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Created: | Apr 21, 2025 at 4:30 p.m. | |
Last updated: | Apr 21, 2025 at 5:46 p.m. | |
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Abstract
Overtopping-induced breaches in earthen dams pose a growing threat, increasingly exacerbated by extreme rainfall events. We present a probabilistic framework to quantify erosion risk by incorporating uncertainties in both hydrologic loading and dam material resistance. Fragility curves are developed to estimate surface erosion probabilities across a range of flood intensities. Coupled hydrologic and hydraulic analyses link rainfall dynamics to dam overflow behavior. Uncertainty in the interaction between applied and critical shear stresses is propagated using Monte Carlo simulations. Applied to three dams affected by the 2015 South Carolina floods, the framework captures distinct erosion responses driven by excess shear stress, with predicted probabilities aligning with observed outcomes. In contrast to deterministic methods that oversimplify hydraulic-material interactions, this probabilistic approach offers a more robust basis for dam safety assessment and flood mitigation planning.
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readme.txt
Paper: A Fragility Framework for Surface Erosion with Application to Earthen Dam Breaching Submitted to: WRR Prepared by: Ege C. Kurter, Ayman M. Nemnem, M. Hanif Chaudhry and Jasim Imran Email to egecankurter@gmail.com for any questions This text explains the documents shared in HydroShare The folder contains the necessary files that were used in producing this research 1) -Figures- folder contains the high-resolution PNG version of all the figures All figures are produced and/or edited in Inkscape, The plots are produced using MATLAB codes 2) -Monte Carlo Simulation.xlsx- file consists the MCS calculations for all dams In the first three sheets: 1st column is the simulation number 2nd column is the generated rainfall depth from Table 2 3rd column is the corresponding applied shear stress calculated using the regression equations given in Fig. 6 4rd column is the generated critical shear stress from the defined probability density functions 5th column is the limit state function Z. The magnitudes in this column are categorized into different erosion state magnitudes. To work with the python code for fragility curve fitting, create extra column of Failure(1)/Non-Failure(0) based on the erosion state magnitude. The fourth sheet summarizes the limit state magnitudes for all three dams. 3) -fitting_fragility_curves.py- file contains the maximum likelihood estimation code for fragility curve fitting 4) -Hydrograpgs.xlsx- file contains inflow hydrographs generated using the HEC-HMS hydrologic model, which served as input for the SSA hydraulic model. It includes two main inflow locations: Jackson Creek, representing the inflow to Cary’s Lake Dam, and Gills Creek, representing the inflow to Upper Rocky Ford Dam. The file provides hydrographs for various storm return periods—10, 25, 50, 100, 200, 500, and 1000 years—as well as the 2015 historic flood event. For each event, the hydrographs include the mean flow along with the lower and upper bounds of the 90% confidence interval (CI). Notes: 1) The random simulation samples are generated using short python scripts for rainfall depth and critical shear stress 2) The complete hydraulic calculations for determining overflow properties are tabulated in Table 3 and B1, therefore we do not provide a separate excel file for them.
Credits
Funding Agencies
This resource was created using funding from the following sources:
Agency Name | Award Title | Award Number |
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National Science Foundation | 2152896 | |
NOAA via the Cooperative Institute for Research to Operations in Hydrology (CIROH) | NA22NWS4320003 | |
Engineer Research and Development Center (ERDC) of the US Army Corps of Engineers | W912HZ-21C-0067 |
Contributors
People or Organizations that contributed technically, materially, financially, or provided general support for the creation of the resource's content but are not considered authors.
Name | Organization | Address | Phone | Author Identifiers |
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M. Hanif Chaudhry | University of South Carolina | |||
Jasim Imran | University of South Carolina |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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