HomeMy WebLinkAboutLiterature Review and Data Gap Analysis Task 2 - Community Advisory Committee ReviewJune 4, 2026 1
Hilo Bay Resilience and Watershed Management Plan
Task 2 Deliverables-Review
On May 7, 2026, the Draft Literature Review and Data Gap Analysis report submitted by Lynker
Corporation was forwarded to members of the Community Advisory Committee with this note:
Aloha,
I am sharing with you the first draft deliverable under our contract with Lynker
Corporation. Please see my brief explanation below and then kindly review the
draft. Please share with me via email any comments, questions, ideas, or data
sources that may help guide this process. I will compile all input, present the
compilation to Lynker, and we will review at a soon to be scheduled Committee
meeting.
Aim for the end of May for comments and questions.
Background: The 2005 Hilo Bay Watershed-Based Restoration Plan was not
approved as a Watershed Management Plan due in large part to insufficient data.
The U.S. Army Corps of Engineers indicated that additional technical studies
including water quality monitoring, was needed to complete a data-informed
Watershed Management Plan.
Since 2005, many organizations, the University of Hawaiʻi at Hilo in particular,
have continued to contribute to data reporting on Hilo Bay and the watershed.
The County asked its contractor to compile available data and to identify data
gaps needed to complete the technical studies needed for a meaningful
management plan.
The draft was compiled by three of Lynker Corporation's subcontractors for
discussion and review by the County and the Community Advisory Committee.
Five committee members generously submitted comments, recommendations, and additional
resources. The following collection of responses is being forwarded to Lynker and the
Community Advisory Committee.
June 4, 2026 2
COMMENT #1 – LITERATURE REVIEW
One Community Advisory Committee Member spotted a reference for a study that does not
exist:
• Mead, L. H., & Wiegner, T. N. (2010). Surface water quality along the longitudinal
continuum of Canoes-Waiākea Stream, Hilo, Hawaiʻi. Pacific Science, 64(4), 539–549.
https://doi.org/10.2984/64.4.539
This member also suggested Lynker conduct a thorough literature search in the UH Hilo
Hawaiian collection as well as the TCBES MS repository.
June 4, 2026 3
COMMENT #2 – REPORT STRUCTURE AND CONTEXT
Another Committee Member remarked that the document is very raw with no framework or
integration. They recommended that there should be a synthesized analysis along with a
description of the workplan (to understand the sequence of tasks and roles of the
subcontractors) and a preliminary outline of a water quality management plan to understand
the context. They also noted that the document focuses on surface flow— anyone analyzing
groundwater flow? Anyone analyzing the sensitivity of the receiving waters in terms of
circulation patterns and ecosystem/substrate types.
June 4, 2026 4
COMMENT #3 – ADDITIONAL RESOURCES FOR LITERATURE REVIEW
Former Hilo Bay Watershed Advisory Group Member provided several resources (some are
duplicates of resources on the project webpage):
• Flood Insurance Study, Hawaii County, Hawaii, Federal Emergency Management Agency
Flood Insurance Study Number 155166V001B
• https://dlnreng.hawaii.gov/nfip/wp-content/uploads/sites/11/2018/01/155166V001B-
09292017.pdf
• Streamflow and Erosion Response to Prolonged Intense Rainfall of November 1–2, 2000,
Island of Hawaii, Hawaii, USGS
• https://pubs.usgs.gov/wri/wri02-4117/pdf/wri02-4117.pdf
And these resources related to Hilo Bay Breakwater:
• HBWAG report: http://www.hilobaywatershed.org/news/breakwater-study/ (Beth’s
note: Broken link.)
• Base and Storm Flow Conditions Weigner & Mead: http://www.hawaii-
county.com/info/Hilo/Hilo%20Bay%20UH%20Final%20Report%202009.pdf
• http://www.springerlink.com/content/a87umrhr150t2p84/
• Hilo Harbor 2035 Master Plan 2009:
http://www.hawaiiharborsplan.com/docs/090519HiloPIMMeeting.pdf
• USDA NRCS Hilo Bay Rapid Watershed Assessment 2008: ftp://ftp-
fc.sc.egov.usda.gov/HI/pub/technical/rwa/09_rwa/Hilo_RWA.pdf (Beth’s note: Broken
link.)
• Big Island Weekly 2009 article on the Breakwater:
http://www.bigislandweekly.com/articles/2009/05/01/read/comment/comment03.txt
• Big Island Weekly article – Dr. Adolf’s buoy & the breakwater 2010:
http://www.bigislandweekly.com/articles/2010/03/31/read/comment/comment03.txt
• Hon Ad 2006 60th Ann. Of ’46 tsunami & effects:
http://the.honoluluadvertiser.com/150/sesq3tsunami
• Clean Hilo Bay 2005:
http://the.honoluluadvertiser.com/article/2005/Apr/11/ln/ln03p.html
• Hilo Bay Watershed-Based Restoration Plan
http://hawaii.gov/health/environmental/water/cleanwater/prc/pdf/WatershedBasedPla
nHiloBay.pdf
• Letter for funding for Modeling Project:
http://records.co.hawaii.hi.us/Weblink/DocView.aspx?id=25808&page=1&dbid=0
(Beth’s note – broken link.)
June 4, 2026 5
• Letter of support – Modeling Project– Keaukaha Community Assn:
http://records.co.hawaii.hi.us/Weblink/0/doc/25604/Page1.aspx (Beth’s note – broken
link.)
• USACE circulation report 2009:
http://www.csc.noaa.gov/cz/CZ09_Proceedings/Abstract%20PDFs/Poster.Podoski.pdf
• 2008 Variation of sediment trace elements and stream nitrate isotope ratios with land
use in the Waiulaula and Hilo Bay watersheds, Hawai'i Island, Hawai'i. Tait, James R.
Thesis (M.S.)- -University of Hawai'i at Hilo Hawaiian Collection; GB857.3.H3 T3 2009a.
• 2008 Surface water metabolism in a tropical estuary, Hilo Bay, Hawaiʻi, USA, during
storm and non-storm conditions Mead, Lucas H.UH Hilo Hawaiian Collection; GC297 .M4
2009a
• Brief History of Breakwater Construction: http://books.google.com/books?id=K6ChFt5o-
qUC&pg=PA101&lpg=PA101&dq=Hilo+Bay+Breakwater&source=bl&ots=5uB8HzJUna&si
g=g0krWWcdLt72YIQ8aOwpVdyTPoY&hl=en&ei=xEV_TNX5Fo_sngef3vXlAQ&sa=X&oi=b
ook_result&ct=result&resnum=22&ved=0CGUQ6AEwFQ#v=onepage&q=Hilo%20Bay%2
0Breakwater&f=false
• 1991 Distribution and dispersion of sewage pollution in Hilo Bay and contiguous waters
Dudley, Walter C., 1945-; Hallacher, Leon E.; Hammond, Thomas.UH Hilo Hawaiian
Collection; TD525.H5 D83 1991
• 1986 Final supplemental environmental impact statement for the proposed Hilo Bay
outfall sewer extension, Hilo, Hawaii. M & E Pacific, Incorporated. Hawaii (County).
Department of Public Works.UH Hilo Hawaiian Collection; TD194.5.S3 M2 1986.
• 1986 Draft supplemental environmental impact statement for the proposed Hilo Bay
outfall sewer extension, Hilo, Hawaii M & E Pacific, Incorporated.; Hawaii Island (Hawaii).
Department of Public Works.UH Manoa Hawaiian (Library Use Only); TD194.5.S3 M2
1986b
• 1985 Hilo Bayfront : a survey report and environmental impact statement for shore
protection and beach restoration United States. Army. Corps of Engineers.UH Hilo
Hawaiian Collection;TD194.5.H3 U533 1985
• 1985 Study on Hilo Bay Water Quality:
http://scholarspace.manoa.hawaii.edu/bitstream/10125/931/3/v39n3-266-273.pdf.txt
• 1983 Hilo area comprehensive study, Hawaii. vol. 3, A draft survey report and
environmental impact statement for Hilo Bayfront Beach United States. Army. Corps of
Engineers.UH Hilo Hawaiian Collection;TC225.H54 U5 1983b
• 1983 Numerical modeling of tsunami inundation of Hilo Harbor Mader, Charles L.; Curtis,
George.; University of Hawaii (Honolulu). Joint Institute for Marine and Atmospheric
Research. UH Manoa Hawaiian (Library Use Only);GC222.H3 M3 1991
June 4, 2026 6
• 1981 Circulation and sediment transport study, Hilo Bayfront Beach,Hilo, Hawaii. Sea
Engineering, Inc.; United States. Army. Corps of Engineers. UH Hilo Hawaiian
Collection;TC225.H54 S43 1981
• 1981: Hilo Bay, a chronological history : land and water use in the Hilo Bay area, island of
Hawaii. Kelly, Marion, 1919-2011.Nakamura, Barry; Barrère, Dorothy B. UH Hilo:
Hawaiian collection; DU629.H5 K44
• 1980 Geological, biological, and water quality investigations of Hilo Bay: final report M &
E Pacific, Inc.; United States. Army. Corps of Engineers. UH Hilo Hawaiian
Collection;GB1025.H3 M2
• 1979 Hilo Bay sand survey United States. Army. Corps of Engineers. Pacific Ocean
Division.; Ocean Innovators.UH Manoa Hawaiian (Library Use Only); TZ 880613.02
• 1977 First spring season environmental studies, Hilo Bay, Hawaii : final report. Sunn, Low,
Tom & Hara.; United States. Army. Corps of Engineers. Honolulu District.UH Hilo
Hawaiian Collection; TD194.5.H3 S8
• 1973 Need for a Hilo Bay study. Hawaii Island Chamber of Commerce.UH Hilo Hawaiian
Collection - HE560.H54 H37.
• 1971 Hilo Bay pollution study Osato, Michael S.; Yuen, Mary Lou.; Chan, John G. UH Hilo
Hawaiian Collection - TD224.H3 H5.
• 1971 Biological, chemical, and sociological consequences of pollution in Hilo Bay, Hawaii.
Hammer, Helen.; Dickson, Patricius. pages 133-138. UH Manoa Hawaiian (Library Use
Only); REPRINT H045.15
• 1965 review of the experimental data relative to the pilot model study for the design of
Hilo Harbor Tsunami Model Keulegan, G. H.UH Hilo Hawaiian Collection; GC220.4.H3 K49
• 1965 Physically feasible means for protecting Hilo from tsunamis : third report Hilo
Technical Tsunami Advisory Council.UH Hilo Hawaiian Collection;GC220.4.H3 H5
• 1963 A study of dispersion in Hilo Bay, Hawaii O'Connell, R. L.,Walter, C. M.United States.
Division of Water Supply and Pollution Control.UH Hilo Hawaiian Vault - Library Use
Only;GC287 .O3 1963
• Simulation of 1960 tsunami hitting the breakwater (watch the left portion)
http://www.youtube.com/watch?v=xFDsZ24tyEA
• 1957 Hilo Seawall, Island of Hawaii, Territory of Hawaii. Munk, Walter H. (Walter
Heinrich),UH Hilo Hawaiian Collection; GC220.4.H3 M8.
• HVO potential of the 1984 lava flow:
http://hvo.wr.usgs.gov/volcanowatch/2002/02_10_31.html
• Local Memory: http://kaukaohana.com/kauka_genealogy_lauchong.html
• Coral Layer below the Panaewa Flow, (and Blondes Reef):
http://www.agu.org/pubs/crossref/1996/95JB03215.shtml
June 4, 2026 7
• Shipweck list (to be verified): http://www.captainrick.com/shipwrecks.htm
• USACE Breakwater Repair reports (Hilo pg 13-15)
http://chl.erdc.usace.army.mil/Media/4/4/3/TechReport4.pdf
• Dives along the breakwater:
http://books.google.com/books?id=m0sDtp33BWQC&pg=PA45&lpg=PA45&dq=Hilo+Bay
+Breakwater&source=bl&ots=rTWV0ODwzR&sig=I9kDCyczW1OSiyBoQCvA7qcT984&hl=
en&ei=xEV_TNX5Fo_sngef3vXlAQ&sa=X&oi=book_result&ct=result&resnum=58&ved=0
CPABEOgBMDk#v=onepage&q=Hilo%20Bay%20Breakwater&f=false
• Old engineering report of the construction:
http://books.google.com/books?id=xKfmAAAAMAAJ&pg=PA699&lpg=PA699&dq=Hilo+B
ay+Breakwater&source=bl&ots=Komliyg7pf&sig=HhsDHOU8Cp5DeJW09ffQB7YMJ0o&hl
=en&ei=xEV_TNX5Fo_sngef3vXlAQ&sa=X&oi=book_result&ct=result&resnum=61&ved=
0CPsBEOgBMDw#v=onepage&q=Hilo%20Bay%20Breakwater&f=false
• Documents relating to a proposed breakwater at Hilo, Territory of Hawaii Slattery, J. L.;
Heuer, W. H. (William Henry), 1843-1925.; Thurston, Lorrin A. (Lorrin Andrews). UH Hilo
Hawaiian Vault - Library Use Only;TC324.1 .D62
• 1916 statements almanac on the beginning of the breakwater:
http://books.google.com/books?id=qEYNAAAAIAAJ&pg=PA644&lpg=PA644&dq=Hilo+Ba
y+Breakwater&source=bl&ots=C_-
beMBT78&sig=RXpiAkPdRDZFzzrr3SWNnXpK7UI&hl=en&ei=xEV_TNX5Fo_sngef3vXlAQ&
sa=X&oi=book_result&ct=result&resnum=69&ved=0CJgCEOgBMEQ#v=onepage&q=Hilo
%20Bay%20Breakwater&f=false
June 4, 2026 8
COMMENT #4 – IMPORTANCE OF UPPER WATERSHEDS/LIT SEARCH
A Committee Member said there was inadequate consideration of the landcover scenarios in
the upper watersheds. The model in the Lynker part of the study does not include the upper
reaches of the watersheds, it almost entirely cuts off all the conservation land.
The member went on to say, “However, I’d hope that consideration of scenarios for green
infrastructure would include scenarios of protecting upper watershed areas in the conservation
land, from approximately the 3,000-8,000’ elevations. That is where the highest rainfall exists
and where landcover changes will be most important for retaining water. This includes scenarios
for installing fence units in the native forest to prevent damage from hooved animals. The
status of native vs alien landcover is a critical factor in stormwater scenarios, both from a
flooding and sedimentation perspective. There have been studies that show that fenced forests
are 25% faster at infiltrating rainwater than forests that are unfenced with feral pigs. Further,
studies show that these native forests are 15 times faster at infiltration than bare ground. Thus,
including in the model scenarios where the upper elevation forest is protected (where we install
fences that protect thousands of acres of native forest) vs scenarios where these forests are left
unprotected and converted to non-native forest will be important for quantifying the
importance of the green infrastructure options.”
The committee member attached a literature review for me to share with the consultant team
that justifies the importance of considering the status of the upper watershed lands. References
from the literature review are included below:
• Izuka, S.K., 2012, Sources of suspended sediment in the Waikele watershed, O‘ahu,
Hawai‘i: U.S. Geological Survey Scientific Investigations Report 2012–5085, 28 p.
https://pubs.usgs.gov/sir/2012/5085/sir2012-5085.pdf.
• Townscape, Inc and AECOM. 2018. Kaiaka Bay Watershed-Based Plan. Volume 1:
Watersheds Characterization. Prepared for the City & County of Honolulu – Department
of Facility Maintenance and the Hawaiʻi State Department of Health- Clean Water
Branch. https://health.hawaii.gov/cwb/files/2018/05/Kaiaka-WBP-Vol -1-
Characterization-Final.pdf
• State of Hawai’i, Department of Health. 2019. 2019 State of Hawaii Water Quality
Monitoring and Assessment Report: Integrated Report to the U.S. Environmental
Protection Agency and the U.S. Congress Pursuant to §303(d) and §305(b), Clean Water
Act (P.L. 97-117)
• https://health.hawaii.gov/cwb/files/2018/09/Final-2018-State-of-Hawaii-Water-Quality-
Monitoring-Assessment-Report.pdf
• Stock, Jonathan and Gordon Tribble, 2010, Erosion and Sediment Loads from Two
Hawaiian Watersheds, 2nd Joint Federal Interagency Conference
June 4, 2026 9
• Izuka, S.K., and Abbott, L.L., 2010, Streamflow, suspended-sediment, and soil-erosion
data from Kaulana and Hakioawa watersheds, Kaho‘olawe, Hawai‘i, 2006 to 2010: U.S.
Geological Survey Open-File Report 2010–1182, 40 p.
• Pacific Islands Water Science Center Data. United States Geological Survey. Cited in
Stock, J.D., Falinksi, K.A., Callender, T., 2016, Reconnaissance sediment budget for
selected watersheds of West Maui, Hawai‘i: U.S. Geological Survey Open-File Report
2015–1190, 42 p., http://www.dx.doi.org/10.3133/ofr20151190.
• Yamamoto, Teruo; Duffy, Paul. 1963. Water storage capacities of soil under four different
land uses in Hawaii. Res. Note PSW-RN-005. Berkeley, CA: U.S. Department of
Agriculture, Forest Service, Pacific Southwest Forest and Range Experiment Station. 4 p.
• Perkins, K., J. D. Stock, J. R. Nimmo. 2018. Vegetation Influences of Infiltration on
Hawaiian Soils. Ecohydrology. https://onlinelibrary.wiley.com/doi/abs/10.1002/eco.1973
• Berio Fortini, L., Leopold, C.R., Perkins, K.S. Chadwick, O., Yelenik, S., Jacobi, J., Bishaw,
K., Gregg, M., Rosa, S., 2021. Landscape level effects of invasive plants and animals on
water infiltration through Hawaiian tropical forests. Biol Invasions.
https://doi.org/10.1007/s10530-021-02494-8
• Field, M. E.; S. Cochran; J. Logan, C. Storlazzi. 2008. The Coral Reef of South Moloka‘i,
Hawai‘i – Portrait of a Sediment-Threatened Fringing Reef.
https://pubs.usgs.gov/sir/2007/5101/ maui
• J. Jacobi, 2013. Ridge To Reef Project Update.
• Stock, J. 2014. Forum: Assessing Impacts of Watershed Projects on Reducing Sediment
Erosion and Transport in West Maui – Lessons Learned and Future Directions. Hawaii
Conservation Conference, Honolulu.
• Falinski, K., D. Minton, R. Kallstrom, S. Tom, R. Carr, E. Conklin. The Nature Conservancy,
2024. Coral Reef and Water Quality Surveys of South Shore Molokai. Report prepared by
The Nature Conservancy with support from the National Oceanic and Atmospheric
Administration’s Coral Reef Conservation Program through a grant from the National
Fish and Wildlife Foundation.
• Izuka, S.K., 2012, Sources of suspended sediment in the Waikele watershed, O‘ahu,
Hawai‘i: U.S. Geological Survey Scientific Investigations Report 2012–5085, 28 p.
https://pubs.usgs.gov/sir/2012/5085/sir2012-5085.pdf
• Rosa, S. 2013. Evaluating Land-Cover Change Effects on Runoff and Recharge in Kawela,
Moloka’i, Hawai’i. A Thesis submitted to the Graduate Division of the University of
Hawai’i at Mānoa in Partial Fulfillment of the Requirements of the Degree of Master of
Science in Natural Resource and Environmental Management.
https://scholarspace.manoa.hawaii.edu/bitstream/10125/53190/1/Thesis_SRosa_MAY2
013.pdf
• Fortini, et al., 2021.
June 4, 2026 10
• Bipartisan Policy Center, 2023. Floods and Fires: Which States are Most at Risk?
V41_1.pdf (mcusercontent.com)
• Vtorov, I. P. (1993). "Feral pig removal: Effects on soil microarthropods in a Hawaiian rain
forest." Journal of Wildlife Management 57(4): 875-880.
• Fortini, et al., 2021.
• Aplet, G. H., S. J. Anderson, C. P. Stone, 1991. Association between Feral Pig Disturbance
and the Composition of Some Alien Plant Assemblages in Hawai`i Volcanoes National
Park. Vegetatio, Vol. 95, No. 1
• Diong, C. H. 1982. Population Biology and Management of the Feral Pig (Sus scrofa L.) in
Kīpahulu Valley, Maui. University of Hawai’i.
• Hughes III, G. D. 2009. Long-term Biological Resource Monitoring, Waikamoi Preserve,
East Maui, Hawai‘i, 1994 and 2008 Vegetation Monitoring. Contract Report to The
Nature Conservancy.
• Loope, L. L., A. C. Medeiros, B. H. Gagne. 1991. Recovery of Vegetation of a Montane Bog
Following Protection from Feral Pig Rooting. Cooperative National Park Resources
Studies Unit Technical Report 77. University of Hawai’i at Mānoa, Department of Botany.
• Dunkell, D. O. 2009. Runoff, Erosion, Fecal Indicator Bacteria, and Effects of Feral Pig (Sus
scrofa) Exclusion in a Forested Hawaiian Watershed. Pacific Science, 65(2):175-194. DOI:
10.2984/65.2.175. University of Hawai’i at Mānoa.
• Asner, G. P., R. F. Hughes, J. Mascaro, A. Uowolo, D. E. Knapp, J. Jacobson, T. Kennedy-
Bowdoin, J. K. Clark. 2011. High-Resolution Carbon Mapping on the Million-Hectare
Island of Hawai’i. Frontiers in Ecology and the Environment. DOI 10.1890/100179.
• Hess, S. C., J. J. Jeffrey, L. W. Pratt, and D. L. Ball. In Press. Effects of ungulate
management on vegetation at Hakalau Forest National Wildlife Refuge, Hawai`i Island.
Pacific Conservation Biology 16(2)
• Cooray, R. G. and D. Mueller-Dombois (1981). Feral pig activity. Island Ecosystems:
Biological Organization in Selected Hawaiian Communities. D. Mueller-Dombois, K. W.
Bridges and H. L. Carson. Stroudsburg, PA, Hutchinson Ross Publishing Co.: 309-317.
• Jacobi JD. 1981. Vegetation changes in a subalpine grassland in Hawai'i following
disturbance by feral pigs. Honolulu (HI): Cooperative National Park Resources Studies
Unit, University of Hawaii at Manoa, Department of Botany. PCSU Technical Report, 41.
• Katahira, L. 1980. The effects of feral pigs on a montane rain forest in Hawaii National
Park. Proceedings of the Conference National Science Hawaii Volcanoes National Park 3:
173-178. https://scholarspace.manoa.hawaii.edu/bitstream/10125/18389/1/third-173-
178.pdf
• R. K. Loh, L., Tunison, J. T. 1999. Vegetation recovery following pig removal in ʻOlaʻa-Koa
Rainforest Unit, Hawaii Volcanoes National Park. Technical Report 123. University of
June 4, 2026 11
Hawaii Pacific Cooperative Studies Unit, Honolulu. 36 pp.
https://core.ac.uk/download/pdf/5096279.pdf
• Reeser, D. B. Harry. 2005. Controlling Wild Ungulate Populations in Native Ecosystem in
Hawaii. Hawaii Conservation Alliance. http://www.hawaiiconservation.org/wp-
content/uploads/ungulates-1.pdf
• Sasaki, D. M., L. Pang, H. P. Minette, C. K. Wakida, W. J. Fujimoto, S. J. Manea, R. Kunioka,
C. R. Middleton. 1993. Active Surveillance and Risk Factors for Leptospirosis in Hawai’i.
The American Journal of Tropical Medicine and Hygenics. January 1993, 48(1):35-43.
• NTM: Honda JR, Hasan NA, Davidson RM, Williams MD, Epperson LE, Reynolds PR, et al.
(2016) Environmental Nontuberculous Mycobacteria in the Hawaiian Islands. PLoS Negl
Trop Dis 10(10): e0005068. doi:10.1371/journal. pntd.0005068 Link to journal.
• Dunkell, D. O. 2009.
• Anderson, S. J., and C. P. Stone. 1994. Indexing sizes of feral pig populations in a variety
of Hawaiian natural areas. Transactions of the Western Section of the Wildlife Society
30:26-39.
• Giffin, J. 1972. Ecology of the Feral Pig on the Island of Hawaii. Pittman-Robertson
Project No. W-15-3, Study No. II.
• Bolds, S.A., Lockaby, B.G., Kalin, L. et al. Wild pig removal reduces pathogenic bacteria in
low-order streams. Biol Invasions (2022). https://doi.org/10.1007/s10530-022-02731-8
• Giambelluca, T. W., R. A. Sutherland, K. Nanko, R. G. Mudd, A. D. Ziegler, 2009. Effects of
Miconia on Hydrology: A First Approximation. Presented at the: Pulling it Together, 2009
International Miconia Conference May 4-7, 2009 Maui, Hawai’i.
http://www.hear.org/conferences/miconia2009/pdfs/giambelluca.pdf
• Stone, C. P., J. M. Scott, eds. 1985. Hawaii’s Terrestrial Ecosystems: Preservation and
Management. Cooperative National Park Resources Studies Unit, University of Hawai’i.
Honolulu. 104 Lal, R. 1990.
• Lal, R. 1990.
• Smith, C. W., J. T. Tunison. 1985. Fire and Alien Plants in Hawai’i: Research and
Management Implications for Native Ecosystems. In Hawaii’s Terrestrial Ecosystems:
Preservation and Management. Cooperative National Park Resources Studies Unit.
Stone, C. P., J. M. Scott, eds. Cooperative National Park Resources Studies Unit,
University of Hawai’i. Honolulu.
• Takahashi, M., Giambelluca, T. W., Mudd, R. G., DeLay, J. K., Nullet, M. A. and Asner, G. P.
2011. Rainfall partitioning and cloud water interception in native forest and invaded
forest in Hawai'i Volcanoes National Park. Hydrological Processes, 25: 448–464. doi:
10.1002/hyp.7797.
• Kagawa, A., L. Sack, K. Duarte, S. James. 2009. Hawaiian Native Forest Conserves Water
Relative to Timber Plantation: Species and Stand Traits Influence Water Use. Ecological
June 4, 2026 12
Applications. 19(6) 1429-1443
https://esajournals.onlinelibrary.wiley.com/doi/10.1890/08-1704.1
• Cavaleri, M., L. Sack. 2010. Comparative water use of native and invasive plants at
multiple scales: A global meta-analysis. Ecology. Sep;91(9):2705-15.
https://esajournals.onlinelibrary.wiley.com/doi/abs/10.1890/09-0582.1
• McDowell, N., H. Barnard, B. J. Bond, T. Hinckley, R. M. Hubbard, H. Ishi, H. Kustner, F.
Magnani, J.D. Marshall, F.C. Meinzer, N. Phillips, M.G. Ryan, D. Whitehead. 2002. The
relationship between tree height and leaf area: sapwood area ratio. Oecologia 132:12-2.
• Barnard, H. R., M. G. Ryan. 2003. A Test of the Hydraulic Limitation Hypothesis in Fast-
Growing Eucalyptus saligna. Plant, Cell and Environment. 26:1235-1245.
https://onlinelibrary.wiley.com/doi/full/10.1046/j.1365-3040.2003.01046.x
• Engott, J. A. 2011. A water-budget model and assessment of groundwater recharge for
the Island of Hawai`i: U.S. Geological Survey Scientific Investigations Report 2011-5078.
https://pubs.usgs.gov/sir/2011/5078/
• Nanko, K., T.W. Giambelluca, R.A. Sutherland, R. G. Mudd, M. A. Nullet, A. D. Ziegler.
2012. Erosion Potential under Miconia Calvescens stands on the Island of Hawai‘i. Land
Degradation & Development.
https://www.researchgate.net/publication/235784011_Erosion_Potential_under_Miconi
a_calvescens_Stands_on_the_Island_of_Hawai'i.
• Pacific Fire Exchange Newsletter Number 1, April 2014.
https://www.pacificfireexchange.org/research-publications/wildfire-in-hawaii-fact-sheet
• Department of Land and Natural Resources, State of Hawai‘i. 2020. Rapid ‘Ohi‘a Death
Strategic Response Plan 2020-2024. link to journal.
• https://alohachallenge.hawaii.gov/pages/nrm-02-watershed-forest-areas. Contact DLNR
Division of Forestry and Wildlife Native Ecosystem Program Manager Emma Yuen at
emma.yuen@hawaii.gov.
• Kaller, M. D., and W. E. Kelso (2006) Swine activity alters invertebrate and microbial
communities in a coastal plain watershed. American Midland Naturalist: (156)163–177.
https://scholar.google.no/citations?view_op=view_citation&hl=th&user=QZHfX9MAAAA
J&citation_for_view=QZHfX9MAAAAJ:9yKSN-GCB0IC
• American Society of Agricultural Engineers. 2005. Manure Production and
Characteristics.
• West, B. C., A. L. Cooper, and J. B. Armstrong. 2009. Managing wild pigs: A technical
guide. Human-Wildlife Interactions Monograph 1:1–55.
• Bieber, C., and T. Ruf (2005) Population dynamics in wild boar Sus scrofa: ecology,
elasticity of growth rate and implications for the management of pulsed resource
consumers. Journal of Applied Ecology: (42)1203–1213.
https://besjournals.onlinelibrary.wiley.com/doi/full/10.1111/j.1365-2664.2005.01094.x
June 4, 2026 13
• Anthony, Stephen S., Hunt, Jr., Charles D., Brasher, Anne M., Miller, Lisa D., and
Tomlinson, Michael S., 2004, Water quality on the island of Oahu, Hawaii: Reston, Va.,
U.S. Geological Survey Circular 1239, 37 p
https://pubs.usgs.gov/circ/2004/1239/pdf/circular1239.pdf
• United States Geological Survey. Website: Circulation and Sediment, Nutrient,
Contaminant, and Larval Dynamics on Reefs. Accessed May 2, 2019. Link to journal.
• Perez III et al. (2014), Effects of terrigenous sediment on settlement and survival of the
reef coral Pocilloporadamicornis. PeerJ 2:e387;DOI10.7717/peerj.387
https://peerj.com/articles/387/
• NOAA, 2018. Coral Reef Conservation Program Strategic Plan.
https://www.fisheries.noaa.gov/feature-story/noaas-vision-thriving-diverse-and-
resilient-coral-reef-ecosystems
• US Forest Service, 2021. Biological Responses to Stream Nutrients: A Synthesis of
Science From Experimental Forests and Ranges. General Technical Report PNWGTR-9.
Biological Responses to Stream Nutrients: A Synthesis of Science From Experimental
Forests and Ranges. https://research.fs.usda.gov/treesearch/63549
June 4, 2026 14
COMMENT #5 – COMPREHENSIVE TECHNICAL REVIEW
COMMUNITY-BASED HILO BAY
RESILIENCE AND WATERSHED MANAGEMENT PLAN
Comprehensive Technical Review
Task 2: Literature Review & Data Gap Analysis
May 8, 2026
The goal of this review is not to identify deficiencies in the Task 2 deliverable, which represents
a comprehensive and methodologically sound foundation for the overall planning effort, but
rather to provide a forward-looking assessment that can strengthen subsequent project phases,
particularly Task 5b Hydraulic Modeling and Flood Hazard Maps, the water quality monitoring
implementation, and the final watershed management plan. Each thematic section of this
document first characterizes what the Task 2 deliverable establishes, then identifies where
enhancements or further development would yield the greatest planning benefit. Technical
recommendations are drawn from federal agency guidelines, peer-reviewed literature, and
established best practices in watershed science, flood hazard management, and community-
based environmental planning.
Recommendations are assigned a priority level (High, Medium, or Low) reflecting the potential
impact on planning outcomes and an effort-to-address estimate to assist the project team in
sequencing work within the remaining project budget and schedule.
Review Comment Summary
Code Section Topic Priority Effort
RC-01 EA-Modeling Terrain resolution in urban
channels
HIGH Moderate
RC-02 EA – Modeling Bridge and culvert data
collection protocol
HIGH Moderate
RC-03 EA – Modeling Honoliʻi Stream hydrologic
analysis method
HIGH Moderate
RC-04 EA – Modeling Future climate flow projection
methodology
HIGH High
RC-05 EA – Modeling Model calibration using high-
water marks
MEDIUM Moderate
RC-06 EA – Modeling Green infrastructure
effectiveness quantification
MEDIUM High
RC-07 EA – Dat Review Stream bathymetry acquisition
approach
HIGH Moderate
June 4, 2026 15
Code Section Topic Priority Effort
RC-08 EA – Data Review NOAA topo-bathymetric data
integration
MEDIUM Low
RC-09 EA – Data Review Levee and flood control
structure condition
MEDIUM Moderate
RC-10 REDI – Ecological Native vegetation and
restoration suitability
MEDIUM Moderate
RC-11 REDI – Ecological Feral ungulate disturbance and
sediment connectivity
HIGH Moderate
RC-12 REDI – Ecological Coral reef and nearshore habitat
linkage
MEDIUM Low
RC-13 ASU – Water
Quality
SSC monitoring network design
and sampling frequency
HIGH Moderate
RC-14 ASU – Water
Quality
OSDS spatial attribution and
loading model
HIGH Moderate
RC-15 ASU – Water
Quality
Continuous turbidity sensor
network integration
MEDIUM Low
RC-16 ASU – Water
Quality
Fecal indicator bacteria source
tracking
MEDIUM Moderate
RC-17 ASU – Water
Quality
Submarine groundwater
discharge quantification
MEDIUM High
RC-18 ASU – Water
Quality
Nutrient load estimation via
storm even sampling
HIGH Moderate
RC-19 Cross-Cutting Adaptive monitoring framework
and data management
HIGH High
RC-20 Cross-Cutting Community and indigenous
knowledge integration
HIGH Moderate
RC-21 Cross-Cutting Cost-benefit analysis framework
for interventions
MEDIUM High
RC-22 Cross-Cutting EPA Section 319 documentation
and reporting alignment
HIGH Low
Data Gaps and Planned Mitigations
EA identifies five key data gaps: bridge geometry, culvert presence and size, stream bathymetry,
AEP flow rates for Honoliʻi/Wailuku/Alenaio, and future climate flow rates. The associated
mitigation strategies — aerial imagery approximation for structures, bathymetric proxying from
LiDAR water surface elevations, drainage area scaling from gauged data, and literature review
for climate projections — are professionally reasonable interim approaches. EA appropriately
concludes that despite these gaps, adequate information exists to construct reliable hydraulic
models and commits to clearly documenting all assumptions.
June 4, 2026 16
One methodological concern deserves explicit attention: the memorandum states that FEMA’s
effective model flood hazard area maps will serve as the ‘primary reference’ for calibration. This
approach introduces a degree of circularity when the updated model is intended to improve
upon, and potentially supersede, those same FEMA estimates. The effective models include
HEC-1 printouts, HEC-2 files, and HEC-RAS files of varying vintage — some representing
methodologies that predate 2D hydraulic analysis by decades. Using these as primary
calibration targets risks anchoring new model performance to outdated flood estimates.
Primary calibration should instead be grounded in observed flood events, streamgage peak flow
records, and documented high-water marks, with FEMA maps serving as a secondary
consistency check. This is addressed in detail in RC-05 below.
RC-01 Terrain Resolution in Urban Channels and Floodplains—HIGH PRIORITY
Observation: The merged LiDAR surveys (2013, 2018, 2023) will serve as the terrain input
for HEC-RAS 2D models. However, urban floodplain environments in lower Wailuku, Alenaio,
and the Waiākea/Wailoa corridor contain dense infrastructure, subsurface drainage systems,
and constructed channels whose hydraulic conveyance is not fully captured by standard
LiDAR point clouds. Resolution gaps in LiDAR beneath vegetation canopy and at channel
banks can systematically underestimate flood depths in vegetated riparian corridors. The
2013 dataset is now over a decade old and may not reflect post-development changes in the
lower watershed.
Recommended Enhancement: Conduct a targeted supplemental survey (structure-from-
motion photogrammetry or terrestrial LiDAR) of the lower 2–3 km of each modeled stream
reach prior to hydraulic model construction. Establish a minimum mesh cell size of 3–5
meters in the active channel and 10–15 meters in the overbank floodplain to resolve urban
hydraulic features. Where the 2013 LiDAR is the only coverage, identify areas of significant
land use change using Google Earth historical imagery (2013–2025) and flag those areas for
manual terrain correction in the HEC-RAS geometry. Apply USACE Engineering Manual EM
1110-2-1416 guidance on terrain processing for 2D models.
Supporting References: USACE EM 1110-2-1416 (River Hydraulics); Brunner, G.W. (2016),
HEC-RAS 2D Modeling User’s Manual, USACE HEC; McKean et al. (2009) Remote sensing of
channel morphology and hydraulic rating curves in mountain rivers, Water Resources
Research; FEMA (2020), Guidance for Flood Risk Analysis and Mapping: Hydraulic Models.
RC-02 Bridge and Culvert Data Collection Protocol—HIGH PRIORITY
Observation: Limited bridge geometry and uncertain culvert presence are among the most
consequential data gaps for model accuracy. Bridges and culverts are primary flow controls
in the urban lower watershed and omitting them or approximating them incorrectly can
June 4, 2026 17
shift 100-year floodplain boundaries by tens to hundreds of meters. The proposed
mitigation of approximating geometry from Google Earth and terrain data is a reasonable
interim approach but is insufficient for final flood hazard mapping intended to support
regulatory and planning decisions.
Recommended Enhancement: Develop a structured field data collection protocol for all
bridges and culverts within each modeling domain prior to the Task 5b model build. At
minimum, record deck thickness, deck elevation (top and bottom chord), span length, pier
dimensions, roadway profile, and inlet/outlet condition for culverts. Coordinate with the
County of Hawaiʻi Department of Public Works for as-built drawings and inspection records.
Apply USACE Engineering Manual EM 1110-2-1603 guidance on hydraulic structure
representation in HEC-RAS. For bridges with scour potential, particularly Wailuku River
crossings, flag for FHWA HEC-18 scour analysis as a secondary deliverable recommendation
for future project phases.
Supporting References: USACE EM 1110-2-1605 (1987) (Hydraulic Design of Navigation
Dams); Richardson & Davis (2001), Evaluating Scour at Bridges (HEC-18), FHWA; Brunner
(2016), HEC-RAS 2D Modeling User’s Manual; FEMA (2016), Bridge Modeling in HEC-RAS
Technical Note.
RC-03 Honoliʻi Stream Hydrologic Analysis Method—HIGH PRIORITY
Observation: Honoliʻi Stream has no FEMA flood hazard mapping, meaning no prior
hydrologic study has established AEP peak flows for this watershed. The USGS gage
(#16717000) measures discharge in the upper watershed near the forest boundary, not at
the channel outlet to Hilo Bay. The coastal plain contributing area below the gage —
including urban land cover additions from Kaumana, Puainako, and lower Honoliʻi — is
ungaged and potentially significant. Simple drainage area scaling from the gage to the outlet
may underestimate peak flows in extreme events due to increasing impervious cover in the
lower contributing area.
Recommended Enhancement: Develop an explicit hydrologic analysis for Honoliʻi Stream
that accounts for the urban contributing area below gage #16717000. Apply both USGS
StreamStats regression equations calibrated for east Hawaiʻi Island and an HMS or
equivalent rainfall-runoff model using NOAA Atlas 14 precipitation frequency estimates. Use
the curve number approach (TR-55/TR-20) to partition pervious and impervious runoff
contributions from the lower basin. Cross-validate estimated AEP flows against the drainage
area scaling method and document the reconciliation. This is especially important because
Honoliʻi carries documented large sediment loads and fecal indicator bacteria associated
with pig activity in the upper watershed.
June 4, 2026 18
Supporting References: USGS (2016), StreamStats User Guide; NOAA (2011), Atlas 14:
Precipitation Frequency Estimates for Hawaii; USDA NRCS (2010), Time of Concentration (TR-
55); Strauch et al. (2014), Climate change and land use drivers of fecal bacteria in tropical
Hawaiian rivers, Journal of Environmental Quality; Young & Godszak (2008), Impact of
Urbanization on the Quality of Hilo Bay
RC-04 Future Climate Flow Projection Methodology—HIGH PRIORITY
Observation: The modeling framework includes an ‘Existing under Future Climate
Conditions (2075)’ scenario, but EA notes that limited literature addresses projected
changes in runoff in this region. Climate projections for the Hawaiian Islands show divergent
trends by elevation and season, with higher-elevation rainfall potentially decreasing under
trade wind weakening scenarios while low-elevation extreme precipitation events may
intensify. Without a robust and explicitly documented method for scaling current AEP flow
rates to 2075 conditions, the Future scenario may produce outputs with poorly
characterized uncertainty ranges that complicate regulatory and planning use.
Recommended Enhancement: Adopt the NOAA/USGS climate-adjusted flood frequency
framework for scaling current AEP flows to 2075 conditions. Supplement with the USGS
2011 Water Budget Model rainfall and runoff projections for the Island of Hawaiʻi, which
include climate-scenario sensitivity analysis. Coordinate with the University of Hawaiʻi
School of Ocean and Earth Science and Technology (SOEST) and the Pacific Islands Climate
Adaptation Science Center (PICASC) to obtain island-scale downscaled climate projections
consistent with the Hawaiʻi Climate Change Mitigation and Adaptation Commission’s
planning guidance. Document the uncertainty range of the 2075 flow projections and
propagate that uncertainty into Future scenario flood hazard map outputs using a sensitivity
analysis.
Supporting References: Hirsch & Ryberg (2012), Has the magnitude of floods across the USA
changed with global CO2 levels?, Hydrological Sciences Journal; Hawaiʻi Climate Change
Mitigation and Adaptation Commission (2017, updated 2025); Frazier et al. (2016),
Comparison of geostatistical approaches to spatially interpolate month-year rainfall for the
Hawaiian Islands; USGS (2011), Water-Budget Model and Assessment of Groundwater
Recharge for the Island of Hawaiʻi
RC-05 Model Calibration Using High Water Marks and Historical Gauge
Records—MEDIUM PRIORITY
Observation: The memorandum states that FEMA’s effective model flood hazard area maps
will serve as the primary calibration reference, supplemented by historical records and
stakeholder observations. Relying primarily on effective FEMA models for calibration is
circular when those models are also the baseline for scenario comparison. For Wailuku
June 4, 2026 19
River, the USGS gage at Piʻihonua (#16704000) has a robust long-term record including
multiple large flood events, and the downstream Hilo gage (#16713000, active 1977–1983)
provides a historical basis for routing calibration. The November 1–2, 2000 flood event
documented as the flood of record for Waiākea provides a specific large-event benchmark.
Recommended Enhancement: Develop a formal calibration and validation plan prior to Task
5b model construction that identifies all available high-water mark data, USGS peak flow
records at Piʻihonua with routing to the outlet using the established regression relationship
(Q_Hilo = 1.48 Q_Piʻihonua + 1.08, R² = 0.98), and the November 2000 peak flow record at
Waiākea. Set explicit calibration targets for peak flow, water surface elevation, and flood
extent. Apply USACE HEC-HMS/HEC-RAS calibration protocols and report model
performance metrics in the Task 5b technical memorandum
Supporting References: USACE HEC (2010), HEC-HMS Technical Reference Manual; FEMA
(2019), Flood Risk Mapping Guidance — Hydraulic Analyses; Presley et al. (2008),
Suspended-sediment and nutrient loads for Waiakea and Alenaio Streams, USGS OFR 2007-
1429
RC-06 Quantifying Green Infrastructure Effectiveness in the Proposed Conditions
Scenario—MEDIUM PRIORITY
Observation: The Proposed Conditions scenario incorporates green stormwater
infrastructure (GSI) adaptations, with model inputs to be provided by other team members.
The hydraulic effectiveness of GSI measures in extreme rainfall events — the very events
that drive floodplain boundaries — is highly variable and often modest at the watershed
scale. Without explicit performance quantification criteria, the Proposed Conditions
scenario may overestimate or underestimate GSI benefits, creating unrealistic expectations
for mitigation outcomes in planning documents.
Recommended Enhancement: Establish explicit performance criteria for GSI measures:
retention volume per unit area, peak flow reduction percentage for the design storm, and
spatial distribution relative to the modeled floodplain. Use EPA’s National Stormwater
Calculator or SWMM to pre-compute GSI performance at the subcatchment level before
incorporating results into HEC-RAS boundary conditions. Ensure that GSI performance
assumptions are conservative for the 100-year and 500-year events, where surface ponding
and inlet surcharging may significantly reduce effective retention capacity.
Supporting References: EPA (2014), National Stormwater Calculator User’s Guide
(EPA/600/R-13/085a); Rossman (2015), Storm Water Management Model (SWMM 5.1),
EPA/600/R-14/413b; Ahiablame et al. (2012), Effectiveness of Low Impact Development
Practices, Water, Air, & Soil Pollution
June 4, 2026 20
RC-07 Stream Bathymetry Acquisition Approach—HIGH PRIORITY
Observation: Existing LiDAR datasets do not capture underwater channel geometry below
the water surface. This gap is particularly significant for Wailuku River, which carries large
sediment loads and has an active channel that experiences dynamic bed changes during
flood events. Without accurate bathymetric cross-sections, HEC-RAS 2D conveyance
calculations in the active channel will be based on assumed or interpolated geometry,
potentially producing systematic errors in flood depth and velocity predictions that cascade
through all five AEP scenarios
Recommended Enhancement: Conduct wading surveys at a minimum of 10–15
representative cross-sections per stream for Wailuku River and Alenaio Stream prior to Task
5b model construction. At cross-sections where wading is unsafe at baseflow, deploy a
SonTek FlowTracker or similar acoustic Doppler current profiler (ADCP) during moderate
flow conditions. For Wailuku River near the bay outlet — the highest-priority reach for
accurate conveyance — acquire boat-mounted single-beam sonar bathymetry coordinated
with USACE or the County’s Marine Division. Integrate measured bathymetric cross-sections
into the HEC-RAS 2D terrain as breaklines and inner boundary refinements.
Supporting References: USACE EM 1110-2-1416 (River Hydraulics); SonTek (2019),
FlowTracker2 Handheld-ADV Technical Manual; Hilldale & Raff (2008), Assessing the ability
of airborne LiDAR to map river bathymetry, Earth Surface Processes and Landforms
RC-08 NOAA Topobathymetric Data Integration for the Hilo Bay Coastal Zone—
MEDIUM PRIORITY
Observation: The memorandum references NOAA LiDAR datasets but does not explicitly
address the integration of topobathymetric data at the interface between the terrestrial
watershed and Hilo Bay. The coastal plain and bay mouth — particularly the Wailuku River
outlet and the Wailoa Pond/estuary — are the zones where tidal backwater effects, sea level
rise, and storm surge interact with riverine flooding. Without high-quality topobathymetric
data at this interface, downstream boundary conditions in the HEC-RAS 2D model may not
accurately represent the transition from fluvial to coastal flood regimes.
Recommended Enhancement: Obtain and integrate the NOAA National Centers for
Environmental Information (NCEI) topobathymetric DEM for the Hilo Bay coastal zone
(NOAA Digital Coast, Coastal National Elevation Database — CoNED). This dataset merges
LiDAR topography with bathymetry to produce a seamless elevation model at the land-sea
interface. Use the topobathymetric DEM to define the HEC-RAS 2D model downstream
extent and ensure that tidal boundary conditions propagate realistically into the lower river
reaches. For sea level rise scenarios, verify that the bay bathymetry accurately represents
shoaling zones and breakwater geometry that affect tide-wave propagation.
June 4, 2026 21
Supporting References: NOAA (2018), Coastal National Elevation Database (CoNED)
Application Layers (NCEI); Barnard et al. (2019), Dynamic flood modeling essential to assess
the coastal impacts of climate change, Scientific Reports; FEMA (2015), Guidance for Flood
Risk Analysis and Mapping — Coastal Analysis and Mapping.
RC-09 Levee and Flood Control Structure Condition Assessment—MEDIUM
PRIORITY
Observation: The memorandum identifies several USACE levee and floodwall documents for
hydraulic model integration. However, hydraulic model representation of levees requires not
only geometric data but also condition assessment. Levees not accredited by FEMA must be
treated as non-existent for Special Flood Hazard Area mapping purposes, which would
materially change floodplain boundaries in the lower Alenaio and Wailoa corridors. The
current data review does not address accreditation status.
Recommended Enhancement: Conduct a review of current FEMA National Levee Database
(NLD) records for all levee and floodwall segments within the modeling domain. Verify
accreditation status for each structure and coordinate with USACE Honolulu District and
FEMA Region 9 to confirm whether levees qualify for SFHA credit in the updated flood
hazard maps. Incorporate the most recent USACE levee inspection reports to assess
structural condition. Where levee accreditation is uncertain, develop both ‘with-levee’ and
‘without-levee’ flood hazard map products to bracket the range of planning outcomes for
affected parcels and infrastructure.
Supporting References: FEMA (2013), Procedure Memorandum No. 64 — Process for
Identifying Provisionally Accredited Levees; USACE (2022), National Levee Database (NLD)
Technical Reference; USACE (2016), Alenaio Stream Levee and Floodwall Inspection Reports
Roth Ecological Design International — Ecological Data and Green
Infrastructure Siting
The most significant outstanding data needs for REDI are the modeled catchment boundaries
and flood extents, which must be delivered by the EA Engineering hydraulic modeling
workstream before REDI’s GSI prioritization can be finalized. This creates a sequencing
dependency that should be explicitly built into the project schedule. REDI also needs
confirmation of the preferred watershed scale (HUC12 vs. HUC8) and applicable TMDL
information from HDOH.
June 4, 2026 22
Ecological Data Gaps and Enhancements
RC -10 Native Vegetation Mapping and Restoration Suitability Assessment—
MEDIUM PRIORITY
Observation: The REDI data inventory identifies land cover, impervious surface, and tree
canopy from NOAA Digital Coast. However, ecological suitability analysis for Nature-Based
Solutions interventions requires more granular native versus invasive species mapping than
current land cover products provide. NOAA C-CAP classifies vegetation at a broad level
(forest, shrub/scrub, grassland) but does not distinguish intact native forest from invasive-
dominated stands such as strawberry guava monocultures, which have fundamentally
different hydrologic properties and restoration cost profiles.
Recommended Enhancement: Commission or obtain a current-conditions native/invasive
vegetation classification for the three primary watersheds using either USGS or DLNR
vegetation maps derived from WorldView or Planet satellite imagery with ground-truthing,
or the Hawaiʻi Statewide Assessment of Forest Conditions (DOFAW, 2016) as the planning
baseline, supplemented with targeted field surveys in upper watershed restoration priority
areas. Overlay vegetation type with slope, soil type, stream proximity, and ownership to
develop a restoration suitability scoring matrix that directly supports prioritization of
riparian buffer, reforestation, and bioretention interventions.
Supporting References: DOFAW (2016), Hawaiʻi Statewide Assessment of Forest Conditions
and Resource Strategy; Cole & Litton (2014), Vegetation response to removal of non-native
feral pigs from Hawaiian tropical montane wet forest, Biological Invasions; Asner et al.
(2008), Invasive species detection in Hawaiian rainforests using airborne imaging
spectroscopy and LiDAR, Remote Sensing of Environment.
RC-11 Feral Ungulate Disturbance and Sediment Connectivity—HIGH PRIORITY
Observation: The ASU section notes that the NWQI critical source area methodology does
not fully capture sediment production from forests inhabited and modified by feral
ungulates. Feral pig and goat activity in the upper Honoliʻi and Wailuku watersheds is well
documented as a primary driver of soil disturbance, understory destruction, and
streambank erosion in native Hawaiian forests. REDI’s ecological data inventory does not
explicitly include ungulate distribution or impact mapping, and current NOAA land cover
products cannot resolve this
Recommended Enhancement: Integrate feral ungulate distribution and impact data from
DLNR Division of Forestry and Wildlife pig and goat management unit records, USDA APHIS
Wildlife Services feral pig removal data, and field transect data from published studies in the
upper watershed. Develop a GIS layer of ‘ungulate disturbance zones’ and overlay with EA
Engineering critical source area mapping and ASU’s sediment monitoring network design to
June 4, 2026 23
identify reach segments where elevated SSC is likely attributable to ungulate-driven soil
disturbance. This distinction is critical for targeting cost-effective interventions: ungulate
exclusion fencing in upper watershed headwaters may deliver greater sediment load
reductions per dollar invested than downstream urban BMPs.
Supporting References: Strauch et al. (2014), Climate change and land use drivers of fecal
bacteria in tropical Hawaiian rivers, Journal of Environmental Quality; Cole & Litton (2014),
Biological Invasions; DLNR DOFAW (2023 & 2024), Feral Ungulate Management Plan,
Wailuku River State Park and Upper Watershed.
RC-12 Coral Reef and Nearshore Habitat Linkage to Watershed Loads—MEDIJM
PRIORITY
Observation: The REDI data inventory covers terrestrial ecological data but does not address
the nearshore coral reef and fishpond (loko iʻa) ecosystems of Hilo Bay, which are the
ultimate ecological receptors of the sediment, nutrient, and bacterial loads delivered from
the watershed. Hilo Bay’s eastern shoreline (Keaukaha) supports coral communities
documented as sensitive to turbidity exceedances, and the Wailoa Pond estuary functions as
a critical nursery habitat. The watershed management plan’s ecological success metrics
should include nearshore habitat condition, not only terrestrial vegetation.
Recommended Enhancement: Establish a nearshore ecological baseline monitoring
component coordinated with the Division of Aquatic Resources (DAR) and the NOAA Pacific
Islands Fisheries Science Center. Obtain existing coral reef survey data from the NOAA
National Coral Reef Monitoring Program (NCRMP) for the Hilo Bay sector. Cross-reference
spatial distribution of turbidity exceedance events with coral colony locations and benthic
cover data. Include coral reef and fishpond habitat condition as co-benefit metrics in the
NBS project evaluation framework, enabling quantification of ecological return on
investment for riparian and sediment reduction projects.
Supporting References: Lucas et al. (2023), Spatially distributed water quality responses to
freshwater discharge in a tropical estuary, Hilo Bay, Environmental Monitoring and
Assessment; NOAA NCRMP (2021), Pacific Islands Network Coral Reef Monitoring Program;
Wiegner et al. (2013), Water quality between low- and high-flow conditions in a tropical
estuary, Estuaries and Coasts.
Arizona State University — Watershed Hydrology and Water
Quality State of Knowledge
The ASU section is the most technically detailed and scientifically rigorous component of the Task
2 deliverable. Its state-of-knowledge synthesis is thorough, the problem framing is grounded in
June 4, 2026 24
the published literature across multiple decades, and the proposed monitoring network design is
well-calibrated to the scale and complexity of the research questions. The section opens with a
culturally grounded introduction that acknowledges the Kānaka Maoli (Native Hawaiian) heritage
of the watershed — its moku-o-loko and ahupuaʻa divisions, traditional loko iʻa fishpond
management, and the historical meanings embedded in stream names like Wailuku (waters of
destruction) and Wailoa (broad river). This framing reflects the community-based orientation of
the overall planning process and is likely to strengthen community ownership of monitoring
outcomes.
ASU Data Gaps and Monitoring Program
ASU identifies six data gaps that collectively define the primary research agenda for the
monitoring phase. The proposed sampling network covering Alenaio, Honoliʻi, Keaukaha,
Pukihae, Puueo, Waiakea, and Wailuku streams and drainages is well-distributed and appropriate
for the study objectives. The combination of autosamplers, turbidity probes, and grab sampling,
coordinated with EPA guidelines for HAR 11-54 compliance reporting, represents a professionally
designed monitoring program. The plan to submit data to HDOH for the 2028 Integrated Report
(§303(d) and §305(b)) provides clear regulatory accountability.
The following review comments address specific enhancements to the ASU monitoring program
that would substantially strengthen the scientific and regulatory value of the data collected.
RC-13 SSC Monitoring Network Design: Sampling Frequency and Event
Coverage—HIGH PRIORITY
Observation: The proposed network uses turbidity probes and autosamplers to develop
SSC-discharge rating curves across the three primary watersheds, consistent with USGS
protocols. However, the critical scientific and regulatory value of SSC monitoring in Hilo Bay
lies in event-scale (storm) sampling, not baseflow characterization. Wailuku River’s storm-
driven SSC response is highly non-linear (supply-limited, power law exponent 0.54), meaning
that the largest 5–10% of events by discharge deliver a disproportionate fraction of the
annual sediment load. Autosampler deployment must be configured to capture these events
at high temporal resolution or the rating curve will be systematically biased toward low-SSC
baseflow conditions.
Recommended Enhancement: Configure autosamplers to trigger at least every 2 hours
during discharge events exceeding the 30th percentile exceedance flow (approximately 3.5
m³/s at Wailuku Piʻihonua, the threshold identified for turbidity exceedance in Hilo Bay). For
events exceeding the 10th percentile (high flow), increase sampling frequency to every 30–
60 minutes to capture the rising limb, peak, and falling limb of the sediment hysteresis loop.
Program turbidity sensors with a 15-minute logging interval during storms. Submit all SSC-
June 4, 2026 25
turbidity and SSC-discharge data to the USGS National Water Information System for long-
term archiving and public accessibility. Follow USGS Techniques and Methods 3-C4
(Rasmussen et al. 2009) for rating curve development and uncertainty quantification.
Supporting References: Rasmussen et al. (2009), Guidelines and Standard Procedures for
Continuous Water-Quality Monitors, USGS Techniques and Methods 1-D3; Gray & Gartner
(2009), Surrogate Technologies for Monitoring Bed-Material Sediment Transport in Rivers,
USGS; Edwards & Glysson (1999), Field Methods for Measurement of Fluvial Sediment, USGS
TWRI Book 3, Chapter C2.
RC-14 Spatial Attribution and Groundwater Loading Model—HIGH PRIORITY
Observation: The current analysis relies on cesspool count and distribution data without a
mechanistic groundwater loading model linking cesspool density to nitrogen and pathogen
concentrations at specific monitoring points. This limits the ability to prioritize cesspool
conversion under Act 125 compliance by watershed impact. The estimated 5.6 MGD of
untreated effluent from over 10,000 OSDS represents a dominant chronic loading pathway,
but its spatial attribution to specific monitoring stations and drinking water well capture
zones has not been quantified.
Recommended Enhancement: Develop a spatially explicit OSDS groundwater loading model
using the USGS MODFLOW framework or a simplified nitrogen loading tool. Input data
should include cesspool location, soil hydraulic conductivity (NRCS WSS), depth to
groundwater (Hawaii DWS well records), and nitrogen effluent loading rates by system type.
Validate model outputs against measured spring and nearshore nitrate concentrations. Use
model results to prioritize cesspool conversion: high-hydraulic-conductivity, shallow-water-
table areas with high cesspool density that discharge to monitored coastal springs or
drinking water well capture zones should receive highest priority for County sewer extension
under Act 125.
Supporting References: Whittier & El-Kadi (2014), Human health and environmental risk
ranking of OSDS, University of Hawaiʻi WRRC; Mezzacapo & Shuler (2022), Characterizing
nutrient sources and transport in the Wailoa River and Waiākea Pond, UH Mānoa WRRC;
Waiki et al. (2025), Sewage pollution from OSDS in coastal waters of Keaukaha, Journal of
Hydrology: Regional Studies; EPA (2002), Onsite Wastewater Treatment Systems Manual.
RC-15 Integration of Continuous Turbidity Sensor Network with PACIOOS Buoy
Data—MEDIUM PRIORITY
Observation: The PACIOOS buoy near the Wailuku River mouth provides continuous
turbidity, temperature, salinity, chlorophyll, and dissolved oxygen data at 15-minute
intervals — a valuable anchor for the proposed monitoring network. The ASU document
June 4, 2026 26
references this data source but does not propose an explicit integration protocol between
the in-stream turbidity sensors and the buoy. Without a formal data linkage protocol, the
relationship between watershed sediment loads and bay water quality outcomes will remain
inferential rather than quantified.
Recommended Enhancement: Establish a formal data-sharing and integration agreement
with PACIOOS at the outset of the monitoring program. Develop a standardized data fusion
workflow that pairs in-stream discharge and turbidity measurements with buoy turbidity
records on matched time steps. Use the existing regression relationship (Q_Wailuku vs.
NTU_buoy; Mead & Wiegner 2010) as the baseline and refine it with new paired
measurements. Produce time-series plots of watershed load delivered versus bay turbidity
response for each major storm event, enabling quantification of the attenuation or
amplification of sediment signals at the bay interface. This paired dataset will be essential
for future TMDL development.
Supporting References: PACIOOS (2024), Hilo Bay Water Quality Buoy Data Archive.
RC-16 Fecal Indicator Bacteria Source Tracking—HIGH PRIORITY
Observation: The ASU review documents high concentrations of Enterococcus, Clostridium
perfringes, and antibiotic-resistant Staphylococcus aureus in Hilo Bay, with 40–50% of
samples testing positive for human waste markers. While the proposed monitoring plan will
characterize fecal indicator bacteria (FIB) concentrations in streams and along the coast, the
design does not include a microbial source tracking (MST) component that would identify
the relative contributions of human (OSDS/sewer), livestock (cattle, pig), and wildlife sources
to FIB loading. Without MST data, it is not possible to prioritize interventions between OSDS
conversion, agricultural BMPs, and feral animal management.
Recommended Enhancement: Add an MST component using quantitative PCR (qPCR) for
human-specific Bacteroides markers (BacHum or HF183) to identify OSDS contributions; Pig-
2-Bac markers to distinguish feral pig contributions (documented by Strauch et al. 2014 for
Honoliʻi); and ruminant markers for cattle and goat contributions in agricultural sub-
watersheds. Sample at a subset of the proposed monitoring stations during both baseflow
and storm events. Analyze samples at a state-certified molecular biology laboratory. MST
data will provide source attribution required for HDOH Clean Water Act reporting and will be
essential documentation for EPA Section 319 grant applications.
Supporting References: Harwood et al. (2014), Microbial source tracking markers for
detection of fecal contamination in environmental waters, FEMS Microbiology Reviews;
Strauch et al. (2014), Journal of Environmental Quality; Gerken et al. (2021), Environmental
surveillance of antibiotic resistant Staphylococcus aureus, Antibiotics; EPA (2005), Microbial
Source Tracking Guide Document (EPA/600/R-05/064).
June 4, 2026 27
RC-17 Submarine Groundwater Discharge Quantification—MEDIUM PRIORITY
Observation: The ASU document estimates submarine groundwater discharge (SGD) to the
eastern half of Hilo Bay at 476 MGD based on 1980 data using mass balance methods — a
figure that predates the extensive OSDS documentation now available and does not account
for 45 years of changes in groundwater recharge patterns or land use. More recent SGD
measurements in Keaukaha (Waiki et al. 2025) provide localized flow rates but not bay-wide
estimates. SGD is identified as the dominant pathway for nutrient and contaminant delivery
to the eastern bay, making its accurate quantification a high priority.
Recommended Enhancement: Include a targeted SGD quantification effort using radium
isotope tracing (²²⁴Ra, ²²³Ra) or radon (²²²Rn) as natural geochemical tracers. This approach
has been successfully applied in other Hawaiian coastal settings and is logistically feasible
with a small boat and portable gamma spectrometer. Sampling during low-flow, dry-season
conditions (May–October) will maximize the SGD signal relative to river-dominated inputs.
Pair SGD flux estimates with nutrient concentration measurements in coastal springs to
compute bay-wide groundwater nitrogen and phosphorus loading rates.
Supporting References: Dulaiova, H., Camilli, R., Henderson, P.B., and Charette, M.A. (2010).
Coupled radon, methane and nitrate sensors for large-scale assessment of groundwater
discharge and non-point source pollution to coastal waters. Journal of Environmental
Radioactivity; Knee et al. (2010), Using radon and radium isotopes to characterize
groundwater inputs, Limnology and Oceanography; Waiki et al. (2025), Journal of
Hydrology: Regional Studies.
RC-18 Storm Event Nutrient Sampling for Load Estimation—HIGH PRIORITY
Observation: The ASU monitoring plan focuses on seasonal nutrient sampling following EPA
HAR 11-54 criteria. This regulatory-compliance framing is appropriate for §303(d) reporting.
However, it may not capture the disproportionate contribution of storm event fluxes to total
annual nutrient loads. Published data from Honoliʻi and Waiākea show that nutrient
concentrations respond non-linearly to discharge — some streams dilute at high flows while
others show chemostatic or mobilization behavior. Without storm event sampling, annual
load estimates will rely on extrapolation from baseflow samples, introducing substantial
uncertainty into TMDL calculations.
Recommended Enhancement: Implement an event-triggered nutrient sampling protocol
using autosamplers deployed in parallel with the turbidity sensors. Program autosamplers to
collect samples every 1–2 hours during storm events exceeding a discharge threshold
corresponding to the 30th percentile exceedance. Analyze samples for the full HAR 11-54
suite: Total Nitrogen, Nitrate+Nitrite, Total Phosphorus, and Total Suspended Solids. Use
event-scale concentration-discharge hysteresis analysis to characterize source flushing
June 4, 2026 28
versus dilution dynamics. Compute event-specific and annual nutrient loads using the USGS
LOAD ESTimator (LOADEST) software to propagate uncertainty from rating curves into load
estimates.
Supporting References: Presley et al. (2008), USGS OFR 2007-1429; Wiegner et al. (2013),
Estuaries and Coasts; Runkel et al. (2004), Load Estimator (LOADEST): A FORTRAN Program
for Estimating Constituent Loads in Streams and Rivers, USGS Techniques and Methods 4-A5.
Cross-Cutting Recommendations
The three Task 2 sections address related phenomena from distinct disciplinary perspectives, and
their combined value will depend substantially on the degree to which hydraulic model outputs,
ecological data, and water quality monitoring are woven together into a coherent management
framework. At present, the three workstreams are described largely in isolation: EA’s hydraulic
model generates flood extents that REDI’s GSI siting analysis requires, but there is no explicit
protocol for how or when that handoff occurs. ASU’s turbidity monitoring will inform sediment
transport dynamics that should update assumptions in EA’s roughness calibration, but that
feedback loop is not articulated. REDI’s restoration priority sites should logically coincide with
ASU’s monitoring stations to enable measurement of treatment effectiveness, but this co-location
is not proposed.
The following four cross-cutting recommendations address the structural integration needs that
will determine whether the three workstreams cohere into a watershed management plan of
lasting value or remain parallel technical deliverables.
RC-19 Adaptive Monitoring Framework and Integrated Data Management—HIGH
PRIORITY
Observation: The three monitoring workstreams will generate datasets that are most
valuable when integrated: hydraulic model outputs inform where to place water quality
sensors; turbidity data validates sediment transport assumptions in the hydraulic model;
ecological restoration sites should be co-located with monitoring stations to measure
treatment effectiveness. Without an explicit adaptive monitoring framework and shared
data management system, these cross-workstream synergies will be lost and the planning
team will be unable to respond dynamically to emerging data during the monitoring phase.
Recommended Enhancement: Establish a Project Data Management Plan (DMP) at the
outset of the monitoring phase that defines a common spatial reference system (Hawaiʻi
State Plane, NAD83) and data schema for all field measurements; specifies data submission
timelines (raw data within 48 hours of collection; QA/QC validated data within 30 days);
identifies a shared cloud data repository accessible to all team members; and defines
June 4, 2026 29
adaptive management trigger points — specific data thresholds that will prompt protocol
modifications during the monitoring period. Apply EPA’s Guidelines for Preparing Quality
Assurance Project Plans (QAPPs) as the framework for data quality standards. Schedule
quarterly data review meetings across all team components
Supporting References: EPA (2002), Guidance for Quality Assurance Project Plans
(EPA/240/R-02/009); USGS (2006), Office of Water Quality Technical Memorandum 2006.01;
EPA (2008), Handbook for Developing Watershed Plans to Restore and Protect Our Waters
(EPA 841-B-08-005).
RC-20 Community and Indigenous Knowledge Integration—HIGH PRIORITY
Observation: The ASU introduction provides a culturally grounded framing of the
watershed, acknowledging Kānaka Maoli place names, traditional resource management
practices, and the historical relationship between the Hilo community and the bay. However,
the monitoring and modeling tasks are described in exclusively Western scientific terms.
Indigenous ecological knowledge (IEK) and community-based participatory monitoring have
been demonstrated to strengthen watershed monitoring programs in Pacific Island settings
by extending spatial coverage, identifying monitoring priorities, and building long-term
community ownership of data and management outcomes.
Recommended Enhancement: Formally integrate a Community-Based Monitoring (CBM)
component into the ASU water quality monitoring program. Partner with existing
community organizations — Hawaiʻi Wai Ola, Wailoa River and Recreation Area
stakeholders, and Native Hawaiian practitioner groups managing Wailoa Pond — to co-
design a subset of sampling locations and protocols reflecting community water quality
priorities such as swimming safety, traditional fishing areas, and drinking water springs. Train
community monitors in basic water quality sampling using low-cost sensors and submit
results to the shared data platform alongside professional monitoring network data.
Acknowledge Indigenous place names and traditional water resource management
frameworks in all public-facing documents and the final watershed management plan.
Supporting References: EPA (2016), Environmental Justice Collaborative Problem-Solving
Cooperative Agreement Program; Silvius (2005), Hilo Bay Watershed Management Plan;
Maly & Maly (2003), Panaeʻo: A Cultural-Historical Study of the Hilo Bay Watershed; Berkes
(2009), Evolution of co-management: Role of knowledge generation, bridging organizations
and social learning, Journal of Environmental Management.
RC-21 Cost Benefit Analysis Framework for Watershed Interventions—MEDIUM
PRIORITY
Observation: ASU Task 2 gap #4 identifies the need for a cost-benefit analysis to prioritize
interventions. The watershed management plan will ultimately need to present a prioritized
June 4, 2026 30
action plan to the County, the State, and federal funding agencies. Without a consistent
economic framework, comparison across intervention types — cesspool conversion, riparian
fencing, GSI, levee maintenance — will rely on qualitative judgment rather than quantified
return on investment, weakening the plan’s credibility with funding agencies.
Recommended Enhancement: Adopt the EPA Handbook for Developing Watershed Plans
framework for cost-effectiveness analysis of BMP alternatives. For each proposed
intervention, quantify capital cost, annual operation and maintenance cost, pollutant or
sediment load reduction in kg per year, cost per unit load reduction in dollars per kg per
year, and co-benefits including flood peak reduction, habitat improvement, and community
access. Apply USDA NRCS RUSLE2 to estimate sediment reduction from agricultural and
forest BMPs. Present results as a cost-effectiveness ranking table suitable for direct
incorporation into the NRCS NWQI implementation plan and future FEMA BRIC grant
applications.
Supporting References: EPA (2008), Handbook for Developing Watershed Plans (EPA 841-B-
08-005); USDA NRCS (2013), RUSLE2 Science Documentation.
RC-22 EPA Section 319 Documentation and Reporting Alignment—HIGH
PRIORITY
Observation: The ASU monitoring plan is explicitly designed to support HDOH Clean Water
Act §303(d) reporting for the 2028 Integrated Report deadline. However, the plan does not
address the parallel documentation requirements for EPA Section 319 (Nonpoint Source
Pollution) grant eligibility, which is likely to be the primary federal funding mechanism for
watershed management implementation. Section 319 requires a state-approved watershed-
based plan (9 Elements Plan) as a prerequisite for implementation funding, and several of
the 9 Elements have direct data requirements that must be addressed during the Task 2
monitoring phase.
Recommended Enhancement: Align the Task 2 monitoring and modeling outputs with the 9
Elements of an EPA Watershed-Based Plan as required for Section 319 funding eligibility. The
specific data requirements that intersect with Task 2 are: Element 1 (identification of
pollutant sources and loads, addressed by ASU monitoring); Element 2 (expected load
reduction under management measures, addressed by ASU and EA modeling); Element 3
(management measures to achieve load reduction, addressed by REDI NBS design); Element
5 (technical and financial assistance, requiring a funding matrix); and Element 8 (monitoring
to track progress, addressed by the ASU monitoring plan). Begin pre-application
coordination with the Hawaiʻi Department of Health Clean Water Branch and USEPA Region
9 Water Division immediately to confirm that Task 2–5 deliverables will satisfy 9 Elements
requirements for the 2028 application cycle.
June 4, 2026 31
Supporting References: EPA (2008), Handbook for Developing Watershed Plans (EPA 841-B-
08-005); 40 CFR Part 130 (Water Quality Planning and Management); USEPA Region 9
(2023), Section 319 Program Implementation Guidance for Pacific States and Territories;
Hawaiʻi Department of Health Clean Water Branch (2024), 2024 Nonpoint Source
Management Program Annual Report.
Implementation Roadmap
The following sequencing integrates all review comments into a phased approach aligned with
the project’s existing Task 2–Task 5b workflow. Recommended actions are grouped into four
implementation windows: Immediate (prior to Task 5b kickoff), Short-Term (during Task 5b model
construction, 0–12 months), Medium-Term (Year 1–2 monitoring phase), and Long-Term (Year 2–
3, watershed management plan integration).
Immediate Actions (Prior to Task 5b Kickoff)
• RC-02: Initiate bridge and culvert field survey coordination with County of Hawaiʻi
Department of Public Works; request as-built drawings and inspection records.
• RC-09: Query FEMA National Levee Database and request USACE levee inspection
reports for all Alenaio and Wailoa levee and floodwall structures; confirm accreditation
status.
• RC-22: Schedule pre-application meeting with HDOH Clean Water Branch and EPA
Region 9 to align Task 2–5 deliverables with EPA Section 319 Nine Elements
documentation requirements for the 2028 application cycle.
• RC-19: Draft Project Data Management Plan and Quality Assurance Project Plan (QAPP)
for the ASU monitoring program; establish shared cloud data repository and common
data schema.
• RC-20: Initiate contact with Hawaiʻi Wai Ola and Wailoa River stakeholder groups to co-
design Community-Based Monitoring sampling locations and protocols.
Short-Term Actions (Task 5b Model Construction, 0–12 Months)
• RC-01: Conduct supplemental structure-from-motion photogrammetry or terrestrial
LiDAR survey of the lower 2–3 km of Wailuku and Alenaio stream channels to fill terrain
resolution gaps.
• RC-07: Deploy wading survey team for bathymetric cross-sections at 10–15 priority
cross-sections per stream on Wailuku River and Alenaio Stream; coordinate boat-
mounted sonar survey at Wailuku River bay outlet.
• RC-03: Complete Honoliʻi hydrologic analysis using combined StreamStats, curve
number, and drainage area scaling approach; document reconciliation of methods.
• RC-05: Develop formal calibration and validation plan; compile Piʻihonua gage record,
November 2000 flood benchmark data, and available high-water marks.
June 4, 2026 32
• RC-13: Install turbidity probes and autosamplers at initial monitoring stations; configure
storm-event triggering thresholds at 30th percentile exceedance flow.
• RC-16: Collect baseline microbial source tracking (MST) samples at watershed outlet
stations during the first wet season; analyze for human-specific Bacteroides, Pig-2-Bac,
and ruminant markers.
• RC-11: Obtain DLNR DOFAW ungulate management unit data; develop GIS ungulate
disturbance zone layer and overlay with EA critical source area map.
Medium-Term Actions (Year 1–2, Monitoring Phase)
• RC-04: Complete future climate flow projection analysis in coordination with UH SOEST
PICASC; document uncertainty range and propagate into Future scenario flood hazard
maps.
• RC-14: Build OSDS groundwater loading model using MODFLOW or EPA Nitrogen
Loading Model framework; validate against Waiki et al. 2025 and Mezzacapo & Shuler
2022 coastal monitoring data.
• RC-17: Deploy radon or radium SGD sampling transects during dry season; compute bay-
wide groundwater nutrient loading rates for nitrogen and phosphorus.
• RC-18: Begin storm event nutrient sampling with autosamplers; compute event loads
using USGS LOADEST; develop annual load estimates.
• RC-10: Commission native/invasive vegetation classification for upper watershed priority
restoration zones; develop restoration suitability scoring matrix.
• RC-21: Develop cost-effectiveness ranking table for proposed watershed interventions
using EPA framework and RUSLE2 sediment reduction estimates.
Long-Term Actions (Year 2–3, Watershed Management Plan Integration)
• RC-06: Incorporate GSI performance data from SWMM pre-modeling into Proposed
Conditions HEC-RAS scenario boundary conditions.
• RC-08: Obtain CoNED topobathymetric DEM for Hilo Bay coastal zone; refine
downstream model boundary conditions for sea level rise scenarios.
• RC-12: Obtain NOAA NCRMP coral reef survey data for Hilo Bay; develop nearshore
habitat co-benefit metrics for NBS project evaluation framework.
• RC-15: Develop formal PACIOOS buoy data integration protocol; produce paired
watershed sediment load versus bay turbidity response time-series for each major storm
event.
• Synthesize all monitoring results, hydraulic model outputs, and ecological assessments
into the final 9-Elements Watershed Management Plan in compliance with EPA 841-B-
08-005 and Section 319 documentation requirements.
Overall Assessment and Conclusions
June 4, 2026 33
Strengths of the Task 2 Deliverable
Task 2 represents a technically sound, well-coordinated, and appropriately scoped literature
review and data gap analysis. Several aspects of the deliverable are particularly noteworthy:
The ASU contribution’s integration of Hawaiian cultural context with rigorous hydrologic science
is both intellectually compelling and strategically important. By framing the watershed in terms
of the moku-o-loko and ahupuaʻa, and acknowledging the deep historical relationship between
Kānaka Maoli communities and the bay, ASU has produced a document that speaks to both the
scientific community and the broader Hilo community. This framing is likely to strengthen the
community-based nature of the overall planning process and to build the trust and ownership
that will be essential for successful implementation of management recommendations.
The geologic-hydrologic analysis in the ASU section — particularly the explanation of how
substrate age drives the dramatic differences in surface runoff ratios across the three
watersheds — provides a scientifically rigorous foundation for the entire monitoring and
modeling program. The conceptual model of the bay as receiving surface-water-dominated
inputs on the west and groundwater-dominated inputs on the east is a powerful and well-
supported organizing framework.
EA’s selection of HEC-RAS 2D with a well-defined four-scenario matrix, combined with explicit
acknowledgment of data gaps and documentation commitments, reflects professional
engineering practice at the appropriate level for this type of watershed-scale planning study.
REDI’s data needs memo, while brief, is appropriately structured for a planning-phase deliverable
and demonstrates a well-curated baseline dataset that spans the necessary spatial and thematic
coverage for a parcel-level GSI siting analysis.
Priority Areas for Strengthening
The most significant areas where the Task 2 foundation can be strengthened are:
The treatment of model calibration deserves special attention. The reliance on FEMA effective
models as the primary calibration reference introduces a circularity risk that could compromise
the credibility of the updated flood hazard maps, particularly for Honoliʻi Stream where no
FEMA mapping currently exists. A calibration strategy grounded in observed peak flows, high-
water marks, and the well-documented November 2000 flood event will produce more
defensible outputs.
The future climate flow projection approach — currently described only as a literature review
plus EA internal resources — represents the most analytically consequential gap for the 2075
June 4, 2026 34
scenario modeling. The divergent and potentially counterintuitive direction of climate change
effects on Hawaiian Island hydrology (possible decreasing trade wind rainfall at high elevations,
intensifying extreme events at low elevations) demands a more structured and explicitly
documented projection methodology.
The cross-workstream integration challenge is structural rather than technical. The three Task 2
sections are individually well-executed, but the mechanisms by which they will be synthesized
— in terms of data exchange, joint interpretation, and integrated recommendations — are not
yet specified. The implementation of a Project Data Management Plan, shared data repository,
and adaptive monitoring framework will be essential to realizing the full value of the combined
program.
Finally, the EPA Section 319 alignment requirement should be addressed immediately rather
than at the end of the planning process. Pre-application coordination with HDOH and EPA
Region 9 will ensure that the data collected and the models built during Tasks 2 through 5
satisfy the Nine Elements documentation requirements that will determine eligibility for the
federal implementation funding the County will need to act on the management plan’s
recommendations.
Conclusion
The Hilo Bay Watershed faces genuinely complex and deeply intertwined stressors: decades of
cesspool-driven groundwater contamination, episodic storm-driven sediment and bacterial
loading, sea level rise compounding coastal flood hazard, and ongoing ecological degradation of
a reef and estuarine system of extraordinary cultural and ecological significance. The Task 2
approach correctly frames these challenges with scientific rigor and community grounding. The
22 review comments in this document are offered in the spirit of continuous improvement and
peer accountability, aimed at ensuring that when the monitoring data arrives and the hydraulic
models are built, the analytical foundation is robust enough to support the management plan
decisions that the County of Hawaiʻi, the State, and federal funding agencies will rely on for the
next 20 years.
Despite the identified enhancement opportunities, adequate information exists to begin
construction of reliable hydraulic models and to implement the monitoring program as
designed. The commitment to document all assumptions, coordinate with the County on risk
tolerance, and engage the community throughout the process — reflected throughout Task 2 —
is the foundation on which a successful watershed management plan can be built.