U.S. Department of the Interior

U.S. Geological Survey

Scientific Investigations Report 2015–5010

Version 2.0, December 2017

Prepared in cooperation with the State of Hawai‘i Commission on Water Resource Management and the City 

and County of Honolulu Board of Water Supply 

Spatially Distributed Groundwater Recharge for 2010 Land Cover 

Estimated Using a Water-Budget Model for the Island of O’ahu, Hawai’i
COVER

From left to right. An upper reach of Kīpapa Stream, Island of O‘ahu, Hawai‘i. Photograph by Reuben H. Wolff, June 2007. Hillside 

in upper Kīpapa Valley covered with native and alien plants, Island of O‘ahu, Hawai‘i. Photograph by Reuben H. Wolff, June 2007. 

View from Waimano Ridge near the crest of the Ko‘olau Range looking southwest toward Pearl Harbor, Island of O‘ahu, Hawai‘i. 

Photograph by Adam G. Johnson, May 2010. Top right: Mean annual recharge for average climate conditions, Island of O‘ahu.
Spatially Distributed Groundwater Recharge 

for 2010 Land Cover Estimated Using a 

Water-Budget Model for the Island of O‘ahu, 

Hawai‘i

By John A. Engott, Adam G. Johnson, Maoya Bassiouni, Scot K. Izuka, and Kolja Rotzoll

Prepared in cooperation with the State of Hawai‘i Commission on Water Resource 

Management and the City and County of Honolulu Board of Water Supply

Scientific Investigations Report 2015–5010

Version 2.0, December 2017

U.S. Department of the Interior

U.S. Geological Survey
ii 

U.S. Department of the Interior

RYAN K. ZINKE, Secretary

U.S. Geological Survey

William H. Werkheiser, Deputy Director exercising the authority

of the Director

U.S. Geological Survey, Reston, Virginia: 2017

First release: 2015, online

Revised: December 2017 (ver. 2.0), online

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Suggested citation:

Engott, J.A., Johnson, A.G., Bassiouni, Maoya, Izuka, S.K., and Rotzoll, Kolja, 2017, Spatially distributed groundwater 

recharge for 2010 land cover estimated using a water-budget model for the Island of O‘ahu, Hawai‘i (ver. 2.0, 

December 2017): U.S. Geological Survey Scientific Investigations Report 2015–5010, 49 p., https://doi.org/10.3133/

sir20155010.

ISSN 2328-0328 (online)
 iii

Contents

Abstract ........................................................................................................................................................1

Introduction...................................................................................................................................................1

Purpose and Scope .............................................................................................................................3

Previous Studies..................................................................................................................................3

Acknowledgments................................................................................................................................3

Description of O‘ahu.....................................................................................................................................3

Physical Setting ...................................................................................................................................3

Climate ................................................................................................................................................5

Hydrogeology.......................................................................................................................................5

Surface Water......................................................................................................................................7

Soils ................................................................................................................................................7

Land Cover ..........................................................................................................................................7

Water-Budget Model.....................................................................................................................................9

Conceptual Model..............................................................................................................................10

Model Calculations ............................................................................................................................10

Iteration.....................................................................................................................................14

Model Input.................................................................................................................................................14

Land Cover ........................................................................................................................................14

Rainfall ..............................................................................................................................................15

Monthly Rainfall ........................................................................................................................15

Daily Rainfall.............................................................................................................................16

Fog Interception.................................................................................................................................16

Irrigation.............................................................................................................................................17

Septic-System Leaching....................................................................................................................17

Storm-Drain Systems.........................................................................................................................18

Direct Runoff......................................................................................................................................18

Computation of Seasonal Runoff-to-Rainfall Ratios..................................................................18

Runoff-to-Rainfall Ratios Assigned to Ungaged Catchment Zones ..........................................20

Runoff-to-Rainfall Ratios Assigned to Gaged Basins within a Single Catchment Zone............24

Runoff-to-Rainfall Ratios Assigned to Gaged Basins with Multiple Catchment Zones..............24

Evapotranspiration.............................................................................................................................24

Forest-Canopy Evaporation and Net Precipitation....................................................................24

Potential Evapotranspiration.....................................................................................................26

Reference Evapotranspiration..........................................................................................27

Crop Coefficients..............................................................................................................28

Moisture-Storage Capacity of the Plant-Root Zone...........................................................................28

Direct Recharge.................................................................................................................................29

Other Input.........................................................................................................................................30

Model Exclusions and Limitations ..............................................................................................................30

Water-Budget and Groundwater-Recharge Estimates ...............................................................................31

Water-Budget and Recharge Estimates for Average Climate Conditions..........................................31

Comparison with the Water Resources Protection Plan ...........................................................31
iv 

Comparisons with Other Relevant Studies ...............................................................................40

Recharge for Drought Conditions ......................................................................................................41

Sensitivity Analysis ............................................................................................................................41

Suggestions for Future Study and Additional Data Collection....................................................................43

Summary and Conclusions.........................................................................................................................44

References Cited........................................................................................................................................45

Figures

 1. Aquifer systems and sectors on the Island of O‘ahu, Hawai‘i ........................................................2

 2. Major towns and geographical features on the Island of O‘ahu, Hawai‘i .......................................4

 3. Mean annual rainfall for 1978–2007 and locations of rain gages used in the water-budget 

calculations, Island of O‘ahu, Hawai‘i ..........................................................................................6

 4. Generalized land cover on the Island O‘ahu during 2010..............................................................8

 5. Generalized water-budget flow diagrams for nonforest and forest land covers ........................... 11

 6. The average incremental percentage change in recharge for water-budget subareas with each 

successive model simulation .....................................................................................................15

 7. Mean runoff-to-rainfall ratios for the dry-season months and wet-season months for drainage 

basins of selected stream-gaging stations and catchment zones on the Island of 

O‘ahu, Hawai‘i............................................................................................................................19

 8. Mean annual reference evapotranspiration for the Island of O‘ahu, Hawai‘i................................27

 9. Calculated moisture-storage capacity of the plant-root zone, Island of O‘ahu, Hawai‘i ...............29

 10. The distribution of mean annual recharge for average climate conditions (1978–2007), 

calculated using the water-budget model, Island of O‛ahu, Hawai‛i...........................................37

 11. Estimated fraction of total water inflow that becomes groundwater recharge in the water-budget 

simulation for average climate conditions on the Island of O‛ahu, Hawai‘i ................................38

 12. The percentage difference in mean annual recharge for drought conditions (1998−2002) 

relative to average climate conditions, calculated using the water-budget model, Island of 

O‘ahu, Hawai‘i............................................................................................................................42

Tables

 1. Previous groundwater recharge studies for the Island of O‘ahu, Hawai‘i.......................................3

 2. General types of land cover, as a fraction of aquifer-system area, Island of O‘ahu, Hawai‘i .........9

 3. Ratios of fog interception to rainfall used in the water-budget model for the Island of O‘ahu, 

Hawai‘i .......................................................................................................................................17

 4. Mean seasonal runoff-to-rainfall ratios for drainage basins of stream-gaging stations on the 

Islands of Kaua‘i, O‘ahu, and Maui, Hawai‘i...............................................................................21

 5. Regional-regression equations used to calculate mean seasonal runoff-to-rainfall ratios for 

catchment zones in ungaged areas on the Island of O‘ahu, Hawai‘i .........................................23

 6. Land-cover parameters used in water-budget calculations for the Island of O‘ahu, Hawai‘i........26

 7. Mean annual water-budget components from this study for average climate and drought 

conditions for the Island of O‘ahu and for individual aquifer-sector areas .................................32

 8. Mean annual water-budget components from this study for average climate and drought 

conditions and components from the Water Resources Protection Plan for aquifer-system 

areas on the Island of O‘ahu, Hawai‘i ........................................................................................33

 9. Important differences between the recharge-estimation methods used in this study and the 

recharge-estimation methods used in the Water Resources Protection Plan............................39
 v

Conversion Factors

Inch/Pound to SI

Multiply By To obtain

Length

inch (in.) 2.54 centimeter (cm)

inch (in.) 25.4 millimeter (mm)

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

Area

acre 4,047 square meter (m2)

acre 0.4047 hectare (ha)

square mile (mi2) 259.0 hectare (ha)

square mile (mi2) 2.590 square kilometer (km2) 

Volume

gallon (gal) 3.785 liter (L) 

gallon (gal) 0.003785 cubic meter (m3) 

million gallons (Mgal) 3,785 cubic meter (m3)

Flow rate

million gallons per day (Mgal/d) 0.04381 cubic meter per second (m3/s)

Vertical coordinate information is referenced to mean sea level.

Horizontal coordinate information is referenced to the North American Datum of 

1983 (NAD 83).

Elevation, as used in this report, refers to distance above the vertical datum.

Acronyms

Acronyms Meaning

CWRM State of Hawaiʻi Commission on Water Resource Management

ET Evapotranspiration

TMK Tax map key

USDA U.S. Department of Agriculture

USGS U.S. Geological Survey

WRPP State of Hawaiʻi Water Resource(s) Protection Plan

 10. Comparison of water-budget components from this study with components from a previous 

study for various areas of the Island of O‛ahu, Hawai‛i..............................................................40

 11. Results of sensitivity testing for selected water-budget parameters performed for selected 

aquifer systems on the Island of O‘ahu, Hawai‘i........................................................................43
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Spatially Distributed Groundwater Recharge for 2010 Land 

Cover Estimated Using a Water-Budget Model for the Island 

of O‘ahu, Hawai‘i

By John A. Engott, Adam G. Johnson, Maoya Bassiouni, Scot K. Izuka, and Kolja Rotzoll

Abstract

Owing mainly to projected population growth, demand 

for freshwater on the Island of Oʻahu is expected to increase 

by about 26 percent between 2010 and 2030, according to 

the City and County of Honolulu. Estimates of groundwater 

recharge are needed to evaluate the availability of fresh 

groundwater. For this study, a water-budget model with a daily 

computation interval was developed and used to estimate the 

spatial distribution of recharge on Oʻahu for average climate 

conditions (1978–2007 rainfall and 2010 land cover) and 

for drought conditions (1998–2002 rainfall and 2010 land 

cover). For average climate conditions, mean annual recharge 

for Oʻahu is about 660 million gallons per day, or about 

36 percent of precipitation (rainfall and fog interception). 

Recharge for average climate conditions is about 34 percent of 

total water inflow, which consists of precipitation, irrigation, 

septic leachate, water-main leakage, and seepage from 

reservoirs and cesspools. Recharge is high along the crest of 

the Koʻolau Range, reaching as much as about 180 inches 

per year in the north-central part of the range. Recharge is 

much lower outside of the mountainous areas of the island, 

commonly less than 5 inches per year in unirrigated areas. 

The island-wide estimate of groundwater recharge for average 

climate conditions from this study is within 1 percent of 

the recharge estimate used in the 2008 State of Hawaiʻi 

Water Resource Protection Plan, which divides the Island of 

Oʻahu into 23 aquifer systems for groundwater management 

purposes. To facilitate direct comparisons with this study, 

these 23 aquifer systems were consolidated into 21 aquifer 

systems. Recharge estimates from this study are higher for 

12 of the aquifer-system areas and lower for 9. Differences in 

mean rainfall distribution and the inclusion of irrigation in this 

study are the primary reasons for discrepancies in recharge 

estimates between this study and the 2008 Hawaiʻi Water 

Resources Protection Plan. For drought conditions, mean 

annual recharge for Oʻahu is about 417 million gallons per 

day, which is about 37 percent less than recharge for average 

climate conditions. For individual aquifer-system areas, 

recharge for drought conditions is about 25 to 70 percent less 

than recharge for average climate conditions. 

 Introduction

An updated, island-wide estimate of groundwaterrecharge distribution is needed for the Island of Oʻahu, 

Hawaiʻi (fig.1) and is recommended in the State’s Water 

Resource Protection Plan (WRPP; State of Hawaiʻi, 2008). 

Published almost 20 years ago, the last island-wide estimate 

of groundwater-recharge distribution was presented in 

Shade and Nichols (1996), which relied heavily on even 

older publications that calculated water budgets for southern 

(Giambelluca, 1983) and southeastern (Eyre and others, 

1986) Oʻahu. In addition to advanced computing power 

and improved geographic information systems (GIS), 

current water-budget models for the estimation of recharge 

in the Hawaiian Islands take into account fog interception, 

canopy evaporation, and direct sources of recharge, such 

as water-main leakage and cesspool seepage (for example, 

Engott, 2011), for which no accounting was consistently 

made in water-budget models prior to the 21st century. 

Groundwater-recharge estimates can be further improved by 

using newly available rainfall and evapotranspiration (ET) 

datasets (Frazier and others, 2016; Giambelluca and others, 

2013; 2014). Estimates of recharge are used by the State 

Commission on Water Resource Management (CWRM) to 

calculate sustainable-yield values for aquifer systems on the 

island (fig. 1). Sustainable yield is defined as the maximum 

rate at which water may be withdrawn from a water source 

without impairing the utility or quality of the water source 

as determined by CWRM (State of Hawaiʻi, 2008). CWRM 

periodically reassesses sustainable yields through their update 

of the WRPP or as updated recharge values and related 

information become available. Although pumpage from 

each aquifer system on Oʻahu was generally less than the 

sustainable yield as of 2008 (State of Hawaiʻi, 2008), demand 

for groundwater is growing as population on the island 

increases. The City and County of Honolulu projects that 

freshwater demand will increase from an estimated164 million 

gallons per day (Mgal/d) in 2010 to 206 Mgal/d in 2030, an 

increase of about 26 percent (State of Hawaiʻi, 2008). This 

increased demand likely will be met by increased groundwater 

pumpage.
2 Spatially Distributed Groundwater Recharge Estimated Using a Water-Budget Model for the Island of O‘ahu, Hawai‘i

Figure 1. Aquifer systems and sectors on the Island of O‘ahu, Hawai‘i (State of Hawai‘i, 2008).

Pälolo

Nuÿuanu

Kalihi

Moanalua

Waiÿalae-West

Waiÿalae-East

Waimalu

Waipahu-Waiawa

ÿEwa-Kunia

Makaïwa

Nänäkuli

Lualualei

Waiÿanae

Mäkaha

Keaÿau

Mokulëÿia

Waialua

Kawailoa

Wahiawä

Koÿolauloa

Kahana

Koÿolaupoko

Waimänalo

ÿEWA CAPROCK

(shaded)

0-ft elevation contour 

of top of volcanic-rock

aquifer

Figure 1. Aquifer systems and sectors on the Island of O‘ahu, Hawai‘i (State of Hawai‘i, 2008).

WAIÿANAE 

AQUIFER 

SECTOR

NORTH

AQUIFER 

SECTOR

WINDWARD

AQUIFER 

SECTOR

HONOLULU

AQUIFER 

SECTOR

PEARL HARBOR

AQUIFER 

SECTOR

CENTRAL

AQUIFER 

SECTOR

22 ̊

20 ̊

160 ̊ 158 ̊ 156 ̊

Kaua‘i

Ni‘ihau

O‘ahu

Maui

Moloka‘i

Lāna‘i

Kaho‘olawe

Hawai‘i

HAWAI‘I

Pacific Ocean

158°

158°10’

157°40’

157°50’

21°30’

21°20’

21°40’

0 5 10 MILES

0 5 10 KILOMETERS

Base modified from U.S. Geological Survey 

National Hydrography Dataset, 1:24,000,

Universal Transverse Mercator projection, 

zone 4, NAD83 datum. 
Description of O‘ahu Description of O‘ahu 3

Table 1. Previous groundwater recharge studies for the Island of 

O‘ahu, Hawai‘i.

Reference Area

Safeeq and Fares (2012a) Mākaha area

Shade and Nichols (1996) Entire island

State of Hawai‘i (1990) Entire island

Eyre and others (1986) Southeastern Oʻahu

Giambelluca (1983; 1986) Southern Oʻahu

Broadbent (1980) Central Oʻahu

Mink (1980) Southern Oʻahu

Mink (1978) Waiʻanae area

Takasaki (1971) Waiʻanae area

Takasaki and others (1969) Windward Oʻahu

Takasaki and Valenciano (1969) Kahuku area

Dale (1967) Pearl Harbor area

Wentworth (1951) Southern Oʻahu

Purpose and Scope

The purpose of this report is to quantify the spatial 

distribution of mean annual groundwater recharge for the Island 

of Oʻahu. To estimate recharge, a water-budget model that 

uses a daily computational interval is developed. Hydrological 

processes and physical conditions that affect recharge on Oʻahu 

are simulated in the water-budget model using the most current 

data available, including maps of rainfall for each month during 

1978–2007 and mean monthly reference grass ET (Frazier and 

others, 2016; Giambelluca and others, 2013; 2014). The spatial 

distribution of mean annual recharge is estimated for two scenarios 

(1) mean climate conditions (1978–2007 rainfall and 2010 land 

cover), and (2) drought conditions (1998–2002 rainfall and 2010 

land cover). Recharge estimates from this study are compared with 

estimates of mean recharge from previous water-budget studies. 

Finally, the sensitivity of recharge estimates to selected waterbudget components is evaluated. 

Previous Studies

A number of previous studies have estimated groundwater 

recharge for various parts of Oʻahu, with the focus being 

primarily on southern Oʻahu and the Pearl Harbor area (table 1). 

Giambelluca (1983) used a highly detailed water-budget approach 

to estimate recharge for southern Oʻahu. Two groundbreaking 

aspects of that study were (1) a daily computational interval 

was used by estimating representative patterns of normalized 

daily rainfall and irrigation distributions, and disaggregating 

mean monthly data accordingly; and (2) spatial variation in 

rainfall and ET was captured by breaking up the study area into 

smaller zones. Shade and Nichols (1996) mostly used regression 

models developed from the results of Giambelluca (1983) to 

estimate recharge for other parts of Oʻahu for predevelopment 

and mid-1980s conditions. Other studies used water budgets 

with monthly or annual computational intervals, which can lead 

to biased recharge estimates (Giambelluca and Oki, 1987; Oki, 

2008). In general, uncertainty in recharge estimates is less for 

water budgets calculated using the shortest computational interval 

that is consistent with the physical processes being represented 

(Oki, 2008). The 1990 WRPP (State of Hawaiʻi, 1990) used a 

water budget with an annual time step to estimate recharge for 

each aquifer-system on Oʻahu (fig. 1) and the other main Hawaiian 

Islands. The water budget for this study uses a daily computational 

interval, which provides a more realistic simulation of rainfall, 

soil moisture, ET, and recharge. Comparisons of the results of this 

study with previous studies of recharge on Oʻahu generally are 

confounded by differences in study periods and areas.

Acknowledgments

This study was conducted in cooperation with the State 

of Hawaiʻi Commission on Water Resource Management. 

The authors thank Abby Frazier and Thomas Giambelluca 

of the University of Hawaiʻi at Mānoa; Roy Hardy, 

Lenore Ohye, and Jeremy Kimura of the State of Hawaiʻi 

Commission on Water Resource Management; and Carolyn 

Sawai of the Honolulu Board of Water Supply for providing 

data and information for this report.

Description of O‘ahu 

The Island of Oʻahu has an area of about 596 square 

miles. Oʻahu is the third largest of the Hawaiian Islands 

and the most populous, with an estimated population of 

983,429 in 2013 (State of Hawaiʻi, 2014). Oʻahu is the center 

of commerce, industry, and government in Hawaiʻi and 

is the site of the State capital, Honolulu. For groundwater 

management purposes, CWRM divides the Island of Oʻahu 

into 6 aquifer sectors and 23 aquifer systems (fig. 1). 

Physical Setting

Oʻahu is formed by the eroded remnants of two 

elongated shield volcanoes with broad, low profiles. 

Weathering and erosion have modified the original domed 

surfaces of the volcanoes, leaving a landscape of deep 

valleys and steep inter-fluvial ridges in the interior highlands. 

The Koʻolau Range in eastern Oʻahu and the Waiʻanae 

Range in western Oʻahu (fig. 2) are the eroded remnants 

of the Koʻolau and Waiʻanae Volcanoes. In central Oʻahu, 

which forms the saddle between the Koʻolau and Waiʻanae 

Ranges, erosion has been less severe and has only slightly 

modified the original domes. A flat coastal plain composed 

of sedimentary deposits, locally referred to as caprock, 

surrounds much of Oʻahu. The caprock varies in width from 

a narrow marine terrace to a broad plain several miles wide.
4 Spatially Distributed Groundwater Recharge Estimated Using a Water-Budget Model for the Island of O‘ahu, Hawai‘i

2,000

3,000

1,000

2,000

1,000

2,000

1,000

Kahuku

Läÿie

Käneÿohe Kailua

Waimänalo

Hawaiÿi Kai

HONOLULU

Pearl City

ÿAiea

Waipahu

ÿEwa Beach

Nänäkuli

Waiÿanae

Mäkaha

Waialua

Haleÿiwa

Wahiawa

Mililani

ÿE W A P L A I N

K o ÿ o l a u 

R a n g e

R a n g e

W a i ÿ a n a e x

x

Mt. Kaÿala

(4,025 feet) 

Puÿu Könähuanui

(3,105 feet)

Käneÿohe

Bay

Pearl Harbor

Mämala Bay

Maunalua Bay

Waimänalo 

Bay

Diamond

Head

Makapuÿu

Point

Barbers Point

Kaÿena

Point

Kahuku Point

Sand 

Island

Ford

Island

Base modified from U.S. Geological Survey 

National Hydrography Dataset, 1:24,000,

Universal Transverse Mercator projection, 

zone 4, NAD83 datum. Shaded relief from 

U.S. Geological Survey 10-meter digital

elevation data.

Figure 2. Major towns and geographical features on the Island of O‘ahu, Hawai‘i. Red lines are elevation contours

with a 1,000-ft interval.

CONTOUR INTERVAL IS 1,000 FEET

VERTICAL DATUM IS LOCAL MEAN SEA LEVEL

PREVAILING

WIND

DIRECTION

158°

158°10’

157°40’

157°50’

21°30’

21°20’

21°40’

0 5 10 MILES

0 5 10 KILOMETERS

Figure 2. Major towns and geographical features on the Island of O‘ahu, Hawai‘i. Red lines are elevation contours with a 1,000-ft interval.
Description of O‘ahu 5

Climate

Weather patterns in Hawaiʻi are affected by the interaction 

between northeast trade winds and the topography of the 

Hawaiian Islands (Schroeder, 1993). The Hawaiian Islands 

are in the path of persistent trade winds that originate from the 

north Pacific anticyclone, which is a region of high atmospheric 

pressure usually located northeast of the Islands. Mountains of the 

Hawaiian Islands obstruct trade-wind airflow and create wetter 

climates on northeast-facing (windward) mountain slopes and 

drier climates on southwest-facing (leeward) mountain slopes 

(Sanderson, 1993). As moist air ascends windward mountain 

slopes, it cools adiabatically and can form clouds. Persistent trade 

winds and orographic lifting of moist air result in recurrent clouds 

and frequent rainfall on windward slopes and near the peaks of all 

but the tallest mountains of the Hawaiian Islands (Giambelluca 

and others, 1986). Loss of moisture from air that ascends 

windward slopes leads to relatively drier climates along leeward 

slopes in the rain shadow of the mountains. 

When trade winds are present, the vertical development 

of clouds is restricted by the trade-wind inversion layer. Within 

the trade-wind inversion layer air temperature increases with 

elevation, whereas the air temperature in regions above and below 

the inversion layer generally decreases with elevation (Schroeder, 

1993). Cao and others (2007) determined the trade-wind inversion 

layer occurs overall about 82 percent of the time in Hawaiʻi and 

has an average base elevation of about 7,100 ft. The elevation of 

the inversion, however, varies over time and space and is affected 

by thermal circulation patterns, such as land and sea breezes 

(Giambelluca and Nullet, 1991). With a maximum elevation of 

4,025 ft (fig. 1), most of Oʻahu is usually immersed in the moist air 

layer below the inversion. 

The variability of weather and rainfall patterns in Hawaiʻi 

during the year is typically described in terms of dry and wet 

seasons. The dry season (May through September) has warm 

temperatures and steady trade winds that blow 80 to 95 percent 

of the time (Blumenstock and Price, 1967; Sanderson, 1993). 

The wet season (October through April) has cooler temperatures 

and less persistent trade winds. Statewide storm rainfall is more 

common during the wet season when low-pressure and frontal 

systems pass near the Islands (Giambelluca and others, 1986). 

Much of the rainfall on leeward sides of the Hawaiian Islands 

comes from these synoptic-scale systems (Schroeder, 1993). 

Low-pressure systems that develop to the west of the Hawaiian 

Islands can result in moist, southerly winds and rainfall that may 

persist for more than a week (Schroeder, 1993). During the early 

part of 2006, for example, a series of low-pressure systems to the 

west of the Hawaiian Islands persisted for nearly seven weeks 

and generated an onslaught of storms that resulted in an unusual 

extended rainy period across the Islands (Nash and others, 2006).

Steep gradients in mean annual rainfall patterns on Oʻahu 

reflect the influence of persistent trade winds and orographic 

rainfall (fig. 3; Giambelluca and others, 2013). Mean rainfall is 

highest—about 280 in/yr—along the north-central crest of the 

Koʻolau Range (figs. 2 and 3), and lowest—about 20 in/yr near 

the southwestern coast of the island. Only about 17 miles separate 

these two locations. The Waiʻanae Range, although generally 

taller than the Koʻolau Range, receives considerably less rainfall 

because it mostly lies in the rain shadow of the Koʻolau Range. 

The highest point in the Waiʻanae Range and on the island, Mt. 

Kaʻala, has a mean rainfall of about 79 in/yr. The central saddle of 

Oʻahu receives about 30 to 40 in/yr of rainfall on average.

Hydrogeology

Oʻahu is primarily formed by layers of shield-stage 

lava flows from the older Waiʻanae Volcano to the west and 

the younger Koʻolau Volcano to the east, and secondarily 

by preshield-, postshield-, and rejuvenated-stage volcanism 

(Langenheim and Clague, 1987). Each volcano has two primary 

rift zones and a third lesser rift zone, all emanating from a 

collapsed caldera. The layers of lava flows are intruded in 

places by dikes, which consist of dense, low-permeability rock 

that formed when magma supplying lava flows solidified in 

narrow, near-vertical fissures below the ground surface. The 

dikes and the rocks they intrude are collectively referred to as 

dike complexes. In the central part of a rift zone, there can be as 

many as 1,000 dikes per mile of horizontal distance across the 

zone (Takasaki and Mink, 1985). The number of dikes decreases 

toward the outer edges of a rift zone. Deposits of terrestrial 

and marine sediments and reef limestone form a coastal plain 

of varying width along the shore of Oʻahu. The coastal plain 

extends more than 5 mi inland near Pearl Harbor. The onshore 

thickness of the coastal deposits generally is greatest at the 

coast and thins in an inland direction (Palmer, 1927; Palmer, 

1946; Wentworth, 1951; Visher and Mink, 1964; Dale, 1978). 

The sedimentary wedge is more than 1,000-ft thick along the 

southern coast near the entrance to Pearl Harbor. 

Within the dike-free flank lavas, fresh groundwater occurs 

in a lens-shaped body underlain by saltwater from the ocean. 

Between this freshwater lens and the underlying saltwater is a 

zone of mixing containing brackish water. Natural discharge from 

the freshwater-lens system generally occurs as diffuse seepage 

near the coast.

The permeability of volcanic rocks varies and depends on 

the type (lava flows, intrusive dikes, or pyroclastic deposits), 

amount of weathering, and the thickness of the rocks. The 

permeability of the subaerial, shield-building, dike-free lava flows 

on Oʻahu is generally high. The regional horizontal hydraulic 

conductivity of the dike-free volcanic rocks typically ranges 

from hundreds to thousands of feet per day (Soroos, 1973; Mink 

and Lau, 1980; Hunt, 1996). Because of the high permeability 

of the dike-free volcanic rocks, horizontal water-table gradients 

in these rocks are small (on the order of 1 ft/mi). In general, 

the vertical hydraulic conductivity of the dike-free lava flows 

may be hundreds of times less than the horizontal hydraulic 

conductivity. On the basis of a numerical-model analysis of the 

Pearl Harbor area, Souza and Voss (1987) estimated the ratio of 

horizontal to vertical hydraulic conductivity to be 200 to 1. Dikes 

that intrude the lava flows impede the flow of groundwater and 

reduce the overall permeability of the aquifer. Estimated bulk 

hydraulic conductivity of dike complexes can be several orders 
6 Spatially Distributed Groundwater Recharge Estimated Using a Water-Budget Model for the Island of O‘ahu, Hawai‘i

Figure 3. Mean annual rainfall for 1978–2007 (modified from Giambelluca and others, 2013) and locations of rain gages used in the water-budget 

calculations, Island of O‘ahu, Hawai‘i.

912 907 911

903

892

885

880

863

855

847

841

833

804

798

784 794

783

781

777

773

772

770

750

741

718

717

715

709

904.1

897.9

892.2

882.4 886.4

874.3

842.1

838.1

837.5

832.2 796.1

791.3

788.1 764.6

723.4

717.2

712.1

702.5

702.2

f

f

f

f

f

f

f

f f

f

f

f

f

f f

f

f

f

f

f

f

f

f

f f

f

f

f

f

f

f

f

f

f

f

f

f

f

f

f

f

f

f

f

f

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f

25

35

220

200

180 160

140

120

100

80

65

50

240

260

120

25

140

35

50

65

EXPLANATION

Thiessen polygon

Line of equal rainfall—

Number is mean annual rainfall, 

in inches, interval varies

Rain gage— Number is 

State Key Number

200

f

Figure 3. 1978–2007 mean annual rainfall (modified from Giambelluca and others, 2013) and locations of rain 

gages used in the water-budget calculations, Island of O‘ahu, Hawai‘i.

158°

158°10’

157°40’

157°50’

21°30’

21°20’

21°40’

0 5 10 MILES

0 5 10 KILOMETERS

Base modified from U.S. Geological Survey 

National Hydrography Dataset, 1:24,000,

Universal Transverse Mercator projection, 

zone 4, NAD83 datum. 
Description of O‘ahu 7

of magnitude lower than that of dike-free flank lavas (Oki, 1999). 

Other rocks and structures, such as ash layers, soil and weathered 

rock, unusually thick lava flows, and lava-draped faults, may 

also form low-permeability features within the otherwise highpermeability lavas of the shield volcano (Stearns and Macdonald, 

1946; Oki, 1999). These low-permeability features can increase 

the thickness of the freshwater lens on the upgradient side of the 

feature. In dike complexes, highly permeable volcanic rocks can 

be compartmentalized and groundwater impounded (Stearns and 

Macdonald, 1946). Groundwater levels in parts of the rift zone of 

the Koʻolau Volcano may be as high as 1,000 ft above sea level. 

The sedimentary deposits and underlying weathered volcanic 

rocks of the coastal plain form a low-permeability confining 

unit, called caprock, that overlies high-permeability volcanic 

rocks and impedes the seaward discharge of freshwater from the 

volcanic-rock aquifers. Although the permeability of the various 

components of the coastal caprock may vary widely, from lowpermeability older alluvium and saprolite to cavernous limestone 

deposits with a hydraulic conductivity of thousands of feet per day, 

the overall effect of the caprock is one of low permeability (Visher 

and Mink, 1964), increasing the thickness of the freshwater lens in 

the volcanic-rock aquifer upgradient of the caprock.

Surface Water

Streams on Oʻahu are short, with steep gradients and 

small drainage areas. Main courses of streams generally 

follow the consequent drainage pattern established on the 

original domed surfaces of the shield volcanoes. Lower-order 

tributaries branch off from the main courses in a dendritic 

pattern. Steep terrain and steep stream gradients cause 

water to run off rapidly following precipitation. As a result, 

streamflow is characteristically flashy, with high flood peaks. 

Few streams are perennial over their entire reach. Streamflow 

is perennial at (1) high elevations where precipitation is 

persistent and streams intercept dike-impounded or perched 

groundwater, and (2) near sea level where streams intercept 

shallow groundwater. These conditions limit surfacewater development on Oʻahu and lead to heavy reliance on 

groundwater for potable supply.

Soils

Factors influencing soil conditions in the Hawaiian 

Islands include parent material, duration of weathering, 

climate, topography, and drainage conditions (Macdonald 

and others, 1983). The ability of a particular soil to absorb 

and store water affects direct runoff, evapotranspiration, 

and recharge. Properties of a soil that control its ability to 

absorb and store water include (1) soil texture, the relative 

percentages of sand-, silt-, and clay-sized particles, (2) 

porosity, a measure of how much water a soil can hold, and 

(3) permeability, a measure of a soil’s ability to transmit water. 

Slope, vegetation, and soil-moisture content can also affect a 

soil’s ability to absorb water. 

The U.S. Department of Agriculture (USDA) produced a 

map of soils on Oʻahu (USDA, 2006a) that classifies the soils 

and land into 160 soil-map units. Soil properties were estimated 

to depths of 60 inches for most soils. Estimates of available water 

capacity, the quantity of water that a soil is capable of storing for 

use by plants, range between 0 and 0.40 inches of water per inch 

of soil. Areas containing soil horizons with reported zero available 

water capacity in the top 40 inches of soil include the steep slopes 

of the windward Koʻolau Range and the steep upper valleys of 

the Waiʻanae Range. In general, soil horizons with zero available 

water capacity are associated with bedrock. Steep slopes may have 

thin soils overlying bedrock owing to erosion removing soil as fast 

as it forms (Macdonald and others, 1983). 

Land Cover

Patterns of existing vegetation and land cover on Oʻahu 

reflect the influence of steep climate gradients, decreasing 

agricultural production, and urban development. Approximately 

43 percent of Oʻahu is covered by forests (table 2; U.S. Geological 

Survey, 2010). Large tracts of forest, generally dominated by the 

native canopy species Metrosideros polymorpha (ʻōhiʻa lehua), 

exist in the wetter, high-elevation areas of the Koʻolau Range, with 

shrubland and grassland in the drier lower elevation areas (fig. 4). 

Fern species such as Dicranopteris linearis (uluhe) dominate wet, 

windward ridges. Small wetlands exist in some of the flat summits 

of old volcanic craters, such as Mt. Kaʻala.

During the 1800s, demand for firewood, commercial logging, 

agricultural and pasture land conversion, effects of grazing and 

browsing ungulates, and increased fire frequency resulted in a 

substantial forest decline on all Hawaiian Islands (Woodcock, 

2003). As a result, forest reserves were established in the early 

1900s and millions of alien trees were planted by the 1930s. These 

dramatic changes in land cover may have affected groundwater 

recharge and base flow (Bassiouni and Oki, 2013). Today (2014), 

alien forest covers large areas at the middle and low elevations of 

the Koʻolau Range and nearly the entirety of the Waiʻanae Range, 

and invasive species continue to replace native forests in many 

areas. 

During most of the 20th century, the gently sloping lands 

of central Oʻahu between the Waiʻanae and Koʻolau Ranges 

and the ʻEwa Plain (fig. 2) were dominated by sugarcane and 

pineapple fields and irrigated by large stream diversions and 

pumped groundwater. The demise of the sugarcane industry 

began in the 1980s, and was complete by 1995. Pineapple has 

been continually cultivated in central Oʻahu since the late 19th 

century, although to a far lesser degree today than previously. 

Former sugarcane and pineapple lands that have not converted 

to diversified agriculture or been developed have become 

dominated by mostly alien grassland. About 29 percent of 

Oʻahu is urban development (table 2; U.S. Geological Survey, 

2010), with major concentrations occurring in the Honolulu, 

Pearl Harbor, and Kāneʻohe/Kailua areas. Since about 1980 

and coinciding with the demise of the sugarcane and pineapple 

industries, new urban development generally has been focused 

on the ʻEwa Plain and in central Oʻahu.
8 Spatially Distributed Groundwater Recharge Estimated Using a Water-Budget Model for the Island of O‘ahu, Hawai‘i

Figure 4. Generalized land cover on the Island O‘ahu during 2010 (modified from U.S. Geological Survey, 2010). Reservoirs and taro are difficult to 

see at this scale. 

Shrubland 

LAND COVER

High-intensity developed

Golf course 

Pineapple 

Diversified agriculture 

Taro 

Coffee 

Low-intensity developed

Kiawe/phreatophytes

Grassland 

Native forest 

Sparsely vegetated 

Water body 

Wetland 

Tree plantation 

Alien forest

UNIRRIGATED IRRIGATED 

Medium-intensity developed 

Corn

Figure 4. Generalized land cover on the Island of O‘ahu during 2010 (modified from U.S. Geological Survey, 2010). 

Reservoirs and taro are difficult to see at this scale.

base of fog zone (2,000 ft)

(white line)

158°

158°10’

157°40’

157°50’

21°30’

21°20’

21°40’

0 5 10 MILES

0 5 10 KILOMETERS

Base modified from U.S. Geological Survey 

National Hydrography Dataset, 1:24,000,

Universal Transverse Mercator projection, 

zone 4, NAD83 datum. 
Water-Budget Model 9

[See fig. 1 for location of aquifer systems. See figure 4 for a map of land cover. Agriculture–irrigated consists of coffee, corn, diversified agriculture, pineapple, 

and taro land covers; Alien forest includes kiawe/phreatophytes and tree plantation; Other consists of sparsely vegetated, reservoir, water body, near-coastal or 

estuarine water body, and wetland land covers]

Table 2. General types of land cover, as a fraction of aquifer-system area, Island of O‘ahu, Hawai‘i.

Aquifer system Agriculture– 

irrigated

Developed 

and 

golf course

Grassland Shrubland Alien forest Native 

forest Other

Pālolo 0.00 0.63 0.01 0.05 0.14 0.14 0.03

Nuʻuanu 0.00 0.54 0.00 0.01 0.26 0.17 0.01

Kalihi 0.00 0.50 0.00 0.02 0.32 0.17 0.00

Moanalua 0.00 0.58 0.00 0.04 0.20 0.16 0.01

Waiʻalae-West 0.00 0.46 0.02 0.04 0.27 0.20 0.01

Waiʻalae-East 0.00 0.37 0.05 0.20 0.29 0.08 0.01

Waimalu 0.00 0.36 0.01 0.05 0.22 0.36 0.01

Waipahu-Waiawa 0.11 0.37 0.07 0.08 0.19 0.17 0.01

ʻEwa-Kunia 0.05 0.30 0.19 0.16 0.27 0.00 0.02

Makaīwa 0.00 0.22 0.37 0.22 0.11 0.00 0.07

Nānākuli 0.00 0.17 0.33 0.20 0.30 0.00 0.00

Lualualei 0.02 0.35 0.11 0.23 0.27 0.00 0.02

Waiʻanae 0.01 0.23 0.17 0.29 0.28 0.01 0.01

Mākaha 0.00 0.21 0.11 0.27 0.37 0.02 0.02

Keaʻau 0.00 0.05 0.41 0.19 0.33 0.00 0.02

Mokulēʻia 0.08 0.11 0.06 0.24 0.48 0.03 0.01

Waialua 0.23 0.18 0.24 0.14 0.15 0.05 0.01

Kawailoa 0.05 0.14 0.06 0.15 0.39 0.20 0.01

Wahiawā 0.03 0.17 0.15 0.06 0.27 0.31 0.01

Koʻolauloa 0.06 0.16 0.01 0.22 0.30 0.23 0.01

Kahana 0.00 0.10 0.01 0.16 0.42 0.30 0.02

Koʻolaupoko 0.00 0.35 0.01 0.10 0.30 0.22 0.01

Waimānalo 0.01 0.44 0.01 0.16 0.21 0.10 0.06

Island of Oʻahu

(all aquifer systems) 0.04 0.29 0.08 0.13 0.27 0.16 0.02

Water-Budget Model

Groundwater recharge replenishes aquifers and is 

mainly fed by precipitation and irrigation that infiltrates 

the ground surface and percolates beyond the root zone in 

the soil. For this study, spatially distributed mean annual 

groundwater recharge on Oʻahu is estimated using a waterbudget model. The water-budget model is designed to 

simulate—on a daily basis—the hydrological processes 

and physical conditions that affect recharge on Oʻahu. 

Hydrological processes simulated by the model include 

rainfall, fog interception, irrigation, direct runoff, and ET. 

Physical conditions are represented using parameters that 

include the moisture-storage capacity of soils and properties 

of the vegetation and land cover that affect ET. 

The water-budget model used for this study is a 

modified version of the models used for previous U.S. 

Geological Survey (USGS) recharge studies for various 

parts of Hawaiʻi (Oki, 2002; Izuka and others, 2005; Engott 

and Vana, 2007; Engott, 2011; Gingerich and Engott, 

2012). The structure of the model used for this study is 

similar to that of the earlier models. The model used for 

this study differs from previous versions of the model 

by covering the entire Island of Oʻahu, and using more 

current maps of rainfall, land cover, and reference grass ET. 

Additionally, the model used for this study includes more 

robust methods for (1) using streamflow records to estimate 

the spatial distribution of direct runoff, and (2) quantifying 

precipitation that is intercepted by, and evaporates from, 

forest canopies.

The water-budget model used for this study is similar 

to other models that simulate a root-zone water balance and 

can be used to estimate recharge (for example, Leavesley 

and others, 1983; Hevesi and others, 2002; Westenbroek 

and others, 2010). However, for this study, the preferred 

approach is to build on previous water-budget models 
10 Spatially Distributed Groundwater Recharge Estimated Using a Water-Budget Model for the Island of O‘ahu, Hawai‘i

developed by USGS for the State of Hawaiʻi because (1) 

these models are better adapted to conditions unique to 

Oʻahu, such as a persistent fog and cloud cover for many 

locations and a pronounced orographic influence on climate, 

and (2) a high degree of spatial detail is needed for defining 

the model subareas. The high degree of spatial detail allows 

the model to represent the wide range of climate conditions, 

vegetation, soils, and land uses on Oʻahu.

Conceptual Model 

The water-budget model used here to estimate 

groundwater recharge is a “threshold-type” or “reservoir” 

model utilizing a variation of the Thornthwaite and Mather 

(1955) mass-balance procedure. The two generalized flow 

diagrams of the water-budget model—one for nonforest land 

covers and one for forest land covers are shown in figure 5. 

The plant-root zone reservoir is included in the model for 

nonforest and forest land covers. The forest-canopy reservoir 

is included in the model for forest land covers only. 

The volume of the plant-root zone reservoir is based 

on the estimated root depth of different plant types and 

the available water capacity of different soil types. Water 

entering, leaving, and being stored within the plant-root 

zone reservoir is accounted for using a daily computational 

interval. At the end of a day, if the volume of water entering 

the system exceeds the storage capacity of the plant-root 

zone reservoir, given the antecedent water content and water 

losses from ET, the reservoir overflows. This overflow is 

counted as groundwater recharge by the model. In some 

areas, recharge includes direct recharge from reservoir and 

cesspool seepage. All water infiltrating the substrate beneath 

the plant-root zone reservoir as overflow or direct recharge 

is considered recharge. 

Direct runoff is the fraction of precipitation (rainfall 

and fog interception) that does not contribute to net 

moisture gain within the plant-root zone reservoir. Direct 

runoff excludes base flow, which is groundwater discharge 

to streams. Direct runoff is assumed to either be diverted 

to other areas or ultimately discharged to the ocean. 

Re-infiltration of direct runoff is not quantified in the model, 

although it is indirectly accounted for in the empirical 

functions used to calculate direct runoff. 

Unlike the plant-root zone reservoir, precipitation 

is not allowed to be stored in the forest-canopy reservoir 

for more than a day. For each daily computational period, 

precipitation in the forest-canopy reservoir either evaporates 

as canopy evaporation or reaches the soil as part of net 

precipitation. Net precipitation is calculated as the sum of 

fog interception and rainfall minus canopy evaporation, and 

thus represents outflow from the forest-canopy reservoir. 

Net precipitation is partitioned into direct runoff and inflow 

to the plant-root zone. The plant-root zone reservoir and the 

forest-canopy reservoir are herein referred to as the plantroot zone and the forest canopy, respectively.

Model Calculations 

Groundwater recharge for the Island of Oʻahu is 

calculated using the water-budget model and input data that 

quantify the spatial and temporal distributions of rainfall, 

fog interception, irrigation, ET, direct runoff, soil type, land 

cover, and seepage from reservoirs and septic systems. For 

the model calculations, the Island of Oʻahu is subdivided 

into small areas with homogeneous properties, termed 

subareas. A map of subareas is generated using Esri ArcGIS 

software (www.esri.com) by intersecting (merging) spatial 

datasets that characterize the spatial distribution of rainfall, 

fog, irrigation, reference ET, runoff, soil type, and land 

cover. Intersecting the spatial datasets resulted in 387,533 

subareas—with an average area of about 1.0 acres—for the 

Oʻahu water-budget model.

Each subarea is treated independently by the waterbudget model. Water transfers between subareas are not 

included in the model calculations. The model domain of 

each subarea extends vertically from the vegetation canopy 

to the base of the plant-root zone, the part of the soil 

and bedrock containing roots. Properties of the substrate 

beneath the plant-root zone are not included in the model 

calculations.

For each subarea, the water-budget model calculates 

recharge on a daily basis for the period of the scenario. 

This study considers two scenarios, one for average climate 

conditions and one for drought conditions. Mean annual 

recharge for each scenario is determined for each subarea. 

Mean annual recharge for subareas is also summed over 

larger areas of interest, including Oʻahu’s 23 aquifer systems.

For each subarea, the model calculates an interim 

moisture storage at the start of each day. Interim moisture 

storage is the amount of water that enters the plant-root zone 

for the current day plus the amount of water already in the 

plant-root zone from the previous day. For the first day of 

the simulation, a value for the amount of water already in the 

plant-root zone from the previous day (initial soil moisture) 

must be assigned. For subareas with nonforest land covers, 

interim moisture storage, Xi, is given by the equation 

Xi = Ri + Fi –Ui + Ii + Li + Wi + Mi-1, (1a)

where

 Xi = interim moisture storage for current day [L],

 Ri = rainfall for current day [L], 

 Fi = fog interception for current day [L], 

 Ui = direct runoff for current day [L],

 Ii = irrigation for current day [L], 

 Li = septic-system leachate for current day [L],

 Wi = excess water from the impervious fraction of 

the subarea distributed over the pervious 

fraction of the subarea [L],

 Mi-1 = moisture storage at the end of the previous 

day (i-1) [L], and

 i = subscript designating current day.
Water-Budget Model 11

Figure 5. Generalized water-budget flow diagrams for nonforest and forest land covers. Figure 5. Generalized water-budget flow diagrams for nonforest and forest land covers.

PLANT-ROOT ZONE RESERVOIR

FOR NONFOREST LAND COVERS:

Total

Evapotranspiration

Irrigation Fog

Interception Rainfall

Groundwater 

Recharge

Direct 

Runoff

Direct

Recharge

Septic-System

Leachate

PLANT-ROOT ZONE RESERVOIR

FOREST-CANOPY RESERVOIR

FOR FOREST LAND COVERS:

(modified from McJannet and others, 2007)

Canopy 

Evaporation

Groundwater 

Recharge

Direct

Runoff

Total

Evapotranspiration

Transpiration Ground 

Evaporation

Net

Precipitation

Rainfall

Fog 

Interception

Septic-System 

Leachate

Direct

Recharge
12 Spatially Distributed Groundwater Recharge Estimated Using a Water-Budget Model for the Island of O‘ahu, Hawai‘i

For subareas with forest land covers, interim moisture storage 

is given by the equation 

 Xi = (NP)i – Ui + Li + Wi + Mi-1,  (1b)

where

 (NP)i = net precipitation for current day [L]. 

For subareas with forest land covers, net precipitation 

is calculated as precipitation minus canopy evaporation, 

which is the amount of precipitation that is intercepted by 

and evaporates from the leaves, stems, and trunks of a forest. 

Precipitation is the sum of rainfall and fog interception:

 Pi = Ri + Fi (2)

where

 

 Pi = precipitation for current day [L].

Net precipitation is calculated as:

 (NP)i = Pi – (CE)i, (3)

where

 (CE)i = forest-canopy evaporation for current 

 day [L]. 

Forest-canopy evaporation is calculated in the waterbudget model using an approach that is derived from the 

rainfall-interception model described by Gash and others 

(1995), herein referred to as the Gash model. Using this 

approach, canopy evaporation for a given day and location 

depends on precipitation amount, forest structure, and mean 

rates of evaporation and precipitation. The Gash model was 

modified for this study so that (1) precipitation includes 

rainfall and fog interception, instead of rain only, and (2) water 

cannot be stored on the forest canopy for more than a day. 

The forest structure is characterized in terms of canopy cover, 

canopy capacity, trunk-storage capacity, and the proportion 

of precipitation diverted to stemflow. Canopy cover, c, is 

the fraction of a forested subarea that is covered by leaves, 

stems, and branches of trees. Canopy capacity, S, is the depth 

of water left on the canopy when rainfall and throughfall 

have ceased (Gash and Morton, 1978). Evaporation of water 

from tree trunks is accounted for using the proportion of 

precipitation that is diverted to stemflow, p, and trunk-storage 

capacity, k, which is considered in terms of an equivalent 

depth of precipitation. The last parameter needed for the Gash 

model is the ratio of the mean evaporation rate to the mean 

precipitation rate during saturated conditions, V.

To calculate forest-canopy evaporation, the first step is 

to determine the minimum depth of precipitation necessary to 

saturate the forest canopy, P’ (Gash and others, 1995). On the 

basis of equation 2 in Gash and others (1995), P’ for subareas 

with forest land covers is calculated as 

P’ = –{S ÷ (c × V)} × ln (1 – V). (4)

where

P’ = precipitation necessary to saturate the 

canopy [L],

 S  = canopy capacity per unit of ground area 

[L] (a constant),

 c  = canopy cover per unit of ground area 

[dimensionless], and

V  = ratio of mean evaporation rate to 

mean precipitation rate during saturated 

conditions [dimensionless].

On the basis of the revised analytical form of the Gash 

model presented in table 1 of Gash and others (1995), forestcanopy evaporation for a given day, (CE)i

, is calculated for 

three canopy conditions as follows: 

for Pi < P’, 

 (CE)i = c × Pi , 

 

for Pi ≥ P’ and Pi ≤ k ÷ p,

 (CE)i = c × P’+ c × V × (Pi – P’) + p × Pi ,

for Pi ≥ P’ and Pi > k ÷ p,

 (CE)i = c × P’ + c × V × (Pi – P’) + k, (5)

where

 

k = trunk-storage capacity [L] (a constant), and 

 p = proportion of precipitation diverted to 

stemflow [dimensionless].

For each subarea with impervious surfaces, such as paved 

roads and buildings, the interim moisture-storage equations 

include the factor Wi (see equations 1a and 1b), which is a function 

of the fraction of the subarea that is impervious. For subareas with 

no impervious surfaces, Wi is zero. The fraction of the subarea 

that is impervious, z, is used to separate, from the total rain that 

falls in a subarea, a depth of water that is treated computationally 

as though it fell on an impervious surface. Based on the rainfallretention capacity of the impervious surface, some water is 

subtracted to account for direct evaporation. The remaining water 

is considered excess water, Wi. For subareas without storm-drain 

systems, Wi is added to the water budget of the pervious fraction 

of the model subarea. In this case, the total daily water input for 

the pervious fraction of a subarea includes excess water from 

the impervious fraction (equations 1a and 1b). For subareas with 
Water-Budget Model 13

storm-drain systems, Wi is assumed to be collected by storm-drain 

systems and is added to runoff or to direct recharge, depending on 

location. 

For subareas with impervious surfaces, excess water, Wi, 

is determined using the following conditions:

 X1i = Pi – Ui + Ti-1, (6)

for X1i ≤ N , 

Wi = 0, and X2i = X1i,

for X1i > N , 

 Wi = (X1i – N) × z ÷ (1 – z), and X2i = N, (7)

where

X1i = first interim moisture storage on the 

 surface of impervious area for 

 current day [L],

X2i = second interim moisture storage on the 

 surface of impervious area for current 

 day [L],

Ti–1 = water storage (ponded water) on the 

 surface of impervious area at the end 

 of the previous day (i –1) [L], 

N = rainfall-retention capacity of 

 the impervious surface (maximum 

 amount of water storage on the surface 

 of impervious area) [L], and 

z = fraction of area that is impervious 

 [dimensionless].

The water storage on the surface of the impervious area at 

the end of the current day, Ti, is determined from the equation:

for X2i ≤ Gi , 

 Ti = 0,

for X2i > Gi , 

 Ti = X2i – Gi, (8)

where

Gi = reference ET for current day [L], and

Ti = water storage (ponded water) on the 

 surface of impervious area at the end of 

 day [L].

The next step in the water-budget computation is to 

determine the amount of water that will be removed from the 

plant-root zone by ET. Actual ET is a function of potential 

ET and interim moisture, Xi. The plant-root zone loses water 

to the atmosphere at the potential-ET rate if sufficient water 

is available. At all sites, potential ET, (PE)i, is calculated as 

the product of (1) reference ET, Gi, the potential ET of a grass 

reference surface, and (2) crop coefficient, kc, a factor that 

depends on vegetation and land cover. 

(PE)i = kc × Gi (9)

where

(PE)i = potential-ET rate for the current day [L/T], 

 and

kc = crop coefficient of land cover 

 [dimensionless].

For moisture storage greater than or equal to a threshold 

value, Ci, the actual-ET rate is assumed to be equal to the 

potential-ET rate. For moisture storage less than Ci, the actualET rate is assumed to occur at a reduced rate that declines 

linearly with soil-moisture content:

for M ≥ Ci, , 

 E = (PE)i , and

for M < Ci and Ci > 0 

E = M × (PE)i ÷ Ci , (10)

where

E = instantaneous actual-ET rate [L/T],

M = instantaneous moisture storage [L], and

Ci = threshold moisture storage for the current 

 day below which the actual-ET rate is 

 less than the potential-ET rate [L].

The threshold moisture storage, Ci, is estimated using the 

model of Allen and others (1998) for soil moisture. In this model, 

a depletion fraction, d, which ranges from 0 to 1, is defined as the 

fraction of maximum moisture storage that can be depleted from 

the plant-root zone before moisture stress causes a reduction in the 

actual-ET rate. Values for d are assigned to land-cover classes on 

the basis of data in Allen and others (1998). The threshold moisture, Ci

, is estimated from d by the equation

 Ci = (1 – d) × Mm , (11)

where 

Mm = moisture-storage capacity of the plant-root 

 zone [L], and

d = depletion fraction [dimensionless].

The moisture-storage capacity of the plant-root zone, 

Mm, expressed as a depth of water, is equal to the plant-root 

depth, D, multiplied by the available water capacity of the 

soil, φ. Available water capacity is the difference between the 

volumetric field-capacity moisture content and the volumetric 

wilting-point moisture content: 
14 Spatially Distributed Groundwater Recharge Estimated Using a Water-Budget Model for the Island of O‘ahu, Hawai‘i

 Mm = D × φ, (12)

where

D = plant-root depth [L],

φ = available water capacity, θfc – θwp [L3/L3], 

θfc = volumetric field-capacity moisture content 

 [L3/L3], and

θwp = volumetric wilting-point moisture content 

 [L3/L3].

In the water-budget model, the actual-ET rate from the 

plant-root zone may be (1) equal to the potential-ET rate for part 

of the day and less than the potential-ET rate for the remainder of 

the day, (2) equal to the potential-ET rate for the entire day, or (3) 

less than the potential-ET rate for the entire day. The total ET from 

the plant-root zone during a day is a function of the potential-ET 

rate, (PE)

i

, interim moisture storage, Xi, and the threshold moisture 

content, Ci. By recognizing that E = -dM/dt, the total depth of 

water removed by ET from the plant-root zone during a day, Ei, is 

determined as follows:

for Xi > Ci and Ci > 0,

Ei = (PE)

i

t

i + Ci

{1 – exp[–(PE)i(1-t

i

) ÷ Ci]},

for Xi > Ci and Ci = 0,

Ei = (PE)it

i

,

for Xi ≤ Ci and Ci > 0,

Ei = Xi{1 – exp[–(PE)i ÷ Ci]}, and

for Xi = Ci, and Ci = 0,

Ei = 0, (13)

where

Ei = evapotranspiration from the plant-root 

zone during the day [L], 

t

i = time during which moisture storage is 

above Ci [T]. It ranges from 0 to 1 

day and is calculated as follows:

for (Xi – Ci) < (PE)i(1 day)

t

i

 = (Xi – Ci) ÷ (PE)i, and

for (Xi – Ci) ≥ (PE)i(1 day),

t

i

 = 1. (14)

After accounting for runoff (equation 1a or 1b), actual ET 

from the plant-root zone for a given day is subtracted from the 

interim moisture storage, and any moisture remaining above 

the maximum moisture storage is assumed to be recharge. 

The daily rate of direct recharge from anthropogenic sources, 

including seepage from cesspools and reservoirs, is also 

added to daily recharge at this point. Recharge and moisture 

storage at the end of a given day are assigned according to the 

following conditions:

for Xi – Ei ≤ Mm , 

 Qi = DR, and Mi = Xi – Ei , and

for Xi – Ei > Mm , 

 Qi = (Xi– Ei – Mm) + DR, and Mi = Mm , (15)

where

Qi = groundwater recharge during the day [L], 

and 

Mi = moisture storage at the end of the current 

day (i) [L], and

DR = daily rate of direct recharge [L].

Iteration

To mitigate possible effects of arbitrary starting values 

and random selection of monthly rainfall fragment sets 

(see Rainfall section, below), the recharge model was run 

multiple times and the results were averaged. To determine the 

appropriate number of simulations to run, the recharge model 

for was run 50 times and the absolute percentage change in 

cumulative mean recharge for the island was calculated for 

each successive simulation (fig. 6). The average percentage 

change did not exceed 0.002 percent after 25 simulations. 

This very small value, 0.002 percent, was determined to be 

adequate for this study. Accordingly, for each model scenario, 

the recharge model was run 25 times and the results were 

averaged

Model Input

Land Cover

A land-cover map for Oʻahu representative of 2010 

conditions, herein referred to as the 2010 land-cover map, 

was developed for this study. The 2010 land-cover map 

identifies 18 types of land cover (fig. 4) and was merged with 

other spatial datasets when creating the map of subareas for 

the water-budget model. The 2010 land-cover map was used 

in the computation of recharge for both scenarios of this 

study: average climate conditions and drought conditions. 

The 2010 land-cover map was created by modifying the 

LANDFIRE Existing Vegetation Type map for Oʻahu (U.S. 

Geological Survey, 2010), herein referred to as the Landfire 

map. Modifications to the Landfire map included converting 
Model Input 15

Figure 6. The average incremental 

percentage change in recharge for 

water-budget subareas with each 

successive model simulation.

0.000

0.002

0.004

0.006

0.008

0.010

0.012

0.014

0.016

0.018

0.020

0 10 20 30 40 50

Absolute percentage change in island-wide recharge

Number of simulations

0.002 percent

Figure 6. The absolute percentage change in cumulative island-wide recharge with each successive 

model simulation.

it from a raster dataset to a vector dataset, combining similar 

land-cover classes, and adding boundaries of golf courses 

and selected crops. These modifications were done using Esri 

ArcGIS software, as summarized in the following paragraphs.

Some land-cover groups of the Landfire map were 

combined into more general classes for the 2010 land-cover 

map. Landfire groups Hawaiian Dry Grassland, Hawaiian 

Mesic Grassland, and Introduced Perennial Grassland and 

Forbland were combined into Grassland for the 2010 landcover map (fig. 4). Landfire groups Hawaiian Dry Shrubland, 

Hawaiian Mesic Shrubland, and Introduced Upland 

Vegetation–Shrub were combined into Shrubland. Landfire 

groups Hawaiian Dry Forest, Hawaiian Mesic Forest, and 

Hawaiian Rainforest were combined into Native forest. The 

Landfire group Introduced Upland Vegetation-Treed was 

renamed Alien forest.

Locations of golf courses and selected crops not specified 

in the Landfire map were delineated in the 2010 land-cover 

map to improve estimates of irrigation, ET, and recharge for 

parcels with these types of land cover. The boundaries of 

golf courses, coffee, pineapple, and taro in the 2010 landcover map (fig. 4) were defined using sources other than the 

Landfire map. The boundaries of golf courses and fields of 

corn, coffee, and pineapple were digitized using 2010–13 

satellite imagery in Google Earth (earth.google.com). Fields 

of taro were digitized on the basis of those identified in 

Gingerich and others (2007). All other parcels classified as 

agriculture in the Landfire map that appeared in the imagery 

as being actively cultivated were classified as diversified 

agriculture. Agriculture parcels that appeared in the imagery 

as uncultivated and mostly covered by grass were defined as 

grassland. 

Impervious surfaces include paved surfaces and 

buildings. Excess water from the impervious fraction of a 

subarea, Wi, that is distributed to the pervious fraction of the 

subarea depends on the impervious fraction of the subarea, z. 

The impervious fraction of each subarea was calculated from 

a map of impervious surfaces on Oʻahu (National Oceanic and 

Atmospheric Administration, 2008).

Rainfall

Monthly Rainfall

Gridded maps of rainfall for each of the 360 months during 

1978–2007 for the Island of Oʻahu were used to define the 

spatial and temporal distribution of rainfall in the water-budget 

calculations. These maps are a subset of the 1,056 rainfall maps 

that were generated for the Rainfall Atlas of Hawaiʻi (Giambelluca 

and others, 2013) for each month from 1920–2007 for the 

Hawaiian Islands by Frazier and others (2016). The monthly 

rainfall maps for 1978–2007 were used in the water budget 

because they have the same base period as the mean monthly and 

mean annual rainfall datasets in Giambelluca and others (2013). 

Rainfall maps are formatted 8.1-arcsecond grids, where each grid 

cell is about 14 acres (770 by 820 ft) and has an estimated rainfall 

value for each month during 1978–2007. Using Esri ArcGIS 

software, the monthly rainfall maps were converted from a raster 
16 Spatially Distributed Groundwater Recharge Estimated Using a Water-Budget Model for the Island of O‘ahu, Hawai‘i

grid to polygon format for use in the water-budget model. The 

rainfall polygons were intersected with the other spatial datasets 

when creating the map of subareas for the water-budget model.

Cell-by-cell comparisons of the mean monthly rainfall 

calculated for 1978–2007 from the Frazier and others (2016) 

dataset and the mean monthly values in Giambelluca and others 

(2013) showed differences. For consistency, the monthly rainfall 

values from Frazier and others (2016) were adjusted to produce 

the same mean monthly rainfall values for 1978–2007 as 

Giambelluca and others (2013). A total of 12 monthly adjustment 

factors for each grid cell were determined as the ratio of the 1978–

2007 mean monthly rainfall from Giambelluca and others (2013) 

to the 1978–2007 mean monthly rainfall calculated from Frazier 

and others (2016). In this study, the monthly rainfall for each grid 

cell was determined by multiplying the value in Frazier and others 

(2016) by the appropriate monthly adjustment factor.

Daily Rainfall

Estimates of the actual rainfall distribution on Oʻahu for 

each day during 1978–2007 were not available and were not 

developed as part of this study. Although records of daily rainfall 

measurements at gages were available, reconstructing the actual 

daily rainfall pattern was not attempted because (1) records for 

many gages have considerable gaps, (2) the spatial interpolation 

of daily records for gages would have high uncertainty, and (3) 

the monthly rainfall maps of Frazier and others (2016) were 

considered to be the best dataset available for estimating historical 

rainfall patterns.

For input to the water-budget model, daily rainfall was 

synthesized by disaggregating the monthly values of the 1978–

2007 rainfall distribution maps using the method of fragments (for 

example, Oki, 2002). The method of fragments creates a synthetic 

sequence of daily rainfall from monthly rainfall by imposing the 

rainfall pattern from a rain gage with daily data. The synthesized 

daily rainfall data approximate the long-term average character 

of daily rainfall, such as frequency, duration, and intensity, but 

may not reproduce the historical daily rainfall record during 

1978–2007. 

Daily rainfall measurements at 47 rain gages on Oʻahu 

during 1905–2011 were used to disaggregate monthly rainfall 

into daily rainfall for the water-budget model. Rain gages were 

selected on the basis of location, and the length and completeness 

of daily records. Daily rainfall data for the period of record of each 

rain gage were obtained from the National Climatic Data Center 

(www.ncdc.noaa.gov) and the USGS (http://waterdata.usgs.gov/hi/

nwis/nwis). Thiessen polygons were drawn around each of the rain 

gages, and the daily rainfall pattern within each Thiessen polygon 

was assumed to be the same as the pattern at the rain gage within 

the Thiessen polygon (fig. 3).

For each rain gage, daily rainfall fragments were calculated 

by dividing each daily rainfall measurement for a particular month 

by the total rainfall measured at the gage for that month. This 

resulted in a set of fragments for that particular month in which 

the total number of fragments was equal to the number of days 

in the month. Fragment sets were compiled for every gage for 

every month in which complete daily rainfall measurements were 

available. Fragment sets were grouped by month of the year and 

by rain gage. 

In the water-budget calculation, the fragment set used for a 

given gage for a given month was selected randomly from among 

all available sets for that gage for that month. Daily rainfall for a 

given month was synthesized by multiplying total rainfall for that 

month (from the monthly rainfall maps) by each fragment in the 

set, thereby providing daily rainfall, Ri, for equation 1a or 1b.

Fog Interception

Fog is often persistent on the mid-elevation mountain 

slopes of most Hawaiian islands, occurring during periods 

of onshore, upsloping winds favorable for orographic cloud 

formation. Fog may be persistent at elevations as low as about 

2,000 to 3,000 ft (Juvik and Ekern, 1978). Orographic cloud 

formation is often limited or capped by the base of the tradewind inversion, which commonly occurs between 5,000 and 

10,000 ft (Giambelluca and Schroeder, 1998). This limitation 

on cloud formation hinders the growth of large raindrops and 

produces high ratios of fog to rain near or at the inversionbase elevation (Juvik and Ekern, 1978). Above the base of the 

inversion, fog tends to dissipate quickly in the drier air regime. 

Where fog is persistent, the interception of this moisture 

by vegetation has been shown to be a significant component of 

the water budget (Ekern, 1964; Juvik and Ekern, 1978; Juvik 

and others, 1993; 2011; Juvik and Nullet, 1995; Scholl and 

others, 2007). Fog interception occurs through the processes of 

turbulent diffusion and gravitational sedimentation of droplets 

onto vegetative surfaces, mainly leaves or needles (Bruijnzeel and 

others, 2005). Rates of fog interception are highly site dependent 

and influenced by both meteorological and biotic variables 

including (1) the duration and frequency of fog periods, (2) 

wind speed and direction, (3) liquid water content of fog, and (4) 

structural characteristics of the forest, such as height, size, spatial 

pattern, and the physical characteristics of leaves and epiphytes 

(Walmsley and others, 1996; Bruijnzeel and others, 2005; Villegas 

and others, 2007). The quantification of fog interception is a 

complex endeavor and is the subject of continuing research, both 

in Hawaiʻi and worldwide. 

For leeward areas above 2,000 ft on Oʻahu, estimates of 

fog interception for this study are based on fog-interception data 

collected in the Koʻolau Range. Monthly ratios of fog-interception 

to rainfall (table 3) were calculated from data presented in 

Ekern (1983). For leeward areas, the lowest ratio, 0.01, occurs 

in October, and the highest ratio, 0.15, occurs in February. For 

windward Oʻahu above 2,000 ft, a relatively small area where no 

fog studies have been conducted, a ratio of 0.20 was used for all 

months. This is the same fog-interception to rainfall ratio used in 

Engott and Vana (2007) for the windward West Maui Mountains.

Fog interception is primarily a phenomenon associated 

with trees and other tall vegetation because the magnitude of 

fog interception is directly related to the height of the vegetated 

surface (Walmsley and others, 1996; Bruijnzeel and others, 2005). 
Model Input 17

Accordingly, fog interception for nonforest land covers is assumed 

to be negligible, except for shrubland, which is assumed to 

intercept fog at one-half the rate of forest land covers. 

Irrigation

Irrigation was applied to golf courses and five agricultural 

land covers: corn, coffee, pineapple, diversified agriculture, 

and taro (fig. 4). Irrigation was also applied to medium- and 

high-intensity developed subareas in order to simulate the 

watering of urban landscapes. Irrigation rates were estimated 

using a demand-based approach. Irrigation demand for a given 

subarea is estimated on the basis of monthly rainfall, runoff, 

potential evapotranspiration, and irrigation-method efficiency: 

for (PE)m + Um > Rm, 

 Im = [(PE)m + Um – Rm] / g

for (PE)m + Um ≤ Rm,

 Im = 0 (16)

where

(PE)m = potential evapotranspiration for month m 

 [L] (varies by location),

Um = amount of runoff for month m [L], 

Rm = amount of rainfall for month m [L],

I

m = amount of irrigation for month m [L], and

g = irrigation-method efficiency 

 [dimensionless].

Table 3. Ratios of fog interception to rainfall used in the water-budget 

model for the Island of O‘ahu, Hawai‘i.

Month Aspect

Leeward Windward

January 0.12 0.20

February 0.15 0.20

March 0.08 0.20

April 0.08 0.20

May 0.02 0.20

June 0.12 0.20

July 0.09 0.20

August 0.06 0.20

September 0.05 0.20

October 0.01 0.20

November 0.05 0.20

December 0.11 0.20

Irrigation-method efficiency is the fraction of applied 

irrigation water that becomes available for plant consumption. 

Corn, diversified agriculture, and pineapple were assumed to 

use drip irrigation, which has an irrigation-method efficiency 

of 0.85 (University of Hawaiʻi, 2008). Coffee was assumed to 

use micro-spray irrigation, which has an irrigation efficiency 

of 0.80 (University of Hawaiʻi, 2008). Golf courses and 

medium- and high-intensity developed land covers were 

assumed to use sprinkler irrigation, which has an irrigation 

efficiency of 0.70 (University of Hawaiʻi, 2008). 

For all irrigated land covers other than pineapple, 

monthly irrigation calculated using equation 16 was allocated 

in equal amounts for each day of a given month. Similar to 

the approach taken in Engott and Vana (2007) for pineapple 

irrigation, the monthly irrigation volume calculated for 

pineapple using equation 16 was uniformly distributed on 

days 1, 2, 3, 8, 9, 10, 15, 16, 17, 22, 23, 24, and 28 of each 

month. Simulation of the pineapple cultivation cycle was not 

attempted in this study. Corn irrigation for this study is based 

on a cultivation cycle of 2 crops per year. Only 25 percent of 

the corn land cover is cultivated at any one time, leaving the 

remaining 75 percent fallow/grassland. This approach was 

developed on the basis of cultivation practices on Molokaʻi. 

An irrigation-estimation multiplier was used to adjust 

the irrigation estimate (equation 16) for the diversified 

agriculture land-cover category because of its relatively 

large total area (fig. 4) combined with the large uncertainty 

involved in selecting crop parameters, given the wide variety 

of crops represented by this category. An irrigation-estimation 

multiplier of 0.55 was used on the basis of irrigation-supply 

information for fields served by the Waiāhole Ditch in central 

and southern Oʻahu. An irrigation-estimation multiplier also 

was used for the medium- and high-intensity land-cover 

categories to calibrate the irrigation estimates from equation 

16 to the rates used in Giambelluca (1983) and Giambelluca 

and others (2014) for urban irrigation in southern Oʻahu.

Owing to the nature of wetland taro cultivation, the 

irrigation rate for taro was not calculated using the demandbased approach described above. Instead, the irrigation rate 

for taro, which is grown in flooded ponds, was set equal to a 

constant recharge rate over the area of active taro cultivation. 

A constant recharge rate of 455 in/yr was used, which is the 

average of the recharge rates derived from four water-use 

studies for various taro fields in Hawaiʻi (Miles, 1931; Watson, 

1964; La Pena and Melchor, 1984; Berg and others, 1997). 

Septic-System Leaching

Some areas on Oʻahu have on-site systems to dispose 

of wastewater. Whittier and El-Kadi (2009) compiled an 

inventory of on-site wastewater-disposal systems on Oʻahu. 

For each tax map key (TMK) parcel, Whittier and El-Kadi 

(2009) specify the number and type (class) of on-site 

disposal systems and the total estimated wastewater effluent 

flux. For the water-budget calculation, all effluent flux for 
18 Spatially Distributed Groundwater Recharge Estimated Using a Water-Budget Model for the Island of O‘ahu, Hawai‘i

each TMK parcel was applied daily as a uniform depth over 

the parcel’s area. Each TMK parcel may contain one or more 

subareas. Hence, all subareas within a TMK parcel that 

contains at least one on-site disposal system can have septic 

effluent, including subareas with undeveloped land covers. 

For TMK parcels with cesspools, the effluent flux was 

considered direct recharge (fig. 5). For TMK parcels with 

other types of septic-systems, the effluent flux was added to 

the plant-root zone as septic-system leachate (fig. 5). 

Storm-Drain Systems

Some developed areas on Oʻahu have storm-drain 

systems that collect and divert rainwater. Water collected by 

storm-drain systems may be diverted into streams, gulches, 

the ocean, infiltration basins, and drywells, thereby affecting 

the water budget. For this study, subareas with medium- and 

high-intensity developed land covers in (1) the Waiʻanae, 

Central, Pearl Harbor, and Honolulu aquifer sectors and (2) the 

Koʻolaupoko and Waimānalo aquifer systems were assumed to 

have storm-drain systems (figs. 1 and 4). For these subareas, 

excess water, Wi, that flows off the impervious fraction of a 

subarea was assumed to be collected by a storm-drain system 

instead of flowing to the pervious fraction of the subarea 

(see equation 7). This collected water was assumed to not 

contribute to recharge. 

Direct Runoff

Direct runoff is the fraction of rainfall that does not 

contribute to net moisture gain within the plant-root zone 

(fig. 5). Direct runoff of rainfall consists of overland flow and 

subsurface storm flow that rapidly returns infiltrated water to 

the stream (Oki, 2003). In the water-budget calculation, direct 

runoff was estimated as a fraction of rainfall using runoffto-rainfall ratios. This approach was also used in previous 

water-budget studies for Hawaiʻi and other Pacific islands 

(for example, Izuka and others, 2005; Engott and Vana, 2007; 

Engott, 2011; Gingerich and Engott, 2012; Johnson, 2012) and 

was shown to provide reasonable estimates of regional average 

direct runoff using a minimal level of complexity. 

The spatial variability of runoff-to-rainfall ratios 

depends on numerous factors including geology, climate, soil 

type, topography, and land use. Runoff-to-rainfall ratios are 

expected to be highest where the rainfall amount and intensity 

are high, permeability of the soils and substrate is low, 

slopes are steep, and soil moisture is high (Oki, 2003). The 

temporal variability in runoff-to-rainfall ratios reflects event 

characteristics, such as antecedent soil moisture and rainfall 

intensity. In Hawaiʻi, runoff-to-rainfall ratios generally follow 

a seasonal pattern. Runoff-to-rainfall ratios are highest during 

the wet-season months and lowest during the dry-season 

months. 

In the water-budget model, daily direct runoff, Ui, was 

calculated by multiplying daily rainfall, Ri, with seasonal 

(wet and dry season) runoff-to-rainfall ratios assigned to 

catchment zones. Catchment zones were delineated by Rea 

and Skinner (2012) for a stream network developed using 

a 10-m digital elevation model with a flow-accumulation 

threshold of 20,000 cells. For this study, each catchment zone 

was assigned two attributes: (1) gaged or ungaged, and (2) 

windward or leeward (fig. 7). The boundaries of the drainage 

basins of selected stream-gaging stations are from Rosa and 

Oki (2010), and the boundary between windward and leeward 

regions is based on topographic divides and consistent with 

previous studies (Yamanaga, 1972; Oki and others, 2010). 

The runoff-to-rainfall ratio assigned to each catchment zone 

and used to calculate direct runoff was selected as one of the 

following (1) the observed seasonal runoff-to-rainfall ratio 

for the season, year, and location of interest, if available, (2) 

the observed mean seasonal runoff-to-rainfall ratio for the 

location of interest, or (3) the mean seasonal runoff-to-rainfall 

ratio estimated using a regression equation for the location of 

interest. A description of the approach used to calculate the 

ratios is presented below. For this study, November through 

April was considered the wet season; May through October 

was considered the dry season.

Seasonal runoff-to-rainfall ratios assigned to catchment 

zones in the water-budget model were calculated from data 

for drainage basins of stream-gaging stations. These drainage 

basins consist of one or more catchment zones. For gaged 

drainage basins consisting of a single catchment zone, 

observed seasonal or mean seasonal runoff-to-rainfall ratios 

for the gaged basin were assigned to the catchment zone. For 

gaged drainage basins consisting of multiple catchment zones, 

observed seasonal or mean seasonal runoff-to-rainfall ratios 

for the gaged drainage basin were spatially disaggregated to 

each catchment zone within the gaged basin. Catchment zones 

in ungaged areas were assigned mean seasonal runoff-torainfall ratios derived from regional-regression models.

Computation of Seasonal Runoff-to-Rainfall Ratios

Runoff and rainfall data for drainage basins of 55 

stream-gaging stations (25 on Maui, 13 on Kauaʻi, and 17 

on Oʻahu) were used to derive seasonal runoff-to-rainfall 

ratios for the water-budget model (table 4). Data for stations 

on Maui and Kauaʻi were included in the analysis to derive 

broadly applicable empirical models for estimating direct 

runoff in ungaged areas. Stream-gaging stations selected for 

the runoff analysis had (1) at least eight complete years of 

daily mean discharge records between 1920 and 2007, (2) a 

drainage-basin area greater than 0.2 mi2, and (3) unregulated 

streamflow or regulated streamflow with complete and reliable 

records of daily mean diverted flow available to reconstruct 

total streamflow at the gage. For drainage basins with more 

than one stream-gaging station, only the station at the lowest 

elevation was used in the runoff analysis because it had the 

largest drainage basin. Additionally, concurrent streamflow 

data for two stations within a drainage basin was generally 

absent or insufficient for improving direct runoff estimates. 
Model Input 19

Figure 7. Mean runoff-to-rainfall ratios for the (A) dry-season months (May through October) and (B) wet-season months (November through April) 

for drainage basins of selected stream-gaging stations and catchment zones on the Island of O‘ahu, Hawai‘i (modified from Rea and Skinner, 2012).

#

#

#

#

#

# #

#

#

#

#

#

#

#

#

#

#

#

#

#

#

# #

#

#

#

#

#

#

#

#

#

Windward

Leeward

Leeward

Windward

158°10'

21°40'

21°30'

21°30'

158°

157°50'

157°40'

16208000

16200000

16211600

16304200

16345000

16325000

16303003

16244000

16229300

16212800

16283000

16278000

16216000

16270500

16226200

16228000

16201000

Figure 7. Mean runoff-to-rainfall ratios for the (A) dry-season months (May through October), and (B) wet-season months (November through April)

Mean seasonal ratio of 

runoff to rainfall

EXPLANATION

16636000 USGS stream-gaging 

station and number

Leeward-windward boundary

0.05

0.02

0.15

0.50

0.25

Dry-season months:

May through October

Wet-season months:

November through April

Base modified from Rea and Skinner, 2012,

Universal Transverse Mercator Projection, Zone 4, NAD83 Datum. 0 5 10 KILOMETERS

0 5 10 MILES

A

B Drainage basin of 

stream-gaging station 

Catchment zone of

Rea and Skinner (2012) 

Model Input 19

for drainage basins of selected stream-gaging stations and catchment zones on the Island of O‘ahu, Hawai‘i (modified from Rea and Skinner, 2012)
20 Spatially Distributed Groundwater Recharge Estimated Using a Water-Budget Model for the Island of O‘ahu, Hawai‘i

The drainage basins of the selected stream-gaging stations 

were delineated using the USGS StreamStats application for 

Hawaiʻi (Rosa and Oki, 2010). Rainfall within each drainage 

basin was calculated using gridded maps of monthly rainfall 

(Frazier and others, 2016). 

Because streamflow measured at most gaging stations 

consists of direct runoff and base flow, the base-flow component 

was estimated and subtracted from the total streamflow. 

Streamflow at stations 16500100 and 16660000 on Maui and 

station 16013000 on Kauaʻi was ephemeral and was assumed 

to have no base flow. Base flow at the other gaged basins was 

estimated using a computerized base-flow separation method 

(Wahl and Wahl, 1995). This method has been used in numerous 

other studies in Hawaiʻi (for example, Izuka and others, 2005; 

Engott and Vana, 2007; Engott, 2011) and provides a reasonable 

estimate of base flow for perennial streams in Hawaiʻi. The 

method defines local streamflow minimums within consecutive, 

nonoverlapping n-day periods and requires two parameters (1) 

f, the turning-point test factor, and (2) n, the number of days in a 

test window. In this study, the f value used for all stations was 0.9. 

The n values were determined for each station using the method 

described by Wahl and Wahl (1995) and ranged from three to 

five days (table 4). Daily base flow was subtracted from daily 

streamflow to determine daily direct runoff.

Observed seasonal runoff-to-rainfall ratios were calculated 

for 17 gaged drainage basins on Oʻahu that were operational 

during 1978–2007. These observed ratios are not presented in 

this report. Each observed seasonal runoff-to-rainfall ratio for the 

gaged drainage basins was calculated as the quotient of cumulative 

direct runoff and cumulative rainfall during the season. For 

example, the observed runoff-to-rainfall ratio for a gaged basin 

during the dry season of 2001 was calculated as the quotient of 

cumulative direct runoff and cumulative rainfall during May–

October 2001. 

For each of the 55 selected gaged drainage basins on 

Kauaʻi, Oʻahu, and Maui, mean seasonal runoff-to-rainfall ratios 

were calculated for a period with rainfall and runoff conditions 

generally representative of those during 1978–2007 (table 4). 

Each mean seasonal runoff-to-rainfall ratio for the gaged drainage 

basins was calculated as the quotient of cumulative direct runoff 

and cumulative rainfall during the appropriate season of the 

selected period. For example, the mean dry season runoff-torainfall ratio for stream-gaging station 16228000 was calculated 

as the quotient of cumulative direct runoff and cumulative rainfall 

during May–October between 1949 and 1978. 

Criteria for selecting periods of record were determined 

by examining temporal variations in seasonal runoff-to-rainfall 

ratios for stream-gaging stations that were operational during 

1978–2007. For these stations, mean seasonal runoff-to-rainfall 

ratios calculated for 1978–2007 were compared with those 

calculated for smaller, subset periods during 1920–2007. The 

results of these comparisons show that the difference between 

mean seasonal runoff-to-rainfall ratios calculated for 1978–2007 

and those calculated for subset periods decreases with increasing 

record length of the subset period and with decreasing differences 

between mean annual rainfall during 1978–2007 and that of 

the subset period. Accordingly, the period of record selected 

to calculate mean seasonal runoff-to-rainfall ratios was (1) the 

entire period during 1978–2007 for stream-gaging stations with 

at least 24 complete years of record during 1978–2007, (2) the 

longest contiguous period during 1920–2007 that had less than 

5-percent difference in mean annual rainfall, relative to rainfall for 

1978–2007, for all remaining stream-gaging stations on perennial 

streams with base flow, and (3) the entire period of record for 

three stream-gaging stations on ephemeral streams. Despite the 

relatively high rainfall during their periods of record (table 4), 

the latter three stations were included in the analysis owing to the 

sparseness of runoff data for areas in the Hawaiian Islands with 

ephemeral streams.

Runoff-to-Rainfall Ratios Assigned to Ungaged 

Catchment Zones 

Ungaged catchment zones are outside of the drainage basins 

of the 17 selected stream-gaging stations on Oʻahu (fig. 6). Direct 

runoff for ungaged catchment zones was calculated using mean 

seasonal runoff-to-rainfall ratios derived from the four regionalregression equations in table 5. Separate windward and leeward 

regression equations were derived for the wet and dry seasons. 

The regional-regression equations relate mean seasonal runoff-torainfall ratios and basin characteristics and were developed with 

methods consistent with discussion given in Helsel and Hirsch 

(1992). 

The regional-regression equations were derived from mean 

seasonal runoff-to-rainfall ratios and basin characteristics for the 

55 stream-gaging stations in table 4. Thirty basin characteristics—

including those related to climate, soil, and vegetation—were 

evaluated as possible explanatory variables (not shown). All 

possible combinations of linear and power regressions using the 

selected basin characteristics were tested to identify the most 

robust and significant relations. The regional regressions in 

table 5 were selected because they had the lowest residual sum 

of squares and met the following criteria. First, all regression 

coefficients were statistically significant at a 5-percent significance 

level. Second, the sign and magnitude of the fitted coefficients 

were physically meaningful. Finally, the cross-validated results 

indicated less than 10 percent bias. For leeward catchment zones, 

wet season runoff-to-rainfall ratios were estimated on the basis 

of mean wet season rainfall during 1978–2007 (Giambelluca and 

others, 2013); dry season runoff-to-rainfall ratios were estimated 

on the basis of mean dry season rainfall during 1978–2007. 

For windward catchment zones, wet season runoff-to-rainfall 

ratios were estimated on the basis of mean annual reference 

ET (Giambelluca and others, 2014) and the percentage of the 

catchment zone’s area with hydrologic soil groups C and D (U.S. 

Department of Agriculture, 2006a,b,c); dry season runoff-torainfall ratios were estimated on the basis of mean dry season 

reference ET and the percentage of the zone’s area with hydrologic 

soil groups C and D. The performance statistics of the regression 

equations in table 5 are used to examine the sensitivity of recharge 

to runoff-to-rainfall ratios (see Sensitivity Analysis).
Model Input 21

Table 4. Mean seasonal runoff-to-rainfall ratios for drainage basins of stream-gaging stations on the Islands of Kaua‘i, O‘ahu, and Maui, Hawai‘i.

1Gaging-station number Stream/river/gulch/ valley Island Aspect

Area of 

drainage 

basin, 

in square 

miles

n

Period of record selected to 

calculate 

mean runoff-to-rainfall ratios

Mean runoff-to-rainfall ratio Mean annual rainfall 

Start End Number of years Wet season: November through April Dry season: May through October During 1978–2007, inches

2Difference during 

selected period of 

record, percentage 

of mean during 

1978–2007

16028000 (16022000, 

16014000)

Waimea River Kaua‘i Leeward 43.68 5 1927 1947 21 0.29 0.22 89.0 5.6

16063000 (16100000, 

16062000, 16061000)

North fork Wailua 

River

Kaua‘i Windward 5.34 4 1957 1984 28 0.63 0.48 199.8 7.4

16068000 East bank of north 

fork Wailua River

Kaua‘i Windward 6.24 4 1978 2007 30 0.50 0.27 129.0 0.0

16071500 Left branch 

‘Ōpaeka‘a Stream

Kaua‘i Windward 0.75 4 1978 2007 30 0.22 0.09 100.5 0.0

16089000 (16088000, 

16087000)

Anahola Stream Kaua‘i Windward 5.45 4 1956 1985 30 0.48 0.35 108.4 5.2

16097500 Halaulani Stream Kaua‘i Windward 1.20 4 1978 2007 30 0.62 0.41 115.0 0.016103000 Hanalei River Kaua‘i Windward 18.51 4 1993 2007 15 0.57 0.34 175.4 -8.116108000 Wainiha River Kaua‘i Windward 10.44 5 1978 2007 30 0.54 0.39 207.6 0.016114000 Limahuli Stream Kaua‘i Windward 1.37 4 1995 2005 11 0.35 0.21 116.5 -2.316115000 Hanakāpī‘ai Stream Kaua‘i Windward 2.75 5 1941 1949 9 0.41 0.28 128.7 1.216116000 Hanakoa Stream Kaua‘i Windward 1.09 5 1939 1947 9 0.53 0.31 105.8 1.916117000 Kalalau Stream Kaua‘i Leeward 1.60 5 1932 1948 17 0.24 0.09 80.5 4.416130000 Nahomalu Valley Kaua‘i Leeward 3.79 E 1964 1971 8 0.04 0.01 36.6 26.716200000 North fork Kaukonahua Stream O‘ahu Leeward 1.38 4 1978 2007 30 0.48 0.49 232.4 0.016201000 Right bank of north 

fork Kaukonahua Stream

O‘ahu Leeward 1.15 4 1940 1951 12 0.34 0.36 213.4 4.6

16208000 South fork Kaukonahua Stream O‘ahu Leeward 4.10 5 1978 2007 29 0.32 0.28 168.9 0.016211600 Mākaha Stream O‘ahu Leeward 2.12 5 1978 2007 30 0.13 0.04 71.2 0.016212800 Kīpapa Stream O‘ahu Leeward 4.25 4 1978 2004 27 0.19 0.13 178.3 0.316216000 Waiawa Stream O‘ahu Leeward 25.19 4 1978 2004 27 0.21 0.12 93.7 0.316226200 North Hālawa 

Stream

O‘ahu Leeward 4.02 5 1983 2007 24 0.19 0.10 111.8 -2.8

[See fig. 7 for locations of drainage basins on Oʻahu; n, number of days used for determining minimum flows in the base flow-separation program (Wahl and Wahl, 1995); E, the base flow-separation program (Wahl and Wahl, 1995) was not used to estimate direct runoff because the streamflow measured at station was ephemeral and was assumed to equal direct runoff; mean annual rainfall estimated from Giambelluca and others (2013) and Frazier and others (2016)]
22 Spatially Distributed Groundwater Recharge Estimated Using a Water-Budget Model for the Island of O‘ahu, Hawai‘i

1Gaging-station number Stream/river/gulch/ valley Island Aspect

Area of 

drainage 

basin, 

in square 

miles

n

Period of record selected to 

calculate 

mean runoff-to-rainfall ratios

Mean runoff-to-rainfall ratio Mean annual rainfall 

Start End Number of years Wet season: November through April Dry season: May through October During 1978–2007, inches

2Difference during 

selected period of 

record, percentage 

of mean during 

1978–2007

16228000 Moanalua Stream O‘ahu Leeward 2.71 4 1949 1978 30 0.15 0.07 117.8 3.116229300 Kalihi Stream O‘ahu Leeward 5.21 4 1978 2003 26 0.21 0.11 97.6 -1.116244000 Pūkele Stream O‘ahu Leeward 1.15 5 1953 1982 30 0.14 0.08 114.6 3.616270500 Kamo‘oali‘i Stream O‘ahu Windward 3.20 3 1967 1976 9 0.18 0.06 82.8 2.916278000 ‘Ioleka‘a Stream O‘ahu Windward 0.32 3 1944 1968 25 0.09 0.07 95.8 0.416283000 Kahalu‘u Stream O‘ahu Windward 0.28 3 1941 1970 30 0.11 0.08 119.2 2.916303000 (16302000) Punalu‘u Stream O‘ahu Windward 2.78 4 1978 2006 29 0.21 0.13 186.6 0.416304200 Kaluanui Stream O‘ahu Windward 1.09 4 1978 2007 30 0.34 0.25 168.4 0.016325000 Kamananui Stream O‘ahu Leeward 3.15 4 1971 2000 30 0.29 0.15 132.0 0.016345000 ‘Ōpae‘ula Stream O‘ahu Leeward 3.00 4 1978 2007 30 0.37 0.24 164.6 0.016500100 Kepuni Gulch Maui Leeward 1.93

E 1963 1972 10 0.04 0.01 33.1 35.1

16501200 ‘Ohe‘o Gulch Maui Leeward 8.53 4 1990 1997 8 0.38 0.25 249.4 0.716508000 Hanawī Stream Maui Windward 3.29 4 1978 2007 30 0.42 0.24 248.7 0.016510000 Kapā‘ula Gulch Maui Windward 1.35 4 1933 1962 30 0.61 0.38 257.3 1.216515000 Waiohue Gulch Maui Windward 0.74 4 1933 1962 30 0.52 0.32 247.9 1.316516000 Kopiliula Stream Maui Windward 3.56 4 1938 1957 20 0.43 0.24 197.8 3.416517000 East Wailuaiki 

Stream

Maui Windward 3.14 4 1928 1957 30 0.58 0.35 201.2 4.7

16518000 West Wailuaiki 

Stream

Maui Windward 3.59 4 1978 2007 30 0.64 0.39 183.5 0.0

16520000 East Wailuanui 

Stream

Maui Windward 0.53 4 1928 1957 30 0.75 0.55 228.1 5.4

16527000 Honomanū Stream Maui Windward 2.94 4 1939 1963 25 0.55 0.45 149.8 3.716552800 Waikamoi Strream Maui Windward 2.50 4 1957 1967 11 0.17 0.12 62.9 3.516557000 Alo Stream Maui Windward 0.47 4 1928 1957 30 0.75 0.65 209.3 2.016565000 Ka‘aiea Gulch Maui Windward 0.68 4 1933 1962 30 0.50 0.44 216.5 -0.516566000 ‘O‘opuola Stream Maui Windward 0.25 4 1931 1957 27 0.64 0.54 189.4 -0.816570000 Na‘ili‘ilihaele Stream Maui Windward 3.69 5 1945 1974 30 0.60 0.50 181.9 -1.716577000 Kailua Stream Maui Windward 2.41 4 1928 1957 30 0.75 0.53 203.4 1.816585000 Ho‘olawanui Stream Maui Windward 1.34 5 1942 1971 30 0.50 0.32 174.9 -0.716586000 Ho‘olawali‘ili‘i 

Stream

Maui Windward 0.62 4 1931 1957 27 0.43 0.33 160.2 4.8

Table 4.—Continued
Model Input 23

1Gaging-station number Stream/river/gulch/ valley Island Aspect

Area of 

drainage 

basin, 

in square 

miles

n

Period of record selected to 

calculate 

mean runoff-to-rainfall ratios

Mean runoff-to-rainfall ratio Mean annual rainfall 

Start End Number of years Wet season: November through April Dry season: May through October During 1978–2007, inches

2Difference during 

selected period of 

record, percentage 

of mean during 

1978–2007

16587000 Honopou Stream Maui Windward 0.59 4 1978 2007 30 0.57 0.38 145.6 0.016604500 ‘Īao Stream Maui Windward 6.13 4 1983 2007 24 0.48 0.40 178.1 -3.816614000 Waihe‘e River Maui Windward 4.27 3 1984 2007 24 0.49 0.45 184.6 -2.416618000 Kahakuloa Stream Maui Windward 3.40 4 1978 2007 30 0.43 0.33 127.0 0.016620000 Honokōhau Stream Maui Windward 4.18 4 1978 2007 28 0.35 0.31 200.3 0.016636000 Kanahā Stream Maui Leeward 1.57 3 1920 1931 11 0.17 0.16 141.8 3.116660000 Kūlanihāko‘i Gulch Maui Leeward 15.03 E 1963 1970 8 0.01 0.00 22.4 38.6

1Data for gaging-station numbers in parentheses were used to reconstruct streamflow at the gaging station whose number is not in parentheses.2For example, mean annual rainfall on the drainage basin of station 16500100 was 35 percent greater during 1963–1972 than that during 1978–2007.

Table 4.—Continued

Region Season Regression used to compute runoff-to-rainfall ratio RMSE Percentage bias Overall O‘ahu Overall O‘ahu

Leeward Wet 0.00320 [mean wet season rainfall] 0.06 0.06 0.6 -3Leeward Dry 0.00293 [mean dry season rainfall] 0.07 0.07 3.8 6Windward Wet [% HSG C]0.185 [% HSG D]0.247 [mean annual ETo](–0.590) 0.12 0.13 -4.8 28Windward Dry [% HSG C]0.186 [% HSG D]0.346 [mean dry season ETo](–0.947) 0.11 0.10 -5.8 23

Table 5.[See fig. 7 for locations of leeward and windward regions on Oʻahu. RMSE, prediction root mean square error; Overall RMSE and percentage bias for the gaged basins on the Islands of Kauaʻi, Oʻahu and Maui used to develop the regional-regression equations; Wet season is November through April; Dry season is May through October; mean wet and dry season rainfall are from Giambelluca and others (2013); mean annual and dry season ETo, reference evapotranspiration, are from Giambelluca and others (2014); % HSG C, percentage of a catchment zone’s area that contains hydrologic soil group C; % HSG D, percentage of catchment zone’s area that contains hydrologic soil group D; Areas of hydrologic soil groups were derived from U.S.Department of Agriculture (2006a, 2006b, 2006c)]

Regional-regression equations used to calculate mean seasonal runoff-to-rainfall ratios for catchment zones in ungaged areas on the Island of O‘ahu, Hawai‘i.
24 Spatially Distributed Groundwater Recharge Estimated Using a Water-Budget Model for the Island of O‘ahu, Hawai‘i

Runoff-to-Rainfall Ratios Assigned to Gaged Basins 

within a Single Catchment Zone

Twelve of the selected stream-gaging stations on Oʻahu 

have drainage basins with a single catchment zone (fig. 7). 

Four of these stations (16201000, 16270500, 16278000, and 

16283000) were not operational during 1978–2007 (table 4). 

For the drainage basins of these four stations, direct runoff was 

calculated using mean seasonal runoff-to-rainfall ratios. For 

the drainage basins of the eight remaining stations (16200000, 

16208000, 16211600, 16244000, 16303000, 16304200, 

16325000, and 16345000), direct runoff was calculated using 

(1) observed seasonal runoff-to-rainfall ratios for seasons when 

observed ratios were available, and (2) mean seasonal runoffto-rainfall ratios for seasons when observed ratios were not 

available.

Runoff-to-Rainfall Ratios Assigned to Gaged Basins 

with Multiple Catchment Zones

Five of the selected stream-gaging stations on Oʻahu 

(16212800, 16216000, 16226200, 16228000, and 16229300) 

have drainage basins containing multiple catchment zones (fig. 7). 

Direct runoff for each of the catchment zones within these gaged 

basins was calculated using adjusted seasonal runoff-to-rainfall 

ratios determined from equation 17:

 (17)

where

 = adjusted runoff-to-rainfall ratio for catchment 

zone a during season t,

= mean runoff-to-rainfall ratio for catchment zone

a estimated using the appropriate regionalregression equation (table 5),

= number of catchment zone in the gaged basin b,

= mean runoff-to-rainfall ratio for catchment zone

i estimated using the regional- regression 

equations,

= rainfall for catchment zone i during season t, 

= rainfall for gaged basin b during season t, and

= observed runoff-to-rainfall ratio for the gaged 

basin b during season t. If the observed 

runoff-to-rainfall ratio for gaged basin b is not 

available during season t, the mean seasonal 

runoff-to-rainfall ratio is used (table 4).

Equation 17 uses the regional-regression models and seasonal rainfall to spatially disaggregate observed seasonal and mean 

seasonal runoff-to-rainfall ratios of a gaged basin for each catchment zone within a gaged basin. Hence, seasonal runoff-to-rainfall 

ratios were allowed to be spatially variable, instead of spatially 

uniform, across the catchment zones within gaged drainage basins 

containing multiple catchment zones.

Evapotranspiration

Evapotranspiration (ET) is the sum of all water that is 

evaporated or transpired from a vegetated surface and plantroot zone. Evapotranspiration can be divided into three main 

evaporative processes (1) canopy evaporation, which is 

evaporation of intercepted rain and fog from the surface of 

vegetation; (2) ground evaporation, which is evaporation of water 

from the soil surface and overlying litter and mulch layers; and 

(3) transpiration, the process by which soil moisture taken up by 

vegetation is eventually evaporated through plant pores (Viessman 

and Lewis, 2003). Because these three processes are difficult 

to quantify individually, they are typically combined in water 

budgets. 

Canopy evaporation in forested areas can substantially 

reduce the rainfall that reaches the ground beneath a forest 

canopy (Gaskill, 2004; DeLay, 2005; McJannet and others, 2007; 

Giambelluca and others, 2011; Safeeq and Fares, 2012b). Owing 

to the height of trees and their canopy structure, turbulent diffusion 

is much more efficient at removing intercepted water from 

forest canopies than from shorter vegetation. Moreover, canopy 

evaporation in forests tends to operate on much shorter time scales 

(hours) than transpiration (weeks or longer) (Savenije, 2004). This 

enhanced rate of evaporation from a wet forest canopy makes 

realistic estimates of ET from forests possible only if transpiration 

and canopy evaporation are evaluated separately (Shuttleworth, 

1993). 

For this study, total ET from subareas with forest land covers 

is calculated by separately estimating forest-canopy evaporation 

and combined ground evaporation and transpiration from the 

plant-root zone (fig. 5). Evaporation from the forest canopy and 

evapotranspiration from the plant-root zone are added together 

to yield total ET. For subareas with nonforest land covers, 

ET is calculated using a more traditional approach in which 

canopy evaporation, ground evaporation, and transpiration are 

not separately estimated (fig. 5). The concept of potential ET, 

combined with empirical models when soil moisture is limited, is 

used to estimate ground evaporation and transpiration for forest 

land covers and total ET for all other land covers. 

Forest-Canopy Evaporation and Net Precipitation

As rain falls on a vegetated surface, a fraction of the droplets 

will accumulate on the leaves, trunks, or stems of the vegetation. 

Additional moisture from fog interception may supplement 

the amount of water that accumulates on vegetation. Canopy 

evaporation is the part of precipitation that accumulates on and 

rr RR rr rf

RR rf a t, a

b t b t

i i t i

j

, ,

, ∑ 1 × = × ×

=

 



rr

a t,

RR a

j

RRi

rfi t,

rrb t,

rfb t,
Model Input 25

then evaporates from the vegetation (Gerrits and Savenije, 2011). 

Net precipitation is the part of precipitation that reaches the forest 

floor (fig. 5). 

In this study, the Gash model was used to calculate forestcanopy evaporation for the following reasons. First, the Gash 

model accounts for gaps in the forest canopy, and this allows for 

a sparse canopy to be differentiated from a dense canopy. Second, 

canopy evaporation during a period of precipitation is dependent 

on the amount of precipitation during that period. Third, the 

Gash model has the capacity to account for spatial differences 

in climate, including climate differences between windward and 

leeward forests. One disadvantage of the Gash model, however, 

is that it is theoretical. Therefore, one of the parameters of the 

Gash model used to calculate canopy evaporation in the waterbudget model was calibrated to the wet-canopy evaporation maps 

of Giambelluca and others (2014) as described below. Use of the 

Gash model, instead of the mean wet-canopy evaporation maps, 

in the water-budget model allows forest-canopy evaporation to 

be calculated on a daily basis in response to daily variations in 

precipitation.

Forest-canopy evaporation is calculated in the water-budget 

model according to equations 4 and 5, which require values for 

rainfall and the following five parameters (1) canopy cover, (2) 

canopy capacity, (3) trunk-storage capacity, (4) proportion of 

precipitation diverted to stemflow, and (5) the ratio of the mean 

evaporation rate to mean precipitation rate during saturated 

conditions, V. For the water-budget calculations, the values 

assigned to parameters 1–4 were derived from published data for 

areas in Hawaiʻi. The values assigned to V were derived using 

maps of mean wet-canopy evaporation for the Islands of Kauaʻi, 

Oʻahu, and Maui (Giambelluca and others, 2014). 

Canopy cover of forest land-covers varies spatially across 

Oʻahu. The canopy cover of each subarea with forest land cover in 

the water-budget model was estimated from a map of mean annual 

vegetation cover fraction (Giambelluca and others, 2014). This 

map quantifies the vegetation cover fraction at a spatial resolution 

of about 14 acres. A canopy cover of 0 implies an absence of 

canopy cover, whereas a value of 1 implies a dense canopy with 

no gaps. The estimated canopy-cover values for subareas with 

forest land covers used in the water-budget model range from 0.03 

to 1. 

Canopy capacity, trunk-storage capacity, and the 

proportion of precipitation diverted to stemflow were assumed 

to be the same for all forests (table 6). Canopy capacity was set 

at 0.05 inches, the mean of the average values reported for six 

forested sites in Hawaiʻi (DeLay, 2005, p. 42; Takahashi and 

others, 2011, Safeeq and Fares, 2012b). Trunk-storage capacity 

was set at 0.01 inches, the mean of the values reported for four 

forest sites in Hawaiʻi (DeLay, 2005, p. 42; Safeeq and Fares, 

2012b). The proportion of precipitation diverted to stemflow 

was assumed to be 0.04, the mean of the values reported for 

eight forest sites in Hawaiʻi (Gaskill, 2004; DeLay, 2005, p. 42; 

Takahashi and others, 2011; Safeeq and Fares, 2012b). Forest 

sites of Takahashi and others (2011) and Safeeq and Fares 

(2012b) with an abundance of Psidium cattleianum (strawberry 

guava) had relatively high stemflow estimates ranging from 29 

to 34 percent of rainfall. In order to have conservative stemflow 

estimates in the water budget, the high stemflow values from these 

sites were excluded from the calculated stemflow mean of 0.04 

used in the water budget. 

A map of mean annual wet canopy evaporation for the Hawaiian 

Islands (Giambelluca and others, 2014) was used to develop a 

regression model for estimating the spatial variability of V. This 

regression model was developed because estimates of V for sites 

in Hawaiʻi are rare, and because canopy-evaporation estimates 

from the water-budget model are sensitive to V. The wet canopy 

evaporation map has mean annual wet canopy evaporation estimates 

at a spatial resolution of about 14 acres. To derive a regression model 

for estimating V, we first selected grid cells from the islands of 

Kauaʻi, Oʻahu, and Maui that consisted of forest land-cover classes 

only, based on the LANDFIRE Existing Vegetation Type map (U.S. 

Geological Survey, 2010). Data from Kauaʻi and Maui were included 

in the analysis to supplement the data from Oʻahu and to provide the 

basis for a broadly applicable V value for Hawaiʻi. Next, for each of 

the selected grid cells, the calibrated V value needed for mean annual 

canopy evaporation from the Gash model for Kauaʻi, Oʻahu, and 

Maui to equal that of the wet canopy evaporation map of Giambelluca 

and others (2014) was determined. The Gash model was used with 

various V values to determine the calibrated V values for the selected 

grid cells. Last, associations between the calibrated V values and 

various other parameters of the selected grid cells, including estimates 

of mean annual rainfall, reference ET, Penman-Monteith ET from 

Giambelluca and others (2014), and estimates of mean annual wind 

speed from AWS Truewind, LLC (2004) were determined. 

Estimates of V from a linear regression model (equation 18) 

relating V to the quotient of mean annual wind speed and mean 

annual rainfall resulted in the best agreement, in terms of bias and 

root mean square error, between estimates of canopy evaporation 

from the wet canopy evaporation maps (Giambelluca and others, 

2014) and the estimates from the Gash model for Kauaʻi, Oʻahu, and 

Maui. The spatial distribution of V was estimated as follows:

for w < 0.009,

 V = 0.01,

for 0.009 ≤ w ≤ 0.192,

V = 2.677 × (w) – 0.014, and

for w > 0.192,

 V = 0.50, (18)

where

w = mean annual wind speed divided by mean 

 annual rainfall (m/s/in).

The variable w is the quotient of (1) mean annual wind speed, 

in meters per second, which was derived from a map of mean annual 

wind speed at height of about 100 ft above the land surface (AWS 

Truewind, 2004), and (2) 1978–2007 mean annual rainfall, in inches 
26 Spatially Distributed Groundwater Recharge Estimated Using a Water-Budget Model for the Island of O‘ahu, Hawai‘i

Table 6. Land-cover parameters used in water-budget calculations for the Island of O‘ahu, Hawai‘i.

Land-cover description

Root 

depth, 

in inches

Depletion 

fraction

Crop

coefficient

Canopy capacity, 

in inches

Trunk-storage capacity, 

in inches

Forest land covers

Alien forest 60 0.50 a0.33, b0.44 0.05 0.01

Native forest 30 0.50 0.30 0.05 0.01

Kiawe/Phreatophytes 71 1.00 0.84 0.05 0.01

Tree plantation 60 0.50 a0.33, b0.44 0.05 0.01

Nonforest land covers

Agriculture—

Coffee 48 0.40 0.91 0 0

Corn 18 0.60 c0.29–1.20 0 0

Diversified 10 0.35 1.00 0 0

Fallow/grassland 39 0.60 0.95 0 0

Macadamia 60 0.50 0.91 0 0

Pineapple 18 0.50 0.30 0 0

Taro 10 1.00 1.05 0 0

Developed—

Low-intensity 12 0.50 1.18 0 0

Medium-intensity 12 0.50 1.18 0 0

High-intensity 12 0.50 1.18 0 0

Golf course 30 0.50 0.85 0 0

Grassland 39 0.60 0.95 0 0

Shrubland 12 0.50 1.00 0 0

Sparsely vegetated 5 0.50 1.18 0 0

Wetland 39 0.50 1.18 0 0

All water bodies 1 1.00 1.05 0 0

a

Value used inside the fog zone, which is above 2,000 feet.

b

Value used outside the fog zone.

c

Varies by month (see Crop Coefficients section for explanation).

[Crop coefficients for forests are used to compute the sum of transpiration and ground evaporation; canopy evaporation is computed separately. Crop coefficients 

for nonforest land covers are used to compute the sum of all evaporative components; All water bodies, includes water bodies, reservoirs, and estuarine/nearcoastal water bodies]

(Giambelluca and others, 2013). In general, estimates of V for wet 

areas are less than those for dry areas. Grid cells that had calibrated 

V values that were outside the range of 0.01–0.50 were excluded 

from the derivation of equation 18. A range of 0.01–0.50 was 

established for this analysis on the basis of the range of published 

estimates of V. The low end of the range, 0.01, was determined 

by Hutjes and others (1990) for a humid, tropical forest site in the 

Ivory Coast. The high end of the range, 0.50, is the mean value 

reported by Safeeq and Fares (2012b) for a forest site on leeward 

Oʻahu. A similar range of mean V estimates (about 0.03–0.40) was 

determined for 54 sites located in various climate zones across 

Australia (Wallace and others, 2013, fig. 6c). An analysis of the 

sensitivity of the water-budget results to selected Gash-model 

parameters is included in the Sensitivity Analysis section of this 

report. 

Potential Evapotranspiration

Potential evapotranspiration (ET) is the maximum rate that 

water can be removed from the plant-root zone by ET if soil 

moisture is nonlimiting (Giambelluca, 1983). The actual-ET 

rate is a function of potential ET, soil-moisture content, and 

threshold-moisture content (see equation 13). The actual-ET rate 

becomes less than the potential rate with the onset of soil-moisture 

stress. As the soil dries, capillary and adsorptive forces bind the 

remaining water to the soil matrix, reducing water flow to roots. 

Soil-moisture stress occurs when the decreasing flow of water 

to the root system induces a response in the plant to slow down 

transpiration and prevent desiccation. The threshold-moisture 

content at which a plant begins to react to soil drying varies with 

the type of plant. 

Potential ET is controlled by atmospheric conditions, 

topography, and land-cover characteristics (Giambelluca, 

1983). Maps of mean monthly reference ET produced by 

Giambelluca and others (2014) were used in the water-budget 

model to estimate the influence of atmospheric conditions 

(radiation, air temperature, air humidity, and wind speed) 

on potential ET. Crop coefficients were used to estimate the 

integrated effects of land-cover and vegetation characteristics 

on potential ET. Potential ET for each subarea was calculated 
Model Input 27

in the water-budget model as the product of mean monthly 

reference ET and the crop coefficient assigned to the land 

cover, and was assumed to be constant within a given month 

(see equation 9).

Reference Evapotranspiration 

Reference ET, as defined in this study, is the potential ET 

of a hypothetical grass surface with specific characteristics and 

optimum soil-water conditions for given climatic conditions 

and is equivalent to FAO Penman-Monteith ET (Allen and 

others, 1998). Reference ET is similar to pan evaporation, 

which has been used in previous water budgets for Maui and 

other Hawaiian Islands. Both pan evaporation and reference 

Figure 8. Mean annual reference evapotranspiration for the Island of O‘ahu, Hawai‘i (modified from grass reference evapotranspiration in 

Giambelluca and others, 2014).

ET provide an index of the energy that is available for ET for 

a given area. 

Maps of mean monthly reference ET (Giambelluca 

and others, 2014) for Oʻahu were used in the water budget. 

These maps have the same grid resolution (about 14 acres) 

as the monthly rainfall maps. Mean annual reference ET 

ranges from about 32 to 112 in on Oʻahu (fig. 8). In general, 

mean annual reference ET is highest in dry lowland areas, 

and is lowest in wet upland areas within the cloud zone. In 

the water-budget calculation, monthly reference ET was not 

varied from year to year, and was assumed to equal mean 

monthly reference ET. Reference ET was assumed to be the 

same each day of a given month.

40

Mean annual 

reference evapotranspiration, 

in inches

32 

50

70

60

80

100

 112

90

EXPLANATION

Figure 8. Mean annual reference evapotranspiration for the Island of O‘ahu, Hawai‘i (modified from grass 

fiiiGiblld h2014) 

158°

158°10’

157°40’

157°50’

21°30’

21°20’

21°40’

0 5 10 MILES

0 5 10 KILOMETERS

Base modified from U.S. Geological Survey 

National Hydrography Dataset, 1:24,000,

Universal Transverse Mercator projection, 

zone 4, NAD83 datum. 
28 Spatially Distributed Groundwater Recharge Estimated Using a Water-Budget Model for the Island of O‘ahu, Hawai‘i

Crop Coefficients 

A crop coefficient is an empirically derived ratio of the 

potential ET of a certain type of land cover and reference 

ET. Crop coefficients provide an index of the integrated 

effect of vegetation characteristics (reflectance, roughness, 

and plant physiology) on potential ET. Crop coefficients 

were assigned to each land-cover class (table 6). Crop 

coefficients were assumed to be temporally constant for all 

classes other than corn. For nonforest land-cover classes, 

crop coefficients integrated the effects of transpiration, 

ground evaporation, and canopy evaporation. For forested 

land-cover classes, crop coefficients integrated the effects of 

transpiration and ground evaporation; canopy evaporation 

was accounted for separately (fig. 5). 

Crop coefficients for nonforest land covers (table 

6) were obtained from published values or were derived 

from pan coefficients used for the same or similar landcover classes in previous water budgets for Hawaiʻi. A 

Hawaiʻi pan coefficient for a given land cover is the ratio 

of potential ET to pan evaporation. Hence, pan coefficients 

are analogous to crop coefficients. Pan coefficients for 

land-covers other than sugarcane were converted to crop 

coefficients by dividing the pan coefficients by 0.85, a factor 

that Engott (2011) used to convert crop coefficients to pan 

coefficients. Crop coefficients for grassland, pineapple, 

taro, wetland, water body, and reservoir land covers were 

obtained from Allen and others (1998). The midpoint of 

the range of crop coefficients for grazing pasture (rotated 

grazing) was used for grassland. The mean of the crop 

coefficients for wetlands with no frost was used for 

wetland. The crop coefficient for open water in the tropics 

was used for taro, water body, and reservoir land covers. 

Crop coefficients for coffee and macadamia were obtained 

from Fares (2008). Crop coefficients for golf course and 

the developed land covers were derived from the pan 

coefficient used by Engott (2011) for developed land covers. 

Crop coefficients for diversified agriculture, shrubland, 

and sparsely vegetated land were also derived from pan 

coefficients used by Engott (2011). The crop coefficients 

for corn vary monthly and are based on information in 

the Hawaii Agricultural Water Use and Development Plan 

(University of Hawaiʻi, 2008). The crop coefficients used 

for corn were 0.85, 0.50, 0.29, 0.40, 0.80, 1.20, 0.85, 0.50, 

0.29, 0.40, 0.80, and 1.20 for the months of January through 

December, respectively.

Maps of mean soil (ground) evaporation and 

transpiration (Giambelluca and others, 2014) were used to 

derive crop coefficients for forest land covers. First, the 

water budgets for Kauaʻi, Oʻahu, and Maui were calculated 

using a range of crop coefficients for forest land covers. 

Next, the sum of ground evaporation and transpiration 

was determined for subareas on Kauaʻi, Oʻahu, and Maui 

with (1) native forest land cover inside of the cloud zone, 

(2) native forest land cover outside of the cloud zone, (3) 

alien forest land cover inside of the cloud zone, and (4) 

alien forest land cover outside of the cloud zone. The crop 

coefficients listed in table 6 resulted in the best match, in 

terms of ground evaporation plus transpiration, between the 

maps of Giambelluca and others (2014) and subareas with 

forest land covers in water budgets of Kauaʻi, Oʻahu, and 

Maui. The derived crop coefficient for alien forests within 

the cloud zone is less than that for alien forests outside 

the cloud zone. This difference could be related to spatial 

differences in tree species or reduced transpiration with the 

presence of fog. The crop coefficients for alien forests are 

also used for tree plantations. For native forests, one crop 

coefficient is used because the crop coefficient estimated 

for areas inside the cloud zone is nearly identical to that for 

areas outside of the cloud zone. 

Moisture-Storage Capacity of the Plant-Root Zone 

The moisture-storage capacity of the plant-root 

zone (fig. 9) was calculated as the product of available 

water capacity and root depth (equation 12). The USDA 

(2006a) soil map and corresponding tables of available 

water capacities were used to quantify the available water 

capacity of the soils on Oʻahu. For each soil unit, the 

tables list the minimum and maximum available water 

capacities for various ranges of depth. A depth-weighted 

mean available water capacity was calculated for each soil 

type in the water-budget model. However, all depths of the 

soil unit “rock outcrop” have zero available water capacity 

according to tables of USDA (2006a). For this study, zero 

available water capacity for the “rock outcrop” soil unit 

was considered too low because many areas with this soil 

unit on Oʻahu were mapped as grassland or shrubland. 

Therefore, for the water-budget calculations, available 

water-capacity values for the “rock land” soil unit were 

used for all subareas with the “rock outcrop” soil unit. The 

soil unit “rock land” was selected because it generally was 

mapped near “rock outcrop” soils and because its available 

water capacity exceeds zero in the top eight inches of soil. 

Subareas with water body and reservoir land covers have 

zero available water capacity at all soil depths and therefore 

have zero soil-moisture storage capacity (fig. 8).

Root depths for each land-cover class were assigned 

values on the basis of published values and root depths used 

in previous water budgets in the Hawaiian Islands (table 

6). The root depth used for pineapple is the middle of the 

range of pineapple root depths reported in Fares (2008) and 

Allen and others (1998). The root depth used for diversified 

agriculture is near the middle of the range reported in 

Fares (2008) for typical diversified agriculture crops in the 

Hawaiian Islands. The root depth used for taro is the middle 

of the range reported in Fares (2008). The root depth used 

for wetland is the same as that used for grassland. For all 

other land-cover classes, the root depths used are the same 

as those used by Engott (2011) in the water budget for the 

Island of Hawaiʻi. 
Model Input 29

Figure 9. Calculated moisture-storage capacity of the plant-root zone, Island of O‘ahu, Hawai‘i.

0.01 

Moisture-storage capacity, in inches

0

2.00

10.00

23.52

5.00

EXPLANATION

Figure 9. Calculated moisture-storage capacity of the plant-root zone, Island of O‘ahu, Hawai‘i.

158°

158°10’

157°40’

157°50’

21°30’

21°20’

21°40’

0 5 10 MILES

0 5 10 KILOMETERS

Base modified from U.S. Geological Survey 

National Hydrography Dataset, 1:24,000,

Universal Transverse Mercator projection, 

zone 4, NAD83 datum. 

Direct Recharge

For this study, direct recharge is defined as water that 

passes directly to the groundwater system, completely 

bypassing the plant-root zone (equation 15). Hence, direct 

recharge is not subject to direct runoff or ET processes. 

Direct recharge was estimated for subareas with water mains, 

cesspools and land covers that are typically saturated—taro, 

water bodies and reservoirs, and estuarine/near-coastal 

water bodies (fig. 4). For subareas within TMK parcels 

with cesspools, the wastewater effluent fluxes estimated by 

Whittier and El-Kadi (2009) were applied as direct recharge 

(see Septic-System Leaching section). The direct recharge 

rate from water bodies was set at 64 in/yr, on the basis of 

seepage estimates in Dugan and others (1975). For reservoirs, 

the direct recharge was set to 528 in/yr, which has been used 

in recent water budgets for Hawaiʻi (Engott and Vana, 2007; 

Engott, 2011). For estuarine/near-coastal water bodies, the 

recharge rate was set to zero, because these water bodies were 

assumed to produce no net recharge. 

Water-main leakage is another source of direct recharge. 

Water-main leakage on Oʻahu was estimated on the basis of maps 

and information supplied by the Honolulu Board of Water Supply. 

A detailed spreadsheet of water-main leaks and breaks on Oʻahu 

in 2007 (Carolyn Sawai, Honolulu Board of Water Supply, written 

commun., 2012) was used to estimate an average annual rate of 
30 Spatially Distributed Groundwater Recharge Estimated Using a Water-Budget Model for the Island of O‘ahu, Hawai‘i

water-main leakage. The total amount of water-main leakage on 

Oʻahu was estimated to be about 1.75 Mgal/d and was applied at 

a uniform rate, 0.01 in/day, along the length of each water main. 

The area subject to leakage was assumed to be 1 m on either side 

of a water-main centerline. A leakage rate of 1.75 Mgal/d is about 

1.2 percent of the average system flow rate, which is substantially 

lower than the typical average rate for a municipal water system—

about 10 percent (State of California, 2014). However, using the 

lower rate is conservative with regard to recharge estimation. 

The effect of using an estimate of water-main leakage consistent 

with 10 percent of average water-system flow is addressed in the 

Sensitivity Analysis section of this report.

Other Input

In addition to the water-budget inputs already listed, 

several other input parameter values were required. The 

initial moisture storage for the pervious fraction of subareas 

was set at 50 percent of the soil moisture-storage capacity. 

The rainfall-retention capacity for impervious surfaces was 

assumed to be 0.25 in. The initial moisture storage for the 

impervious fraction of subareas was set at 0.125 in, which is 

calculated as 50 percent of the rainfall-retention capacity of 

0.25 in. These values were also used for other recent Hawaiʻi 

water budgets (Izuka and others, 2005; Engott and Vana, 2007; 

Engott, 2011). The effects of these inputs on regional-scale 

mean annual recharge generally are minor because they either 

pertain to only a small area or are applicable during only a 

small fraction of time.

Model Exclusions and Limitations

Several exclusions were made to simplify the water-budget 

model. Re-infiltration of direct runoff, water that runs off one 

subarea and then infiltrates the plant-root zone of a different 

subarea, was not explicitly considered in the water-budget model. 

Re-infiltration of direct runoff within gaged basins was assumed to 

be included in streamflow records used to derive runoff-to-rainfall 

ratios. Spatial variations in the re-infiltration of direct runoff within 

a drainage basin, however, were not accounted for in the model. 

For example, if re-infiltration of direct runoff was considerable 

within streambeds, then recharge may have been underestimated 

in intra-channel (streambed) areas and overestimated in interchannel (nonstreambed) areas. Additionally, direct runoff from 

upland areas that seeps into the streambed of lower reaches near 

the coast was not quantified. Surface-water diversion systems, 

however, can reduce or prevent streambed seepage in lower 

reaches of certain streams on Oʻahu. 

Owing to the sparseness of data and the use of synthesized 

daily rainfall, the water-budget model did not reconstruct 

the actual distributions of the water-budget components 

(rainfall, fog interception, irrigation, septic-system leachate, 

runoff, evapotranspiration, and recharge) on Oʻahu for each 

simulated day. The reconstruction of actual daily runoff was 

also prevented by the use of seasonal runoff-to-rainfall ratios. 

Additionally, runoff may have been overestimated by the 

model on days with light rain and underestimated on days with 

intense rain. The water-budget model did, however, reproduce 

the spatial distribution of (1) monthly rainfall on Oʻahu during 

1978–2007 that was estimated by Frazier and others (2016), 

and (2) mean monthly and mean annual rainfall on Oʻahu 

during 1978–2007 that was estimated by Giambelluca and 

others (2014). For gaged drainage basins, the water-budget 

model reproduced seasonal runoff estimates that were based on 

streamflow measurements at stream-gaging stations.

Some parameters and conditions not included in the 

calculations of the water-budget model were inherent in other 

parameters used in the model. For example, the permeability 

and vertical hydraulic conductivity of the plant-root zone 

and underlying substrate were not included in the model 

calculations. Their effect on direct runoff, however, would 

be inherent in streamflow records used to derive runoff-torainfall ratios that were used to calculate direct runoff in 

the model. For subareas with forest land covers, a reduction 

in the potential ET of the plant-root zone in response to 

evaporation from the forest canopy was not included in the 

model calculations. However, the effects of forest-canopy 

evaporation on the potential-ET rate likely were accounted 

for in the forest crop coefficients, which were calibrated to the 

maps of mean transpiration and ground evaporation produced 

by Giambelluca and others (2014).

Some processes and conditions were excluded from the 

water-budget calculations. Potential ET was assumed to be 

uniform each day of the month and consequently may have 

been overestimated on cloudy days and underestimated on 

clear days. For subareas with impervious surfaces, potential 

ET was not reduced to account for evaporation from 

impervious surfaces. Adjustments to reference ET at scales 

less than the spatial resolution of the reference ET maps, 

such as those related to shading in rugged terrain, were not 

accounted for in the model. Other conditions not considered 

in the model include the variability of soil moisture with 

regard to depth within the soil root zone, the effect of soil 

texture on irrigation demand, and removal of water from 

saturated groundwater zones by transpiration. Additionally, 

daily irrigation estimates were based on monthly variations in 

rainfall, runoff, and potential ET instead of daily variations. 

The daily irrigation estimates of the water-budget model may 

also differ from actual irrigation rates because, in addition 

to the model not reproducing actual daily rainfall, the model 

does not account for other factors—such as field observations, 

nonirrigation water needs, and water availability—that may be 

considered by irrigation managers each day.

Datasets for calibrating recharge estimates of the model 

were not available. ET estimates of the model for forested 

areas, however, were calibrated to maps of actual ET produced 

by Giambelluca and others (2014). Additionally, runoff was 

estimated using an empirical model derived from streamflow 

records.
Water-Budget and Groundwater-Recharge Estimates 31

Water-Budget and GroundwaterRecharge Estimates

The water-budget model was used to calculate recharge 

for two scenarios: average climate conditions and drought 

conditions. Monthly rainfall during 1978–2007 was used for the 

average-climate-conditions scenario. Monthly rainfall during 

1998–2002 was used for the drought-conditions scenario. Both 

scenarios used 2010 land cover and mean monthly reference 

evapotranspiration. Water-budget estimates for average climate 

conditions are compared with previous estimates.

Water-Budget and Recharge Estimates for 

Average Climate Conditions

For the Island of Oʻahu, mean annual recharge is about 

660 Mgal/d for average climate conditions (table 7). Recharge 

is about 36 percent of precipitation and is about 34 percent of 

total inflow (sum of rainfall, fog interception, irrigation, septic 

leachate, and direct recharge). Direct recharge, which consists 

of leakage from water mains and seepage from reservoirs and 

cesspools, accounts for about 3 percent of overall recharge. 

Expressed as a depth of water uniformly distributed across 

the island, mean annual recharge is about 23 in. Mean annual 

recharge, in inches, is highest in the Central aquifer sector and 

lowest in the Waiʻanae aquifer sector (table 7). 

The spatial pattern of mean annual recharge on Oʻahu 

for average climate conditions resembles that of mean annual 

rainfall, but also reflects (1) spatial variations in vegetation 

and soils, (2) irrigation in agricultural and developed areas, (3) 

seepage from reservoirs, and (4) persistent cloud layers where 

fog interception supplements rainfall (fig. 10). Recharge is 

high along the crest of the Koʻolau Range, reaching as much as 

about 180 in/yr in the north-central part of the range. Relatively 

high recharge rates also occur in the higher elevations of the 

Waiʻanae Range, reaching as much as about 60 in/yr near 

the summit of Mt. Kaʻala. Recharge is much lower outside 

of the mountainous areas of the island. In undeveloped and 

nonagricultural areas at low elevation, recharge is commonly 

less than 5 in/yr. Detectable at these lower elevations are the 

footprints of irrigated agricultural fields and golf courses, which 

contribute higher rates of recharge than adjacent, unirrigated 

areas. Also detectable are small areas of very high recharge, 

which generally correspond to taro cultivation, reservoirs, or 

areas of high cesspool usage.

The estimated fraction of total water inflow that becomes 

groundwater recharge is shown in figure 11. For most of Oʻahu, 

the fraction is less than 40 percent. Apart from areas of taro 

cultivation and reservoirs, which have a fraction of 100 percent 

by definition, the areas with the highest fraction, over 60 percent, 

occur in the high rainfall areas of the Koʻolau Range. This roughly 

corresponds to the areas with high recharge. The consistently wet 

conditions keep the soil moisture high. Some notable areas with a 

fraction over 40 percent include (1) the wetter, higher elevations 

of the Waiʻanae Range; (2) the pineapple fields of central Oʻahu, 

where the low transpiration rate of the crop is responsible; and (3) 

patches of the ʻEwa Plain and leeward coast, where a combination 

of very low rates of runoff (fig. 7), low soil moisture storage 

capacity (fig. 9), and low total water inflow is responsible. 

Comparison with the Water Resources Protection 

Plan 

The 1990 Water Resources Protection Plan (WRPP; State 

of Hawaiʻi, 1990) included recharge estimates, in Mgal/d, for all 

aquifer systems on Oʻahu. Although not listed in the document, 

the 2008 WRPP (State of Hawaiʻi, 2008) used the same recharge 

values as the 1990 WRPP for most aquifer systems. However, 

recharge estimates for some aquifer systems were updated and 

some aquifer systems, as delineated in the 1990 WRPP, were split 

and (or) combined in the 2008 WRPP. Recharge estimates used in 

the 2008 WRPP were provided by the State Commission on Water 

Resource Management (CWRM; Roy Hardy, written commun., 

May 2014) . 

Recharge estimates reported in the 1990 WRPP were based 

on a water budget that considered mean annual rainfall, runoff, 

and ET. For comparison with results from this study, estimates 

of precipitation, runoff, and ET reported in the 1990 WRPP were 

converted from units of in/yr to Mgal/d on the basis of the aquifersystem areas provided by CWRM (table 8; Roy Hardy, written 

commun., May 2014). Because some of the 1990-WRPP aquifer 

systems were split and (or) combined in the 2008 WRPP, some 

recombining of aquifer systems, as delineated in the 2008 WRPP, 

was needed to compare water-budget components from the 1990 

WRPP with the results from this study (table 8). 

Caprock areas were excluded from the calculation of aquifersystem recharge in the 1990 WRPP. The spatial extent of caprock 

areas on Oʻahu, however, was not defined in the 1990 WRRP. In 

the 2008 WRPP, the ʻEwa caprock area was delineated (fig. 1), but 

other caprock areas were not. To facilitate comparison between 

recharge estimates from the 2008 WRPP and the estimates of 

this study, the caprock area was estimated to consist of all areas 

seaward of the 0-ft elevation contour of the top of the volcanicrock aquifer (fig. 1). This is water-budget-area description “B” 

in table 8. Because there was a small difference in the areas, the 

ʻEwa caprock area, as defined in the 2008 WRPP, was also used 

to compare study estimates for the Waipahu-Waiawa, ʻEwaKunia, and Makaīwa aquifer systems. This is water-budget area 

description “C” in table 8. 

Another complication in comparing recharge estimates 

from the 2008 WRPP and the estimates of this study concerns 

the redistribution of high-level recharge from the Wahiawā 

aquifer system to adjacent aquifer systems. According to 

the 2008 WRPP, 62 Mgal/d of recharge is allocated to the 

Waipahu-Waiawa aquifer system, 14 Mgal/d is allocated to 

the combined ʻEwa-Kunia and Makaīwa aquifer systems, and 

41 Mgal/d is allocated to the Waialua aquifer system. The 

Waialua allocation is calculated from information given in the 

2008 WRPP and the recharge estimates provided by CWRM 
32 Spatially Distributed Groundwater Recharge Estimated Using a Water-Budget Model for the Island of O‘ahu, Hawai‘i Location Condition/ Scenario Area, in square miles Water-budget component, in Mgal/d Recharge, in/yr Rain Fog Irr Septic Direct rech Runoff Canopy evap Total ET Storm drain Recharge Island of Oʻahu Average climate 595.84 1,821.35 10.63 114.75 1.32 20.71 264.77 237.90 1,015.44 39.96 660.21 23.27 Drought 1,346.58 7.94 129.21 1.32 20.71 190.48 198.94 894.77 20.23 417.34 14.71 Honolulu aquifer sector Average climate 84.99 240.61 0.74 19.97 0.04 2.11 28.58 36.52 147.29 15.57 73.62 18.19 Drought 179.15 0.53 22.31 0.04 2.11 21.08 30.58 131.93 8.38 44.78 11.07 Pearl Harbor aquifer sector Average climate 162.84 444.08 2.23 54.43 0.04 5.68 59.00 56.70 261.45 13.38 175.54 22.64 Drought 330.35 1.72 60.54 0.04 5.68 39.16 47.93 234.19 6.39 122.57 15.81 Waiʻanae aquifer sector Average climate 60.91 111.41 0.79 6.19 0.17 0.87 8.09 13.25 73.20 1.16 37.27 12.85 Drought 67.90 0.43 6.77 0.17 0.87 4.52 9.12 58.69 0.53 13.18 4.55 North aquifer sector Average climate 93.94 236.81 0.87 10.72 0.47 5.56 25.28 36.65 161.95 0.00 69.15 15.46 Drought 168.95 0.47 12.21 0.47 5.56 17.48 29.67 138.99 0.00 34.50 7.71 Central aquifer sector Average climate 68.82 303.50 3.74 2.12 0.00 3.00 63.32 36.89 118.45 2.28 129.07 39.39 Drought 242.19 3.00 2.49 0.00 3.00 50.79 32.42 106.80 1.25 93.22 28.45 Windward aquifer sector Average climate 124.35 484.94 2.26 21.32 0.60 3.49 80.50 57.89 253.10 7.57 175.56 29.65 Drought 358.04 1.79 24.89 0.60 3.49 57.45 49.22 224.17 3.68 109.09 18.43 Table 7. Mean annual water-budget components from this study for average climate and drought conditions for the Island of O‘ahu and for individual aquifer-sector areas. [See fig. 1 for locations of aquifer sectors; Mgal/d, million gallons per day; in/yr, inches per year; Irr, irrigation; Septic, septic-system leachate; Direct rech, direct recharge; Canopy evap, forest canopy evaporation; Total ET, total evapotranspiration which includes canopy evaporation. Average climate conditions for this study are 1978–2007 rainfall and 2010 land cover; drought conditions for this study are 1998–2002 rainfall and 2010 land cover. Components may not balance because of rounding and direct recharge from cesspools and reservoirs. The source of water for direct recharge may be from external sources, including groundwater and imported streamflow. Some recharge may discharge to streams as base flow. Ford and Sand Islands (fig. 2) are not included]
Water-Budget and Groundwater-Recharge Estimates 33

Aquifer 

sector Aquifer system Source of estimate Water- budget-area description Area, in square miles Condition/ Scenario Water-budget component, in Mgal/d Rain Fog Irr Septic Direct rech Runoff Canopy evap Total ET Storm drain Recharge

Honolulu Pālolo This study A 10.10 Average climate 28.27 0.09 3.05 0.01 0.25 3.14 3.30 17.81 2.85 8.28

This study A 10.10 Drought 21.66 0.06 3.35 0.01 0.25 2.42 2.83 16.51 1.73 5.12This study B 5.36 Average climate 21.31 0.09 0.75 0.01 0.07 2.70 3.25 11.07 1.20 7.24This study B 5.36 Drought 16.62 0.06 0.84 0.01 0.07 2.10 2.80 10.24 0.79 4.46WRPP D 4.43 Natural 17.29 n/a n/a n/a n/a 3.37 n/a 8.44 n/a 6

Nuʻuanu This study A 14.79 Average climate 55.82 0.24 1.86 0.02 0.79 8.21 7.80 29.13 2.71 18.62

This study A 14.79 Drought 44.94 0.18 2.05 0.02 0.79 6.64 6.91 27.04 1.61 12.73This study B 9.72 Average climate 47.53 0.24 0.41 0.02 0.64 7.57 7.75 22.31 0.87 17.85This study B 9.72 Drought 38.88 0.18 0.48 0.02 0.64 6.17 6.88 20.87 0.63 12.33WRPP D 8.62 Natural 41.45 n/a n/a n/a n/a 10.26 n/a 16.42 n/a 20

Kalihi This study A 9.83 Average climate 34.94 0.07 1.57 0.00 0.19 4.88 5.44 18.85 2.54 10.57

This study A 9.83 Drought 27.63 0.05 1.80 0.00 0.19 3.50 4.79 17.52 1.49 7.23This study B 6.57 Average climate 28.87 0.07 0.64 0.00 0.06 4.31 5.43 14.49 0.78 10.04This study B 6.57 Drought 23.22 0.05 0.75 0.00 0.06 3.11 4.78 13.55 0.52 6.88WRPP D 6.33 Natural 27.12 n/a n/a n/a n/a 6.03 n/a 12.05 n/a 12

Moanalua This study A 22.95 Average climate 63.16 0.19 5.91 0.00 0.50 7.25 9.40 38.64 4.03 20.79

This study A 22.95 Drought 47.49 0.14 6.54 0.00 0.50 5.28 8.14 34.82 2.04 13.65This study B 10.89 Average climate 46.68 0.19 0.79 0.00 0.01 6.23 9.29 22.84 0.53 18.05This study B 10.89 Drought 36.73 0.14 0.90 0.00 0.01 4.62 8.06 20.75 0.34 12.04WRPP D 10.92 Natural 41.07 n/a n/a n/a n/a 4.68 n/a 20.80 n/a 24

Waiʻalae-West This study A 7.30 Average climate 18.84 0.07 2.01 0.01 0.20 1.88 3.77 12.61 1.10 5.56

This study A 7.30 Drought 13.33 0.05 2.23 0.01 0.20 1.32 3.04 11.22 0.57 2.74This study B 4.73 Average climate 15.45 0.07 0.48 0.00 0.03 1.69 3.66 9.04 0.44 4.85This study B 4.73 Drought 11.08 0.05 0.54 0.00 0.03 1.20 2.96 7.94 0.25 2.31

Waiʻalae-East This study A 20.02 Average climate 39.58 0.08 5.57 0.00 0.18 3.22 6.81 30.25 2.34 9.80

This study A 20.02 Drought 24.10 0.05 6.34 0.00 0.18 1.92 4.87 24.82 0.94 3.31This study B 14.17 Average climate 31.31 0.08 2.07 0.00 0.12 2.71 6.44 21.53 1.23 8.11This study B 14.17 Drought 19.35 0.05 2.37 0.00 0.12 1.64 4.63 17.30 0.52 2.50

Table 8. Mean annual water-budget components from this study for average climate and drought conditions and components from the Water Resources Protection Plan (State of Hawai‘i, 1990; 2008) for aquifer-system areas on the Island of O‘ahu, Hawai‘i.[See fig. 1 for locations of aquifer systems. Mgal/d, million gallons per day; Irr, irrigation; Septic, septic-system leachate; Direct rech, direct recharge; Canopy evap, forest canopy evaporation; Total ET, total evapotranspiration, which includes forest-canopy evaporation. n/a, not accounted for or not reported. WRPP, Water Resources Protection Plan (State of Hawai‘i, 1990; 2008). Water-budget-area descriptions: A, entire aquifer-system area; B, entire aquifer-system area excluding areas seaward of the 0-ft elevation contour of the top of the volcanic-rock aquifer (see fig. 1); C, entire aquifer-system area excluding ʻEwa caprock areas (see fig. 1); D, aquifer-system used in WRPP. Average climate conditions for this study are 1978–2007 rainfall and 2010 land cover. Drought conditions for this study are 1998–2002 rainfall and 2010 land cover. Natural conditions for WRPP are 1916–83 mean rainfall and a uniform, unirrigated land cover. All WRPP water-budget components are from the 1990 WRPP, except where noted. Components may not balance because of rounding and direct recharge from cesspools and reservoirs. The source of water for direct recharge may be from external sources, including groundwater and imported streamflow. Some recharge may discharge to streams as base flow. Recharge estimates from this study do not include spillover from other aquifer-system areas]
34 Spatially Distributed Groundwater Recharge Estimated Using a Water-Budget Model for the Island of O‘ahu, Hawai‘i Aquifer sector Aquifer system Source of estimate Water- budget-area description Area, in square miles Condition/ Scenario Water-budget component, in Mgal/d Rain Fog Irr Septic Direct rech Runoff Canopy evap Total ET Storm drain Recharge Honolulu Waiʻalae-West and Waiʻalae-East combined This study

A 27.32 Average climate 58.42 0.15 7.58 0.01 0.38 5.10 10.58 42.86 3.44 15.36

This study

A 27.32 Drought 37.43 0.10 8.57 0.01 0.38 3.24 7.91 36.04 1.51 6.05

This study

B 18.89 Average climate 46.76 0.15 2.55 0.00 0.15 4.40 10.10 30.57 1.67 12.96

This study

B 18.89 Drought 30.43 0.10 2.91 0.00 0.15 2.84 7.59 25.24 0.77 4.81

WRPP

D 18.77 Natural 44.68 n/a n/a n/a n/a 4.47 n/a 33.06 n/a 6, 8a

Pearl 

Harbor

Waimalu This study

A 38.20 Average climate 153.27 0.86 5.33 0.01 0.13 22.81 23.53 70.16 4.06 62.81

This study

A 38.20 Drought 118.90 0.66 5.91 0.01 0.13 14.93 20.47 64.03 2.04 44.85

This study

B 31.48 Average climate 144.38 0.86 3.08 0.01 0.10 22.24 23.45 62.25 2.04 61.86

This study

B 31.48 Drought 113.15 0.66 3.46 0.01 0.10 14.56 20.42 57.02 1.14 44.56

WRPP

D 32.10 Natural 136.02 n/a n/a n/a n/a 19.87 n/a 61.13 n/a 63

WaipahuWaiawa This study

A 82.92 Average climate 231.64 1.11 38.86 0.02 4.25 33.01 26.43 141.02 6.97 96.60

This study

A 82.92 Drought 176.41 0.91 43.32 0.02 4.25 22.42 22.96 129.28 3.39 72.09

This study

B 60.47 Average climate 207.88 1.11 21.38 0.01 2.97 32.07 24.34 108.70 4.84 87.99

This study

B 60.47 Drought 163.04 0.91 24.11 0.01 2.97 21.92 21.66 100.38 2.52 66.75

This study

C 66.59 Average climate 214.75 1.11 22.70 0.00 3.05 32.36 24.90 115.14 5.62 89.26

This study

C 66.59 Drought 167.12 0.91 25.55 0.00 3.05 22.08 22.02 105.62 2.86 67.23

WRPP

D 60.72 Natural 215.97 n/a n/a n/a n/a 28.65 n/a 102.15 n/a 143, 139a, 77b

ʻEwa-Kunia This study

A 38.64 Average climate 55.08 0.26 9.64 0.01 1.29 2.97 6.53 47.20 2.25 14.69

This study

A 38.64 Drought 32.60 0.15 10.66 0.01 1.29 1.69 4.36 38.32 0.92 5.10

This study

B 26.12 Average climate 42.25 0.26 5.21 0.00 0.91 2.47 5.13 34.81 0.61 10.87

This study

B 26.12 Drought 25.46 0.15 5.83 0.00 0.91 1.43 3.51 27.87 0.26 3.30

This study

C 26.42 Average climate 42.56 0.26 5.28 0.00 0.91 2.48 5.16 35.04 0.65 10.98

This study

C 26.42 Drought 25.65 0.15 5.90 0.00 0.91 1.43 3.52 28.02 0.28 3.38

Makaīwa This study

A 3.07 Average climate 4.09 0.00 0.60 0.00 0.01 0.21 0.21 3.07 0.10 1.44

This study

A 3.07 Drought 2.44 0.00 0.65 0.00 0.01 0.12 0.14 2.56 0.04 0.53

This study

B 2.31 Average climate 3.23 0.00 0.09 0.00 0.01 0.17 0.20 2.04 0.02 1.11

This study

B 2.31 Drought 1.93 0.00 0.10 0.00 0.01 0.10 0.13 1.61 0.01 0.35

This study

C 2.78 Average climate 3.78 0.00 0.50 0.00 0.01 0.20 0.20 2.70 0.09 1.33

This study

C 2.78 Drought 2.26 0.00 0.54 0.00 0.01 0.11 0.14 2.23 0.03 0.48

ʻEwa-KuniaandMakaīwacombined

This study

A 41.71 Average climate 59.17 0.26 10.24 0.01 1.30 3.18 6.74 50.27 2.35 16.13

This study

A 41.71 Drought 35.04 0.15 11.31 0.01 1.30 1.81 4.50 40.88 0.96 5.63

This study

B 28.43 Average climate 45.48 0.26 5.30 0.00 0.92 2.64 5.33 36.85 0.63 11.98

This study

B 28.43 Drought 27.39 0.15 5.93 0.00 0.92 1.53 3.64 29.48 0.27 3.65

This study

C 29.20 Average climate 46.34 0.26 5.78 0.00 0.92 2.68 5.36 37.74 0.74 12.31

This study

C 29.20 Drought 27.91 0.15 6.44 0.00 0.92 1.54 3.66 30.25 0.31 3.86

WRPP

D 28.10 Natural 46.10 n/a n/a n/a n/a 3.11 n/a 33.68 n/a 22, 21a, 7b

Table 8.—Continued
Water-Budget and Groundwater-Recharge Estimates 35

Aquifer 

sector Aquifer system Source of estimate Water- budget-area description Area, in square miles Condition/ Scenario Water-budget component, in Mgal/d Rain Fog Irr Septic Direct rech Runoff Canopy evap Total ET Storm drain Recharge

Waiʻanae Nānākuli This study A 5.42 Average climate 9.29 0.05 0.35 0.01 0.08 0.58 1.09 6.04 0.13 3.02

This study A 5.42 Drought 5.75 0.03 0.38 0.01 0.08 0.34 0.75 4.82 0.06 1.06This study B 4.59 Average climate 8.22 0.05 0.09 0.00 0.01 0.53 1.05 5.12 0.04 2.69This study B 4.59 Drought 5.10 0.03 0.10 0.00 0.01 0.31 0.72 4.04 0.02 0.91WRPP D 4.67 Natural 6.89 n/a n/a n/a n/a 0.22 n/a 5.11 n/a 2

Lualualei This study A 23.97 Average climate 37.22 0.13 2.51 0.07 0.33 2.22 4.41 26.77 0.65 10.80

This study A 23.97 Drought 22.56 0.07 2.72 0.07 0.33 1.28 2.98 21.24 0.30 3.33This study B 15.30 Average climate 27.32 0.13 0.36 0.02 0.06 1.74 3.94 17.77 0.09 8.29This study B 15.30 Drought 16.66 0.07 0.40 0.02 0.06 1.01 2.67 13.76 0.04 2.52WRPP D 13.86 Natural 23.76 n/a n/a n/a n/a 1.32 n/a 17.82 n/a 5

Waiʻanae This study A 9.35 Average climate 18.14 0.21 1.15 0.04 0.27 1.44 2.13 11.12 0.27 7.09

This study A 9.35 Drought 10.90 0.11 1.22 0.04 0.27 0.83 1.47 9.00 0.12 2.79This study B 7.61 Average climate 16.23 0.21 0.64 0.03 0.17 1.35 2.06 9.44 0.09 6.43This study B 7.61 Drought 9.79 0.11 0.67 0.03 0.17 0.77 1.43 7.54 0.04 2.50WRPP D 7.66 Natural 13.86 n/a n/a n/a n/a 0.73 n/a 10.21 n/a 3

Mākaha This study A 9.50 Average climate 20.85 0.29 2.17 0.05 0.18 1.83 2.79 13.06 0.11 8.57

This study A 9.50 Drought 12.72 0.16 2.44 0.05 0.18 0.87 1.95 10.99 0.05 3.70This study B 7.77 Average climate 18.76 0.29 1.07 0.00 0.04 1.71 2.73 10.87 0.02 7.58This study B 7.77 Drought 11.48 0.16 1.21 0.00 0.04 0.80 1.92 9.03 0.01 3.10WRPP D 8.09 Natural 15.79 n/a n/a n/a n/a 0.77 n/a 11.94 n/a 4

Keaʻau This study A 12.67 Average climate 25.91 0.11 0.01 0.00 0.01 2.02 2.83 16.21 0.00 7.79

This study A 12.67 Drought 15.97 0.06 0.01 0.00 0.01 1.20 1.97 12.64 0.00 2.30This study B 11.42 Average climate 23.95 0.11 0.00 0.00 0.01 1.89 2.78 14.83 0.00 7.34This study B 11.42 Drought 14.76 0.06 0.00 0.00 0.01 1.12 1.93 11.59 0.00 2.20WRPP D 11.33 Natural 21.04 n/a n/a n/a n/a 1.08 n/a 15.64 n/a 5

North Mokulēʻia This study A 34.89 Average climate 73.69 0.85 3.30 0.07 0.74 5.97 11.96 51.64 0.00 21.60

This study A 34.89 Drought 44.95 0.46 3.81 0.07 0.74 3.45 8.46 41.01 0.00 6.72This study B 27.49 Average climate 61.73 0.85 0.15 0.00 0.14 5.19 11.49 39.99 0.00 17.69This study B 27.49 Drought 37.76 0.46 0.18 0.00 0.14 3.01 8.14 30.84 0.00 5.06WRPP D 33.22 Natural 72.75 n/a n/a n/a n/a 4.74 n/a 53.77 n/a 16

Waialua This study A 21.40 Average climate 40.65 0.00 6.08 0.14 3.40 3.58 3.17 34.19 0.00 13.45

This study A 21.40 Drought 28.94 0.00 6.88 0.14 3.40 2.54 2.67 30.35 0.00 7.82This study B 18.36 Average climate 36.12 0.00 3.21 0.01 2.63 3.32 3.03 28.24 0.00 11.02This study B 18.36 Drought 26.07 0.00 3.73 0.01 2.63 2.38 2.57 24.87 0.00 6.12WRPP D 17.19 Natural 36.83 n/a n/a n/a n/a 2.46 n/a 27.01 n/a 8, 49a, 8b

Table 8.—Continued
36 Spatially Distributed Groundwater Recharge Estimated Using a Water-Budget Model for the Island of O‘ahu, Hawai‘i Aquifer sector Aquifer system Source of estimate Water- budget-area description Area, in square miles Condition/ Scenario Water-budget component, in Mgal/d Rain Fog Irr Septic Direct rech Runoff Canopy evap Total ET Storm drain Recharge North Kawailoa This study

A 37.65 Average climate 122.47 0.02 1.34 0.26 1.42 15.73 21.52 76.12 0.00 34.10

This study

A 37.65 Drought 95.06 0.01 1.52 0.26 1.42 11.49 18.54 67.63 0.00 19.96

This study

B 35.19 Average climate 117.68 0.02 0.86 0.13 0.97 15.38 21.21 71.62 0.00 32.92

This study

B 35.19 Drought 91.60 0.01 0.98 0.13 0.97 11.24 18.30 63.77 0.00 19.25

WRPP

D 35.69 Natural 144.43 n/a n/a n/a n/a 20.39 n/a 67.97 n/a 56

Central Wahiawā This study

A 68.82 Average climate 303.50 3.74 2.12 0.00 3.00 63.32 36.89 118.45 2.28 129.07

This study

A 68.82 Drought 242.19 3.00 2.49 0.00 3.00 50.79 32.42 106.80 1.25 93.22

WRPP

D 68.87 Natural 327.89 n/a n/a n/a n/a 59.02 n/a 131.16 n/a 138

Windward Koʻolauloa This study

A 41.19 Average climate 173.89 1.46 8.42 0.19 1.00 21.04 21.75 88.35 0.00 76.24

This study

A 41.19 Drought 130.86 1.16 9.76 0.19 1.00 15.16 18.59 79.80 0.00 48.80

This study

B 30.56 Average climate 148.19 1.46 0.84 0.01 0.09 17.50 20.15 63.94 0.00 69.12

This study

B 30.56 Drought 113.10 1.16 0.99 0.01 0.09 12.76 17.35 57.55 0.00 44.93

WRPP

D 32.57 Natural 165.92 n/a n/a n/a n/a 32.56 n/a 62.02 n/a 71

Kahana This study

A 18.45 Average climate 101.88 0.24 0.29 0.09 0.24 21.38 11.62 38.57 0.00 43.24

This study

A 18.45 Drought 80.08 0.20 0.32 0.09 0.24 15.91 10.29 35.17 0.00 30.48

This study

B 16.40 Average climate 95.74 0.24 0.05 0.01 0.05 20.18 11.17 33.74 0.00 42.13

This study

B 16.40 Drought 75.60 0.20 0.05 0.01 0.05 15.06 9.92 30.89 0.00 29.92

WRPP

D 16.24 Natural 109.02 n/a n/a n/a n/a 49.48 n/a 30.93 n/a 29

Koʻolaupoko This study

A 29.71 Average climate 125.51 0.45 3.14 0.19 1.11 23.83 15.19 64.33 3.24 39.08

This study

A 29.71 Drought 92.63 0.35 3.91 0.19 1.11 17.40 13.12 57.09 1.73 22.31

This study

B 26.58 Average climate 116.22 0.45 2.38 0.11 0.87 22.15 14.85 57.82 2.61 37.45

This study

B 26.58 Drought 86.13 0.35 3.03 0.11 0.87 16.25 12.85 51.55 1.40 21.49

WRPP

D 27.22 Natural 125.71 n/a n/a n/a n/a 33.69 n/a 51.84 n/a 40

Waimānalo This study

A 35.00 Average climate 83.66 0.11 9.47 0.13 1.14 14.25 9.33 61.85 4.33 17.00

This study

A 35.00 Drought 54.47 0.08 10.90 0.13 1.14 8.98 7.22 52.11 1.95 7.50

This study

B 18.81 Average climate 52.95 0.11 2.41 0.04 0.22 9.25 8.43 33.18 1.16 12.11

This study

B 18.81 Drought 35.29 0.08 2.83 0.04 0.22 5.99 6.58 27.09 0.54 5.00

WRPP

D 19.60 Natural 64.39 n/a n/a n/a n/a 10.26 n/a 37.33 n/a 17, 13a

aUpdated value used in the 2008 WRPP (Roy Hardy, CWRM, written commun., May 2014).bUpdated value used in the 2008 WRPP (Roy Hardy, CWRM, written commun., May 2014) with spillover removed.

Table 8.—Continued
Water-Budget and Groundwater-Recharge Estimates 37

Figure 10. The distribution of mean annual recharge for average climate conditions (1978–2007), calculated using the water-budget model, Island 

of O‛ahu, Hawai‛i. 

10

20

0

30

40

100

200

150

300

50

Mean annual groundwater recharge, 

in inches

Areas where mean annual recharge 

is between 455 and 528 inches– 

includes taro fields and reservoirs, which 

are difficult to see at this scale

Boundaries of named aquifer systems 

(modified from State of Hawai̒i, 2008)

EXPLANATION

158°

158°10’

157°40’

157°50’

21°30’

21°20’

21°40’

0 5 10 MILES

0 5 10 KILOMETERS

Base modified from U.S. Geological Survey 

National Hydrography Dataset, 1:24,000,

Universal Transverse Mercator projection, 

zone 4, NAD83 datum. 
38 Spatially Distributed Groundwater Recharge Estimated Using a Water-Budget Model for the Island of O‘ahu, Hawai‘i

Figure 11. Estimated fraction of total water inflow that becomes groundwater recharge in the water-budget simulation for average climate conditions 

on the Island of O‛ahu, Hawai‛i.

20

0.1

0

40

80

99

60

EXPLANATION

Fraction of water inflow (rainfall, 

fog, irrigation, septic leachate, 

and direct recharge) that 

becomes recharge, in percent

Boundaries of named aquifer systems 

(modified from State of Hawaiÿi, 2008)

Figure 11. Estimated fraction of total water inflow that becomes groundwater recharge in the water-budget 

simulation for average climate conditions on the Island of Oÿahu.

158°

158°10’

157°40’

157°50’

21°30’

21°20’

21°40’

0 5 10 MILES

0 5 10 KILOMETERS

Base modified from U.S. Geological Survey 

National Hydrography Dataset, 1:24,000,

Universal Transverse Mercator projection, 

zone 4, NAD83 datum. 
Water-Budget and Groundwater-Recharge Estimates 39

(Roy Hardy, written commun., May 2014). These allocations, 

termed spillover in the 2008 WRPP, are included in the 

recharge estimate for each of these systems in the 2008 WRPP. 

For purposes of comparison, spillover is subtracted from the 

WRPP-recharge estimates in table 8. 

As shown on table 8, water-budget-area description B 

approximates the areas given in the WRPP fairly well for most 

aquifer systems. Overall water-budget area is about 466 mi2 in 

the WRPP and about 461 mi2 for water-budget-area description 

B in this study. Owing to this, the remainder of this section 

will compare recharge estimates from the WRPP with recharge 

estimates from this study for water-budget-area description B, 

except for the Wahiawā aquifer system, which will be compared 

using water-budget-area description A because no caprock occurs 

in this area.

Island-wide, the recharge estimate in this study for average 

climate conditions, 612 Mgal/d for water-budget area B, is very 

close to the WRPP recharge estimate of 608 Mgal/d. However, 

differences in recharge estimates are substantial for some aquifer 

systems. Recharge estimates from this study are higher than 

estimates in the WRPP for 12 of the 21 aquifer systems compared 

(includes recombined aquifer systems; table 8). Small area 

inconsistencies aside, the reasons for differences in the recharge 

estimates are related to methods and datasets used to estimate 

individual water-budget components (table 9). The 1990 WRPP 

states that ET was estimated as (1) 40 in/yr for areas where mean 

rainfall was at least 55 in/yr, and (2) 73 percent of rainfall for 

areas where mean rainfall was less than 55 in/yr. In this study, 

ET is calculated daily on the basis of available mean monthly 

potential ET, soil moisture, vegetative cover, and soil type. The 

runoff-rainfall relations used to estimate runoff in the WRPP were 

developed from streamflow measurements without subtracting 

base flow. In contrast, base flow was subtracted from streamflow 

measurements when developing the runoff-rainfall relations 

for this study. Fog interception is included in this study, but 

not in the WRPP. Rainfall estimates of the WRPP are based on 

1916–83 mean isohyets (Giambelluca and others, 1986), whereas 

estimates of this study are based on 1978–2007 monthly rainfall 

maps (Frazier and others, 2016). Different spatial extrapolation 

techniques were used to prepare these two rainfall datasets; 

therefore, the difference in the rainfall values for any given area 

may not be attributable only to the different periods of record. 

Additionally, the WRPP did not account for septic leachate, 

irrigation, and direct recharge from reservoirs, cesspools, and 

water-main leaks. 

The recharge estimates of this study are substantially 

higher than estimates of the WRPP for the aquifer systems in the 

Waiʻanae aquifer sector, including Keaʻau, Mākaha, Waiʻanae, 

Lualualei, and Nānākuli (table 8). Estimates from this study 

are 35 to 114 percent higher than the WRPP estimates for these 

aquifer systems. The primary reason for the higher recharge 

estimates is the substantially higher rainfall in the Frazier and 

others (2016) monthly rainfall maps compared to Giambelluca 

and others (1986). The recharge estimate from this study is 

Table 9. Important differences between the recharge-estimation methods used in this study and the recharge-estimation methods used in the Water 

Resources Protection Plan (State of Hawai‛i, 1990)

1

All other factors being equal. 

2

Includes water-main leakage and seepage from cesspools, reservoirs, and other water bodies.

3

Both studies assumed certain areas of aquifer systems, generally near the coast, did not contribute recharge to the volcanic-rock aquifer

Factor This study WRPP

Effect on amount of recharge 

estimated in this study relative to 

the WRPP recharge estimate1

Time step Daily Annual More

Irrigation Included Not included More

Fog interception Included Not included More

Septic-system leachate Included Not included More

Direct recharge2 Included Not included More

Storm-drain capture Included Not included Less

Direct runoff Estimated as the difference between streamflow and base flowEstimated as being equal 

to streamflow (without 

subtracting base flow

More

Total evapotranspiration 

(ET)

Estimated using potential ET, soil moisture, 

and land-cover and soil properties; canopyevaporation is separately estimated and 

included for forests

Estimated on the basis 

of mean annual rainfall; 

canopy evaporation is not 

separately estimated

Indeterminate (depends on area 

being considered)

Rainfall 1978–2007 monthly rainfall (Frazier and 

others, 2016)

1916–1983 mean annual 

rainfall (Giambelluca and 

others, 1986)

Indeterminate (depends on area 

being considered)

Excluded parts of 

aquifer systems3

Defined Not explicitly defined Indeterminate (excluded areas not 

explicitly defined in the WRPP)

[WRPP, Water Resources Protection Plan (State of Hawaiʻi, 1990)]
40 Spatially Distributed Groundwater Recharge Estimated Using a Water-Budget Model for the Island of O‘ahu, Hawai‘i

Table 10. Comparison of water-budget components from this study with components from a previous study for various areas of the Island of O‛ahu, 

Hawai‛i.

also substantially higher for the combined Waiʻalae-East and 

Waiʻalae-West aquifer systems. Higher rainfall estimates in 

Frazier and others (2016), lower total ET, and lower runoff are 

responsible for the 62 percent higher recharge calculated in this 

study for these combined aquifer systems. For the Kahana aquifer 

system, in which this study estimates 45 percent more recharge 

than the WRPP, rainfall in Frazier and others (2016) is actually 

much lower than the WRPP estimate. However, runoff is more 

than twice as high in the WRPP versus this study, leading to a 

higher recharge estimate in this study. The recharge estimate of 

this study is 41 percent lower than the estimate of the WRPP 

for the Kawailoa aquifer system. Lower rainfall in the Frazier 

and others (2016) monthly rainfall maps is the primary reason 

for the lower recharge estimate. Removing spillover from the 

WRPP estimates of recharge for the Waialua, Waipahu-Waiawa, 

and combined ʻEwa-Kunia and Makaīwa aquifer systems, yields 

recharge estimates of 8, 77, and 7 Mgal/d, respectively (table 8). 

Recharge estimates from this study are 38, 14, and 71 percent 

higher, respectively, for these aquifer systems. The primary reason 

for the higher recharge estimates for these areas is the inclusion of 

irrigation, which is left out of the WRPP water budget. 

Comparisons with Other Relevant Studies 

Comparisons of recharge for average climate conditions 

estimated in this study are compared with estimates from Shade 

and Nichols (1996) for the mid-1980s (table 10). Because of 

the substantial changes in agricultural land use and associated 

irrigation practices that occurred in north-central and southern 

Oʻahu between the mid-1980s and 2010, comparisons for these 

Location Source of 

estimate

Condition/

Scenario

Area, in 

square 

miles

Water-budget component, in Mgal/d

Rain Fog Irr Septic Direct 

rech Runoff Canopy evap

Total 

ET

Storm 

drain Recharge

Waiʻanae 

Aquifer 

Sector

This study Average 

climate

60.91 111.40 0.79 6.19 0.17 0.86 8.09 13.25 73.20 1.16 37.27

Shade and 

Nichols 

(1996)

Mid-1980s 60.91 103 n/a n/a n/a n/a 8 n/a 63 n/a 32

Windward 

Aquifer 

Sector

This study Average 

climate

124.35 484.94 2.26 21.32 0.59 3.49 80.50 57.88 253.10 7.57 175.55

Shade and 

Nichols 

(1996)

Mid-1980s 124.47 536 n/a n/a n/a n/a 100 n/a 238 n/a 198

Waiʻalae-East 

and West 

Aquifer 

Systems

This study Average 

climate

27.32 58.42 0.15 7.58 0.01 0.38 5.10 10.58 42.86 3.44 15.36

Shade and 

Nichols 

(1996)

Mid-1980s 28.44 62 n/a n/a n/a n/a 7 n/a 36 n/a 19

[See fig. 1 for locations of aquifer sectors and systems; Mgal/d, million gallons per day; Irr, irrigation; Septic, septic-system leachate; Direct rech, direct 

recharge; Canopy evap, forest canopy evaporation; Total ET, total evapotranspiration, which includes forest-canopy evaporation; Average climate conditions 

for this study are 1978–2007 rainfall and 2010 land cover; conditions for Shade and Nichols (1996) are 1916–83 rainfall and mid-1980s land cover; n/a, not 

accounted for or not reported. Components may not balance because of rounding and direct recharge from cesspools and reservoirs. The source of water for 

direct recharge may be from external sources, including groundwater and imported streamflow. Some recharge may discharge to streams as base flow]

areas were not deemed relevant. Estimated recharge for the 

Waiʻanae aquifer sector is about 16 percent higher in this study 

than in Shade and Nichols (1996). The primary reason for the 

difference is the inclusion of irrigation, mostly for developed 

land covers, in this study; Shade and Nichols (1996) did not 

include any irrigation. The sum of rainfall, total ET, and runoff 

is nearly equal in the two studies. Estimated recharge for the 

Windward aquifer sector is about 11 percent lower in this study 

than in Shade and Nichols (1996). The inclusion of irrigation 

in this study is not enough to compensate for the lower rainfall, about 10 percent, and higher ET, about 6 percent, compared 

with Shade and Nichols (1996). Estimated recharge for the 

combined Waiʻalae-East and Waiʻalae-West aquifer systems is 

19 percent lower in this study than in Shade and Nichols (1996). 

Because the sum of rainfall, total ET, and runoff is nearly equal 

in the two studies, the difference in recharge can be attributed to 

the inclusion of storm-drain capture in this study. For the three 

locations compared in table 10, total ET in this study is always 

higher than Shade and Nichols (1996).

Because of their importance to the overall water budget, 

estimates of ET from this study are compared to the latest 

estimates from Giambelluca and others (2014). For the Island of 

Oʻahu, mean annual total ET for this study for average climate 

conditions is about 1,015 Mgal/d, which is 16 percent more than 

mean annual ET from Giambelluca and others (2014). Compared 

to ET estimates of Giambelluca and others (2014), the mean 

annual total ET estimates in this study are (1) about 13 percent 

higher for subareas mapped as grassland, (2) about 1 percent 

lower for subareas mapped as shrubland, (3) about 8 percent 

higher for subareas mapped as native forest, alien forest, or tree 
Water-Budget and Groundwater-Recharge Estimates 41

plantation, (4) about 33 percent higher for subareas mapped as 

developed, and (5) about 5 percent lower for subareas mapped 

as sparsely vegetated. ET estimates for forests were expected to 

be close because forest crop coefficients and canopy evaporation 

were calibrated to ET datasets of Giambelluca and others (2014). 

However, they were calibrated using data that included all 

forests on Kauaʻi and Maui, as well as Oʻahu. The differences in 

mean annual ET estimates may be related to differences in base 

periods, computational methods, and soil-moisture estimates. For 

example, in areas where ET estimates are much greater than those 

of Giambelluca and others (2014), the estimated amount of soil 

moisture available for ET may be greater than that estimated by 

Giambelluca and others (2014), allowing for a greater volume of 

ET with all other conditions being equal. On the other hand, in 

areas where ET estimates of the water budget are less than those 

of Giambelluca and others (2014), the estimated amount of soil 

moisture available for ET in the water-budget model may be less. 

Recharge for Drought Conditions

To assess the impact of drought conditions on recharge, 

rainfall during 1998–2002 was selected to represent drought 

conditions on Oʻahu because this period had the lowest 5-yr mean 

rainfall during 1978–2007. Other than rainfall, all water-budget 

inputs used to calculate recharge for drought conditions were the 

same as those used for average climate conditions. Because the 

fog-to-rainfall ratios used for average climate conditions were also 

used for drought conditions, fog-interception rates for drought 

conditions were less than those for average climate conditions. 

For the Island of Oʻahu, recharge for drought conditions 

is about 417 Mgal/d, which is about 37 percent lower than 

recharge for average climate conditions (table 7). Aquifersystem precipitation for drought conditions ranges from 20 to 

41 percent lower than corresponding precipitation for average 

climate conditions (table 8). Aquifer-system recharge for drought 

conditions is about 25 to 70 percent lower than corresponding 

recharge for average climate conditions. The reduction in recharge 

for drought conditions, as a percentage (fig. 12), tends to be more 

pronounced in areas with lower mean rainfall. The reduction in 

recharge is directly related to the reduction in precipitation relative 

to average climate conditions, except in areas with inflows from 

irrigation, septic-system leachate, and direct recharge. 

Sensitivity Analysis

Uncertainty exists in many of the water-budget inputs used 

in this study. The inputs used in the water-budget calculations 

were considered to be those most reasonable. To analyze the 

effect that uncertainty in water-budget inputs has on estimated 

recharge, the water-budget model was rerun, changing one 

input value at a time within a reasonable range. The parameters 

tested were (1) available water capacity, (2) fog interception-torainfall ratios, (3) root depth, (4) runoff-to-rainfall ratios, (5) crop 

coefficient, (6) canopy capacity, (7) ratio of mean evaporation rate 

to mean precipitation rate during saturated canopy conditions,

V, and (8) storm-drain systems. For available water capacity, the 

high and low published values (USDA, 2006a) were tested. For 

fog interception-to-rainfall ratios and root depths, the “baseline” 

ratios and values, respectively, used in water-budget calculations 

for average climate and drought conditions were increased by 

50 percent and decreased by 50 percent. Runoff-to-rainfall ratios 

were adjusted on the basis of bias and root-mean-square-error 

statistics (for Oʻahu) of the runoff regression models (table 5). For 

crop coefficients, baseline values were increased by 20 percent 

and decreased by 20 percent. Canopy-storage capacity values of 

0.08 and 0.02, corresponding to an increase and decrease of 0.03 

from the baseline value, were tested. Values for V were increased 

by 0.1 units and were decreased by 0.1 units. For the latter case, 

however, V was assumed to be no less than 0.01. A water-main 

leakage rate of 15 Mgal/d, equal to 10 percent of the average 

system flow rate, was tested. Finally, the effect of storm-drain 

collection in medium- and high-intensity developed land covers 

was tested by “turning off” storm drains, meaning that the excess 

water, Wi, that flows off the impervious fraction of a subarea flows 

to the pervious fraction of that subarea, instead of being collected 

in the storm drain.

The recharge estimates for the sensitivity analysis are 

compared with recharge estimates for average climate conditions 

for Mākaha, Waipahu-Waiawa, Nuʻuanu, Waimānalo, and 

Kawailoa aquifer systems (table 11). These five aquifer systems 

cover a range of climates and land covers on Oʻahu. The Mākaha 

aquifer system is representative of the drier, leeward side of the 

Waiʻanae Range. Its land cover is dominated by mostly alien 

forest and grassland. The Waipahu-Waiawa aquifer system is 

representative of south-central Oʻahu and the Pearl Harbor area. It 

encompasses a wide variety of land cover and climate conditions 

and is very important to the municipal water supply of the island. 

The Nuʻuanu aquifer is representative of southeast, leeward 

O‘ahu. The aquifer system extends from the urban center of 

Honolulu up to the crest of the Koʻolau Range. Its land cover is 

mostly high- to medium-intensity developed at lower elevations 

and alien and native forest at higher elevations; the rainfall 

gradient is steep. The Waimānalo aquifer system is representative 

of the windward side of the Koʻolau Range and encompasses 

a wide variety of land covers. The Kawailoa aquifer system is 

representative of the northern side of the island. Alien and native 

forest dominate the upper elevations, and the lower elevations are 

mostly grass and shrubland with some low-intensity development 

near the coast. 

 For the Mākaha aquifer system, the parameters with the 

largest effects on recharge are root depth and V. Both of these 

parameters are related to ET and demonstrate the importance of 

ET, especially canopy evaporation, in drier, forested areas.

For the Waipahu-Waiawa aquifer system, the parameter 

with the largest effect on recharge is V. Changes to all other 

parameters have small effects—less than 7 percent—on 

recharge. The wide variety of land cover and climate may be 

responsible for the relatively small changes to recharge. 

For the Nuʻuanu aquifer system, three parameters have 

substantial effects on recharge: runoff-to-rainfall ratios, stormdrain capture, and V. In the wetter, forested uplands of this aquifer 
42 Spatially Distributed Groundwater Recharge Estimated Using a Water-Budget Model for the Island of O‘ahu, Hawai‘i

Figure 12. The percentage difference in mean annual recharge for drought conditions (1998−2002) relative to average climate conditions, 

calculated using the water-budget model, Island of O‘ahu, Hawai‘i.

Difference in mean annual recharge 

for drought conditions, relative to that 

for average climate conditions, 

in percent

0

4

–10

–50

–25

–75

–100

Boundaries of named aquifer systems 

(modified from State of Hawai‘i, 2008)

EXPLANATION

Figure 12. The percentage difference in mean annual recharge for drought conditions (1998− 2002) relative to

average climate conditions, calculated using the water-budget model, Island of O‘ahu, Hawai‘i.

158°

158°10’

157°40’

157°50’

21°30’

21°20’

21°40’

0 5 10 MILES

0 5 10 KILOMETERS

Base modified from U.S. Geological Survey 

National Hydrography Dataset, 1:24,000,

Universal Transverse Mercator projection, 

zone 4, NAD83 datum. 
Suggestions for Future Study and Additional Data Collection 43

Table 11. Results of sensitivity testing for selected water-budget parameters performed for selected aquifer systems on the Island of O‘ahu, Hawai‘i.

Parameter Adjusted parameter value Percentage difference in recharge 

Mākaha Waipahu-Waiawa Nu‘uanu Waimānalo Kawailoa

Available water capacity Low reported value1 -2.3 -0.8 -0.9 -2.3 -1.2

High reported value1 2.6 1.0 1.2 3.1 1.4

Fog interception-to-rainfall 

ratios

150% of baseline 1.3 0.5 0.5 0.3 0.0

50% of baseline -1.3 -0.5 -0.5 -0.3 0.0

Root depth 150% of baseline -4.8 -2.8 -2.4 -8.5 -3.9

50% of baseline 10.3 5.5 4.6 16.5 7.9

Runoff-to-rainfall ratios Regression bias adjustment2 -0.1 0.1 0.3 12.6 -0.1

Increase by regression 

RMSE3

-6.7 -4.3 -14.7 -27.5 -12.9

Decrease by regression 

RMSE3

6.2 4.1 14.9 30.4 13.6

Crop coefficients 120% of baseline -4.7 -3.9 -8.8 -7.6 -11.0

80% of baseline 6.5 4.8 10.0 10.7 14.3

Canopy capacity Increase by 0.03 units -2.4 -4.7 -7.6 -5.4 -7.6

Decrease by 0.03 units 1.8 3.3 5.8 4.4 5.9

Ratio of the mean 

evaporation rate to mean 

precipitation rate during 

saturated conditions, V

Increase by 0.1 units -8.0 -12.9 -15.6 -11.9 -17.3

Decrease by 0.1 units 8.3 8.4 13.7 11.9 17.4

Water-main leakage Increase system leakage rate 

to 15 Mgal/d4

0.2 0.3 0.4 0.5 0.1

Storm-drain capture off 1.2 6.5 13.3 23.2 0.0

[See fig.1 for locations of aquifer systems; baseline parameters are those used for average climate conditions; %, percent; RMSE, root mean square error of 

regional-runoff regression; see table 5 for RMSE and bias for Oʻahu]

1

Low and high values reported in U.S. Department of Agriculture (2006a).

2

For leeward areas, runoff-to-rainfall ratios were increased by 1.0 and decreased by 13.8 percent for the wet and dry seasons, respectively. For windward 

areas, runoff-to-rainfall ratios were decreased by 33.0 and 28.8 percent for the wet and dry seasons, respectively.

3

For leeward areas, runoff-to-rainfall ratios were adjusted by 0.06 and 0.07 units for the wet and dry seasons, respectively. For windward areas, runoff-torainfall ratios were adjusted by 0.12 and 0.09 units for the wet and dry seasons, respectively.

4

The value of 15 Mgal/d represents 10% of the average flow through the water system.

system, runoff and canopy evaporation are important to the water 

budget. In the lower, urban area, storm-drain capture is important. 

For the Waimānalo aquifer system, four parameters have 

substantial effects on recharge: root depth, runoff-to-rainfall 

ratios, storm-drain capture, and V. The uncertainty in the runoffto-rainfall ratio regression is higher on the windward side of the 

island than on the leeward side (table 5), resulting in a greater 

change in recharge compared to the other aquifer systems 

tested. The relatively large percentage of developed land cover 

is responsible for the considerable sensitivity to storm-drain 

capture.

For the Kawailoa aquifer system, three parameters have 

substantial effects on recharge: runoff-to-rainfall ratios, crop 

coefficients, and V. The large percentage of forest, nearly all 

of which lies outside of the fog zone, is responsible for the 

sensitivity to the canopy-evaporation parameter, V. Relatively 

high rainfall in the higher elevations leads to substantial 

sensitivity to runoff ratios.

Suggestions for Future Study and 

Additional Data Collection

Lack of data or sparse, uneven distribution of data in space 

and time, and poor understanding of some hydrologically relevant 

processes limit the accuracy of study results. This section discusses 

information that could advance future efforts to more accurately 

assess the distribution of groundwater recharge on Oʻahu. 

Rainfall is an essential dataset for estimating recharge. 

Although Oʻahu has a higher number of rain gages per square mile 

than most other Hawaiian Islands, the placement of gages and their 

periods of operation have been dictated by the water-supply needs 

of humans—particularly agriculture (Giambelluca and others, 

1986). Rain gages are scarce in areas that are less populated or 

unfavorable for agriculture, such as in the high-elevation interiors 

of islands or areas having rugged terrain. Estimates of rainfall for 

these areas thus have a greater degree of uncertainty (Giambelluca 
44 Spatially Distributed Groundwater Recharge Estimated Using a Water-Budget Model for the Island of O‘ahu, Hawai‘i

and others, 2013), yet these tend to be the wettest areas of the 

islands and the areas where most recharge occurs. Recharge 

estimates in areas can be improved with rainfall data from these 

sparsely gaged areas. The number of rain gages, however, has 

decreased sharply in the past 30 years, particularly as a result of 

the discontinuation of gage networks that were maintained by 

large sugarcane and pineapple plantations and associated irrigation 

companies (Giambelluca and others, 2013).

Fog-interception data are particularly scant. Fog interception 

provides a substantial part of the water available for groundwater 

recharge over large areas of the Hawaiian Islands, but has been 

quantified by only a few studies in a few places. As a result, foginterception distribution was applied in a very generalized fashion 

in the recharge calculation. Recharge estimates can be improved 

with a better quantification of the spatial and temporal variability 

of fog-interception rates, and the ability of different types of 

vegetation to intercept fog. 

An acknowledged limitation of the water-budget model is 

that monthly reference ET is uniformly distributed among each 

day of the month, regardless of the daily rainfall distribution over 

the month. In reality, reference ET should be lower during cloudy, 

rainy days than during sunny days. Recharge estimates could 

be improved with more measurements of the daily variations of 

reference ET across the study area. 

Another ET-related limitation of this study is the current lack 

of data needed to more accurately differentiate ET parameters 

among native and alien species of plants. Replacement of native 

forest by invasive alien plants like strawberry guava (Psidium 

cattleianum) is a problem on Oʻahu. More data could be used to 

develop better crop coefficients for native and alien plants. These 

improvements would help to better estimate the difference in 

recharge that could be expected in native versus alien dominated 

forests. 

The accuracy of the modified Gash canopy-interception 

model used in this study is limited by the quantity, quality, and 

spatial distribution of data used to develop model parameters. 

Field measurements of one parameter, the ratio of the mean 

evaporation rate to the mean precipitation rate during saturated 

canopy conditions (V), are especially lacking. Additional 

measurements of canopy-evaporation and related parameters 

could be used to better confirm and calibrate the canopyevaporation estimates of the modified Gash model.

Runoff is perhaps the most uncertain parameter in the 

recharge analysis. The runoff-to-rainfall ratio method in the waterbudget model in this study was improved by developing regression 

equations relating the ratio to drainage-basin characteristics, 

and using these equations to extrapolate the ratios from gaged 

to ungaged basins. However, because the number of ungaged 

basins was far greater than the number of gaged basins, ratios had 

to be extrapolated to some ungaged basins having characteristic 

values that were beyond the range of values used to develop the 

regression equations. Stream-gage data from more basins with 

a wider range of characteristic values are needed to improve the 

regression approach to regionalizing runoff-to-rainfall ratios. 

The runoff-to-rainfall ratio method used in the water-budget 

model in this study was also improved by varying the ratios on 

a seasonal basis with rainfall. Concurrent daily direct runoff and 

high-resolution rainfall data could improve the understanding of 

the processes controlling temporal variability in runoff estimates. 

Results of the regional-regression analysis suggest that runoff 

in windward and leeward basins differ statistically. Better 

understanding of the physical basis of this statistical difference 

would improve conceptualization of runoff processes.

The water-budget model used in this study applies the runoffto-rainfall ratios at the catchment-zone level, that is, ratios do not 

vary spatially within a catchment zone, even though the catchment 

zone may encompass a variety of land covers, soil types, slopes, 

and a range of climates. The catchment-zone-level application 

of runoff-to-rainfall ratios limits the ability of the model to 

assess differences in runoff and groundwater recharge that may 

exist between different areas within the catchment zone, such as 

between forested and deforested areas. Part of the limitation stems 

from the scarcity of studies assessing the variation in runoff rates 

for different vegetation, soil, and slope characteristics in Hawaiʻi. 

In a study comparing adjacent deforested rangeland and reforested 

areas on the south slope of Haleakalā, Maui, Perkins and others 

(2012; 2014) found that the reforested areas had soil hydraulic 

properties that favored rapid and deep infiltration of water. This 

finding suggests that runoff would be lower from the forested 

area than from the deforested area of their study, but the study did 

not measure runoff. Better understanding of the processes and 

distribution of hydrogeological characteristics at the catchmentzone scale are important for answering questions that are often 

posed about watershed management, such as the effect of forest 

restoration on water resources.

Summary and Conclusions

The main objective of this study was to determine the spatial 

distribution of mean annual groundwater recharge for the Island of 

Oʻahu. Recharge was calculated with a water-budget model that 

used a daily computational interval to simulate the hydrological 

processes and physical conditions that affect recharge. 

Hydrological processes and physical conditions on Oʻahu were 

defined using the most current datasets available—including 

maps of 2010 land cover, 1978–2007 monthly rainfall, and mean 

monthly reference ET. Monthly rainfall was disaggregated into 

daily rainfall using the method of fragments and daily rainfall 

records from 47 rain gages. The water-budget model and the 

most current datasets available were used to estimate the spatial 

distribution of mean annual groundwater recharge for two 

scenarios, (1) average climate conditions, based on 2010 land 

cover and rainfall during 1978–2007, and (2) drought conditions, 

based on 2010 land cover and rainfall during 1998–2002.

For the Island of Oʻahu, mean annual recharge is about 

660 Mgal/d for average climate conditions. Expressed as a 

uniform depth over the entire area of the island, recharge 

for average climate conditions is about 23.3 in/yr. Recharge 

is about 36 percent of precipitation (sum of rainfall and fog 

interception) and is about 34 percent of total inflow (sum of 
References Cited 45

precipitation, irrigation, septic-system leachate, and direct 

recharge). Recharge is high along the crest of the Koʻolau 

Range, reaching as much as about 180 in/yr in the northcentral part of the range. Relatively high recharge rates 

also occur in the higher elevations of the Waiʻanae Range, 

reaching as much as about 60 in/yr near the summit of Mt. 

Kaʻala. Recharge is much lower outside of the mountainous 

areas of the island. In undeveloped and nonagricultural areas 

at low elevation, recharge is commonly less than 5 in/yr. In 

general, areas that have water inflows from irrigation, septicsystem leaching, and direct recharge have more recharge 

than nearby areas without these supplemental water inflows. 

On the basis of assumptions made regarding caprock areas 

and the spillover of high-level recharge in the 2008 WRPP, 

the island-wide estimate of groundwater recharge for average 

climate conditions from this study is within 1 percent of the 

recharge estimate used in the 2008 WRPP. Recharge estimates 

from this study are higher for 12 of the aquifer-system areas 

and lower for 9. Differences in mean rainfall distribution and 

the inclusion of irrigation in this study are the primary reasons 

for differences in recharge estimates between this study and the 

2008 WRPP. Compared to ET estimates of Giambelluca and 

others (2014), ET estimates of this study are about 16 percent 

higher island-wide. This difference is largely attributable to 

higher ET estimates for developed and grassland land covers 

in this study, which are about 33 and 13 percent higher, 

respectively.

Mean annual recharge on Oʻahu for drought conditions is 

about 417 Mgal/d, which is about 37 percent lower than recharge 

for average climate conditions. Expressed as a uniform depth 

over the entire area of the island, recharge for drought conditions 

is about 14.7 in/yr. Aquifer-system precipitation for drought 

conditions ranges from 20 to 41 percent less than corresponding 

precipitation for average climate conditions. Aquifer-system 

recharge for drought conditions ranges from 25 to 70 percent 

lower than corresponding recharge for average climate conditions. 

The spatial distribution of rainfall is the primary factor 

determining the spatial distribution of recharge for most 

areas on Oʻahu. In forested areas, recharge estimates are 

also sensitive to forest-canopy evaporation. In drier areas, 

recharge estimates are more sensitive to parameters that 

are related to ET, such as root depths and crop coefficients, 

whereas in wetter areas, recharge estimates are more 

sensitive to runoff-to-rainfall ratios. Additional collection 

and analysis of precipitation, ET, runoff, and soils data are 

necessary to better understand the hydrological processes 

that affect recharge across Oʻahu.

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Menlo Park Publishing Service Center, California

Manuscript approved for publication December 1, 2017

Edited by Katherine Jacques

Design and layout by Cory Hurd
Engott and others—Spatially Distributed Groundwater Recharge for 2010 Land Cover Estimated Using a Water-Budget Model for the Island of O‘ahu, Hawai‘i—

Scientific Investigations Report 2015–5010 (ver. 2.0)

https://doi.org/10.3133/sir20155010

ISSN 2328-0328 (online)