Zahra Zahmatkesh - Academia.edu (original) (raw)
Papers by Zahra Zahmatkesh
Hydrology, 2018
Estimating maximum possible rainfall is of great value for flood prediction and protection, parti... more Estimating maximum possible rainfall is of great value for flood prediction and protection, particularly for regions, such as Canada, where urban and fluvial floods from extreme rainfalls have been known to be a major concern. In this study, a methodology is proposed to forecast real-time rainfall (with one month lead time) using different number of spatial inputs with different orders of lags. For this purpose, two types of models are used. The first one is a machine learning data driven-based model, which uses a set of hydrologic variables as inputs, and the second one is an empirical-statistical model that employs the multi-criteria decision analysis method for rainfall forecasting. The data driven model is built based on Artificial Neural Networks (ANNs), while the developed multi-criteria decision analysis model uses Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approach. A comprehensive set of spatially varying climate variables, including geopotential height, sea surface temperature, sea level pressure, humidity, temperature and pressure with different orders of lags is collected to form input vectors for the forecast models. Then, a feature selection method is employed to identify the most appropriate predictors. Two sets of results from the developed models, i.e., maximum daily rainfall in each month (RMAX) and cumulative value of rainfall for each month (RCU), are considered as the target variables for forecast purpose. The results from both modeling approaches are compared using a number of evaluation criteria such as Nash-Sutcliffe Efficiency (NSE). The proposed models are applied for rainfall forecasting for a coastal area in Western Canada: Vancouver, British Columbia. Results indicate although data driven models such as ANNs work well for the simulation purpose, developed TOPSIS model considerably outperforms ANNs for the rainfall forecasting. ANNs show acceptable simulation performance during the calibration period (NSE up to 0.9) but they fail for the validation (NSE of 0.2) and forecasting (negative NSE). The TOPSIS method delivers better rainfall forecasting performance with the NSE of about 0.7. Moreover, the number of predictors that are used in the TOPSIS model are significantly less than those required by the ANNs to show an acceptable performance (7 against 47 for forecasting RCU and 6 against 32 for forecasting RMAX). Reliable and precise rainfall forecasting, with adequate lead time, benefits enhanced flood warning and decision making to reduce potential flood damages.
<p&... more <p>Statistical analysis of hydrologic variables is of great importance for water resources systems. Design and operation of these systems is often based on the assumption of data stationarity. However, long-term average of variables such as rainfall as well as sea level is observed to shift over time, mostly attributed to the climate change. These changes, in turn, affect flood volume, peak value and frequency. In this study, a framework was proposed for bi- variate frequency analysis of extreme sea level and rainfall. The analysis was performed on rainfall for the coastal area of Charleston and Savannah, and sea level for the coastal area of Charleston and Fort Pulaski, South Carolina, USA. Extreme values were selected based on the peak over threshold method. To determine the most appropriate distribution, AIC and BIC goodness of fit tests were used. Frequency analysis was then carried out using nonstationary Generalized Extreme Value probability distribution function. Results showed an increase in the sea level long term average, significant trends and outliers (specifically in recent decades), while although the analysis of rainfall data confirms the presence of outliers in the time series, it does not indicate significant trends or heterogeneity. Therefore, in performing bi-variate frequency analysis of extreme rainfall and sea level, non-stationary approaches should be used to provide a more reliable prediction of the joint probability of these variables.</p>
Journal of Hydrology, 2019
This is a PDF file of an article that has undergone enhancements after acceptance, such as the ad... more This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Hydrological Sciences Journal, 2019
In snow-dominated basins, collection of snow data while capturing its spatio-temporal variability... more In snow-dominated basins, collection of snow data while capturing its spatio-temporal variability is difficult; therefore, integrating assimilation products could be a viable alternative for improving streamflow simulation. This study evaluates the accuracy of daily snow water equivalent (SWE) provided by the SNOw Data Assimilation System (SNODAS) of the National Weather Service at a 1-km 2 resolution for two basins in eastern Canada, where SWE is a critical variable intensifying spring runoff. A geostatistical interpolation method was used to distribute snow observations. SNODAS SWE products were bias-corrected by matching their cumulative
Journal of Hydrologic Engineering, 2018
It is imperative for cities to develop sustainable water management and planning strategies in or... more It is imperative for cities to develop sustainable water management and planning strategies in order to best serve urban communities that are currently facing increasing population and water demand. Water resources managers are often chastened by experiencing failures attributed to natural extreme droughts and floods. However, recent changes in water management systems have been responding to these uncertain conditions. Water managers have become thoughtful about the adverse effects of uncertain extreme events on the performance of water supply systems. Natural hydrologic variability and inherent uncertainties associated with the future climate variations make the simulation and management of water supplies a greater challenge. The hydrologic simulation process is one of the main components in integrated water resources management. Hydrologic simulations incorporate uncertain input values, model parameters, and a model structure. Therefore, stochastic streamflow simulation and prediction, and consideration of uncertainty propagation on performance of water supply systems (WSSs) are essential phases for efficient management of these systems. The proposed integrated framework in this study models a WSS by taking into account the dynamic nature of the system and utilizing a Markov chain Monte Carlo (MCMC) algorithm to capture the uncertainties associated with hydrologic simulation. Hydrologic responses from the results of a rainfall-runoff model for three watersheds of Karaj, Latyan, and Lar in Tehran, Iran, as the case study are used as inputs to the reservoirs. Results confirm that uncertainties associated with the hydrologic model's parameters propagate through the simulation and lead to a wide variation in reservoir storage and WSS performance metrics such as vulnerability and reliability. For example, water storage simulation in the Karaj Reservoir can vary up to 70% compared with the observed values. This causes contradiction and conflict in the management of reservoirs and water systems and decision making. The results emphasize the importance of analyzing WSS performance under uncertain conditions to improve the simulation of natural processes and support water managers for a more efficient decision-making process.
Canadian Water Resources Journal / Revue canadienne des ressources hydriques, 2019
This paper discusses flood forecasting procedures currently practiced at the Canadian provincial ... more This paper discusses flood forecasting procedures currently practiced at the Canadian provincial river flood forecast centers. In Canada, each province is responsible for collecting and managing meteorological and hydrometric data (through provincial authorities and/or under Federal/ Provincial agreements), developing suitable hydrological models, and providing information about river discharge and water level to the public. In case of an extreme event such as flood or drought, the forecast center is responsible for issuing alerts and supporting provincial emergency management. Due to the large diversity in landscape, weather, and hydrological features across the country, extreme events are triggered by different mechanisms such as snowmelt, heavy rainfall, rain on snow, etc., at different times of the year. Each river forecast center deals with unique challenges in data collection, hydrologic/hydraulic modeling, and flood forecasting. Thus, the focus of the Center in planning for developments and future directions could be significantly different from one province to another. In this paper, the significance of river flood forecasting in Canada, as well as the development in hydrological modelling procedures are highlighted. Moreover, an overview of the current approaches for streamflow/flood forecasting used by the Centers is provided. The content presented here is an outcome of our interaction with the forecast centers. This further resulted in identifying a number of research questions to help bridge the gap between ongoing research and needs of the Centers.
Water Resources Management, 2017
A great challenge has been appeared on if the assumption of data stationary for flood frequency a... more A great challenge has been appeared on if the assumption of data stationary for flood frequency analysis is justifiable. Results for frequency analysis (FA) could be substantially different if non-stationarity is incorporated in the data analysis. In this study, extreme water levels (annual maximum and daily instantaneous maximum) in a coastal part of New York City were considered for FA. Annual maximum series (AMS) and peak-over threshold (POT) approaches were applied to build data timeseries. The resulted timeseries were checked for potential trend and stationarity using statistical tests including Man-Kendall, Augmented Dickey-Fuller (ADF) and Kwiatkowski-Phillips-Schmidt-Shin (KPSS). Akaike information criterion (AIC) was utilized to select the most appropriate probability distribution models. Generalized Extreme Value (GEV) distribution and Generalized Pareto Distribution (GPD) were then applied as the probability distribution functions on the selected data based on AMS and POT methods under non-stationary assumption. Two methods of maximum likelihood and penalized maximum likelihood were applied and compared for the estimation of the distributions' parameters. Results showed that by incorporating non-stationarity in FA, design values of extreme water levels were significantly different from those obtained under the assumption of stationarity. Moreover, in the non-stationary FA, consideration of time-dependency for the distribution parameters resulted in a range of variation for design floods. The findings of this study emphasize on the importance of FA under the assumptions of data stationarity and nonstationarity, and taking into account the worst case flooding scenarios for future planning of the Water Resour Manage
Journal of Irrigation and Drainage Engineering, 2017
AbstractSuperstorm Sandy and Hurricane Irene on the East Coast of the United States were wake-up ... more AbstractSuperstorm Sandy and Hurricane Irene on the East Coast of the United States were wake-up calls that the floodplain delineation and flood damage estimation models need major overhaul. The fi...
Journal of Water Resources Planning and Management, 2017
Wastewater Treatment Plants that are constructed in the coastal regions need more attention since... more Wastewater Treatment Plants that are constructed in the coastal regions need more attention since the flood occurrence may cause excessive loads on the infrastructures. These excessive loads may result in the system's failure and innumerable damages on the infrastructure. In this study, in order to reduce WWTPs' flood vulnerability, an index called Resiliency was developed to quantify system's characteristics. Later, two main approaches were considered to enhance the infrastructure performance: the "Resource allocation" and the "Cooperative behavior" method. The former method was applied employing those factors which were improvable with the investment of funds and financial allocations. They were utilized to make the system more robust. In addition, implementing some new agents with potential impacts on funding were described in order to have a more realistic vision. As for the latter method, the cooperative behavior approach, the cooperation was utilized to demonstrate joint operation among WWTPs and the way they interact. For this purpose, WWTPs' placement was analyzed to check if they could operate jointly. Thereafter, effectiveness of these two approaches was compared in order to make the best decision regarding different cases. The results showed that in three collaborations among Bowery Bay, Tallman Island, Newtown Creek, and Red Hook WWTPs, cooperation has had a significant effect on the resiliency index.
Science of The Total Environment, 2016
In this paper, an integrated framework is proposed for urban runoff management. To control and im... more In this paper, an integrated framework is proposed for urban runoff management. To control and improve runoff quality and quantity, Low Impact Development (LID) practices are utilized. In order to determine the LIDs' areas and locations, the Non-dominated Sorting Genetic Algorithm-II (NSGA-II), which considers three objective functions of minimizing runoff volume, runoff pollution and implementation cost of LIDs, is utilized. In this framework, the Storm Water Management Model (SWMM) is used for stream flow simulation. The non-dominated solutions provided by the NSGA-II are considered as management scenarios. To select the most preferred scenario, interactions among the main stakeholders in the study area with conflicting utilities are incorporated by utilizing bargaining models including a non-cooperative game, Nash model and social choice procedures of Borda count and approval voting. Moreover, a new social choice procedure, named pairwise voting method, is proposed and applied. Based on each conflict resolution approach, a scenario is identified as the ideal solution providing the LIDs' areas, locations and implementation cost. The proposed framework is applied for urban water quality and quantity management in the northern part of Tehran metropolitan city, Iran. Results show that the proposed pairwise voting method tends to select a scenario with a higher percentage of reduction in TSS (Total Suspended Solid) load and runoff volume, in comparison with the Borda count and approval voting methods. Besides, the Nash method presents a management scenario with the highest cost for LIDs' implementation and the maximum values for percentage of runoff volume reduction and TSS removal. The results also signify that selection of an appropriate management scenario by stakeholders in the study area depends on the available financial resources and the relative importance of runoff quality improvement in comparison with reducing the runoff volume.
Advances in Water Resources, 2015
ABSTRACT
World Environmental and Water Resources Congress 2011, 2011
Water Resources Management, 2014
ABSTRACT Optimal reservoir operation and water allocation are critical issues in sustainable wate... more ABSTRACT Optimal reservoir operation and water allocation are critical issues in sustainable water resource management due to increasing water demand. Multiplicity of stockholders with different objectives and utilities makes reservoir operation a complicated problem with a variety of constraints and objectives to be considered. In this case, the conflict resolution models can be efficiently used to determine the optimal water allocation scheme considering the utility and relative authority of different stakeholders. In this study, the Nash product is used for formulation of the objective function of a reservoir water allocation model. The Analytic Hierarchy Process (AHP) is used to determine the importance of each stockholder in bargaining for water. The Particle Swarm Optimization algorithm (PSO) and the Imperialism Competitive Algorithm (ICA) are applied to solve the proposed optimization model. System performance indices including reliability, resiliency and vulnerability are used to evaluate the performance of optimization algorithms. The simplest and most often-used reservoir policy (Standard Operating Policy, SOP) is also used in order to evaluate the performance of the proposed models. The proposed model is applied to the Karkheh River-Reservoir system located in south western part of Iran as a case study. Results show the significance of the application of conflict resolution models, such as the Nash theory and proposed optimization algorithms, for water allocation in the regional scale especially in complicated water supply systems.
World Environmental and Water Resources Congress 2008, 2008
In this paper, two deterministic and stochastic multilateral, multi-issue, non-cooperative bargai... more In this paper, two deterministic and stochastic multilateral, multi-issue, non-cooperative bargaining methodologies are proposed for urban runoff quality management. In the proposed methodologies, a calibrated Storm Water Management Model (SWMM) is used to simulate stormwater runoff quantity and quality for different urban stormwater runoff management scenarios, which have been defined considering several Low Impact Development (LID) techniques. In the deterministic methodology, the best management scenario, representing location and area of LID controls, is identified using the bargaining model. In the stochastic methodology, uncertainties of some key parameters of SWMM are analyzed using the info-gap theory. For each water quality management scenario, robustness and opportuneness criteria are determined based on utility functions of different stakeholders. Then, to find the best solution, the bargaining model is performed considering a combination of robustness and opportuneness criteria for each scenario based on utility function of each stakeholder. The results of applying the proposed methodology in the Velenjak urban watershed located in the northeastern part of Tehran, the capital city of Iran, illustrate its practical utility for conflict resolution in urban water quantity and quality management. It is shown that the solution obtained using the deterministic model cannot outperform the result of the stochastic model considering the robustness and opportuneness criteria. Therefore, it can be concluded that the stochastic model, which incorporates the main uncertainties, could provide more reliable results.
Journal of Irrigation and Drainage Engineering, 2015
ABSTRACT doi: 10.1061/(ASCE)IR.1943-4774.0000770
World Environmental and Water Resources Congress 2012, 2012
Journal of Hydrologic Engineering, 2015
ABSTRACT doi: 10.1061/(ASCE)HE.1943-5584.0001064
Journal of Water Resources Planning and Management, 2015
ABSTRACT doi: 10.1061/(ASCE)WR.1943-5452.0000497
World Environmental and Water Resources Congress 2014, 2014
Climate change is projected to have significant impacts on patterns of weather variables, all aro... more Climate change is projected to have significant impacts on patterns of weather variables, all around the world. To study the impacts of climate change on rainfall, different global climate models (GCMs) and climate scenarios are used to build projections for probable future patterns of rainfall. Using the rainfall projections, the change in runoff peaks and volumes can be projected. In this paper,a climate change impact study is presentedto investigate the effect of future uncertain rainfall patterns on urbanrunoff in the Bronx River watershed in New York City,
World Environmental and Water Resources Congress 2014, 2014
Resilience is a desirable property of coastal systems in facing a range of potential stresses, in... more Resilience is a desirable property of coastal systems in facing a range of potential stresses, including extreme rainfall events, devastating hurricanes, storm surges, sea level rise and climate change impacts. Urban resilient areas are able to withstand extreme natural disasters, such as flood without suffering devastating losses, damage, loosing productivity, or quality of life. Furthermore, these systems can follow their usual activities in a short period after disaster. In order to assess the resiliency of a city towards the flood events, performance evaluation criteria should be defined and quantified. In this study a resiliency measure of urban area in dealing with flood is proposed which is composed of four terms of redundancy, resourcefulness, robustness, and rapidity. These terms are quantified based on the system characteristics including socioeconomic and natural conditions. Recent history of the destructive flood disasters in New York City emphasizes on the importance and necessity of quantifying and then increasing resilience in this region. Therefore the proposed measure is applied to a coastal part of NYC Appropriate planning in urban areas considering improving system resilience regarding the main weakness points of the system, could mitigate some adverse impacts of flood disaster in an urban area.
Hydrology, 2018
Estimating maximum possible rainfall is of great value for flood prediction and protection, parti... more Estimating maximum possible rainfall is of great value for flood prediction and protection, particularly for regions, such as Canada, where urban and fluvial floods from extreme rainfalls have been known to be a major concern. In this study, a methodology is proposed to forecast real-time rainfall (with one month lead time) using different number of spatial inputs with different orders of lags. For this purpose, two types of models are used. The first one is a machine learning data driven-based model, which uses a set of hydrologic variables as inputs, and the second one is an empirical-statistical model that employs the multi-criteria decision analysis method for rainfall forecasting. The data driven model is built based on Artificial Neural Networks (ANNs), while the developed multi-criteria decision analysis model uses Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approach. A comprehensive set of spatially varying climate variables, including geopotential height, sea surface temperature, sea level pressure, humidity, temperature and pressure with different orders of lags is collected to form input vectors for the forecast models. Then, a feature selection method is employed to identify the most appropriate predictors. Two sets of results from the developed models, i.e., maximum daily rainfall in each month (RMAX) and cumulative value of rainfall for each month (RCU), are considered as the target variables for forecast purpose. The results from both modeling approaches are compared using a number of evaluation criteria such as Nash-Sutcliffe Efficiency (NSE). The proposed models are applied for rainfall forecasting for a coastal area in Western Canada: Vancouver, British Columbia. Results indicate although data driven models such as ANNs work well for the simulation purpose, developed TOPSIS model considerably outperforms ANNs for the rainfall forecasting. ANNs show acceptable simulation performance during the calibration period (NSE up to 0.9) but they fail for the validation (NSE of 0.2) and forecasting (negative NSE). The TOPSIS method delivers better rainfall forecasting performance with the NSE of about 0.7. Moreover, the number of predictors that are used in the TOPSIS model are significantly less than those required by the ANNs to show an acceptable performance (7 against 47 for forecasting RCU and 6 against 32 for forecasting RMAX). Reliable and precise rainfall forecasting, with adequate lead time, benefits enhanced flood warning and decision making to reduce potential flood damages.
<p&... more <p>Statistical analysis of hydrologic variables is of great importance for water resources systems. Design and operation of these systems is often based on the assumption of data stationarity. However, long-term average of variables such as rainfall as well as sea level is observed to shift over time, mostly attributed to the climate change. These changes, in turn, affect flood volume, peak value and frequency. In this study, a framework was proposed for bi- variate frequency analysis of extreme sea level and rainfall. The analysis was performed on rainfall for the coastal area of Charleston and Savannah, and sea level for the coastal area of Charleston and Fort Pulaski, South Carolina, USA. Extreme values were selected based on the peak over threshold method. To determine the most appropriate distribution, AIC and BIC goodness of fit tests were used. Frequency analysis was then carried out using nonstationary Generalized Extreme Value probability distribution function. Results showed an increase in the sea level long term average, significant trends and outliers (specifically in recent decades), while although the analysis of rainfall data confirms the presence of outliers in the time series, it does not indicate significant trends or heterogeneity. Therefore, in performing bi-variate frequency analysis of extreme rainfall and sea level, non-stationary approaches should be used to provide a more reliable prediction of the joint probability of these variables.</p>
Journal of Hydrology, 2019
This is a PDF file of an article that has undergone enhancements after acceptance, such as the ad... more This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Hydrological Sciences Journal, 2019
In snow-dominated basins, collection of snow data while capturing its spatio-temporal variability... more In snow-dominated basins, collection of snow data while capturing its spatio-temporal variability is difficult; therefore, integrating assimilation products could be a viable alternative for improving streamflow simulation. This study evaluates the accuracy of daily snow water equivalent (SWE) provided by the SNOw Data Assimilation System (SNODAS) of the National Weather Service at a 1-km 2 resolution for two basins in eastern Canada, where SWE is a critical variable intensifying spring runoff. A geostatistical interpolation method was used to distribute snow observations. SNODAS SWE products were bias-corrected by matching their cumulative
Journal of Hydrologic Engineering, 2018
It is imperative for cities to develop sustainable water management and planning strategies in or... more It is imperative for cities to develop sustainable water management and planning strategies in order to best serve urban communities that are currently facing increasing population and water demand. Water resources managers are often chastened by experiencing failures attributed to natural extreme droughts and floods. However, recent changes in water management systems have been responding to these uncertain conditions. Water managers have become thoughtful about the adverse effects of uncertain extreme events on the performance of water supply systems. Natural hydrologic variability and inherent uncertainties associated with the future climate variations make the simulation and management of water supplies a greater challenge. The hydrologic simulation process is one of the main components in integrated water resources management. Hydrologic simulations incorporate uncertain input values, model parameters, and a model structure. Therefore, stochastic streamflow simulation and prediction, and consideration of uncertainty propagation on performance of water supply systems (WSSs) are essential phases for efficient management of these systems. The proposed integrated framework in this study models a WSS by taking into account the dynamic nature of the system and utilizing a Markov chain Monte Carlo (MCMC) algorithm to capture the uncertainties associated with hydrologic simulation. Hydrologic responses from the results of a rainfall-runoff model for three watersheds of Karaj, Latyan, and Lar in Tehran, Iran, as the case study are used as inputs to the reservoirs. Results confirm that uncertainties associated with the hydrologic model's parameters propagate through the simulation and lead to a wide variation in reservoir storage and WSS performance metrics such as vulnerability and reliability. For example, water storage simulation in the Karaj Reservoir can vary up to 70% compared with the observed values. This causes contradiction and conflict in the management of reservoirs and water systems and decision making. The results emphasize the importance of analyzing WSS performance under uncertain conditions to improve the simulation of natural processes and support water managers for a more efficient decision-making process.
Canadian Water Resources Journal / Revue canadienne des ressources hydriques, 2019
This paper discusses flood forecasting procedures currently practiced at the Canadian provincial ... more This paper discusses flood forecasting procedures currently practiced at the Canadian provincial river flood forecast centers. In Canada, each province is responsible for collecting and managing meteorological and hydrometric data (through provincial authorities and/or under Federal/ Provincial agreements), developing suitable hydrological models, and providing information about river discharge and water level to the public. In case of an extreme event such as flood or drought, the forecast center is responsible for issuing alerts and supporting provincial emergency management. Due to the large diversity in landscape, weather, and hydrological features across the country, extreme events are triggered by different mechanisms such as snowmelt, heavy rainfall, rain on snow, etc., at different times of the year. Each river forecast center deals with unique challenges in data collection, hydrologic/hydraulic modeling, and flood forecasting. Thus, the focus of the Center in planning for developments and future directions could be significantly different from one province to another. In this paper, the significance of river flood forecasting in Canada, as well as the development in hydrological modelling procedures are highlighted. Moreover, an overview of the current approaches for streamflow/flood forecasting used by the Centers is provided. The content presented here is an outcome of our interaction with the forecast centers. This further resulted in identifying a number of research questions to help bridge the gap between ongoing research and needs of the Centers.
Water Resources Management, 2017
A great challenge has been appeared on if the assumption of data stationary for flood frequency a... more A great challenge has been appeared on if the assumption of data stationary for flood frequency analysis is justifiable. Results for frequency analysis (FA) could be substantially different if non-stationarity is incorporated in the data analysis. In this study, extreme water levels (annual maximum and daily instantaneous maximum) in a coastal part of New York City were considered for FA. Annual maximum series (AMS) and peak-over threshold (POT) approaches were applied to build data timeseries. The resulted timeseries were checked for potential trend and stationarity using statistical tests including Man-Kendall, Augmented Dickey-Fuller (ADF) and Kwiatkowski-Phillips-Schmidt-Shin (KPSS). Akaike information criterion (AIC) was utilized to select the most appropriate probability distribution models. Generalized Extreme Value (GEV) distribution and Generalized Pareto Distribution (GPD) were then applied as the probability distribution functions on the selected data based on AMS and POT methods under non-stationary assumption. Two methods of maximum likelihood and penalized maximum likelihood were applied and compared for the estimation of the distributions' parameters. Results showed that by incorporating non-stationarity in FA, design values of extreme water levels were significantly different from those obtained under the assumption of stationarity. Moreover, in the non-stationary FA, consideration of time-dependency for the distribution parameters resulted in a range of variation for design floods. The findings of this study emphasize on the importance of FA under the assumptions of data stationarity and nonstationarity, and taking into account the worst case flooding scenarios for future planning of the Water Resour Manage
Journal of Irrigation and Drainage Engineering, 2017
AbstractSuperstorm Sandy and Hurricane Irene on the East Coast of the United States were wake-up ... more AbstractSuperstorm Sandy and Hurricane Irene on the East Coast of the United States were wake-up calls that the floodplain delineation and flood damage estimation models need major overhaul. The fi...
Journal of Water Resources Planning and Management, 2017
Wastewater Treatment Plants that are constructed in the coastal regions need more attention since... more Wastewater Treatment Plants that are constructed in the coastal regions need more attention since the flood occurrence may cause excessive loads on the infrastructures. These excessive loads may result in the system's failure and innumerable damages on the infrastructure. In this study, in order to reduce WWTPs' flood vulnerability, an index called Resiliency was developed to quantify system's characteristics. Later, two main approaches were considered to enhance the infrastructure performance: the "Resource allocation" and the "Cooperative behavior" method. The former method was applied employing those factors which were improvable with the investment of funds and financial allocations. They were utilized to make the system more robust. In addition, implementing some new agents with potential impacts on funding were described in order to have a more realistic vision. As for the latter method, the cooperative behavior approach, the cooperation was utilized to demonstrate joint operation among WWTPs and the way they interact. For this purpose, WWTPs' placement was analyzed to check if they could operate jointly. Thereafter, effectiveness of these two approaches was compared in order to make the best decision regarding different cases. The results showed that in three collaborations among Bowery Bay, Tallman Island, Newtown Creek, and Red Hook WWTPs, cooperation has had a significant effect on the resiliency index.
Science of The Total Environment, 2016
In this paper, an integrated framework is proposed for urban runoff management. To control and im... more In this paper, an integrated framework is proposed for urban runoff management. To control and improve runoff quality and quantity, Low Impact Development (LID) practices are utilized. In order to determine the LIDs' areas and locations, the Non-dominated Sorting Genetic Algorithm-II (NSGA-II), which considers three objective functions of minimizing runoff volume, runoff pollution and implementation cost of LIDs, is utilized. In this framework, the Storm Water Management Model (SWMM) is used for stream flow simulation. The non-dominated solutions provided by the NSGA-II are considered as management scenarios. To select the most preferred scenario, interactions among the main stakeholders in the study area with conflicting utilities are incorporated by utilizing bargaining models including a non-cooperative game, Nash model and social choice procedures of Borda count and approval voting. Moreover, a new social choice procedure, named pairwise voting method, is proposed and applied. Based on each conflict resolution approach, a scenario is identified as the ideal solution providing the LIDs' areas, locations and implementation cost. The proposed framework is applied for urban water quality and quantity management in the northern part of Tehran metropolitan city, Iran. Results show that the proposed pairwise voting method tends to select a scenario with a higher percentage of reduction in TSS (Total Suspended Solid) load and runoff volume, in comparison with the Borda count and approval voting methods. Besides, the Nash method presents a management scenario with the highest cost for LIDs' implementation and the maximum values for percentage of runoff volume reduction and TSS removal. The results also signify that selection of an appropriate management scenario by stakeholders in the study area depends on the available financial resources and the relative importance of runoff quality improvement in comparison with reducing the runoff volume.
Advances in Water Resources, 2015
ABSTRACT
World Environmental and Water Resources Congress 2011, 2011
Water Resources Management, 2014
ABSTRACT Optimal reservoir operation and water allocation are critical issues in sustainable wate... more ABSTRACT Optimal reservoir operation and water allocation are critical issues in sustainable water resource management due to increasing water demand. Multiplicity of stockholders with different objectives and utilities makes reservoir operation a complicated problem with a variety of constraints and objectives to be considered. In this case, the conflict resolution models can be efficiently used to determine the optimal water allocation scheme considering the utility and relative authority of different stakeholders. In this study, the Nash product is used for formulation of the objective function of a reservoir water allocation model. The Analytic Hierarchy Process (AHP) is used to determine the importance of each stockholder in bargaining for water. The Particle Swarm Optimization algorithm (PSO) and the Imperialism Competitive Algorithm (ICA) are applied to solve the proposed optimization model. System performance indices including reliability, resiliency and vulnerability are used to evaluate the performance of optimization algorithms. The simplest and most often-used reservoir policy (Standard Operating Policy, SOP) is also used in order to evaluate the performance of the proposed models. The proposed model is applied to the Karkheh River-Reservoir system located in south western part of Iran as a case study. Results show the significance of the application of conflict resolution models, such as the Nash theory and proposed optimization algorithms, for water allocation in the regional scale especially in complicated water supply systems.
World Environmental and Water Resources Congress 2008, 2008
In this paper, two deterministic and stochastic multilateral, multi-issue, non-cooperative bargai... more In this paper, two deterministic and stochastic multilateral, multi-issue, non-cooperative bargaining methodologies are proposed for urban runoff quality management. In the proposed methodologies, a calibrated Storm Water Management Model (SWMM) is used to simulate stormwater runoff quantity and quality for different urban stormwater runoff management scenarios, which have been defined considering several Low Impact Development (LID) techniques. In the deterministic methodology, the best management scenario, representing location and area of LID controls, is identified using the bargaining model. In the stochastic methodology, uncertainties of some key parameters of SWMM are analyzed using the info-gap theory. For each water quality management scenario, robustness and opportuneness criteria are determined based on utility functions of different stakeholders. Then, to find the best solution, the bargaining model is performed considering a combination of robustness and opportuneness criteria for each scenario based on utility function of each stakeholder. The results of applying the proposed methodology in the Velenjak urban watershed located in the northeastern part of Tehran, the capital city of Iran, illustrate its practical utility for conflict resolution in urban water quantity and quality management. It is shown that the solution obtained using the deterministic model cannot outperform the result of the stochastic model considering the robustness and opportuneness criteria. Therefore, it can be concluded that the stochastic model, which incorporates the main uncertainties, could provide more reliable results.
Journal of Irrigation and Drainage Engineering, 2015
ABSTRACT doi: 10.1061/(ASCE)IR.1943-4774.0000770
World Environmental and Water Resources Congress 2012, 2012
Journal of Hydrologic Engineering, 2015
ABSTRACT doi: 10.1061/(ASCE)HE.1943-5584.0001064
Journal of Water Resources Planning and Management, 2015
ABSTRACT doi: 10.1061/(ASCE)WR.1943-5452.0000497
World Environmental and Water Resources Congress 2014, 2014
Climate change is projected to have significant impacts on patterns of weather variables, all aro... more Climate change is projected to have significant impacts on patterns of weather variables, all around the world. To study the impacts of climate change on rainfall, different global climate models (GCMs) and climate scenarios are used to build projections for probable future patterns of rainfall. Using the rainfall projections, the change in runoff peaks and volumes can be projected. In this paper,a climate change impact study is presentedto investigate the effect of future uncertain rainfall patterns on urbanrunoff in the Bronx River watershed in New York City,
World Environmental and Water Resources Congress 2014, 2014
Resilience is a desirable property of coastal systems in facing a range of potential stresses, in... more Resilience is a desirable property of coastal systems in facing a range of potential stresses, including extreme rainfall events, devastating hurricanes, storm surges, sea level rise and climate change impacts. Urban resilient areas are able to withstand extreme natural disasters, such as flood without suffering devastating losses, damage, loosing productivity, or quality of life. Furthermore, these systems can follow their usual activities in a short period after disaster. In order to assess the resiliency of a city towards the flood events, performance evaluation criteria should be defined and quantified. In this study a resiliency measure of urban area in dealing with flood is proposed which is composed of four terms of redundancy, resourcefulness, robustness, and rapidity. These terms are quantified based on the system characteristics including socioeconomic and natural conditions. Recent history of the destructive flood disasters in New York City emphasizes on the importance and necessity of quantifying and then increasing resilience in this region. Therefore the proposed measure is applied to a coastal part of NYC Appropriate planning in urban areas considering improving system resilience regarding the main weakness points of the system, could mitigate some adverse impacts of flood disaster in an urban area.