Pub Date : 2023-09-01DOI: 10.1061/jwrmd5.wreng-5985
Astrid Hernández-Cruz, S. Sandoval‐Solis, L. Mendoza-Espinosa, J. Ramírez-Hernández, J. Medellín-Azuara, L. W. Daesslé
: The water management of the Colorado River is at a tipping point. This paper describes water management strategies in the Mexican portion of the Colorado River Basin considering water scarcity scenarios. A water allocation model was constructed representing current and future water demands and supply. The Colorado River system in Mexican territory is used as a case study, and all its water demands are characterized [Irrigation District Rio Colorado (DR-014), Mexicali, San Luis Rio Colorado, Tecate, Tijuana-Rosarito, and Ensenada]. Individual strategies were run by subsystem and then their impact was analyzed systemwide. Performance criteria and a performance-based sustainability index were evaluated to identify water stressors and management strategies to improve water supply for agricultural, urban, and environmental users. Analysis of results shows that the irrigation district (DR-014) is the most affected user due to water cuts because it has the lowest priority and, thus, any reduction in Colorado River allocations affects them directly. A range of water management strategies was investigated, including a no-action scenario. The current system depends on the long-term aquifer overdraft to supply water demand. The reduction of the cultivated area was the strategy that increased the sustainability index the most for DR-014. Agricultural to urban transfers, water use efficiency, wastewater reuse, and desalination are prime possibilities to improve the current water supply in the coastal zone (Tijuana, Rosarito, Ensenada). This research shows the spectrum of possible outcomes that could be expected, ranging from systemwide effects of inaction to the implementation of a portfolio of water
{"title":"Assessing Water Management Strategies under Water Scarcity in the Mexican Portion of the Colorado River Basin","authors":"Astrid Hernández-Cruz, S. Sandoval‐Solis, L. Mendoza-Espinosa, J. Ramírez-Hernández, J. Medellín-Azuara, L. W. Daesslé","doi":"10.1061/jwrmd5.wreng-5985","DOIUrl":"https://doi.org/10.1061/jwrmd5.wreng-5985","url":null,"abstract":": The water management of the Colorado River is at a tipping point. This paper describes water management strategies in the Mexican portion of the Colorado River Basin considering water scarcity scenarios. A water allocation model was constructed representing current and future water demands and supply. The Colorado River system in Mexican territory is used as a case study, and all its water demands are characterized [Irrigation District Rio Colorado (DR-014), Mexicali, San Luis Rio Colorado, Tecate, Tijuana-Rosarito, and Ensenada]. Individual strategies were run by subsystem and then their impact was analyzed systemwide. Performance criteria and a performance-based sustainability index were evaluated to identify water stressors and management strategies to improve water supply for agricultural, urban, and environmental users. Analysis of results shows that the irrigation district (DR-014) is the most affected user due to water cuts because it has the lowest priority and, thus, any reduction in Colorado River allocations affects them directly. A range of water management strategies was investigated, including a no-action scenario. The current system depends on the long-term aquifer overdraft to supply water demand. The reduction of the cultivated area was the strategy that increased the sustainability index the most for DR-014. Agricultural to urban transfers, water use efficiency, wastewater reuse, and desalination are prime possibilities to improve the current water supply in the coastal zone (Tijuana, Rosarito, Ensenada). This research shows the spectrum of possible outcomes that could be expected, ranging from systemwide effects of inaction to the implementation of a portfolio of water","PeriodicalId":17655,"journal":{"name":"Journal of Water Resources Planning and Management","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48828516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-01DOI: 10.1061/jwrmd5.wreng-5950
Mingsheng Yang, G. Bayraksan
{"title":"Stochastic Multistage Multiobjective Water Allocation with Hedging Rules for Multireservoir Systems","authors":"Mingsheng Yang, G. Bayraksan","doi":"10.1061/jwrmd5.wreng-5950","DOIUrl":"https://doi.org/10.1061/jwrmd5.wreng-5950","url":null,"abstract":"","PeriodicalId":17655,"journal":{"name":"Journal of Water Resources Planning and Management","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43384191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-01DOI: 10.1061/jwrmd5.wreng-5933
Renjie Wu, K. Soga
{"title":"Isolation Valve Placement Strategy for Resilience Improvement of Water Distribution Systems","authors":"Renjie Wu, K. Soga","doi":"10.1061/jwrmd5.wreng-5933","DOIUrl":"https://doi.org/10.1061/jwrmd5.wreng-5933","url":null,"abstract":"","PeriodicalId":17655,"journal":{"name":"Journal of Water Resources Planning and Management","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44677576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-01DOI: 10.1061/jwrmd5.wreng-5728
V. Tran, Stefanie Helmrich, N. Quinn, Peggy A. O'Day
{"title":"Operationalizing Real-Time Monitoring Data in Simulation Models Using the Public Domain HEC-DSSVue Software Platform","authors":"V. Tran, Stefanie Helmrich, N. Quinn, Peggy A. O'Day","doi":"10.1061/jwrmd5.wreng-5728","DOIUrl":"https://doi.org/10.1061/jwrmd5.wreng-5728","url":null,"abstract":"","PeriodicalId":17655,"journal":{"name":"Journal of Water Resources Planning and Management","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48568333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-01DOI: 10.1061/jwrmd5.wreng-5811
Can Cui, Z. Dong, Yun Luo, Yalei Han, Tianyan Zhang
{"title":"Lake Impoundment in Advance of Post-Flood Period Based on Large-Scale Numerical Simulation","authors":"Can Cui, Z. Dong, Yun Luo, Yalei Han, Tianyan Zhang","doi":"10.1061/jwrmd5.wreng-5811","DOIUrl":"https://doi.org/10.1061/jwrmd5.wreng-5811","url":null,"abstract":"","PeriodicalId":17655,"journal":{"name":"Journal of Water Resources Planning and Management","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46525138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Water use was impacted significantly by the COVID-19 pandemic. Although previous studies quantitatively investigated the effects of COVID-19 on water use, the relationship between water-use variation and COVID-19 dynamics (i.e., the spatial-temporal characteristics of COVID-19 cases) has received less attention. This study developed a two-step methodology to unravel the impact of COVID-19 pandemic dynamics on water-use variation. First, using a water-use prediction model, the water-use change percentage (WUCP) indicator, which was calculated as the relative difference between modeled and observed water use, i.e., water-use variation, was used to quantify the COVID-19 effects on water use. Second, two indicators, i.e., the number of existing confirmed cases (NECC) and the spatial risk index (SRI), were applied to characterize pandemic dynamics, and the quantitative relationship between WUCP and pandemic dynamics was examined by means of regression analysis. We collected and analyzed 6-year commercial water-use data from smart meters of Zhongshan District in Dalian City, Northeast China. The results indicate that commercial water use decreased significantly, with an average WUCP of 59.4%, 54.4%, and 45.7%during the three pandemic waves, respectively, in Dalian. Regression analysis showed that there was a positive linear relationship between water-use changes (i.e., WUCP) and pandemic dynamics (i.e., NECC and SRI). Both the number of COVID-19 cases and their spatial distribution impacted commercial water use, and the effects were weakened by restriction strategy improvement, and the accumulation of experience and knowledge about COVID-19. This study provides an in-depth understanding of the impact of COVID-19 dynamics on commercial water use. The results can be used to help predict water demand under during future pandemic periods or other types of natural and human-made disturbance.
{"title":"Unraveling the Impact of COVID-19 Pandemic Dynamics on Commercial Water-Use Variation","authors":"Fuzhi Shu, Haixing Liu, G. Fu, Siao Sun, Yu Li, Wei Ding, Jian Wu, Huicheng Zhou, Yongqin Yuan, Junguo He, Lingduo Zhang","doi":"10.1061/jwrmd5.wreng-5940","DOIUrl":"https://doi.org/10.1061/jwrmd5.wreng-5940","url":null,"abstract":"Water use was impacted significantly by the COVID-19 pandemic. Although previous studies quantitatively investigated the effects of COVID-19 on water use, the relationship between water-use variation and COVID-19 dynamics (i.e., the spatial-temporal characteristics of COVID-19 cases) has received less attention. This study developed a two-step methodology to unravel the impact of COVID-19 pandemic dynamics on water-use variation. First, using a water-use prediction model, the water-use change percentage (WUCP) indicator, which was calculated as the relative difference between modeled and observed water use, i.e., water-use variation, was used to quantify the COVID-19 effects on water use. Second, two indicators, i.e., the number of existing confirmed cases (NECC) and the spatial risk index (SRI), were applied to characterize pandemic dynamics, and the quantitative relationship between WUCP and pandemic dynamics was examined by means of regression analysis. We collected and analyzed 6-year commercial water-use data from smart meters of Zhongshan District in Dalian City, Northeast China. The results indicate that commercial water use decreased significantly, with an average WUCP of 59.4%, 54.4%, and 45.7%during the three pandemic waves, respectively, in Dalian. Regression analysis showed that there was a positive linear relationship between water-use changes (i.e., WUCP) and pandemic dynamics (i.e., NECC and SRI). Both the number of COVID-19 cases and their spatial distribution impacted commercial water use, and the effects were weakened by restriction strategy improvement, and the accumulation of experience and knowledge about COVID-19. This study provides an in-depth understanding of the impact of COVID-19 dynamics on commercial water use. The results can be used to help predict water demand under during future pandemic periods or other types of natural and human-made disturbance.","PeriodicalId":17655,"journal":{"name":"Journal of Water Resources Planning and Management","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49142801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-01DOI: 10.1061/jwrmd5.wreng-5943
Sasha Schück, S. Díaz, K. Lansey
{"title":"Reducing Water Age in Residential Premise Plumbing Systems","authors":"Sasha Schück, S. Díaz, K. Lansey","doi":"10.1061/jwrmd5.wreng-5943","DOIUrl":"https://doi.org/10.1061/jwrmd5.wreng-5943","url":null,"abstract":"","PeriodicalId":17655,"journal":{"name":"Journal of Water Resources Planning and Management","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49211882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-01DOI: 10.1061/jwrmd5.wreng-5856
Gaiqiang Yang, Shuang Xia, L. Huo, Mo Li, Chenglong Zhang, Yuxin Su, D. Guo
{"title":"Two-Stage Multiobjective Decision-Making Method Based on Agricultural Water-Energy-Food Nexus: Case Study in Hetao Irrigation District, China","authors":"Gaiqiang Yang, Shuang Xia, L. Huo, Mo Li, Chenglong Zhang, Yuxin Su, D. Guo","doi":"10.1061/jwrmd5.wreng-5856","DOIUrl":"https://doi.org/10.1061/jwrmd5.wreng-5856","url":null,"abstract":"","PeriodicalId":17655,"journal":{"name":"Journal of Water Resources Planning and Management","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44749041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-01DOI: 10.1061/jwrmd5.wreng-6047
Lochan Basnet, Downey Brill, R. Ranjithan, K. Mahinthakumar
{"title":"Supervised Machine Learning Approaches for Leak Localization in Water Distribution Systems: Impact of Complexities of Leak Characteristics","authors":"Lochan Basnet, Downey Brill, R. Ranjithan, K. Mahinthakumar","doi":"10.1061/jwrmd5.wreng-6047","DOIUrl":"https://doi.org/10.1061/jwrmd5.wreng-6047","url":null,"abstract":"","PeriodicalId":17655,"journal":{"name":"Journal of Water Resources Planning and Management","volume":" ","pages":""},"PeriodicalIF":3.1,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42814153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-01DOI: 10.1061/jwrmd5.wreng-6001
Xi Wan, Raziyeh Farmani, Edward Keedwell
With the availability of real-time monitoring data, leakage detection for water distribution networks (WDNs) based on data-driven methods has received increasing attention in recent years. Accurate forecasts based on historical data could provide valuable information about the condition of the WDN, and abnormal events could be detected if the observed behavior is substantially different from the typical behavior. Therefore, an accurate forecast model is essential for prediction-based leakage detection methods. While most data-driven methods focus on burst detection, it is also important to develop an early warning system for gradual leakage events because they will cause more water loss due to a longer time to awareness. Therefore, a real-time early leakage detection technique based on a multistep forecasting strategy is proposed in this study. A multistep flow forecasting model is introduced to capture the diurnal, weekly, and seasonal patterns in the historical data. The generated multistep forecasting is further compared with the observed measurements, and residuals are calculated based on cosine distance. Based on the analysis of the residual vector, the gradual leakage event could be detected in a timely manner. The proposed method is applied to the L-town datasets containing one year of real-life flow monitoring data. The results prove the superiority of the proposed multistep prediction model-based method over the traditional one-step prediction model for gradual leakage detection. In addition, the results show that the proposed methodology can detect small gradual leakage events within just a few days while generating no false alarms. The method was further applied to a real-life network and showed consistent results.
{"title":"Gradual Leak Detection in Water Distribution Networks Based on Multistep Forecasting Strategy","authors":"Xi Wan, Raziyeh Farmani, Edward Keedwell","doi":"10.1061/jwrmd5.wreng-6001","DOIUrl":"https://doi.org/10.1061/jwrmd5.wreng-6001","url":null,"abstract":"With the availability of real-time monitoring data, leakage detection for water distribution networks (WDNs) based on data-driven methods has received increasing attention in recent years. Accurate forecasts based on historical data could provide valuable information about the condition of the WDN, and abnormal events could be detected if the observed behavior is substantially different from the typical behavior. Therefore, an accurate forecast model is essential for prediction-based leakage detection methods. While most data-driven methods focus on burst detection, it is also important to develop an early warning system for gradual leakage events because they will cause more water loss due to a longer time to awareness. Therefore, a real-time early leakage detection technique based on a multistep forecasting strategy is proposed in this study. A multistep flow forecasting model is introduced to capture the diurnal, weekly, and seasonal patterns in the historical data. The generated multistep forecasting is further compared with the observed measurements, and residuals are calculated based on cosine distance. Based on the analysis of the residual vector, the gradual leakage event could be detected in a timely manner. The proposed method is applied to the L-town datasets containing one year of real-life flow monitoring data. The results prove the superiority of the proposed multistep prediction model-based method over the traditional one-step prediction model for gradual leakage detection. In addition, the results show that the proposed methodology can detect small gradual leakage events within just a few days while generating no false alarms. The method was further applied to a real-life network and showed consistent results.","PeriodicalId":17655,"journal":{"name":"Journal of Water Resources Planning and Management","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135717283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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