Bridging the research gap between reservoir operations and inundation risks under the future climate, this study integrates a hydrologic reservoir management model with a 2D hydrodynamic model, comparing the conventional regulatory and the optimized reservoir operations based on the particle swarm optimization (PSO) algorithm. Results reveal that optimized operations using the PSO algorithm consistently outperform conventional strategies by better-managing peak discharges and controlling downstream inundation. The study further differentiates between PSO-optimized plans: PSO1, which prioritizes peak reduction at the flood control point, and PSO2, which focuses on minimizing inundation areas. Interestingly, PSO2 proves superior for single-point peak reduction, typically the primary objective in current practices, whereas PSO1, despite lesser peak reduction, achieves a smaller inundation area, enhancing basin-scale flood resilience. This discrepancy underscores the need to consider downstream inundation risks as critical evaluation metrics in reservoir optimization, a factor often overlooked in existing studies. The research underscores the importance of updating operational frameworks to incorporate 2D inundation risks and adapt to increased flood risks under changing climate conditions. Despite optimization, future climate scenarios predict increased flood exposure, indicating that the current safety discharge rates and flow regulations at control points are outdated and require revision.
{"title":"Associating reservoir operations with 2D inundation risk and climate uncertainty","authors":"Youcan Feng, Run Zheng, Donghe Ma, Xin Huang","doi":"10.2166/ws.2024.162","DOIUrl":"https://doi.org/10.2166/ws.2024.162","url":null,"abstract":"\u0000 Bridging the research gap between reservoir operations and inundation risks under the future climate, this study integrates a hydrologic reservoir management model with a 2D hydrodynamic model, comparing the conventional regulatory and the optimized reservoir operations based on the particle swarm optimization (PSO) algorithm. Results reveal that optimized operations using the PSO algorithm consistently outperform conventional strategies by better-managing peak discharges and controlling downstream inundation. The study further differentiates between PSO-optimized plans: PSO1, which prioritizes peak reduction at the flood control point, and PSO2, which focuses on minimizing inundation areas. Interestingly, PSO2 proves superior for single-point peak reduction, typically the primary objective in current practices, whereas PSO1, despite lesser peak reduction, achieves a smaller inundation area, enhancing basin-scale flood resilience. This discrepancy underscores the need to consider downstream inundation risks as critical evaluation metrics in reservoir optimization, a factor often overlooked in existing studies. The research underscores the importance of updating operational frameworks to incorporate 2D inundation risks and adapt to increased flood risks under changing climate conditions. Despite optimization, future climate scenarios predict increased flood exposure, indicating that the current safety discharge rates and flow regulations at control points are outdated and require revision.","PeriodicalId":509977,"journal":{"name":"Water Supply","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141649013","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}
Safe and reliable drinking water is essential for sustaining life. Chlorination is widely used for disinfection in water distribution networks (WDNs). A higher dose of chlorine is required in an overhead service reservoir to maintain minimum residual chlorine at the farthest end in WDNs. However, delivering high dosages of chlorine from storage tanks can pose public health issues, especially for the residents living near overhead service reservoirs due to the formation of trihalomethanes, haloacetic acids, and chlorophenols. In addition, a higher dosage will lead to increased chlorine consumption and will accelerate pipe corrosion. Booster chlorination (BC) stations with smaller dosages are a solution to this problem. However, identifying the optimal number, locations, and dosage of each BC station in a cost-effective manner is challenging. This study proposes a methodology for determining the optimal number, locations, and chlorine dosages of BC stations in WDNs using a mixed integer linear programming problem. The methodology is illustrated through a simplified WDN in Holeta town, Ethiopia. The results indicate that if one adds two BC stations beyond the three dosage stations at the source, it will lead to a 49% reduction in chlorine use and a 27% decrease in the life cycle cost.
安全可靠的饮用水对维持生命至关重要。氯化被广泛用于输水管网的消毒。高架配水库需要较高剂量的氯，以维持输水管网最远处的最低余氯量。然而，从储水罐中输送高剂量的氯会造成公共卫生问题，特别是对居住在架空配水库附近的居民，因为会形成三卤甲烷、卤乙酸和氯酚。此外，较高的用量会导致氯消耗量增加，并加速管道腐蚀。使用较小剂量的增压加氯站（BC）可以解决这一问题。然而，以具有成本效益的方式确定每个 BC 站的最佳数量、位置和剂量是一项挑战。本研究提出了一种方法，利用混合整数线性规划问题来确定 WDN 中 BC 站的最佳数量、位置和氯剂量。该方法通过埃塞俄比亚 Holeta 镇的一个简化 WDN 进行了说明。结果表明，如果在源头的三个配料站之外再增加两个碱性催化还原站，将使氯的使用量减少 49%，生命周期成本降低 27%。
{"title":"Optimizing the number, locations, and chlorine dosages of booster chlorination stations in water distribution networks","authors":"Yomif Dereje Sime, M. Kansal","doi":"10.2166/ws.2024.161","DOIUrl":"https://doi.org/10.2166/ws.2024.161","url":null,"abstract":"\u0000 \u0000 Safe and reliable drinking water is essential for sustaining life. Chlorination is widely used for disinfection in water distribution networks (WDNs). A higher dose of chlorine is required in an overhead service reservoir to maintain minimum residual chlorine at the farthest end in WDNs. However, delivering high dosages of chlorine from storage tanks can pose public health issues, especially for the residents living near overhead service reservoirs due to the formation of trihalomethanes, haloacetic acids, and chlorophenols. In addition, a higher dosage will lead to increased chlorine consumption and will accelerate pipe corrosion. Booster chlorination (BC) stations with smaller dosages are a solution to this problem. However, identifying the optimal number, locations, and dosage of each BC station in a cost-effective manner is challenging. This study proposes a methodology for determining the optimal number, locations, and chlorine dosages of BC stations in WDNs using a mixed integer linear programming problem. The methodology is illustrated through a simplified WDN in Holeta town, Ethiopia. The results indicate that if one adds two BC stations beyond the three dosage stations at the source, it will lead to a 49% reduction in chlorine use and a 27% decrease in the life cycle cost.","PeriodicalId":509977,"journal":{"name":"Water Supply","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141653425","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 rate of groundwater extraction is increasing due to population growth. Balancing pumping rates with natural recharge is necessary for sustainable use. The safe groundwater pumping rate was determined using the groundwater model ModelMuse. To determine the safe pumping rate, 39 borehole data points were gathered and adjusted for 4, 8, and 12 h of pumping scenarios for 50 years in a steady-state pumping condition. The recharge rates in the study area were calculated using four empirical approaches in addition to the water balance method. Of the four empirical methods, the water balance technique provided the most accurate estimates of groundwater recharge, with an estimated average recharge rate of 176.75 mm per year. The ModelMuse model water balance report demonstrated that there was positive storage for all boreholes to be pumped simultaneously under 4- and 8-h pumping rate scenarios, but that there would be a significant drawdown under 12-h pumping from the stress period of 2039–2065, and the summation of inflow and outflow would become negative, indicating that the withdrawal rate is greater than the recharge rate. Thus, the safe pumping rate for Borkena groundwater was calculated to be 975 L/s in 8-h pumping rate scenarios.
{"title":"Groundwater modeling and estimation of the safe pumping rate for the sustainable use of groundwater resources in Kombolcha town, upper Borkena watershed, Ethiopia","authors":"Wasihun Deribe Tsegawu, Gurmu Deressa Katebu, Shawl Abebe Desta, Getnet Solomon Temtime, Bezawit Tesfaye Ejigu, Anteneh Yayeh Adamu, Ayalke Belete Amsie","doi":"10.2166/ws.2024.159","DOIUrl":"https://doi.org/10.2166/ws.2024.159","url":null,"abstract":"\u0000 The rate of groundwater extraction is increasing due to population growth. Balancing pumping rates with natural recharge is necessary for sustainable use. The safe groundwater pumping rate was determined using the groundwater model ModelMuse. To determine the safe pumping rate, 39 borehole data points were gathered and adjusted for 4, 8, and 12 h of pumping scenarios for 50 years in a steady-state pumping condition. The recharge rates in the study area were calculated using four empirical approaches in addition to the water balance method. Of the four empirical methods, the water balance technique provided the most accurate estimates of groundwater recharge, with an estimated average recharge rate of 176.75 mm per year. The ModelMuse model water balance report demonstrated that there was positive storage for all boreholes to be pumped simultaneously under 4- and 8-h pumping rate scenarios, but that there would be a significant drawdown under 12-h pumping from the stress period of 2039–2065, and the summation of inflow and outflow would become negative, indicating that the withdrawal rate is greater than the recharge rate. Thus, the safe pumping rate for Borkena groundwater was calculated to be 975 L/s in 8-h pumping rate scenarios.","PeriodicalId":509977,"journal":{"name":"Water Supply","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141664620","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}
Na Li, Rui Zhang, Heping Shu, AnRong He, Xiaoyan Zhang, XinYuan Wang
As urbanisation continues to accelerate in China, the contradiction between rapid economic development and water scarcity in semi-arid cities is becoming increasingly evident. Consequently, the study of the relationship between water resources use and economic growth is of particular importance. Lanzhou City was selected as the study area, an evaluation index system was established to comprehensively evaluate the status of water resources utilisation, meanwhile, the water footprint method and Tapio decoupling model were adopted to measure the decoupling status between water utilisation and economic development from 2002 to 2021. The result showed that the total water footprint and per capita water footprint followed an increasing and then decreasing trend. The water footprint varied significantly by industrial sector, with agriculture accounting for 72.87% of total water use. The self-sufficiency rate of water resources was above 96.5%. The economic value increased substantially from 22.54 CNY/m3 in 2002 to 183.99 CNY/m3 in 2021. The water scarcity index and the pressure index were high, with annual mean values of 0.95 and 0.99, respectively. Water consumption and economic growth are generally decoupled weakly and strongly, with the number of strong decoupling occurrences increasing significantly from 2011 to 2021.
{"title":"Study on the sustainable utilisation of water resources in semi-arid megacities of China based on water footprints","authors":"Na Li, Rui Zhang, Heping Shu, AnRong He, Xiaoyan Zhang, XinYuan Wang","doi":"10.2166/ws.2024.158","DOIUrl":"https://doi.org/10.2166/ws.2024.158","url":null,"abstract":"\u0000 As urbanisation continues to accelerate in China, the contradiction between rapid economic development and water scarcity in semi-arid cities is becoming increasingly evident. Consequently, the study of the relationship between water resources use and economic growth is of particular importance. Lanzhou City was selected as the study area, an evaluation index system was established to comprehensively evaluate the status of water resources utilisation, meanwhile, the water footprint method and Tapio decoupling model were adopted to measure the decoupling status between water utilisation and economic development from 2002 to 2021. The result showed that the total water footprint and per capita water footprint followed an increasing and then decreasing trend. The water footprint varied significantly by industrial sector, with agriculture accounting for 72.87% of total water use. The self-sufficiency rate of water resources was above 96.5%. The economic value increased substantially from 22.54 CNY/m3 in 2002 to 183.99 CNY/m3 in 2021. The water scarcity index and the pressure index were high, with annual mean values of 0.95 and 0.99, respectively. Water consumption and economic growth are generally decoupled weakly and strongly, with the number of strong decoupling occurrences increasing significantly from 2011 to 2021.","PeriodicalId":509977,"journal":{"name":"Water Supply","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141668330","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}
Abdullah Nadeem, Muhammad Atiq Ur Rehman Tariq, Kaleem Sarwar, Mudassar Iqbal, Khalil Ahmad, Khalil Ahmed
As the global population is approaching toward 9 billion by 2050, challenges of food and water scarcity intensify. Hydroponics, an innovative and eco-friendly technology, has gained prominence in addressing these challenges. This study employs life cycle assessment (LCA) to comprehensively evaluate the environmental and economic impacts of utilizing reclaimed water in a hydroponic system. Results from midpoint, endpoint, and normalized analyses reveal key contributors to the hydroponic system's environmental burden, including water, substrates, fertilizers, and energy sources. Significant impacts have been observed in marine and terrestrial ecotoxicity as well as photochemical ozone formation. Reclaimed water consistently demonstrates lower environmental impacts compared to conventional water across various indicators, such as climate change (131 kg CO2 eq.), fine particulate matter formation (0.108 kg PM2.5 eq.), and freshwater consumption (0.291 m3). The study emphasizes the potential of hydroponics with reclaimed water to offer sustainable and environmentally friendly agricultural practices. The detailed LCA results provide valuable insights for policymakers and stakeholders, promoting the adoption of hydroponics to address food and water scarcity challenges. From the findings, reclaimed water in hydroponics lowers the environmental impacts as compared to conventional water and PVC along with electricity is the major contributor in environmental burden.
{"title":"Assessing the environmental impacts of reclaimed and conventional water in hydroponics based on a life cycle assessment approach","authors":"Abdullah Nadeem, Muhammad Atiq Ur Rehman Tariq, Kaleem Sarwar, Mudassar Iqbal, Khalil Ahmad, Khalil Ahmed","doi":"10.2166/ws.2024.160","DOIUrl":"https://doi.org/10.2166/ws.2024.160","url":null,"abstract":"\u0000 \u0000 As the global population is approaching toward 9 billion by 2050, challenges of food and water scarcity intensify. Hydroponics, an innovative and eco-friendly technology, has gained prominence in addressing these challenges. This study employs life cycle assessment (LCA) to comprehensively evaluate the environmental and economic impacts of utilizing reclaimed water in a hydroponic system. Results from midpoint, endpoint, and normalized analyses reveal key contributors to the hydroponic system's environmental burden, including water, substrates, fertilizers, and energy sources. Significant impacts have been observed in marine and terrestrial ecotoxicity as well as photochemical ozone formation. Reclaimed water consistently demonstrates lower environmental impacts compared to conventional water across various indicators, such as climate change (131 kg CO2 eq.), fine particulate matter formation (0.108 kg PM2.5 eq.), and freshwater consumption (0.291 m3). The study emphasizes the potential of hydroponics with reclaimed water to offer sustainable and environmentally friendly agricultural practices. The detailed LCA results provide valuable insights for policymakers and stakeholders, promoting the adoption of hydroponics to address food and water scarcity challenges. From the findings, reclaimed water in hydroponics lowers the environmental impacts as compared to conventional water and PVC along with electricity is the major contributor in environmental burden.","PeriodicalId":509977,"journal":{"name":"Water Supply","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141666843","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}
Ruoyu Yin, Lei Jin, Haiyan Fu, Yurui Fan, Xi Zhang, Li Wang
This study addresses the pivotal challenge of water resource allocation in urban environments by introducing a novel approach – a multi-objective chance-constrained fuzzy interval linear programming model integrated with principal component analysis (PCA). This innovative model aims to alleviate subjectivity in urban water management processes, particularly in adjusting water demands across various sectors. The proposed model incorporates correlation analysis to identify dimensionality-reducing factors of multitarget components, determining the proportion of each target component relative to the total components. Fuzzy sets are applied to irrigation water resource allocation quantity, segmented into six levels of fuzzy membership to analyze the stochasticity of water supply. Results demonstrate the model's efficacy, revealing that variations in risk probabilities impact water supply, necessitating positive water management strategies to enhance agricultural efficiency and negative strategies to mitigate the risk of inadequate water supply. Key findings emphasize the significance of agricultural water availability and the structure of irrigation water use in optimal resource allocation. Importantly, the study showcases the enhanced precision achieved through the proposed multi-objective chance-constrained fuzzy interval linear programming with PCA, thereby refining the optimization outcomes for water management under multifaceted objectives.
{"title":"Integrated multi-objective chance-constrained fuzzy interval linear programming model with principal component analysis for optimizing agricultural water resource management under uncertainties","authors":"Ruoyu Yin, Lei Jin, Haiyan Fu, Yurui Fan, Xi Zhang, Li Wang","doi":"10.2166/ws.2024.156","DOIUrl":"https://doi.org/10.2166/ws.2024.156","url":null,"abstract":"\u0000 \u0000 This study addresses the pivotal challenge of water resource allocation in urban environments by introducing a novel approach – a multi-objective chance-constrained fuzzy interval linear programming model integrated with principal component analysis (PCA). This innovative model aims to alleviate subjectivity in urban water management processes, particularly in adjusting water demands across various sectors. The proposed model incorporates correlation analysis to identify dimensionality-reducing factors of multitarget components, determining the proportion of each target component relative to the total components. Fuzzy sets are applied to irrigation water resource allocation quantity, segmented into six levels of fuzzy membership to analyze the stochasticity of water supply. Results demonstrate the model's efficacy, revealing that variations in risk probabilities impact water supply, necessitating positive water management strategies to enhance agricultural efficiency and negative strategies to mitigate the risk of inadequate water supply. Key findings emphasize the significance of agricultural water availability and the structure of irrigation water use in optimal resource allocation. Importantly, the study showcases the enhanced precision achieved through the proposed multi-objective chance-constrained fuzzy interval linear programming with PCA, thereby refining the optimization outcomes for water management under multifaceted objectives.","PeriodicalId":509977,"journal":{"name":"Water Supply","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141675040","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}
Urban water demand prediction is not only the foundation of water resource planning and management, but also an important component of water supply system optimization and scheduling. Therefore, predicting future water demand is of great significance. For univariate time series data, the issue of outliers can be solved through data preprocessing. Then, the data input dimension is increased through feature engineering, and finally, the LightGBM (Light Gradient Boosting Machine) model is used to predict future water demand. The results demonstrate that cubic polynomial interpolation outperforms the Prophet model and the linear method in the context of missing value interpolation tasks. In terms of predicting water demand, the LightGBM model demonstrates excellent forecasting performance and can effectively predict future water demand trends. The evaluation indicators MAPE (mean absolute percentage error) and NSE (Nash–Sutcliffe efficiency coefficient) on the test dataset are 4.28% and 0.94, respectively. These indicators can provide a scientific basis for short-term prediction of water supply enterprises.
{"title":"Research on urban water demand prediction based on machine learning and feature engineering","authors":"Dongfei Yan, Yi Tao, Jianqi Zhang, Huijia Yang","doi":"10.2166/ws.2024.157","DOIUrl":"https://doi.org/10.2166/ws.2024.157","url":null,"abstract":"\u0000 \u0000 Urban water demand prediction is not only the foundation of water resource planning and management, but also an important component of water supply system optimization and scheduling. Therefore, predicting future water demand is of great significance. For univariate time series data, the issue of outliers can be solved through data preprocessing. Then, the data input dimension is increased through feature engineering, and finally, the LightGBM (Light Gradient Boosting Machine) model is used to predict future water demand. The results demonstrate that cubic polynomial interpolation outperforms the Prophet model and the linear method in the context of missing value interpolation tasks. In terms of predicting water demand, the LightGBM model demonstrates excellent forecasting performance and can effectively predict future water demand trends. The evaluation indicators MAPE (mean absolute percentage error) and NSE (Nash–Sutcliffe efficiency coefficient) on the test dataset are 4.28% and 0.94, respectively. These indicators can provide a scientific basis for short-term prediction of water supply enterprises.","PeriodicalId":509977,"journal":{"name":"Water Supply","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141679951","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}
Gaozhen Wang, Hongxiang Wang, Lintong Huang, Ning He, Bing Wang, Fengtian Hong, Yanhua Li, Handong Ye, Jiaqi Lan, Wenxian Guo
Few evaluation frameworks investigate the mechanisms causing runoff alterations by quantifying the causes of runoff alterations across different time scales (wet/normal/dry seasons and months) and in-depth analysis of each meteorological indicator's contribution to runoff change. This study quantitatively evaluated the hydrological regime of the Jialing River before and after the abrupt change predicated on the indicators of hydrologic alteration and range of variability approach (IHA-RVA) and the Gini coefficient. Through the partial differential equation of runoff characteristics (MLLR-Budyko), and separated in detail the contribution of each meteorological indicator to runoff alterations. Additionally, the ABCD model expanded and validated the results of the partial differential equations on the runoff contribution on a time scale. The findings demonstrate that the overall hydrological regime changed moderately in the river (48.63%). Of the 14 meteorological indicators separated by MLLR-Budyko, the wet season precipitation contributed the most to the runoff alterations, with a contribution rate of −178.12% of the runoff changes driven by all the meteorological indicators, and the coefficient of variation of the annual precipitation contributed the least, with a contribution rate of 2.16%; use ABCD model reconstruction of natural runoff found significant differences in the contribution of drivers at different time scales.
{"title":"Quantitative evaluation of runoff drivers based on the MLLR-Budyko framework","authors":"Gaozhen Wang, Hongxiang Wang, Lintong Huang, Ning He, Bing Wang, Fengtian Hong, Yanhua Li, Handong Ye, Jiaqi Lan, Wenxian Guo","doi":"10.2166/ws.2024.129","DOIUrl":"https://doi.org/10.2166/ws.2024.129","url":null,"abstract":"\u0000 \u0000 Few evaluation frameworks investigate the mechanisms causing runoff alterations by quantifying the causes of runoff alterations across different time scales (wet/normal/dry seasons and months) and in-depth analysis of each meteorological indicator's contribution to runoff change. This study quantitatively evaluated the hydrological regime of the Jialing River before and after the abrupt change predicated on the indicators of hydrologic alteration and range of variability approach (IHA-RVA) and the Gini coefficient. Through the partial differential equation of runoff characteristics (MLLR-Budyko), and separated in detail the contribution of each meteorological indicator to runoff alterations. Additionally, the ABCD model expanded and validated the results of the partial differential equations on the runoff contribution on a time scale. The findings demonstrate that the overall hydrological regime changed moderately in the river (48.63%). Of the 14 meteorological indicators separated by MLLR-Budyko, the wet season precipitation contributed the most to the runoff alterations, with a contribution rate of −178.12% of the runoff changes driven by all the meteorological indicators, and the coefficient of variation of the annual precipitation contributed the least, with a contribution rate of 2.16%; use ABCD model reconstruction of natural runoff found significant differences in the contribution of drivers at different time scales.","PeriodicalId":509977,"journal":{"name":"Water Supply","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141267980","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}
Arsenic is found in significant quantities within the alluvial aquifers. Bangladesh heavily relies on the alluvial aquifers of the Bengal Basin as a source of irrigation and drinking water. Due to the flat topography, arsenic within an aquifer is not easily flushed out of the system. Additionally, continuous, unregulated pumping causes arsenic from deeper aquifers to migrate to shallower levels. This study simulates groundwater and contaminant transport in the alluvial aquifers of the Bengal Basin by comparison between two scenarios prior to human intervention with different sea levels, employing a combination of MODFLOW, MODPATH and MT3DMS. The simulations demonstrate that the hydraulic gradient and flow rates were higher during periods of considerably lower sea levels than they are at present. Additionally, it would require 5,600 years for the Holocene aquifer and 3,300 years for the Last Glacial Period aquifer to flush arsenic to the Bangladesh standard concentrations in drinking water in a 100-m-thick contaminated aquifer. This implies that if the sea level continues to rise with climate change, it will be difficult to remove arsenic from the alluvial aquifers in the Bengal Basin by natural flushing, which means artificial interventions need to be done in that region in the interest of the nation's health.
{"title":"Remediation potential of arsenic in the alluvial aquifers in the Bengal Basin: insights from simulations and time estimates","authors":"Xinyi Chen","doi":"10.2166/ws.2024.128","DOIUrl":"https://doi.org/10.2166/ws.2024.128","url":null,"abstract":"\u0000 Arsenic is found in significant quantities within the alluvial aquifers. Bangladesh heavily relies on the alluvial aquifers of the Bengal Basin as a source of irrigation and drinking water. Due to the flat topography, arsenic within an aquifer is not easily flushed out of the system. Additionally, continuous, unregulated pumping causes arsenic from deeper aquifers to migrate to shallower levels. This study simulates groundwater and contaminant transport in the alluvial aquifers of the Bengal Basin by comparison between two scenarios prior to human intervention with different sea levels, employing a combination of MODFLOW, MODPATH and MT3DMS. The simulations demonstrate that the hydraulic gradient and flow rates were higher during periods of considerably lower sea levels than they are at present. Additionally, it would require 5,600 years for the Holocene aquifer and 3,300 years for the Last Glacial Period aquifer to flush arsenic to the Bangladesh standard concentrations in drinking water in a 100-m-thick contaminated aquifer. This implies that if the sea level continues to rise with climate change, it will be difficult to remove arsenic from the alluvial aquifers in the Bengal Basin by natural flushing, which means artificial interventions need to be done in that region in the interest of the nation's health.","PeriodicalId":509977,"journal":{"name":"Water Supply","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141270785","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}
Sidi Yusuf Dawa, Mou Leong Tan, N. Samat, Ranjan Roy, Fei Zhang
Ground observations are often considered as the most reliable and precise source of precipitation data. However, long-term precipitation data from ground observations are lacking in many parts of the world. Gridded precipitation products (GPPs) therefore have emerged as crucial alternatives to ground observations, but it is essential to assess their capability to accurately replicate precipitation patterns. This study aims to evaluate the performance of five GPPs, NASA POWER, TerraClimate, Climate Hazards Group Infrared Precipitation with Climate Data (CHIRPS), GPCC, and Climate Research Unit (CRU), in capturing precipitation and drought patterns from 1981 to 2021 in Yobe, Nigeria. The results indicate that GPCC had good performance at both monthly and annual scales, with high correlation coefficients and low error values. However, it tends to underestimate precipitation amounts in certain areas. Other products also exhibit satisfactory performance with moderate correlations with ground observations. Drought analysis indicates that GPCC outperforms other products in standardised precipitation index-6 calculations, while NASA POWER demonstrates inconsistencies with ground observations, particularly during the early 1980s and mid-2000s. In conclusion, GPCC is the most preferable GPP for precipitation and drought analysis in the Yobe State in Nigeria.
地面观测通常被认为是最可靠、最精确的降水数据来源。然而，世界上许多地方都缺乏来自地面观测的长期降水数据。因此，网格降水产品（GPPs）成为地面观测的重要替代品，但评估其准确复制降水模式的能力至关重要。本研究旨在评估 NASA POWER、TerraClimate、Climate Hazards Group Infrared Precipitation with Climate Data (CHIRPS)、GPCC 和 Climate Research Unit (CRU) 这五种 GPP 在捕捉尼日利亚约贝 1981 年至 2021 年降水和干旱模式方面的性能。结果表明，GPCC 在月度和年度尺度上均表现良好，相关系数高，误差值低。不过，它往往会低估某些地区的降水量。其他产品的性能也令人满意，与地面观测数据的相关性适中。干旱分析表明，GPCC 在标准化降水指数-6 计算方面优于其他产品，而 NASA POWER 与地面观测数据不一致，特别是在 20 世纪 80 年代早期和 2000 年代中期。总之，在尼日利亚约贝州进行降水和干旱分析时，GPCC 是最理想的 GPP。
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