Pub Date : 2024-02-02DOI: 10.3390/hydrology11020021
David C. Froehlich
Mitigating nonpoint source pollution from stormwater runoff demands effective strategies for treating the first flush depth. Whether through off-stream storage or pass-through treatment devices, designing diversion structures and filtering materials is critical. This study proposes a streamlined procedure for determining first flush design flow rates, employing the modified rational method and rainfall intensity–duration equations applicable to any U.S. location. The dimensionless solution, which is presented as an equation requiring an iterative calculation for the desired flow rates, is complemented by precision graphs. Examples from the semi-arid Southwestern United States illustrate the methodology’s utility.
{"title":"A Modified Rational Method Approach for Calculating First Flush Design Flow Rates to Mitigate Nonpoint Source Pollution from Stormwater Runoff","authors":"David C. Froehlich","doi":"10.3390/hydrology11020021","DOIUrl":"https://doi.org/10.3390/hydrology11020021","url":null,"abstract":"Mitigating nonpoint source pollution from stormwater runoff demands effective strategies for treating the first flush depth. Whether through off-stream storage or pass-through treatment devices, designing diversion structures and filtering materials is critical. This study proposes a streamlined procedure for determining first flush design flow rates, employing the modified rational method and rainfall intensity–duration equations applicable to any U.S. location. The dimensionless solution, which is presented as an equation requiring an iterative calculation for the desired flow rates, is complemented by precision graphs. Examples from the semi-arid Southwestern United States illustrate the methodology’s utility.","PeriodicalId":508746,"journal":{"name":"Hydrology","volume":"42 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139870049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-02DOI: 10.3390/hydrology11020021
David C. Froehlich
Mitigating nonpoint source pollution from stormwater runoff demands effective strategies for treating the first flush depth. Whether through off-stream storage or pass-through treatment devices, designing diversion structures and filtering materials is critical. This study proposes a streamlined procedure for determining first flush design flow rates, employing the modified rational method and rainfall intensity–duration equations applicable to any U.S. location. The dimensionless solution, which is presented as an equation requiring an iterative calculation for the desired flow rates, is complemented by precision graphs. Examples from the semi-arid Southwestern United States illustrate the methodology’s utility.
{"title":"A Modified Rational Method Approach for Calculating First Flush Design Flow Rates to Mitigate Nonpoint Source Pollution from Stormwater Runoff","authors":"David C. Froehlich","doi":"10.3390/hydrology11020021","DOIUrl":"https://doi.org/10.3390/hydrology11020021","url":null,"abstract":"Mitigating nonpoint source pollution from stormwater runoff demands effective strategies for treating the first flush depth. Whether through off-stream storage or pass-through treatment devices, designing diversion structures and filtering materials is critical. This study proposes a streamlined procedure for determining first flush design flow rates, employing the modified rational method and rainfall intensity–duration equations applicable to any U.S. location. The dimensionless solution, which is presented as an equation requiring an iterative calculation for the desired flow rates, is complemented by precision graphs. Examples from the semi-arid Southwestern United States illustrate the methodology’s utility.","PeriodicalId":508746,"journal":{"name":"Hydrology","volume":"120 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139809966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-01DOI: 10.3390/hydrology11020019
Livinia Saputra, Sang Hyun Kim, Kyung-Jin Lee, S. Ki, Ho Young Jo, Seunghak Lee, Jaeshik Chung
The vadose zone acts as a natural buffer against groundwater contamination, and thus, its attenuation capacity (AC) directly affects groundwater vulnerability to pollutants. A regression model from the previous study predicting the overall AC of soils against diesel was further expanded to the GIS-based overlay-index model. Among the six physicochemical parameters used in the regression model, saturation degree (SD) is notably susceptible to climatological and meteorological events. To accommodate the lack of soil SD historical data, a series of infiltration simulations were separately conducted using Phydrus code with moving boundary conditions (i.e., rainfall records). The temporal variation of SD and the resulting AC under transient conditions are captured by building a space–time cube using a temporal raster across the study area within the designated time frame (1997–2022). The emerging hot spot analysis (EHSA) tool, based on the Getis–Ord Gi* and Mann–Kendall statistics, is applied to further identify any existing pattern associated with both SD and AC in both space and time simultaneously. Under stationary conditions, AC decreases along depth and is relatively lower near water bodies. Similarly, AC cold spot trends also show up near water bodies under transient conditions. The result captures not only the trends across time but also shows the exact location where the changes happen. The proposed framework provides an efficient tool to look for locations that have a persistently low or a gradually decreasing ability to attenuate diesel over time, indicating the need for stricter management regulations from a long-term perspective.
{"title":"A Conceptual Framework for Modeling Spatiotemporal Dynamics of Diesel Attenuation Capacity: A Case Study across Namyangju, South Korea","authors":"Livinia Saputra, Sang Hyun Kim, Kyung-Jin Lee, S. Ki, Ho Young Jo, Seunghak Lee, Jaeshik Chung","doi":"10.3390/hydrology11020019","DOIUrl":"https://doi.org/10.3390/hydrology11020019","url":null,"abstract":"The vadose zone acts as a natural buffer against groundwater contamination, and thus, its attenuation capacity (AC) directly affects groundwater vulnerability to pollutants. A regression model from the previous study predicting the overall AC of soils against diesel was further expanded to the GIS-based overlay-index model. Among the six physicochemical parameters used in the regression model, saturation degree (SD) is notably susceptible to climatological and meteorological events. To accommodate the lack of soil SD historical data, a series of infiltration simulations were separately conducted using Phydrus code with moving boundary conditions (i.e., rainfall records). The temporal variation of SD and the resulting AC under transient conditions are captured by building a space–time cube using a temporal raster across the study area within the designated time frame (1997–2022). The emerging hot spot analysis (EHSA) tool, based on the Getis–Ord Gi* and Mann–Kendall statistics, is applied to further identify any existing pattern associated with both SD and AC in both space and time simultaneously. Under stationary conditions, AC decreases along depth and is relatively lower near water bodies. Similarly, AC cold spot trends also show up near water bodies under transient conditions. The result captures not only the trends across time but also shows the exact location where the changes happen. The proposed framework provides an efficient tool to look for locations that have a persistently low or a gradually decreasing ability to attenuate diesel over time, indicating the need for stricter management regulations from a long-term perspective.","PeriodicalId":508746,"journal":{"name":"Hydrology","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139891286","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 wake of frequent and intensive human activities, highly urbanized areas consistently grapple with severe water environmental challenges. It becomes imperative to establish corresponding water environment models for simulating and forecasting regional water quality, addressing the associated environmental risks. The distributed framework water environment modeling system (DF-WEMS) incorporates fundamental principles, including the distributed concept and node concentration mass conservation. It adeptly merges point source and non-point source pollution load models with zero-dimensional, one-dimensional, and two-dimensional water quality models. This integration is specifically tailored for various Hydrological Feature Units (HFUs), encompassing lakes, reservoirs, floodplains, paddy fields, plain rivers, and hydraulic engineering structures. This holistic model enables the simulation and prediction of the water environment conditions within the watershed. In the Taihu Lake basin of China, a highly urbanized region featuring numerous rivers, lakes and gates, the DF-WEMS is meticulously constructed, calibrated, and validated based on 26 key water quality monitoring stations. The results indicate a strong alignment between the simulation of water quality indicators (WQIs) and real-world conditions, demonstrating the model’s reliability. This model proves applicable to the simulation, prediction, planning, and management of the water environment within the highly urbanized watershed.
{"title":"Simulation and Application of Water Environment in Highly Urbanized Areas: A Case Study in Taihu Lake Basin","authors":"Pengxuan Zhao, Chuanhai Wang, Jinning Wu, Gang Chen, Tianshu Zhang, Youlin Li, Pingnan Zhang","doi":"10.3390/hydrology11020020","DOIUrl":"https://doi.org/10.3390/hydrology11020020","url":null,"abstract":"In the wake of frequent and intensive human activities, highly urbanized areas consistently grapple with severe water environmental challenges. It becomes imperative to establish corresponding water environment models for simulating and forecasting regional water quality, addressing the associated environmental risks. The distributed framework water environment modeling system (DF-WEMS) incorporates fundamental principles, including the distributed concept and node concentration mass conservation. It adeptly merges point source and non-point source pollution load models with zero-dimensional, one-dimensional, and two-dimensional water quality models. This integration is specifically tailored for various Hydrological Feature Units (HFUs), encompassing lakes, reservoirs, floodplains, paddy fields, plain rivers, and hydraulic engineering structures. This holistic model enables the simulation and prediction of the water environment conditions within the watershed. In the Taihu Lake basin of China, a highly urbanized region featuring numerous rivers, lakes and gates, the DF-WEMS is meticulously constructed, calibrated, and validated based on 26 key water quality monitoring stations. The results indicate a strong alignment between the simulation of water quality indicators (WQIs) and real-world conditions, demonstrating the model’s reliability. This model proves applicable to the simulation, prediction, planning, and management of the water environment within the highly urbanized watershed.","PeriodicalId":508746,"journal":{"name":"Hydrology","volume":"44 143","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139814474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-01DOI: 10.3390/hydrology11020019
Livinia Saputra, Sang Hyun Kim, Kyung-Jin Lee, S. Ki, Ho Young Jo, Seunghak Lee, Jaeshik Chung
The vadose zone acts as a natural buffer against groundwater contamination, and thus, its attenuation capacity (AC) directly affects groundwater vulnerability to pollutants. A regression model from the previous study predicting the overall AC of soils against diesel was further expanded to the GIS-based overlay-index model. Among the six physicochemical parameters used in the regression model, saturation degree (SD) is notably susceptible to climatological and meteorological events. To accommodate the lack of soil SD historical data, a series of infiltration simulations were separately conducted using Phydrus code with moving boundary conditions (i.e., rainfall records). The temporal variation of SD and the resulting AC under transient conditions are captured by building a space–time cube using a temporal raster across the study area within the designated time frame (1997–2022). The emerging hot spot analysis (EHSA) tool, based on the Getis–Ord Gi* and Mann–Kendall statistics, is applied to further identify any existing pattern associated with both SD and AC in both space and time simultaneously. Under stationary conditions, AC decreases along depth and is relatively lower near water bodies. Similarly, AC cold spot trends also show up near water bodies under transient conditions. The result captures not only the trends across time but also shows the exact location where the changes happen. The proposed framework provides an efficient tool to look for locations that have a persistently low or a gradually decreasing ability to attenuate diesel over time, indicating the need for stricter management regulations from a long-term perspective.
{"title":"A Conceptual Framework for Modeling Spatiotemporal Dynamics of Diesel Attenuation Capacity: A Case Study across Namyangju, South Korea","authors":"Livinia Saputra, Sang Hyun Kim, Kyung-Jin Lee, S. Ki, Ho Young Jo, Seunghak Lee, Jaeshik Chung","doi":"10.3390/hydrology11020019","DOIUrl":"https://doi.org/10.3390/hydrology11020019","url":null,"abstract":"The vadose zone acts as a natural buffer against groundwater contamination, and thus, its attenuation capacity (AC) directly affects groundwater vulnerability to pollutants. A regression model from the previous study predicting the overall AC of soils against diesel was further expanded to the GIS-based overlay-index model. Among the six physicochemical parameters used in the regression model, saturation degree (SD) is notably susceptible to climatological and meteorological events. To accommodate the lack of soil SD historical data, a series of infiltration simulations were separately conducted using Phydrus code with moving boundary conditions (i.e., rainfall records). The temporal variation of SD and the resulting AC under transient conditions are captured by building a space–time cube using a temporal raster across the study area within the designated time frame (1997–2022). The emerging hot spot analysis (EHSA) tool, based on the Getis–Ord Gi* and Mann–Kendall statistics, is applied to further identify any existing pattern associated with both SD and AC in both space and time simultaneously. Under stationary conditions, AC decreases along depth and is relatively lower near water bodies. Similarly, AC cold spot trends also show up near water bodies under transient conditions. The result captures not only the trends across time but also shows the exact location where the changes happen. The proposed framework provides an efficient tool to look for locations that have a persistently low or a gradually decreasing ability to attenuate diesel over time, indicating the need for stricter management regulations from a long-term perspective.","PeriodicalId":508746,"journal":{"name":"Hydrology","volume":"194 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139831475","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 wake of frequent and intensive human activities, highly urbanized areas consistently grapple with severe water environmental challenges. It becomes imperative to establish corresponding water environment models for simulating and forecasting regional water quality, addressing the associated environmental risks. The distributed framework water environment modeling system (DF-WEMS) incorporates fundamental principles, including the distributed concept and node concentration mass conservation. It adeptly merges point source and non-point source pollution load models with zero-dimensional, one-dimensional, and two-dimensional water quality models. This integration is specifically tailored for various Hydrological Feature Units (HFUs), encompassing lakes, reservoirs, floodplains, paddy fields, plain rivers, and hydraulic engineering structures. This holistic model enables the simulation and prediction of the water environment conditions within the watershed. In the Taihu Lake basin of China, a highly urbanized region featuring numerous rivers, lakes and gates, the DF-WEMS is meticulously constructed, calibrated, and validated based on 26 key water quality monitoring stations. The results indicate a strong alignment between the simulation of water quality indicators (WQIs) and real-world conditions, demonstrating the model’s reliability. This model proves applicable to the simulation, prediction, planning, and management of the water environment within the highly urbanized watershed.
{"title":"Simulation and Application of Water Environment in Highly Urbanized Areas: A Case Study in Taihu Lake Basin","authors":"Pengxuan Zhao, Chuanhai Wang, Jinning Wu, Gang Chen, Tianshu Zhang, Youlin Li, Pingnan Zhang","doi":"10.3390/hydrology11020020","DOIUrl":"https://doi.org/10.3390/hydrology11020020","url":null,"abstract":"In the wake of frequent and intensive human activities, highly urbanized areas consistently grapple with severe water environmental challenges. It becomes imperative to establish corresponding water environment models for simulating and forecasting regional water quality, addressing the associated environmental risks. The distributed framework water environment modeling system (DF-WEMS) incorporates fundamental principles, including the distributed concept and node concentration mass conservation. It adeptly merges point source and non-point source pollution load models with zero-dimensional, one-dimensional, and two-dimensional water quality models. This integration is specifically tailored for various Hydrological Feature Units (HFUs), encompassing lakes, reservoirs, floodplains, paddy fields, plain rivers, and hydraulic engineering structures. This holistic model enables the simulation and prediction of the water environment conditions within the watershed. In the Taihu Lake basin of China, a highly urbanized region featuring numerous rivers, lakes and gates, the DF-WEMS is meticulously constructed, calibrated, and validated based on 26 key water quality monitoring stations. The results indicate a strong alignment between the simulation of water quality indicators (WQIs) and real-world conditions, demonstrating the model’s reliability. This model proves applicable to the simulation, prediction, planning, and management of the water environment within the highly urbanized watershed.","PeriodicalId":508746,"journal":{"name":"Hydrology","volume":"68 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139874384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-19DOI: 10.3390/hydrology11010011
Alexia Balla, V. Teofilović, T´ımea Kiss
The hydro-geomorphological background in microplastic (MP) deposition and mobilization is often neglected, though the sampling environment is the key point in a monitoring scheme. The aim of the study was to analyze the environmental driving factors of MP transport over three years (2020–2022) along a 750 km-long section of the Tisza River, Central Europe. The mean MP content of the fresh clayey sediments was 1291 ± 618 items/kg in 2020, and then it decreased (2021: 730 ± 568 items/kg; 2022: 766 ± 437 items/kg). The upstream and downstream sections were the most polluted due to improper local sewage treatment. In 2020, 63% of the sites were hotspot (≥2000 items/kg), but their number decreased to one-third in 2021 and 2022. MP pollution is influenced by highly variable environmental factors. (1) The geomorphological setting of a site is important, as most of the hotspots are on side bars. (2) The tributaries convey MP pollution to the Tisza River. (3) The bankfull or higher flood waves effectively rearrange the MP pollution. (4) The dams and their operation influence the downstream trend of MP pollution in the reservoir. (5) Downstream of a dam, the clear-water erosion increases the proportion of the pristine sediments; thus, the MP concentration decreases.
{"title":"Microplastic Contamination of Fine-Grained Sediments and Its Environmental Driving Factors along a Lowland River: Three-Year Monitoring of the Tisza River and Central Europe","authors":"Alexia Balla, V. Teofilović, T´ımea Kiss","doi":"10.3390/hydrology11010011","DOIUrl":"https://doi.org/10.3390/hydrology11010011","url":null,"abstract":"The hydro-geomorphological background in microplastic (MP) deposition and mobilization is often neglected, though the sampling environment is the key point in a monitoring scheme. The aim of the study was to analyze the environmental driving factors of MP transport over three years (2020–2022) along a 750 km-long section of the Tisza River, Central Europe. The mean MP content of the fresh clayey sediments was 1291 ± 618 items/kg in 2020, and then it decreased (2021: 730 ± 568 items/kg; 2022: 766 ± 437 items/kg). The upstream and downstream sections were the most polluted due to improper local sewage treatment. In 2020, 63% of the sites were hotspot (≥2000 items/kg), but their number decreased to one-third in 2021 and 2022. MP pollution is influenced by highly variable environmental factors. (1) The geomorphological setting of a site is important, as most of the hotspots are on side bars. (2) The tributaries convey MP pollution to the Tisza River. (3) The bankfull or higher flood waves effectively rearrange the MP pollution. (4) The dams and their operation influence the downstream trend of MP pollution in the reservoir. (5) Downstream of a dam, the clear-water erosion increases the proportion of the pristine sediments; thus, the MP concentration decreases.","PeriodicalId":508746,"journal":{"name":"Hydrology","volume":"7 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139525039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-17DOI: 10.3390/hydrology11010010
C. Zafra-Mejía, H. Rondón-Quintana, Carlos Felipe Urazán-Bonells
The objective of this paper is to use autoregressive, integrated, and moving average (ARIMA) and transfer function ARIMA (TFARIMA) models to analyze the behavior of the main water quality parameters in the initial components of a drinking water supply system (DWSS) of a megacity (Bogota, Colombia). The DWSS considered in this study consisted of the following components: a river, a reservoir, and a drinking water treatment plant (WTP). Water quality information was collected daily and over a period of 8 years. A comparative analysis was made between the components of the DWSS based on the structure of the ARIMA and TFARIMA models developed. The results show that the best water quality indicators are the following: turbidity > color > total iron. Increasing the time window of the ARIMA analysis (daily/weekly/monthly) suggests an increase in the magnitude of the AR term for each DWSS component (WTP > river > reservoir). This trend suggests that the turbidity behavior in the WTP is more influenced by past observations compared to the turbidity behavior in the river and reservoir, respectively. Smoothing of the data series (moving average) as the time window of the ARIMA analysis increases leads to a greater sensitivity of the model for outlier detection. TFARIMA models suggest that there is no significant influence of past river turbidity events on turbidity in the reservoir, and of reservoir turbidity on turbidity at the WTP outlet. Turbidity outlier events between the river and reservoir occur mainly in a single observation (additive outliers), and between the reservoir and WTP also have a permanent effect over time (level shift outliers). The AR term of the models is useful for studying the transfer of effects between DWSS components, and the MA term is useful for studying the influence of external factors on water quality in each DWSS component.
{"title":"ARIMA and TFARIMA Analysis of the Main Water Quality Parameters in the Initial Components of a Megacity’s Drinking Water Supply System","authors":"C. Zafra-Mejía, H. Rondón-Quintana, Carlos Felipe Urazán-Bonells","doi":"10.3390/hydrology11010010","DOIUrl":"https://doi.org/10.3390/hydrology11010010","url":null,"abstract":"The objective of this paper is to use autoregressive, integrated, and moving average (ARIMA) and transfer function ARIMA (TFARIMA) models to analyze the behavior of the main water quality parameters in the initial components of a drinking water supply system (DWSS) of a megacity (Bogota, Colombia). The DWSS considered in this study consisted of the following components: a river, a reservoir, and a drinking water treatment plant (WTP). Water quality information was collected daily and over a period of 8 years. A comparative analysis was made between the components of the DWSS based on the structure of the ARIMA and TFARIMA models developed. The results show that the best water quality indicators are the following: turbidity > color > total iron. Increasing the time window of the ARIMA analysis (daily/weekly/monthly) suggests an increase in the magnitude of the AR term for each DWSS component (WTP > river > reservoir). This trend suggests that the turbidity behavior in the WTP is more influenced by past observations compared to the turbidity behavior in the river and reservoir, respectively. Smoothing of the data series (moving average) as the time window of the ARIMA analysis increases leads to a greater sensitivity of the model for outlier detection. TFARIMA models suggest that there is no significant influence of past river turbidity events on turbidity in the reservoir, and of reservoir turbidity on turbidity at the WTP outlet. Turbidity outlier events between the river and reservoir occur mainly in a single observation (additive outliers), and between the reservoir and WTP also have a permanent effect over time (level shift outliers). The AR term of the models is useful for studying the transfer of effects between DWSS components, and the MA term is useful for studying the influence of external factors on water quality in each DWSS component.","PeriodicalId":508746,"journal":{"name":"Hydrology","volume":"26 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139527297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-11DOI: 10.3390/hydrology11010009
Mar�a del Mar Navarro-Farfán, Liliana García-Romero, M. Martínez-Cinco, M. A. Hernández-Hernández, S. T. Sánchez-Quispe
Groundwater models serve the function of predicting and analyzing aquifer behavior. They require input information, such as hydrogeological parameters like hydraulic conductivity and storage coefficient, which are used to calibrate the model, and elementary actions that include recharge and extracted volumes. There are cases in which it is insufficient to know the homogeneous recharge entering through the surface basin, referred to as traditional recharge, since, in many instances, the distribution is altered by changes in land use. For this reason, based on the geomorphological characteristics of the basin, weighting is proposed for sites with greater recharge capacity. The present work shows a solution to the recharge distribution using the potential groundwater recharge (PGR) map, which is formed by weighting spatially distributed information: (i) drainage, (ii) precipitation, (iii) land use, (iv) geological faults, (v) soil type, (vi) slope, and (vii) hydrogeology. A comparison is made between groundwater modeling using traditional recharge and PGR recharge. It is noted that the modeling perform similarly for both recharges, and the errors do not exceed 5% absolute error, which validates the model’s reliability. This manuscript demonstrates how to model and calibrate groundwater in aquifers with scarce information and variable recharge, making it reproducible.
{"title":"Comparison between MODFLOW Groundwater Modeling with Traditional and Distributed Recharge","authors":"Mar�a del Mar Navarro-Farfán, Liliana García-Romero, M. Martínez-Cinco, M. A. Hernández-Hernández, S. T. Sánchez-Quispe","doi":"10.3390/hydrology11010009","DOIUrl":"https://doi.org/10.3390/hydrology11010009","url":null,"abstract":"Groundwater models serve the function of predicting and analyzing aquifer behavior. They require input information, such as hydrogeological parameters like hydraulic conductivity and storage coefficient, which are used to calibrate the model, and elementary actions that include recharge and extracted volumes. There are cases in which it is insufficient to know the homogeneous recharge entering through the surface basin, referred to as traditional recharge, since, in many instances, the distribution is altered by changes in land use. For this reason, based on the geomorphological characteristics of the basin, weighting is proposed for sites with greater recharge capacity. The present work shows a solution to the recharge distribution using the potential groundwater recharge (PGR) map, which is formed by weighting spatially distributed information: (i) drainage, (ii) precipitation, (iii) land use, (iv) geological faults, (v) soil type, (vi) slope, and (vii) hydrogeology. A comparison is made between groundwater modeling using traditional recharge and PGR recharge. It is noted that the modeling perform similarly for both recharges, and the errors do not exceed 5% absolute error, which validates the model’s reliability. This manuscript demonstrates how to model and calibrate groundwater in aquifers with scarce information and variable recharge, making it reproducible.","PeriodicalId":508746,"journal":{"name":"Hydrology","volume":"44 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139533813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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