Comparative Effectiveness and Reliability of NEXRAD Data to Predict Outlet Hydrographs Using the GSSHA and HEC-HMS Hydrologic Models

Hamedi, Amirmasoud; Fuentes, Héctor R.

doi:10.1061/9780784479162.142

Cited by 8 publications

(6 citation statements)

References 6 publications

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“…SWMM was chosen because it has been approved by FEMA for hydrologic and hydraulic modeling and because it is among the most widely used models for modeling stormwater in urban settings and small watersheds (FEMA 2019a, b;Niazi et al 2017;Rossman 2015). Likewise, GSSHA was chosen because it includes the ability to model storm sewer networks, it is the only fully distributed model approved by FEMA for hydrologic modeling (FEMA 2019b), and because it has been found to provide more accurate simulations than semidistributed models such as SWMM (Moore et al 2017;Zhang and Shuster 2014), Hydrologic Engineering Center (HEC)-1 and HEC-Hydrologic Modeling System (HEC-HMS) (El Hassan et al 2013;Hamedi and Fuentes 2015;Niedzialek and Ogden 2003;Ogden et al 2011b;Paudel et al 2011), and Hydrological Simulation Program FORTRAN (HSPF) (Diaz-Ramirez et al 2010).…”

Section: Introductionmentioning

confidence: 99%

Modeling Storm Sewer Networks and Urban Flooding in Roanoke, Virginia, with SWMM and GSSHA

2021

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Modeling urban flooding is challenging because of complex spatial variations and interactions between precipitation, land cover, and drainage networks. This paper presents a case study of the development of two hydrology and hydraulics models-the semidistributed storm water management model (SWMM) and the fully distributed gridded surface/subsurface hydrologic analysis (GSSHA) model-to simulate the hydrologic response of two neighboring urban watersheds with large storm sewer networks in the city of Roanoke, Virginia. Both models were calibrated and validated for the two watersheds based on nine events (May-October 2018), and the models were assessed on their ability to replicate measured stream discharge and storm sewer flow depths. The findings from the study indicate that both models reasonably capture the observed hydrologic responses but that each model offers unique benefits. Overall, SWMM's value to the city is its ability to provide detailed information regarding the hydraulic conditions within the city's storm sewer network, whereas GSSHA's value to the city is its ability to predict the duration and spatial extent of flooding in two dimensions.

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Section: Introductionmentioning

confidence: 99%

Modeling Storm Sewer Networks and Urban Flooding in Roanoke, Virginia, with SWMM and GSSHA

2021

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“…Although it is shown that the combination of physical and numerical modeling provide better results compared to numerical analysis in engineering application, [8], [9], [10] however numerical modeling considering realistic values may lead to good results. This is especially valid for a complicated problem of rail dynamic analysis.…”

Section: Modeling Proceduresmentioning

confidence: 99%

An Investigation on the Effect of Rail Corrugation on Track Response

Fesharaki¹

2016

IJSEA

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Rail corrugation increases life cycle cost of both track and vehicle and is one of the main reasons of track and vehicle defects. To address this problem, this paper explores the effect of rail corrugation on track response. A Finite Element model developed to consider vehicle and track characteristics. Vehicle is a 10 degree of freedom mass-spring-dashpot model which can simulate vertical displacements and rotations. Rail is modeled as an Euler-Bernoulli beam with two degrees of freedom at each node which lies on discrete support to simulate sleeper and fastening system support. The total train-track matrices of mass, damping and stiffness have been formed. Solving the differential equations of motion in time domain for each time step results the response of track to train dynamic forces. A sensitivity analysis has been performed to explore the effect of different train and track parameters on rail displacement. The results of analyses show the effect of corrugation depth and wavelength as well as train speed and axle load on rail deflections and demonstrate the importance of each parameter in the studied range.

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“…In contrast to the shortcomings of rain gauge observations in representing spatial and temporal structures of precipitation, radar precipitation data provide a better capture of precipitation over spatial and temporal scales that are paramount to hydrologic applications [19]. Radars do not directly measure rainfall amounts but estimate the rainfall rate via an empirical relationship with the radar reflectivity factor.…”

Section: Introductionmentioning

confidence: 99%

“…One particular interest is tests on rainfall gauge data, radar data, and remote-sensed rainfall products (e.g., Tropical Rainfall Measuring Mission (TRMM)) using the Hydrologic Engineering Center's Hydrologic Modeling System (HEC-HMS) developed by the U.S. Army Corps of Engineers [30], which has been applied to a wide range of geographic areas for solving a variety of hydrological problems. Hamedi and Fuentes examined the effectiveness of Gridded Surface Subsurface Hydrologic Analysis (GSSHA) and HEC-HMS to predict outlet hydrographs in the Park City catchment basin in Utah using next-generation radar (NEXRAD) and gauge data as input and suggested the reliability of using NEXRAD [19]. Investigation over the Brays Bayou watershed in Houston proved simulated outflows from radar data to be accurate, and in some cases more accurate, than those from rain gauges [31].…”

Section: Introductionmentioning

confidence: 99%

Flood Simulation in South Carolina Watersheds Using Different Precipitation Inputs

Gao

Carbone

2018

Advances in Meteorology

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Flooding induced by extreme rainfall events causes tremendous loss of life and property and infrastructure failure. Accurate representation of precipitation, which has high variation in space and time, is critical to hydrologic model simulations and flood analyses. In this study, we examined responses of differently sized United States Geological Survey (USGS) hydrologic units to heavy precipitation using three different data sets. e first consists of rainfall observed at individual meteorological gauges. e second uses the National Centers for Environmental Prediction (NCEP) Environmental Modeling Center (EMC) 4 km gridded radar-estimated precipitation (GRIB) Stage IV data. e third one derives from the method we developed that blends gauge data with the spatial coverage of the Parameter-elevation Relationships on Independent Slopes Model (PRISM) data. We examined how two watersheds in South Carolina respond to the three different representations of heavy rainfall, using the Hydrologic Engineering Center's Hydrologic Modeling System (HEC-HMS) developed by the U.S. Army Corps of Engineers. We found that the latter two precipitation inputs that consider spatial representation of rainfall yielded similar performance and improved simulated streamflow as compared to simulation using rainfall observed at individual meteorological gauges. e method we developed overcomes the spatial sparsity of rain gauges required for interpolation and extends availability of precipitation surfaces. Our study advances the understanding of advantages and limitations of different precipitation products for flood simulation.

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Comparative Effectiveness and Reliability of NEXRAD Data to Predict Outlet Hydrographs Using the GSSHA and HEC-HMS Hydrologic Models

Cited by 8 publications

References 6 publications

Modeling Storm Sewer Networks and Urban Flooding in Roanoke, Virginia, with SWMM and GSSHA

Modeling Storm Sewer Networks and Urban Flooding in Roanoke, Virginia, with SWMM and GSSHA

An Investigation on the Effect of Rail Corrugation on Track Response

Flood Simulation in South Carolina Watersheds Using Different Precipitation Inputs

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