HomeMy WebLinkAbout130910 Puna Hydrology n Hydraulic Report 070913
HYDROLOGIC AND
HYDRAULIC REPORT
Puna Flood Study Project
Puna, Hawai‘i
Prepared for:
County of Hawai‘i
Department of Public Works
Prepared by:
Oceanit Laboratories, Inc.
828 Fort Street Mall, Suite 600
Honolulu, Hawai‘i 96813
August 2013
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Hydrologic and Hydraulic Report
August 2013 i
CONTENTS
1 INTRODUCTION ................................................................................................. 1
1.1 BACKGROUND ....................................................................................................................... 1
1.2 PURPOSE AND SCOPE ............................................................................................................ 1
1.3 METHODOLOGY .................................................................................................................... 2
1.4 PREVIOUS STUDIES ............................................................................................................... 3
1.5 ACKNOWLEDGEMENTS ........................................................................................................ 3
2 STUDY AREA DESCRIPTION ............................................................................ 4
2.1 STUDY AREA OVERVIEW ..................................................................................................... 4
2.2 TOPOGRAPHY, VEGETATION, AND LAND USE ................................................................ 4
2.2.1 Geology and Climate .................................................................................................... 6
2.2.2 Water Resources and Hydrology ................................................................................. 7
2.3 HYDROLOGIC DATA ............................................................................................................. 7
2.3.1 Rain Gages ...................................................................................................................... 7
2.3.2 Stream Gages ................................................................................................................. 8
2.3.3 Field Survey .................................................................................................................... 8
2.4 FLOODING PROBLEMS IN THE STUDY AREA .................................................................. 10
2.5 SOUTH KŪLANI FLOOD DIVERSION STRUCTURE .......................................................... 10
3 HYDROLOGIC ANALYSIS .................................................................................. 11
3.1 HEC-HMS MODEL OVERVIEW ........................................................................................ 11
3.2 GEOSPATIAL INFORMATION USED ................................................................................... 11
3.3 METEOROLOGICAL EVENTS .............................................................................................. 22
3.4 BASIN LOSS .......................................................................................................................... 32
3.5 ESTIMATION OF TIME OF CONCENTRATIONS ................................................................ 40
3.6 HYDROGRAPH TRANSFORM PARAMETERS ...................................................................... 41
3.7 MODEL CALIBRATION ........................................................................................................ 44
3.8 HYDROLOGIC ANALYSIS RESULTS .................................................................................... 48
4 HYDRAULIC ANALYSIS .................................................................................... 50
4.1 FLO-2D MODEL OVERVIEW ............................................................................................ 50
4.2 FLO-2D MODEL SETUP ..................................................................................................... 50
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4.2.1 Topographic Database ................................................................................................ 50
4.2.2 Sub-domains and Grid Size ....................................................................................... 51
4.2.3 Hydrologic Input ......................................................................................................... 51
4.2.4 Streams .......................................................................................................................... 54
4.2.5 Water Diversion Systems ........................................................................................... 58
4.2.6 Bridges and Culverts ................................................................................................... 63
4.3 FLO-2D MODEL CALIBRATION ....................................................................................... 66
4.4 HYDRAULIC ANALYSIS RESULTS ....................................................................................... 67
4.4.1 Water Diversion System Assessment ....................................................................... 67
4.4.2 FLO-2D Model Calibration Result ........................................................................... 67
4.4.3 FLO-2D Model Results .............................................................................................. 74
4.5 DETERMINATION OF FLOODPLAIN BOUNDARIES ......................................................... 90
5 CONCLUSION AND LIMITATION ................................................................. 91
REFERENCES…………………………………………………………………………...93
APPDENDIX A - FLO-2D HYDROLOGGY MODEL DEVELOPMENT
APPDENDIX B - FIELD SURVEY SOUTH KULANI BRIDGE DIVERSION
STRUCTURE
APPDENDIX C - FIELD SURVEY ROADWAY CULVERTS & BRIDGE
CROSSINGS
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LIST OF FIGURES
Figure ES-1. Watershed and Junction Locations…………………………………………..ix
Figure 2 - 1. Location Map for Puna Study Area. ........................................................................... 5
Figure 3 - 1. Puna Study Sub-watershed. ........................................................................................ 13
Figure 3 - 2. Sub-basin Centroids for Puna. ................................................................................... 14
Figure 3 - 3. HEC-HMS Model Layout for Puna Study Area. .................................................... 15
Figure 3 - 4. HEC-HMS Model Structure for Puna Study Area. ................................................ 16
Figure 3 - 5. Junctions of Interest for Puna Study Area. .............................................................. 17
Figure 3 - 6. Rainfall of Each Sub-watershed for 10-yr Storm Return Period. ......................... 23
Figure 3 - 7. Rainfall of Each Sub-watershed for 50-yr Storm Return Period. ......................... 24
Figure 3 - 8. Rainfall of Each Sub-watershed for 100-yr Storm Return Period. ....................... 25
Figure 3 - 9. Rainfall of Each Sub-watershed for 500-yr Storm Return Period. ....................... 26
Figure 3 - 10. Designed 100-year 24-hour Rainfall Distribution for Sub-watershed 43
(Typical Hyetograph). ........................................................................................................................ 27
Figure 3 - 11. Soil Type for Puna Study Area. ............................................................................... 35
Figure 3 - 12. Saturated Soil Conductivities for Puna Watershed. .............................................. 36
Figure 3 - 13. Rain Gages Thiessen Polygon for November 1, ato 2, 2000, Storm. ................ 45
Figure 4 - 1. FLO-2D Model Sub-domains. .................................................................................. 52
Figure 4 - 2 Hydrograph Inflow locations for the sub-watersheds. ........................................... 53
Figure 4 - 3. Typical Steady State Inflow Hydrographs. ............................................................... 54
Figure 4 - 4. Keaau Stream locations from Hawaii State Geographic Information System. .. 55
Figure 4 - 5. 40th Avenue at 1400 Feet North of the Intersection with Pohuku Drive. ......... 56
Figure 4 - 6. 40th Avenue at 1800 Feet South of the Intersection with Pohuku Drive. ......... 56
Figure 4 - 7. The Intersection between the 39th Avenue and Pohaku Drive. .......................... 57
Figure 4 - 8. Keaau Stream before Crossing the Intersection between the 39th Avenue and
Pohaku Drive. ..................................................................................................................................... 57
Figure 4 - 9. Potential Flooding Problem at Hawaiian Acres by HACA. .................................. 60
Figure 4 - 10. Diversionary Structure Layout. ................................................................................ 61
Figure 4 - 11. Photo of Rock Wall. .................................................................................................. 62
Figure 4 - 12. One Section of the Rock Wall. ................................................................................ 62
Figure 4 - 13. Failed Section of Rock Wall. .................................................................................... 63
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Figure 4 - 14. Satellite Image of the Area around the Hydraulic Division System. .................. 64
Figure 4 - 15. Surveyed Hydraulic Structure Locations. ............................................................... 65
Figure 4 - 16. Comparison of Flow Depth Downstream the South Kūlani Bridge. ................ 68
Figure 4 - 17. Flow Surface Elevation in the Case of With- and Without-structure. ............... 69
Figure 4 - 18. Flooded Roads at Puna District. ............................................................................. 70
Figure 4 - 19. Flood Waters Washed Away One Stretch of the Road at Hawaiian Acres. ..... 71
Figure 4 - 20. Flood Waters Washed over the Kukui Camp Road. ............................................ 71
Figure 4 - 21. Field Visit Locations for Storm Event of November 1 to 2, 2000. ................... 73
Figure 4 - 22. Damaged Road Surface at Kuauli Road. ................................................................ 74
Figure 4 - 23. Outflow Boundary Cross-section Locations. ........................................................ 76
Figure 4 - 24. Flood Profile for Keaau Stream. ............................................................................. 78
Figure 4 - 25. Flood Profile for Keaau Stream (continued). ........................................................ 79
Figure 4 - 26. Flood Profile for Keaau Stream (continued). ........................................................ 80
Figure 4 - 27. Flood Profile for Keaau Stream (continued). ........................................................ 81
Figure 4 - 28. Flow Depth for 10-Year Flood. .............................................................................. 82
Figure 4 - 29. Flow Depth for 50-Year Flood. .............................................................................. 83
Figure 4 - 30. Flow Depth for 100-Year Flood. ............................................................................ 84
Figure 4 - 31. Flow depth for 500-Year Flood. ............................................................................. 85
Figure A - 1. FLO-2D Model Subdomains. ................................................................................ A-1
Figure A - 2. Typical 24-hour, 100-year Accumulated Rainfall Distribution. ........................ A-2
Figure B - 1 Hydraulic Structure Survey Points. .......................................................................... B-2
Figure B - 2 Hydraulic Diversion Structures. ............................................................................... B-3
Figure B - 3. Surveyed Cross-sections. .......................................................................................... B-4
Figure B - 4. Surveyed Cross-sections (continued). .................................................................... B-5
Figure B - 5.. Surveyed Cross-sections (continued). ................................................................... B-6
Figure B - 6. Surveyed Cross-sections (continued). .................................................................... B-7
Figure B - 7. Surveyed Cross-sections (continued). .................................................................... B-8
Figure B - 8. Surveyed Cross-sections (continued). .................................................................... B-9
Figure B - 9. Surveyed Cross-sections (continued). .................................................................. B-10
Figure B - 10. Surveyed Cross-sections (continued). ................................................................ B-11
Figure B - 11. Surveyed Cross-sections (continued). ................................................................ B-12
Figure B - 12. Surveyed Cross-sections (continued). ................................................................ B-13
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Figure B - 13. Surveyed Cross-sections (continued). ................................................................ B-14
Figure C- 1. Benchmark for GPS Instrument Error Correction. ............................................. C-1
Figure C- 2. Photo of the Keaa-Pahoa Road Culvert 1. ............................................................. C-2
Figure C- 3. Cross-sections of the Keaa-Pahoa Road Culvert 1. .............................................. C-2
Figure C- 4. Rating Curve of the Keaa-Pahoa Road Culvert 1. ................................................ C-3
Figure C- 5. Keaa-Pahoa Road Culvert 2. .................................................................................... C-3
Figure C- 6. Rating Curve of Keaa-Pahoa Road Culvert 2. ....................................................... C-4
Figure C- 7. Waipahoehoe Stream Bridge. ................................................................................... C-4
Figure C- 8. Rating Curve of Waipahoehoe Stream Bridge. ...................................................... C-5
Figure C- 9. Photo of Moho Road Culvert 1. .............................................................................. C-5
Figure C- 10. Cross-section of Moho Road Culvert 1. ............................................................... C-6
Figure C- 11. Rating Curve of Moho Road Culvert 1. ............................................................... C-6
Figure C- 12. Photo of Moho Road Culvert 2 (Downstream side). ......................................... C-7
Figure C- 13. Cross-section of Moho Road Culvert 2. ............................................................... C-7
Figure C- 14. Rating Curve of Moho Road Culvert 2. ............................................................... C-8
Figure C- 15. Photo of South Kūlani Road Bridge. .................................................................... C-8
Figure C- 16. Cross-section of South Kūlani Road Bridge. ....................................................... C-9
Figure C- 17. Rating Curve of South Kūlani Road Bridge. ....................................................... C-9
Figure C- 18. Photo of Enos Road Culvert. ............................................................................. C-10
Figure C- 19. Cross-section of Enos Road Culvert. ................................................................ C-10
Figure C- 20. Rating Curve of Enos Road Culvert. ................................................................. C-11
Figure C- 21. Cross-section of South Pszyk Road Culvert 1. ................................................. C-11
Figure C- 22. Rating Curve of South Pszyk Road Culvert 1. ................................................. C-12
Figure C- 23. Photo of South Pszyk Road Culvert 2. .............................................................. C-12
Figure C- 24. Cross-section of South Pszyk Road Culvert 2. ................................................. C-13
Figure C- 25. Rating Curve of South Pszyk Road Culvert 2. ................................................. C-13
Figure C- 26. Cross-section of South Kopua Road Bridge..................................................... C-14
Figure C- 27. Rating Curve of South Kopua Road Bridge. .................................................... C-14
Figure C- 28. Cross-section of South Kopua Road Culvert. .................................................. C-15
Figure C- 29. Rating Curve of South Kopua Road Culvert. ................................................... C-15
Figure C- 30. Photo of North Oshiro Road Bridge 2. ............................................................ C-16
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Figure C- 31. Cross-section of North Oshiro Road Bridge 2. ............................................... C-16
Figure C- 32. Rating Curve of North Oshiro Road Bridge 2. ................................................ C-17
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LIST OF TABLES
Table ES-1. Peak Discharges for Storm Events………………………………………….viii
Table 2 - 1. Rain Gages. ...................................................................................................................... 8
Table 3 - 1. Sub-Watersheds, Areas and Centroids. ...................................................................... 18
Table 3 - 2. Sub-watersheds, Junctions, and Drainage Areas of Puna Study Area. .................. 20
Table 3 - 3. Rainfall for Sub-watersheds Extracted from Atlas 14. ............................................ 28
Table 3 - 4. Soil Types in Puna Study Area. ................................................................................... 34
Table 3 - 5. Green-Ampt Infiltration Parameters Determination for Puna Study Area. ......... 37
Table 3 - 6. Average Saturated Hydraulic Conductivities for Sub-watersheds. ........................ 39
Table 3 - 7. Time of Concentration Values for Puna Study Area. .............................................. 42
Table 3 - 8. Gage Depth and Time Weights for November 1 to 2, 2000, Storm. .................... 46
Table 3 - 9. Comparison of Model Results for November 1 to 2, 2000, Storm. ...................... 47
Table 4 - 1 Names of the Surveyed Bridges and Culverts. .......................................................... 66
Table 4 - 2. FLO-2D Model Calibration Results for November 1 to 2, 2000 Storm .............. 72
Table 4 - 3. Boundary Inflow Hydrographs at Cross-sections 1-9. ............................................ 77
Table 4 - 4. FLO-2D Model Result Summary for 10-year Flood Event. .................................. 86
Table 4 - 5. FLO-2D Model Result Summary for 50-year Flood Event. .................................. 87
Table 4 - 6. FLO-2D Model Result Summary for 100-year Flood Event. ................................ 88
Table 4 - 7. FLO-2D Model Result Summary for 500-year Flood Event. ................................ 89
Table A - 1. Rainfall for Each FLO-2D Model Sub-domain. .................................................. A-1
Table A - 2. Puna Study Area FLO-2D Results. ........................................................................ A-3
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LIST OF ABBREVIATIONS
BFE Base Flood Elevation
DLNR Department of Land and Natural Resources, State of Hawaii
DPW Department of Public Works, County of Hawaii
DTM Digital Terrain Model
ESRI "Environmental Systems Research Institute, Inc.
ft feet
ft2 Square Feet
FEMA Federal Emergency Management Agency
FHM Flood Hazard Map
GDS Grid Developer System
GIS Geographic Information Systems
HEC-GeoHMS Hydrologic Engineering Center -Geospatial Hydrologic
Modeling Extension
HEC-HMS Hydrologic Engineering Center Hydrologic Modeling System
hr hour
ID Identification Number
IDF Intensity-Duration-Frequency
in inches
in/hr Inches per hour
Ksat Saturated Hydraulic Conductivity
LIDAR Light Detection and Ranging
mi2 Square Miles
min minute
NCDC National Climatic Data Center
NOAA National Oceanic and Atmospheric Administration
NRCS Natural Resources Conservation Service
NWS National Weather Service
N-SPECT Nonpoint-Source Pollution and Erosion Comparison Tool
OID Operator Interface Device
Ref. Reference
SID Station Identifiers
SCS Soil Conservation Service
Tc Time of Concentration
TIN Triangulated Irregular Network
Tt Travel times
U.S. United States
USACE United States Army Corps of Engineers
USGS United States Geological Survey
yr year
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EXECUTIVE SUMMARY
On November 1 to 2, 2000, a combination of several meteorological and topographic
factors produced extreme rainfall over the eastern part of the Island of Hawai‘i. Storm
rainfall was concentrated in two distinct areas, the Puna and Kapāpala areas, where
maximum rainfall totals of 32.47 and 38.97 inches were recorded (USGS 2000). Resultant
flooding caused damages in excess of 70 million dollars, among the highest totals associated
with flooding in the State’s history. The department of Public Works (DPW), County of
Hawai‘i contracted Oceanit to perform the Puna Flood Study and generate Digital Flood
Insurance Rates Maps (DFIRMs) for the Puna District, County of Hawai‘i.
A hydrologic analysis was conducted using a hydrologic model to provide credible flood
events in terms of the 10%, 2%, 1%, and 0.2% exceedance probabilities (i.e. the 10-, 50-,
100-, and 500-year return period floods) for the Puna District. The rainfall-runoff HEC-
HMS (U.S. Army Corps of Engineers, Version 3.5) model was used in this analysis.
HEC-HMS is a lumped one-dimensional hydrologic model, which is a FEMA approved
hydrology analysis model. Since no stream gage data are available for this study area, a two-
dimensional hydrologic and hydraulic model- FLO-2D model was also developed to verify
the result of the HEC-HMS model. Comparison of results between the two models helped
to build the confidence in the simulation results in this area where no gage records are
available.
The flood discharges calculated from the HEC-HMS hydrologic model were used as input
for the subsequent hydraulic analyses. The results from the FLO-2D model were just used
for comparison purpose only. Table ES-1 shows the peak discharges at nine selected
junctions for storm events in terms of the different return periods. The two models provide
similar and consistent results. Figure ES-1 provides watershed boundaries and junction
locations for the Puna study area.
Using results of hydrology analysis for the Puna area, this study performed hydraulic analyses
for flooding in the Puna area. FEMA’s Guidelines and Specifications for Flood Hazard Mapping
Partners Appendix E: Guidance for Shallow Flooding Analyses and Mapping is followed in the
hydraulic analysis and mapping procedures. A two-dimensional analysis of the flood
inundation at the Puna area was conducted using the FLO-2D flood routing model. This
analysis simulated the 10-, 2-, 1-, and 0.2-percent–annual-chance events based on discharge
hydrographs computed under the hydrologic analyses task.
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Table ES-1. Peak Discharges for Storm Events.
Junctions Description
10- Year
(10% Annual
Chance)
cfs
50- Year
(2% Annual
Chance)
cfs
100- Year
(1% Annual
Chance)
cfs
500- Year
(0.2% Annual
Chance)
cfs
HEC-
HMS
FLO-
2D
HEC-
HMS
FLO-
2D
HEC-
HMS
FLO-
2D
HEC-
HMS
FLO-
2D
J2
Volcano Rd &
Kahaualeale
Rd
9,454 9,596 23,955 22,330 35,157 33,418 46,240 46,266
J3 Near Mauaana
Rd 19,063 17,648 40,749 36,532 59,984 54,024 80,339 74,770
J4 Near Apele
Rd 19,538 17,410 36,533 31,291 45,384 44,008 61,031 63,610
J5 South Kūlani
Rd Bridge 25,024 20,684 45,398 39,041 61,326 51,602 84,906 75,217
J7
Keaau-Pahoa
Rd & Keaau
Bypass Rd
15,187 14,734 30,993 31,463 40,720 40,507 63,826 59,910
J8 Volcano Rd &
Huina Rd 5,859 6,017 12,212 13,046 17,055 16,191 25,270 24,023
J10 Railroad Aves.
& Keaau Rd 1,361 1,248 3,916 3,684 5,539 5,640 11,894 11,935
JK1 Pulelehua Rd
& Poola Rd 1,229 777 8,197 7,360 17,854 16,165 28,551 29,194
J16
Waimakao
Pele Rd &
Pahoehe Rd
241 171 1,035 1,080 2,672 2,608 8,712 8,581
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1 INTRODUCTION
1.1 Background
The Puna area, located between the two volcanoes, Mauna Loa and Kilauea in the Island of
Hawai‘i, is formed by combined volcanic flows both from Mauna Loa and Kilauea. The
altitude within the study area ranges from mean sea level at the coastal areas, to about 5,000
feet at the western boundary near the Mauna Loa Volcano. The entire study area is relatively
flat with average slopes range between 2% to 6%. Since geologically this area is relatively
young and drainage channelization is not well-developed, there is often flooding from
unconfined flows. Flooding damage has mainly been caused by surface sheet flows.
Historically, flash floods are very common at Puna area. The area indexed by Tax Map Key:
1-6, 7, 8 and 9 has had active storm events and substantial property damages in recent years.
On November 1 to 2, 2000, a combination of several meteorological and topographic
factors produced extreme rainfall over the eastern side of Hawai‘i Island. Storm rainfall was
concentrated in two distinct areas, the Puna and Kapāpala areas, where maximum rainfall
totals of 32.47 and 38.97 inches were recorded (USGS 2002). According to USGS (2002),
this storm rainfall had recurrence intervals that were estimated from 25 years to 100 years for
a 24-hour period. Major flooding occurred on the Waiakea and Palai Stream watersheds. The
floodwater impacted the Hilo area causing Hawai‘i County to evacuate over 200 people from
their homes. Resultant flooding caused damages in excess of $70 million, among the highest
associated with flooding in the State’s history.
A study of the hydrologic and hydraulic conditions in the area is essential to assess the flood
hazard in the area and to determine the extent of administrative actions needed to safeguard
life and property. In response to this event, the department of Public Works (DPW), County
of Hawai‘i has contracted Oceanit to perform hydrologic and hydraulic analyses and generate
Digital Flood Insurance Rates Maps (DFIRMs) for the Puna district. This study focused on
the flooding problem at the northern part of the Puna area, and is the first effort to generate
the Digital Flood Insurance Rates Maps (DFIRM) for that part of Puna District, County of
Hawaii.
1.2 Purpose and Scope
The Puna District currently does not have Flood Insurance Rate Maps (FIRMs). The
purpose and scope of the Puna Flood Study is to conduct detailed hydrologic and hydraulic
analyses in watershed and then produce reliable DFIRMs based on the results of these
analyses. The Flood Hazard Maps (FHMs) for the Puna Study area will delineate floodplain
boundaries, providing a valuable planning reference for the county. This flood study
investigates the severity of flood hazards in the northern area of the Puna District and
provides a basis for the administration of the National Flood Insurance Act of 1968 and the
Flood Disaster Protection Act of 1993. This study develops flood risk information that will
be used to establish actual flood insurance rates and assist the community in its effort to
promote sound floodplain management. Minimum floodplain management requirements for
participation in the National Flood Insurance Program (NFIP) are set forth in the Code of
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Federal Regulations (CFR) Title 44, Part 60.3. Coastal flooding analyses were not conducted
as part of this study.
The report documents the hydrologic analyses of the Puna Flood Study Project. Hydrologic
analysis determines the peak discharge-frequency relationships at junctions where flows from
sub-watershed meet. Calculations were made for the northern Puna Study area in terms of
peak flows for flood events that recur at 10-, 50-, 100-, and 500-year periods. These flood
recurrence periods correlate to the exceedance probabilities of 10-, 2-, 1-, and 0.2-percent.
These peak flood discharges were used as input for the subsequent hydraulic analyses.
The report describes the methodology and results of the FLO-2D hydraulic models. The
hydraulic analyses based on numerical models were used to establish flood elevations and
floodways for the project area. A two dimensional flood routing model FLO-2D was used to
simulate flooding caused by 10-, 2-, 1-, and 0.2-percent–annual-chance events.
1.3 Methodology
A rainfall-runoff computer model (HEC-HMS Version 3.5) was utilized and is described in
detail in Section 3. The HEC-HMS model for Puna study area is based on hypothetical
meteorological events to simulate the rainfall in terms of varied return periods in a 24-hour
duration. Precipitation frequency estimates from NOAA Atlas 14 (NOAA 2009) were used
to determine the total cumulative rainfall produced by 10-, 50-, 100-, and 500-year frequency
storms within the study area. As a lumped model, HEC-HMS applied the Green-Ampt
method as its loss method and the Snyder unit hydrograph as its transform method. The
HEC-HMS model for Puna study area used a historical storm event on November 1 and 2,
2000 as a calibration event. Four hypothetical meteorological events (10-, 50-, 100-, and 500-
year frequency storms) were computed to obtain the flood discharges at varied return years.
The flood discharges calculated from the HEC-HMS hydrologic model would be used as
input for the subsequent hydraulic analyses in the hydraulic analysis report.
Due to the lack of stream gage data in the study area, FLO-2D (Version 2009) hydrologic
model was also developed for the comparison purpose. FLO-2D is a distributed rainfall-
runoff model, based on a volume conservation principle that distributes a flood hydrograph
over a system of grid elements. The Green-Ampt loss method was applied to account for
precipitation loss due to infiltration in the FLO-2D model. FLO-2D simulated the surface
runoff by discretizing and solving flow continuity and momentum equations at the grid
elements. FLO-2D model used the same storm rainfall data for its meteorological input as
the HEC-HMS model. Comparison between the two types of the models helps to build
confidence in the simulation results in this study area where no gage records are available.
The results of the FLO-2D model were only used to verify the results of the HEC-HMS
model.
The methodology used in the hydraulic analysis followed the FEMA’s Guidelines and
Specifications for Flood Hazard Mapping Partners - Appendix E: Guidance for Shallow Flooding
Analysis and Mapping. A FEMA approved two-dimensional flood routing model FLO-2D was
used to provide the flood elevations, regulatory floodways, and inundation areas.
Topographic LiDAR data of the study area was used as the digital terrain data set for the
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FLO-2D models. Additional topo data gaps was supplemented with field collected data. The
FLO-2D models used steady state hydrographs from the hydrology analysis of this study to
start the flood routing. The floodplain Manning’s n values were assigned by referring the
land use and land cover information of the Puna District. The entire watershed within the
project area was split into five sub-domains. This provided more computational operable
size for FLO-2D hydraulic modeling. Boundary conditions were generated to transfer flow
hydrographs to downstream sub-domains. Total water volume conservation was tracked for
each sub-model to ensure the accuracy of the FLO-2D models.
1.4 Previous Studies
The following reports and studies contain pertinent historical hydrologic information used
for this study.
1. County of Hawai‘i, Department of Planning. (October 1995). Puna Community
Development Plan. Prepared by Community Management Associates, Inc.
2. County of Hawai‘i, Department of Planning. (November 2005). Puna Regional Circulation
Plan, Final report. Prepared by Townscape, Inc.
3. County of Hawai‘i, Department of Public Works. (March 1974). Mountain View Drainage
Study and Master Plan. Prepared by Austin, Smith & Associates, Inc.
4. County of Hawai‘i, Department of Public Works. (August 1976). Mountain View Drainage
Improvements, Environmental Impact Statement.
1.5 Acknowledgements
Many thanks to the project managers of the County of Hawai‘i, Department of Public
Works, Mr. Frank DeMarco and Mr. Carter Romero for constructive advice and support on
this project. Mahalo to Highway Maintenance Division for helping find historical flooding
locations and identifying the approximate floodwater depths of historical flooding events.
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2 STUDY AREA DESCRIPTION
2.1 Study Area Overview
Puna is one of nine districts in Hawai‘i County and is located on the east side (windward
side) of the Island of Hawai‘i, sharing borders with the South Hilo District to the north and
Ka‘ū District to the west. The Puna District encompasses 499.5 square miles or 319,680
acres. Primary access to the district is from the east-west roadway (Volcano Road) that runs
parallel to the northern boundary of the district. A main branch road at Kea‘au runs south to
access the southern and eastern portions of the district.
The Puna study area is shown in Figure 2 -1. The figure also includes areas from Tax Map
Key maps 1-6, 7, 8, & 9, which in recent years has experienced both active land development
and storm events capable of substantial property damage. The study area for the project
includes the northernmost portion of the Puna District and lies below 5000-feet elevation.
The study area is approximately 282 square miles (mi2), or 180,480 acres, including the
subdivisions of Mountain View, Kurtistown, Kea‘au, Hawai‘i Acres, Orchid Land, Hawaiian
Paradise Park, and Fern Forest.
2.2 Topography, Vegetation, and Land Use
A large fraction of the Puna study area in Puna is characterized by gently sloping topography
with poorly defined waterways. The Puna landscape is formed of porous volcanic rock and
soils from Mauna Loa and Kīlauea volcanic eruptions. An extensive network of subterranean
lava tubes runs throughout much of the study area and are accessible through collapsed
openings (Facts about Puna Hawai‘i 2012).
Vegetation in the study area varies from rain forest to desert shrub and coastal strand. The
historic landscape of Puna was covered with forest, brush, and coastal strand prior to being
transformed into ranchland and sugarcane fields (County of Hawai‘i, Department of
Planning 2005). Between historic lava flows, Puna vegetation started with lichens, ferns, and
shrubs. Historically, this region supported wet and dry taro, banana, sugarcane, sweet potato,
coconut, and breadfruit (Rhodes 2001).
Puna watershed land use is generally zoned as agricultural, residential, open (conservation),
industrial, or commercial (County of Hawai‘i, Department of Planning 2005). Actual land
uses include residential subdivisions, agricultural farms, an industrial park, and several small
commercial service centers.
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2.2.1 Geology and Climate
The Puna region was formed as part of the shield volcano mountain-building process of
Mauna Loa and Kīlauea. Kīlauea is currently active and lava has covered numerous acres of
developed lands within the Puna District in the last thirty years. Recent eruptions have
generally been limited to National Park lands (County of Hawai‘i, Department of Planning
2005). The lava tubes and cave systems of the Puna area are an integral and common
element of extrusive volcanic landscapes in shield volcanoes such as Kīlauea and Mauna Loa.
Although exact numbers cannot be determined, thousands of lava tubes possibly lie within
the pāhoehoe lava flows, and most of these caves are too small to be an important concern
in land planning.
The Puna flood study area is located between two volcanoes, Mauna Loa and Kīlauea, and
formed by lava flows both from Mauna Loa and Kīlauea. The rocks of Kīlauea are divided
into the older Hilina Volcanic Series and the younger Puna Volcanic Series. The Puna Series
overlies Pāhala ash and is correlative with the Ka‘u Series of Mauna Loa. Lava flows of the
Puna and Ka‘u series interfinger along the boundary between the two volcanoes. Both the
Hilina and the Puna Series consist of pāhoehoe and ‘a‘ā lava flows of tholeiitic basalt, olivine
basalt, and oceanite, and associated cinder-and-spatter cones and ash deposits (MacDonald
1983).
The lavas of the Puna Volcanic Series erupted almost entirely from vents in the area of the
present Kīlauea caldera and along two rift zones that extend in an east west direction from
the summit of the volcano (Wright and Fiske 1971). At the top of the Hilina fault scarp,
lavas are only one or two flows thick, but in the cliff at western side of the caldera lava flows
totaling 380 feet thick are exposed. The total thickness of Puna lavas is only a slight bit more
than the thickness now visible in the cliff. Elsewhere, their base is not exposed, and the
thickness is unknown (Wright and Fiske 1971).
The altitude within the study area ranges from mean sea level along the coastal areas to 1,950
feet at Mountain View and approximately 4,950 feet at the western boundary on the slope of
Mauna Loa. The entire study area is relatively flat with the average slope ranging between 2%
to 6% (Facts about Puna Hawai‘i 2012).
Several soil groups are found in the Puna study area. Although all the surface geologic
materials are highly permeable, the different permeabilities of ‘a‘ā lava flows, pāhoehoe lava
flows, and ash are likely to affect infiltration and runoff during rainfall. Stearns and
Macdonald (1946) considered the Pāhala Ash to be generally less permeable than the lava
flows of the Hamakua Volcanics, and suggested that the ash may increase runoff during
storms. Sato et al. (1973) considered pāhoehoe lavas to have low permeability in comparison
to surrounding soils, although they noted that ‘a‘ā lava flows act as ground-water recharge
areas presumably contributing little or no surface runoff. For most soils (Sato et al. 1973),
surface permeability varies from 2.0 to 4.0 in/hr. The permeability of most soils overlaying
ash or pāhoehoe lavas, at depths range from 8 to 72 inches below the land surface, has a
decrease about two orders of magnitude. The parts of the study area are more likely to
generate shallow subsurface flow during heavy rainfall, owing to their decrease in
permeability at shallow depths on steep slopes (Freeze 1974).
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The climate in Puna varies widely due to significant changes in elevation. The study area
stretches from sea level up to about 5,000 feet elevation. The climate in the study area is
tropical with large fluctuations in temperature and rainfall depending on location and
elevation. Temperatures average 67 degrees Fahrenheit (˚F) in Mountain View at the 1,530-
foot elevation and daily temperatures range between 50 and 68 degrees. August and
September are the warmest months, January, February, and March are the coolest (Puna
Weather 2012). Rainfall averages 132 inches per year (Druecher and Fan 1976). June is
usually the driest month, and December is the wettest. However, monthly and annual
rainfalls are very unpredictable, and rainfall in East Hawai‘i can vary by a factor of three
from year to year (60 to 180 inches a year) (Puna Weather 2012). Rainfall averages are higher
at upper elevations and range from 50 inches a year along the southwestern coast to 300
inches in the northern boundary of the Puna District (County of Hawai‘i, Department of
Planning 2005).
2.2.2 Water Resources and Hydrology
Puna’s major potable water source comes from rainwater catchment. County water is
available in some areas, usually located close to the highways. Puna’s abundant rainfall and
the absence of sediment load create high-quality groundwater (Facts about Puna Hawai‘i
2012).
High rainfall, particularly in the upper elevations, contributes to the abundant water
resources that can be found throughout the area (Facts about Puna Hawai‘i 2012). Due to
the high permeability of the rocks and soils, there are no well-defined perennial streams in
the study area (Oki 2003).
2.3 Hydrologic Data
The character of the land, historical rainfall data, and historical stream flow data are relevant
to the hydrological analysis of the Puna study area. Data used for analysis included rainfall
gage data, records of historical storm events, and field surveys. Stream flow gage data are not
available in this region. Rainfall intensity-frequency-duration (IDF) relationships were
determined from this raw data. The rainfall data is used for meteorological input in the
hydrological rainfall-runoff models discussed in Section 3.
2.3.1 Rain Gages
Critical rainfall data, obtained for this study from gages throughout the Puna study area, was
use for hydrological analysis purposes. According to the State Geographic Information
Systems (GIS) program (http://www.state.hi.us/dbedt/gis/), up to 30 rain gages are in the
study area, however only a few of them are currently active. In total, five gages owned by the
National Weather Service were used for calibration of the hydrologic analysis. Rain gages
with available historical precipitation data for the storm on November 1 and 2, 2000, are:
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Gage HI81, Mountain View
Gage HI-83 Pāhoa Rain Gage
Gage HI-91 Piihonua Rain Gage
Gage HI-92 Waiākea Uka Rain Gage
Gage HI-94 Glenwood Rain gage
Table 2-1 and Figure 2-2 provide the names, locations, elevations, and identification
numbers for these rain gages. These rainfall gages record either daily total measurements or
real-time measurements at 15-minute time intervals.
Table 2 - 1. Rain Gages.
SID OID LATITUDE LONGITUDE ELEVATION
(feet)
Glenwood GLNH1 HI-94 19.508N -155.171W 2,632
Mountain View MTVH1 HI-81 19.549N -155.110W 1,519
Pahoa PHAH1 HI-83 19.541N -154.973W 487
Piihonua PIIH1 HI-91 19.710N -155.139W 974
Waiakea Uka WKAH1 HI-92 19.659N -155.128W 997
2.3.2 Stream Gages
There are no stream gages located in the study area.
2.3.3 Field Survey
Field surveys were conducted by Oceanit to locate and verify stream conditions that may
lead to flooding. Locations and sizes of the drainage pipes were noted for drainage analysis
purposes. Field surveys verified drainage inlet points, possible constriction points, overflow
points, and a flood diversion structure near South Kūlani Road. Hydraulic structures were
also measured for the subsequent hydraulic analysis.
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2.4 Flooding Problems in the Study Area
Information in the Puna Community Development Plan (County of Hawai‘i 1995) identified
subdivisions in Glenwood on the Mauna Loa side of Highway 11 (Hawaii Belt Road)
including Orchid Isle, Aloha, Glenwood, and Pacific Paradise Mountain View Manor are
areas that are particularly subject to flooding, because of high rainfall and low permeability
ash clay soil. Roads have incurred flooding damage repeatedly. The cost for drainage
improvements, to mitigate flooding for permitted development, is expected to be prohibitive
(County of Hawai‘i 1995). The most severe flooding event in the Puna study area occurred
during November 1 and 2, 2000. Prolonged and intensive rain fell in two separate areas of
the Hawaii Island: the Waiakea area and the Kapāpala area.
The Puna flood study area, which extends from about Pāpa‘ikou on the north to Glenwood
on the south and from sea level to the altitude of approximately 4,000 ft, is located in the
Waiākea High-rainfall area (USGS 2002). Because of the high rainfall and ash clay soil, the
subdivisions in Glenwood on the Mauna Loa side of Highway 11 including Orchid Isle,
Aloha, Glenwood, and Pacific Paradise Mountain View Manor are particularly subject to
flooding (County of Hawai‘i, Department of Public Works 1976). Roads have been washed
out repeatedly. There is no clearly defined drainage ways within the study area (County of
Hawai‘i, Department of Public Works 1974).
2.5 South Kūlani Flood Diversion Structure
The South Kūlani Flood Diversion Structure is a V-shape flow split dike with a series of
guiding walls, totaling over one half mile in length. This structure channels water into
Hawaiian Acres starting at the South Kūlani Road Bridge. The depth of water along the
structure, in Hawaiian Acres and Orchid Isle areas, can exceed five feet during heavy rainfall
events. According to the residents, the structure was built by ‘Ōla‘a Sugar Company in 1938
to divert floodwater away from sugar cane fields along the Mauna Loa/Kīlauea boundary
into what was then called “wasteland” owned by W.H. Shipman (Puna Community
Development Plan 1995). The structure consisted of a cemented stone wall, which crosses
five lots in Hawaii Acres. The wall is overgrown with strawberry, guava, and other plants.
Portions of the wall are significantly damaged because of tree roots and lack of maintenance.
In 1979, debris blocked the flow under South Kūlani Bridge, diverting floodwaters away
from the wall to what may have been the original drainage channel (Puna Community
Development Plan 1995).
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3 HYDROLOGIC ANALYSIS
3.1 HEC-HMS Model Overview
The U.S. Army Corps Hydrologic Modeling System (HEC-HMS) is designed to simulate the
precipitation-runoff processes of dendritic watershed systems. This model is a one
dimensional precipitation-runoff process model which includes a basin model, a
meteorological model, and a control model.
Covering the project watershed area, a basin model was built based on the sub-watershed
delineations. In this study, the final basin model consisted of 39 sub-watersheds. Key
parameters of the basin model were based on acceptable methodologies of hydrologic
analysis. The Green-Ampt infiltration method was used as the loss method, and the Snyder
Unit Hydrograph method was the transform method used for creating peak discharges and
relevant hydrographs. The NRCS TR-55 model was used to determine the parameters for
the time of concentration (Tc). Channel routing through reaches was done by the Kinematic
Wave method to account for peak flow attenuation. A total of 20 stream reaches were
modeled using the Kinematic Wave routing method to simulate open channel flow within
the simulated stream channels and their banks. The parameters of length, slope, and shape
for each reach were determined based upon topographic data, field survey, and satellite
imagery. The Manning’s n values for stream channel and its banks were determined using
Chow’s (1959) guidelines and actual channel conditions.
The meteorological model used historical storm hydrographs for calibration and frequency-
based rainfall to compute the synthetic flood events. For creating the peak discharges of
varied return periods, the frequency storm with an intensity position at the 50% time period
was used in computing the peaks and hydrographs.
The control model set the computation parameters such as starting time, ending time, and
time interval. This model used a 15-minute computation interval for calibration and a 5-
minute interval for frequency storm computations.
3.2 Geospatial Information Used
Geospatial information and field survey observations were used to determine the
hydrological conditions, such as the terrain roughness characteristics and the stream channel
cross-section shapes. Information collected includes LiDAR data and aerial maps.
LiDAR data was used as original input using ArcView 3.3 with the HEC-GeoHMS 1.1
extension to create a geospatial model of the Puna watershed. The HEC-GeoHMS model
was the tool to delineate the initial sub-watershed boundaries, calculate sub-watershed areas,
and to determine flow path lengths and slopes. NOAA’s Nonpoint Source Pollution and
Erosion Comparison Tool (N-SPECT) was also used to delineate the watershed. N-SPECT
is an extension to Environmental Systems Research Institute’s (ESRI) ArcGIS software
package, version 9.x, and requires ESRI’s Spatial Analyst extension. N-SPECT is designed to
provide the user access to the necessary data. The final sub-watershed delineation was a
combination of results of HEC-GeoHMS and the N-SPECT models. Figure 3-1 shows the
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delineated sub-watersheds of the Puna study area. The centroids of each sub-watershed are
shown in Figure 3-2. The sub-watersheds, their areas, and their centroids are listed in Table
3-1.
After the sub-watersheds were delineated, the layout and structure of the HEC-HMS model
were developed. Figure 3-3 shows the HEC-HMS model layout. The letter “J” refers to
junctions in the model and the letter “R” refers to reaches in the model. Figure 3-4 displays
the same HEC-HMS model layout but rearranges the sub-watershed positions for a clearer
illustration of the model structure. A total of 23 junctions are in the HEC-HMS model.
These junctions are listed in Table 3-2, which also shows the sub-watersheds and associated
drainage areas for each junction. Nine major junctions were selected to summarize the peak
discharges of the HEC-HMS model and also used to compare the peak discharges of the
HEC-HMS model with the results of another hydrologic model (FLO-2D model). These
nine junctions of interest are shown in Figure 3-5.
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Table 3 - 1. Sub-Watersheds, Areas and Centroids.
Sub-Watershed Area (mi2) Centroid Point
Longitude Latitude
29 7.982 -155.229W 19.446N
30 0.156 -155.182W 19.464N
34 4.676 -155.126W 19.448N
35 5.462 -155.107W 19.445N
37 4.188 -155.219W 19.478N
38 10.575 -155.262W 19.471N
39 6.322 -155.169W 19.469N
42 4.47 -155.134W 19.507N
43 9.968 -155.175W 19.490N
45 1.643 -155.219W 19.499N
47 6.909 -155.221W 19.511N
49 8.748 -155.001W 19.488N
50 11.267 -155.042W 19.468N
52 7.673 -155.211W 19.522N
54 4.147 -155.115W 19.528N
56 13.594 -155.221W 19.534N
58 0.378 -155.101W 19.547N
60 22.874 -155.129W 19.477N
64 5.449 -155.074W 19.544N
65 2.753 -154.968W 19.541N
66 17.86 -155.040W 19.502N
69 12.826 -155.168W 19.557N
70 10.425 -155.182W 19.564N
71 1.147 -154.931W 19.579N
74 3.414 -154.947W 19.573N
80 5.492 -155.091W 19.564N
81 2.883 -155.065W 19.598N
82 16.042 -155.021W 19.548N
84 9.195 -155.029W 19.582N
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Sub-Watershed Area (mi2)
Centroid Point
Longitude Latitude
89 8.656 -154.966W 19.599N
93 8.862 -155.110W 19.595N
96 1.456 -155.022W 19.616N
99 7.239 -155.096W 19.611N
102 3.132 -154.996W 19.623N
108 3.979 -155.042W 19.630N
110 3.428 -155.005W 19.642N
112 5.449 -154.997W 19.667N
115 9.23 -155.032W 19.667N
117 8.502 -155.025W 19.695N
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Table 3 - 2. Sub-watersheds, Junctions, and Drainage Areas of Puna Study Area.
Sub-watershed/Junction ID Drainage Area (mi2)
Middle Sub-domain
Subwatershed 29 29 7.871
Subwatershed 38 38 10.500
Junction 1 J1 18.370
Subwatershed 30 30 0.156
Subwatershed 37 37 4.188
Junction 2 J2 22.714
Subwatershed 39 39 6.351
Subwatershed 42 42 4.491
Subwatershed 43 43 9.906
Junction 3 J3 43.462
Subwatershed 45 45 1.593
Subwatershed 47 47 6.857
Junction 4 J4 51.912
Subwatershed 52 52 7.644
Subwatershed 56 56 13.473
Junction 6 J6 21.117
Subwatershed 54 54 4.147
Subwatershed 58 58 0.378
Junction 5 J5 77.554
Subwatershed 69 69 12.785
Subwatershed 70 70 10.367
Junction 8 J8 23.151
Subwatershed 80 80 5.492
Subwatershed 81 81 2.883
Junction 7 J7 109.080
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Sub-watershed/Junction ID Drainage Area (mi2)
Subwatershed 93 93 8.722
Subwatershed 99 99 6.941
Junction 10 J10 15.663
Subwatershed 96 96 1.456
Subwatershed 108 108 3.979
Junction 9 J9 130.179
Subwatershed 110 110 3.429
Junction 11 J11 133.607
Subwatershed 60 60 22.792
Subwatershed 64 64 5.449
Junction K1 JK1 28.241
Subwatershed 82 82 16.042
Subwatershed 84 84 9.195
Junction K2 JK2 53.478
Subwatershed 102 102 3.131
Junction K3 JK3 56.609
South Sub-domain
Subwatershed 34 34 4.660
Subwatershed 35 35 5.419
Junction 16 J16 10.079
Subwatershed 49 49 8.644
Subwatershed 50 50 11.160
Junction 19 J19 19.804
Subwatershed 65 65 2.753
Subwatershed 66 66 17.860
Junction 17 J17 50.497
Subwatershed 74 74 3.352
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Junction 18 J18 53.849
Sub-watershed/Junction ID Drainage Area (mi2)
Subwatershed 71 71 1.037
Junction 20 J20 1.037
Subwatershed 89 89 8.660
Junction 15 J15 8.660
North Sub-domain
Subwatershed 112 112 5.466
Junction 14 J14 5.466
Subwatershed 115 115 9.147
Junction 13 J13 9.147
Subwatershed 117 117 7.622
Junction 12 J12 7.622
3.3 Meteorological Events
The Puna HEC-HMS model is based on hypothetical meteorological events to simulate the
rainfall in terms of varied return periods in a 24-hour duration. Precipitation frequency
estimates from NOAA Atlas 14 (NOAA 2009) were used to determine the total cumulative
rainfall produced by 10-, 50-, 100-, and 500-year frequency storms in the study area. Atlas 14
contains precipitation frequency estimates for the United States and U.S. affiliated territories
(Perica, et al. 2009). The precipitation in the centroid of a particular sub-watershed was
applied to the entire sub-watershed uniformly. The precipitation values used for the 10-, 50-,
100-, and 500-year return storm events in a 24-hour were plotted in Figures 3-6 through 3-9.
The number in each sub-watershed is the rainfall value that was used. The Rainfall values
that were extracted from Atlas 14 for various storm return periods and durations for each
sub-watershed are listed in Table 3-3.
With the IDF for each sub-watershed available (Table 3-3), hyetographs were generated
using the HEC-HMS frequency storm method with an intensity position at 50%. Figure 3-10
shows a typical 24-hour, 100-year accumulated hyetograph for a sub-watershed.
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Figure 3 - 10. Designed 100-year 24-hour Rainfall Distribution for Sub-watershed 43
(Typical Hyetograph).
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Table 3 - 3. Rainfall for Sub-watersheds Extracted from Atlas 14.
Sub-
water-
shed
ARI
(years) 5-min 10-min 15-min 30-min 1-hr 2-hr 3-hr 6-hr 12-hr 24-hr
29
10 0.85 1.16 1.45 2.15 3.1 4.7 5.67 7.72 10.34 13.44
50 1.08 1.48 1.85 2.75 3.96 6.16 7.47 10.3 14.02 18.45
100 1.14 1.56 1.95 2.88 4.16 6.26 7.81 11.15 15.79 21.85
500 1.39 1.9 2.38 3.52 5.08 7.59 9.48 13.68 19.36 26.85
30
10 1.07 1.47 1.84 2.72 3.93 5.81 7.04 9.43 12.64 16.47
50 1.36 1.86 2.33 3.46 4.99 7.48 9.12 12.44 16.91 22.32
100 1.48 2.03 2.54 3.76 5.43 8.2 10.02 13.74 18.79 24.89
500 1.77 2.43 3.04 4.5 6.49 9.87 12.12 16.85 23.27 31.09
34
10 0.94 1.29 1.61 2.39 3.44 5.09 6.17 8.54 11.7 15.48
50 1.19 1.63 2.04 3.02 4.36 6.57 8.03 11.32 15.75 21.11
100 1.29 1.77 2.22 3.29 4.74 7.21 8.84 12.55 17.57 23.65
500 1.53 2.1 2.63 3.89 5.62 8.69 10.72 15.5 22.02 29.9
35
10 0.92 1.26 1.58 2.34 3.38 5 6.07 8.41 11.54 15.31
50 1.17 1.6 2 2.97 4.28 6.46 7.9 11.15 15.56 20.89
100 1.27 1.74 2.18 3.23 4.65 7.09 8.69 12.37 17.36 23.41
500 1.5 2.06 2.58 3.82 5.51 8.54 10.55 15.28 21.75 29.6
37
10 0.97 1.32 1.66 2.45 3.54 5.25 6.4 8.67 11.8 13.21
50 1.24 1.69 2.12 3.14 4.53 6.78 8.32 11.46 15.77 21.12
100 1.35 1.85 2.31 3.42 4.94 7.43 9.14 12.65 17.48 23.49
500 1.62 2.23 2.79 4.12 5.95 8.94 11.03 15.47 21.5 29.07
38
10 0.69 0.94 1.18 1.75 2.52 3.78 4.7 6.78 9.74 13.57
50 0.9 1.23 1.54 2.28 3.29 4.95 6.19 9.06 13.1 18.38
100 0.98 1.35 1.68 2.49 3.6 5.43 6.81 10.02 14.52 20.41
500 1.19 1.62 2.03 3.01 4.34 6.54 8.23 12.26 17.78 25.08
39
10 1.06 1.45 1.81 2.68 3.87 5.72 6.92 9.33 12.54 16.37
50 1.34 1.83 2.29 3.4 4.9 7.37 8.98 12.31 16.81 22.23
100 1.46 1.99 2.49 3.69 5.33 8.07 9.86 13.62 18.7 24.82
500 1.73 2.38 2.97 4.4 6.35 9.72 11.94 16.73 23.24 31.13
42
10 1.09 1.5 1.88 2.78 4.01 5.92 7.15 9.59 12.84 16.7
50 1.38 1.89 2.37 3.51 5.06 7.61 9.27 12.64 17.18 22.66
100 1.5 2.06 2.58 3.81 5.5 8.33 10.17 13.97 19.09 25.29
500 1.79 2.45 3.07 4.54 6.56 10.01 12.29 17.13 23.68 31.68
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Sub-
water-
shed
ARI
(years) 5-min 10-min 15-min 30-min 1-hr 2-hr 3-hr 6-hr 12-hr 24-hr
43
10 1.04 1.43 1.78 2.64 3.81 5.62 6.82 9.17 12.35 16.17
50 1.32 1.81 2.26 3.35 4.84 7.23 8.84 12.08 16.49 21.89
100 1.44 1.97 2.46 3.65 5.26 7.91 9.7 13.33 18.28 24.36
500 1.72 2.35 2.94 4.36 6.29 9.49 11.68 16.27 22.51 30.24
45
10 0.97 1.34 1.67 2.48 3.57 5.29 6.4 8.77 11.92 15.72
50 1.23 1.69 2.11 3.12 4.51 6.82 8.32 11.6 16.02 21.42
100 1.34 1.83 2.29 3.39 4.9 7.48 9.14 12.84 17.85 23.98
500 1.58 2.17 2.71 4.01 5.79 8.99 11.07 15.8 22.28 30.25
47
10 1.08 1.48 1.85 2.74 3.95 5.83 7.05 9.46 12.67 16.55
50 1.36 1.87 2.34 3.46 5 7.48 9.12 12.44 16.91 22.4
100 1.48 2.03 2.54 3.76 5.43 8.18 9.99 13.72 18.75 24.94
500 1.76 2.42 3.02 4.48 6.46 9.79 12.02 16.73 23.09 31
49
10 0.85 1.17 1.46 2.16 3.11 4.74 5.71 7.71 10.2 13.14
50 1.09 1.49 1.86 2.76 3.98 6.23 7.54 10.3 13.87 18.07
100 1.18 1.62 2.03 3 4.34 6.86 8.33 11.43 15.52 20.31
500 1.41 1.93 2.41 3.57 5.15 8.37 10.21 14.17 19.61 25.88
50
10 0.88 1.21 1.51 2.23 3.23 4.84 5.86 8.05 10.91 14.35
50 1.12 1.53 1.92 2.85 4.11 6.31 7.69 10.72 14.76 19.66
100 1.22 1.67 2.09 3.1 4.47 6.94 8.48 11.89 16.49 22.05
500 1.45 1.98 2.48 3.68 5.3 8.42 10.34 14.71 20.74 27.99
52
10 1.13 1.55 1.94 2.87 4.14 6.09 7.37 9.86 13.15 17.12
50 1.42 1.95 2.44 3.62 5.22 7.81 9.52 12.95 17.55 23.19
100 1.54 2.12 2.65 3.92 5.66 8.54 10.43 14.29 19.46 25.84
500 1.83 2.51 3.14 4.65 6.72 10.22 12.54 17.43 24.02 32.22
54
10 0.91 1.25 1.56 2.31 3.33 4.96 6 8.29 11.34 14.98
50 1.15 1.57 1.97 2.91 4.2 6.4 7.8 10.97 15.27 20.45
100 1.24 1.7 2.13 3.16 4.56 7.01 8.58 12.15 17.02 22.93
500 1.47 2.01 2.52 3.72 5.37 8.42 10.38 14.96 21.29 29.03
56
10 1.1 1.51 1.89 2.79 4.03 5.92 7.17 9.65 12.93 16.95
50 1.39 1.9 2.38 3.52 5.07 7.59 9.26 12.68 17.25 22.95
100 1.5 2.06 2.57 3.81 5.5 8.29 10.14 13.97 19.13 25.57
500 1.77 2.43 3.04 4.5 6.5 9.89 12.16 17 23.56 31.84
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Sub-
water-
shed
ARI
(years) 5-min 10-min 15-min 30-min 1-hr 2-hr 3-hr 6-hr 12-hr 24-hr
58
10 0.89 1.22 1.52 2.25 3.25 4.83 5.85 8.1 11.1 14.66
50 1.12 1.53 1.92 2.84 4.1 6.24 7.61 10.71 14.94 20.02
100 1.21 1.66 2.08 3.08 4.44 6.83 8.36 11.86 16.66 22.45
500 1.43 1.95 2.44 3.62 5.22 8.19 10.11 14.61 20.85 28.44
60
10 0.94 1.29 1.61 2.38 3.44 5.08 6.17 8.52 11.65 15.41
50 1.19 1.63 2.04 3.02 4.36 6.57 8.03 11.28 15.69 21.02
100 1.29 1.77 2.22 3.28 4.74 7.2 8.82 12.51 17.5 23.55
500 1.53 2.1 2.62 3.89 5.61 8.67 10.71 15.44 21.92 29.76
64
10 0.89 1.21 1.52 2.25 3.25 4.85 5.87 8.12 11.07 14.58
50 1.12 1.54 1.92 2.85 4.11 6.3 7.67 10.78 14.96 19.98
100 1.22 1.67 2.09 3.09 4.46 6.91 8.44 11.95 16.7 22.43
500 1.44 1.97 2.46 3.65 5.27 8.34 10.25 14.74 20.96 28.48
65
10 0.83 1.14 1.43 2.11 3.05 4.63 5.57 7.55 10.03 12.99
50 1.07 1.46 1.83 2.71 3.91 6.1 7.38 10.12 13.69 17.94
100 1.17 1.6 2 2.96 4.27 6.73 8.17 11.25 15.35 20.2
500 1.39 1.9 2.38 3.53 5.09 8.23 10.06 14.01 19.48 25.85
66
10 0.87 1.19 1.49 2.21 3.18 4.79 5.79 7.93 10.69 13.98
50 1.11 1.51 1.9 2.81 4.05 6.26 7.61 10.57 14.49 19.19
100 1.2 1.65 2.06 3.06 4.41 6.89 8.4 11.73 16.2 21.56
500 1.43 1.95 2.44 3.62 5.22 8.36 10.25 14.52 20.41 27.44
69
10 1.04 1.43 1.79 2.65 3.83 5.67 6.85 9.35 12.59 16.54
50 1.31 1.8 2.25 3.34 4.82 7.3 8.89 12.33 16.89 22.53
100 1.43 1.95 2.44 3.62 5.22 7.99 9.76 13.63 18.79 25.21
500 1.68 2.31 2.89 4.27 6.17 9.6 11.79 16.71 23.4 31.81
70
10 1.06 1.45 1.82 2.69 3.88 5.74 6.95 9.47 12.76 16.79
50 1.33 1.83 2.29 3.39 4.89 7.39 9.02 12.48 17.11 22.85
100 1.45 1.98 2.48 3.67 5.3 8.09 9.9 13.79 19.03 25.57
500 1.71 2.34 2.93 4.34 6.26 9.72 11.95 16.9 23.68 32.22
71
10 0.8 1.1 1.38 2.04 2.94 4.44 5.34 7.28 9.77 12.69
50 1.03 1.41 1.76 2.6 3.76 5.83 7.05 9.75 13.31 17.5
100 1.12 1.53 1.92 2.84 4.09 6.43 7.8 10.84 14.92 19.7
500 1.33 1.82 2.28 3.37 4.86 7.83 9.55 13.46 18.88 25.18
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Sub-
water-
shed
ARI
(years) 5-min 10-min 15-min 30-min 1-hr 2-hr 3-hr 6-hr 12-hr 24-hr
74
10 0.81 1.12 1.4 2.07 2.98 4.51 5.42 7.4 9.92 12.88
50 1.04 1.43 1.79 2.65 3.82 5.92 7.17 9.91 13.52 17.76
100 1.14 1.56 1.95 2.88 4.16 6.53 7.92 11.01 15.14 19.99
500 1.35 1.85 2.31 3.42 4.94 7.96 9.71 13.67 19.17 25.55
80
10 0.89 1.22 1.52 2.26 3.26 4.86 5.87 8.14 11.14 14.69
50 1.12 1.54 1.93 2.85 4.12 6.29 7.66 10.79 15.03 20.12
100 1.22 1.67 2.09 3.1 4.47 6.89 8.43 11.96 16.77 22.57
500 1.44 1.97 2.46 3.65 5.26 8.3 10.21 14.74 21.02 28.65
81
10 0.89 1.22 1.52 2.25 3.25 4.84 5.85 8.14 11.11 14.61
50 1.13 1.55 1.94 2.87 4.13 6.32 7.69 10.86 15.09 20.13
100 1.23 1.68 2.11 3.12 4.5 6.95 8.48 12.06 16.88 22.65
500 1.45 1.99 2.49 3.69 5.32 8.43 10.33 14.93 21.27 28.93
82
10 0.86 1.18 1.47 2.18 3.15 4.75 5.73 7.83 10.52 13.68
50 1.1 1.5 1.88 2.79 4.02 6.23 7.55 10.46 14.3 18.84
100 1.2 1.64 2.05 3.03 4.38 6.86 8.34 11.62 16 21.18
500 1.42 1.94 2.43 3.6 5.19 8.34 10.19 14.4 20.21 27.03
84
10 0.87 1.19 1.48 2.2 3.17 4.74 5.72 7.9 10.75 14.06
50 1.1 1.51 1.89 2.8 4.04 6.21 7.53 10.56 14.62 19.39
100 1.2 1.65 2.06 3.05 4.4 6.83 8.31 11.73 16.36 21.82
500 1.42 1.95 2.44 3.62 5.22 8.3 10.15 14.54 20.66 27.89
89
10 0.82 1.13 1.41 2.09 3.02 4.54 5.46 7.48 10.12 13.18
50 1.05 1.44 1.8 2.67 3.86 5.96 7.21 10.03 13.8 18.21
100 1.15 1.57 1.97 2.91 4.2 6.57 7.97 11.15 15.46 20.51
500 1.36 1.87 2.33 3.46 4.99 8 9.75 13.85 19.57 26.27
93
10 0.92 1.25 1.57 2.32 3.35 5 6.05 8.42 11.5 15.18
50 1.16 1.59 1.99 2.94 4.24 6.48 7.9 11.17 15.52 20.8
100 1.26 1.72 2.15 3.19 4.6 7.11 8.7 12.38 17.32 23.34
500 1.48 2.03 2.54 3.76 5.42 8.58 10.54 15.24 21.7 29.66
96
10 0.86 1.19 1.48 2.2 3.17 4.72 5.69 7.89 10.79 14.14
50 1.11 1.51 1.9 2.81 4.05 6.19 7.51 10.57 14.71 19.57
100 1.21 1.65 2.07 3.06 4.42 6.82 8.3 11.76 16.49 22.06
500 1.43 1.96 2.45 3.63 5.24 8.3 10.15 14.62 20.89 28.31
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Sub-
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shed
ARI
(years) 5-min 10-min 15-min 30-min 1-hr 2-hr 3-hr 6-hr 12-hr 24-hr
99
10 0.91 1.24 1.56 2.31 3.33 4.96 6.01 8.38 11.44 15.06
50 1.15 1.58 1.98 2.92 4.22 6.46 7.87 11.13 15.46 20.69
100 1.25 1.71 2.15 3.18 4.58 7.1 8.67 12.34 17.27 23.25
500 1.48 2.02 2.53 3.75 5.41 8.58 10.53 15.22 21.68 29.6
102
10 0.85 1.17 1.46 2.16 3.12 4.67 5.62 7.73 10.58 13.83
50 1.09 1.49 1.87 2.76 3.99 6.13 7.42 10.37 14.43 19.16
100 1.19 1.62 2.03 3.01 4.35 6.75 8.2 11.54 16.18 21.6
500 1.41 1.93 2.41 3.57 5.16 8.21 10.02 14.34 20.5 27.72
108
10 0.87 1.19 1.49 2.21 3.19 4.74 5.72 7.95 10.88 14.28
50 1.11 1.52 1.91 2.83 4.08 6.22 7.56 10.67 14.86 19.81
100 1.22 1.66 2.08 3.08 4.45 6.85 8.36 11.87 16.67 22.35
500 1.44 1.98 2.47 3.66 5.28 8.34 10.23 14.78 21.13 28.71
110
10 0.85 1.16 1.46 2.16 3.11 4.65 5.6 7.73 10.58 13.87
50 1.09 1.49 1.86 2.76 3.98 6.09 7.38 10.37 14.46 19.24
100 1.19 1.62 2.03 3.01 4.34 6.71 8.16 11.55 16.22 21.71
500 1.41 1.93 2.41 3.57 5.16 8.17 9.99 14.39 20.58 27.9
112
10 0.83 1.14 1.43 2.11 3.05 4.55 5.48 7.57 10.39 13.58
50 1.06 1.46 1.83 2.7 3.9 5.97 7.24 10.15 14.19 18.82
100 1.16 1.59 1.99 2.95 4.25 6.58 8 11.29 15.91 21.22
500 1.38 1.89 2.36 3.49 5.04 8.01 9.78 14.03 20.15 27.24
115
10 0.84 1.15 1.44 2.13 3.08 4.59 5.53 7.68 10.58 13.84
50 1.07 1.47 1.84 2.73 3.94 6.02 7.3 10.29 14.43 19.15
100 1.17 1.6 2.01 2.97 4.29 6.64 8.06 11.44 16.16 21.59
500 1.39 1.9 2.38 3.52 5.08 8.07 9.85 14.2 20.45 27.68
117
10 0.82 1.13 1.41 2.09 3.02 4.5 5.42 7.54 10.46 13.63
50 1.05 1.44 1.8 2.67 3.85 5.91 7.15 10.1 14.23 18.82
100 1.15 1.57 1.96 2.91 4.19 6.51 7.89 11.21 15.93 21.19
500 1.35 1.85 2.32 3.44 4.96 7.92 9.61 13.87 20.11 27.1
3.4 Basin Loss
Basin loss was estimated using the Green-Ampt infiltration method. The parameters of the
Green-Ampt method were determined from several references. These were: (1) Application of
the Green-Ampt Infiltration Equation to Watershed Modeling. Water Resources Bulletin, Vol. 28
(James et al. 1992); (2) Fullerton’s Master Thesis, Colorado State University (1983);
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(3) USACE Technical Engineering and Design Guide, No. 19 (1997). Several justifications are
described as follows:
i. Saturated Soil Conductivity (Ksat)
The most important parameter is the saturated hydraulic conductivity. The soil
conductivity depends on soil types. Soil types in the Puna study area are listed in
Table 3-4 and shown in Figure 3-11. Lau and Mink (2006) pointed out that the
values of saturated hydraulic conductivity in Hawai‘i’s soils are typically a few inches
per day. Rocky mucks are thin soil layers on unweathered pāhoehoe or ‘a‘ā. The Ksat
of the rock is very low except where there are fractures. These fractures would be
plugged with the muck resulting in lower soil permeability which inhibits flow and
the effect the fractures. It is assumed that ‘a‘ā would have high Ksat value, and the
initial Ksat value was set at the maximum of 10 in/hr. Unweathered pāhoehoe with
no soil would have lower permeability, but will increase with fractures. The stony
clay loams were slightly more permeable than the clay loams. Figure 3-12 shows the
saturated soil conductivities of Puna study area
ii. Porosity
Soil porosities range from a 0.08 for agriculture land to more than 0.7 for forest area
soils. Rocky mucks are thin soil layers on unweathered pāhoehoe or ‘a‘ā. It is
reasonable to assume that the porosity is a combination of both soil and rock
porosities. The porosity of the rock is about 0.1 and the porosity of the soil is much
higher. The usable porosity of the rock is about 0.1, but fractures near the surface
may increase this porosity to about 0.2.
iii. Impervious
The Puna study area is mostly undeveloped. The roofs of structures, roadways and
other hard surface areas are negligible. The impervious values are set as zero.
iv. Soil Suction
Soil suction assumed to be the canopy interception storage. Soil suction is a function
of vegetation type. The rain can be stored from a particular event. The value
selected was based on Fullerton’s estimate for Forest Floor.
v. Soil Moisture Deficit
The soil moisture deficit is a rough estimate base on the FLO-2D manual (2006)
Table 5. The soil moisture deficit used in HEC-HMS model was 0.3 for most soil
types, which was implemented by an initial content 0.16 and a saturated content 0.46.
This assumes that the soil retains a certain level of moisture. ‘A‘ā and pāhoehoe soils
retain less because they are fractured and subject to solar drying.
Table 3-5 gives Green-Ampt infiltration parameters determination for Puna Study Area. The
Green-Ampt parameters for each sub-watershed were calculated by averaging the values
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from a GIS shape file containing the data of the infiltration parameters. Table 3-6 shows the
average saturated hydraulic conductivities for each sub-watershed.
Table 3 - 4. Soil Types in Puna Study Area.
NRCS
Description Soil Type Percent Slopes Area (acres)
Akc ‘Akaka silty clay loam 0 to 10 19,969
HIC Hīlea silty clay loam 6 to 12 4,354
HoC Hilo silty clay loam 0 to 10 753
HoD Hilo silty clay loam 10 to 20 34
rKAD Kahalu‘u extremely rocky muck 6 to 20 1,638
rKFD Keaukaha extremely rocky muck 6 to 20 7,634
rKGD Ke‘ei extremely rocky muck 6 to 20 32,639
rKHD Kekake extremely rocky muck 6 to 20 88
rKXD Kīloa extremely stony muck 6 to 20 10,028
rLLD Lalaau extremely stony muck 6 to 20 3,219
rLV Lava flows, ‘a‘ā - 91
rLW Lava flows,pāhoehoe - 50,363
rMUB Manu silt loam 2 to 6 1,149
OSD ‘Ōhi‘a extremely stony silty clay loam 0 to 20 4,068
OHC ‘Ōhi‘a silty clay loam 0 to 10 6,580
OID ‘Ōla‘a extremely stony silty clay loam 0 to 20 1,549
OaC ‘Ōla‘a silty clay loam 0 to 10 1,990
rOPE ‘Ōpihikao extremely rocky muck 3 to 25 158
PeC Pana‘ewa very rocky silty clay loam 0 to 10 2,968
rPAE Pāpa‘i extremely stony muck 3 to 25 12,182
POD Pi‘ihonua extremely stony silty clay loam 6 to 20 113
PND Pi‘ihonua silty clay loam 6 to 20 7,275
POD Puaulu silt loam 0 to 10 6,692
PND Puhimau silt loam 2 to 6 1,022
PPC Pu‘uk‘ala very rocky silt loam 6 to 12 47
RB Rough broken land - 29
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Puna Flood Study
Hydrologic and Hydraulic Report
August 2013 39
Table 3 - 6. Average Saturated Hydraulic Conductivities for Sub-watersheds.
Sub-
watershed
Saturated Hydraulic Conductivity Classification (in/hr)
Total
(Acres)
Average
Conductivity
(in/hr)
0.50 0.80 1.00 1.20 1.50 2.00 5.00 10.00
Area in Each Saturated Hydraulic Conductivity Classification (acres)
29 401.4 3653.7 982.1 5037.2 1.01
30 75.3 24.6 99.9 0.87
34 2872.2 109.9 2982.1 2.07
35 3431.1 37.3 3468.4 2.02
37 2180.4 357.9 141.9 2680.2 0.62
38 2178.0 4220.9 0.0 46.7 274.2 6719.9 0.76
39 1885.4 1501.0 659.7 4046.1 1.63
42 2859.8 0.9 2860.7 0.50
43 5562.1 345.0 432.2 0.4 6339.6 0.62
45 704.6 94.1 220.5 1019.3 1.40
47 3885.3 503.2 4388.6 0.67
49 1575.1 3957.4 5532.5 3.43
50 5762.1 1380.3 7142.4 2.39
52 3404.3 76.2 1411.6 4892.1 0.94
54 2105.9 128.5 419.7 2654.1 1.13
56 5002.9 486.7 3133.2 8622.7 1.08
58 112.3 124.8 4.9 242.0 0.93
60 436.9 282.7 9727.3 4139.8 14586.6 2.50
64 223.2 845.2 2419.2 3487.6 3.29
65 1762.2 1762.2 4.00
66 205.4 5371.1 5854.2 11430.7 3.00
69 3329.7 44.8 1151.8 3655.9 8182.2 1.27
70 3040.9 411.7 3164.9 17.2 6634.8 1.28
71 145.6 514.1 659.7 3.56
74 12.5 2132.4 2144.9 3.99
80 1346.1 89.0 1008.9 93.3 977.5 3514.9 1.73
81 1052.9 91.5 42.1 582.8 75.4 1844.8 1.16
82 260.4 1771.7 8234.9 10267.0 3.57
84 1135.9 889.3 3859.6 5884.8 3.02
89 5534.7 5534.7 4.00
93 1235.8 484.2 866.9 2916.6 73.5 5577.1 1.56
96 303.9 203.0 9.3 415.8 932.1 2.19
99 166.3 95.7 39.6 4140.7 4442.2 1.92
102 0.0 2003.3 2003.3 4.00
108 772.7 334.1 1440.0 2546.8 1.41
110 39.6 169.4 1148.8 835.6 2193.4 2.66
112 1753.6 1730.1 3483.7 2.99
115 4867.3 985.7 5853.0 2.34
117 36.9 2759.3 2058.9 4855.0 2.84
Total 43907.6 8860.2 1548.6 4208.7 46.7 67562.6 50324.1 90.7 176549.3 2.11
Puna Flood Study
Hydrologic and Hydraulic Report
August 2013 40
3.5 Estimation of Time of Concentrations
Time of concentration determination is necessary for preparing the transform method for a
selected unit hydrograph in the HEC-HMS model. The standard TR-55 methodology
(NRCS 1986) was employed to calculate the time of concentration (Tc) for each sub-
watershed. Time of concentration (Tc) was computed by summing the Tc values of three
consecutive flow segments: sheet flow, shallow concentrated flow, and channel flow. Based
on the TR-55 method, traveling times for these three flows were added together to calculate
time of concentration. The sheet flow segment describes the time period from raindrop
impact until overland flow accumulates to a depth of about 0.1 foot. The sheet flow segment
and it is calculated using Manning's kinematic solution, dependent on Manning's roughness
coefficient “n”, the flow length, the rainfall amount, and the land slope. For this study, the
sheet flow characteristics of all sub-watersheds assumed a Manning's roughness coefficient n
of 0.040 (representing light underbrush surface conditions) and a flow length of 100 feet.
The land slope value for each sub-watershed was obtained from the LiDAR topographic
data and is shown in Table 3-7.
Manning’s “n” values for the sheet flow terrain were selected from Table 3-1 of TR 55
(NRCS 1986). For the open channel flow segments, manning’s “n” values were selected
from Roughness Characteristics of Natural Channels (Barnes 1967) and the guideline specified by
Open Channel Hydraulics (Chow 1959).
Based on the TR-55 method, the following equations were used to calculate the travel times
(Tt) of each flow segment:
i. Sheet Flow:
4.05.0
2
8.0007.0
SP
nLTt
L = Flow length (feet), 300 feet maximum
P2 = 2-yr, 24-hr rainfall amount at the sub-basin (in), NOAA Precipitation Frequency
Data
S = Average land slope (feet vertical/feet horizontal)
n = Manning's roughness coefficient for sheet flow
ii. Shallow Concentrated Flow:
V
LTt3600
If paved surface:
0.520.3282VS
Puna Flood Study
Hydrologic and Hydraulic Report
August 2013 41
)()()(channeltcentratedshallowcontsheettcTTTT
If unpaved surface:
0.516.1345VS
L= Length of shallow concentrated flow path (feet)
S= Average watercourse slope (feet vertical/feet horizontal)
iii. Channel Flow:
V
LTt3600
Where,
213249.1 SRnV
L = Length of channel (feet)
S = Average channel slope (feet vertical/feet horizontal)
R = Hydraulic radius of bank full open channel or culvert flowing full (feet). The
hydraulic radius equals the cross sectional flow area (feet2) divided by the wetted
perimeter (feet).
n = Manning's roughness coefficient for open channel flow
iv. Time of Concentration:
The Tc Values for the sub-watershed are listed in Table 3-7 and ranged from about 0.3 hour
to 4.7 hours. These Tc values were adjusted as part of the HEC-HMS model calibration.
3.6 Hydrograph Transform Parameters
The Snyder peaking coefficient of 0.45 was the initial value for each sub-watershed. The
initial lag time parameters were obtained from the Tc calculation, where lag equals to 0.6
times Tc. These initial values were adjusted in the calibration process to provide more
reasonable representations for each sub-watershed.
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)
Cr
o
s
s
S
e
c
t
i
o
n
ar
e
a
(f
t
2 )
We
t
t
e
d
Pe
r
i
m
e
t
e
r
(f
t
)
Ch
a
n
n
e
l
Sl
o
p
e
Manning’s n Velocity (ft/s) T t (hr)T otal T c (hr)
29
7
.
9
8
2
0
.
4
1
0
0
9
.
3
5
0
.
0
4
5
7
0
.
1
5
0
U
n
p
a
v
e
d
2
5
0
0
0
0
.
0
4
6
4
1
.
9
9
8
7
5
0
0
6
0
3
5
0
.
0
4
0
0
.
0
6
5
6
.
5
6
7
0
.
3
1
7
2.466
30
0
.
1
5
6
0
.
4
1
0
0
1
0
.
7
9
0
.
0
4
1
0
0
.
1
4
6
U
n
p
a
v
e
d
1
2
0
0
0
.
0
4
0
6
0
.
1
0
3
1
0
5
0
2
0
0
1
5
0
0
.
0
4
1
0
.
0
6
5
5
.
6
2
3
0
.
0
5
2
0.301
34
4
.
6
7
6
0
.
4
1
0
0
1
0
.
2
3
0
.
0
3
8
5
0
.
1
5
4
U
n
p
a
v
e
d
1
6
0
0
0
0
.
0
3
6
5
1
.
4
4
2
1
8
0
0
0
6
0
3
5
0
.
0
3
9
0
.
0
6
5
6
.
4
7
5
0
.
7
7
2
2.368
35
5
.
4
6
2
0
.
4
1
0
0
1
0
.
1
1
0
.
0
3
8
3
0
.
1
5
5
U
n
p
a
v
e
d
1
5
0
0
0
0
.
0
3
8
2
1
.
3
2
1
1
7
5
0
0
6
0
3
5
0
.
0
3
8
0
.
0
6
5
6
.
3
8
4
0
.
7
6
1
2.238
37
4
.
1
8
8
0
.
4
1
0
0
1
0
.
1
2
0
.
0
5
0
0
0
.
1
3
9
U
n
p
a
v
e
d
2
1
0
0
0
0
.
0
4
6
0
1
.
6
8
6
7
0
0
0
6
0
3
5
0
.
0
4
0
0
.
0
6
5
6
.
5
6
7
0
.
2
9
6
2.121
38
1
0
.
5
7
5
0
.
4
1
0
0
8
.
6
5
0
.
0
5
0
0
0
.
1
5
1
U
n
p
a
v
e
d
2
8
0
0
0
0
.
0
4
6
4
2
.
2
3
7
1
2
0
0
0
1
2
0
8
0
0
.
0
5
3
0
.
0
6
5
6
.
9
3
7
0
.
4
8
1
2.869
39
6
.
3
2
2
0
.
4
1
0
0
1
0
.
7
6
0
.
0
5
0
0
0
.
1
3
5
U
n
p
a
v
e
d
1
6
0
0
0
0
.
0
7
1
3
1
.
0
3
2
2
0
0
0
0
1
2
0
8
0
0
.
0
4
2
0
.
0
6
5
6
.
1
5
6
0
.
9
0
2
2.070
42
4
.
4
7
0
.
4
1
0
0
1
0
.
9
7
0
.
0
7
2
0
0
.
1
1
6
U
n
p
a
v
e
d
2
4
5
0
0
0
.
0
5
5
5
1
.
7
9
0
9
6
0
0
6
0
3
5
0
.
0
4
0
0
.
0
6
5
6
.
5
3
3
0
.
4
0
8
2.314
43
9
.
9
6
8
0
.
4
1
0
0
1
0
.
5
4
0
.
0
8
5
0
0
.
1
1
1
U
n
p
a
v
e
d
4
1
0
0
0
0
.
0
5
6
6
2
.
9
6
7
1
4
0
0
0
6
0
3
5
0
.
0
4
4
0
.
0
6
5
6
.
9
1
0
0
.
5
6
3
3.641
45
1
.
6
4
3
0
.
4
1
0
0
1
0
.
3
7
0
.
0
6
2
0
0
.
1
2
6
U
n
p
a
v
e
d
9
0
0
0
0
.
0
8
8
9
0
.
5
2
0
8
0
0
0
1
2
0
1
0
0
0
.
0
3
0
0
.
0
6
5
4
.
4
8
4
0
.
4
9
6
1.142
47
6
.
9
0
9
0
.
4
1
0
0
1
0
.
8
0
0
.
0
9
6
0
0
.
1
0
4
U
n
p
a
v
e
d
4
8
0
0
0
0
.
0
5
7
9
3
.
4
3
4
1
5
0
0
0
6
0
3
5
0
.
0
4
7
0
.
0
6
5
7
.
0
9
3
0
.
5
8
7
4.125
49
8
.
7
4
8
0
.
4
1
0
0
8
.
6
0
0
.
0
4
1
0
0
.
1
6
4
U
n
p
a
v
e
d
2
0
5
0
0
0
.
0
4
0
0
1
.
7
6
5
1
8
0
0
0
6
0
3
5
0
.
0
2
9
0
.
0
6
5
5
.
5
8
1
0
.
8
9
6
2.824
50
1
1
.
2
6
7
0
.
4
1
0
0
9
.
4
4
0
.
0
3
3
5
0
.
1
7
0
U
n
p
a
v
e
d
2
7
0
0
0
0
.
0
3
1
5
2
.
6
1
9
3
4
0
0
0
6
0
3
5
0
.
0
3
1
0
.
0
6
5
5
.
7
8
1
1
.
6
3
4
4.422
52
7
.
6
7
3
0
.
4
1
0
0
1
1
.
2
2
0
.
1
2
2
0
0
.
0
9
3
U
n
p
a
v
e
d
4
5
0
0
0
0
.
0
5
9
1
3
.
1
8
7
2
2
0
0
0
6
0
3
5
0
.
0
4
8
0
.
0
6
5
7
.
2
0
7
0
.
8
4
8
4.127
54
4
.
1
4
7
0
.
4
1
0
0
9
.
8
8
0
.
0
4
8
0
0
.
1
4
4
U
n
p
a
v
e
d
1
1
5
0
0
0
.
0
4
6
0
0
.
9
2
3
1
2
7
0
0
6
0
3
5
0
.
0
4
1
0
.
0
6
5
6
.
6
4
8
0
.
5
3
1
1.597
56
1
3
.
5
9
4
0
.
4
1
0
0
1
1
.
0
9
0
.
0
9
5
0
0
.
1
0
3
U
n
p
a
v
e
d
4
4
0
0
0
0
.
0
5
6
4
3
.
1
9
1
1
7
2
0
0
6
0
4
0
0
.
0
6
9
0
.
0
6
5
7
.
8
6
8
0
.
6
0
7
3.901
58
0
.
3
7
8
0
.
4
1
0
0
9
.
6
7
0
.
0
3
7
6
0
.
1
6
0
U
n
p
a
v
e
d
1
8
0
0
0
.
0
3
7
6
0
.
1
6
0
5
0
0
0
1
0
0
8
0
0
.
0
3
8
0
.
0
6
5
5
.
1
5
6
0
.
2
6
9
0.589
60
2
2
.
8
7
4
0
.
4
1
0
0
1
0
.
1
7
0
.
0
4
7
9
0
.
1
4
2
U
n
p
a
v
e
d
2
3
0
0
0
0
.
0
4
7
5
1
.
8
1
7
4
9
0
0
0
4
0
0
3
0
0
0
.
0
3
4
0
.
0
6
5
5
.
0
8
8
2
.
6
7
5
4.634
64
5
.
4
4
9
0
.
4
1
0
0
9
.
6
0
0
.
0
3
4
5
0
.
1
6
6
U
n
p
a
v
e
d
1
5
0
0
0
0
.
0
3
5
0
1
.
3
8
0
1
4
0
0
0
6
0
3
5
0
.
0
3
2
0
.
0
6
5
5
.
8
7
4
0
.
6
6
2
2.209
65
2
.
7
5
3
0
.
4
1
0
0
8
.
4
7
0
.
0
3
2
8
0
.
1
8
0
U
n
p
a
v
e
d
6
5
0
0
0
.
0
3
2
0
0
.
6
2
6
2
0
5
0
0
4
0
0
3
0
0
0
.
0
2
8
0
.
0
6
5
4
.
6
4
7
1
.
2
2
5
2.032
66
1
7
.
8
6
0
.
4
1
0
0
9
.
1
8
0
.
0
4
3
8
0
.
1
5
4
U
n
p
a
v
e
d
1
0
5
0
0
0
.
0
4
2
7
0
.
8
7
5
6
2
0
0
0
4
0
0
3
0
0
0
.
0
2
8
0
.
0
6
5
4
.
6
4
7
3
.
7
0
6
4.736
69
1
2
.
8
2
6
0
.
4
1
0
0
1
0
.
9
2
0
.
1
0
8
0
0
.
0
9
9
U
n
p
a
v
e
d
4
2
0
0
0
0
.
0
6
1
9
2
.
9
0
6
4
1
0
0
0
6
0
3
5
0
.
0
4
6
0
.
0
6
5
7
.
0
6
8
1
.
6
1
1
4.616
70
1
0
.
4
2
5
0
.
4
1
0
0
1
1
.
0
7
0
.
1
1
0
0
0
.
0
9
7
U
n
p
a
v
e
d
3
7
0
0
0
0
.
0
6
1
1
2
.
5
7
7
4
5
5
0
0
6
0
3
5
0
.
0
4
8
0
.
0
6
5
7
.
2
2
0
1
.
7
5
1
4.425
71
1
.
1
4
7
0
.
4
1
0
0
8
.
2
8
0
.
0
2
6
5
0
.
1
9
9
U
n
p
a
v
e
d
4
0
0
0
0
.
0
2
5
5
0
.
4
3
1
6
0
0
0
6
0
3
5
0
.
0
2
5
0
.
0
6
5
5
.
1
9
2
0
.
3
2
1
0.951
74
3
.
4
1
4
0
.
4
1
0
0
8
.
4
1
0
.
0
2
7
8
0
.
1
9
4
U
n
p
a
v
e
d
7
5
0
0
0
.
0
2
6
6
0
.
7
9
2
1
2
0
0
0
4
0
0
3
0
0
0
.
0
2
6
0
.
0
6
5
4
.
4
7
8
0
.
7
4
4
1.730
80
5
.
4
9
2
0
.
4
1
0
0
9
.
6
8
0
.
0
3
9
6
0
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1
5
7
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n
p
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d
2
5
0
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0
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4
1
.
9
1
7
2
9
0
0
0
4
0
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3
0
0
0
.
0
3
5
0
.
0
6
5
5
.
1
9
5
1
.
5
5
1
3.624
Puna Flood Study
Hy
d
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H
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Dr
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s
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Fl
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w
Le
n
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t
h
(f
t
)
Tw
o
-
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e
a
r
2
4
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h
o
u
r
Ra
i
n
f
a
l
l
(
i
n
)
La
n
d
S
l
o
p
e
T t
(h
r
)
Su
r
f
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De
s
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r
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p
t
i
o
n
Flo
w
L
e
n
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t
h
(f
t
)
Slo
p
e
T t (
h
r
)
Fl
o
w
Le
n
g
t
h
(f
t
)
Cr
o
s
s
S
e
c
t
i
o
n
ar
e
a
(
f
t
2 )
We
t
t
e
d
Pe
r
i
m
e
t
e
r
(
ft
)
Ch
a
n
n
e
l
Sl
o
p
e
Manning n Velocity (ft/s) T t (hr)T otal T c (hr)
81
2
.
8
8
3
0
.
4
1
0
0
9
.
5
6
0
.
0
4
0
2
0
.
1
5
7
U
n
p
a
v
e
d
1
3
6
0
0
0
.
0
4
2
6
1
.
1
3
4
1
0
5
0
0
4
0
0
3
0
0
0
.
0
3
0
0
.
0
6
5
4
.
8
4
8
0
.
6
0
2
1.892
82
1
6
.
0
4
2
0
.
4
1
0
0
8
.
9
5
0
.
0
3
8
6
0
.
1
6
5
U
n
p
a
v
e
d
1
2
0
0
0
0
.
0
3
7
7
1
.
0
6
4
4
8
0
0
0
2
0
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1
5
0
0
.
0
2
7
0
.
0
6
5
4
.
5
6
3
2
.
9
2
2
4.151
84
9
.
1
9
5
0
.
4
1
0
0
9
.
1
8
0
.
0
4
3
1
0
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1
5
5
U
n
p
a
v
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d
6
5
0
0
0
.
0
4
2
0
0
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5
4
6
3
0
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4
0
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3
0
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0
.
0
2
2
0
.
0
6
5
4
.
1
1
9
2
.
0
2
3
2.725
89
8
.
6
5
0
.
4
1
0
0
8
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Puna Flood Study
Hydrologic and Hydraulic Report
July 2013 44
3.7 Model Calibration
The calibration rainfall data were from the NOAA Hydronet rain gages HI81, HI83, HI91,
HI92, and HI94 (see Section 2.3.1). The simulation time period was 42 hours from 0:00,
11/1/2000, to 18:00, 11/2/2000. Since there are no stream gage data available within the
Puna study area, a second hydrologic model (FLO-2D) was applied for the same study area
for comparative purposes. (Appendix A).
The gage weights method was used to determine the rainfall amount for calibration
purposes. A Thiessen Polygon mechanism was initially applied to determine the gage weight
for each sub-watershed. Figure 3-13 shows the Thiessen Polygon for this study. After the
rainfall pattern, data quality, storm movement and distribution were considered; the final
gage and time weights and relevant 42-hour rainfall of the November 1 to 2, 2000, storm for
the sub-watersheds were determined as shown in Table 3-8.
Both the HEC-HMS and FLO-2D models were run for the calibration storm event
(November 1 to 2, 2000). The results of both models are shown in Table 3-9. The results of
the two models matched closely to each other, with an average difference of 11%.
Puna Flood Study
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Hydrologic and Hydraulic Report
August 2013 46
Table 3 - 8. Gage Depth and Time Weights for November 1 to 2, 2000, Storm.
Precipitation Gage Depth (Time) Weights
Sub-watershed Area(mi2) HI81 HI83 HI91 HI92 HI94
42-hr Rainfall
(in)
29 7.982 0.5(0) 0.5(1) 23.62
30 0.156 0.5(0) 0.5(1) 23.62
34 4.676 0.3(0.5) 0.3(0) 0.4(0.5) 26.81
35 5.462 0.3(0.4) 0.3(0) 0.4(0.6) 26.81
37 4.188 0.5(0.5) 0.5(0.5) 23.63
38 10.575 0.6(0) 0.4(1) 22.6
39 6.322 0.2(0) 0.8(1) 26.69
42 4.47 0.2(0) 0.8(1) 26.69
43 9.968 0.1(0.1) 0.5(0) 0.4(0.9) 24.01
45 1.643 0.5(0.5) 0.5(0.5) 30.64
47 6.909 0.2(0.5) 0.5(0) 0.3(0.5) 24.39
49 8.748 1(1) 18.52
50 11.267 0.2(0.5) 0.7(0.5) 0.1(0) 22.35
52 7.673 0.3(0.5) 0.4(0) 0.3(0.5) 19.76
54 4.147 0.8(0.8) 0.2(0.2) 31.79
56 13.594 0.2(0.5) 0.4(0) 0.4(0.5) 25.41
58 0.378 1(1) 32.55
60 22.874 0.4(0.5) 0.3(0.1) 0.4(0.4) 27.33
64 5.449 0.8(1) 0.2(0) 29.74
65 2.753 1(1) 18.52
66 17.86 0.2(0) 0.8(1) 21.33
69 12.826 0.5(1) 0.2(0) 0.3(0) 28.6
70 10.425 0.4(0.7) 0.3(0) 0.3(0.3) 27.2
71 1.147 0.8(1) 18.52
74 3.414 0.9(1) 18.52
80 5.492 0.8(0.8) 0.2(0.2) 31.79
81 2.883 0.6(0.8) 0.4(0.2) 26.94
82 16.042 0.2(0.5) 0.8(0.5) 21.33
84 9.195 0.2(0.5) 0.8(0.5) 21.33
Puna Flood Study
Hydrologic and Hydraulic Report
August 2013 47
Precipitation Gage Depth (Time) Weights
Sub-watershed Area(mi2) HI81 HI83 HI91 HI92 HI94
42-hr Rainfall
(in)
89 8.656 0.85(1) 18.52
93 8.862 0.4(0.5) 0.2(0.3) 0.4(0.2) 27.39
96 1.456 0(0.2) 1(0.8) 18.52
99 7.239 0.5(0.5) 0.5(0.5) 31.77
102 3.132 0.9(0.8) 0.1(0.2) 31.15
108 3.979 0.2(0.2) 0.3(0.3) 0.5(0.5) 27.56
110 3.428 0.1(0.1) 0.6(0.6) 0.3(0.3) 23.66
112 5.449 0.6(0.5) 0.4(0.5) 23.5
115 9.23 0.5(0.2) 0.5(0.8) 24.75
117 8.502 0.5(0.1) 0.2(0.3) 0.3(0.6) 23.81
Table 3 - 9. Comparison of Model Results for November 1 to 2, 2000, Storm.
Junctions Description Drainage Area
(mi2)
HEC-HMS
(cfs)
FLO-2D
(cfs)
J2 Volcano Rd &
Kahaualeale Rd 22.90 12,717 12,215
J3 Near Mauaana Rd 43.66* 23,983 23,087
J4 Near ‘Āpele Rd 52.21* 21,215 22,803
J5 South Kūlani Rd
Bridge 78.00* 30,386 32,402
J7 Kea‘au-Pāhoa Rd &
Keaau Bypass Rd 109.63* 22,449 24,019
J8 Volcano Rd & Huina
Rd 23.25 8,786 9,875
J10 Railroad Ave. &
Kea‘au Rd 16.10 2,993 2,725
JK1 Pulelehua Rd & Poola
Rd 28.32 3,554 3,496
*The Marked Drainage Area is the area without considering the topographic diversion.
Puna Flood Study
Hydrologic and Hydraulic Report
August 2013 48
3.8 Hydrologic Analysis Results
After the calibration, the next step is to select the final model parameters for the storm
frequency computations. For the reason that there is only one calibration event, the
November 1 to 2, 2000 storm, it’s difficult to assess an accurate prediction basin model for
future storms. The final basin models were compared with FLO-2D model results and to
optimize the model using FLO-2D model results as referenced observed flows. The HEC-
HMS parameters were checked to make sure they are in a reasonable range. Table 3-10 gives
the HEC-HMS model results for the four designed storm events at the selected nine
junctions.
Table 3 - 10. Puna Study Area HEC-HMS Results
Junctions Description
Drainage
Area
(mi2)
10-year
(10%
Annual
Chance)
(cfs)
50-year
(2%
Annual
Chance)
(cfs)
100-year
(1%
Annual
Chance)
(cfs)
500-year
(0.2%
Annual
Chance)
(cfs)
J2
Volcano Rd &
Kahaualeale
Rd
22.90 9,454 23,955 35,157 46,240
J3 Near Mauaana
Rd 43.66 19,063 40,749 59,984 80,339
J4 Near ‘Āpele
Rd 52.21 19,538 36,533 45,384 61,031
J5 South Kūlani
Rd Bridge 78.00 25,024 45,398 61,326 84,906
J7
Kea‘au-Pāhoa
Rd & Keaau
Bypass Rd
109.63 15,187 30,993 40,720 63,826
J8 Volcano Rd &
Huina Rd 23.25 5,859 12,212 17,055 25,270
J10 Railroad Ave.
& Kea‘au Rd 16.10 1,361 3,916 5,539 11,894
JK1 Pulelehua Rd
& Poola Rd 28.32 1,229 8,197 17,854 28,551
J16
Volcano Rd &
Kahaualeale
Rd
10.14 241 1,035 2,672 8,712
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Hydrologic and Hydraulic Report
August 2013 49
The HEC-HMS model results were compared with the FLO-2D model results (Appendix A).
Table 3-11 gives the comparison of the peak discharges at the nine conjunctions for the four
storm events. The HEC-HMS results are comparative and match closely with the FLO-2D
results. The differences between the two models at the major junctions are within 15%.
Based on this comparison, HEC-HMS model results provide sufficient estimations for the
four storm events. The hydrologic results of HEC-HMS model are applicably accurate to use
as input to the FLO-2D model in hydraulic analysis.
Table 3 - 11. Peak Discharge for Storm Events
Junctions Description
10- Year
(10% Annual
Chance)
cfs
50- Year
(2% Annual
Chance)
cfs
100- Year
(1% Annual
Chance)
cfs
500- Year
(0.2% Annual
Chance)
cfs
HEC-
HMS
FLO-
2D
HEC-
HMS
FLO-
2D
HEC-
HMS
FLO-
2D
HEC-
HMS
FLO-
2D
J2
Volcano Rd
&
Kahaualeale
Rd
9,454 9,596 23,955 22,330 35,157 33,418 46,240 46,266
J3
Near
Mauaana
Rd
19,063 17,648 40,749 36,532 59,984 54,024 80,339 74,770
J4 Near Apele
Rd 19,538 17,410 36,533 31,291 45,384 44,008 61,031 63,610
J5
South
Kūlani Rd
Bridge
25,024 20,684 45,398 39,041 61,326 51,602 84,906 75,217
J7
Keaau-
Pahoa Rd &
Keaau
Bypass Rd
15,187 14,734 30,993 31,463 40,720 40,507 63,826 59,910
J8 Volcano Rd
& Huina Rd 5,859 6,017 12,212 13,046 17,055 16,191 25,270 24,023
J10
Railroad
Aves. &
Keaau Rd
1,361 1,248 3,916 3,684 5,539 5,640 11,894 11,935
JK1
Pulelehua
Rd & Poola
Rd
1,229 777 8,197 7,360 17,854 16,165 28,551 29,194
J16
Waimakao
Pele Rd &
Pahoehe Rd
241 171 1,035 1,080 2,672 2,608 8,712 8,581
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Hydrologic and Hydraulic Report
August 2013 50
4 HYDRAULIC ANALYSIS
4.1 FLO-2D Model Overview
The terrain of the Puna area is characterized by broad and gentle slopes. The land surface
consists of porous volcanic rock and soils from Mauna Loa and Kilauea eruptions. There are
no well-defined waterways within the project area. There is an extensive network of
subterranean lava tubes throughout much of this area. For this reason, a two dimensional
hydraulic model such as FLO-2D would have advantage over one dimensional model such
as HEC-RAS. FLO-2D model was selected to conduct the hydraulic analysis of the complex
two-dimensional flood flows in the Puna area.
FLO-2D is one of FEMA’s approved hydraulic models for both riverine and unconfined
alluvial fan flood studies. FLO-2D simulates flood wave attenuation and predicts the area of
inundation by numerically solving the continuity equation and the dynamic wave momentum
equations on a grid system. As a two-dimensional model, FLO-2D distributes the rainfall
and runoff based on the terrain information on each grid and provides more accurate
representation of overland flow. FLO-2D does not distinguish subcritical and supercritical
flow and so it doesn’t have restrictions when computing the transition between the flow
regimes. The model has the capability to include many parameters such as the rainfall,
infiltration, ground surface roughness, levees, and hydraulic structures.
4.2 FLO-2D Model Setup
4.2.1 Topographic Database
The topographic data has an average point spacing of 8 feet. The Digital Terrain Model
(DTM) data for Puna Watershed was formed with a re-sampling resolution of 16 feet by 16
feet to reduce the data file size. A 300-foot-grid-size model for the whole study area was
preliminarily tested to determine general trends of the floods before the final 128-foot grid
models were fully developed. The re-sampled data was used to build the FLO-2D model
using a 128’ x 128’ grid cell size. This grid cell size was recognized by county of Hawaii,
Department of Public Works. Each grid element contained an average of 64 elevation points
(DTM data with resolution of 16’ x 16’) from which the grid elevations were determined. As
suggested by the FEMA’s Guidelines and Specifications for Flood Hazard Mapping Partners-
Appendix C, the selection of the cell size should not only consider the accuracy of the
topographic data, but also the computational efficiency of the model and mapping and
floodplain management needs. “Too small a cell size not only slows computations, but also
creates too many elevation grids, which may not practically be presented on the floodplain
map.”
For significant structures, such as the South Kūlani Flood Diversion Structure, and the
major bridges and culverts, the field survey data was used to better define the elevation and
dimensions of these structure. All elevation data utilized was converted and referred to
North American Horizontal Datum of 1983 (NAD–1983–HARN–StatePlane–Hawaii–1–
FIPS–5101–Feet). The Vertical Datum is based on Local Tidal Level.
Puna Flood Study
Hydrologic and Hydraulic Report
August 2013 51
4.2.2 Sub-domains and Grid Size
In the hydraulics analysis, five sub-domains were developed, subdividing the whole study
area into operable sizes for computational purposes in the FLO-2D models. These five sub-
domains were designated as North, Middle North, Middle South, Middle East, and South
sub-study areas (See Figure 4-1). These computational sub-domains built up five FLO-2D
models. North and South models are individual models for two independent watersheds.
The Middle North, Middle South and Middle East models needed the hydrograph input
from the upstream basins, so they have to be executed sequentially in the order from Middle
South to Middle North and to Middle East. As shown in Figure 3-1, a total of 39 sub-
watersheds were delineated across the five model sub-domains. The Northern sub-domain
has three separate sub-watersheds (112, 115, and 117), which discharge directly to the Pacific
Ocean. The South sub-domain includes sub-watersheds 34, 35, 49, 50, 65, 66, 71, 74, and 89.
The Middle sub-domains are comprised of 27 sub-watersheds with a total area of 191.3 mi2.
The 128 feet by 128 feet grid size were selected for all sub-domains. Tests indicated the grid
element size of 128 feet had already provided sufficient resolution for large flood events.
These final models have altogether about 0.5 million grid elements and a substantial long run
time.
4.2.3 Hydrologic Input
The methodology used to develop the flood hydrographs for 10, 50, 100, and 500 return
years for the Puna study area were described in Section 3 Hydrologic Analysis. In this
hydraulic analysis, hydrographs from each sub-watershed were input as inflow sources
assigned to specific individual FLO-2D model grid. Figure 4-2 shows the input locations of
the hydrograph inflow for FLO-2D models. The hydrologic mode of FLO-2D model was
run first (also see Appendix A) to determine the flow paths and the floodplains. Based on
the initial test, the input locations of hydrograph inflows were selected along the flow
concentration point (normally at the upstream of the major flow path) to provide a
conservative predict. A steady state inflow condition was considered for each sub-watershed
by keeping the inflow hydrographs at their peak values after the inflow hydrographs reach
the peak. The use of steady state condition removes the timing influence on peak discharges
and eliminates the attenuation of peak discharges due to volume storage within the
floodplain. This method was used in other hydraulic analysis projects such as the “Upper
Goose Creek and Two-mile Canyon Creek Flood Mapping Study Update” (City of Boulder
Public Works Department, 2012). This approach was taken to meet applicable Federal
Emergency Management Agency (FEMA). Figure 4-3 shows the difference between the
original hydrograph and the steady state hydrograph at sub-watershed 29 as a typical
example. Through the trial and error test, the sub-watersheds at the north sub-domain do
not have flooding problem. So the inflow hydrographs for these sub-watersheds are
disregarded.
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Hydrologic and Hydraulic Report
August 2013 54
Figure 4 - 3. Typical Steady State Inflow Hydrographs.
4.2.4 Streams
Puna area is composed of recent lava flows. Currently there are no well-defined stream
channels in this area because of the slow development of the soil mantle. The terrain in Puna
is characterized by broad and gentle slopes, and an extensive network of subterranean lava
tubes that runs throughout much of this study area. For these reasons, unconfined flows
commonly occurred this area. Shallow stream channel and braided channels have been
developed alternatively. Figure 4-4 shows the stream centerline position from Hawaii State
Geographic Information System (http://hawaii.gov/dbedt/gis/) with the LiDAR data as the
background image. From the comparison, the stream channel can hardly be identified from
the LiDAR data in most of the stream locations. At some locations, the stream channel
seems to have wandered and relocated. During the field survey, the stream channel is also
not identifiable at some locations. Pictures were taken during one field visiting as marked by
the numbers 1 through 4 in Figure 4-4. Figure 4-5 through 4-8 show the pictures taken at
those locations. At some locations, where the streams cross the road, the road only show
wavy geomorphologic features with no typical features for a stream channel such as the
stream bed or stream banks. The stream behaves like overland flow at some places as shown
in Figure 4-8. Combining all these observations, we can assess the Kea‘au stream is not a
well-defined stream. Therefore in this hydraulic study, streams are not simulated as the one-
dimensional channels. The FLO-2D model simulates the streams as floodplain flow with
proper manning’s n values. Stream water surface elevation is extracted from the floodplain
water surface elevation along the stream centerline.
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Figure 4 - 5 40th Avenue at 1400 Feet North of the Intersection with Pohuku Drive
Figure 4 - 6 40th Avenue at 1800 Feet South of the Intersection with Pohuku Drive
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Figure 4 - 7 The Intersection between the 39th Avenue and Pohaku Drive
Figure 4 - 8 Keaau Stream before Crossing the Intersection between the 39th Avenue
and Pohaku Drive
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4.2.5 Water Diversion Systems
The South Kūlani diversion system is a water diversion structure, which extends over one
half mile in length. According to the recollections of the local residents, the walls were built
by ‘Ōla‘a Sugar Company in 1938, to divert floodwater away from cane fields along the
Mauna Loa/Kilauea boundary into what was then called “wasteland”, owned by W.H.
Shipman (County of Hawai‘i, Department of Planning 1995). In 1958, the “wasteland” was
developed as a subdivision, now called Hawaiian Acres. Many local people living there are
unaware of the flooding problems.
Hawaiian Acres Community Association (HACA) has tried to make the local residents aware
of the potential of flood hazards at the Hawaiian Acres. HACA provided a brief map to
describe the possible flood path down the South Kūlani Bridge as shown in Figure 4-9
(Figure from http://www.hawaiianacres.org/history.shtml). This map provided the
approximate structure location while giving an impression that there is a floodwall
downstream the South Kūlani Bridge which blocked the initial main watercourse to divert
the water to the Hawaiian Acres. Since this “floodwall” was not picked up in the LiDAR
data, Oceanit conducted land survey to locate this “floodwall”. The structure was surveyed
in October, 2011 and the results did not match with the HACA sketch. The diversion system
composed of a flow split made of a V-shape dike and a series of guiding walls made of
cemented rocks. A plan view of the whole structure layout is shown in Figure 4-10 (Notice:
the map is rotated to give an easy comparison with Figure 4-9). The blue lines in the figure
show the existing structures with the slopes indicated in front of them at some locations.
Appendix B provides a detailed analysis of the surveyed structure profile. The survey data
and the LiDAR data generally show similar confinement effects on flow since the crest
elevation of the rock wall is not higher than the landward ground elevation in most of the
sections. The survey results turn out be similar with the LiDAR data with only few cross-
sections more pronounced than the LiDAR data.
Figures 4-11 through 4-12 show the current situations of the cemented rock wall. Trees and
dense vegetation grow along the wall. Portion of the wall has collapsed due to the lack of
maintenance (Figure 4-12). From the layout of the structure, it seems that the cemented rock
walls were used to divert the water to the Hawaiian Acres for small flooding events. Their
functionality is a little different from the levee structure. Formerly, FEMA used the without
levee approach to assess flood hazards associated with non-accredited levee system. “Under
the former approach, when a levee system did not meet the National Flood Insurance
Program (NFIP) requirements cited in the Code of Federal Regulations (CFR) at Title 44,
Chapter 1, Section 65.10 (44CFR65.10), FEMA analyzed the flood hazards and represented
the flood hazards in leveed areas on the Flood Insurance Rate Map (FIRM) as if the levee
system does not exist (FEMA 2011)”. FEMA updated the method to model the non-
accredited levees in December 9, 2011. The proposed Levee analysis and mapping protocol
include several procedures: Sound Reach Procedure, Freeboard Deficient Procedure,
Overtopping Procedure, Structural-Based Inundation Procedure and Natural Valley
Procedure. The guiding wall in this hydraulic diversion system is not the same as the levee
structure. However, sensitivity analysis is still conducted to see the difference between the
with-structure and without-structure situation.
The rock walls were built along the south side of the stream bank and were simulated by
using the levee component in FLO-2D. The location and top elevation of the wall was input
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into the FLO-2D model. The FLO-2D levee component confines flow by blocking one or
more of the eight flow directions in each grid element. When the flow depth exceeds the
levee height, the discharge over the levee is computed using a broad-crested weir flow
equation. From Figure 4-10 or Figure 4-14, a narrow stream channel around 30 feet wide can
be seen along the north side of the rock wall footprint. This sub-grid topographic feature
cannot be represented by the FLO-2D grid size, so a channel component was added in the
FLO-2D model to mimic the topographic restriction on the flow. Based on the survey data
and the LiDAR data, this channel feature has a depth in the range of 1 foot to 8.7 feet under
the right bank crest elevation.
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Figure 4 - 9 Potential Flooding Problems at Hawaiian Acres by HACA
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Figure 4 - 11 Photo of Rock Wall
Figure 4 - 12 One Section of the Rock Wall
Top of the Rock Wall
Toe of the Rock Wall
Top of the Rock Wall
Toe of the Rock Wall
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Figure 4 - 13 Failed Section of Rock Wall
4.2.6 Bridges and Culverts
Bridges and culverts play an important role on the floodplain delineation. The major bridges
and culverts within the project area were surveyed by the Oceanit engineers. Based on the
analysis of the previous field photos, altogether 12 structures were surveyed including 5
bridges and 7 culverts (Denoted by a number in Figure 4-15). The corresponding names of
these bridges and culverts are listed in Table 4-1.
Since FLO-2D cannot directly model bridge or culvert hydraulics, the HEC-RAS model was
utilized to provide the discharge-rating curves for the FLO-2D model. LiDAR data in the
vicinity of the bridges and culverts were converted to the Triangulated Irregular Network
(TIN) data. ArcGIS with HEC-GEORAS were utilized to extract the cross-section data
close to the hydraulic structures. These cross-section data provided the geometric input for
the HEC-RAS model. The surveyed dimensions of the hydraulic structures were then
assigned into the HEC-RAS model by HEC-RAS tools. A series of flow rates were applied
to the hydraulic models to achieve the rating curve of water elevation vs. the flow discharge.
See Appendix C for the hydraulic structure cross-section information and their rating curves.
All culverts less than a 36” diameter were not included in the FLO-2D model, since those
culverts would not have sufficient conveyance capacity to impact the results of floodplain
delineation for this study. The rating curves were assigned to the specific cells related to the
structure locations in FLO-2D to account for the bridge and culvert hydraulics.
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Table 4 - 1 Names of the Surveyed Bridges and Culverts
No. Name Crossing Road Name
1 Keaau-Pahoa Road Culvert 1 Keaau-Pahoa Road
2 Keaau-Pahoa Road Culvert 2 Keaau-Pahoa Road
3 Waipahoehoe Stream Bridge Keaau-Pahoa Road
4 Moho Road Culvert 1 Moho Road
5 Moho Road Culvert 2 Moho Road
6 S. Kūlani Road Bridge S. Lulani Road
7 Enos Road Culvert Enos Road
8 S. Pszyk Road Culvert 1 S. Pszyk Road
9 S. Pszyk Road Culvert 2 S. Pszyk Road
10 S. Kopua Road Bridge 1 S. Kopua Road
11 S. Kopua Road Bridge 2 S. Kopua Road
12 N. Oshiro Road Bridge 2 N. Oshiro Road
4.3 FLO-2D Model Calibration
The severe flooding event on November 1 to 2, 2000 caused significant damage to the
windward side of the Big Island of Hawai’i. In some places, cottages and stretches of paved
roads were washed away, and bridges and culverts were washed out from the roads. The
FLO-2D model was calibrated using this flood event. The Manning’s n values were adjusted
to calibrate the model to simulate the historic event. The Manning’s n values were kept in
the reasonable range of the recommend values in Table 1 of the FLO-2D manual (2009).
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4.4 Hydraulic Analysis Results
4.4.1 Water Diversion System Assessment
The influence of the water diversion system on the flooding area downstream the South
Kūlani Road Bridge was analyzed by a with-structure and without-structure method. The
FLO-2D results of the with-structure and without-structure situation are presented in
Figures 4-16 and 4-17. Figure 4-16 shows the water depth for the 100-year event
downstream the South Kūlani Bridge and Figure 4-17 gives the water surface elevation
profiles for these two situations. From the comparison, these two cases provided very similar
results. Hence, the LiDAR data alone can represent the rock wall crest height sufficiently in
the terrain model requiring no levee component addition in FLO-2D models. As also noted
from Appendix B, the crest elevation of the rock wall is close to the landward ground
elevation in most sections.
4.4.2 FLO-2D Model Calibration Result
Reliable inundation area maps or reliable water surface elevation records for the November 1
to 2, 2000 flooding event were not available. The calibration of FLO-2D was based on
general matches with the sparse observations of that flood event. The flooding situation at
the Puna area was reconstructed by combining different sources of records.
A video record from the Flood Hazards Gallery (University of Hawai’i at Hilo, 2003) shows
the disastrous flooding scenes during the November 1 to 2, 2000. Figure 4-18 through 4-20
were snapshots from that video. The exact locations for those snapshots are unknown.
Figure 18 shows the ponding water on the road at Puna District. Figure 4-19 shows that
flood waters washed away one stretch of the road at Hawaiian Acres. In the picture, a truck
fell into the breach in the road and strong sheet flow flowed over the road surface. Figure 4-
20 shows the flood waters flowing over the Kukui Camp Road. Flood waves can be seen
splashing at the courtyard walls of local residents. Flood flow depth in Figure 4-21 replicates
these flood situations.
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Oceanit working with the staff from the Highway Maintenance Division Department of
Public Works, County of Hawai‘i re-visited many flooding locations associated with the
flood event. The observed flooding water depth for the November 1 and 2, 2000 event was
recalled from the field survey mentioned earlier. Figure 4-21 shows the field visit locations
with the flooding map of model result in the background. Table 4-2 lists the observed
flooding water depth and the flooding water depth from the model.
Another source for the flooding validation is from the County of Hawai‘i Memo (County of
Hawai‘i, 2001). The Memo mentioned that the stretch of Kuauli Road has been completely
washed out in 1986, 1994, and 2000 flood events (Figure 4-22). Figure 4-21 shows a major
flood path across the Kuauli Road, which is consistent with the event. Modeling of the road
breach is out of the scope of this work.
Figure 4 - 18 Flooded Roads at Puna District
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Figure 4 - 19 Flood Waters Wash Away a Stretch of the Road at Hawaiian Acres
Figure 4 - 20 Flood Waters Flow over the Kukui Camp Road
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Table 4 - 2 FLO-2D Model Calibration Results for November 1 to 2, 2000 Storm
ID Locations Water depth Observed by Highways
Maintenance Division
FLO-2D
Model
Results(Feet)
1 Oshiro Rd bridge 2 About 15 ft at bridge 13
2 N. Peck Rd. Bridge 1 overtopped 0.53
3 N. Peck Rd. Bridge 2 overtopped 2.16
4 Intersection of S. Kopua
Rd. and Volcano Rd overtopped 8.4
5 Intersection of S. Pszyk Rd.
and Volcano Rd
6x10 box culvert, 14 ft length, overtopped
box culvert 0.3
6 S Kūlani Rd. Bridge flooding area 5
7 ENOS RD overtopped, deep water 1.9
8 Kukui Camp Rd Based on water mark at Kukui Camp Rd.,
the water depth was about 6-8 ft 2.4
9 Ala Loop. and Volcano Rd very deep water, 5-10 ft 7.6
10 Kuauli Rd. about 2 ft 3
11 Moho Rd. flooding area 0.4
12 Moho Rd., flooding area flooding area 0.5
13 Moho Rd. and Poola Rd.,
Flooding Area flooding area 0.3
14 Hale Pule Loop. flooding area 0.9
15 Olaa Rd, close to Volcano
Rd. wide flooding area 0.9
16 Kapiki PL flooding area 0.6
17 Ipuaiwaha St., Deep Water Deep Water 1.7
18 Between Keaau Pahou Rd.
and Keaau Bypass Rd. flooding area 6.0
19 Kipimana St. and Kalara St.,
Edge of Pit
Deep lower area at Kipimana St. and Kalara
St. -
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Figure 4 - 22 Damaged Road Surface at Kuauli Road
4.4.3 FLO-2D Model Results
The North and South sub-domains represent two independent sub-watersheds and there are
no inflow hydrographs from upstream watersheds to those sub-models. The term of sub-
domain is used instead of sub-watershed since some sub-domain boundary doesn’t cover the
whole sub-watershed. The Middle South sub-domain doesn’t receive boundary inflow and
provides outflow to the Middle North sub-domain and the Middle East sub-domain. The
Middle North sub-domain receives inflow from the Middle South sub-domain and provides
the outflow to the Middle East sub-domain. The Middle East sub-domain receives inflows
from both the Middle North and Middle South sub-domains. Figure 4-23 illustrates the
boundary outflow cross-section locations for each sub-domain. In this study, the flow
hydrographs were obtained at each grid element along the boundary cross-sections and
applied to the following elements at downstream sub-domains to consider the variation of
inflow along the cross-sections. Since there are over 50 boundary elements involved, for the
purpose of clarity only the boundary hydrographs for each cross-section are presented here.
The input hydrographs for the downstream sub-domains are listed in Table 4-3.
The flood profiles for the Keaau stream downstream of the South Kūlani Road Bridge were
extracted from the FLO-2D model results as shown in Figures 4-24 through 4-27. This
reach has a length of about 8 miles and an average stream-bed slope of about 2.5%. From
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these flood profiles, the riverine and overland flow alternate features can be verified at some
locations. The result also indicates the stream channel is not well-defined.
Figures 4-28 through 4-29 present the maximum water depth for each event. The results for
each FLO-2D model run are summarized in the Table 4-4 through 4-7. Volume
conservation is the key criteria for the flood routing. It can be seen that the total inflow
volume (Inflow hydrograph) and outflow volume (Floodplain outflow, Infiltration and
Storage) in these tables match well, which indicates models are accurate and reliable. The
maximum inundation area in the table is the area where the minimum water depth is 0.1
foot. The FLO-2D input files, output files, and shape files generated by FLO-2D Mapper
tools are submitted as digital files with this report.
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Puna Flood Study
Hydrologic and Hydraulic Report
August 2013 90
4.5 Determination of Floodplain Boundaries
FLO-2D model results were post-processed by the automated mapping tools of FLO-2D
Mapper. FLO-2D Mapper tool can interpolate the flow depth data and generate the contour
shape files for further processing. ArcGIS tool or the DFIRM tool, a separate tool from
FLO-2D Company, can be used to generate the final electronic map.
Detailed maps showing flood hazard boundaries and flood depths are provided in Appendix
D. The flood insurance risk zone type was determined according to the Appendix E of
FEMA’s Guidelines and Specifications for Flood Hazard Mapping Partners. The flood
insurance risk zones for shallow flooding are described as (FEMA, 2002):
Zone A – “is the flood insurance risk zone that corresponds to the 1-percent-annual-chance
floodplains that are determined by approximate-study methods.”
Zone AO – “is the flood insurance risk zone that corresponds to the areas of 1-percent-
annual-chance shallow flooding (usually sheet flow on sloping terrain) where average depths
are between 1.0 and 3.0 feet.”
Zone AH – “is he flood insurance risk zone that corresponds to the areas of 1-percent-
annual-chance shallow flooding (usually areas of ponding) where average depths are between
1.0 and 3.0 feet.”
Zone X – “is the flood insurance risk zone that corresponds to areas outside the 0.2-
percent-annual chance floodplain, and includes the following areas within the 0.2-percent-
annual-chane floodplain: Those areas of 1-percent-annual-chance flooding where average
depths are less than 1.0 foot; Those areas of 1-percent-annual-chance flooding where the
contributing drainage area is less than 1.0 square mile, and the areas protected from the 1-
percent-annual-chance flood of the main flooding source by levees.”
Puna Flood Study
Hydrologic and Hydraulic Report
August 2013 91
5 CONCLUSION AND
LIMITATION
This report has documented the data, methodology and results for hydrologic and hydraulic
analysis of the Northern Puna area. HEC-HMS model was used for hydrologic analysis and
FLO-2D model was used for hydraulic analysis. The lumped HEC-HMS model requires
knowledge of the flow direction in advance. HEC-HMS model does not automatically
consider the flow diversion induced by topographic features. Flow diversion curves are
generated by FLO-2D model when necessary for HEC-HMS to simulate the flow diversion.
In the Puna study area, stream channels are not well developed, and the two dimensional
FLO-2D model provides a better estimate of flow distribution in the watershed. Generally
FLO-2D, as also a hydrology model, works well in the Puna study area, where the overland
flow is prevalent. However, since FLO-2D hydrology model is not an accepted hydrology
model by FEMA, the FLO-2D hydrology model is only presented for the comparison
purpose (Appendix A).
The HEC-HMS model results were compared with the FLO-2D model results. The HEC-
HMS results match well with the FLO-2D results. The differences between the two models
at the major junctions are within 15%. Based on this comparison, HEC-HMS model results
provide good estimations for the four storm events. The hydrologic results of HEC-HMS
model are sufficiently accurate to use as input to the FLO-2D model in hydraulic analysis.
FLO-2D is listed on the FEMA’s list of approved hydraulic models for riverine and
unconfined flood studies. The project area mainly consists of recent lava flow and currently
there are no well-defined stream channel due to the slow development of soil mantle and
high permeability of the soil. Shallow flooding is dominated in this area. Historically surface
sheet flow flooding ensues throughout the project area when large storm events occur.
The hydraulic calibration to the November 1 to 2, 2000 flood event proved that the FLO-
2D model replicated historical flood closely. The hydraulic analysis found that the
unconfined overland flooding is common at Puna area. Results of the FLO-2D model have
demonstrated that model has performed consistently and reasonably.
There are still some limitations for this flood study:
LiDAR data from Airborne 1 USA were used to provide the FLO-2D terrain information.
The LiDAR data used in this study meets the minimum standards to pass the quantitative
assessment (vertical accuracy) and is marginally acceptable for detailed qualitative
assessment. There are some errors and anomalies in the LiDAR data, which is common and
typical for this type of geographic data in the dense vegetated areas like Puna. The FLO-2D
model interpolated the LiDAR data by filter criteria and assigned an average topographic
data for each grid size. This was done to alleviate the influence of the original data errors. In
general, FLO-2D results are expected to be reasonable and reliable.
The hydraulic analysis assumed no sedimentation and debris blockages of the bridge
openings. Water loss due to cavities and lava tubes were not considered in this study. This
Puna Flood Study
Hydrologic and Hydraulic Report
August 2013 92
study reflects flooding potentials based on conditions existing at the northern Puna area at
the time of completion of this study. Maps and flood elevations should be amended
periodically to reflect future changes.
Puna Flood Study
Hydrologic and Hydraulic Report
August 2013 93
REFERENCES
Barnes, H. H. 1967. Roughness characteristics of natural channels. Washington, DC: US
Government Printing Office.
Chow, V. T. 1959. Open Channel Hydraulics. New York: McGraw-Hill Inc.
City of Boulder Public Works Department, 2012, Upper Goose Creek and Twomile Canyon Creek
Flood Mapping Study Update, 394p, Colorado.
County of Hawai‘i, Department of Planning. 1995. Puna Community Development Plan.
Prepared by Community Management Associates, Inc.
County of Hawai‘i, Department of Planning. 2005. Puna Regional Circulation Plan, Final report.
Prepared by Townscape, Inc.
County of Hawai‘i, Department of Public Works. 1974. Mountain View Drainage Study and
Master Plan. Prepared by Austin, Smith & Associates, Inc.
County of Hawai‘i, Department of Public Works. 1976. Mountain View Drainage Improvements,
Environmental Impact Statement. Hilo, Hawaii.
County of Hawai‘i, Department of Public Works. 1970. Storm Drainage Standard. Hilo,
Hawaii.
Dewberry, 2010. QAQC Report, Oceanit: Puna, Hawaii. Fairfax, VA.
Druecher, Michael and Fan, Pow-foong. 1976. Hydrology and Chemistry of Ground Water in Puna,
Hawai‘i Ground Water 14(5): 328-338.
Facts about Puna Hawai‘i.2012. https://www.punaguide.com/puna-hawaii.html.
Federal Emergency Management Agency. 2004. Flood Insurance Study, Hawaii County, Hawaii.
Washington, DC: US Government Printing Office.
Federal Emergency Management Agency. 2003. Guidelines and Specifications for Flood Hazard
Mapping Partners. Washington, DC: US Government Printing Office.
Federal Emergency Management Agency. 2007. Requirements of 44 CFR Section 65.10: Mapping
of Areas Protected by Levee Systems.
Federal Emergency Management Agency. 2011. Analysis and Mapping Procedures for Non-
Accredited Levees.
FLO-2D Software, Inc. 2006. FLO-2D user’s manual, Version 2006.01.
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August 2013 94
FLO-2D Software, Inc. 2009. FLO-2D Reference manual, 2009.
Hawaiian Acres Community Association.2011.The History, Biology, Geology and Current Living
Conditions of Hawaiian Acres. http://www.hawaiianacres.org/history.shtml
Interagency Advisory Committee on Water Data. 1982. Guidelines for determining flood flow
frequency (Bulletin #17B of the Hydrology Subcommittee). Reston, VA.
James, W.P., J. Warinner, and M. Reedy. 1992. Application of the Green-Ampt Infiltration
Equation to Watershed Modeling. Water Resources Bulletin 28(3): 623-635.
Juvik, Sonia P. and Juvik, James O..1983. Atlas of Hawaii, third edition. Honolulu: University of
Hawai‘i Press
Lau, L. S., & Mink, J. F. 2006. Hydrology of the Hawaiian Islands. Honolulu: University of
Hawai‘i Press.
Lee, Rhodes Diane. 2001. A cultural history of three traditional Hawai‘i sites on the west coast of
Hawai‘i island. Overview of Hawaii History.
(http://www.donch.com/LULH/culturehist6.htm)
Loucks, Eric.2009. FEMA Levee Analysis Guidelines PowerPoint slides.National Oceanic and
Atmospheric Administration. 2011.Precipitation Frequency Data Server. Available from
http://hdsc.nws.noaa.gov/hdsc/pfds/
MacDonald, G. A., Abbott, A. T., and Peterson, F. L. 1970. Volcanoes in the sea: The geology of
Hawaii. Honolulu: University of Hawai‘i Press.
Natural Resources Conservation Service. 1986. Urban Hydrology for small watersheds(Technical
Release 55). Washington, DC: US Government Printing Office.
Natural Resources Conservation Service. 2006. Physical Soil Properties, Island of Hawaii.
Washington, DC: US Government Printing Office.
National Weather Service Forecast Office, Honolulu, HI. Hawaii Archived Hydronet Data.
Available from http://www.prh.noaa.gov/hnl/hydro/hydronet/hydronet-data.php
National Oceanic and Atmospheric Administration, Precipitation Frequency Data Server. Altas 14
Point Precipitation Frequency Estimates. Available from
http://hdsc.nws.noaa.gov/hdsc/pfds/
Oki, Delwyn S. 2003. Surface Water in Hawai‘i. U.S. Geological Survey.
Perica, S., Martin, D. B. Lin, Parzybok, T., Riley, D., Yekta, Hiner, M. L., Chen, L.-C.
Brewer, D., Yan, F., Maitaria, K., Trypaluk, C., Bonnin, G.M.. 2009). Precipitation-
Frequency Atlas of the United States. NOAA Atlas 14, Volume 4, Version 2, NOAA, National
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Weather Service, Silver Spring, Maryland, 2009 Extracted: Tue April 18, 2011. Available
from http://hdsc.nws.noaa.gov/hdsc/pfds/hi/hi_pfds.html
Puna Weather. 2012. http://www.punaguide.com/Puna-weather.html
Sato, H.H., Ikeda, W., Paeth, R., Smythe, R. and Takehiro, Jr. M. 1973. Soil Survey of the Island
of Hawaii, State of Hawaii. USDA, Soil Conservation Service, Washington, DC
Stearns, H.T., and Macdonald, G.A. 1946. Geology and Ground-water Resources of the Island of
Hawai‘i: Hawai‘i (Terr.) Division of Hydrography Bulletin 9, 363 p.; 2 folded maps in
pocket (scale 1:125,000) [includes plates].
Sonia, P. Juvik, and James, O. Juvik. 1983. Atlas of Hawai‘i, third edition. Honolulu: University
of Hawai‘i Press.
Tetra Tech, Inc. 2002. Development of the Middle Rio Grande FLO-2D Flood Routing Model Cochiti
Dam to Elephant Butte Reservoir. New Mexico.
University of Hawai’i at Hilo.2003. Natural Hazards Big Island-Flood Hazards Gallery.
http://hilo.hawaii.edu/~nat_haz/floods/gallery.php.
U.S. Army Corps of Engineers, Honolulu District. 1990. Alenaio Stream Flood Control Project,
Hilo, Hawai‘i, General Design Memorandum and Environmental Assessment Study.
U.S. Army Corps of Engineers, Honolulu District. 2006. Waiakea Stream Flood Damage
Reduction Feasibility Study, Hilo, Hawai‘i.
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U.S. Geological Survey, Water Resources Investigations Report 02-4117. 2002. Streamflow and
Erosion Response to Prolonged Intense Rainfall of November 1-2, 2000, Island of Hawaii, Hawaii.
By Richard A. Fontaine and Barry R. Hill.
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August 2007, for Kilauea East Rift Zone Eruptions, Hawaii Island. By Jim Kauahikaua.
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Kīlauea Volcano, Hawai‘i.12(1). 1-65.
Appendix A
FLO-2D HYDROLOGGY MODEL DEVELOPMENT
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August 2013 A-1
APPENDIX A
A. FLO-2D Hydrology Model Development
A.1 FLO-2D Model Overview
FLO-2D is a two-dimensional flood routing model that can simulate unconfined overland
flow, channel flow, floodwave attenuation, floodplain inundation, spatially variable water
depth and infiltration. FLO-2D is based on a volume conservation principle that distributes
a flood hydrograph over a system of grid elements developed from a Digital Terrain Model
(DTM). The equation of motion (i.e., full dynamic wave momentum equation) is solved by
computing the average flow velocity across each grid element boundary. The program
calculates values in eight potential flow directions-the four compass directions (north, east,
south, and west) and the four diagonal directions (northeast, southeast, southwest, and
northwest) (Tetra Tech, Inc. 2002). According to FLO-2D User Manual (2006), the FLO-2D
model has the advantage of representing the grid system’s spatial variability over complex
topography and roughness.
FLO-2D (Version 2009) is a FEMA-approved hydraulics model and can be used for both
hydrologic and hydraulic analyses. Rainfall and runoff can be simulated in the FLO-2D
model to generate hydrographs for downstream watercourses. The storm rainfall is
discretized as a cumulative percent of the total precipitation and can be assigned on the
model domain using a temporal distribution.
In the Puna Flood Study, FLO-2D (Version 2009) was employed to perform the hydrologic
analyses for the purpose of comparison with the HEC-HMS model results. As an integrated
flood routing model, FLO-2D couples hydraulic simulation with hydrologic simulation. The
FLO-2D model for this study was set up and executed for both hydrologic simulation and
hydraulic simulations. The FLO-2D computations were carried out over the whole
watershed; therefore calculating the time of concentration was unnecessary.
A.1.1 Topographic Database
Terrain data must be provided in a DTM file to start a flood simulation in FLO-2D. Oceanit
obtained light detection and ranging (LiDAR) data from the County, which has a separate
contract with Airborne 1 to collect the data. The LiDAR data were collected from 2007
through 2008. The product is a mass point dataset with an average point spacing of 8 feet.
Oceanit formed the DTM data for the Puna Study Area with a re-sampling resolution of 16
feet by 16 feet. This resolution gives one elevation point within an area of 256 square feet
(ft2). The re-sampled data from Airborne 1 was used to build the FLO-2D models using a
128-foot x 128-foot grid cell size. Each grid element contained an average of 64 elevation
points from which the grid elevations were determined.
At the areas with significant structures, such as the South Kūlani Flood Diversion Structure
the major bridges, and culverts, the ground survey data were used to better define the
elevations of these structures. All elevation data utilized were based on the North American
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August 2013 A-2
Horizontal Datum of 1983 (NAD–1983–HARN–StatePlane–Hawaii–1–FIPS–5101–Feet).
The vertical datum was based on the tidal datum.
The FLO-2D software package includes a grid developer system (GDS), which prepares the
basic input files and overlays the grid system on a DTM set of points. The main purpose of
the GDS is to filter DTM points, interpolate the DTM data, and assign required parameters
to grid elements. In general, the GDS prepares input files for running the FLO-2D model.
A.1.2 Estimation of Manning’s “n” Values for Overland Flow
In the formulation of the kinematic wave approximation for overland flow, the Manning’s
“n” value or overland flow roughness coefficient plays an important role. Higher the
roughness of the surface, the flow is retarded more and hence the slower the overland
velocity. Suggested typical value of “n” for overland flow on the surface are in the range of
0.2 to 0.35 and does not represent realistic values of “n” that might be used in channel flow
calculations. The overland flow of the FLO-2D model is routed in eight possible flow
directions for each grid element; each cell is treated as an octagon rather than a square.
Typical Manning’s “n” values for overland flow can be found in Table 2 of the FLO-2D
user manual.
The manning’s “n” values of the final model were assigned into three separate categories: the
overland or sheet flow area, the shallow concentrated flow area, and the stream channel. The
final selected “n” values for the overland flow area in the Puna study area were 0.10 to 0.15
(FLO-2D Reference Manual, 2009), and a typical value of 0.125 was used in most overland
flow areas. The overland flow path is primarily a function of the topography. For those areas
with deeper water, lower “n” values were assigned to the grid cells; whereas the higher n
values used were assigned to grid cells with lower water depth. For residential areas, the “n”
values used were 0.065 to 0.10 according to the different surface conditions such as roads,
and grass. The “n” values for stream channels delineated by the FLO-2D model ranged from
0.045 to 0.065.
A.1.3 Estimation of Infiltration Rates
Infiltration is the process by which water seeps into the ground through the surface. The
infiltration rate depends on soil texture and compaction, initial soil water content, vegetative
cover, and the rate of precipitation. The soil types in the Puna study area are shown in
Section 3.4 Basin Loss. Spatially variable infiltration rates were graphically assigned in the
GDS program. Infiltration in FLO-2D is simulated using the Green-Ampt infiltration
method that assumes a ponding condition and a uniformly advancing wetting front, which is
subjected to a soil suction head. The five parameters of the Green-Ampt infiltration method
include hydraulic conductivity, capillarity suction, soil moisture deficit, rainfall abstraction,
and the impervious area for floodplain elements. Only hydraulic conductivity is relevant for
channel elements. The Green-Ampt infiltration parameters used for this study are the same
as those used by the HEC-HMS model.
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A.1.4 FLO-2D Model Sub-domains
The total study area of 180,480 acres (282 mi2) was divided into five smaller areas or sub-
domains for modeling with a 128-foot by 128-foot grid cell size. The selected grid cell size
provides sufficient resolution to represent topographic variations in the study area. The five
sub-domains (Shown in Figure A-1) were labeled North, South, Middle North, Middle South
and Middle East. The sub-domains were delineated based on the available LiDAR
topographic data. The North and South sub-domains are independent of the other sub-
domains. The Middle North sub-domain receives inflow from the Middle South sub-domain,
and the Middle East sub-domain receives inflow from both the Middle North and Middle
South sub-domains.
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A.1.5 Meteorological Events
The Puna study area covers a very large area and the intensity and distribution of rainfall
vary greatly from sub-watershed to sub-watershed. The study area was divided into 39 sub-
watersheds, as shown in Figure 3-1 in Section 3. As a grid system model, FLO-2D allows to
apply the rainfall in each grid. In this study, the rainfall amount was applied through the sub-
watersheds in FLO-2D to have an easy comparison with the HEC-HMS model. The
meteorological events used to simulate the rainfall represent varied return periods in a 24-
hour duration. Precipitation frequency estimates from NOAA Atlas 14 (NOAA 2009) were
used to determine the total cumulative rainfall produced by 10-, 50-, 100-, and 500-year
frequency storms in the study area. Atlas 14 contains precipitation frequency estimates for
the United States and U.S. affiliated territories (Perica, et al. 2009). The precipitation in the
centroid of a particular sub-watershed was applied to the entire sub-watershed uniformly.
The precipitation values used for the 10-, 50-, 100-, and 500-year return storm events in a
24-hour were plotted in Figures 3-6 through 3-10 in Section 3. The number in each sub-
watershed is the rainfall value that was used. The rainfall for each model sub-domain was
obtained by calculating the weighted average of the sub-watersheds in each model sub-
domain. Table A-1 lists the calculated rainfall for the various storm return periods in each
domain.
With the IDF for each sub-watershed available, hyetographs were generated from the HEC-
HMS frequency storm method with an intensity position at 50%. Figure A-2 shows a typical
24-hour, 100-year accumulated hyetograph for the study area
Table A - 1 Rainfall for Each FLO-2D Model Sub-domain
Return Period 24-hour Rainfall (in)
North Middle South Middle North Middle East South
10-year 13.70 15.98 16.17 14.46 13.94
50-year 18.95 21.61 22.15 19.88 19.14
100-year 21.36 24.20 24.56 22.35 21.50
500-year 27.36 30.18 30.60 28.51 27.36
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Figure A - 2. Typical 24-hour, 100-year Accumulated Rainfall Distribution.
A.1.6 FLO-2D Model Results
The hydrologic results of the FLO-2D model are presented in Table A-2. This table lists the
results by storm return period and junction. The nine major junctions are identified in Figure
ES-1 and represent key locations in the study area of converging floodwaters. These
junctions were selected to compare the hydrologic results of the FLO-2D model with the
peak discharges given by the HEC-HMS model (Table A-2).
0
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Table A - 2. Puna Study Area FLO-2D Results.
Junctions Description Drainage Area
(mi2)
10-year
(10%
Annual
Chance)
cfs
50-year
(2%
Annual
Chance)
cfs
100-year
(1%
Annual
Chance)
cfs
500-year
(0.2%
Annual
Chance)
cfs
J2 Volcano Rd &
Kahaualeale Rd 22.90 9,596 22,330 33,418 46,266
J3 Near Mauaana
Rd 43.66 17,648 36,532 54,024 74,770
J4 Near ‘Āpele Rd 52.21 17,410 31,291 44,008 63,610
J5 South Kūlani
Rd Bridge 78.00 20,684 39,041 51,602 75,217
J7
Kea‘au-Pāhoa
Rd & Keaau
Bypass Rd
109.63 14,734 31,463 40,507 59,910
J8 Volcano Rd &
Huina Rd 23.25 6,017 13,046 16,191 24,023
J10 Railroad Ave. &
Kea‘au Rd 16.10 1,248 3,684 5,640 11,935
JK1 Pulelehua Rd &
Poola Rd 28.32 777 7,360 16,165 29,194
J16
Waimakao Pele
Rd & Pahoehe
Rd
10.14 171 1,080 2,608 8,581
Appendix B
FIELD SURVEY SOUTH KULANI BRIDGE DIVERSION STRUCTURE
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July 2013 B-1
APPENDIX B
Oceanit contracted the ParEn, Inc. dba Park Engineering to conduct a detail hydraulic
diversion structure survey downstream the South Kūlani Bridge. ParEn, Inc. dba Park
Engineering surveyed the structure during October, 2011. The survey started from the South
Kūlani Bridge and cross-sections were measured in about 100 feet interval and additional
cross-sections were taken when necessary. For each cross-section where a wall exists, two
points on the top of the wall together with one point at the front of the wall and another
point at the back of wall were taken. Figure B1 provides the survey points along the project
site. The points of each cross-section is named by the structure suffix (“S1” represents
Structure 1 and “S2” represents Structure 2) followed by the section number. Figure B2
shows the real structures and in some sections a slope in front of the wall is also depicted.
Figure B3 through B11 provide the surveyed cross-sections comparing with the LiDAR data.
The surveyed data and the LiDAR data generally show similar flow confinement effects
since the crest elevation of the rock wall is not higher than the landward ground elevation in
most of the places. The surveyed cross-sections only show very few pronounced difference
from the LiDAR data.
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Figure B - 3. Surveyed Cross-sections.
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Figure B - 4. Surveyed Cross-sections (continued).
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Figure B - 5.. Surveyed Cross-sections (continued).
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Figure B - 6. Surveyed Cross-sections (continued).
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Figure B - 7. Surveyed Cross-sections (continued).
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Figure B - 8. Surveyed Cross-sections (continued).
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Figure B - 9. Surveyed Cross-sections (continued).
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Figure B - 10. Surveyed Cross-sections (continued).
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Figure B - 11. Surveyed Cross-sections (continued).
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Figure B - 12. Surveyed Cross-sections (continued).
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Figure B - 13. Surveyed Cross-sections (continued).
Appendix C
FIELD SURVEY ROADWAY CULVERTS & BRIDGE CROSSINGS
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August 2013 C-1
APPENDIX C
The field survey team from Oceanit surveyed the major hydraulic structures in the Puna area
during June 14 to 15, 2011. The team applied the GPS instrument (ProHX by Trimble) to
locate and record the critical points on the hydraulic structures. Generally four critical points
on the bridge were geo-referenced using the GPS. Those four critical points are the locations
of the top center of the bridge abutments. Geo-reference photos were taken at each location
to record the details. A tape was then used to refer the other measurements to these geo-
referenced points. The basic measurements included the deck width, the stream bed depth in
the channel, the distance from the deck to the stream bank, the hydraulic width, and the pier
size if applicable. The measurements were taken at both upstream side and downstream side
of the bridges. For the culverts, GPS points were usually taken in the top center of the
headwall. The culvert size and stream bed depth were measured by tape. Notes on the
stream bed conditions, head wall, and wing wall were taken. Sketches were made if
necessary. The GPS coordinates were corrected according to the Benchmark Coconut
(Figure B1) near the intersection of Hawaii Belt Road and Old Volcano Road at Keaau
Town.
The dimensions of the 12 hydraulic structures are listed as follows with photos if applicable
(Notice the difference in horizontal and vertical scales). Rating curves achieved by the HEC-
RAS modeling are plotted.
Figure C- 1. Benchmark for GPS Instrument Error Correction.
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1) Keaau-Pahoa Road Culvert 1
Figure C- 2. Photo of the Keaau-Pahoa Road Culvert 1.
Figure C- 3. Cross-sections of the Keaau-Pahoa Road Culvert 1.
0 20 40 60 80 100 120 140 160 180305
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315
320
325
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Figure C- 4. Rating Curve of the Keaau-Pahoa Road Culvert 1.
2) Keaau-Pahoa Road Culvert 2
Figure C- 5. Keaau-Pahoa Road Culvert 2.
0 10000 20000 30000 40000 50000305
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culvert1 Plan: Plan 02 6/24/2011
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Figure C- 6. Rating Curve of Keaau-Pahoa Road Culvert 2.
3) Waipahoehoe Stream Bridge
Figure C- 7. Waipahoehoe Stream Bridge.
0 2000 4000 6000 8000 10000294
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300
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Figure C- 8. Rating Curve of Waipahoehoe Stream Bridge.
4) Moho Road Culvert 1
Figure C- 9. Photo of Moho Road Culvert 1.
0 10000 20000 30000 40000 50000285
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Figure C- 10. Cross-section of Moho Road Culvert 1.
Figure C- 11. Rating Curve of Moho Road Culvert 1.
0 20 40 60 80 100 120812
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v
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f
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Legend
Ground
Bank Sta
0 20 40 60 80 100 120812
813
814
815
816
817
818
819
820
RS=77.63796Downstream (Culvert)
Station (ft)
Ele
v
a
t
i
o
n
(
f
t
)
0 2000 4000 6000 8000 10000812
814
816
818
820
822
824
826
828
culvert4 Plan: Plan 01 6/23/2011
Geom: culvert4
River = Culvert4 Reach = Tin8 RS = 77.63796 Culv
Q Total (cfs)
W.
S
.
E
l
e
v
(
f
t
)
Legend
W.S. Elev
Puna Flood Study
Hydrologic and Hydraulic Report
August 2013 C-7
5) Moho Road Culvert 2
Figure C- 12. Photo of Moho Road Culvert 2 (Downstream side).
Figure C- 13. Cross-section of Moho Road Culvert 2.
0 50 100 150 200810
811
812
813
814
815
816
RS=153.9224Upstream (Culvert)
El
e
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Legend
Ground
Bank Sta
0 50 100 150 200810
811
812
813
814
815
816
RS=153.9224Downstream (Culvert)
Station (ft)
El
e
v
a
t
i
o
n
(
f
t
)
Puna Flood Study
Hydrologic and Hydraulic Report
August 2013 C-8
Figure C- 14. Rating Curve of Moho Road Culvert 2.
6) South Kūlani Road Bridge
Figure C- 15. Photo of South Kūlani Road Bridge.
0 2000 4000 6000 8000 10000810
815
820
825
830
835
culvert4_cross Plan: Plan 01 6/23/2011
Geom: culvert4_cross
River = curlvet_cross Reach = Tin8 RS = 153.9224 Culv
Q Total (cfs)
W.S
.
E
l
e
v
(
f
t
)
Legend
W.S. Elev
Puna Flood Study
Hydrologic and Hydraulic Report
August 2013 C-9
Figure C- 16. Cross-section of South Kūlani Road Bridge.
Figure C- 17. Rating Curve of South Kūlani Road Bridge.
0 50 100 150 200 2501264
1266
1268
1270
1272
1274
1276
1278
1280
1282
RS=183.7071Upstream (Bridge)
Ele
v
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t
i
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(
f
t
)
Legend
Ground
Bank Sta
0 50 100 150 200 2501264
1266
1268
1270
1272
1274
1276
1278
1280
1282
RS=183.7071Downstream (Bridge)
Station (ft)
Ele
v
a
t
i
o
n
(
f
t
)
0 10000 20000 30000 40000 500001265
1270
1275
1280
1285
1290
1295
Bridge3 Plan: Plan 01 6/24/2011
Geom: Geom 01
River = river 4 Reach = TIN7 RS = 183.7071 BR
Q Total (cfs)
W.
S
.
E
l
e
v
(
f
t
)
Legend
W.S. Elev
Puna Flood Study
Hydrologic and Hydraulic Report
August 2013 C-10
7) Enos Road Culvert
Figure C- 18. Photo of Enos Road Culvert.
Figure C- 19. Cross-section of Enos Road Culvert.
0 50 100 150 2001226
1228
1230
1232
1234
1236
1238
1240
1242
1244
RS=218.5095Upstream (Culvert)
El
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Legend
Ground
Bank Sta
0 50 100 150 2001226
1228
1230
1232
1234
1236
1238
1240
1242
1244
RS=218.5095Downstream (Culvert)
Station (ft)
Ele
v
a
t
i
o
n
(
f
t
)
Puna Flood Study
Hydrologic and Hydraulic Report
August 2013 C-11
Figure C- 20. Rating Curve of Enos Road Culvert.
8) South Pszyk Road Culvert 1
Figure C- 21. Cross-section of South Pszyk Road Culvert 1.
0 2000 4000 6000 8000 100001234
1236
1238
1240
1242
1244
1246
1248
1250
1252
Culvert5_1 Plan: Plan 01 6/23/2011
Geom:
River = river5 Reach = tin12 RS = 218.5095 Culv
Q Total (cfs)
W.S
.
E
l
e
v
(
f
t
)
Legend
W.S. Elev
0 20 40 60 80 100 120 140 1601538
1540
1542
1544
1546
1548
RS=103.4580Upstream (Culvert)
Ele
v
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t
i
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(
f
t
)
Legend
Ground
Bank Sta
0 20 40 60 80 100 120 140 1601538
1540
1542
1544
1546
1548
RS=103.4580Downstream (Culvert)
Station (ft)
Ele
v
a
t
i
o
n
(
f
t
)
Puna Flood Study
Hydrologic and Hydraulic Report
August 2013 C-12
Figure C- 22. Rating Curve of South Pszyk Road Culvert 1.
9) South Pszyk Road Culvert 2
Figure C- 23. Photo of South Pszyk Road Culvert 2.
0 2000 4000 6000 8000 100001538
1540
1542
1544
1546
1548
1550
1552
culvert6u Plan: Plan 01 6/29/2011
Geom: culvert6u
River = river6u Reach = tin6 RS = 148.2235
Q Total (cfs)
W.
S
.
E
l
e
v
(
f
t
)
Legend
W.S. Elev
Puna Flood Study
Hydrologic and Hydraulic Report
August 2013 C-13
Figure C- 24. Cross-section of South Pszyk Road Culvert 2.
Figure C- 25. Rating Curve of South Pszyk Road Culvert 2.
0 20 40 60 80 100 120 140 1601524
1526
1528
1530
1532
1534
1536
RS=132.3269Upstream (Culvert)
Ele
v
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t
i
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(
f
t
)
Legend
Ground
Bank Sta
0 20 40 60 80 100 120 140 1601524
1526
1528
1530
1532
1534
1536
RS=132.3269Downstream (Culvert)
Station (ft)
Ele
v
a
t
i
o
n
(
f
t
)
0 2000 4000 6000 8000 100001526
1528
1530
1532
1534
1536
1538
1540
1542
Culvert6d Plan: Plan 01 6/29/2011
Geom: Culvert6d
River = river6d Reach = tin6 RS = 132.3269 Culv
Q Total (cfs)
W.S
.
E
l
e
v
(
f
t
)
Legend
W.S. Elev
Puna Flood Study
Hydrologic and Hydraulic Report
August 2013 C-14
10) South Kopua Road Bridge
Figure C- 26. Cross-section of South Kopua Road Bridge.
Figure C- 27. Rating Curve of South Kopua Road Bridge.
0 20 40 60 80 100 120 140 1601644
1646
1648
1650
1652
1654
1656
RS=128.1996Upstream (Culvert)
El
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Legend
Ground
Bank Sta
0 20 40 60 80 100 120 140 1601644
1646
1648
1650
1652
1654
1656
RS=128.1996Downstream (Culvert)
Station (ft)
Ele
v
a
t
i
o
n
(
f
t
)
0 2000 4000 6000 8000 100001644
1646
1648
1650
1652
1654
1656
1658
1660
1662
bridge7 Plan: Plan 01 6/29/2011
Geom:
River = river7 Reach = tin3 RS = 128.1996 Culv
Q Total (cfs)
W.S
.
E
l
e
v
(
f
t
)
Legend
W.S. Elev
Puna Flood Study
Hydrologic and Hydraulic Report
August 2013 C-15
11) S. Kopua Road Culvert
Figure C- 28. Cross-section of South Kopua Road Culvert.
Figure C- 29. Rating Curve of South Kopua Road Culvert.
0 20 40 60 80 100 120 140 160 1801650
1655
1660
1665
1670
1675
RS=115.9821Upstream (Bridge)
Ele
v
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t
i
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(
f
t
)
Legend
Ground
Bank Sta
0 20 40 60 80 100 120 140 160 1801650
1655
1660
1665
1670
1675
RS=115.9821Downstream (Bridge)
Station (ft)
Ele
v
a
t
i
o
n
(
f
t
)
0 2000 4000 6000 8000 100001650
1655
1660
1665
1670
1675
bridge8 Plan: Plan 01 6/29/2011
Geom: bridge8
River = river8 Reach = tin5 RS = 115.9821 BR
Q Total (cfs)
W
.
S
.
E
l
e
v
(
f
t
)
Legend
W.S. Elev
Puna Flood Study
Hydrologic and Hydraulic Report
August 2013 C-16
12) North Oshiro Road Bridge 2.
Figure C- 30. Photo of North Oshiro Road Bridge 2.
Figure C- 31. Cross-section of North Oshiro Road Bridge 2.
0 50 100 150 2001930
1935
1940
1945
1950
1955
RS=196.4366Upstream (Bridge)
Ele
v
a
t
i
o
n
(
f
t
)
Legend
Ground
Bank Sta
0 50 100 150 2001930
1935
1940
1945
1950
1955
RS=196.4366Downstream (Bridge)
Station (ft)
Ele
v
a
t
i
o
n
(
f
t
)
Puna Flood Study
Hydrologic and Hydraulic Report
August 2013 C-17
Figure C- 32. Rating Curve of North Oshiro Road Bridge 2.
0 2000 4000 6000 8000 100001930
1935
1940
1945
1950
1955
1960
1965
Bridge10 Plan: Plan 01 6/29/2011
Geom: Geom 01
River = bridge10 Reach = tin1 RS = 196.4366 BR
Q Total (cfs)
W.
S
.
E
l
e
v
(
f
t
)
Legend
W.S. Elev