rainwater. Water quality is evaluated for domestic and agricultural uses using chemical analyses of the main cations (Ca2+, Mg2+, Na+, K+), anions (HCO3-, SO42-, Cl-, NO3-), as well as measurements of the acidity function (pH), electrical conductivity (Ec), concentration of total dissolved salts (TDS), and total hardness (TH). The valley water is considered to be within the limits permitted for drinking by the World Health Organization. If held inside the water harvesting project of the Bandawaya dam, the water of Bandawaya Valley is freshwater, suitable for drinking and domestic applications, according to the water quality index (WQI). It is also suitable for irrigation of agricultural lands adjacent to the valley in accordance with standards of the percentage of sodium (SSP), the rate of sodium adsorption (Sodium Adsorption Ratio, SAR), the quantity of residual sodium carbonate (Residual Sodium Bicarbonate, RSBC), and the percentage of magnesium (MAR). When there is little rain, the harvested water will be used for irrigation, as well as for supplemental irrigation techniques.","PeriodicalId":43297,"journal":{"name":"Journal of Water Management Modeling","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66654937","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}
Developing a solid understanding of the nitrogen dynamics across the Tigris River is critical to evaluate the environmental degradation of the increased N fluxes. Nitrite, nitrate, and total oxidized N (nitrite+nitrate) were monitored from April 2018 to August 2019. Plug flow reactors and continuously stirred tank reactors in series models were implemented to explore N behavior in the river system. The results indicated that the total oxidized N decreased over the first half of the study period, then was followed by a high rate of nitrate production. These findings are also supported by changes of the river flow rates, dissolved oxygen, pH, and chemical oxygen demand. The models have the capacity to simulate N dynamics, with varied prediction errors. Root mean squared errors between measured and predicted nitrite, nitrate, and total oxidized N concentrations were 0.118, 2.595, and 2.560 g m-3, respectively, for the PFR model, while these values were 0.05, 0.175 g m-3, and 0.176 g m-3, respectively, for the CSTRS model. The correlation coefficients were 0.012, 0.925, and 0.922 for nitrite, nitrate, and total oxidized N, respectively, when the PFR model was applied. These values were 0.92, 0.99, and 0.99, respectively, after the application of the CSTRS model. Obtained results revealed that the modeling approach can provide a useful framework to improve understanding of N dynamics, which helps to develop mitigation strategies for sustaining water quality in the Tigris River.
对底格里斯河流域氮动态的深入了解，对于评价氮通量增加所造成的环境退化至关重要。2018年4月至2019年8月监测亚硝酸盐、硝酸盐和总氧化氮(亚硝酸盐+硝酸盐)。采用塞流反应器和连续搅拌槽式反应器进行串联模型，探索N在河流系统中的行为。结果表明，在试验前半期，总氧化氮呈下降趋势，随后硝态氮高产。这些发现也得到了河流流速、溶解氧、pH值和化学需氧量变化的支持。该模型具有模拟N动态的能力，具有不同的预测误差。对于PFR模型，亚硝酸盐、硝酸盐和总氧化氮浓度的测量值与预测值的均方根误差分别为0.118、2.595和2.560 g m-3，而对于CSTRS模型，这些值分别为0.05、0.175 g m-3和0.176 g m-3。采用PFR模型时，亚硝酸盐、硝酸盐和总氧化氮的相关系数分别为0.012、0.925和0.922。应用CSTRS模型后，这些值分别为0.92、0.99和0.99。所获得的结果表明，建模方法可以提供一个有用的框架，以提高对氮动力学的理解，这有助于制定缓解策略，以维持底格里斯河的水质。
{"title":"Model-based Analysis of Nitrogen Dynamics in the Tigris River in Baghdad City","authors":"Muwafaq H. Al Lami, I. Alwan, H. Ismael","doi":"10.14796/jwmm.c495","DOIUrl":"https://doi.org/10.14796/jwmm.c495","url":null,"abstract":"Developing a solid understanding of the nitrogen dynamics across the Tigris River is critical to evaluate the environmental degradation of the increased N fluxes. Nitrite, nitrate, and total oxidized N (nitrite+nitrate) were monitored from April 2018 to August 2019. Plug flow reactors and continuously stirred tank reactors in series models were implemented to explore N behavior in the river system. The results indicated that the total oxidized N decreased over the first half of the study period, then was followed by a high rate of nitrate production. These findings are also supported by changes of the river flow rates, dissolved oxygen, pH, and chemical oxygen demand. The models have the capacity to simulate N dynamics, with varied prediction errors. Root mean squared errors between measured and predicted nitrite, nitrate, and total oxidized N concentrations were 0.118, 2.595, and 2.560 g m-3, respectively, for the PFR model, while these values were 0.05, 0.175 g m-3, and 0.176 g m-3, respectively, for the CSTRS model. The correlation coefficients were 0.012, 0.925, and 0.922 for nitrite, nitrate, and total oxidized N, respectively, when the PFR model was applied. These values were 0.92, 0.99, and 0.99, respectively, after the application of the CSTRS model. Obtained results revealed that the modeling approach can provide a useful framework to improve understanding of N dynamics, which helps to develop mitigation strategies for sustaining water quality in the Tigris River.","PeriodicalId":43297,"journal":{"name":"Journal of Water Management Modeling","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66655163","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}
A decision tree-based approach is projected to predict surface water quality and is a good tool to assess the quality and guarantee the safe use of water for drinking. Modeling surface water quality using artificial intelligence-based models is essential in projecting suitable mitigation measures; however, it remains a challenge and requires further research to enhance the modeling accuracy. Because of the serious effects of low water quality, a faster and less expensive solution is required. With this motivation, this research explores a series of supervised machine learning algorithms to estimate the water quality. The objective of this study is to assess the surface water quality of the Daya watercourse to determine the optimal procedure to measure quality of drinking water. Samples were collected from designated locations throughout different seasons (winter, summer, rainy) over a period of five years (2016, 2017, 2018, 2019, and 2020). Total dissolved solids, pH, alkalinity, chloride, nitrate, total hardness, calcium, magnesium, iron, fluoride, were all tested, as well as total coliform, fecal coliform, and E. coli. Through this decision tree regression model, accuracy of prediction is 93.77%. This is a significant result, indicating that the decision tree-based approach has the potential to be a useful tool for surface water quality prediction. However, it is important to note that there may be limitations and uncertainties in the model, and further research and validation may be required to improve the accuracy and dependability of forecasts. The catastrophic consequences of poor water quality, as well as the need for faster and less expensive technologies for testing water quality, are the driving factors in this study. The study's findings can help to improve knowledge of water quality in the Daya watercourse and enhance the decision-making processes to ensure safe drinking water.
{"title":"Surface Water Quality Assessment, Prediction, and Modeling of the River Daya in Odisha","authors":"Pramod Kumar Jena, Sayed Modinur Rahaman, Pradeep Kumar Das Mohapatra, Durga Prasad Barik, Dikshya Surabhi Patra","doi":"10.14796/jwmm.c508","DOIUrl":"https://doi.org/10.14796/jwmm.c508","url":null,"abstract":"A decision tree-based approach is projected to predict surface water quality and is a good tool to assess the quality and guarantee the safe use of water for drinking. Modeling surface water quality using artificial intelligence-based models is essential in projecting suitable mitigation measures; however, it remains a challenge and requires further research to enhance the modeling accuracy. Because of the serious effects of low water quality, a faster and less expensive solution is required. With this motivation, this research explores a series of supervised machine learning algorithms to estimate the water quality. The objective of this study is to assess the surface water quality of the Daya watercourse to determine the optimal procedure to measure quality of drinking water. Samples were collected from designated locations throughout different seasons (winter, summer, rainy) over a period of five years (2016, 2017, 2018, 2019, and 2020). Total dissolved solids, pH, alkalinity, chloride, nitrate, total hardness, calcium, magnesium, iron, fluoride, were all tested, as well as total coliform, fecal coliform, and E. coli. Through this decision tree regression model, accuracy of prediction is 93.77%. This is a significant result, indicating that the decision tree-based approach has the potential to be a useful tool for surface water quality prediction. However, it is important to note that there may be limitations and uncertainties in the model, and further research and validation may be required to improve the accuracy and dependability of forecasts. The catastrophic consequences of poor water quality, as well as the need for faster and less expensive technologies for testing water quality, are the driving factors in this study. The study's findings can help to improve knowledge of water quality in the Daya watercourse and enhance the decision-making processes to ensure safe drinking water.","PeriodicalId":43297,"journal":{"name":"Journal of Water Management Modeling","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135559718","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}
The rainfall–runoff relationship was studied in the Wadi El Kebir watershed, located in Northeastern Algeria, using TOPMODEL (topography based hydrological model). This is a geomorphological and semi-distributed model which is used to predict the hydrological behaviour of watersheds and to calculate the water storage deficit of an aquifer in any location. It uses topographic information of the watershed to predict the extent of contributing areas in the production of runoff. TOPMODEL was applied with event-based rainfall–runoff modeling where 13 hourly rainfall series were used to predict the discharge at the basin outlet. A digital elevation model (DEM) was also used to define the contours of the basin and to map out the drainage directions and the topographic index. TOPMODEL was calibrated and validated using the measured discharges and various objective functions such as Nash (Nash-Sutcliffe) and coefficient of determination (R2). The TOPMODEL results showed a high-performance level. Indeed, after the calibration and validation procedure, the performance of the model oscillates between satisfactory and very good. For the calibration, Nash varied between 0.59 and 0.91, and R2 between 0.66 and 0.91. However, the values of these criteria coefficients were slightly reduced during the validation phase, Nash (0.53 to 0.84) and R2 (0.59 to 0.87). Also, the proposed model shows the weak contribution of groundwater flows in the hydrological response of the study area.
{"title":"Modeling the Rainfall–Runoff Relationship with TOPMODEL in the Wadi El Kebir Watershed","authors":"Noureddine Maref, Khaled Korichi, Zakaria Mahfoud","doi":"10.14796/jwmm.c497","DOIUrl":"https://doi.org/10.14796/jwmm.c497","url":null,"abstract":"The rainfall–runoff relationship was studied in the Wadi El Kebir watershed, located in Northeastern Algeria, using TOPMODEL (topography based hydrological model). This is a geomorphological and semi-distributed model which is used to predict the hydrological behaviour of watersheds and to calculate the water storage deficit of an aquifer in any location. It uses topographic information of the watershed to predict the extent of contributing areas in the production of runoff. TOPMODEL was applied with event-based rainfall–runoff modeling where 13 hourly rainfall series were used to predict the discharge at the basin outlet. A digital elevation model (DEM) was also used to define the contours of the basin and to map out the drainage directions and the topographic index. TOPMODEL was calibrated and validated using the measured discharges and various objective functions such as Nash (Nash-Sutcliffe) and coefficient of determination (R2). The TOPMODEL results showed a high-performance level. Indeed, after the calibration and validation procedure, the performance of the model oscillates between satisfactory and very good. For the calibration, Nash varied between 0.59 and 0.91, and R2 between 0.66 and 0.91. However, the values of these criteria coefficients were slightly reduced during the validation phase, Nash (0.53 to 0.84) and R2 (0.59 to 0.87). Also, the proposed model shows the weak contribution of groundwater flows in the hydrological response of the study area.","PeriodicalId":43297,"journal":{"name":"Journal of Water Management Modeling","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66654756","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}
Given the wide dependency on surface water used to supply drinking water, agricultural irrigation, and industrial activities, nitrate pollution has posed a serious concern in the Tigris River in recent years. The main objective of this study was to develop an understanding of the spatiotemporal patterns of nitrate distribution in the Tigris River through an integrated approach using hydrological data, physicochemical parameters, and model-based analysis. Eighty-four monthly sampling campaigns from forty monitoring locations along the Tigris River were carried out from January 2011 to December 2018. Obtained results demonstrated that the NO3- dynamics were strongly correlated with the length of transport distance and flow rates along the river system (p < 0.05). High flow rates in the upper courses of the river system favored physical transport of NO3- and promoted a dilution effect. However, low flow rates in the lower sections favored the accumulation processes of NO3- and promoted a concentration effect. High concentration of 7.0±1.96 g NO3- m-3 was observed in February 2018 downstream in the river. No significant seasonal effect in NO3- concentrations were observed. These results were supported by the changes in dissolved oxygen concentration and pH in the river system and indicated high nitrification rates and elevated NO3- accumulation, particularly downstream in the river. This modeling approach has also confirmed field observations of NO3- dynamics with 65% of the variances in the river system being explained by the model.
{"title":"Spatial and Temporal Analysis of Nitrate Dynamics along the Tigris River","authors":"Muwafaq H. Al Lami","doi":"10.14796/jwmm.c503","DOIUrl":"https://doi.org/10.14796/jwmm.c503","url":null,"abstract":"Given the wide dependency on surface water used to supply drinking water, agricultural irrigation, and industrial activities, nitrate pollution has posed a serious concern in the Tigris River in recent years. The main objective of this study was to develop an understanding of the spatiotemporal patterns of nitrate distribution in the Tigris River through an integrated approach using hydrological data, physicochemical parameters, and model-based analysis. Eighty-four monthly sampling campaigns from forty monitoring locations along the Tigris River were carried out from January 2011 to December 2018. Obtained results demonstrated that the NO3- dynamics were strongly correlated with the length of transport distance and flow rates along the river system (p < 0.05). High flow rates in the upper courses of the river system favored physical transport of NO3- and promoted a dilution effect. However, low flow rates in the lower sections favored the accumulation processes of NO3- and promoted a concentration effect. High concentration of 7.0±1.96 g NO3- m-3 was observed in February 2018 downstream in the river. No significant seasonal effect in NO3- concentrations were observed. These results were supported by the changes in dissolved oxygen concentration and pH in the river system and indicated high nitrification rates and elevated NO3- accumulation, particularly downstream in the river. This modeling approach has also confirmed field observations of NO3- dynamics with 65% of the variances in the river system being explained by the model.","PeriodicalId":43297,"journal":{"name":"Journal of Water Management Modeling","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66654930","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}
Khee Ling Woon, H. Goh, Chun Kiat Chang, Siti Fairuz Juiani, N. Zakaria
Model for Urban Storm Water Improvement Conceptualism (MUSIC) software has been widely used to predict the treatment and performance of stormwater Best Management Practices (BMPs) such as bioretention for decision-making purposes in stormwater management. However, the calibration of bioretention models based on pollutant runoff characteristics in the tropics is rarely studied. This paper presents the calibration of bioretention model parameters using MUSIC software to treat polluted runoff in a tropical climate. The bioretention model was simulated based on a pilot study at the Universiti Sains Malaysia (USM) engineering campus to evaluate the flow rate and pollutant’s reduction performance. Two stages of calibration were conducted, with the first stage to calibrate the inflow and pollutant concentrations, and the second stage to further calibrate the k-C* model to fit the experimental results. The validation of the model was done using the percentage bias between modeled and experimental data to evaluate the accuracy of bioretention modeling using MUSIC software. Overall, the accuracy of this model increased after calibration and can be accepted, as the performance of bioretention models for total suspended solids, total nitrogen, and total phosphorus removal percentage are good or very good (-13%, -4%, and -39% respectively), whereas the flow rate reduction is satisfactory (17%).
{"title":"Bioretention Model for Urban Runoff Treatment in a Tropical Climate: A Case Study at the Universiti Sains Malaysia","authors":"Khee Ling Woon, H. Goh, Chun Kiat Chang, Siti Fairuz Juiani, N. Zakaria","doi":"10.14796/jwmm.c498","DOIUrl":"https://doi.org/10.14796/jwmm.c498","url":null,"abstract":"Model for Urban Storm Water Improvement Conceptualism (MUSIC) software has been widely used to predict the treatment and performance of stormwater Best Management Practices (BMPs) such as bioretention for decision-making purposes in stormwater management. However, the calibration of bioretention models based on pollutant runoff characteristics in the tropics is rarely studied. This paper presents the calibration of bioretention model parameters using MUSIC software to treat polluted runoff in a tropical climate. The bioretention model was simulated based on a pilot study at the Universiti Sains Malaysia (USM) engineering campus to evaluate the flow rate and pollutant’s reduction performance. Two stages of calibration were conducted, with the first stage to calibrate the inflow and pollutant concentrations, and the second stage to further calibrate the k-C* model to fit the experimental results. The validation of the model was done using the percentage bias between modeled and experimental data to evaluate the accuracy of bioretention modeling using MUSIC software. Overall, the accuracy of this model increased after calibration and can be accepted, as the performance of bioretention models for total suspended solids, total nitrogen, and total phosphorus removal percentage are good or very good (-13%, -4%, and -39% respectively), whereas the flow rate reduction is satisfactory (17%).","PeriodicalId":43297,"journal":{"name":"Journal of Water Management Modeling","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66654766","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}
Luis A. Gil-Alana, María Jesús González-Blanch, Carmen Lafuente, Tiina Nõges, Merja Pulkkanen
This paper uses long memory and fractional integration techniques to analyze the presence of time trends in the water temperatures of three large European rivers (the Rhine at Lobith, the Danube at Wienna, the Meuse at Eijsden) and two lakes (Saimaa in Finland, and Võrtsjärv in Estonia). Long memory is a feature frequently observed in hydrological data, and it is important to consider it to appropriately estimate the potential trends in the data. The results indicate the existence of significant positive trends in all the five series examined, possibly as a consequence of global warming. Interestingly, once the time trends are taken into consideration, the degree of persistence substantially decreases in all cases and the long memory property in the data disappears.
{"title":"Long Memory, Time Trends, and the Degree of Persistence in Water Temperatures of Five European Rivers and Lakes","authors":"Luis A. Gil-Alana, María Jesús González-Blanch, Carmen Lafuente, Tiina Nõges, Merja Pulkkanen","doi":"10.14796/jwmm.c505","DOIUrl":"https://doi.org/10.14796/jwmm.c505","url":null,"abstract":"This paper uses long memory and fractional integration techniques to analyze the presence of time trends in the water temperatures of three large European rivers (the Rhine at Lobith, the Danube at Wienna, the Meuse at Eijsden) and two lakes (Saimaa in Finland, and Võrtsjärv in Estonia). Long memory is a feature frequently observed in hydrological data, and it is important to consider it to appropriately estimate the potential trends in the data. The results indicate the existence of significant positive trends in all the five series examined, possibly as a consequence of global warming. Interestingly, once the time trends are taken into consideration, the degree of persistence substantially decreases in all cases and the long memory property in the data disappears.","PeriodicalId":43297,"journal":{"name":"Journal of Water Management Modeling","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135007783","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：