This document summarizes a master's thesis defense presentation on predicting travel time and developing flood inundation maps for flood warning systems. The presentation covers: (1) background on floods and need for warning systems; (2) objectives to quantify effects of elevation data and roughness on travel time/inundation area and develop maps; (3) methodology using HEC-RAS modeling; and (4) results on effects of topography/roughness and developing maps for various flood stages along the Grand River, Ohio.
Investigating Flooding Pattern Using Hydrologic Engineering Center-River Anal...Niraj Lamichhane
This study analyzed ice jams and flooding in the Grand River watershed in northern Ohio using the HEC-RAS hydraulic model. The objectives were to understand how ice jams contribute to flooding and create flood maps of different return periods. Field data and aerial imagery were used to develop the HEC-RAS model. The model showed that a 500-year flood would inundate homes, bridges and parks. Historical data analysis found that ice jams were most common during neutral ENSO phases. Increased winter temperatures may exacerbate ice jam flooding by accelerating snow and ice melt. The results can help identify at-risk areas and improve flood warning systems.
APPLICATIONS OF ARC SWAT MODEL FOR HYDROLOGICAL MODELLINGAbhiram Kanigolla
SWAT is a watershed-scale model used to predict the impacts of management on water resources. It divides watersheds into subwatersheds and hydrologic response units. Model setup involves watershed delineation, HRU definition, weather data input, editing SWAT inputs, and running the model. Several case studies demonstrate applications of SWAT for developing inflow-outflow models, estimating water resources, managing check dams, quantifying land use change impacts, and modeling best management practices.
This document discusses using machine learning techniques to forecast agricultural drought by incorporating high-resolution soil moisture data. It aims to 1) forecast soil water deficit index (SWDI) up to one week using support vector machines (SVM) improved with dual ensemble Kalman filters, and 2) evaluate satellite-derived soil moisture against in situ observations to assess its use in drought indices. The results show dual EnKF greatly improves SVM predictions of SWDI at different soil layers and SMAP satellite soil moisture captures the dynamics of root-zone soil moisture compared to in situ observations.
This document discusses using hydrological models like SWAT, MODFLOW, and SEAWAT to assess the impacts of climate change on water resources. It provides an overview of these models, including their inputs, outputs, capabilities, and examples of case studies applying the models. Specifically, SWAT is highlighted as it can be used at the watershed scale to model processes like precipitation, evapotranspiration, infiltration, surface runoff, and streamflow under different climate scenarios. The document emphasizes the importance of hydrological modeling and tools like MODFLOW for understanding and predicting hydrologic system responses to climate change.
The document describes calibrating and validating the parameters of the HEC-HMS hydrological model for the Kharkai River Basin in eastern India. The objectives are to calibrate parameters like initial loss, constant rate, impervious area, lag time and peaking coefficient that affect rainfall-runoff processes. The validated model is used to compute flood peaks and times to peak from rainfall events. Model performance is evaluated using statistical measures for the study area. Calibration results show the model can accurately predict peak flood volumes and times to peak, indicating HEC-HMS is suitable for modeling the Kharkai catchment.
This document describes Arc SWAT, an ArcGIS extension tool for watershed modeling using SWAT. It can be used for developing inflow-outflow models, estimating water resources, managing check dams, and quantifying impacts of land use change. The document provides details on how Arc SWAT works, including delineating watersheds and subbasins, defining land use/soil/slope data, determining hydrologic response units, and running SWAT simulations. It then presents a case study applying ArcSWAT to model the Poondi sub-watershed in India.
Investigating Flooding Pattern Using Hydrologic Engineering Center-River Anal...Niraj Lamichhane
This study analyzed ice jams and flooding in the Grand River watershed in northern Ohio using the HEC-RAS hydraulic model. The objectives were to understand how ice jams contribute to flooding and create flood maps of different return periods. Field data and aerial imagery were used to develop the HEC-RAS model. The model showed that a 500-year flood would inundate homes, bridges and parks. Historical data analysis found that ice jams were most common during neutral ENSO phases. Increased winter temperatures may exacerbate ice jam flooding by accelerating snow and ice melt. The results can help identify at-risk areas and improve flood warning systems.
APPLICATIONS OF ARC SWAT MODEL FOR HYDROLOGICAL MODELLINGAbhiram Kanigolla
SWAT is a watershed-scale model used to predict the impacts of management on water resources. It divides watersheds into subwatersheds and hydrologic response units. Model setup involves watershed delineation, HRU definition, weather data input, editing SWAT inputs, and running the model. Several case studies demonstrate applications of SWAT for developing inflow-outflow models, estimating water resources, managing check dams, quantifying land use change impacts, and modeling best management practices.
This document discusses using machine learning techniques to forecast agricultural drought by incorporating high-resolution soil moisture data. It aims to 1) forecast soil water deficit index (SWDI) up to one week using support vector machines (SVM) improved with dual ensemble Kalman filters, and 2) evaluate satellite-derived soil moisture against in situ observations to assess its use in drought indices. The results show dual EnKF greatly improves SVM predictions of SWDI at different soil layers and SMAP satellite soil moisture captures the dynamics of root-zone soil moisture compared to in situ observations.
This document discusses using hydrological models like SWAT, MODFLOW, and SEAWAT to assess the impacts of climate change on water resources. It provides an overview of these models, including their inputs, outputs, capabilities, and examples of case studies applying the models. Specifically, SWAT is highlighted as it can be used at the watershed scale to model processes like precipitation, evapotranspiration, infiltration, surface runoff, and streamflow under different climate scenarios. The document emphasizes the importance of hydrological modeling and tools like MODFLOW for understanding and predicting hydrologic system responses to climate change.
The document describes calibrating and validating the parameters of the HEC-HMS hydrological model for the Kharkai River Basin in eastern India. The objectives are to calibrate parameters like initial loss, constant rate, impervious area, lag time and peaking coefficient that affect rainfall-runoff processes. The validated model is used to compute flood peaks and times to peak from rainfall events. Model performance is evaluated using statistical measures for the study area. Calibration results show the model can accurately predict peak flood volumes and times to peak, indicating HEC-HMS is suitable for modeling the Kharkai catchment.
This document describes Arc SWAT, an ArcGIS extension tool for watershed modeling using SWAT. It can be used for developing inflow-outflow models, estimating water resources, managing check dams, and quantifying impacts of land use change. The document provides details on how Arc SWAT works, including delineating watersheds and subbasins, defining land use/soil/slope data, determining hydrologic response units, and running SWAT simulations. It then presents a case study applying ArcSWAT to model the Poondi sub-watershed in India.
The Development of a Catchment Management Modelling System for the Googong Re...GavanThomas
A scenario assessment model to assist the end-user in determining priorities for a series of agreed management prescriptions that can be enacted through controls on existing landuse
A study confined to the lower tapi basin in Gujarat, India to find out the primary causes for 2006 floods in Surat city. The study involves collection of topographical data from the local geological survey organization, rainfall data from meteorological department of india and the application of HEC-HMS software from US Army corps of engineers to identify the primary cause of the runoff.
Assessing the ability of SWAT as a water quality model in the Lake Victoria b...Timo Brussée
There is a need for a water quality model for use in the Lake Victoria basin countries in East-Africa. The
region is characterised by data scarcity, a tropical climate and riverine, lacustrine tidal wetlands which form
an important buffer to riverine pollution of the lake. These characteristics of the basin form a challenge for
water quality models. The objective is to state the strengths and weaknesses of a potential water quality
model under these challenging conditions. This objective is executed with the soil water assessment tool
(SWAT) in a catchment of the Lake Victoria Basin as pilot area. The pilot area of the Mara river basin is
hydrologically complex containing tropical and plantation forest, savanna, grasslands, bi-annual agriculture,
shrublands and wetlands. It has varied soil types and bi-annual rain seasons
The study consist of literature research and flow simulation of the transboundary Mara river basin. The
model study aims to characterise the hydrology in the pilot area. The study includes a thorough analysis of
rainfall, stage and flow data. Model preparation steps include the use of weighted-area rainfall estimation
methods, climate model data and empirical derivation of soil input parameters. Discharge calibration
methods include multi-site calibration, by making use of an alternative objective function statistic for the
commonly used Nash-Sutcliffe Efficiency (NSE) called the Kling-Gupta Efficiency (KGE). The literature study
targets previous flow and water quality studies done in tropical or wetland areas, thereby looking to see how
these studies adapted to hydrological modelling with SWAT in tropical or wetland areas, and why theses
adaptions were made. The literature research also includes a comparison of wetland processes in SWAT
with the physical, biological and chemical processes as described in previous studies.
The Mara river basin flow simulation gave a satisfactory model performance for two out of three calibration
sites, thereby being able to give preliminary outputs on water-balance and other flow characteristics. During
research, a number of model, knowledge and data gaps were found to be critical for better understanding
the hydrological and water quality system workings in the Lake Victoria and Mara river basin. From the
model and literature study it is concluded that several issues on data scarcity and hydrological model
processes in the tropics can be overcome. These do not necessarily decrease model performance or
uncertainty in the SWAT model. However, wetland processes are oversimplified in SWAT. Modification and
coupled SWAT models yet have not been able to provide an alternative to the default model that adequately
represents the main flow, sediment and nutrients processes and fluxes that are present in Mara’s wetlands.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
This document discusses the history and recent advances in hydrologic modeling. It begins with definitions of hydrology and applications of hydrologic models such as water resources planning. It then discusses the historical development of early component models in the 1900s and the creation of integrated watershed models starting in the 1960s. Recent advances include the use of remote sensing, GIS, and handling spatial and temporal variability. The future outlook emphasizes increasing model complexity through linking with other domains and improving reliability.
Hydrologic Assessment in a Middle Narmada Basin, India using SWAT ModelSumant Diwakar
The document describes a study that used the SWAT (Soil and Water Assessment Tool) model to assess hydrologic processes in the middle Narmada River basin in India. Key inputs to the SWAT model included digital elevation data, land use/land cover maps, soil data, and weather data. The model was set up to simulate hydrologic response units based on land use, soil type, and slope. Model outputs included estimates of precipitation, temperature, evapotranspiration, and streamflow over the study period. Results indicated that about 46% of annual precipitation was lost to evapotranspiration in the basin. The study provides a hydrologic assessment of the basin using remote sensing and geospatial data within the SWAT
Groundwater models are simplified representation of large and real hydrogeologic systems like river basins or watersheds. GWM is attempted to analyse the mechanisms which control the occurrence and movement of groundwater and to evaluate the policies, actions and designs which may affect the systems. These models are less complex prototypes of complex hydrogeologic systems developed using spatially varying aquifer parameters, hydrologic properties, geologic boundary conditions and positions of withdrawal wells or recharging structures. These are designed to compute how pumping or recharge might affect the local or regional groundwater levels.
This document provides an introduction and overview of groundwater modeling. It discusses why groundwater modeling is needed for effective groundwater management. It outlines the modeling process, including developing a conceptual model, selecting governing equations, model design, calibration, validation, and using the model for prediction. It describes different types of mathematical models, including analytical, finite difference, and finite element models. It emphasizes that a modeling protocol should establish the modeling purpose and ensure the conceptual model adequately represents the system behavior. The document stresses the importance of calibration, verification, and sensitivity analysis to evaluate a model's ability to reproduce measured conditions and the effects of uncertainty.
Sea level rise and storm surge tools and datasets supporting Municipal Resili...GrowSmart Maine
Why plan for growth and change, when it seems so much easier to simply react?
When there is a distinct and shared vision for your community - when residents, businesses and local government anticipate a sustainable town with cohesive and thriving neighborhoods - you have the power to conserve your beautiful natural spaces, enhance your existing downtown or Main Street, enable rural areas to be productive and prosperous, and save money through efficient use of existing infrastructure.
This is the dollars and sense of smart growth.
Success is clearly visible in Maine, from the creation of a community-built senior housing complex and health center in Fort Fairfield to conservation easements creating Forever Farms to Rockland's revitalized downtown. Communities have options. We have the power to manage our own responses to growth and change.
After all, “Planning is a process of choosing among those many options. If we do not choose to plan, then we choose to have others plan for us.” - Richard I. Winwood
And in the end, this means that our children and their children will choose to make Maine home and our economy will provide the opportunities to do so.
The Summit offers you a wonderful opportunity to be a part of the transformative change in Maine that we’ve seen these gatherings produce. We encourage you to consider the value of being actively involved in growing Maine’s economy and protecting the reasons we choose to live here.
Streamflow simulation using radar-based precipitation applied to the Illinois...Alireza Safari
This paper describes the application of a spatially distributed hydrological model WetSpa (Water and Energy Transfer between Soil, Plants and Atmosphere) using radar-based rainfall data provide by the United States Hydrology Laboratory of NOAA's National Weather Service for a distributed model intercomparison project. The model is applied to the
river basin above Tahlequah hydrometry station with 30-m spatial resolution and one hour time--step for a total simulation period of 6 years. Rainfall inputs are derived from radar. The distributed model parameters are based on an extensive database of watershed characteristics available for the region, including digital maps of DEM, soil type, and land use. The model is calibrated and validated on part of the river flow records. The simulated hydrograph shows a good correspondence with observation (Nash efficiency coeffiecient >80%, indicating that the model is able to simulate the relevant hydrologic processes in the basin accurately.
Poster prepared by Mahtsente Tibebe, Birhanu Zemadim, Dereje Haile and Assefa Melesse at the Nile Basin Development Challenge (NBDC) Science Workshop, Addis Ababa, Ethiopia, 9–10 July 2013
Groundwater modeling has several purposes including understanding aquifer properties, characteristics, and response. It requires collecting hydrological, physical, and boundary condition data. Common groundwater modeling software includes MODFLOW and Sutra. The modeling process involves defining the problem, collecting data, choosing a code, running simulations, verifying results match field data through calibration, and using the model to inform management decisions.
This document discusses using the MODFLOW groundwater model to evaluate the impact of artificial groundwater recharge in Abbid Sarbishe, Iran. A conceptual model of the study area was developed using hydrogeological data and discretized into a grid for use in MODFLOW. The model was calibrated and validated before using it to simulate different levels of artificial recharge. The results show that recharge has the greatest impact on piezometers closest to the recharge site, with water levels rising up to 2.25 meters. Western parts of the recharge site had a larger impact due to thinner unsaturated zones in the aquifer in that area.
Birr - Identifying Critical Portions of the LandscapeJose A. Hernandez
Terrain attributes derived from digital elevation models can be used to identify critical source areas for water quality protection. A study calculated terrain attributes like slope, curvature, and stream power index for two pilot watersheds in Minnesota. Field surveys showed higher values of attributes like specific catchment area and stream power index corresponded to locations of gullies and other erosion features. The results indicate terrain analysis can efficiently identify priority areas for conservation practices to reduce sediment and nutrient runoff.
Dredging and Disposal Site Reclamation at John Redmond Reservoir, KansasMatt Unruh
This document summarizes a dredging and disposal project at John Redmond Reservoir in Kansas that took place from 2015 to 2017. Over 3 million cubic yards of sediment were removed from the reservoir and placed into confined disposal facilities. The project involved permitting and environmental reviews, construction of the disposal sites, dredging operations using a large electric dredge, and ongoing reclamation efforts to return the disposal sites to agricultural use. The $20 million project was financed through state bonds and water resources funds to help address declining storage capacity in the reservoir due to sedimentation.
DSD-INT 2017 Basin Water Resources Management Planning in Indonesia - HendartiDeltares
Presentation by Henni Hendarti (PT-MLD) at the River Basin Planning and Modelling symposium, during Delft Software Days - Edition 2017. Wednesday, 25 October 2017, Delft.
This document summarizes land cover change analysis tools and data developed by NOAA to improve conservation and restoration efforts in the Great Lakes region. It describes the Coastal Change Analysis Program, which maps land cover every 5 years. Analysis of C-CAP data from 1985 to 2010 found increases in developed and scrubland areas and decreases in agriculture, forest, and grasslands. The document also outlines a land cover atlas, wetland modeling tool, planned water quality tool, and an open-source nonpoint source pollution model.
Developing a Model to Validate the Use of Landsat and MODIS Data to Monitor C...daileya
This document describes developing a model to analyze Landsat and MODIS data to monitor coastal wetland areas in Louisiana for persistent saltwater intrusion. The model combines data from various sources, including USGS monitoring stations and Landsat imagery, to identify relationships between salinity, flooding, and vegetation changes. It extracts relevant data for selected dates and locations to produce a database for analyzing how wetlands respond to physical changes. Results show the procedure fulfills requirements for sorting multi-source data and aiding interpretation of remote sensing products for coastal wetland monitoring and restoration.
Drs. Witold Krajewski and Ricardo Mantilla have developed graphical user interfaces for a comprehensive model evaluation that allows for testing model performance in new regions. They have developed methodologies for rapid model implementation and parameterization, the extension of the domain of rainfall product, and techniques for
data assimilation to insure high-quality food forecasts.
This document describes a study that used cryospheric-hydrological models to evaluate the impacts of climate change on glaciers, runoff, and water availability in two Himalayan river basins. The models were set up and calibrated for the basins, then driven by downscaled climate projections from the CORDEX regional climate models. The results show declines in glacier volume and increases in air temperature and precipitation by 2100. Runoff is projected to initially increase but then decline in both basins. Water availability per person is projected to decrease in both basins due to the combined effects of climate change and population growth.
The Development of a Catchment Management Modelling System for the Googong Re...GavanThomas
A scenario assessment model to assist the end-user in determining priorities for a series of agreed management prescriptions that can be enacted through controls on existing landuse
A study confined to the lower tapi basin in Gujarat, India to find out the primary causes for 2006 floods in Surat city. The study involves collection of topographical data from the local geological survey organization, rainfall data from meteorological department of india and the application of HEC-HMS software from US Army corps of engineers to identify the primary cause of the runoff.
Assessing the ability of SWAT as a water quality model in the Lake Victoria b...Timo Brussée
There is a need for a water quality model for use in the Lake Victoria basin countries in East-Africa. The
region is characterised by data scarcity, a tropical climate and riverine, lacustrine tidal wetlands which form
an important buffer to riverine pollution of the lake. These characteristics of the basin form a challenge for
water quality models. The objective is to state the strengths and weaknesses of a potential water quality
model under these challenging conditions. This objective is executed with the soil water assessment tool
(SWAT) in a catchment of the Lake Victoria Basin as pilot area. The pilot area of the Mara river basin is
hydrologically complex containing tropical and plantation forest, savanna, grasslands, bi-annual agriculture,
shrublands and wetlands. It has varied soil types and bi-annual rain seasons
The study consist of literature research and flow simulation of the transboundary Mara river basin. The
model study aims to characterise the hydrology in the pilot area. The study includes a thorough analysis of
rainfall, stage and flow data. Model preparation steps include the use of weighted-area rainfall estimation
methods, climate model data and empirical derivation of soil input parameters. Discharge calibration
methods include multi-site calibration, by making use of an alternative objective function statistic for the
commonly used Nash-Sutcliffe Efficiency (NSE) called the Kling-Gupta Efficiency (KGE). The literature study
targets previous flow and water quality studies done in tropical or wetland areas, thereby looking to see how
these studies adapted to hydrological modelling with SWAT in tropical or wetland areas, and why theses
adaptions were made. The literature research also includes a comparison of wetland processes in SWAT
with the physical, biological and chemical processes as described in previous studies.
The Mara river basin flow simulation gave a satisfactory model performance for two out of three calibration
sites, thereby being able to give preliminary outputs on water-balance and other flow characteristics. During
research, a number of model, knowledge and data gaps were found to be critical for better understanding
the hydrological and water quality system workings in the Lake Victoria and Mara river basin. From the
model and literature study it is concluded that several issues on data scarcity and hydrological model
processes in the tropics can be overcome. These do not necessarily decrease model performance or
uncertainty in the SWAT model. However, wetland processes are oversimplified in SWAT. Modification and
coupled SWAT models yet have not been able to provide an alternative to the default model that adequately
represents the main flow, sediment and nutrients processes and fluxes that are present in Mara’s wetlands.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
This document discusses the history and recent advances in hydrologic modeling. It begins with definitions of hydrology and applications of hydrologic models such as water resources planning. It then discusses the historical development of early component models in the 1900s and the creation of integrated watershed models starting in the 1960s. Recent advances include the use of remote sensing, GIS, and handling spatial and temporal variability. The future outlook emphasizes increasing model complexity through linking with other domains and improving reliability.
Hydrologic Assessment in a Middle Narmada Basin, India using SWAT ModelSumant Diwakar
The document describes a study that used the SWAT (Soil and Water Assessment Tool) model to assess hydrologic processes in the middle Narmada River basin in India. Key inputs to the SWAT model included digital elevation data, land use/land cover maps, soil data, and weather data. The model was set up to simulate hydrologic response units based on land use, soil type, and slope. Model outputs included estimates of precipitation, temperature, evapotranspiration, and streamflow over the study period. Results indicated that about 46% of annual precipitation was lost to evapotranspiration in the basin. The study provides a hydrologic assessment of the basin using remote sensing and geospatial data within the SWAT
Groundwater models are simplified representation of large and real hydrogeologic systems like river basins or watersheds. GWM is attempted to analyse the mechanisms which control the occurrence and movement of groundwater and to evaluate the policies, actions and designs which may affect the systems. These models are less complex prototypes of complex hydrogeologic systems developed using spatially varying aquifer parameters, hydrologic properties, geologic boundary conditions and positions of withdrawal wells or recharging structures. These are designed to compute how pumping or recharge might affect the local or regional groundwater levels.
This document provides an introduction and overview of groundwater modeling. It discusses why groundwater modeling is needed for effective groundwater management. It outlines the modeling process, including developing a conceptual model, selecting governing equations, model design, calibration, validation, and using the model for prediction. It describes different types of mathematical models, including analytical, finite difference, and finite element models. It emphasizes that a modeling protocol should establish the modeling purpose and ensure the conceptual model adequately represents the system behavior. The document stresses the importance of calibration, verification, and sensitivity analysis to evaluate a model's ability to reproduce measured conditions and the effects of uncertainty.
Sea level rise and storm surge tools and datasets supporting Municipal Resili...GrowSmart Maine
Why plan for growth and change, when it seems so much easier to simply react?
When there is a distinct and shared vision for your community - when residents, businesses and local government anticipate a sustainable town with cohesive and thriving neighborhoods - you have the power to conserve your beautiful natural spaces, enhance your existing downtown or Main Street, enable rural areas to be productive and prosperous, and save money through efficient use of existing infrastructure.
This is the dollars and sense of smart growth.
Success is clearly visible in Maine, from the creation of a community-built senior housing complex and health center in Fort Fairfield to conservation easements creating Forever Farms to Rockland's revitalized downtown. Communities have options. We have the power to manage our own responses to growth and change.
After all, “Planning is a process of choosing among those many options. If we do not choose to plan, then we choose to have others plan for us.” - Richard I. Winwood
And in the end, this means that our children and their children will choose to make Maine home and our economy will provide the opportunities to do so.
The Summit offers you a wonderful opportunity to be a part of the transformative change in Maine that we’ve seen these gatherings produce. We encourage you to consider the value of being actively involved in growing Maine’s economy and protecting the reasons we choose to live here.
Streamflow simulation using radar-based precipitation applied to the Illinois...Alireza Safari
This paper describes the application of a spatially distributed hydrological model WetSpa (Water and Energy Transfer between Soil, Plants and Atmosphere) using radar-based rainfall data provide by the United States Hydrology Laboratory of NOAA's National Weather Service for a distributed model intercomparison project. The model is applied to the
river basin above Tahlequah hydrometry station with 30-m spatial resolution and one hour time--step for a total simulation period of 6 years. Rainfall inputs are derived from radar. The distributed model parameters are based on an extensive database of watershed characteristics available for the region, including digital maps of DEM, soil type, and land use. The model is calibrated and validated on part of the river flow records. The simulated hydrograph shows a good correspondence with observation (Nash efficiency coeffiecient >80%, indicating that the model is able to simulate the relevant hydrologic processes in the basin accurately.
Poster prepared by Mahtsente Tibebe, Birhanu Zemadim, Dereje Haile and Assefa Melesse at the Nile Basin Development Challenge (NBDC) Science Workshop, Addis Ababa, Ethiopia, 9–10 July 2013
Groundwater modeling has several purposes including understanding aquifer properties, characteristics, and response. It requires collecting hydrological, physical, and boundary condition data. Common groundwater modeling software includes MODFLOW and Sutra. The modeling process involves defining the problem, collecting data, choosing a code, running simulations, verifying results match field data through calibration, and using the model to inform management decisions.
This document discusses using the MODFLOW groundwater model to evaluate the impact of artificial groundwater recharge in Abbid Sarbishe, Iran. A conceptual model of the study area was developed using hydrogeological data and discretized into a grid for use in MODFLOW. The model was calibrated and validated before using it to simulate different levels of artificial recharge. The results show that recharge has the greatest impact on piezometers closest to the recharge site, with water levels rising up to 2.25 meters. Western parts of the recharge site had a larger impact due to thinner unsaturated zones in the aquifer in that area.
Birr - Identifying Critical Portions of the LandscapeJose A. Hernandez
Terrain attributes derived from digital elevation models can be used to identify critical source areas for water quality protection. A study calculated terrain attributes like slope, curvature, and stream power index for two pilot watersheds in Minnesota. Field surveys showed higher values of attributes like specific catchment area and stream power index corresponded to locations of gullies and other erosion features. The results indicate terrain analysis can efficiently identify priority areas for conservation practices to reduce sediment and nutrient runoff.
Dredging and Disposal Site Reclamation at John Redmond Reservoir, KansasMatt Unruh
This document summarizes a dredging and disposal project at John Redmond Reservoir in Kansas that took place from 2015 to 2017. Over 3 million cubic yards of sediment were removed from the reservoir and placed into confined disposal facilities. The project involved permitting and environmental reviews, construction of the disposal sites, dredging operations using a large electric dredge, and ongoing reclamation efforts to return the disposal sites to agricultural use. The $20 million project was financed through state bonds and water resources funds to help address declining storage capacity in the reservoir due to sedimentation.
DSD-INT 2017 Basin Water Resources Management Planning in Indonesia - HendartiDeltares
Presentation by Henni Hendarti (PT-MLD) at the River Basin Planning and Modelling symposium, during Delft Software Days - Edition 2017. Wednesday, 25 October 2017, Delft.
This document summarizes land cover change analysis tools and data developed by NOAA to improve conservation and restoration efforts in the Great Lakes region. It describes the Coastal Change Analysis Program, which maps land cover every 5 years. Analysis of C-CAP data from 1985 to 2010 found increases in developed and scrubland areas and decreases in agriculture, forest, and grasslands. The document also outlines a land cover atlas, wetland modeling tool, planned water quality tool, and an open-source nonpoint source pollution model.
Developing a Model to Validate the Use of Landsat and MODIS Data to Monitor C...daileya
This document describes developing a model to analyze Landsat and MODIS data to monitor coastal wetland areas in Louisiana for persistent saltwater intrusion. The model combines data from various sources, including USGS monitoring stations and Landsat imagery, to identify relationships between salinity, flooding, and vegetation changes. It extracts relevant data for selected dates and locations to produce a database for analyzing how wetlands respond to physical changes. Results show the procedure fulfills requirements for sorting multi-source data and aiding interpretation of remote sensing products for coastal wetland monitoring and restoration.
Drs. Witold Krajewski and Ricardo Mantilla have developed graphical user interfaces for a comprehensive model evaluation that allows for testing model performance in new regions. They have developed methodologies for rapid model implementation and parameterization, the extension of the domain of rainfall product, and techniques for
data assimilation to insure high-quality food forecasts.
This document describes a study that used cryospheric-hydrological models to evaluate the impacts of climate change on glaciers, runoff, and water availability in two Himalayan river basins. The models were set up and calibrated for the basins, then driven by downscaled climate projections from the CORDEX regional climate models. The results show declines in glacier volume and increases in air temperature and precipitation by 2100. Runoff is projected to initially increase but then decline in both basins. Water availability per person is projected to decrease in both basins due to the combined effects of climate change and population growth.
This document describes a study that used cryospheric-hydrological models to evaluate the impacts of climate change on glaciers, runoff, and water availability in two Himalayan river basins. The models were set up and calibrated for the basins, then driven by downscaled climate projections from the CORDEX regional climate models. The results show declines in glacier volume and increases in air temperature and precipitation by 2100. Runoff is projected to initially increase but then decline in both basins. Water availability per person is projected to decrease in both basins due to the combined effects of climate change and population growth.
This document provides an overview of guidance materials for the management of surface water data within India's Hydrological Information System (HIS). It describes the lifecycle of hydrometric data from collection through analysis and publication. Key documents that provide procedures for surface water data management are the HIS Manual Surface Water and various training modules developed under the Hydrology Project. The manual and modules cover topics like network design, data collection, entry, validation, processing, analysis, and dissemination of water level, stage-discharge, and flow data. The goal is to standardize surface water data management practices across states and agencies to improve data quality and usability.
ICLR Friday Forum: Modelling of Future Flood Risk Across Canada (May 31, 2019)glennmcgillivray
On May 31, 2019, ICLR conducted a Friday Forum webinar lead by Dr. Slobodan Simonovic of Western University titled 'Modelling of Future Flood Risk Across Canada Under Climate Change.'
Climate change has induced changes in key climate variables and the hydrological cycle across Canada. With continuous emission of greenhouse gases, this trend is expected to continue over the 21st century and beyond. In this study, a macro-scaled hydrodynamic model is used to simulate 25 km resolution daily streamflow across Canada for historical (1961-2005) and future (2061-2100) timelines.
Future projections from 21 GCMs following four Representative Concentration Pathways (RCPs) were used for the analysis. Changes in the frequency and magnitude of historical 100-year and 250-year return period flood events and month of occurrence of peak flow are analyzed. Results obtained from uncertainty analysis for both return period flood events found that flood frequency will increase in most of the northern Canada, southern Ontario, southern British Columbia, northern Alberta, Manitoba and Saskatchewan. However, northern British Columbia, northern Ontario, Manitoba and northeastern Quebec will be facing decrease in flood frequency. Results indicate that 40%-60% of Canada’s 100 most populated cities including many prominent cities such as Toronto and Montreal are high at risk of increased riverine flooding under climate change.
Slobodan P. Simonovic is Professor of Civil and Environmental Engineering at the University of Western Ontario and Director of Engineering Studies at ICLR. Prof. Simonovic is globally recognized for his unique interdisciplinary research in Systems Analysis and has over 500 professional publications and three major textbooks. Prof. Simonovic was inducted to the Canadian Academy of Engineering in June of 2013.
This document is a thesis submitted by Niraj Lamichhane to Youngstown State University in partial fulfillment of the requirements for a Master of Science degree in engineering. The thesis investigates the prediction of travel time and development of flood inundation maps for a flood warning system on the Grand River in Ohio, including scenarios involving ice jams. Hydraulic modeling was performed using HEC-RAS and HEC-GeoRAS to simulate floods, generate inundation maps, and assess the impacts of different elevation data resolutions and Manning's roughness values. The study found that coarser elevation data led to overprediction of travel time and inundated areas compared to LiDAR data integrated with field surveys.
This study developed a rainfall-runoff model using HEC-HMS to simulate runoff from Irwin Creek watershed in Charlotte, North Carolina under current and future climate change precipitation scenarios. The model was calibrated and validated using stream gauge data and produced comparable results. Simulation of design storms indicated that an 18% increase in storm depth due to climate change could increase peak discharge by 43%. The study concluded HEC-HMS is a useful tool for watershed modeling and that future flood management should consider potential impacts of climate change.
Objectives:
Develop a replicable integrated model (methodology) for evaluating the extent and development potential of renewable (non-renewable) groundwater resources in arid lands, with the Eastern Desert of Egypt as a pilot site.
The model will be replicable for similar arid areas; North of Sudan, Tibesty, Yemen, and Saudi Arabia.
Building national capacities.
This document provides information about a training module on processing stream flow data organized by the Central Training Unit of the Central Water Commission in India. The training is intended for engineers involved in reviewing, analyzing, and processing stream flow data. The document includes details about the module such as its objectives, key concepts, session plan, and evaluation suggestions. It aims to help participants learn how to analyze and process gauge-discharge data, sediment data, water quality data, bed material data, and meteorological data through methods like consistency checks and reliability assessments.
This document provides information and instructions for processing stream flow data collected at hydrological observation stations in India. It discusses the importance of processing data for correctness and consistency before publication. Key aspects of data processing include checking data forms for accuracy, developing stage-discharge relationships from gauge readings and discharge measurements, applying corrections, and ensuring consistency between station records over time. The document outlines methods for checking stage and discharge data, developing rating curves, identifying potential errors, applying adjustments, and analyzing processed data through various hydrological techniques. The overall aim is to produce reliable hydrological records of water quantity, quality and sediment levels at observation stations.
This work report summarizes Amaljit Bharali's contributions in 2016 related to water resources, hydrology, and flood modelling in Northeast India. Major contributions included operational work on a Flood Early Warning System including hydrological modelling. Other work included database development, field surveys, and training. Research activities included urban flood modelling in Shillong and hydraulic modelling of flood prone rivers. Publications and conferences were also listed.
The document describes a training module on analyzing rainfall data. It includes sessions on checking data homogeneity, computing basic statistics, fitting frequency distributions, and deriving frequency-duration and intensity-duration-frequency curves. Exercises are provided for trainees to practice analyzing monthly and daily rainfall series, fitting distributions, and deriving curves for different durations and return periods. Case studies from India are referenced as examples throughout the training material.
This document provides guidance on analyzing rainfall data. It discusses checking data homogeneity, computing basic statistics, developing annual exceedance rainfall series, fitting frequency distributions, and deriving frequency-duration and intensity-duration-frequency curves. The document includes examples demonstrating how to calculate statistics for a monthly rainfall series and develop frequency curves. It also outlines computational procedures and examples for depth-area-duration analysis. Key steps in the rainfall data analysis process are presented along with example results and figures.
23 - NRSC - Remote Satellite Imgae - Hydrology and Water Management-Sep-17indiawrm
This document discusses the use of satellite remote sensing for hydrology and water management applications. It provides examples of how satellite data can be used to monitor surface water bodies, snow cover, soil moisture, precipitation and other variables. It also describes how satellite data has been used to assess irrigation potential, monitor irrigation tanks and reservoirs, model hydrology and forecast flooding. The satellite data provides valuable information to support water resources management.
The document describes a hazard mitigation planning project for the Seward Bear Creek Flood Service Area near Seward, Alaska. The project team updated the local hazard mitigation plan by evaluating natural hazards in the area like flooding, developing damage estimates using Hazus software, and considering scenarios for climate change and land use change. They encountered challenges with data collection and modeling hazards in the Alaskan environment. The team used LiDAR data and user-defined facilities in Hazus to model flooding risks and assess climate change impacts on glacially-fed rivers. They also adapted 2D alluvial fan flood models and tsunami maps into Hazus for risk assessments.
1 - MoWR - Overview of HP-III Workshop-15th Sep 2014indiawrm
This document summarizes the key achievements and objectives of the Hydrology Project in India across its three phases. The project aims to develop a standardized national water resources monitoring and information system to improve water resources planning and management. Key achievements of phase II included upgrading monitoring networks, developing web-based data management and tools for planning, and conducting studies on groundwater management and water quality issues. Phase III will further develop these systems nationwide and introduce tools for flood forecasting, reservoir operation, and assessing climate change impacts. The ultimate goal is to establish a permanent water resources information coordination center.
The document discusses using earth observation (EO) data to monitor freshwater quality and quantity. It provides an overview of current capabilities to derive water quality parameters like chlorophyll-a and suspended sediments from satellites. Methods are described to classify different optical water types and select the best algorithm for each type. Ongoing work includes developing a global lakes observatory to monitor 1,000 lakes using EO and integrating data from multiple platforms and sources. EO shows potential to improve freshwater monitoring for research and management.
DSD-INT 2023 Fast compound flood modelling using reduced complexity model - d...Deltares
Presentation by Roel de Goede (Deltares, Netherlands) at the Symposium on Emulating 2D flood modelling, during the Delft Software Days - Edition 2023 (DSD-INT 2023). Wednesday, 27 September 2023, Delft.
DSD-INT 2023 Fast compound flood modelling using reduced complexity model - d...
Presentation_Niraj_Final
1. Department of Civil/Environmental and Chemical Engineering
Youngstown State University
Master’s Thesis Defense
April 25, 2016
Niraj Lamichhane
Committee:
Dr. Suresh Sharma
Dr. Tony Vercellino, and
Dr. Bradley A. Shellito
Prediction of Travel Time and Development of Flood
Inundation Maps for Flood Warning System Including Ice
Jam Scenario : A Case Study of the Grand River, Ohio
3. Background/Need of study
Flood/Flood Warning System:
• Most common form of natural disaster
• ~ 520 millions people affected every year worldwide
• Property loss ~ 50 - 60 billions USD
• In US: loss of 140 people lives/year & property loss ~ 8 billions USD
• Ice jam flooding - common event in Northern region of the US that
result the loss of lives and millions’ dollar worth properties
• Flood warning system - warn people sufficient time ahead
3April 25, 2016
4. Background
General Terms
No Flood
2006 Flood
Location: ECKART America Corporation, 830 E Erie St., Painesville OH
Source : USGS Report 2006 Flood
Flood travel time :
Time taken by flood to travel
from one place to another
Inundation area :
The areas covered by flood during
peak flooding time
cont.
4April 25, 2016
5. I. To quantify the effects of resolution of elevation datasets and
Manning’s roughness in travel time and inundation area prediction
II. To develop an approach for flood warning system and generate flood
inundation maps for the Grand River
III. To assess the potential impacts in river stage and hydraulic structures
due to winter ice cover/ice jam
Flood maps could be uploaded online.
Objectives
5April 25, 2016
6. Theoretical Description
HEC-RAS
(Hydraulic Engineering Center - River Analysis System)
Widely accepted hydraulic tool, developed by United States Army Corps
of Engineers (USACE)
Two types of simulation in HEC-RAS
• Steady Flow
• Unsteady Flow
Chapter 2
6April 25, 2016
7. Theoretical Description
Unsteady flow
• Flow velocity changes with
time
Continuity Equation
Momentum Equation
Steady flow
• Flow velocity do not change with
time
Energy Equation
cont. Chapter 2
7April 25, 2016
8. • Located in Northeastern region of Ohio
• Watershed Area : 705 mi2
• Length of Grand River : 102.7 mi
Materials
Study Area:
Map of USA Grand River Watershed
Grand River Outlet
City of Painesville
Harpersfield
Ohio
Chapter 2
8April 25, 2016
9. • Harpersfield to mouth at Fairport Harbor: 32.2 mi. in length
• Three major tributaries: Mill, Paine, and Big Creek
Materials
Study Area:
cont.
Source: Google Map
Harpersfield
City of
Painesville
Fairport
Harbor
04211820
04212100
Chapter 2
9April 25, 2016
10. Methodology
Collection of input data
Preparation of geospatial
data in HEC-GeoRAS
Simulation in HEC-RAS
Flood maps generation in
HEC-GeoRAS
1. Pre -processing
2. Processing
3. Post -processing
Overall Methodology
Chapter 2Objective I
10April 25, 2016
11. Methodology cont.
1. Pre-processing: Collection of input data
• Elevation datasets (LiDAR, 10m DEM, 30m DEM)
• Detail topographic survey of the river
• Land cover
• Discharge/Stage
• Aerial photographs
• Detail drawing of bridges
Collection of input data
Preparation of geo-spatial
data in HEC-GeoRAS
Simulation in
HEC-RAS
Flood maps generation in
HEC-GeoRAS
Chapter 2Objective I
11April 25, 2016
LiDAR – Light Detection and Ranging
DEM – Digital Elevation Model
Process for obtaining LiDAR data
12. Methodology cont.
1. Pre-processing: Geo-spatial data preparation
Collection of input data
Preparation of geo-spatial
data in HEC-GeoRAS
Simulation in
HEC-RAS
Flood maps generation in
HEC-GeoRAS
• Create geo-spatial data (river, cross sections, bank
stations, flow path) for all datasets (LiDAR DEM, 10m
DEM, and 30m DEM).
• Export to HEC-RAS
Chapter 2Objective I
Geo-spatial data preparation in HEC-GeoRAS
12April 25, 2016
Surveyed points
Points where cross section
elevation are compared for
various elevation datasets
13. Methodology cont.
2. Processing: Simulation in HEC-RAS
• Import datasets from HEC-GeoRAS
Collection of input data
Preparation of geo-spatial
data in HEC-GeoRAS
Simulation in
HEC-RAS
Flood maps generation in
HEC-GeoRAS
LiDAR DEM
10m DEM
30m DEM
LiDAR with survey
10m DEM with survey
30m DEM with survey
• Surveyed in 77
cross sections
• Integration of survey data in all
datasets.
• Elevation datasets for modeling
Chapter 2Objective I
13April 25, 2016
14. Methodology cont.
2. Processing: Simulation in HEC-RAS
Collection of input data
Preparation of geo-spatial
data in HEC-GeoRAS
Simulation in
HEC-RAS
Flood maps generation in
HEC-GeoRAS
• Apply boundary condition (discharge, stage data, etc.)
• Run simulation for 10, 50, 100, 500 return floods and
2006 floods using6 datasets
• Export data to HEC-GeoRAS
Chapter 2Objective I
HEC-RAS Model
D/S streamgage station
U/S streamgage station
04212100
04211820
14April 25, 2016
15. Collection of input data
Preparation of geo-spatial
data in HEC-GeoRAS
Simulation in
HEC-RAS
Flood maps generation in
HEC-GeoRAS
Methodology cont.
2. Processing: Simulation in HEC-RAS
Calibration/Validation
• Manning’s roughness - only variable in HEC-RAS
• Calibrated/validated for 8 events between 1996-1998 for
stage and discharge
• Model evaluation - Using 4 statistical criteria
• Calibrated roughness value : 0.035 - channel, 0.15 - flood plain
Chapter 2Objective I
15April 25, 2016
R2=0.99 R2=0.99
16. Methodology cont.
Collection of input data
Preparation of geo-spatial
data in HEC-GeoRAS
Simulation in
HEC-RAS
Flood maps generation in
HEC-GeoRAS
3. Post-processing: Flood maps generation
• Hydraulic computations imported from HEC-RAS
• Flood maps generation using HEC-GeoRAS
Chapter 2Objective I
Comparison of predicted flood inundation maps for 2006 Flood when different elevation datasets were used
Area in red color
covers all the area
of other colors.
16April 25, 2016
17. Results & DiscussionsObjective I
Effect of topography (Resolution of elevation datasets) :
• Cross section greatly vary for different resolution datasets
• 10m DEM - better in channel than LiDAR
Chapter 2
• Topographic survey performed.
• LiDAR with integration of survey
data was taken for comparison and
generating maps
17April 25, 2016
18. Results & DiscussionsObjective I
Effect of topography: Flood travel time (to City of Painesville)
• Travel time – calculated for 5 different floods using 6 datasets
Travel time difference:
Chapter 2
Note: Comparison was done with the result obtained from LiDAR with survey
• % difference in travel
time was highest for
coarse elevation
dataset.
18April 25, 2016
11.03%-15.01%1.19%-3.35% 10.24%-11.75%
3.67%-4.87%8.73%-10.52%
19. Results & DiscussionsObjective I
Effect of Topography: Inundation area
• Inundation maps – generated for 5 different floods using 6 datasets
Inundation area difference
Chapter 2
Note: Comparison was done with the result obtained from LiDAR with survey data
• % difference in
inundation area is
highest for coarse
elevation dataset
19April 25, 2016
32.56%-44.52%3.55%-7.80% 8.08%-15.48%
17.36%-18.71%10.85%-18.71%
20. Results & DiscussionsObjective I
Effect of Manning’s roughness “n” : Flood travel time (Table 2-6)
Chapter 2
In channel sections
• 0.035, 0.030, 0.025, and 0.020
• Varied in channel & constant in
flood plains
• Travel time: highest for higher
“n” (0.035)
• Decrement in travel time:
7.48% - 22.35%
In flood plains
• 0.15, 0.10, 0.09, and 0.7
• Varied in flood plains & constant
in channel
• Travel time: lowest for higher
“n” (0.15)
• Increment in travel time:
0.60% - 3.45%
20April 25, 2016
21. Results & DiscussionsObjective I
Effect of Manning’s roughness: Inundation area
Chapter 2
In channel section In flood plain
Note: Comparison was done with the result obtained when roughness value is
0.035 in channel & 0.15 in flood plain
• The sensitivity of Manning’s roughness - found to be more in channel
than in floodplain
21April 25, 2016
22. Results & DiscussionsObjective I
Effect of Manning’s roughness: Inundation area
Chapter 2
Difference in predicted inundation area for various sets of Manning’s roughness values
0.020_0.15
0.025_0.15
0.030_0.15
0.035_0.07
0.035_0.09
0.035_0.10
0.035_0.15
World Imagery
Ü
22April 25, 2016
23. To develop an approach for flood warning system and generate inundation
maps for various flood stages in the Grand River
Objective II
23April 25, 2016
24. MethodologyObjective II Chapter 3
Overall Flood Warning Approach
Development of
hydraulic model
Calibrate steady model
and run the simulation
Preparation of digital
flood inundation maps
Installation of siren
system
Evacuation time
Recommendation for better
warning system
24April 25, 2016
25. Results & DiscussionsObjective II Chapter 3
Rating curve
for streamgage at City of Painesville
Validation of rating curve
Steady flow : Calibrated using high-water marks of 2006 flood
calibration
Rating curve : Developed using 75% exceedance flow of 1988-2005
Q=166.67H1.79
Validation : 2006-2015
R2=0.93
25April 25, 2016
26. Results & DiscussionsObjective II Chapter 3
Calculation of travel time & development of flood-inundation maps
• Flood travel time for 12 different flood stages
• Developed digital inundation maps can be uploaded online.
( E.g. http://water.weather.gov/ahps/inundation.php )
Travel time and inundation area for various flood stages
26April 25, 2016
27. Results & DiscussionsObjective II Chapter 3
Flood damages along the Grand River
• Major affected places: Hidden-Valley Park near S. Madison Rd, Helen
Hazen Wyman Park, Mill Stone Drive, Steel Ave. and Grand River Ave,
Kiwanis Recreation Park, Western Reserve & Fairport Harbor Yacht
Clubs, Ram Island, Hidden Harbor Drive area, Fairport Harbor
• Affected bridges: Bridges at Vrooman Rd., Lakeland Freeway &
Fairport Rd. Vrooman Bridge - more critical (water level increased>3 ft
above road level) from the analysis as well as from the historical data
• More than 100 houses, many roads and parks are susceptible to 500 year
return period or greater floods
27April 25, 2016
28. Results & DiscussionsObjective II Chapter 3
Flood inundation map for 19.35 ft stage (2006 flood) near City of Painesville
S.MadisonRd
Huntington Road
Western Reserve &
Fairport Yacht Club
28April 25, 2016
29. Results & DiscussionsObjective II Chapter 3
1D and 2D animation of 2006 flood in the Grand River
Flood Animation in HEC-RAS
29April 25, 2016
30. Results & DiscussionsObjective II Chapter 3
Water level at various bridges for 19.35 ft flood stage (2006 Flood)
30April 25, 2016
31. Results & DiscussionsObjective II Chapter 3
Recommendation for more effective automated flood warning system
• Reestablish discontinued streamgage (04211820) at Harpersfield
• Establish new streamgages for major creeks like Mill, Paine and Big
Creeks
• Install automated warning system containing a rain gauge, a
Geostationary Operational Environmental Satellite (GOES) transmitter,
a Radio Frequency transmitter using Automated Local Evaluation in
Real Time (ALERT) protocol and a voice modem
31April 25, 2016
32. Objective III
To assess the potential impacts in river stage and hydraulic structures due
to winter ice cover/ice jam
32April 25, 2016
33. Objective III
Near Fairport Harbor
Near Fairport Rd. bridge
33April 25, 2016
Objective III Chapter 4
Historical
Source: CRREL Ice Jam Database, USACE (2015)
34. 34
MethodologyObjective III Chapter 4
Overall Approach
April 25, 2016
Historical analysis and
estimate ice thickness
Prepare input data and run the
simulation for various
scenarios
Compare and analyze results
of those scenarios
Generate flood inundation
maps
Maximum estimated ice thickness= 10 inches for
1977/1978 period
Where
ti = thickness of ice
𝛼 = coefficient for wind and snow cover
AFDD = Accumulated Freezing Degree Days
Ta = Temperature of air
Historical analysis and ice thickness estimation
𝑡𝑖=𝛼√𝐴𝐹𝐷𝐷
𝐴𝐹𝐷𝐷 = (32−𝑇 𝑎)
Modified Stefan’s equation
35. MethodologyObjective III Chapter 4
Ice jam simulation was run for 3 different scenarios using 5 winter discharge
a) without ice cover & jam with bridges
b) with ice cover and ice jam with bridge
c) with ice cover & ice jam but no bridges
35April 25, 2016
cont.
5 different winter discharge values
a) 25 Percentile b) 50 Percentile
c) 75 Percentile d) 90 Percentile
e) 100 Percentile
36. Results & DiscussionsObjective III Chapter 4
Relationship discharge, AFDD & precipitation
• Increase in river discharge due to ice melting not due to precipitation.
Increase in discharge
1976/1977 1984/1985
36April 25, 2016
37. Results & DiscussionsObjective III Chapter 4
Comparison of water level
• Overall increase in river stage (~2 ft.) due to ice cover/jam
• Increase in stage was higher mostly at the upstream part of bridge (Table 4-6)
Longitudinal profile of bridge at South Madison road Longitudinal profile of bridge at Blair Road
Effect of bridge:
Increase in river stage by 4.16 ft Increase in river stage by 1.21 ft
37April 25, 2016
4.16 ft
1.21 ft
38. Results & DiscussionsObjective III Chapter 4
Vrooman bridge - more crucial - water level crossed deck level
Affected several times - 2007, 2010, 2011, and 2014
Large volume of ice blocks in jam location - can result flooding when it
melts
38April 25, 2016
39. Results & DiscussionsObjective III Chapter 4
Flood inundation maps - Generated for 5 different winter discharge
Increase in inundation area for all return period floods
22 % for 100 percentile & 52% for 25 percentile
Flood plain map for highest winter flow (100 percentile flow)
39April 25, 2016
40. Conclusions/Recommendations Chapter 5
• Travel time and inundation area: high for coarse elevation datasets
• Channel is better represented by 10m DEM than by LiDAR data
• Manning’s roughness – more sensitive in channel than in flood plains
• > 100 houses, many roads, parks and bridges affected by 500 years return
period flood or the higher ones
• Significant effects of ice cover/jam observed in river stage and flood
• Installation of siren system in suitable location to warn people
40April 25, 2016
41. Conclusions/Recommendations Chapter 5
• Results can be uploaded in National/Regional Portal System
• Further calibration and validation with detail recording of high-water
marks and ice jam recordings might help develop more reliable model
41April 25, 2016
42. Acknowledgements
Advisor: Dr. Suresh Sharma
Committee Members: Dr. Tony Vercellino and Dr. Bradley A. Shellito
• Dr. Anwarul Islam, Department Chair
• Ohio Sea Grant – for providing research grant
• Christopher R. Goodel
• My parents and families
• Friends and well wishers: Binod, Kamal, Shobha, Aashish, Janga, Bhishan, Sabin,
Sanjay, Abhijeet and many others
• Department of Civil/Environmental and Chemical Engineering
April 25, 2016