Coupling a land surface model with a hydrodynamic model for regional flood risk assessment due to climate change: Application to the Susquehanna River near Harrisburg, Pennsylvania

Modi, Parthkumar; Czuba, Jonathan A.; Easton, Zachary M.

doi:10.1111/jfr3.12763

Cited by 3 publications

(2 citation statements)

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“…Because of this, modelers should consider a range of ratios of channel width to resolution that would work for their study sites. To contextualize our findings with other hydrodynamic modeling studies, we found that channel width to DEM resolution ratio tends to range from 2 to 175 (Abu-Aly et al, 2014;Cobby et al, 2003;Cook & Merwade, 2009;Mason et al, 2003;Modi et al, 2022;Papaioannou et al, 2020). Mesh grid resolution was not clearly reported in the cited literature, thus we cannot comment on that ratio.…”

Section: Discussionsupporting

confidence: 77%

Lidar DEM and Computational Mesh Grid Resolutions Modify Roughness in 2D Hydrodynamic Models

Prior,

Michaelson,

Czuba

et al. 2024

Water Resources Research

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Topography and the computational mesh grid are fundamental inputs to all two‐dimensional (2D) hydrodynamic models, however their resolutions are often arbitrarily selected based on data availability. With the increasing use of drone technology, the end user can collect topographic data down to centimeter‐scale resolution. With this advancement comes the responsibility of choosing a resolution. In this study, we investigated how the choice of mesh grid and digital elevation model (DEM) resolutions affect 2D hydrodynamic modeling results, specifically water depths, velocities, and inundation extent. We made pairwise comparisons between simulations from a 2D HEC‐RAS model with varying mesh grid resolutions (1 and 2 m) and drone‐based lidar DEM resolutions (0.1, 0.25, 0.5, 1, and 2 m) over a 1.5 km reach of Stroubles Creek in Blacksburg, Virginia. The model was rerun for up to ±4% change in floodplain roughness to determine how the DEM and mesh grid changes relate to an equivalent change in roughness. We found that the modeled differences from resolution change were equivalent to altering floodplain roughness by up to 12% for depths and 44% for velocities. The largest differences in velocity were concentrated at the channel‐floodplain interface, whereas differences in depth occurred laterally throughout the floodplain and were not correlated with lidar ground point density. We also found that the inundation boundary is dependent on the DEM resolution. Our results suggest that modelers should carefully consider what resolution best represents the terrain while also resolving important riparian topographic features.

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Section: Discussionsupporting

confidence: 77%

Lidar DEM and Computational Mesh Grid Resolutions Modify Roughness in 2D Hydrodynamic Models

Prior,

Michaelson,

Czuba

et al. 2024

Water Resources Research

Self Cite

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“…Flood disasters are a major concern in many regions of the world due to the recent increase in the frequency of short-duration floods caused by climate change [1][2][3]. In particular, short-duration rainfall extremes cause the collapse of irrigation structures and residential facilities, the burial of agricultural land, and the deterioration of river water quality, resulting in socioeconomic losses [4,5].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Effects of Spatial Distributed Soil Properties and Soil Moisture Behavior on Hourly Streamflow Estimate through the Integration of SWAT and LSM

Lee,

Lim,

Kim

2024

Sustainability

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This study addresses the challenge of accurately estimating hourly flow and soil moisture by integrating the Soil and Water Assessment Tool (SWAT) with a Land Surface Model (LSM). Our approach enhances SWAT by incorporating spatially distributed soil properties and a physically-based soil moisture process, using the Noah LSM for hourly soil moisture estimation. This integration captures spatial variations in soil moisture and hydraulic properties from remote sensing across the watershed. The parameter sensitivity analysis and the calibration of hourly flow were significantly impacted by the physically-based hourly soil moisture routing and the incorporation of spatially distributed soil properties. Consequently, the modified SWAT model showed improved accuracy in hourly flow simulations for long-term and multiple rainfall events. Validation results showed significant improvements, with Coefficient of Determination (R2) and Nash and Sutcliffe Efficiency (NSE) increasing by 25.95% and 33.3%, respectively, and Percent Bias (PBIAS) decreasing by 85.8%. Notably, the average error for peak flows across eight events decreased by 49%. These findings highlight the importance of initializing soil parameters based on spatial soil moisture distribution and incorporating physical process-based moisture routing to enhance hourly flow simulation accuracy. Future research should focus on validating the physical feasibility of the soil parameter set in the study area with detailed hourly flow and soil moisture data and exploring its applicability in various regions. This study provides valuable insights for the scientific community, water resources, and agricultural decision-makers regarding integrated modeling of soil moisture and hourly flow, which can inform dam operation management, disaster planning, and crop yield improvement.

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Assessment of inland flood hazard sensitivity to hydrological intensification in coastal watersheds

Miller

2022

Front. Water

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IntroductionIntensification of the hydrologic cycle induced by climate variability and landscape modification is expected to increase the frequency of extreme flood events. Multi-jurisdictional approaches to manage inland flood risks at watershed scales demand the ability to objectively assess not only future flood potentials, but to also set priorities based upon multiple factors such as the stream channels most sensitive to hydrologic stress.MethodsThis study presents a method to estimate flood hazard sensitivities to increasing stormwater runoff due to hydrologic intensification (e.g., urbanization, climate effects) on local and watershed scales. The method is demonstrated in the low-gradient inland watershed regions of southwestern coastal Louisiana, USA. Utilizing highly detailed numerical models from the Federal Emergency Management Agency (FEMA), absolute and relative flood sensitivities were calculated for 45 flood-prone stream channels in the Lafayette, LA region. Channel sensitivities to flood hazards induced by changes in the 10-yr (10% annual exceedance probability) flood flows were quantified by analysis of 485 scenarios developed using a downward counterfactual scaling strategy.Results and discussionRelying entirely upon publicly available numerical models and input datasets, the study revealed key information about the relationship between estimable hydraulic characteristics (e.g., conveyance, resistance, and flow) and absolute and relative flood hazard sensitivity measures on a per-channel basis. Information from the subset of detailed numerical models was efficiently leveraged to provide a regional map of relative flood sensitivities. The methodology is robust and can be applied in very general settings to address the concern of hydrologic intensification in practical flood risk management applications.

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Coupling a land surface model with a hydrodynamic model for regional flood risk assessment due to climate change: Application to the Susquehanna River near Harrisburg, Pennsylvania

Cited by 3 publications

References 42 publications

Lidar DEM and Computational Mesh Grid Resolutions Modify Roughness in 2D Hydrodynamic Models

Lidar DEM and Computational Mesh Grid Resolutions Modify Roughness in 2D Hydrodynamic Models

Analysis of Effects of Spatial Distributed Soil Properties and Soil Moisture Behavior on Hourly Streamflow Estimate through the Integration of SWAT and LSM

Assessment of inland flood hazard sensitivity to hydrological intensification in coastal watersheds

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