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Data For Terrain Analysis Enhancements to the Height Above Nearest Drainage Flood Inundation Mapping Method


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Created: Aug 19, 2019 at 7:35 p.m.
Last updated: Sep 03, 2019 at 5:50 a.m.
DOI: 10.4211/hs.7235a0d6a18343078b2028085b7d8018
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Content types: Geographic Feature Content  Geographic Raster Content 
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Abstract

This resource contains the data and scripts used for: Garousi-Nejad, I., D. G. Tarboton, M. Aboutalebi and A. F. Torres-Rua, (2019), "Terrain Analysis Enhancements to the Height Above Nearest Drainage Flood Inundation Mapping Method," Water Resources Research, http://doi.org/10.1029/2019WR024837.

Abstract from the paper:
Flood inundation remains challenging to map, model, and forecast because it requires detailed representations of hydrologic and hydraulic processes. Recently, Continental‐Scale Flood Inundation Mapping (CFIM), an empirical approach with fewer data demands, has been suggested. This approach uses National Water Model forecast discharge with Height Above Nearest Drainage (HAND) calculated from a digital elevation model to approximate reach‐averaged hydraulic properties, estimate a synthetic rating curve, and map near real‐time flood inundation from stage. In 2017, rapid snowmelt resulted in a record flood on the Bear River in Utah, USA. In this study, we evaluated the CFIM method over the river section where this flooding occurred. We compared modeled flood inundation with the flood inundation observed in high‐resolution Planet RapidEye satellite imagery. Differences were attributed to discrepancies between observed and forecast discharges but also notably due to shortcomings in the derivation of HAND from National Elevation Dataset as implemented in CFIM, and possibly due to sub optimal hydraulic roughness parameter. Examining these differences highlights limitations in the HAND terrain analysis methodology. We present a set of improvements developed to overcome some limitations and advance CFIM outcomes. These include conditioning the topography using high‐resolution hydrography, dispersing nodes used to subdivide the river into reaches and catchments, and using a high‐resolution digital elevation model. We also suggest an approach to obtain a reach specific Manning's n from observed inundation and validated improvements for the flood of March 2019 in the Ocheyedan River, Iowa. The methods developed have the potential to improve CFIM.

The file Readme.md describes the contents and steps for reproducing the analyses in the paper.

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Resource Level Coverage

Spatial

Coordinate System/Geographic Projection:
WGS 84 EPSG:4326
Coordinate Units:
Decimal degrees
North Latitude
41.8419°
East Longitude
-112.0371°
South Latitude
41.5583°
West Longitude
-112.1418°

Content

Readme.md

This resource contains the data and scripts used for: Garousi-Nejad, I., D. G. Tarboton, M. Aboutalebi and A. F. Torres-Rua, (2019), Terrain Analysis Enhancements to the Height Above Nearest Drainage Flood Inundation Mapping Method, Water Resources Research, http://doi.org/10.1029/2019WR024837.

There are 11 directories in this resource.

  1. Topography holds the 3 m and 10 m National Elevation Dataset (NED) digital elevation models (DEM) of the Bear River case study and the 3 m NED DEM of the Ocheyedan River validation case study. It also holds three conditioned DEMs from the Etching approach developed in this research.

  2. Streamflow holds the observed discharge values at the USGS and PacifiCorp gages on Feb 15, 2017 for the Bear River case study and on Mar 21, 2019 for the Ocheyedan River validation study.

  3. Planet holds the 5 m, 3 m, and 10 m classified RapidEye image from Feb 15, 2017 for the Bear River case study and the 3 m and 10 m classified Sentinel-2 image from Mar 21, 2019 for the Ocheyedan River validation study.

  4. Hydrography holds the medium (1:100,000) and the high (1:24,000) resolution National Hydrography Datasets for both Bear River case study and Ocheyedan River validation study.

  5. CFIM holds the HAND map and hydraulic properties tables for the Bear River and Ocheyedan River HUC 6 watersheds from the NFIE Continental Flood Inundation Mapping - Data Repository (https://web.corral.tacc.utexas.edu/nfiedata/). It also holds the modeled inundation map for the Bear River case study for the CFIM scenario.

  6. BearRiver holds the data for each scenario in the Bear River case study and its associated IPython Jupyter Notebook which shows the steps to reproduce results in the Bear River case study.

  7. OcheyedanRiver holds the data for each scenario in the Ocheyedan River validation study and its associated Ipython Jupyter Notebook which shows the steps to reproduce results in the Ocheyedan River validation study.

  8. Hydraulic-properties holds the hydraulic properties tables created for different scenarios in both Bear River case study and Ocheyedan River validation study.

  9. HAND holds the Height Above Nearest Drainage (HAND) maps created for different scenarios in both Bear River case study and Ocheyedan River validation study.

  10. Scripts holds python scripts that can be use for reproducing results.

  11. Results holds observed vs modeled comparison raster files that are generated from the modeled and observed inundation for each scenario. The evaluation metrics (Fit and Correctness) are computed using these observed vs modeled comparison raster files.

Detailed contents of each directory

1. Topography:

  • 10mNED_BearRiver.tif: 10 m National Elevation Dataset DEM for the Hydrologic Unit Code (HUC8=16010204).
  • 3mNED_BearRiver.tif: Available 3 m National Elevation Dataset DEM covering a reach of Bear River within the study domain.
  • 3mNED_OcheyedanRiver.tif: Available 3 m National Elevation Dataset DEM covering a reach of Ocheyedan River within the study domain.
  • 10mETCH_BearRiver.tif: Conditioned 10 m DEM using the developed etching approach in the Bear River case study.
  • 3mETCH_BearRiver.tif: Conditioned 3 m DEM using the developed etching approach in the Bear River case study.
  • 3mETCH_OcheydanRiver.tif: Conditioned 3 m DEM using the developed etching approach in the Ocheyedan River validation study.

2. Streamflow:

  • historical_annual_peakflow_fromUSGSgage_at_Corrine.csv: Historical annual peak values observed at gage 10126000 near Corrine on the Bear River, retrieved from the USGS https://waterdata.usgs.gov/nwis/uv?site_no=10126000.
  • February2017_15min_flow_fromUSGS_at_gage10126000_Corrine.csv: The observed 15-minutes streamflow from gage 10126000 near Corrine on the Bear River, retrieved from the USGS https://waterdata.usgs.gov/nwis/uv?site_no=10126000.
  • February2017_daily_flow_fromUSGS_at_gage10126000_Corrine.csv: The observed daily average streamflow from gage 10126000 near Corrine on the Bear River, retrieved from the USGS https://waterdata.usgs.gov/nwis/uv?site_no=10126000.
  • February2017_daily_flow_fromPacifiCorp_Collinston.csv: The observed daily average streamflow from PacifiCorp gage at Collinston on the Bear River, retrieved from Bear River Commission http://bearriverbasin.org/rivers/rivers/.
  • March2019_daily_flow_fromUSGS_at_gage06605000_Spencer.csv: The observed daily average streamflow from gage 06605000 near Spencer on the Ocheyedan River, retrieved from the USGS https://waterdata.usgs.gov/nwis/uv?site_no=06605000.

3. Planet:

  • Planet_Observed_Bear_RapidEye.tif: The classified observed flood inundation map from Planet RapidEye satellites captured on the flood date (Feb 15, 2017) in the Bear River case study. Note that this file has a WGS 84 WGS 1984 UTM Zone 12N projection and the spatial resolution is 5 m.
  • Planet_Observed_10m_Bear.tif: The 10 m resampled classified observed flood inundation map from Planet RapidEye satellites captured on the flood date (Feb 15, 2017) in the Bear River case study. The spatial resolution is the same as the DEM.
  • Planet_Observed_3m_Bear.tif: The 3 m resampled classified observed flood inundation map from Planet RapidEye satellites captured on the flood date (Feb 15, 2017) in the Bear River case study. The spatial resolution is the same as the DEM.
  • Planet_Observed_Ocheyedan_Sentinel2.tif: The classified observed flood inundation map from Planet Sentinel-2 satellites captured on the flood date (March 21, 2019) in the Ocheyedan River validation study. Note that this file has a WGS 1984 UTM Zone 15N projection and the spatial resolution is 10 m.
  • Planet_Observed_10m_Ocheyedan.tif: The 10 m resampled classified observed flood inundation map from Planet Sentinel-2 satellites captured on the flood date (March 21, 2019) in the Ocheyedan River validation study. The spatial resolution is the same as the DEM.
  • Planet_Observed_3m_Ocheyedan.tif: The 3 m resampled classified observed flood inundation map from Planet Sentinel-2 satellites captured on the flood date (March 21, 2019) in the Ocheyedan River validation study. The spatial resolution is the same as the DEM.

4. Hydrography:

  • Bear_medres_NHDPlusflowline.shp: Subset of the medium resolution NHDPlus reaches for the Hydrologic Unit Code (HUC2=16) that includes the Bear River study area obtained from Fagan, C. (2015). NFIE-Geo Great Basin Region, HydroShare, http://www.hydroshare.org/resource/46c1b0f6c16c4ae1b71298cda7cfc0ab. This is a subset prepared for the National Flood Interoperability Experiment (NFIE) that only includes reaches for which the National Water model forecasts are produced.
  • Bear_highres_NHDPlusflowline.shp: The high resolution NHDPlus reaches for the HUC4 (1601) that includes the Bear River study area obtained from the national map https://viewer.nationalmap.gov/basic/?basemap=b1&category=nhd&title=NHD%20View.
  • Ocheyedan_medres_NHDPlusFlowline.shp: Subset of the medium resolution NHDPlus reaches for the Hydrologic Unit Code (HUC4=1023) that includes the Ocheyedan River validation area obtained from Fagan, C. (2015). NFIE-Geo Mississippi Region, HydroShare, http://www.hydroshare.org/resource/126bb28f05224636a8bc8b3d1bdad6b5.
  • Ocheyedan_highres_NHDPlusflowline.shp: The high resolution NHDPlus reaches for the HUC4=1023 that includes the Ocheyedan River validation area obtained from the national map https://viewer.nationalmap.gov/basic/?basemap=b1&category=nhd&title=NHD%20View.

5. CFIM:

  • 160102dd.tif: The Height Above Nearest Drainage (HAND) map retrieved from NFIE Continental Flood Inundation Mapping - Data Repository https://web.corral.tacc.utexas.edu/nfiedata/HAND/160102/ including the Bear River case study domain.
  • 16010204inunmap.tif: The modeled inundation map using the hourly assimilated NWM streamflow data for the flood data (Feb 15, 2017 at 18:00 UTC) for Huc8=16010204. This has been created using scripts provided for NFIE project at https://github.com/cybergis/nfie-floodmap.
  • 102300dd.tif: The Height Above Nearest Drainage (HAND) map retrieved from NFIE Continental Flood Inundation Mapping - Data Repository https://web.corral.tacc.utexas.edu/nfiedata/HAND/102300/ including the Ocheyedan River validation study domain.
  • hydroprop-fulltable-160102.csv: The hydraulic properties for the NHDPlus reaches within HUC6=160102 retrieved from NFIE Continental Flood Inundation Mapping - Data Repository https://web.corral.tacc.utexas.edu/nfiedata/HAND/160102/ for the Bear River case study domain.
  • hydroprop-fulltable-102300.csv: The hydraulic properties for the NHDPlus reaches within HUC6=102300 retrieved from NFIE Continental Flood Inundation Mapping - Data Repository https://web.corral.tacc.utexas.edu/nfiedata/HAND/102300/ for the Ocheyedan River validation study domain.

6. BearRiver:

This directory holds six scenarios considered in the Bear River case study. In each scenario, there are (1) a Jupyter Notebook and (2) a folder called Input. The iPython Jupyter Notebook shows the steps that are required to reproduce the results for that particular scenario. Each computing cell in the Jupyter Notebook calls a specific script from the /Script directory within the root level of this HydroShare resource. Some inputs (such as the DEM and hydrography datasets) are called from the root directory of the HydroShare resource. The other required inputs are called from the /Input directory inside the Scenario directory. Please look at the first section of each Jupyter Notebook for more details on the inputs that are used in each scenario.

  • Scenario1, CFIM methodology with NWM assimilated flows

    • BearRiverScenario1.ipynb
    • Input
      • 3mdemdomain.shp
      • domain_Metric.shp
  • Scenario2, CFIM methodology with observed flow

    • BearRiverScenario2.ipynb
    • Input
      • 3mdemdomain.shp
      • domain_Metric.shp
      • catch_mrg.shp
      • catch_mrg_rs.tif
      • Adjusted_Q.txt
      • linkid.txt
  • Scenario3, Evenly distributed nodes and TauDEM used to re-delineate channels and catchments from 10 m DEM

    • BearRiverScenario3.ipynb
    • Input
      • 3mdemdomain.shp
      • domain_Metric.shp
      • catch_mrg.shp
      • catch_mrg_rs.tif
      • Evenly_dispersed_nodes
      • inlets_on_mainstem.tif
      • dangle_mainstem.shp
      • Adjusted_Q.txt
      • linkid.txt
      • STAGES.txt
      • INDEX.txt
  • Scenario4, High-resolution National Hydrography Dataset (NHD) flow paths eched into 10 m DEM

    • BearRiverScenario4.ipynb
    • Input
      • 3mdemdomain.shp
      • domain_Metric.shp
      • catch_mrg.shp:
      • catch_mrg_rs.tif
      • Evenly_dispersed_nodes
      • inlets_on_mainstem.tif
      • dangle_mainstem.shp
      • highres_NHDPlusflowline
      • Adjusted_Q.txt
      • linkid.txt
      • STAGES.txt
      • INDEX.txt
  • Scenario5, Evenly distributed nodes and TauDEM used to re-delineate channels and catchments from 3 m DEM

    • BearRiverScenario5.ipynb
    • Input
      • 3mdemdomain.shp
      • domain_Metric.shp
      • catch_mrg.shp
      • catch_mrg_rs.tif
      • Evenly_dispersed_nodes
      • inlets_on_mainstem.tif
      • dangle_mainstem.shp
      • Adjusted_Q.txt
      • linkid.txt
      • STAGES.txt
      • INDEX.txt
  • Scenario6, High-resolution National Hydrography Dataset (NHD) flow paths eched into 3 m DEM

    • BearRiverScenario6.ipynb
    • Input
      • 3mdemdomain.shp
      • domain_Metric.shp
      • catch_mrg.shp
      • catch_mrg_rs.tif
      • Evenly_dispersed_nodes
      • inlets_on_mainstem.tif
      • dangle_mainstem.shp
      • highres_NHDPlusflowline
      • Adjusted_Q.txt
      • linkid.txt
      • STAGES.txt
      • INDEX.txt

7. OcheyedanRiver:

  • Scenario1, CFIM methodology with observed flow

    • OcheyedanRiverScenario1.ipynb
    • Input
      • 3mdemdomain.shp
      • domain_Metric.shp
      • catch_mrg.shp:
      • catch_mrg_rs.tif
      • Adjusted_Q.txt
      • linkid.txt
  • Scenario2, Evenly distributed nodes and TauDEM used to re-delineate channels and catchments from 3 m DEM

    • OcheyedanRiverScenario2.ipynb
    • Input
      • 3mdemdomain.shp
      • domain_Metric.shp
      • catch_mrg.shp:
      • catch_mrg_rs.tif
      • Evenly_dispersed_nodes
      • inlets_on_mainstem.tif
      • dangle_mainstem.shp
      • Adjusted_Q.txt
      • linkid.txt
      • STAGES.txt
      • INDEX.txt
  • Scenario3, High-resolution National Hydrography Dataset (NHD) flow paths eched into 3 m DEM

    • OcheyedanRiverScenario3.ipynb
    • Input
      • 3mdemdomain.shp
      • domain_Metric.shp
      • catch_mrg.shp
      • catch_mrg_rs.tif
      • Evenly_dispersed_nodes
      • inlets_on_mainstem.tif
      • dangle_mainstem.shp
      • highres_NHDPlusflowline
      • Adjusted_Q.txt
      • linkid.txt
      • STAGES.txt
      • INDEX.txt

8. Hydraulic-properties:

  • BearRiver_Sc3_10mUniform_hp.csv: The computed reach-averaged hydraulic properties in Scenario 3 (10m-Uniform) in the Bear River case study.
  • BearRiver_Sc4_10mETCH_hp.csv: The computed reach-averaged hydraulic properties in Scenario 4 (10m-ETCH) in the Bear River case study.
  • BearRiver_Sc5_3mUniform_hp.csv: The computed reach-averaged hydraulic properties in Scenario 5 (3m-Uniform) in the Bear River case study.
  • BearRiver_Sc6_3mETCH_hp.csv: The computed reach-averaged hydraulic properties in Scenario 6 (3m-ETCH) in the Bear River case study.
  • BearRiver_Sc6_3mETCH_FittedManning_hp.csv: The computed reach-averaged hydraulic properties in Scenario 6 (3m-ETCH) with the fitted Manning's n in the Bear River case study.
  • BearRiver_Sc6_3mETCH_AverageManning_hp.csv: The computed reach-averaged hydraulic properties in Scenario 6 (3m-ETCH) with the average of the fitted Manning's n in the Bear River case study.
  • OcheyedanRiver_Sc2_3mUniform_hp.csv: The computed reach-averaged hydraulic properties in Scenario 2 (3m-Uniform) in the Ocheyedan River validation study.
  • OcheyedanRiver_Sc3_3mETCH_hp.csv: The computed reach-averaged hydraulic properties in Scenario 3 (3m-ETCH) in the Ocheyedan River validation study.
  • OcheyedanRiver_Sc3_3mETCH_FittedManning_hp.csv: The computed reach-averaged hydraulic properties in Scenario 3 (3m-ETCH) with the fitted Manning's n in the Ocheyedan River validation study.
  • OcheyedanRiver_Sc3_3mETCH_AverageManning_hp.csv: The computed reach-averaged hydraulic properties in Scenario 3 (3m-ETCH) with the average of the fitted Manning's n in the Ocheyedan River validation study.

9. HAND:

  • BearRiver_Sc3_10mUniform_hand.tif: The computed HAND map in Scenario 3 (10m-Uniform) in the Bear River case study.
  • BearRiver_Sc4_10mETCH_hand.tif: The computed HAND map in Scenario 4 (10m-ETCH) in the Bear River case study.
  • BearRiver_Sc5_3mUniform_hand.tif: The computed HAND map in Scenario 5 (3m-Uniform) in the Bear River case study.
  • BearRiver_Sc6_3mETCH_hand.tif: The computed HAND map in Scenario 6 (3m-ETCH) in the Bear River case study.
  • OcheyedanRiver_Sc2_3mUniform_hand.tif: The computed HAND map in Scenario 2 (3m-Uniform) in the Ocheyedan River case study.
  • OcheyedanRiver_Sc3_3mETCH_hand.tif: The computed HAND map in Scenario 3 (3m-ETCH) in the Ocheyedan River case study.

10. Scripts:

  • FloodInundationMapping: This directory contains 14 python scripts to generate flood inundation mapping results.
    • N01_script_01_Hydroprop: This script creates modeled inundation maps for a range of stage values.
    • N02_script_02_Hydroprop This script extracts the required information (such as the number of flooded grid cells) from the results of N01_script_01_Hydroprop.py that are used later to generate the hydraulic properties table.
    • N03_script_03_Hydroprop: This script uses the information that are created from N02_script_02_Hydroprop.py script to calculate the geometry properties of the reaches within the study domain.
    • N04_script_04_Hydroprop: This script uses the geometry properties information created above and computes the hydraulic properties and synthetic rating curves for the reaches within the study domain.
    • N05_script_EstimateFloodStage: This script estimates the flood stage for each National Hydrography Dataset (medium-resolution) and is used in all scenarios except for CFIM related ones. For CFIM related scenarios, N05_script_EstimateFloodStage_CFIM.py is used.
    • N05_script_EstimateFloodStage_CFIM: This script estimates the flood stage for each National Hydrography Dataset (medium-resolution) and is used in CFIM scenarios since the HAND map is not directly generated in these scenarios. It is just called from the root directory.
    • N06_script_Inundationmap: This script uses the estimated flood stage and the HAND raster to map the inundation and is used in all scenarios except for CFIM related ones. For CFIM related scenarios, N06_script_Inundationmap_CFIM.py is used.
    • N06_script_Inundationmap_CFIM: This script uses the estimated flood stage and the HAND raster to map the inundation and is used in CFIM scenarios since the required inputs are called from the root directory.
    • N07_script_ObservedModeledComparision: This script compares the modeled and observed inundation by creating a classified map that holds the values of -1 (i.e., observed as dry and modeled as wet), 0 (i.e., both dry), 1 (i.e., both wet), 2 (i.e., observed as wet and modeled as dry). This is used in all scenarios except for CFIM related scenarios.
    • N07_script_ObservedModeledComparision_CFIM: This script compares the modeled and observed inundation by creating a classified map that holds the values of -1 (i.e., observed as dry and modeled as wet), 0 (i.e., both dry), 1 (i.e., both wet), 2 (i.e., observed as wet and modeled as dry). This is used in the CFIM related scenarios.
    • N07_script_ObservedModeledComparision_CFIM_1: This script compares the modeled and observed inundation by creating a classified map that holds the values of -1 (i.e., observed as dry and modeled as wet), 0 (i.e., both dry), 1 (i.e., both wet), 2 (i.e., observed as wet and modeled as dry). This is called in the Bear River Scenario 1. Because in this scenario the required input (i.e., the modeled inundation map) from the root directory.
    • N08_script_Evaluationmetrics: This script computes the evaluation metrics (Correctness, C, and Fit, F) over the entire domain. This is used in all scenarios in both Bear River case study and Ocheyedan River validation study.
    • N09_script_FandCforStages: This script computes the hydraulic properties, rating curve, flood inundation stage, flood inundation map, and evaluation metrics for a range of stage (h) values for delineated catchments. Note that this is used only for the Manning's n sensitivity analysis (Scenario6 in the Bear River case study and Scenario 3 in the Ocheyedan River validation study).
    • N10_script_BestStageBasedonBestF: This script finds the best h value based on the maximum value of F for each catchment. Note that this is used only for the Manning's n sensitivity analysis (Scenario6 in the Bear River case study and Scenario 3 in the Ocheyedan River validation study).
    • N11_script_BestInundationdepthBasedonBestF: This script finds the best average inundation depth value based on the best stage. Note that this is used only for the Manning's n sensitivity analysis (Scenario6 in the Bear River case study and Scenario 3 in the Ocheyedan River validation study).
    • N12_script_BestManningBasedonBestF: This script finds the best Manning's n based on the best average flood inundation depth. Note that this is used only for the Manning's n sensitivity analysis (Scenario6 in the Bear River case study and Scenario 3 in the Ocheyedan River validation study).
    • N13_script_SensitivityManning: This script creates two hydraulic properties using the optimal Manning's n and the average Manning's n. Note that this is used only for the Manning's n sensitivity analysis (Scenario6 in the Bear River case study and Scenario 3 in the Ocheyedan River validation study).
    • N14_scriptEvaluationmetrics_over_specificCATCH: This script computes evaluation metrics for each catchment. Note that this is used only for the Manning's n sensitivity analysis (Scenario6 in the Bear River case study).
  • PlanetResampling: This directory contains two python scripts that we used to resample the observed flood inundation map to a specific spatial resolution based on the DEM cell size. The PlanetResampling_CFIM.py is used in Scenario 1 of both case studies since the HAND map is within the root directory and is not generated with the scripts developed.
  • SlopeAdjustment: This directory contains a python script that we developed for adjusting slope values where the value was 0. There is also a PDF document that describes this algorithm.
  • TerrainAnalysis: This directory contains two python scripts showing the steps that need to be done to reproduce the HAND map. The difference between HAND.py and HAND_with_Etching.py is that the HAND_with_Etching.py creates a HAND map based on a conditioned DEM. The steps that lead to create a conditioned DEM (using the developed etching approach) is also included in HAND_with_Etching.py script.

11. Results:

  • BearRiver_Sc1_CFIMNWM_results.tif: The observed versus modeled comparison created for Scenario 1 (CFIM-NWM) in the Bear River case study.
  • BearRiver_Sc2_CFIMOBS_results.tif: The observed versus modeled comparison created for Scenario 2 (CFIM-OBS) in the Bear River case study.
  • BearRiver_Sc3_10mUniform_results.tif: The observed versus modeled comparison created for Scenario 3 (10m-Uniform) in the Bear River case study.
  • BearRiver_Sc4_10mETCH_results.tif: The observed versus modeled comparison created for Scenario 4 (10m-ETCH) in the Bear River case study.
  • BearRiver_Sc5_3mUniform_results.tif: The observed versus modeled comparison created for Scenario 5 (3m-Uniform) in the Bear River case study.
  • BearRiver_Sc6_3mETCH_results.tif: The observed versus modeled comparison created for Scenario 6 (3m-ETCH) in the Bear River case study.
  • BearRiver_Sc6_3mETCH_FittedManning_results.tif: The observed versus modeled comparison created for Scenario 6 (3m-ETCH) in the Bear River case study with the fitted Manning's n values.
  • BearRiver_Sc6_3mETCH_AverageManning_results.tif: The observed versus modeled comparison created for Scenario 6 (3m-ETCH) in the Bear River case study with the average of the fitted Manning's n values.
  • OcheyedanRiver_Sc1_CFIMOBS_results.tif: The observed versus modeled comparison created for Scenario 1 (CFIM-OBS) in the Ocheyedan River validation study.
  • OcheyedanRiver_Sc2_3mUniform_results.tif: The observed versus modeled comparison created for Scenario 32 (3m-Uniform) in the Ocheyedan River validation study.
  • OcheyedanRiver_Sc3_3mETCH_results.tif: The observed versus modeled comparison created for Scenario 3 (3m-ETCH) in the Ocheyedan River validation study.
  • OcheyedanRiver_Sc3_3mETCH_FittedManning_results.tif: The observed versus modeled comparison created for Scenario 3 (3m-ETCH) in the Ocheyedan River validation study with the fitted Manning's n values.
  • OcheyedanRiver_Sc3_3mETCH_AverageManning_results.tif: The observed versus modeled comparison created for Scenario 3 (3m-ETCH) in the Ocheyedan River validation study with the average of the fitted Manning's n values.

References

Related Resources

The content of this resource serves as the data for: Garousi-Nejad, I., D. G. Tarboton, M. Aboutalebi and A. F. Torres-Rua, (2019), "Terrain Analysis Enhancements to the Height Above Nearest Drainage Flood Inundation Mapping Method," Water Resources Research, http://doi.org/10.1029/2019WR024837.

Credits

Funding Agencies

This resource was created using funding from the following sources:
Agency Name Award Title Award Number
National Science Foundation Scalable Capabilities for Spatial Data Synthesis 1443080
Utah Water Research Laboratory Graduate Student Research Assistantship for I Garousi-Nejad

Contributors

People 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
Shaowen Wang University of Illinois at Urbana-Champaign Illinois, US
Yan Liu UIUC/CyberGIS
Carri Richards Utah State University

How to Cite

Garousi-Nejad, I., D. Tarboton, M. Aboutalebi, A. F. Torres-Rua (2019). Data For Terrain Analysis Enhancements to the Height Above Nearest Drainage Flood Inundation Mapping Method, HydroShare, https://doi.org/10.4211/hs.7235a0d6a18343078b2028085b7d8018

This resource is shared under the Creative Commons Attribution CC BY.

 http://creativecommons.org/licenses/by/4.0/
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