A New 1D/2D Coupled Modeling Approach for a Riverine‐Estuarine System Under Storm Events: Application to Delaware River Basin

Bakhtyar, Roham; Maitaria, Kazungu; Velissariou, P.; Trimble, B.; Mashriqui, Hassan; Moghimi, Saeed; Abdolali, Ali; Westhuysen, A. J. Van der; Ma, Zhifeng; Clark, Edward P.; Flowers, T.

doi:10.1029/2019jc015822

Cited by 50 publications

(45 citation statements)

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“…Decoupling of different shallow water processes, where hydrodynamics and ocean waves are modeled stand-alone or in a one-way fashion, introduces error in the models' outputs. Note that the necessity of dynamic coupling between atmospheric, wave, surge, and hydrological model is recognized; therefore, a tremendous effort across modeling groups is in place (Moghimi et al 2020;Bakhtyar et al 2020), leading to improvement in the accuracy of each individual model in the coupled system. On the other hand, the observations including stationary observations, along satellite tracks or radar field snapshots carry errors and uncertainties, mostly due to device accuracy, calibration, and post-processing algorithm.…”

Section: Model and Observation Sources Of Errormentioning

confidence: 99%

Evaluating the accuracy and uncertainty of atmospheric and wave model hindcasts during severe events using model ensembles

Abdolali

Westhuysen

et al. 2021

Ocean Dynamics

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Various uncertainties exist in a hindcast due to the inabilities of numerical models to resolve all the complicated atmosphere-sea interactions, and the lack of certain ground truth observations. Here, a comprehensive analysis of an atmospheric model performance in hindcast mode (Hurricane Weather and Research Forecasting model—HWRF) and its 40 ensembles during severe events is conducted, evaluating the model accuracy and uncertainty for hurricane track parameters, and wind speed collected along satellite altimeter tracks and at stationary source point observations. Subsequently, the downstream spectral wave model WAVEWATCH III is forced by two sets of wind field data, each includes 40 members. The first ones are randomly extracted from original HWRF simulations and the second ones are based on spread of best track parameters. The atmospheric model spread and wave model error along satellite altimeters tracks and at stationary source point observations are estimated. The study on Hurricane Irma reveals that wind and wave observations during this extreme event are within ensemble spreads. While both Models have wide spreads over areas with landmass, maximum uncertainty in the atmospheric model is at hurricane eye in contrast to the wave model.

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Section: Model and Observation Sources Of Errormentioning

confidence: 99%

Evaluating the accuracy and uncertainty of atmospheric and wave model hindcasts during severe events using model ensembles

Abdolali

Westhuysen

et al. 2021

Ocean Dynamics

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“…Therefore, the downstream boundary conditions are set to be the measured tidal data for all the cases. These effects are incorporated to the present model following the approach of by Brunner (2016b), JAICA (2009), and Bakhtyar et al (2020).…”

Section: Hydrodynamic Modelmentioning

confidence: 99%

“…Additionally, the present modelling approach takes into account the tidal effects at the sea outfall where the sea outfall is set as one of the boundaries with the stage computed using Admiralty tide tables (UKHO 2004) and an external model following the approach of JAICA ( 2009) and Bakhtyar et al (2020). As Kelani River is a tidally influenced river, Gunathilaka et al (2010) showed that the high tide during flood events would create the worst-case scenario in the vicinity of Nagalagam Street.…”

Section: Calibration Of Hydrodynamic Modelmentioning

confidence: 99%

Flood inundations and risk mapping in a tidal river: a case study for the Kelani River basin, Sri Lanka

Samarasinghe

Perera

Teo

et al. 2021

Preprint

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The downstream low-lying regions of the Kelani River, including some areas in the Districts of Colombo and Gampaha, Sri Lanka, frequently face severe inundations due to extreme rainfalls in the upper basin. In the present study, 1-D and 2-D hydrodynamic models in HEC-RAS have been used to examine the flood inundations in the tidal influenced Kelani River with ground observations and remote sensing. The HEC-RAS model has been used to produce a flood hazard map for hazard assessment in the lower Kelani River basin under different return periods. Furthermore, expected discharges for different return periods have been estimated using the hydrological model HEC–HMS with the updated intensity depth frequency curves for the Kelani River basin. Sentinel 1 imagery and field survey results are used to validate the simulated flood inundation extent; hydrodynamic model results validated against observed stage measurements; hydrological model validated against discharge measurements. Further, the validated hydrodynamic model showed the high capability to capture flow processes (Nash-Sutcliffe coefficient = 0.90 and Pearson coefficient of correlation = 0.95) along with inundation extent (Success Index = 0.90) of selected historical extreme events. Then the hydrological model is used to predict the flows of the Kelani River basin with a good agreement (Nash-Sutcliffe coefficient = 0.91 and the Pearson coefficient of correlation = 0.93). Finally, flood risk zoning for different return periods are developed based on the present model which would be a useful benchmark to design and implement flood control and mitigation measures for the river basin.

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“…It was found that the inclusion of riverine discharge into the SCHSIM model resulted in elevated water surface levels for more than 2 weeks after Hurricane Irene hit that area. Bakhtyar et al (2020b) executed a loose one-way coupling between the NWM and ADCIRC/WAVEWATCH III using the D-Flow FM hydraulic model to assess compound flooding impacts for tropical cyclones in the Delaware river basin and it was shown that water level predictions depend on a detailed representation of riverine discharge and elevated sea levels as well as detailed pressure and wind forcing (Bakhtyar et al, 2020b). Gori et al (2020) investigated the contribution of flooding due to river discharge along the North Carolina coast by loosely coupling the storm surge model ADCIRC, and the hydraulic model HEC-RAS by using ADCIRC output as downstream boundary conditions into the 1-D/2-D HEC-RAS hydraulic model in order to account for the effects of storm surge (Gori et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Developing a Modeling Framework to Simulate Compound Flooding: When Storm Surge Interacts With Riverine Flow

et al. 2021

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Compound flooding is a physical phenomenon that has become more destructive in recent years. Moreover, compound flooding is a broad term that envelops many different physical processes that can range from preconditioned, to multivariate, to temporally compounding, or spatially compounding. This research aims to analyze a specific case of compound flooding related to tropical cyclones where the compounding effect is on coastal flooding due to a combination of storm surge and river discharge. In recent years, such compound flood events have increased in frequency and magnitude, due to a number of factors such as sea-level rise from warming oceans. Therefore, the ability to model such events is of increasing urgency. At present, there is no holistic, integrated modeling system capable of simulating or forecasting compound flooding on a large regional or global scale, leading to the need to couple various existing models. More specifically, two more challenges in such a modeling effort are determining the primary model and accounting for the effect of adjacent watersheds that discharge to the same receiving water body in amplifying the impact of compound flooding from riverine discharge with storm surge when the scale of the model includes an entire coastal line. In this study, we investigated the possibility of using the Advanced Circulation (ADCIRC) model as the primary model to simulate the compounding effects of fluvial flooding and storm surge via loose one-way coupling with gage data through internal time-dependent flux boundary conditions. The performance of the ADCIRC model was compared with the Hydrologic Engineering Center- River Analysis System (HEC-RAS) model both at the watershed and global scales. Furthermore, the importance of including riverine discharges and the interactions among adjacent watersheds were quantified. Results showed that the ADCIRC model could reliably be used to model compound flooding on both a watershed scale and a regional scale. Moreover, accounting for the interaction of river discharge from multiple watersheds is critical in accurately predicting flood patterns when high amounts of riverine flow occur in conjunction with storm surge. Particularly, with storms such as Hurricane Harvey (2017), where river flows were near record levels, inundation patterns and water surface elevations were highly dependent on the incorporation of the discharge input from multiple watersheds. Such an effect caused extra and longer inundations in some areas during Hurricane Harvey. Comparisons with real gauge data show that adding internal flow boundary conditions into ADCIRC to account for river discharge from multiple watersheds significantly improves accuracy in predictions of water surface elevations during coastal flooding events.

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A New 1D/2D Coupled Modeling Approach for a Riverine‐Estuarine System Under Storm Events: Application to Delaware River Basin

Cited by 50 publications

References 50 publications

Evaluating the accuracy and uncertainty of atmospheric and wave model hindcasts during severe events using model ensembles

Evaluating the accuracy and uncertainty of atmospheric and wave model hindcasts during severe events using model ensembles

Flood inundations and risk mapping in a tidal river: a case study for the Kelani River basin, Sri Lanka

Developing a Modeling Framework to Simulate Compound Flooding: When Storm Surge Interacts With Riverine Flow

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