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Irene Garousi-Nejad

Utah State University | Graduate Research Assistant

Subject Areas: Hydrology, Water Resources

 Recent activity

ABSTRACT:

Flood inundation remains stubbornly challenging to map, model, and forecast with high precision for decision making because it requires a detailed
representation of the hydrologic and hydraulic processes, which are computationally demanding, and data limited. Recently, an empirical approach,
Continental-Scale Flood Inundation Mapping (CFIM), having fewer data demands and perhaps offering a more practical alternative, has been
presented as a scientific workflow where a Height Above Nearest Drainage (HAND) terrain model along with the National Water Model (NWM)
forecast discharge is employed for near real-time flood inundation mapping. In February 2017, a record flood occurred on the Bear River in Box
Elder County due to rapid snowmelt and rain on snow. In this study, we evaluated the CFIM method over the reach of the Bear River where this
flooding occurred. We evaluated the performance of the CFIM in terms of its accuracy in representing flooded and non-flooded areas when
comparing the results with flood inundation observed in imagery from the high-resolution Planet CubeSat RapidEye Satellites. The results indicate
that there were differences between CFIM flood inundation predictions and flooded area recorded by CubeSat Imagery. We used evaluation of these
differences to address challenges of CFIM and present a set of improvements to overcome some of the limitations and advance the outcome of
CFIM. The improvements utilize (1) the high-resolution (1:24,000) National Hydrography Dataset (NHD) to provide an obstacle-removed and
hydrologically conditioned topography, and (2) a higher-resolution Digital Elevation Model (DEM) dataset available for this area. The results indicate
that differences between CFIM flood inundation predictions and flooded area recorded by CubeSat Imagery were attributed to differences in observed
and forecast discharges, but also notably due to shortcomings in the HAND method and the derivation of HAND from the national elevation dataset
as implemented in CFIM. Examination of the causes for these differences has led us to develop proposed improvements to the CFIM methods,
which in this study were evaluated only for this single location. Nonetheless, the proposed improvements have the potential, following further
evaluation, to improve the broad application of the CFIM methodology.

PLAIN LANGUAGE SUMMARY:
Flood inundation is difficult to map, model, and forecast because of the data needed and computational demand. Recently an approach based on
the Height Above Nearest Drain (HAND) derived from a digital elevation model along with using the National Water Model forecasts has been
suggested, for both flood mapping and obtaining reach hydraulic properties. This approach was tested for a recent snowmelt flood on the Bear River
and compared to inundated area mapped using CubeSat satellite imagery. Initial differences found were reduced by addressing shortcomings in the
terrain analysis evaluation of HAND both in terms of the digital elevation model resolution and method used to condition the digital elevation model
using streamline information.

Slides for AGU Fall Meeting 2018 presentation H34G-08 at Washington D.C., December 12, 2018
Session: H34G: Research, Development, and Evaluation of the National Water Model and Facilitation of Community Involvement II

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ABSTRACT:

This presentation is provided for the attendees of the Global Academy program at Utah State University in summer 2018 and talks about HydroShare, a web-based collaboration environment to enable more rapid advances in hydrologic understanding through collaborative data sharing, analysis, and modeling.

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ABSTRACT:

The normals are baseline datasets describing average monthly and annual conditions over the most recent three full decades. They are our most popular datasets. The current PRISM normals cover the period 1981-2010. This figure illustrates the 800m (18-350MB per data file; 5MB per full-size image) annual precipitation data downloaded from http://prism.nacse.org/normals/.

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ABSTRACT:

My name is Irene Garousi-Nejad. I am a graduate student in Civil and Environmental Engineering at Utah State University working with David G. Tarboton. My research is exploring options for improving flood and water supply forecasting in the Western United States, such as the Great Salt Lake and Colorado River basins, using physically-based distributed hydrologic modeling.

"Models are undeniably beautiful; however, they may have their hidden vices. The question is not only whether they are good to look at, but whether we can live happily with them" -- A. Kaplan, 1964 --

Outside of academics, I enjoy mountain climbing, playing and listening to music, and making Papier-Mache art.
You can contact me at: i.garousi@aggiemail.usu.edu

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ABSTRACT:

Population growth and socioeconomic changes in developing countries over the past few decades have created sever stress on the available water resources across the world, particularly in semiarid regions, such as Utah. Hence, the optimal management of water resources is imperative. This study aimed to explore opportunities to provide the optimal reservoir operation rules for the Hyrum Reservoir, located on the Little Bear River in Utah, considering the reliability and vulnerability as the objective functions. Solving the multi-objective (herein two-objective) problem contributed us to investigate the interaction between reliability and vulnerability in this project. Modified Firefly Algorithm (MFA) was implemented as the optimization tool and three different problems, namely (1) single objective problem with reliability as the objective function, (2) single objective problem with vulnerability as the objective function, and (3) multi-objective problem with reliability and vulnerability as the objective functions, were solved. The results demonstrate the trade-off between the two objectives in the multi-objective problem. It also manifest that considering a multi-objective problem provide solutions whose the reliability and vulnerability values are within the upper and lower ranges calculated in the single objective problems.

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 Contact

Resources
All 0
Collection 0
Composite Resource 0
Generic 0
Geographic Feature 0
Geographic Raster 0
HIS Referenced Time Series 0
Model Instance 0
Model Program 0
MODFLOW Model Instance Resource 0
Multidimensional (NetCDF) 0
Script Resource 0
SWAT Model Instance 0
Time Series 0
Web App 0
Generic Generic

ABSTRACT:

This proposal represents the need of using GIS as a tool to prepare inputs data of WRF-Hydro hydrologic model to simulate and predict streamflow in a small watershed in the GSL. WRF-Hydro, developed by National Center for Atmospheric Research ( NCAR), is the underlying hydrologic model implemented in National Water Model (NWM). The goal of this work is to use WRF-Hydro for a small watershed and compare the outputs with those of NWM.

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Generic Generic
NWM_USGS_retrieval
Created: Dec. 6, 2016, 5:13 p.m.
Authors: Irene Garousi-Nejad

ABSTRACT:

In hydrology, water data and specifically streamflow, has been an interesting issue, and historical observations of streamflow are collected by the United States Geological Survey (USGS). Additionally, several hydrologic models are used to produce forecasts of streamflow conditions in the future. Among efforts to forecast streamflow, the most recent endeavors to predict streamflow have led to the development, launch, and unveiling of America’s first National Water Model (NWM) on August 16, 2016. This model forecasts more precise, detailed, frequent, and expanded water information that can be utilized by various communities to improve water-related decisions. However, researchers who aim to use NWM forecast data may face some problems due to the retrieval, management, and analysis of these data. To cope with these challenges, a retrieval code (NWM_USGS_retrieval) that facilitates and automates the process of querying and retrieving data was generated in this project using the Python scripting language and demonstrated in a Jupyter IPython Notebook.

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Generic Generic

ABSTRACT:

Population growth and socioeconomic changes in developing countries over the past few decades have created sever stress on the available water resources across the world, particularly in semiarid regions, such as Utah. Hence, the optimal management of water resources is imperative. This study aimed to explore opportunities to provide the optimal reservoir operation rules for the Hyrum Reservoir, located on the Little Bear River in Utah, considering the reliability and vulnerability as the objective functions. Solving the multi-objective (herein two-objective) problem contributed us to investigate the interaction between reliability and vulnerability in this project. Modified Firefly Algorithm (MFA) was implemented as the optimization tool and three different problems, namely (1) single objective problem with reliability as the objective function, (2) single objective problem with vulnerability as the objective function, and (3) multi-objective problem with reliability and vulnerability as the objective functions, were solved. The results demonstrate the trade-off between the two objectives in the multi-objective problem. It also manifest that considering a multi-objective problem provide solutions whose the reliability and vulnerability values are within the upper and lower ranges calculated in the single objective problems.

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Geographic Feature (ESRI Shapefiles) Geographic Feature (ESRI Shapefiles)
iGarousi_homewatershed
Created: April 10, 2017, 4:26 p.m.
Authors: Irene Garousi-Nejad

ABSTRACT:

My name is Irene Garousi-Nejad. I am a graduate student in Civil and Environmental Engineering at Utah State University working with David G. Tarboton. My research is exploring options for improving flood and water supply forecasting in the Western United States, such as the Great Salt Lake and Colorado River basins, using physically-based distributed hydrologic modeling.

"Models are undeniably beautiful; however, they may have their hidden vices. The question is not only whether they are good to look at, but whether we can live happily with them" -- A. Kaplan, 1964 --

Outside of academics, I enjoy mountain climbing, playing and listening to music, and making Papier-Mache art.
You can contact me at: i.garousi@aggiemail.usu.edu

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Generic Generic
30-yr Normal Precipitation: Anual
Created: May 11, 2017, 6:24 a.m.
Authors: Irene Garousi-Nejad

ABSTRACT:

The normals are baseline datasets describing average monthly and annual conditions over the most recent three full decades. They are our most popular datasets. The current PRISM normals cover the period 1981-2010. This figure illustrates the 800m (18-350MB per data file; 5MB per full-size image) annual precipitation data downloaded from http://prism.nacse.org/normals/.

···
Composite Resource Composite Resource

ABSTRACT:

This presentation is provided for the attendees of the Global Academy program at Utah State University in summer 2018 and talks about HydroShare, a web-based collaboration environment to enable more rapid advances in hydrologic understanding through collaborative data sharing, analysis, and modeling.

···
Composite Resource Composite Resource

ABSTRACT:

Flood inundation remains stubbornly challenging to map, model, and forecast with high precision for decision making because it requires a detailed
representation of the hydrologic and hydraulic processes, which are computationally demanding, and data limited. Recently, an empirical approach,
Continental-Scale Flood Inundation Mapping (CFIM), having fewer data demands and perhaps offering a more practical alternative, has been
presented as a scientific workflow where a Height Above Nearest Drainage (HAND) terrain model along with the National Water Model (NWM)
forecast discharge is employed for near real-time flood inundation mapping. In February 2017, a record flood occurred on the Bear River in Box
Elder County due to rapid snowmelt and rain on snow. In this study, we evaluated the CFIM method over the reach of the Bear River where this
flooding occurred. We evaluated the performance of the CFIM in terms of its accuracy in representing flooded and non-flooded areas when
comparing the results with flood inundation observed in imagery from the high-resolution Planet CubeSat RapidEye Satellites. The results indicate
that there were differences between CFIM flood inundation predictions and flooded area recorded by CubeSat Imagery. We used evaluation of these
differences to address challenges of CFIM and present a set of improvements to overcome some of the limitations and advance the outcome of
CFIM. The improvements utilize (1) the high-resolution (1:24,000) National Hydrography Dataset (NHD) to provide an obstacle-removed and
hydrologically conditioned topography, and (2) a higher-resolution Digital Elevation Model (DEM) dataset available for this area. The results indicate
that differences between CFIM flood inundation predictions and flooded area recorded by CubeSat Imagery were attributed to differences in observed
and forecast discharges, but also notably due to shortcomings in the HAND method and the derivation of HAND from the national elevation dataset
as implemented in CFIM. Examination of the causes for these differences has led us to develop proposed improvements to the CFIM methods,
which in this study were evaluated only for this single location. Nonetheless, the proposed improvements have the potential, following further
evaluation, to improve the broad application of the CFIM methodology.

PLAIN LANGUAGE SUMMARY:
Flood inundation is difficult to map, model, and forecast because of the data needed and computational demand. Recently an approach based on
the Height Above Nearest Drain (HAND) derived from a digital elevation model along with using the National Water Model forecasts has been
suggested, for both flood mapping and obtaining reach hydraulic properties. This approach was tested for a recent snowmelt flood on the Bear River
and compared to inundated area mapped using CubeSat satellite imagery. Initial differences found were reduced by addressing shortcomings in the
terrain analysis evaluation of HAND both in terms of the digital elevation model resolution and method used to condition the digital elevation model
using streamline information.

Slides for AGU Fall Meeting 2018 presentation H34G-08 at Washington D.C., December 12, 2018
Session: H34G: Research, Development, and Evaluation of the National Water Model and Facilitation of Community Involvement II

···