Rainfall-flow modeling remains necessary, even essential, to understand the dynamics of a watershed and to solve problems related to the disruption of hydrological regimes. It has been proven effective by providing solutions to many water-related problems, such as sizing and management of structures, and flood forecasting. Global hydrological models can simulate the transformation of rainfall data into flows on natural basins for many practical applications in the field of water resource management. Our study aims to evaluate the reliability of one of these models, that of Rural Engineering 'GR' at three time steps: annual (GR1A), monthly (GR2M), and daily (GR4J), which will be applied to the Beni Bahdel watershed with an area of 1040 km², one of the sub-basins of Northwestern Algeria. The input parameters are precipitation and potential evapotranspiration (PET), and the output parameters are flows. The results obtained, both in calibration and validations, are encouraging, where the evaluation criteria taken into consideration, namely the Nash criterion and the correlation coefficient, exceeded 70% and 0.80 respectively. The study could be a decision-making tool for the simulation of flows, and be very useful for future hydraulic developments in the study area.
{"title":"Rainfall-flow Modeling Using a Global Conceptual Model: Case of the Beni Bahdel Watershed (Northwest of Algeria)","authors":"Sid Ahmed Bouguerra, Bekhta Mansour","doi":"10.14796/jwmm.c500","DOIUrl":"https://doi.org/10.14796/jwmm.c500","url":null,"abstract":"Rainfall-flow modeling remains necessary, even essential, to understand the dynamics of a watershed and to solve problems related to the disruption of hydrological regimes. It has been proven effective by providing solutions to many water-related problems, such as sizing and management of structures, and flood forecasting. Global hydrological models can simulate the transformation of rainfall data into flows on natural basins for many practical applications in the field of water resource management. Our study aims to evaluate the reliability of one of these models, that of Rural Engineering 'GR' at three time steps: annual (GR1A), monthly (GR2M), and daily (GR4J), which will be applied to the Beni Bahdel watershed with an area of 1040 km², one of the sub-basins of Northwestern Algeria. The input parameters are precipitation and potential evapotranspiration (PET), and the output parameters are flows. The results obtained, both in calibration and validations, are encouraging, where the evaluation criteria taken into consideration, namely the Nash criterion and the correlation coefficient, exceeded 70% and 0.80 respectively. The study could be a decision-making tool for the simulation of flows, and be very useful for future hydraulic developments in 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":"66654778","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}
F. Maricar, R. Karamma, M. R. Mustamin, M. F. Maricar
Flood historical data from the Kelara River in the last 10 years shows that the river has often overflowed, and the worst floods happened on January 22, 2019. One of the efforts to minimize the negative impact of a flood disaster is to conduct flood tracking. Flood tracking is an analysis of the flood along the river, or also known as flood propagation, which can be used as a reference in the preparation of a flood early warning system. This study aims to determine the propagation of the Kelara River flood which can be used to determine flood-prone areas and as a reference in the preparation of a flood early warning system. This research was carried out in 3 stages, namely flood hydrology analysis using the HEC-HMS program, numerical simulation of 2D floods using the HEC-RAS program, spatial modeling of flood-prone areas using the ArcGIS program, and preparation of a flood early warning system. The results of this study showed that the flood that occurred on January 22, 2019, was a 100-year return period flood, and determined that 10 points of residential areas/villages must be alerted when the intensity of rain is high, with the fastest time to be alerted being 52 minutes.
{"title":"Numerical Simulation of Flood Propagation in the Kelara River Flood Early Warning System","authors":"F. Maricar, R. Karamma, M. R. Mustamin, M. F. Maricar","doi":"10.14796/jwmm.c501","DOIUrl":"https://doi.org/10.14796/jwmm.c501","url":null,"abstract":"Flood historical data from the Kelara River in the last 10 years shows that the river has often overflowed, and the worst floods happened on January 22, 2019. One of the efforts to minimize the negative impact of a flood disaster is to conduct flood tracking. Flood tracking is an analysis of the flood along the river, or also known as flood propagation, which can be used as a reference in the preparation of a flood early warning system. This study aims to determine the propagation of the Kelara River flood which can be used to determine flood-prone areas and as a reference in the preparation of a flood early warning system. This research was carried out in 3 stages, namely flood hydrology analysis using the HEC-HMS program, numerical simulation of 2D floods using the HEC-RAS program, spatial modeling of flood-prone areas using the ArcGIS program, and preparation of a flood early warning system. The results of this study showed that the flood that occurred on January 22, 2019, was a 100-year return period flood, and determined that 10 points of residential areas/villages must be alerted when the intensity of rain is high, with the fastest time to be alerted being 52 minutes.","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":"66654819","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}
LEAK2D (L2D) is a new, two-dimensional, dual-permeability model for the simulation of preferential water flow in the vadose zone, allowing for the continuous exchange of water between the matrix and the fracture domain. It is based on the two-dimensional Richards equation for the simulation of flow in the matrix domain and on the kinematic wave equation for the simulation of flow in the fracture domain. The Richards equation is solved by a combination of the Alternating Direction Implicit method and the Douglas-Jones predictor-corrector method. This combination leads to a very efficient, stable, and time-consuming method. A variable time step is used by which any instability of the numerical solution is avoided. The water transfer from the fracture to the matrix domain is estimated as a first-order approximation of the water diffusion equation. The model was used to satisfactorily simulate preferential flow under an extreme rainfall/irrigation event. The exchange of water between the two domains depends on parameters which have physical meaning; however, their exact values are difficult to be determined or measured. Based on the most common values of these parameters found in the literature, a sensitivity analysis was performed to define their effect on the output of the model.
{"title":"A New Two-dimensional Dual-permeability Model of Preferential Water Flow in the Vadose Zone","authors":"C. Paraskevas, C. Babajimopoulos","doi":"10.14796/jwmm.c502","DOIUrl":"https://doi.org/10.14796/jwmm.c502","url":null,"abstract":"LEAK2D (L2D) is a new, two-dimensional, dual-permeability model for the simulation of preferential water flow in the vadose zone, allowing for the continuous exchange of water between the matrix and the fracture domain. It is based on the two-dimensional Richards equation for the simulation of flow in the matrix domain and on the kinematic wave equation for the simulation of flow in the fracture domain. The Richards equation is solved by a combination of the Alternating Direction Implicit method and the Douglas-Jones predictor-corrector method. This combination leads to a very efficient, stable, and time-consuming method. A variable time step is used by which any instability of the numerical solution is avoided. The water transfer from the fracture to the matrix domain is estimated as a first-order approximation of the water diffusion equation. The model was used to satisfactorily simulate preferential flow under an extreme rainfall/irrigation event. The exchange of water between the two domains depends on parameters which have physical meaning; however, their exact values are difficult to be determined or measured. Based on the most common values of these parameters found in the literature, a sensitivity analysis was performed to define their effect on the output of 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":"66654830","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}
K. Irvine, L. Chua, M. Ashrafi, H. Loc, Song Ha Le
Urbanization continues to increase in countries with tropical climates and this trend, combined with the likely increasing frequency of extreme rainfall events due to a changing climate, places such development at risk and in need of resiliency assessment. Conceptual models to assess runoff dynamics can be an important component of resiliency assessment, but there are comparatively less data to calibrate these models than are available in the global north. As such, there also is less information with respect to the drivers of model uncertainty and sensitivity. To address this gap in knowledge, we summarize the calibration results of PCSWMM for subcatchment areas in a tropical climate study catchment for which there are substantial rainfall and runoff data. Subsequently, we used the calibrated model to evaluate the impact that rain gauge density may have on runoff estimates. We also investigated the sensitivity of PCSWMM peak flow and total volume estimates to physical subcatchment parameters other than rainfall. With between 38 and 87 events captured for each monitoring station, the NSE, r2, and ISE ratings varied, but generally were in the respective ranges 0.7–0.8, 0.79–0.85, and good–excellent. It can be concluded that PCSWMM performed well in representing the tropical storm events. The rainfall pattern in the study catchment exhibited considerable spatial variability, both annually and seasonally, with annual rainfall increasing from 2063 mm near the coast to 3100 mm less than 17 km further inland. While the model was sensitive to %imperviousness, subcatchment width, impervious Manning’s n, and, to a lesser extent, various surface storage and infiltration parameters, the spatial variability of rainfall had the greatest impact on model uncertainty.
{"title":"Drivers of Model Uncertainty for Urban Runoff in a Tropical Climate: The Effect of Rainfall Variability and Subcatchment Parameterization","authors":"K. Irvine, L. Chua, M. Ashrafi, H. Loc, Song Ha Le","doi":"10.14796/jwmm.c496","DOIUrl":"https://doi.org/10.14796/jwmm.c496","url":null,"abstract":"Urbanization continues to increase in countries with tropical climates and this trend, combined with the likely increasing frequency of extreme rainfall events due to a changing climate, places such development at risk and in need of resiliency assessment. Conceptual models to assess runoff dynamics can be an important component of resiliency assessment, but there are comparatively less data to calibrate these models than are available in the global north. As such, there also is less information with respect to the drivers of model uncertainty and sensitivity. To address this gap in knowledge, we summarize the calibration results of PCSWMM for subcatchment areas in a tropical climate study catchment for which there are substantial rainfall and runoff data. Subsequently, we used the calibrated model to evaluate the impact that rain gauge density may have on runoff estimates. We also investigated the sensitivity of PCSWMM peak flow and total volume estimates to physical subcatchment parameters other than rainfall. With between 38 and 87 events captured for each monitoring station, the NSE, r2, and ISE ratings varied, but generally were in the respective ranges 0.7–0.8, 0.79–0.85, and good–excellent. It can be concluded that PCSWMM performed well in representing the tropical storm events. The rainfall pattern in the study catchment exhibited considerable spatial variability, both annually and seasonally, with annual rainfall increasing from 2063 mm near the coast to 3100 mm less than 17 km further inland. While the model was sensitive to %imperviousness, subcatchment width, impervious Manning’s n, and, to a lesser extent, various surface storage and infiltration parameters, the spatial variability of rainfall had the greatest impact on model uncertainty.","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":"66655208","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}
Ismail Karaoui, A. Arioua, D. Elhamdouni, Wafae Nouaim, kamal Ait ouhamchich, Mohamed Hssaisoune
In semi-arid or arid regions, where available freshwater is limited, surface water requires repeated quality testing to avoid pollution. Sampling trips of different frequencies are onerous and require expensive laboratory analysis. Simulation appears to be a reliable alternative method to overcome such challenges. The simulation presented here was conducted by solving the mass balance equation while considering the inputs controlling each simulated parameter. The mass balance equation (a differential equation) was solved by finite difference numerical approximation to provide parameters for pollutant concentrations at each station or moment (based on selected steps). This solution was integrated to simulate pollution indicators (biochemical oxygen demand and dissolved oxygen), nitrogen forms, and orthophosphates. The National Sanitation Foundation water quality index (NSF-WQI) was calculated using these parameters. Using 12 months of measurement data, results were compared for NSF-WQI calculated through measured and simulated data, showing a significant correlation with R2 = 0.8, meaning the model demonstrated good calibration and validation. The elaborated model is a useful tool for decision makers to test and propose quality improvement solutions for watercourses suffering from quality deterioration.
{"title":"Assessing Water Quality Status Using a Mathematical Simulation Model of El Abid River (Morocco)","authors":"Ismail Karaoui, A. Arioua, D. Elhamdouni, Wafae Nouaim, kamal Ait ouhamchich, Mohamed Hssaisoune","doi":"10.14796/jwmm.c491","DOIUrl":"https://doi.org/10.14796/jwmm.c491","url":null,"abstract":"In semi-arid or arid regions, where available freshwater is limited, surface water requires repeated quality testing to avoid pollution. Sampling trips of different frequencies are onerous and require expensive laboratory analysis. Simulation appears to be a reliable alternative method to overcome such challenges. The simulation presented here was conducted by solving the mass balance equation while considering the inputs controlling each simulated parameter. The mass balance equation (a differential equation) was solved by finite difference numerical approximation to provide parameters for pollutant concentrations at each station or moment (based on selected steps). This solution was integrated to simulate pollution indicators (biochemical oxygen demand and dissolved oxygen), nitrogen forms, and orthophosphates. The National Sanitation Foundation water quality index (NSF-WQI) was calculated using these parameters. Using 12 months of measurement data, results were compared for NSF-WQI calculated through measured and simulated data, showing a significant correlation with R2 = 0.8, meaning the model demonstrated good calibration and validation. The elaborated model is a useful tool for decision makers to test and propose quality improvement solutions for watercourses suffering from quality deterioration.","PeriodicalId":43297,"journal":{"name":"Journal of Water Management Modeling","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66655097","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}
Water quality modeling with dynamic parameters, especially of rivers, is important in terms of proactive pollution management strategies. Techniques such as artificial neural networks (ANNs) have become popular for such applications. In the present study, an ANN is used to construct a multilayer perceptron and radial basis function neural network model to simulate and predict dissolved oxygen in the River Ganga in selected regions of Uttar Pradesh, and to demonstrate its application in identifying complex nonlinear relationships between input and output variables. The results of the model analysis demonstrate that the multi-layer perceptron model provides greater correlation coefficients (R = 0.993) and a lower mean square error (RMSE = 0.1984) than the radial basis function model (R = 0.789; RMSE = 1.0011). The results of the analysis suggest the suitability of the proposed MLP-ANN model to predict water quality parameters such as dissolved oxygen using limiting data sets for the River Ganga, in particular, and other rivers in general.
{"title":"Water Quality Modeling of the River Ganga in the Northern Region of India Using the Artificial Neural Network Technique","authors":"R. Bhardwaj, R. K. Singh","doi":"10.14796/jwmm.c486","DOIUrl":"https://doi.org/10.14796/jwmm.c486","url":null,"abstract":"Water quality modeling with dynamic parameters, especially of rivers, is important in terms of proactive pollution management strategies. Techniques such as artificial neural networks (ANNs) have become popular for such applications. In the present study, an ANN is used to construct a multilayer perceptron and radial basis function neural network model to simulate and predict dissolved oxygen in the River Ganga in selected regions of Uttar Pradesh, and to demonstrate its application in identifying complex nonlinear relationships between input and output variables. The results of the model analysis demonstrate that the multi-layer perceptron model provides greater correlation coefficients (R = 0.993) and a lower mean square error (RMSE = 0.1984) than the radial basis function model (R = 0.789; RMSE = 1.0011). The results of the analysis suggest the suitability of the proposed MLP-ANN model to predict water quality parameters such as dissolved oxygen using limiting data sets for the River Ganga, in particular, and other rivers in general.","PeriodicalId":43297,"journal":{"name":"Journal of Water Management Modeling","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66654896","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}
Steven X. Jin, Biren Saparia, J. Norton, Bryon Wood, A. Abdallah, Tara McClinton, Joe Burchi, Laura Radtke
Great Lakes Water Authority (GLWA) operates one of the largest water systems in the United States and, like most other water utilities, is facing the problem of aging water infrastructure. Internal pressure transient events can be a major contributing factor in the deterioration and failure of aging water pipes. To evaluate the impact of pressure transients on water main deterioration, for over three years GLWA has maintained a real-time pressure transient monitoring program within its water transmission system. The Trimble Unity Remote Monitoring suite is used; it includes high speed pressure sensors and data loggers. Approximately 6000 transient events have been recorded by the 30 transient monitoring sensors installed within the transmission system. A quantitative approach to evaluating the relative impact of pressure transients on the deterioration of water pipes has been used in analyzing the pressure transient events. The approach is based on the frequencies and pressure ranges of transient events. This paper presents the development of the transient monitoring program and analytical results of the pressure transient data. These analytical results, plus the ongoing transient monitoring data, are being used in updating GLWA’s system risk assessment.
{"title":"Monitoring of Pressure Transients in Great Lakes Water Authority Water Transmission System","authors":"Steven X. Jin, Biren Saparia, J. Norton, Bryon Wood, A. Abdallah, Tara McClinton, Joe Burchi, Laura Radtke","doi":"10.14796/jwmm.c492","DOIUrl":"https://doi.org/10.14796/jwmm.c492","url":null,"abstract":"Great Lakes Water Authority (GLWA) operates one of the largest water systems in the United States and, like most other water utilities, is facing the problem of aging water infrastructure. Internal pressure transient events can be a major contributing factor in the deterioration and failure of aging water pipes. To evaluate the impact of pressure transients on water main deterioration, for over three years GLWA has maintained a real-time pressure transient monitoring program within its water transmission system. The Trimble Unity Remote Monitoring suite is used; it includes high speed pressure sensors and data loggers. Approximately 6000 transient events have been recorded by the 30 transient monitoring sensors installed within the transmission system. A quantitative approach to evaluating the relative impact of pressure transients on the deterioration of water pipes has been used in analyzing the pressure transient events. The approach is based on the frequencies and pressure ranges of transient events. This paper presents the development of the transient monitoring program and analytical results of the pressure transient data. These analytical results, plus the ongoing transient monitoring data, are being used in updating GLWA’s system risk assessment.","PeriodicalId":43297,"journal":{"name":"Journal of Water Management Modeling","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66655132","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}
JOSE G. VASCONCELOS, H. Gheith, Robson L. Pachaly, M. Abdel-latif, Robert Herr
The City of Columbus, Ohio is implementing a tunnel system to reduce the number of episodes of combined sewer overflows into the Scioto River. The tunnel systems provide relief to the existing Olentangy Scioto Interceptor Sewer. Two new tunnels being implemented are the OSIS Augmentation and Relief Sewer (OARS), in service since July 2017, and the Lower Olentangy Tunnel (LOT) that is planned to be in service in 2025. The performance of these tunnels in respect to high inflow conditions was investigated with the use of the HAST mixed flow model and the OpenFOAM CFD model to determine the magnitude of surges, the possibility of air pocket entrapment, air–water surging, and the consequences of uncontrolled air pocket releases through shafts. Inflows into the systems were obtained from a calibrated collection system SWMM model. Modeling results quantified surging in the tunnel dropshafts and their mitigation from built-in surge control chambers. HAST simulations also pointed to locations where air pockets could form. These results were used in OpenFOAM to determine the effects of uncontrolled air release through the shaft that links the two tunnels. It was shown that proper ventilation at the shaft will mitigate the growth of air phase pressure to damaging levels.
{"title":"Multiphase Rapid Filling Conditions of Tunnel System in Columbus, Ohio","authors":"JOSE G. VASCONCELOS, H. Gheith, Robson L. Pachaly, M. Abdel-latif, Robert Herr","doi":"10.14796/jwmm.c479","DOIUrl":"https://doi.org/10.14796/jwmm.c479","url":null,"abstract":"The City of Columbus, Ohio is implementing a tunnel system to reduce the number of episodes of combined sewer overflows into the Scioto River. The tunnel systems provide relief to the existing Olentangy Scioto Interceptor Sewer. Two new tunnels being implemented are the OSIS Augmentation and Relief Sewer (OARS), in service since July 2017, and the Lower Olentangy Tunnel (LOT) that is planned to be in service in 2025. The performance of these tunnels in respect to high inflow conditions was investigated with the use of the HAST mixed flow model and the OpenFOAM CFD model to determine the magnitude of surges, the possibility of air pocket entrapment, air–water surging, and the consequences of uncontrolled air pocket releases through shafts. Inflows into the systems were obtained from a calibrated collection system SWMM model. Modeling results quantified surging in the tunnel dropshafts and their mitigation from built-in surge control chambers. HAST simulations also pointed to locations where air pockets could form. These results were used in OpenFOAM to determine the effects of uncontrolled air release through the shaft that links the two tunnels. It was shown that proper ventilation at the shaft will mitigate the growth of air phase pressure to damaging levels.","PeriodicalId":43297,"journal":{"name":"Journal of Water Management Modeling","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66655064","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}
Prediction of low flows in ungauged catchments is desirable for planning and management of water resources development and for sustaining the environment. The main objective of this study was to regionalize low flow indexes (the baseflow index BFI, Q80, Q90, and Q95) in the Lake Abaya–Chamo sub-basin by using multiple linear regression models. To develop the regional equation, nine baseflow separation methods were compared: two digital graphical methods and seven recursive digital filters were compared and applied in eight gauged catchments. The methods were evaluated through the coefficient of determination (R2) and the root mean square error (RMSE) as performance measures. The flow duration analyses were conducted to compute the flow exceedance quantiles Q80, Q90, and Q95. Regionalizing those indexes required the identification of homogeneous regions, which was accomplished through cluster analysis, based on physiographic and climatic data. Three significantly different homogeneous areas were identified using k-means clustering, and multiple linear regression models were developed for every low flow index in each homogeneous region. The R2 values in the model developed for BFI, Q80, Q90, and Q95 range from 0.75 to 0.98 throughout the region. For checking the performance of the model, verification of regional models was carried out by determining the relative error over four gauged catchments assuming they were ungauged. All regional models performed well by having relative errors <10% in the regions showing high performance. Therefore, the developed regional models could potentially solve the low flow estimation in the vast majority of ungauged catchments in the sub-basin. Consequently, current and future water resources development endeavors may use such estimation methods for planning, designing, and management purposes.
{"title":"Regionalization of Low Flow Analysis in Data Scarce Region: The Case of the Lake Abaya-Chamo Sub-basin, Rift Valley Lakes Basin, Ethiopia","authors":"D. Abdi, S. Gebrekristos","doi":"10.14796/jwmm.c487","DOIUrl":"https://doi.org/10.14796/jwmm.c487","url":null,"abstract":"Prediction of low flows in ungauged catchments is desirable for planning and management of water resources development and for sustaining the environment. The main objective of this study was to regionalize low flow indexes (the baseflow index BFI, Q80, Q90, and Q95) in the Lake Abaya–Chamo sub-basin by using multiple linear regression models. To develop the regional equation, nine baseflow separation methods were compared: two digital graphical methods and seven recursive digital filters were compared and applied in eight gauged catchments. The methods were evaluated through the coefficient of determination (R2) and the root mean square error (RMSE) as performance measures. The flow duration analyses were conducted to compute the flow exceedance quantiles Q80, Q90, and Q95. Regionalizing those indexes required the identification of homogeneous regions, which was accomplished through cluster analysis, based on physiographic and climatic data. Three significantly different homogeneous areas were identified using k-means clustering, and multiple linear regression models were developed for every low flow index in each homogeneous region. The R2 values in the model developed for BFI, Q80, Q90, and Q95 range from 0.75 to 0.98 throughout the region. For checking the performance of the model, verification of regional models was carried out by determining the relative error over four gauged catchments assuming they were ungauged. All regional models performed well by having relative errors <10% in the regions showing high performance. Therefore, the developed regional models could potentially solve the low flow estimation in the vast majority of ungauged catchments in the sub-basin. Consequently, current and future water resources development endeavors may use such estimation methods for planning, designing, and management purposes.","PeriodicalId":43297,"journal":{"name":"Journal of Water Management Modeling","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66654943","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}
Hong Li, Hongkai Gao, Yanlai Zhou, I. Storteig, L. Nie, N. Sælthun, Chong-yu Xu
The Storm Water Management Model (SWMM) has been globally used for stormwater management. However, the calibration and evaluation of SWMM for historical rainfall–runoff events in partially separated and combined drainage systems is rarely reported in Norway. In this study, we employed SWMM for the Grefsen catchment in Oslo, Norway. The main problem in the Grefsen basin is combined sewer overflow. We calibrated the model parameters based on 32 rainfall–runoff events and evaluated the calibrations using four indicators: Nash–Sutcliffe efficiency, percentage bias, and continuity errors for runoff and flow. There were 32 successful calibrations using Nash–Sutcliffe efficiency, 30 successful calibrations using percentage bias, 32 successful calibrations using continuity error runoff, and four successful calibrations using continuity error flow. SWMM can well simulate the dynamics of hydrological and hydraulic systems in this catchment. Among the 124 validations, there were 88 successful simulations using Nash–Sutcliffe efficiency, 35 successful simulations using percentage bias, 124 successful simulations using continuity error for runoff, and 62 successful simulations using continuity error for flow. The results show that percentage bias and continuity error flow are the critical indicators for model calibration. This study reveals the large uncertainty caused by calibration and validation criteria, and highlights the importance of considering model computation error.
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