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ESTIMATING PEAK DISCHARGESIN SMALL URBAN HAWAIIAN WATERSHEDSFOR SELECTED RAINFALL FREQUENCIES,KANE'OHE WATERSHED, O'AHU, HAWAIII
by
Nancy C. LopezGordon L. Dugan
Technical Memorandum No. 58
August 1978
WATER RESOURCES RESEARCH CENTER
and the
HAWAI I ENVIRONMENTAL SIMULATION LABORATORY
University of Hawaii
ESTIMATING PEAK DISCHARGESIN SMALL URBAN HAWAIIAN WATERSHEDSFOR SELECTED RAINFALL FREQUENCIES,KANE'OHE WATERSHED, O'AHU, HAWAIII
by
Nancy C. LopezGordon L. Dugan
Technical Memorandum No. 58
August 1978
WATER RESOURCES RESEARCH CENTER
and the
HAWAI I ENVIRONMENTAL SIMULATION LABORATORY
University of Hawaii
iii
ABSTRACT
Since its establishment in the spring of 19?1~ the Hawaii Environmental
Simulation Laboratory (HESL) has attempted to simulate some of the conse
quences of alternative land use-economic decisions. The Kane'ohe region on
O'ahu Island~ Hawai'i was selected as a study area. Flooding~ which has
historically created hazard areas in Kane'ohe~ appears to be significantly
altere4 by the rapid urbanization of the region. The problem of predicting
flooding patterns in the Kane'ohe region~ as well as Hawai'i in general~ is
complicated by the rather small area of the individual watersheds~ the abrupt
cha~ges in terrain~and the short times of concentration~ generally less than
Z hr.
Using existing technology~ a planning-oriented tool for predicting peak
discharges resulting from various patterns of urbanization has been developed
by HESL for Hawaiian conditions. The tool utilizes the U.S. Soil Conservation
Service Runoff CUrves~ a unique time of concentration formula~ and the U.s.
Weather Bureau Rainfall-Frequency Atlas of the Hawaiian Islands. Areas with
in the watershed were segregated by ranges of slope into response zones. In
put data include soil class and cover~ hydraulic' length~ and average slope.
The model was applied to ten individual watersheds within the Kane'ohe region~
~nd estimates of peak discharge for the watersheds were made for selected
rainfall return intervals. Peak discharge values were determined for exist
ing land use and for three different scenarios (hypothetical patterns of
urban growth) for the year 1995. Tests of the model using the rather limited
existing peak discharge records have been very encouraging.
iii
ABSTRACT
Since its establishment in the spring of 19?1~ the Hawaii Environmental
Simulation Laboratory (HESL) has attempted to simulate some of the conse
quences of alternative land use-economic decisions. The Kane'ohe region on
O'ahu Island~ Hawai'i was selected as a study area. Flooding~ which has
historically created hazard areas in Kane'ohe~ appears to be significantly
altere4 by the rapid urbanization of the region. The problem of predicting
flooding patterns in the Kane'ohe region~ as well as Hawai'i in general~ is
complicated by the rather small area of the individual watersheds~ the abrupt
cha~ges in terrain~and the short times of concentration~ generally less than
Z hr.
Using existing technology~ a planning-oriented tool for predicting peak
discharges resulting from various patterns of urbanization has been developed
by HESL for Hawaiian conditions. The tool utilizes the U.S. Soil Conservation
Service Runoff CUrves~ a unique time of concentration formula~ and the U.s.
Weather Bureau Rainfall-Frequency Atlas of the Hawaiian Islands. Areas with
in the watershed were segregated by ranges of slope into response zones. In
put data include soil class and cover~ hydraulic' length~ and average slope.
The model was applied to ten individual watersheds within the Kane'ohe region~
~nd estimates of peak discharge for the watersheds were made for selected
rainfall return intervals. Peak discharge values were determined for exist
ing land use and for three different scenarios (hypothetical patterns of
urban growth) for the year 1995. Tests of the model using the rather limited
existing peak discharge records have been very encouraging.
ABSTRACT...
INTRODUCTION.
CONTENTS
iii
v
-KANE'OHE WATERSHED.
STORM WATER RUNOFF MODELS
HESL DISCHARGE FREQUENCY MODEL.
SUMMARY ....
ACKNOWLEDGMENTS
REFERENCES. . .
FIGURES
3
4
22
23
24
1. Drainage Sub-Basins in the Kane'ohe Bay Watershed, WindwardOlahiJ, Hawai'i. . . . . . . . . . . . . . . . . . . . . . . 2
2. Unit Peak Discharge ?f Runoff vs. Time of Concentration, Tc ' forType I 24-hr Eva1uatlon Storm. . .. . .. 10
3. SCS Type I 24-hr Evaluation Storm 11
4. Sample Slope Zone Lengths . • I .. 13
5. Comparison of HESL and DLNR Discharge Frequency Values for Waihe'e. 15
6. Comparison of HESL and DLNR Discharge Frequency Values for Kaha1u ' u 16
7. Comparison of HESL and DLNR Discharge Frequency Values for Puke1e 17
8. Comparison of HESL and DLNR Discharge Frequency Values for Ka1ihi 18
9. Land-Use Effects for a Hypothetical Case.
TABLES
20
1. SCS Hydrologic Classification of Hawaiian Soils .
2. Runoff Curve Numbers for Rural Soil/Cover Complexes, Hawai'i.
3. Runoff Curve Numbers for Urban Soil/Cover Complexes, Hawaili.
6
7
7
ABSTRACT...
INTRODUCTION.
CONTENTS
iii
v
-KANE'OHE WATERSHED.
STORM WATER RUNOFF MODELS
HESL DISCHARGE FREQUENCY MODEL.
SUMMARY ....
ACKNOWLEDGMENTS
REFERENCES. . .
FIGURES
3
4
22
23
24
1. Drainage Sub-Basins in the Kane'ohe Bay Watershed, WindwardOlahiJ, Hawai'i. . . . . . . . . . . . . . . . . . . . . . . 2
2. Unit Peak Discharge ?f Runoff vs. Time of Concentration, Tc ' forType I 24-hr Eva1uatlon Storm. . .. . .. 10
3. SCS Type I 24-hr Evaluation Storm 11
4. Sample Slope Zone Lengths . • I .. 13
5. Comparison of HESL and DLNR Discharge Frequency Values for Waihe'e. 15
6. Comparison of HESL and DLNR Discharge Frequency Values for Kaha1u ' u 16
7. Comparison of HESL and DLNR Discharge Frequency Values for Puke1e 17
8. Comparison of HESL and DLNR Discharge Frequency Values for Ka1ihi 18
9. Land-Use Effects for a Hypothetical Case.
TABLES
20
1. SCS Hydrologic Classification of Hawaiian Soils .
2. Runoff Curve Numbers for Rural Soil/Cover Complexes, Hawai'i.
3. Runoff Curve Numbers for Urban Soil/Cover Complexes, Hawaili.
6
7
7
vi
4.
5.
Comparison of HESL and U.S. Army Corps of EngineersPeak Discharges for Design of the Keapuka Dam andReservoir, Kane'ohe, Q'ahu .
Summary of Land-Use Assumptions and Discharges forScenarios Applications in Four Kane'ohe Watersheds,QI ahu, Hawa iii . . • . . . . . . . . . . . . . . . .
19
21
vi
4.
5.
Comparison of HESL and U.S. Army Corps of EngineersPeak Discharges for Design of the Keapuka Dam andReservoir, Kane'ohe, Q'ahu .
Summary of Land-Use Assumptions and Discharges forScenarios Applications in Four Kane'ohe Watersheds,QI ahu, Hawa iii . . • . . . . . . . . . . . . . . . .
19
21
ESTIMATING PEAK DISCHARGES IN SMALL URBANIZING HAWAIIANWATERSHEDS FOR SELECTED RAINFALL FREQUENCIES l
Nancy C. Lopez 2 and Gordon L. Dugan 3
INTRODUCTION
Since its establishment in the spring of 1971, the Hawaii EnvironmentalSimulation Laboratory (HESL) has attempted to develop means to simulate theenvironmental effects of alternative land-use decisions on O'ahu Island,Hawai'i, and particularly in the Kane'ohe region, as shown in Figure 1.
The Kane'ohe region was selected as the initial study area for thefollowing reasons: (1) Kane'ohe Bay is one of the state's most valuablenatural resources and its largest protected salt water area, (2) the bay isundergoing serious ecological change as a consequence of rapid urbanizationof the watershed; however, abatement of the bay's deterioration appears possible with appropriate control of land use and waste dispo~al practices, (3)the region is a semi-isolated ecological unit with well-defined boundaries,and (4) the local residents provide a representative cross section ofHawai'i's diverse population. Like other states which have experiencedrapid growth, the state of Hawai'i is faced with the serious problem of providing its citizens with adequate housing and other facilities that are ecologically and economically feasible. It is anticipated that informationgenerated from this region will be applicable, not only to other regions inHawai'i, but also to some degree to similar situations throughout the nation.
KANE'OHE WATERSHED
The Kane'ohe region contains a population of approximately 40,000 compared to over 700~000 for the entire island of O'ahu. O'ahu's land area isIpaper presented to the 23d Annual Specialty Conference, Hydraulic Engineering for Optimal Use of Water Resources, 6-8 August 1975, Seattle, WA.2Hydrologic Specialist, Hawaii Environmental Simulation Laboratory, Univ. ofHawaii, Honolulu, Hawai'i at the time the paper was initially written, and~resently a Hydraulic Engineer with the U.S. Army Corps of Engineers, Washlngton, D.C.3Professor of Civil Engineering and Manager of the Hydrologic-Water QUalitySection, Hawaii Environmental Simulation Laboratory, University of Hawaii,Honolulu, Hawai'i.
ESTIMATING PEAK DISCHARGES IN SMALL URBANIZING HAWAIIANWATERSHEDS FOR SELECTED RAINFALL FREQUENCIES l
Nancy C. Lopez 2 and Gordon L. Dugan 3
INTRODUCTION
Since its establishment in the spring of 1971, the Hawaii EnvironmentalSimulation Laboratory (HESL) has attempted to develop means to simulate theenvironmental effects of alternative land-use decisions on O'ahu Island,Hawai'i, and particularly in the Kane'ohe region, as shown in Figure 1.
The Kane'ohe region was selected as the initial study area for thefollowing reasons: (1) Kane'ohe Bay is one of the state's most valuablenatural resources and its largest protected salt water area, (2) the bay isundergoing serious ecological change as a consequence of rapid urbanizationof the watershed; however, abatement of the bay's deterioration appears possible with appropriate control of land use and waste dispo~al practices, (3)the region is a semi-isolated ecological unit with well-defined boundaries,and (4) the local residents provide a representative cross section ofHawai'i's diverse population. Like other states which have experiencedrapid growth, the state of Hawai'i is faced with the serious problem of providing its citizens with adequate housing and other facilities that are ecologically and economically feasible. It is anticipated that informationgenerated from this region will be applicable, not only to other regions inHawai'i, but also to some degree to similar situations throughout the nation.
KANE'OHE WATERSHED
The Kane'ohe region contains a population of approximately 40,000 compared to over 700~000 for the entire island of O'ahu. O'ahu's land area isIpaper presented to the 23d Annual Specialty Conference, Hydraulic Engineering for Optimal Use of Water Resources, 6-8 August 1975, Seattle, WA.2Hydrologic Specialist, Hawaii Environmental Simulation Laboratory, Univ. ofHawaii, Honolulu, Hawai'i at the time the paper was initially written, and~resently a Hydraulic Engineer with the U.S. Army Corps of Engineers, Washlngton, D.C.3Professor of Civil Engineering and Manager of the Hydrologic-Water QUalitySection, Hawaii Environmental Simulation Laboratory, University of Hawaii,Honolulu, Hawai'i.
2
CoconutIs. 'V
KAMO I OAL II 1
l'N
(.o
Kahalu'uWatershed
Waihe'eWatershed
PiikeleWatershed
INDEX MAP
FIGURE 1. DRAINAGE SUB-BASINS IN THE KANE'OHE BAY WATERSHED,WINDWARD O'AHU, HAWAI I I
2
CoconutIs. 'V
KAMO I OAL II 1
l'N
(.o
Kahalu'uWatershed
Waihe'eWatershed
PiikeleWatershed
INDEX MAP
FIGURE 1. DRAINAGE SUB-BASINS IN THE KANE'OHE BAY WATERSHED,WINDWARD O'AHU, HAWAI I I
3
less than 1',554 x 109m2 (600 miles 2) and includes 82% of the state's population
The relative scarcity of developable land for housing has escalated land
costs and, consequently, other land uses, particularly agriculture, have been
converted,to urban use. Land use in the Kane'ohe region is mainly for urban
and rural residences intermingled with agricultural pursuits. There are no
major industries in the area.
Geographically, the Kane'ohe region comprises a watershed area of
approximately 97.128 x 106 m2 (24,000 acres) with 10 major streams draining
the small sub-basins. The region receives the northeastern trade winds,
which strike the sharply rising Ko'olau Range (>100% slope), causing oro
graphic rainfall. Moisture brought by the trade winds is the major contri
butor to the total precipitation that ranges from an annual average of less
than 1.27 m (50 in.) near the coast to greater than 5.08 m (200 in.) along
the crest of the Ko'olau Range.
High'rainfall rates, which have exceeded 0.51 m (20 in.) in 24 hr, to
gether with relatively short, steep drainage paths, have resulted in times
of concentration* of much less than 1 hr for nearly all of the Kane'ohe re
gion subdrainage basins. Since the decade of the 1960s, flooding resulting, ..
from the rapid surface water runoff from several storms has caused hundreds
of thousands of dollars worth of damage to private homes, businesses, and
public facilities in the Kane'ohe region. As a result, two federal flood
control projects have been planned for the region. Concern over possible
flood damage, attendant sediment damage, and nutrient transport to the re
ceiving waters has increased as more land in the Kane'ohe region is con
verted from rural or agricultural to urban use.
STORM WATER RUNOFF MODELS
Among the numberous other considerations with which decision makers are
faced, the problem of estimating the effect that a proposed development would
have upon flooding and its attendant problems, both on the land and in the re
ceiving waters, is of paramount importance. These decisions are normallymnde
with minimal data. More often than not, adequate streamflow re~ords ncceesary
to establish the existing flow regime arc unavailable. Several hydrologic
*The time required for storm water runoff to flow from the most remote pointin a drainage area to the point under consideration. '
3
less than 1',554 x 109m2 (600 miles 2) and includes 82% of the state's population
The relative scarcity of developable land for housing has escalated land
costs and, consequently, other land uses, particularly agriculture, have been
converted,to urban use. Land use in the Kane'ohe region is mainly for urban
and rural residences intermingled with agricultural pursuits. There are no
major industries in the area.
Geographically, the Kane'ohe region comprises a watershed area of
approximately 97.128 x 106 m2 (24,000 acres) with 10 major streams draining
the small sub-basins. The region receives the northeastern trade winds,
which strike the sharply rising Ko'olau Range (>100% slope), causing oro
graphic rainfall. Moisture brought by the trade winds is the major contri
butor to the total precipitation that ranges from an annual average of less
than 1.27 m (50 in.) near the coast to greater than 5.08 m (200 in.) along
the crest of the Ko'olau Range.
High'rainfall rates, which have exceeded 0.51 m (20 in.) in 24 hr, to
gether with relatively short, steep drainage paths, have resulted in times
of concentration* of much less than 1 hr for nearly all of the Kane'ohe re
gion subdrainage basins. Since the decade of the 1960s, flooding resulting, ..
from the rapid surface water runoff from several storms has caused hundreds
of thousands of dollars worth of damage to private homes, businesses, and
public facilities in the Kane'ohe region. As a result, two federal flood
control projects have been planned for the region. Concern over possible
flood damage, attendant sediment damage, and nutrient transport to the re
ceiving waters has increased as more land in the Kane'ohe region is con
verted from rural or agricultural to urban use.
STORM WATER RUNOFF MODELS
Among the numberous other considerations with which decision makers are
faced, the problem of estimating the effect that a proposed development would
have upon flooding and its attendant problems, both on the land and in the re
ceiving waters, is of paramount importance. These decisions are normallymnde
with minimal data. More often than not, adequate streamflow re~ords ncceesary
to establish the existing flow regime arc unavailable. Several hydrologic
*The time required for storm water runoff to flow from the most remote pointin a drainage area to the point under consideration. '
4
and hydraulic t~chniques for estimating surface water runoff characteristics:": .
have been tested in Hawai'i including the U.S. Soil Conservation Service (SCS)
TR-2Q Model, the Stanford Model, the U.S. Army Corps of Engineers (USACE)
Flood Hydrograph Package, and the U.S. Geological Survey (USGS) Optimization
Model. All these models are generally too complex for ready application by
a land-use planner and/or decision maker, and historically only the SCS model
considered specifically land-use change. Recently the USACE included the SCS
curve number technique as an option in the Flood Hydrograph Package.
HESL DISCHARGE FREQUENCY MODEL
In order to address this land-use planning problem, HESL developed a
tool for estimating incremental storm water runoff rate changes caused by
proposed development alternatives within the watershed using existing tech
nology. The planning-oriented technique incorporates the SCS curve number
technique, a locally derived time of concentration formula, and the U.S.
Weather Bureau (1962) Rainfall-Frequency Atlas of the Hawaiian Islands. A
fundamental assumption of the preposed technique is that over long periods
of time rainfall frequencies can provide a reasonable approximation of run
off frequencies.
Since this assumption is the subject of much controversy, the following
discussion is offered to support it for the present application. The
assumption is applied to events equaling or exceeding a one year frequency.
This restriction mitigates the effects of antecedent moisture conditions
which predominate during more frequent events. Also, the areas under con
sideration are small so that for significant events the order of magnitude
differences in rainfall volume over the basin would be extremely rare. The
assumption is used to estimate long-term trends, rather than individual
events.
Previous research supports the use of rainfall frequencies to approximate
runoff frequencies for small watersheds. Reich and Larson (1973) researched
the question using rainfall and discharge data for twenty small watersheds
in Pennsylvania and concluded that:
Despite high variability of individual years, storm rainfalland runoff rank and recurrence interval have a distinct centraltendency toward being equal. Thus, for design purposes, theassumption of equality is justified and appropriate.
4
and hydraulic t~chniques for estimating surface water runoff characteristics:": .
have been tested in Hawai'i including the U.S. Soil Conservation Service (SCS)
TR-2Q Model, the Stanford Model, the U.S. Army Corps of Engineers (USACE)
Flood Hydrograph Package, and the U.S. Geological Survey (USGS) Optimization
Model. All these models are generally too complex for ready application by
a land-use planner and/or decision maker, and historically only the SCS model
considered specifically land-use change. Recently the USACE included the SCS
curve number technique as an option in the Flood Hydrograph Package.
HESL DISCHARGE FREQUENCY MODEL
In order to address this land-use planning problem, HESL developed a
tool for estimating incremental storm water runoff rate changes caused by
proposed development alternatives within the watershed using existing tech
nology. The planning-oriented technique incorporates the SCS curve number
technique, a locally derived time of concentration formula, and the U.S.
Weather Bureau (1962) Rainfall-Frequency Atlas of the Hawaiian Islands. A
fundamental assumption of the preposed technique is that over long periods
of time rainfall frequencies can provide a reasonable approximation of run
off frequencies.
Since this assumption is the subject of much controversy, the following
discussion is offered to support it for the present application. The
assumption is applied to events equaling or exceeding a one year frequency.
This restriction mitigates the effects of antecedent moisture conditions
which predominate during more frequent events. Also, the areas under con
sideration are small so that for significant events the order of magnitude
differences in rainfall volume over the basin would be extremely rare. The
assumption is used to estimate long-term trends, rather than individual
events.
Previous research supports the use of rainfall frequencies to approximate
runoff frequencies for small watersheds. Reich and Larson (1973) researched
the question using rainfall and discharge data for twenty small watersheds
in Pennsylvania and concluded that:
Despite high variability of individual years, storm rainfalland runoff rank and recurrence interval have a distinct centraltendency toward being equal. Thus, for design purposes, theassumption of equality is justified and appropriate.
5
In the present context the assumption is applied for planning purposes,
rather than for the design of specific structures. The HESL technique
has been used for numerous evaluations with seemingly reliable results.
A 1975 SCS publication entitled, "Urban Hydrology for Small Water
sheds," presents a very similar approach which is applicable to most of
the United States except the Pacific coast and Hawai'i. The SCS method
provides several coefficients to refine timing and peak rate values as
functions of percent impervious area and percent hydraulic length modified.
Provision is also made for adjusting peak rates for slope effects. Although
the need for considering these three effects in Hawai'i is recognize~, the
data base to support such modifications is lacking at the present time.
The effects of urbanization on peak discharge are incorporated into the
HESL procedure by means of the SCS (1969, sec. 4, chaps. 9, 10) curve
number technique. The curve number (CN) technique was developed by SCS for
calculating runoff on ungaged watersheds by using estimated precipitation,
soils and cover information, and antecedent moisture condition. The SCS
(1969, chap. 7 and Table 7.1, pp. 7.6-7.26) has classified thousands of
soils allover the nation into four groups labelled A to D. Hawaiian soils
classified into these four groups are listed in Table 1. Curve numbers
estimated by the SCS (1969, p. 9.2) Honolulu Office, in cooperation with
the U.S. Forest Service, for nonurban conditions in Hawai'i are shown in
Table 2. Curve numbers for Hawai'i Class A soils, which show a large
variability in the rates of infiltration, have not been assigned. Thus,
for Class A soils in Hawai'i, the curve numbers have to be estimated on a
case by case basis.
For urban conditions HESL based the curve numbers on work performed
by Miller and Viessman (1973,p. 432) which graphically related curve numbers
and percent impervious surfaces. Miller and Viessman assume that urban
curve numbers should be at least as high as curve numbers for bare clay
soil. The bulldozing, compaction,and loss of top soil, which are normally
associated with construction practices, make this assumption reasonable.
Over the long term, soils in suburban areas may recover some porosity, and,
if they do, lower curve numbers should be used. The urban curve numbers
are presented in Table 3. These curve numbers are subject to revision as
more data becomes available. Composite curve numbers weighted by percent
areal distribution are necessary when more than one soil class or land use
5
In the present context the assumption is applied for planning purposes,
rather than for the design of specific structures. The HESL technique
has been used for numerous evaluations with seemingly reliable results.
A 1975 SCS publication entitled, "Urban Hydrology for Small Water
sheds," presents a very similar approach which is applicable to most of
the United States except the Pacific coast and Hawai'i. The SCS method
provides several coefficients to refine timing and peak rate values as
functions of percent impervious area and percent hydraulic length modified.
Provision is also made for adjusting peak rates for slope effects. Although
the need for considering these three effects in Hawai'i is recognize~, the
data base to support such modifications is lacking at the present time.
The effects of urbanization on peak discharge are incorporated into the
HESL procedure by means of the SCS (1969, sec. 4, chaps. 9, 10) curve
number technique. The curve number (CN) technique was developed by SCS for
calculating runoff on ungaged watersheds by using estimated precipitation,
soils and cover information, and antecedent moisture condition. The SCS
(1969, chap. 7 and Table 7.1, pp. 7.6-7.26) has classified thousands of
soils allover the nation into four groups labelled A to D. Hawaiian soils
classified into these four groups are listed in Table 1. Curve numbers
estimated by the SCS (1969, p. 9.2) Honolulu Office, in cooperation with
the U.S. Forest Service, for nonurban conditions in Hawai'i are shown in
Table 2. Curve numbers for Hawai'i Class A soils, which show a large
variability in the rates of infiltration, have not been assigned. Thus,
for Class A soils in Hawai'i, the curve numbers have to be estimated on a
case by case basis.
For urban conditions HESL based the curve numbers on work performed
by Miller and Viessman (1973,p. 432) which graphically related curve numbers
and percent impervious surfaces. Miller and Viessman assume that urban
curve numbers should be at least as high as curve numbers for bare clay
soil. The bulldozing, compaction,and loss of top soil, which are normally
associated with construction practices, make this assumption reasonable.
Over the long term, soils in suburban areas may recover some porosity, and,
if they do, lower curve numbers should be used. The urban curve numbers
are presented in Table 3. These curve numbers are subject to revision as
more data becomes available. Composite curve numbers weighted by percent
areal distribution are necessary when more than one soil class or land use
6
TABLE 1. SCS HYDROLOGIC CLASSIFICATION OF HAWAIIAN SOILS
Sol I Name and Hydrologic Parameter)
Alf'lskee B Kaipoloi B L"f1a Ina B Paklnl 13Akaka A Kaiwi kl A Lalaau A-I Palapalal BAlae A Kalae B Lauma I"I B Pamoa CAleelo8 B Kalapa B Lawai B Panaewa 0Alakal 0 Kalaupapapa 0 Lei lehua B Pane BAlapal A Ka I ihl 0 Lihue B Papaa 0Amalu 0 Kaloko 0 Lokekaa B Papal A-IApakule A Ka"akoa A Lualualel 0 Paumalu BEwa B Kamaoa 8 M3hana B Pauwela BHaiku la Kamaole B Mahukona B Pearl Harbor DHalawa a Kaneohe n Mai'le A Pihonua l~
Haleiwa 18 Kanepuu B Makaalae B Pohakupu AHa I I I IB Kapaa A Makalapa 0 Pooku AHailimalle 8 Kapapala B Makapi I I A Puaulu AHarrakuapoko 8 Kapuhikani 0 Mak.3wao B Puhi AHana A Kaupo A Makawe 1I 8 Puhlmau I)
HanaleI It Kawaihae C Makena B Pulehu BHanlpoe 19 Kawaihapal B Makikl B Puna A-IHanamaulu ,r... Keaau 0 Mala B Punaluu DHawl 8 Keahua B Malama A-I Punohu AHeake !O Kealakekwa C Mamala 0 Puukala 0Helemano 'e Keal Ia 0 Manahaa C Puuone CHi"lman~ A Keaukaha D Manana C Puu 00 AHi lea D KeawakaplJ B Manu C Puu Opae BHi 10 ,A Keel D Mawae A-I Puu Pa BHolomua B Keekee B Moaula A Tantalus AHor,aunau C Kehena C Mokuleia B Ulupalakua BHo()okaa 1\ Kekaha B Molokal B Uma AHor'ol ua B Kekake D Naalehu B Umikoa BHor'omau B Kemoo B Naiwa B Uwala BHor'oullul I 0 Kikonl B Nlu B Wahiawa BHor,uaul u A-I Kilauea B NluI I I C Wahl kull BHoolehua B Kiloa A-I Nohi I I 0 Wa aha 0Hulkau A KI Johana A Nonopahu 0 Wa akoa CHulua 0 Koele 8 Oanapuka B Wa aleale 0Iael C Kohala A Chia A Wa alua B10 B Kc,kee B Olaa A-I Wa awa 0loleau C Koko B Olelo B Wa huna 0Jallcas A-' Kc,kokahl 0 ell B lola kaloa BKaaluala A Kc.lekole C 01 inda B lola kane BKa€ma D Koloa C Olokul 0 Walkapu BKaha Iuu D Kc,Jokolo B Ookala A Waikomo 0Kahana 8 Kc,na 0 Opihikao 0 Wai luku BKahanu I 8 Koo 1au C F'aai II B Waimea BKahua D Kuka1au A F'ea loa B Wainee BKailua A Kl/la B F'aauhau 'A Waipahu CKaimu A-I KlJn Ia 8 F'Ci Ia CKaiRallu A Kunuwela C F'c,ka Ia B
SOURCE: USDA Soil Conservation Service (1~75, p. 8-21).rocky phases ofNOTE: The hydrologic grougin g for the rOCKy to extremely
these soils should e reduced one group.llndlcator ~f minimum rate of Infiltration obtained for a bare soi I afterprolonged wetting;A" low runoff potential; high infiltration rate.B = Hodcr~tp Infi ltr0tion r~te.
C = Slow infi \}ration rafe.D" H <]h runof potentj.] : very 5!"W infl1triltlon rate.
6
TABLE 1. SCS HYDROLOGIC CLASSIFICATION OF HAWAIIAN SOILS
Sol I Name and Hydrologic Parameter)
Alf'lskee B Kaipoloi B L"f1a Ina B Paklnl 13Akaka A Kaiwi kl A Lalaau A-I Palapalal BAlae A Kalae B Lauma I"I B Pamoa CAleelo8 B Kalapa B Lawai B Panaewa 0Alakal 0 Kalaupapapa 0 Lei lehua B Pane BAlapal A Ka I ihl 0 Lihue B Papaa 0Amalu 0 Kaloko 0 Lokekaa B Papal A-IApakule A Ka"akoa A Lualualel 0 Paumalu BEwa B Kamaoa 8 M3hana B Pauwela BHaiku la Kamaole B Mahukona B Pearl Harbor DHalawa a Kaneohe n Mai'le A Pihonua l~
Haleiwa 18 Kanepuu B Makaalae B Pohakupu AHa I I I IB Kapaa A Makalapa 0 Pooku AHailimalle 8 Kapapala B Makapi I I A Puaulu AHarrakuapoko 8 Kapuhikani 0 Mak.3wao B Puhi AHana A Kaupo A Makawe 1I 8 Puhlmau I)
HanaleI It Kawaihae C Makena B Pulehu BHanlpoe 19 Kawaihapal B Makikl B Puna A-IHanamaulu ,r... Keaau 0 Mala B Punaluu DHawl 8 Keahua B Malama A-I Punohu AHeake !O Kealakekwa C Mamala 0 Puukala 0Helemano 'e Keal Ia 0 Manahaa C Puuone CHi"lman~ A Keaukaha D Manana C Puu 00 AHi lea D KeawakaplJ B Manu C Puu Opae BHi 10 ,A Keel D Mawae A-I Puu Pa BHolomua B Keekee B Moaula A Tantalus AHor,aunau C Kehena C Mokuleia B Ulupalakua BHo()okaa 1\ Kekaha B Molokal B Uma AHor'ol ua B Kekake D Naalehu B Umikoa BHor'omau B Kemoo B Naiwa B Uwala BHor'oullul I 0 Kikonl B Nlu B Wahiawa BHor,uaul u A-I Kilauea B NluI I I C Wahl kull BHoolehua B Kiloa A-I Nohi I I 0 Wa aha 0Hulkau A KI Johana A Nonopahu 0 Wa akoa CHulua 0 Koele 8 Oanapuka B Wa aleale 0Iael C Kohala A Chia A Wa alua B10 B Kc,kee B Olaa A-I Wa awa 0loleau C Koko B Olelo B Wa huna 0Jallcas A-' Kc,kokahl 0 ell B lola kaloa BKaaluala A Kc.lekole C 01 inda B lola kane BKa€ma D Koloa C Olokul 0 Walkapu BKaha Iuu D Kc,Jokolo B Ookala A Waikomo 0Kahana 8 Kc,na 0 Opihikao 0 Wai luku BKahanu I 8 Koo 1au C F'aai II B Waimea BKahua D Kuka1au A F'ea loa B Wainee BKailua A Kl/la B F'aauhau 'A Waipahu CKaimu A-I KlJn Ia 8 F'Ci Ia CKaiRallu A Kunuwela C F'c,ka Ia B
SOURCE: USDA Soil Conservation Service (1~75, p. 8-21).rocky phases ofNOTE: The hydrologic grougin g for the rOCKy to extremely
these soils should e reduced one group.llndlcator ~f minimum rate of Infiltration obtained for a bare soi I afterprolonged wetting;A" low runoff potential; high infiltration rate.B = Hodcr~tp Infi ltr0tion r~te.
C = Slow infi \}ration rafe.D" H <]h runof potentj.] : very 5!"W infl1triltlon rate.
SOURCE:
NOTE:
7
TABLE 2. RUNOFF CURVE NUMBERS FOR RURALSOl L/COVER COMP LEXES, HAWA I I I
LAND USE "CURVE NUMBER (Crt) FOR"SOIL GROUPSB C D
Row Crop 78 85 89Pasture 61 74 80
Orcha rd 58 72 78Brush* 59 73 79Cemetery 58 71 78
Golf Course 65 74 80
Forest 55 No soi 1 cover
SOURCE: Rural curve numbers from U.S. Soil ConservationService, Honolulu, Hawaii i, Summer 1973.
NOTE: Average moisture condition assumed for runoff curvenumbers.
*Includes farmsteads, greenhouses, poultry farms, ungrazedgrasslands, piggeries.
TABLE 3. RUNOFF CURVE NUMBERS FOR URBAN501 L/COVER COMPLEXES, HAWA I I I
Land Use Curve Number % ImperviousSurface
Sing 1e-Fam i 1y 91 10-35Multi-Family 94 48Commercial 97 75Schools/Playground 94 48Industrial 98 95Roads 98 95
HESL urban curve numbers after Miller and. Viessman (1973, p. 432); soil type not con~idered.
Average moisture conditions are assumed for runoffcurve numbers.
SOURCE:
NOTE:
7
TABLE 2. RUNOFF CURVE NUMBERS FOR RURALSOl L/COVER COMP LEXES, HAWA I I I
LAND USE "CURVE NUMBER (Crt) FOR"SOIL GROUPSB C D
Row Crop 78 85 89Pasture 61 74 80
Orcha rd 58 72 78Brush* 59 73 79Cemetery 58 71 78
Golf Course 65 74 80
Forest 55 No soi 1 cover
SOURCE: Rural curve numbers from U.S. Soil ConservationService, Honolulu, Hawaii i, Summer 1973.
NOTE: Average moisture condition assumed for runoff curvenumbers.
*Includes farmsteads, greenhouses, poultry farms, ungrazedgrasslands, piggeries.
TABLE 3. RUNOFF CURVE NUMBERS FOR URBAN501 L/COVER COMPLEXES, HAWA I I I
Land Use Curve Number % ImperviousSurface
Sing 1e-Fam i 1y 91 10-35Multi-Family 94 48Commercial 97 75Schools/Playground 94 48Industrial 98 95Roads 98 95
HESL urban curve numbers after Miller and. Viessman (1973, p. 432); soil type not con~idered.
Average moisture conditions are assumed for runoffcurve numbers.
8
exists within a drainage area.
The soi l/cover complex of a watcr'shcd is uscll to estimate the amount of
water that will be lost from runoff as a result of infiltration into the soil
and initial abstraction, e.g., wetting plant leaves. The losses (S) are cal
culated using the following equation (SCS 1969, p. 10.6):
in which
S = 1000/CN - 10
S = losses in surface inches
CN = curve number
(1)
nitrogen/event.
Curve numbers in
Once a volume of precipitation is determined, the runoff volume associated
with that rain can be calculated for an area with a known curve number using
the following equation (SCS 1969, p. 10.5)
Q =(p - 0.2S)2 (2)p + 0.8S
in which
Q = surface runoff in inches
p= surface precipitation in inches
S= rainfall loss calculated from eq. (1)
The SCS curve number technique thus estimates how much runoff will occur
as a results of a given depth of storm rainfall. Among the many potential
uses for such a model, its use for water quality management is of particular
interest in environmental management. The depth of storm water runoff from
equation (2) (over the drainage area in question) together with known or esti
mated chemical constituent concentrations can be used to determine total or
incremental constituent loads, such as pounds suspended solids/event or pounds
conjunction with time of concentration (T ), rainfallcdata, and a unit peak discharge graph can be combined to calculate peak
storm-water runoff rates. Many factors affect time of concentration but
two major factors are the distance surface water has to travel and the
slope of the land. The time of concentration equation used by HESL was
developed in 1973 by W. J. Matthews of the U.S. Army Corps of Engineers,
Pacific Ocean Division (Honolulu). The equation is based on the USACE
and SCS data and is a modification of the SCS lag time equation for
8
exists within a drainage area.
The soi l/cover complex of a watcr'shcd is uscll to estimate the amount of
water that will be lost from runoff as a result of infiltration into the soil
and initial abstraction, e.g., wetting plant leaves. The losses (S) are cal
culated using the following equation (SCS 1969, p. 10.6):
in which
S = 1000/CN - 10
S = losses in surface inches
CN = curve number
(1)
nitrogen/event.
Curve numbers in
Once a volume of precipitation is determined, the runoff volume associated
with that rain can be calculated for an area with a known curve number using
the following equation (SCS 1969, p. 10.5)
Q =(p - 0.2S)2 (2)p + 0.8S
in which
Q = surface runoff in inches
p= surface precipitation in inches
S= rainfall loss calculated from eq. (1)
The SCS curve number technique thus estimates how much runoff will occur
as a results of a given depth of storm rainfall. Among the many potential
uses for such a model, its use for water quality management is of particular
interest in environmental management. The depth of storm water runoff from
equation (2) (over the drainage area in question) together with known or esti
mated chemical constituent concentrations can be used to determine total or
incremental constituent loads, such as pounds suspended solids/event or pounds
conjunction with time of concentration (T ), rainfallcdata, and a unit peak discharge graph can be combined to calculate peak
storm-water runoff rates. Many factors affect time of concentration but
two major factors are the distance surface water has to travel and the
slope of the land. The time of concentration equation used by HESL was
developed in 1973 by W. J. Matthews of the U.S. Army Corps of Engineers,
Pacific Ocean Division (Honolulu). The equation is based on the USACE
and SCS data and is a modification of the SCS lag time equation for
9
areas of less than 8.09 x 106m2 (2000 acres) (SCS 1969, p. 15.7). The lag
equation is used in the January 1975 Urban Hydrology release (SCS 1975). The
SCS developed the lag equation for small watersheds where the effect of the
surface storage, rather than storage in major channels, is the important fac
tor in determining time of concentration.
The Matthews equation is as follows:
in which
Tc
= 4(L/400 + 2)0.6(S +1)°·8yQ.1l
(3)
T = time of concentration in minutescL hydraulic length (length from the most distant point)
in feet
S = rainfall loss calcuated from eq. (l)
Y = percent slope of land surface (rise over run)
As the curve number increases for the same slope and length in a water
shed, the S value in eq. (3) decreases and the time of concentration becomes
smaller. Although numerous other equations for time of concentration have
been developed, the Matthews equation is particularly useful to estimate the
effects of increased urban land use in small areas.
In procedures described in the SCS (1969) National Engineering Handbook,
the SCS calculates unit peak discharge rates for 0.025 m (1 in.) of run-off
on 2.59 x 106m2 (1.0 mi 2 ) of land for di~ferent times of concentration, a graph
of which is sho~~ in Figure 2. It can be noted that Figure 2 is for a 24-hr
rainfall .event with a standard Type I pattern rainfall, which is a reasonable
approximation for storm rainfall patterns in Hawai'i and certain regions of
the Pacific coast. A graph of the Type I storm distribution over a 24-hr
period is presented in Figure 3.
The remaining factor needed to calculate peak discharge rates is rainfall
depth for a 24-hr time period over rainfall return periods from 1 to 100 yr,
and it can be obtained from the U.S. Weather Bureau (1962) Rainfall-Frequency
Atlas of the Hawaiian Islands.
From the previously presented material, peak discharge for a given storm
in a specific watershed can be calculated as follows:
Q = q 'A' QP P
(4)
9
areas of less than 8.09 x 106m2 (2000 acres) (SCS 1969, p. 15.7). The lag
equation is used in the January 1975 Urban Hydrology release (SCS 1975). The
SCS developed the lag equation for small watersheds where the effect of the
surface storage, rather than storage in major channels, is the important fac
tor in determining time of concentration.
The Matthews equation is as follows:
in which
Tc
= 4(L/400 + 2)0.6(S +1)°·8yQ.1l
(3)
T = time of concentration in minutescL hydraulic length (length from the most distant point)
in feet
S = rainfall loss calcuated from eq. (l)
Y = percent slope of land surface (rise over run)
As the curve number increases for the same slope and length in a water
shed, the S value in eq. (3) decreases and the time of concentration becomes
smaller. Although numerous other equations for time of concentration have
been developed, the Matthews equation is particularly useful to estimate the
effects of increased urban land use in small areas.
In procedures described in the SCS (1969) National Engineering Handbook,
the SCS calculates unit peak discharge rates for 0.025 m (1 in.) of run-off
on 2.59 x 106m2 (1.0 mi 2 ) of land for di~ferent times of concentration, a graph
of which is sho~~ in Figure 2. It can be noted that Figure 2 is for a 24-hr
rainfall .event with a standard Type I pattern rainfall, which is a reasonable
approximation for storm rainfall patterns in Hawai'i and certain regions of
the Pacific coast. A graph of the Type I storm distribution over a 24-hr
period is presented in Figure 3.
The remaining factor needed to calculate peak discharge rates is rainfall
depth for a 24-hr time period over rainfall return periods from 1 to 100 yr,
and it can be obtained from the U.S. Weather Bureau (1962) Rainfall-Frequency
Atlas of the Hawaiian Islands.
From the previously presented material, peak discharge for a given storm
in a specific watershed can be calculated as follows:
Q = q 'A' QP P
(4)
10
00
50
0
.......4
-4
-0C:JL..C.-"-
<'lQ
)
--E1
00
"-III'+
-U--Q
.
0-~
~-La.4J
.-C;:)
--.....~~
r-....1'00..~
....~~
"-.......""""'"
~
~-~-
-~
.-I-"'"
i--"'-
-"'- ,-
"'~r'-
'~I~
"
IIIII0.1
1.0
Tim
eo
fC
on
centratio
n,
T(hr)
c
10.0
oFIGURE
2.UNIT
PEAKDISCHARGE
OFRUNOFF
VS.
TIME
OFCONCENTRATION,
Te•
FORTYPE
I24-H
REVALUATION
STORM
10
00
50
0
4-
4-0C:JL..C"-
<'lQ
)
E1
00
"-III'+
-U
Q.
0-~
~La.
4JC;:)
--...~~
r-....""""~i"oo~~~
.......""""""'"~-~-~
10
-~.I-~ ,..~~--~-,-
~~
r'-~"
II~
,-
IIIII0.1
1.0
Tim
eo
fC
on
centratio
n,
T(hr)
c
10.0
oFIGURE
2.UNIT
PEAKDISCHARGE
OFRUNOFF
VS.
TIME
OFCONCENTRATION,
Te•
FORTYPE
I24-H
REVALUATION
STORM
11
2 6 10 14 18 22
0.9
0.1
~_----'__---L__---L.__-'-__--'-__-'-__~_----'__---L__"""""__-'-__"'"
0.9
0.1
~0.7 0.7
~ -C I'llI'll
C.~ .-
I'll I'llL-
- ;"0.5 0.5I'll I'll
4- ~C 0.- I-I'llIX
..0-l-e( 0.3 0.3IX
,2 6 10 14
TIME (hr)18 22
FIGURE 3. SCS TYPE I 24-HR EVALUATION STORM
11
2 6 10 14 18 22
0.9
0.1
~_----'__---L__---L.__-'-__--'-__-'-__~_----'__---L__"""""__-'-__"'"
0.9
0.1
~0.7 0.7
~ -C I'llI'll
C.~ .-
I'll I'llL-
- ;"0.5 0.5I'll I'll
4- ~C 0.- I-I'llIX
..0-l-e( 0.3 0.3IX
,2 6 10 14
TIME (hr)18 22
FIGURE 3. SCS TYPE I 24-HR EVALUATION STORM
12
in which
Qp =qp =
A =Q =
storm peak discharge in cfs
storm water runoff per 0.02S m (1.0 in.) rainfallper 2.59 x 106m2 (1.0 mile2
) in cfs from Figure 2
drainage area in mile 2
sto~m runoff volume in m (in.) from equation (2).
APPLICATION OF THE HESL DISCHARGE FREQUENCY MODEL
The peak discharge value calculated from equation (4) represents flow
from land with roughly uniform slopes. When significantly different slopes
are encountered within the drainage area additional procedures are required.
As a part of its regional study, HESL divided the Kane'ohedrainage basin
into lS2.4-m (SOO-ft) square grid cells and for each cell coded a sizable
quantity of physical information for computer storage; thus, specific slope
ranges, soil types, vegetative cover, and land uses, over a given area could
be readily obtained. However, for the general case, the various data inputs
can be determined from appropriate maps.
For the alternative future studies, the individual drainage areas in
the Kane'ohe region were separated into three zones: "flat", 0 to 10%;
"hills", 11 to 99%; and "paU" (precipice), greater than 99%. These slope
zones were chosen by inspecting a topographic map. Soils maps can also be
used to determine response zones. The slope zone ranges must also represent
a downward elevation sequence to allow for the normal flow of storm water
runoff. Length of the storm water runoff drainage path was determined for
each slope zone for use in the time of concentration (eq. [3]). The lengths
are estimated from the watershed outlet point, rather than from the zone
outlet point, inasmuch as peak discharges are desired for the entire water
shed area. The utilization of the slope zones is illustrated in Figure 4.
After peak discharges were calculated for each slope zone in a drainage
area for the rainfall events chosen from the Rainfall Frequency Atlas, drain
age area peak discharges for each storm were calculated by summing the indi
vidual slope zone peak flows. Simple summation was feasible because the
basins were small and steep, consequently, the times of concentration for
each of the zones were measured in minutes. Summing, rather than routing,
the zone responses greatly reduces the complexity of the technique and the
amount of data required to apply it. Summing infers that peak flows from
12
in which
Qp =qp =
A =Q =
storm peak discharge in cfs
storm water runoff per 0.02S m (1.0 in.) rainfallper 2.59 x 106m2 (1.0 mile2
) in cfs from Figure 2
drainage area in mile 2
sto~m runoff volume in m (in.) from equation (2).
APPLICATION OF THE HESL DISCHARGE FREQUENCY MODEL
The peak discharge value calculated from equation (4) represents flow
from land with roughly uniform slopes. When significantly different slopes
are encountered within the drainage area additional procedures are required.
As a part of its regional study, HESL divided the Kane'ohedrainage basin
into lS2.4-m (SOO-ft) square grid cells and for each cell coded a sizable
quantity of physical information for computer storage; thus, specific slope
ranges, soil types, vegetative cover, and land uses, over a given area could
be readily obtained. However, for the general case, the various data inputs
can be determined from appropriate maps.
For the alternative future studies, the individual drainage areas in
the Kane'ohe region were separated into three zones: "flat", 0 to 10%;
"hills", 11 to 99%; and "paU" (precipice), greater than 99%. These slope
zones were chosen by inspecting a topographic map. Soils maps can also be
used to determine response zones. The slope zone ranges must also represent
a downward elevation sequence to allow for the normal flow of storm water
runoff. Length of the storm water runoff drainage path was determined for
each slope zone for use in the time of concentration (eq. [3]). The lengths
are estimated from the watershed outlet point, rather than from the zone
outlet point, inasmuch as peak discharges are desired for the entire water
shed area. The utilization of the slope zones is illustrated in Figure 4.
After peak discharges were calculated for each slope zone in a drainage
area for the rainfall events chosen from the Rainfall Frequency Atlas, drain
age area peak discharges for each storm were calculated by summing the indi
vidual slope zone peak flows. Simple summation was feasible because the
basins were small and steep, consequently, the times of concentration for
each of the zones were measured in minutes. Summing, rather than routing,
the zone responses greatly reduces the complexity of the technique and the
amount of data required to apply it. Summing infers that peak flows from
Explanation
---FLATS
------HILLS
-·_·-PALI
HILLS51 ope >11 %and <99%
FLATSslope <11 %
13
FIGURE 4. SAMPLE SLOPE ZONE LENGTHS
Explanation
---FLATS
------HILLS
-·_·-PALI
HILLS51 ope >11 %and <99%
FLATSslope <11 %
13
FIGURE 4. SAMPLE SLOPE ZONE LENGTHS
14
zones overlap at the outlet, which is the most critical circumstance. In
small, steep watersheds overlapping during natural events would be sensitive
to the time and space distribution of rainfall and the duration of high
intensity bursts over the basin.
The purpose of the model described above is to estimate changes in the
long term flow responses of a small watershed which are attributable to
changes in the land use of the watershed. Currently no data are available
to validate such a model for Hawaiian conditions, and only limited testing
is possible. To overcome this deficiency, a data collection and analysis
program was established in 1972 by the University of Hawaii Water Resources
Research Center (Fok 1973). Figures 5 through 8 provide sample comparisons
of flow frequency curves derived statistically by the Hawaii State Depart
ment of Land and Natural Resources (DLNR) using a log Pearson Type III
equation and values derived using the proposed HESL model. The HESL model
was applied for five to six rainfall return intervals assuming both an
average and a wet antecedent moisture condition as indicated by the letters
"A" and "W" in Figures 5 to 8. The watershed locations are shown in Figure 1.
The watershed areas, lengths of record, and standard deviations of the his
torical peaks are shown on the figures. The frequency values for the HESL
peak discharges are assumed equal to the rainfall input frequency values used
to derive the peaks as previously described. None of the gages are in the
coastal plains where major development occurs.
The peak values are sensitive to moisture condition. The more frequent
events are better estimated by average moisture assumptions and, in general,
the rarer events are better estimated by wet moisture assumptions. However,
for Puke1e watershed low frequency values (rare events) are better estimated
by average moisture conditions. Average moisture assumptions produce superior
results for large events at another watershed which will be discussed later.
It is not included here because it does not have long-term flow records.
At the present time, there are insufficient data to derive a general
statement covering moisture condition assumptions for rare storm frequencies.
The number of long~term gage records is too small, and the model is a gross
simplification. However, the better estimates of frequencies most sensitive
to changes in land use tend toward the average antecedent moisture conditions.
Use of the average antecedent moisture condition assumption for estimating
the impact of urbanization on incremental changes in peak discharges will
14
zones overlap at the outlet, which is the most critical circumstance. In
small, steep watersheds overlapping during natural events would be sensitive
to the time and space distribution of rainfall and the duration of high
intensity bursts over the basin.
The purpose of the model described above is to estimate changes in the
long term flow responses of a small watershed which are attributable to
changes in the land use of the watershed. Currently no data are available
to validate such a model for Hawaiian conditions, and only limited testing
is possible. To overcome this deficiency, a data collection and analysis
program was established in 1972 by the University of Hawaii Water Resources
Research Center (Fok 1973). Figures 5 through 8 provide sample comparisons
of flow frequency curves derived statistically by the Hawaii State Depart
ment of Land and Natural Resources (DLNR) using a log Pearson Type III
equation and values derived using the proposed HESL model. The HESL model
was applied for five to six rainfall return intervals assuming both an
average and a wet antecedent moisture condition as indicated by the letters
"A" and "w" in Figures 5 to 8. The watershed locations are shown in Figure 1.
The watershed areas, lengths of record, and standard deviations of the his
torical peaks are shown on the figures. The frequency values for the HESL
peak discharges are assumed equal to the rainfall input frequency values used
to derive the peaks as previously described. None of the gages are in the
coastal plains where major development occurs.
The peak values are sensitive to moisture condition. The more frequent
events are better estimated by average moisture assumptions and, in general,
the rarer events are better estimated by wet moisture assumptions. However,
for Puke1e watershed low frequency values (rare events) are better estimated
by average moisture conditions. Average moisture assumptions produce superior
results for large events at another watershed which will be discussed later.
It is not included here because it does not have long-term flow records.
At the present time, there are insufficient data to derive a general
statement covering moisture condition assumptions for rare storm frequencies.
The number of long~term gage records is too small, and the model is a gross
simplification. However, the better estimates of frequencies most sensitive
to changes in land use tend toward the average antecedent moisture conditions.
Use of the average antecedent moisture condition assumption for estimating
the impact of urbanization on incremental changes in peak discharges will
.0.0
19
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010
Ann
ual
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ESL
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URE
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ESL
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FIG
URE
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AND
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I7
31Y
ears
of
Rec
ord
"I"
0.28
Mil
e2
Are
aW
/A
W-
Wet
Moi
stur
eC
ondi
tion
A'
A-
Avg
.M
oist
ure
Con
diti
onAI
Sta
ndar
dD
evis
tio
n=
300
cfs'
W,
A-
HESL
VJ
w".
~~/
<$/
l// ,..
VA
/'
./
1....,...
00~
10·
99
.99
99
90
50
10A
nnua
lP
rob
abil
ity
of
Exc
eeda
nce
(%)
0.01
FIG
URE
6.CO
MPA
RISO
NOF
HESL
AND
DLNR
DISC
HARG
EFR
EQUE
NCY
VALU
ESFO
RKA
HALU
'U
104
Vl~
U ........
- PUKE
LE24
4019
69L
and
Use
43Year~
of
Rec
ord
1.18
Mil
e2
Are
aW
-W
etM
oist
ure
Con
diti
onA
-A
vg.
Moi
stur
eC
ondi
tion
WS
tan
dar
dD
evia
tio
n=
500
cfs
WW
,A
-HE
SL..
W
~l/
A
~
/A
WA
/II"
W1
/1
/1I
A
/~~/
A<:)
'7.
V,V
Q) en :0
103
.J:: U Vl
o
102 9
9.9
99
99
05
010
Ann
ual
Pro
bab
ilit
yo
fE
xcee
danc
e(%
)0
.01
FIG
URE
7.CO
MPA
RISO
NOF
HESL
AND
DLNR
DIS
CHA
RGE
FREQ
UENC
YVA
LUES
FOR
PUKE
LE
~..,~,.~i~~~';:'-'ff:~""'~;,.l-'t.i·i:~";';',~~,,,;
__.r
c...
-..~
.,,-
--=~
~"~.
~..~~--""''''''.
..''''
''....-
--
.......
- PUKE
LE24
4019
69L
and
Use
43Y
ears
of
Rec
ord
1.18
Mil
e2
Are
aW
-W
etM
oist
ure
Con
diti
onA
-A
vg.
Moi
stur
eC
ondi
tion
WS
tan
dar
dD
evia
tio
n=
500
cfs
W}W
.A
-HE
SL-
W
~,/
~
/AW
A/
Wl/
1/
l/A
V.i
/A
QY.
V,V
1Il
4 o o
102 9
9.9
99
99
05
010
Ann
ual
Pro
bab
ilit
yo
fE
xcee
danc
e(%
)0
.01
FIG
URE
7.CO
MPA
RISO
NOF
HESL
AND
DLNR
DIS
CHA
RGE
FREQ
UENC
YVA
LUES
FOR
PUKE
LE
00
0.0
19
9
KALI
HIAT
HONO
LULU
2290
l'W/1
1969
Land
Use
1/
W~
w1
53Y
ears
of
Rec
ord
'i'
I2
.6M
ile
2A
rea
V-
AW
-W
etM
oist
ure
Co
nd
itio
nA
A-
Avg
.M
oist
ure
Co
nd
itio
n/
iii'"~
Sta
nd
ard
Dev
iati
on
-22
00cf
sl/1i
I'"W
,A
-H
ESL
A
/
PV<;
)'V
f/
A
//
) V/
V9
05
010
Ann
ual
Pro
bab
ilit
yo
fE
xcee
danc
e(%
)
FIG
URE
8.CO
MPA
RISO
NOF
HES
LAN
DDL
NRD
ISCH
ARG
EFR
EQUE
NCY
VALU
ESFO
RK
ALI
HI
102 99
.99
Cl
104
Q) ~
103
III
.s::::. U III
.-..
VI~
U .......
00
0.01
99
KALI
HIAT
HONO
LULU
2290
Ji'
/1W
1969
Land
Use
/W
I53
Yea
rso
fR
ecor
d./
W~
2.6
Mil
e2
Are
a~'
I
W-
Wet
Moi
stur
eC
on
dit
ion
~A
AA
-A
vg.
Moi
stur
eC
on
dit
ion
/S
tan
dar
dD
evia
tio
n-
2200
.cfs
1\
W,
A-
HES
L1I
I"
..A
/
~V
<:)'V
7 /A
//
I I
II V9
05
010
Ann
ual
Pro
bab
ilit
yo
fE
xcee
danc
e(%
)
FIG
URE
8.CO
MPA
RISO
NOF
HES
LAN
DDL
NRD
ISCH
ARG
EFR
EQUE
NCY
VALU
ESFO
RK
ALI
HI
102 99
.99
Cl
.......
1Il
" U -
19
produce estimates that are larger than if wet conditions are used. For ex
tremely rare events, greater than the 2% event, prudent engineering judge
ment would indicate the use of wet conditions unless available data indicate
otherwise. The choice of an appropriate moisture condition for a frequency
event has to be made after considering the calibration data available and
the purpose of the study.
Since no data are available to test the discharge frequency curve calcu
lations for a before and after example of land-use change,' only hypothetical
cases c~n be examined. Figure 9 shows for a hypothetical waters~ed the cal
culated results when there is: an extreme change in land use from all forest
to all subdivision. Dramatic reductions in times of concehtration are ob
served, and significant changes in peak discharge are calculated for these
extreme land-use changes for all frequencies:
The data shown in Table 4 are a comparison of the HESL Peak Discharge
Model estimates with the results of the USACE technique for the design
storms used to determine the capacity of the proposed Keapuka Dam site fon
Kamo'oali'i Stream, which is within the Kane'ohe region. Average moisture
conditions are used in this example since average assumptions provided supe
rior estimates for this basin during tests of actual events. One of these
observed events is believed to be within the 1% range. This comparison is
provided for information only and is not intended to imply that the proposed
technique is a design technique.
TABLE 4. COMPARISON OF HESL AND U.S. ARMY CORPS OF ENGINEERSPEAK DISCHARGES FOR DESIGN OF THE KEAPUKA DAM ANDRfSERVOIR, KANE'OHE O'AHU
DESIGN STORM RAINFALL( in.)
PEAK DISCHARGEUSACE
(cfs)HESL
Standard 24 hr
Maximum Probable(6,hr)*
Flood
27.8
29.7
15 000
30 000
13 000
28 000
NOTE: Rainfall data and peak discharge values for USACE obtainedin 1973. The USACE standard flood ,is a large event thathas no stated frequency; it is less than a probable maximum event and usually greater than a 1% event.
NOTE: in. x 0.025 40 = mcfs x 0.028 32 = m2/s.
*A 6-hr duration unit peak discharge graph was provided by theU.S. Soil Conservation Service for calculating the second event.
The model was used as a regional planning tool to estimate changes in
19
produce estimates that are larger than if wet conditions are used. For ex
tremely rare events, greater than the 2% event, prudent engineering judge
ment would indicate the use of wet conditions unless available data indicate
otherwise. The choice of an appropriate moisture condition for a frequency
event has to be made after considering the calibration data available and
the purpose of the study.
Since no data are available to test the discharge frequency curve calcu
lations for a before and after example of land-use change,' only hypothetical
cases c~n be examined. Figure 9 shows for a hypothetical waters~ed the cal
culated results when there is: an extreme change in land use from all forest
to all subdivision. Dramatic reductions in times of concehtration are ob
served, and significant changes in peak discharge are calculated for these
extreme land-use changes for all frequencies:
The data shown in Table 4 are a comparison of the HESL Peak Discharge
Model estimates with the results of the USACE technique for the design
storms used to determine the capacity of the proposed Keapuka Dam site fon
Kamo'oali'i Stream, which is within the Kane'ohe region. Average moisture
conditions are used in this example since average assumptions provided supe
rior estimates for this basin during tests of actual events. One of these
observed events is believed to be within the 1% range. This comparison is
provided for information only and is not intended to imply that the proposed
technique is a design technique.
TABLE 4. COMPARISON OF HESL AND U.S. ARMY CORPS OF ENGINEERSPEAK DISCHARGES FOR DESIGN OF THE KEAPUKA DAM ANDRfSERVOIR, KANE'OHE O'AHU
DESIGN STORM RAINFALL( in.)
PEAK DISCHARGEUSACE
(cfs)HESL
Standard 24 hr
Maximum Probable(6,hr)*
Flood
27.8
29.7
15 000
30 000
13 000
28 000
NOTE: Rainfall data and peak discharge values for USACE obtainedin 1973. The USACE standard flood ,is a large event thathas no stated frequency; it is less than a probable maximum event and usually greater than a 1% event.
NOTE: in. x 0.025 40 = mcfs x 0.028 32 = m2/s.
*A 6-hr duration unit peak discharge graph was provided by theU.S. Soil Conservation Service for calculating the second event.
The model was used as a regional planning tool to estimate changes in
104
..-..
.
I/l~
U - Q) E
103
ro .c u I/l
c
102
HYPO
THET
ICAL
WAT
ERSH
ED
Slo
pe=
5%L
engt
h=
10,0
00ft
Are
a=
1.0
Mil
e2
Rai
nfa
11F
requ
ency
Inch
es./
'f'.
14
V5
8/
1010
~il'
..
2511
VV
~
5013
100
15V
VV
l/I-'
~
I1
II""
//
ALL
SUBD
IVIS
ION
/V
/Tc
=25
min
'L
~
V/
~,
~
//
1/2
SUBDIVISION~
I(
Tc=
50m
in-'- V
JI( V
ALL
FOR
ESTI
Tc=
90--
min
11
I
N o
99
.99
99
90
50
10·1
Ann
ual
Pro
bab
ilit
y~f
Exc
eeda
nce
(%)
FIG
URE
9.LA
ND
-USE
EFFE
CTS
FOR
AH
YPO
THET
ICA
LCA
SE
0.01
_
til
4 U ........
Cl
102
,
HYPO
THET
ICAL
WAT
ERSH
EDS
lope
=5%
Len
gth
=10
,000
ftA
rea
=1
.0M
ile
2
Rai
nfa
llF
requ
ency
Inch
esL
~.
-1
4
V5
810
10/
~II'
..25
11/
/.".
..50
13
/'10
015
V~/
V~
~I
IWi
"",/
./
ALL
SUB
DIV
ISIO
N/
~/
Tc=
25m
in'
/II
'/
V".
j
V/
1/2
SUBDIVISION~
Ij
Tc=
50m
inV J
'( VAL
LFO
RES
TITc
=90
--m
inI
II
N o
99
99
.99
90
50
10A
nnua
lP
rob
abil
ity
~f
Exc
eeda
nce
(%)
FIG
URE
9.LAND~USE
EFFE
CTS
FOR
AH
YPO
THET
ICA
LCA
SE
0.01
..
21
peak discharges for ten streams in the Kanetohe region for alternative pat
terns of future developmetn (HESL 1974). Results for four of these locations
are shown for comparative purposes in Table 5. Scenario I represents
"Current Trends" and is based on the City and County of Honolulu's 1964
amended General Plan. Scenario II represents "Unrestrained Growth" and is
based on developers' intentions through 1985 as indicated by qpplications
submitted to the Department of Land Utilization. After 1985, sites meeting
traditional land picking criteria used by developers were included. Sce
nario III represents "Controlled Growth" and is based on specific environ
mental restrictions other than peak discharge considerations. The base year
for purposes of comparison is 1970, and the time horizon for the three pat
terns is 1995. Average moisture assumptions were used for this study. The
resulting peak discharges calculated for the three scenario projections are
shown in Table 5. As can be observed from Table 5, the resulting peak dis
charges and potential flooding hazards may alter development and/or design
considerations for any of the three scenarios for the individual drainage
areas within the Kane'ohe region.
Interpretation of the percent increases in peak discharge requires
special consideration of two points: first, although peak discharge might
double as the result of a land-use change, it does not necessarily follow
that flood depths would also double since the velocity increases with depth
and the relationships between peak cfs and flow depth are not linear; and
second, losses caused by infiltration and initial abstraction constitute a
greater share of low magnitude rainfall events than that of high magnitude
events. Therefore, percent changes in peak discharge for an event expected
once a year are greater than that of the percent changes for an event ex~
pected once every 100 years.
SUMMARY
In summary the HESL Peak Discharge Model is a relatively simple planning
oriented tool that was developed, using existing technology, for both gaged
and ungaged small watersheds (up to approximately 8.094 x 106 m2 or
2000 acres) in Hawai'i. The model was not intended for use in determining
the peak discharges necessary for design of specific structures but, rather,
for such uses as ascertaining incremental changes in peak discharges and in
21
peak discharges for ten streams in the Kanetohe region for alternative pat
terns of future developmetn (HESL 1974). Results for four of these locations
are shown for comparative purposes in Table 5. Scenario I represents
"Current Trends" and is based on the City and County of Honolulu's 1964
amended General Plan. Scenario II represents "Unrestrained Growth" and is
based on developers' intentions through 1985 as indicated by qpplications
submitted to the Department of Land Utilization. After 1985, sites meeting
traditional land picking criteria used by developers were included. Sce
nario III represents "Controlled Growth" and is based on specific environ
mental restrictions other than peak discharge considerations. The base year
for purposes of comparison is 1970, and the time horizon for the three pat
terns is 1995. Average moisture assumptions were used for this study. The
resulting peak discharges calculated for the three scenario projections are
shown in Table 5. As can be observed from Table 5, the resulting peak dis
charges and potential flooding hazards may alter development and/or design
considerations for any of the three scenarios for the individual drainage
areas within the Kane'ohe region.
Interpretation of the percent increases in peak discharge requires
special consideration of two points: first, although peak discharge might
double as the result of a land-use change, it does not necessarily follow
that flood depths would also double since the velocity increases with depth
and the relationships between peak cfs and flow depth are not linear; and
second, losses caused by infiltration and initial abstraction constitute a
greater share of low magnitude rainfall events than that of high magnitude
events. Therefore, percent changes in peak discharge for an event expected
once a year are greater than that of the percent changes for an event ex~
pected once every 100 years.
SUMMARY
In summary the HESL Peak Discharge Model is a relatively simple planning
oriented tool that was developed, using existing technology, for both gaged
and ungaged small watersheds (up to approximately 8.094 x 106 m2 or
2000 acres) in Hawai'i. The model was not intended for use in determining
the peak discharges necessary for design of specific structures but, rather,
for such uses as ascertaining incremental changes in peak discharges and in
N
TABL
E5.
SUMM
ARY
OFLAND~USE
ASSU
MPT
IONS
AND
DISC
HARG
ESFO
RSC
ENAR
IOS
APP
LICA
TIO
NS
,--.>
INFO
URKA
NE'O
HEW
ATER
SHED
S,O
·AHU
,HA
WAI
II
URBA
NIZ
ATIO
N·.
DISC
HARG
ES
1970
Sce
nari
os(1
995)
Ret
urn
1970
Sce
nari
os(1
995)
WAT
ERSH
EDAR
EAB
ase
III
III
Inte
rval
Bas
eI
"II
I
Yea
r%
Incr
ease
Yea
r%
Incr
ease
(mI1
e2)
(%)
from
1970
to19
95(y
r)(c
fs)
from
1970
to19
95
Unn
amed
Dit
ch1.
063
035
0.1
320
084
0
Are
a10
1500
040
0
5022
000
350
'Ahu
lman
u2.
3111
1822
131
680
3862
31
1031
0016
2614
5047
0015
2111
Kea
Iah
a1a
0.62
417
721
126
012
1542
1088
07
925
5013
000
015
WaI
kane
2.64
00
60
185
00
160
1035
000
90
50.
5400
07
0
NOTE
:m
lle
2x
259
000
0-
m2
cfs
x0.
028
32=
m3/s
.
TABL
E5.
N
SUM
MAR
YOF
LAND
·USE
ASSU
MPT
IONS
AND
DISC
HARG
ESFO
RSC
ENAR
IOS
APP
LICA
TIO
NS
,-.>
INFO
URKA
NE'O
HEW
ATER
SHED
S,O
IAH
U,
HAW
AIII
URBA
NIZ
ATIO
NDI
SCHA
RGES
1970
Scen
ari
os(1
995)
Ret
urn
1970
Sce
nari
os(1
995)
WAT
ERSH
EDAR
EAB
ase
III
III
Bas
eI
"II
I
Yea
r%
Incr
ease
Inte
rval
Yea
r%
Incr
ease
(mil
e2
)(%
)fr
om19
70to
1995
(yr)
(cfs
)fr
om19
70to
1995
Unn
amed
Dit
ch1.
063
035
0.1
320
084
0
Are
a10
1500
040
0
5022
000
350
'Ahu
iman
u2.
3111
1822
131
680
3862
31
1031
0016
2614
5047
0015
2111
Kea
Iah
ala
0.62
417
721
126
012
1542
10.
880
79
25
5013
000
015
Wai
kane
2.64
00
60
850
016
0
1035
000
90
50
.54
0'0
07
0
NOTE
:m
ile
2x
259
000
0-
ml
cfs
x0.
028
32=
m3/s
.
23the quality of storm water runoff, if constituent ,values are available, foralternate land-use patterns. Thus, it is a tool that can be used by engineers, land-use planners, and/or decision makers for technical assessmenttasks that range from reconnaissance surveys to environmental' impact evaluations in situations where use of the more time consuming, sophisticatedmethods is not warranted.
ACKNOWLEDGMENTS
The research forming the basis of this paper was supported by the HawaiiEnvironmental Simulation Laboratory, University of Hawaii, which was fundedin part by Grant GI-36224 from the National Science Foundation and by Grant730-0042 from the Ford Foundation, and, in part, by the Hawaii State Officeof Environmental Quality Control. Special acknowledgments are extended toSalvador Palalay of the Honolulu office of the U.S. Soil Conservation Servic~ fOr his sound advice and help in providing SCS material for the study;and also to William J. Matthews of the U.S. Army Corps of Engineers,Pacific Ocean Division, for his counsel and generosity in providing thetime of concentration equation applicable to Hawaiian conditions, which hedeveloped from a SCS relationship for lag time. And special appreciationis extended to Paul Bartram of the HESL staff whose help and suggestionswere invaluable, and to Dr. L. Stephen Lau, Director of the Water ResourcesResearch Center, University of Hawaii, for his interest ,and assistance inthe publication of this report.
23the quality of storm water runoff, if constituent ,values are available, foralternate land-use patterns. Thus, it is a tool that can be used by engineers, land-use planners, and/or decision makers for technical assessmenttasks that range from reconnaissance surveys to environmental' impact evaluations in situations where use of the more time consuming, sophisticatedmethods is not warranted.
ACKNOWLEDGMENTS
The research forming the basis of this paper was supported by the HawaiiEnvironmental Simulation Laboratory, University of Hawaii, which was fundedin part by Grant GI-36224 from the National Science Foundation and by Grant730-0042 from the Ford Foundation, and, in part, by the Hawaii State Officeof Environmental Quality Control. Special acknowledgments are extended toSalvador Palalay of the Honolulu office of the U.S. Soil Conservation Servic~ fOr his sound advice and help in providing SCS material for the study;and also to William J. Matthews of the U.S. Army Corps of Engineers,Pacific Ocean Division, for his counsel and generosity in providing thetime of concentration equation applicable to Hawaiian conditions, which hedeveloped from a SCS relationship for lag time. And special appreciationis extended to Paul Bartram of the HESL staff whose help and suggestionswere invaluable, and to Dr. L. Stephen Lau, Director of the Water ResourcesResearch Center, University of Hawaii, for his interest ,and assistance inthe publication of this report.
24
REFERENCES
Division of Water and Land Development. 1970. Flood frequenciep'for
selected streams in Hawaii. R36, Department of Land and Natural
Resources, State of Hawaii.
Fok, Y.S. 1973. A preliminary report on urban hydrology and "urban water
resources: Oahu, Hawaii. Tech. Rep. No. 74, Water Resources Research
Center, University of Hawaii.
Hawaii Environmental Simulation Laboratory. 1974. Kaneohe alternatives:
An application of impact methodology. Report to the Office of Environ
mental Quality Control, State of Hawaii by HESL. University of Hawaii.
Larson, C.L., and Reich, B.M. 1973. Relationship of observed rainfall and
runoff recurrence intervals. In Proc. 2d Intl. Sympos. in Hydrology
September 11-13, 1972, Water Resources Publications, Fort Collins,
Colorado.
Lopez, N.C. 1974. "Estimating the effect of urbanization of small water
shed peak discharges." Working Paper WP 73-001, Hawaii Environmental
Simulation Laboratory, University of Hawaii.
Miller, C.R., and Viessman, W., Jr. 1973. Runoff volumes from small
watersheds. Water Resources Res. 8(2):432.
Soil Conservation Service. 1969. National engineering handbook. U.S.
Dept. of Agriculture, U.S. Government Printing Office.
1970. Estimating peak discharges for watershed evaluation storms
'----and preliminary designs. TSC Tech. Note-Hydrology PO-2, U.S. Dept.
of Agriculture, U.S; Government Printing Office.
1975. Urban hydrology for small watersheds. Tech. Release No.
55, U.S. Dept. of Agriculture, U.S. Government Printing Office.
U.S. Army Corps' of Engineers. 1973. Hydrology, flood control and allied
purposes, Kaneohe-Kailua area, Oahu, Hawaii. Design Memo. No.1,
USACE, Pacific Ocean Division, Honolulu, Hawaii.
U.S. Weather Bureau. Rainfall frequency atlas of the Hawaiian Islands.
Tech. Paper No. 43. Washington, D.C.
24
REFERENCES
Division of Water and Land Development. 1970. Flood frequenciep,,for
selected streams in Hawaii. R36, Department of Land and Natural
Resources, State of Hawaii.
Fok, Y.S. 1973. A preliminary report on urban hydrology and "urban water
resources: Oahu, Hawaii. Tech. Rep. No. 74, Water Resources Research
Center, University of Hawaii.
Hawaii Environmental Simulation Laboratory. 1974. Kaneohe alternatives:
An application of impact methodology. Report to the Office of Environ
mental Quality Control, State of Hawaii by HESL. University of Hawaii.
Larson, C.L., and Reich, B.M. 1973. Relationship of observed rainfall and
runoff recurrence intervals. In Proc. 2d Intl. Sympos. in Hydrology
September 11-13, 1972, Water Resources Publications, Fort Collins,
Colorado.
Lopez, N.C. 1974. "Estimating the effect of urbanization of small water
shed peak discharges." Working Paper WP 73-001, Hawaii Environmental
Simulation Laboratory, University of Hawaii.
Miller, C.R., and Viessman, W., Jr. 1973. Runoff volumes from small
watersheds. Water Resources Res. 8(2):432.
Soil Conservation Service. 1969. National engineering handbook. U.S.
Dept. of Agriculture, U.S. Government Printing Office.
1970. Estimating peak discharges for watershed evaluation storms
'----and preliminary designs. TSC Tech. Note-Hydrology PO-2, U.S. Dept.
of Agriculture, U.S; Government Printing Office.
1975. Urban hydrology for small watersheds. Tech. Release No.
55, U.S. Dept. of Agriculture, U.S. Government Printing Office.
U.S. Army Corps' of Engineers. 1973. Hydrology, flood control and allied
purposes, Kaneohe-Kailua area, Oahu, Hawaii. Design Memo. No.1,
USACE, Pacific Ocean Division, Honolulu, Hawaii.
U.S. Weather Bureau. Rainfall frequency atlas of the Hawaiian Islands.
Tech. Paper No. 43. Washington, D.C.
