Hosseini-Shakib_etal_2022_preprint

Uncertainties surrounding flood hazard estimates is the primary driver of riverine flood risk projections

Iman Hosseini-Shakib^1*, Sanjib Sharma¹, Benjamin Seiyon Lee², Vivek Anand Srikrishnan³, Robert Nicholas^1,4, and Klaus Keller^1,5

¹ Earth and Environmental Systems Institute, The Pennsylvania State University, University Park, PA, USA
² Department of Statistics, George Mason University, Fairfax, VA, USA
³ Department of Biological & Environmental Engineering, Cornell University, Ithaca, NY, USA
⁴ Department of Meteorology and Atmospheric Science, The Pennsylvania State University, University Park, PA, USA
⁵ Thayer School of Engineering, Dartmouth College, Hanover, NH, USA

* corresponding author: ishakib@gmail.com

Abstract

Flooding drives considerable risks. Designing strategies to manage these risks is complicated by the often large uncertainty surrounding flood-risk projections. Uncertainty surrounding flood risks can stem, for example, from choices regarding boundary conditions, model structures, and parameters. Dynamic interactions among hazard, exposure, and vulnerability can modulate the uncertainty surrounding flood risks. A quantitative understanding of which factors drive uncertainties surrounding flood hazards and risks can inform the design of mission-oriented research. Here characterize key uncertainties impacting flood-risk projections and perform a global sensitivity analysis to characterize the most important drivers of the uncertainties surrounding flood hazards and risks. We find that the flood risk model is sensitive to upstream discharge, river bed elevation, channel roughness and digital elevation model resolution.

Journal reference

Hosseini-Shakib, I., Sharma, S., Lee, B.S., Srikrishnan, V.A., Nicholas, R., & Keller, K. (2022). Uncertainties surrounding flood hazard estimates is the primary driver of riverine flood risk projections. preprint

Data reference

Input data

The 1/3 arcsec digital elevation model (DEM) tile for Selinsgrove,PA is downloaded from the USGS website at API: https://prd-tnm.s3.amazonaws.com/StagedProducts/Elevation/13/TIFF/historical/n41w077/USGS_13_n41w077_20220429.tif
The small size input data are stored in the "Inputs" folder and are as follows:

• "Isle of Que": shapefile of the Isle of Que in Selinsgrove
• "NLCD": Land use land cover 30m gridded data from the USGS National Land Cover Database (2016) clipped for Selinsgrove, PA
• "Rivers": shapefile of the Susquehanna River from Pennsylvania Spatial Data Access (https://www.pasda.psu.edu) clipped for the region
• "Roads": shapefile of the Roads from Pennsylvania Spatial Data Access (https://www.pasda.psu.edu) clipped for the region
• "Susquehanna_west_bank": shapefile of the west bank of Sussquehanna from Pennsylvania Spatial Data Access (https://www.pasda.psu.edu) clipped for the region
• "clip_area": a rectangular shapefile that covers Selinsgrove, PA used to clip DEMs
• "houses_for_sale": shapefile of the houses for sale in Selinsgrove obtained from zillow.com accessed in February 2020
• "Selinsgrove_shapefile": shapefile of Selinsgrove, PA from Pennsylvania Spatial Data Access (https://www.pasda.psu.edu)

Contributing modeling software

Model	Version	Platform
R	3.6.0	x86_64-redhat-linux-gnu (64-bit)
LISFLOOD-FP	6.0.4	x86_64-redhat-linux-gnu (64-bit)

R packages used in this study are as follows in alphabetical order: "adaptMCMC", "data.table", "dataRetrieval", "DEoptim", "doParallel", "evd", "evir", "extRemes", "foreach", "geosphere", "GGally", "ggplot2", "graphics", "parallel", "plotrix", "raster", "RColorBrewer", "rgdal", "sensobol", "TruncatedDistributions".

Reproduce my experiment

These scripts perform a coupled analysis to estimate the expected annual flood damages of 2,000 hypothetical houses in Selinsgrove, PA. The analysis is organized in four parts: (1) initialization of the study region and hypothetical houses; (2) a statistical analysis to sample the discharge uncertainty; (3) a hydraulic model (LISFLOOD-FP) to estimate the flood hazard; (4) an exposure-vulnerability model to estimate the flood risk.

We estimate the run time for this repository using 400 CPUs from the Pennsylvania State Unversity high-performance computation facilities to be approximately 3 weeks. If you do not have access to high-performance computation facilities and wish to reproduce our results and plots, you can use the files in the pregenerated_run_results to avoid running the precalibration (10,000 model runs), the Sobol global sensitivity analysis (76,000 model runs) and the Morris one-step-at-a-time sensitivity analysis (73 model runs).

Users need to clone the Inputs, LISFLOOD,figures, and workflow folders, then run the main_script.R code that sources the codes in the workflow and figures folders by the order. The exact roles of each piece of code and input files are described in detail as follows:

Workflow:

Script Name	Description
code_w00-packages.R	Script to install the required R packages
code_w01-DEMs_and_land_cover.R	Script to create land use map and DEMs at different resolutins for Selinsgrove, PA
code_w02-hypothetical_houses.R	Script to create 2,000 hypothetical houses in Selinsgrove, PA
code_w03-hypothetical_house_prices.R	Script to estimate hypothetical house prices based on the exposure module
code_w04-discharge_GEV_MLE.R	Script to use frequentist maximum likelihood method to estimate GEV parameters for the annual maxima of discharge
code_w05-MCMC_and_MLE_Bayes_Comparison.R	Script to use the Metropolis-Hastings Markov Chain Monte Carlo method to quantify the uncertainty sorrounding the annual maxima of discharge
code_w06-initial_ensemble_for_precalib.R	Script to an initial ensemble of 10,000 rows for precalibration
code_w07-initial_model_run.R	Script to run the flood hazard model for 10,000 runs for precalibration
code_w08-precalibration.R	Script to perform precalibration
code_w09-Sobol_GSA_ensemble.R	Script to set up the 76,000 row ensemble used for global sensitivity analysis
code_w10-Sobol_GSA_model_run.R	Script to run flood risk model for the 76,000 row parameter set
code_w11-Sobol_GSA_risk_hazard_indices.R	Script to calculate Sobol sensitivity indices for hazard and risk parameters
code_w12-radial_plot_tables_risk.R	Script to set up the tables required for plotting the flood risk sensitivity results
code_w13-radial_plot_tables_hazard.R	Script to set up the tables required for plotting the flood hazard sensitivity results
code_w14-OAT_ensemble.R	Script to set up the ensemble of 73 rows for the Morris one-step-at-a-time sensitivity analysis
code_w15-OAT_model_run.R	Script to run the flood risk model for the Morris one-step-at-a-time sensitivity analysis

The following scripts are the functions used by the codes in the workflow directory and are stored in workflow/functions/

Functions:

Script Name	Description
OAT_haz_risk_function.R	Function to estimate average flood depth in m and total damage in USD for the Morris one-step-at-a-time analysis
batchmeans.R	Functions to calculate consistent batch means and imse estimators of Monte Carlo standard errors
flood_extent_function.R	Function to estimate flood extent and grid cell flood depth in m in Selinsgrove, PA used for precalibration
haz_risk_function.R	Function to estimate average flood depth in m and total damage in USD for the Sobol global sensitivity analysis method
sobol_functions.R	Functions used in plotting Sobol sensitivity results for hazard and risk

Reproduce my figures

Use the scripts found in the figures directory to reproduce the figures used in this publication.

Figures:

Script Name	Description
code_f01-discharge_annual_maxima.R	Script to plot the annual maxima of discharge for the USGS gauge of Susquehanna River at Sunbury
code_f02-discharge_90percent_uncert_plot.R	Script to plot the results of MCMC for upstream discharge
code_f03-return_periods_90CI.R	Script to plot uncertainty bounds of upstream discharge for different return periods
code_f04-MCMC_pairs_plot.R	Script to plot MCMC GEV parameters pairs
code_f05-initial_parameters_pdf_plots.R	Script to plot the pdfs of the initial parameter sets used for precalibration
code_f06-initial_parameter_pairs_plot.R	Script to plot initial parameters pairs used for precalibration
code_f07-precalibrated_parameters_pdf_plots.R	Script to plot pdfs of parameters used in the Sobol global sensitivity analysis
code_f08-precalibrated_parameter_pairs_plot.R	Script to plot the parameter sets pairs used in the Sobol global sensitivity analysis
code_f09-model_response_plots.R	Script to plot flood hazard and risk results used in the Sobol global sensitivity analysis
code_f10-radial_plots.R	Script to plot the results of flood hazard and risk global sensitivity analysis
code_f11-OAT_sensitivity_plot.R	Script to plot the results of the Morris one-step-at-a-time sensitivity analysis