Häwï

Kawaihae

Waimea

Hilo

Kailua

Captain Cook

Pähala

Volcano

Honokaÿa

Mauna Kea

Mauna Loa

Hualälai

d

d

d

Pähoa

U.S. Department of the Interior

U.S. Geological Survey

Scientific Investigations Report 2011–5078

A Water-Budget Model and Assessment of 

Groundwater Recharge for the Island of Hawai‘i
COVER: Map of the Island of Hawaiÿi showing the relative distribution of estimated mean annual 

recharge for baseline conditions. Estimated recharge is shown using a spectral color scale with 

red representing very low recharge and violet representing very high recharge. White areas 

represent zero estimated recharge. 
 

Scientific Investigations Report 2011–5078

U.S. Department of the Interior

U.S. Geological Survey

A Water-Budget Model and Assessment of 

Groundwater Recharge for the Island of Hawai‘i

By John A. Engott 
U.S. Department of the Interior

KEN SALAZAR, Secretary

U.S. Geological Survey

Marcia K. McNutt, Director

U.S. Geological Survey, Reston, Virginia: 2011

This report and any updates to it are available online at:

http://pubs.usgs.gov/sir/2011/5078/

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copyright owners to reproduce any copyrighted materials contained within this report.

Suggested citation:

Engott, J.A., 2011, A water-budget model and assessment of groundwater recharge for the 

Island of Hawai‘i: U.S. Geological Survey Scientific Investigations Report 2011–5078, 53 p.
 iii

Concern surrounding increasing demand for groundwater on the Island of Hawai‘i, caused by a growing population 

and an increasing reliance on groundwater as a source for 

municipal and private water systems, has prompted a study of 

groundwater recharge on the island using the most current data 

and accepted methods. This report documents the development 

of a daily water-budget model for computing groundwater 

recharge for the entire Island of Hawai‘i and the application 

of the model to estimate mean recharge for various land-cover 

and rainfall conditions. The development of a submodel for 

the Kona area and the application of the model to estimate 

historical groundwater recharge in the Kona area during the 

period 1984–2008 also are documented. Recharge estimates 

from this study are compared to recharge estimates used by the 

State of Hawai‘i Commission on Water Resource Management 

(CWRM) in setting the sustainable yields (maximum allowable pumping rates) of Hawai‘i aquifer systems in the 2008 

version of the Water Resource Protection Plan (2008 WRPP). 

Groundwater Recharge on Hawai‘i

Estimated mean annual recharge on the Island of Hawai‘i 

is 6,594 million gallons per day, which is about 49 percent of 

mean annual rainfall. Recharge is highest on the windward 

slopes of Mauna Loa, below the tradewind inversion, and lowest on the leeward slopes of Kohala and Mauna Kea (fig. ES1). 

Local recharge maxima also occur on (1) the higher elevations of windward Kohala, (2) windward Mauna Kea below 

the tradewind inversion, (3) windward Kïlauea, (4) the middle 

elevations of southeastern Mauna Loa, and (5) the lower 

middle elevations of leeward Mauna Loa and southwestern 

Hualälai, in the Kona area. Local recharge minima also occur 

on (1) Mauna Kea and Mauna Loa, above the tradewind inversion, (2) the northern tip of Kohala, (3) leeward Kïlauea, (4) 

the southern tip of Mauna Loa, and (5) the northwestern slopes 

of Mauna Loa and Hualälai. 

In 18 of the 24 aquifer systems on the island, mean 

annual recharge estimated in this study for baseline conditions 

was higher than the recharge estimates used in the 2008 WRPP 

(fig. ES2). Baseline conditions for this study were 2008 land 

cover and mean annual rainfall from the period 1916–1983. 

The higher recharge estimates for most areas in this study 

generally are attributable to differences in the methods used 

to estimate runoff and ET, the inclusion of fog interception in 

this study, and the shorter time step used in this study. Substantially lower estimates of recharge were calculated for the 

Mähukona, Waimea, and Häwï aquifer systems—38, 34, and 

29 percent lower, respectively. These lower estimates mainly 

are due to much higher ET estimates in this study compared to 

the 2008 WRPP. This may be cause for concern, because these 

particular areas are experiencing a growth in development and 

a related growth in water demand. For the drought simulation performed in this study, the estimates of recharge for all 

three of these aquifer systems were substantially less than the 

sustainable yields of the aquifer systems set by CWRM.

Recent projections of change in rainfall owing to effects 

of ongoing climate change generally indicate a slight increase 

in islandwide rainfall, and estimates of annual recharge in the 

late 21st century are higher than baseline estimates for every 

aquifer system, except ÿAnaehoÿomalu. On average, these 

aquifer-system recharge estimates are higher by about 8 percent compared to baseline estimates. 

Recharge in the Kona Area (1984–2008)

For the Kona submodel, the period 1984–2008 was broken into five subperiods to simplify calculation: 1984–1988, 

1989–1993, 1994–1998, 1999–2003, and 2004–2008. Groundwater recharge was highest during 2004–8 and lowest during 

1999–2003 (fig. ES3). Estimated mean annual recharge during 

1999–2003 was only 50 percent of estimated recharge during 

2004–8. These extremes coincided with the periods of lowest 

and highest mean rainfall, respectively. On a monthly basis, 

average recharge during the entire 1984–2008 period was 

highest in January and lowest in August; however, no clear 

seasonal pattern is discernible. Spatially, the highest recharge 

occurred in a belt about 4 miles wide running parallel to the 

coast about 2 miles inland.

Executive Summary
0 10 20 30 40 50 100 200150 300

EXPLANATION

Mean annual groundwater recharge, in inches

0 10 20 Miles

0 10 20 Kilometers

Base modified from U.S. Geological Survey 

National Hydrography Dataset, 1:24,000,

Universal Transverse Mercator projection, 

zone 5, NAD83 datum.

MAUNA LOA

MAUNA KEA

HUALÄLAI

KÏLAUEA

KOHALA

156°

155°

155°20'

155°40'

20°

19°40'

19°20'

19°

Hilo

Waimea

Näÿälehu

Pähoa

Keaÿau

ÿÖlaÿa

Kaÿapuna

Onomea

ÿAnaehoÿomalu

Manukä

Kïholo

Ka Lae

Kalapana

Hakalau

Paÿauilo

Kealakekua

Keauhou

Keaïwa

Honokaÿa

Mähukona

Hilina

Häwï

Waimanu

Kapäpala

PREVAILING

WIND

DIRECTION

iv

Figure ES1. Distribution of mean annual groundwater recharge for baseline conditions on the Island of Hawaiÿi calculated 

using the water-budget model. Areas of zero recharge appear as white. Boundaries of named aquifer systems (State of 

Hawaiÿi, 2008) are shown in gray. The generalized boundaries of the surface rocks of the five volcanoes forming the island 

are shown in white.
156°

155°

155°20'

155°40'

20°

19°40'

19°20'

19°

0 10 20 Miles

0 10 20 Kilometers

Hilo

Waimea

Näÿälehu

Pähoa

Keaÿau

ÿÖlaÿa

Kaÿapuna

Onomea

ÿAnaehoÿomalu

Manukä

Kïholo

Ka Lae

Kalapana

Hakalau

Paÿauilo

Kealakekua

Keauhou

Keaïwa

Honokaÿa

Mähukona

Hilina

Häwï

Waimanu

Kapäpala

− 29

+4

− 38

− 11

− 11

+7

+24

− 34

+3

+2

+60

+166

+78

+49

+183

+73

+108

+207

− 8

+36

+264

+140

+77

+84

EXPLANATION

Difference in estimated recharge 

relative to estimate from Water 

Resource Protection Plan 

(State of Hawai‘i, 2008), in percent

Less than zero

Greater than zero

and less than 100

Greater than 100

Base modified from U.S. Geological Survey 

National Hydrography Dataset, 1:24,000,

Universal Transverse Mercator projection, 

zone 5, NAD83 datum.

 v

Figure ES2. Relative difference, by aquifer system, between the recharge calculated in this study and the recharge used 

in the Water Resource Protection Plan (State of Hawai‘i, 2008).
155 ̊40’

155 ̊50’

156 ̊

19 ̊40’

19 ̊50’

19 ̊30’

19 ̊20’

EXPLANATION

Mean annual groundwater 

recharge, in inches

0

150

50

100

40

30

20

10

0 10 Miles

0 10 Kilometers

1984–88 1989–93 1994–98

1999–2003 2004–08

Base modified from U.S. Geological 

Survey National Hydrography Dataset, 

1:24,000, Universal Transverse Mercator 

projection, zone 5, NAD83 datum.

vi

Figure ES3. Distribution of estimated mean annual groundwater recharge during five time periods between 1984 and 2008

calculated using the water-budget model for the Kona area of the Island of Hawaiÿi. Areas of zero recharge appear as white.
 vii

Contents

Executive Summary....................................................................................................... iii

Groundwater Recharge on Hawai‘i......................................................................... iii

Recharge in the Kona Area (1984–2008)............................................................... iii

Conversion Factors and Abbreviations .......................................................................... xi

Acronyms....................................................................................................................... xi

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

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

Purpose and Scope.................................................................................................2

Previous Investigations............................................................................................2

Acknowledgments ...................................................................................................2

Description of the Island of Hawaiÿi ................................................................................2

Physical Setting.......................................................................................................2

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

Hydrogeology ..........................................................................................................7

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

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

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

Conceptual Model ..................................................................................................9

Model Exclusions and Assumptions........................................................................9

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

Model Input...................................................................................................................12

Land-Cover Map....................................................................................................12

Rainfall ..................................................................................................................12

Mean Rainfall .................................................................................................12

Temporal Variability ........................................................................................12

Fog Interception ....................................................................................................13

Irrigation ................................................................................................................15

Agricultural Irrigation ......................................................................................15

Urban-Landscape Irrigation............................................................................15

Runoff....................................................................................................................15

Runoff Zones..................................................................................................17

Runoff-to-Rainfall Ratios ................................................................................20

Computation of Runoff from Streamgage Data..............................................20

Evapotranspiration.................................................................................................20

Canopy Evaporation and Net Precipitation ....................................................22

Potential Evapotranspiration...........................................................................23

Pan Evaporation ............................................................................................23

Pan Coefficients......................................................................................25

Moisture-Storage Capacity....................................................................................26

Direct Recharge ....................................................................................................28

Other Input ............................................................................................................28

Model Randomness......................................................................................................28
viii

Groundwater-Recharge Estimates ...............................................................................34

Baseline Recharge................................................................................................34

Comparison to Water Resources Protection Plan..........................................36

Drought Conditions................................................................................................36

Replacement of Alien Forest with Native Forest ...................................................38

Future Urbanization...............................................................................................38

Climate Change.....................................................................................................38

Kona-Area Submodel ............................................................................................41

Historical ........................................................................................................41

1984–2008..............................................................................................41

Hypothetical Scenarios ..................................................................................43

Baseline ..................................................................................................43

Drought Conditions .................................................................................43

Future Urbanization ................................................................................46

Climate Change ......................................................................................46

Sensitivity Analysis................................................................................................46

Suggestions for Future Study and Additional Data Collection......................................48

Summary and Conclusions ..........................................................................................48

References Cited..........................................................................................................49

Figures

ES1. Map showing the distribution of mean annual groundwater 

recharge for baseline conditions on the Island of Hawaiÿi .................................. iv

ES2. Map showing the relative difference, by aquifer system, between 

the recharge calculated in this study and the recharge used in the 

Water Resource Protection Plan .........................................................................v

ES3. Maps showing the distribution of estimated mean annual groundwater 

recharge during five time periods between 1984 and 2008 ............................... vi

1. Map of the Island of Hawaiÿi showing major geographical features and 

the generalized extent of the surface rocks of the five volcanoes that 

form the island.....................................................................................................3

2. Map showing aquifer-systems (State of Hawaiÿi, 2008), judicial districts, 

and the Kona water-budget area .........................................................................4

3. Map showing mean annual rainfall and locations of rain gages used 

in the water-budget calculation for the Island of Hawaiÿi......................................6

4. Map showing land cover on the Island of Hawaiÿi................................................8

5. Generalized water-budget flow diagrams for both forest and 

nonforest land covers ..........................................................................................9

6. Maps showing the rain-gage stations and the seven rainfall-variability 

zones used to simulate annual variability of rainfall on the Island of Hawaiÿi ....13

7. Map showing areas of fog contribution to the water budget 

on the Island of Hawaiÿi .....................................................................................16

8. Map showing runoff zones defined for the water-budget calculation 

on the Island of Hawaiÿi .....................................................................................19
 ix

9. Graph showing analysis of the linear relation between net precipitation and 

fog interception in forests, based on data from studies in the Hawaiian 

Islands and similar tropical locations around the world........................................22

10. Map showing mean annual pan evaporation and pan-evaporation zones 

defined for the water-budget calculation on the Island of Hawaiÿi ........................24

11. Map showing calculated moisture-storage capacity on the Island of Hawai‘i.......27

12. Chart showing the average absolute percentage change in recharge of all 

the water-budget subareas with each successive model simulation....................28

13. Map showing the distribution of mean annual groundwater recharge for 

baseline conditions on the Island of Hawaiÿi calculated using the 

water-budget model .............................................................................................29

14. Map showing the estimated fraction of total water inflow that becomes 

groundwater recharge in the water-budget simulation for mean annual 

recharge for baseline conditions on the Island of Hawai‘i....................................35

15. Map showing the relative difference, by aquifer system, between the 

recharge calculated in this study and the recharge used in the Water 

Resource Protection Plan ....................................................................................37

16. Map showing the distribution of mean annual groundwater recharge for 

drought conditions on the Island of Hawaiÿi .........................................................39

17. Maps showing three possible distributions of mean annual groundwater 

recharge during the late 21st century ..................................................................42

18. Vertical bar plot showing estimated groundwater recharge during five 

historical time periods for the Kona area of the Island of Hawai‘i............................43

19. Maps showing the distribution of estimated mean annual groundwater 

recharge during five time periods between 1984 and 2008.................................44

20. Vertical bar graph showing average ratio of observed to mean annual 

rainfall for the eight gages used to simulate historical rainfall for the 

Kona-area water-budget submodel......................................................................46

Tables

1. Previous water-budget investigations for the Island of Hawai‘i.................................5

2. Ratios of observed rainfall to mean rainfall for rain gages used to simulate 

interannual variability in the water-budget model for the Island of Hawai‘i.............14

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

for the Island of Hawai‘i..........................................................................................17

4. Land-cover parameters used in water-budget calculations for the 

Island of Hawaiÿi.....................................................................................................18

5. Ratios of runoff to rainfall used in the water-budget model for the 

Island of Hawaiÿi.....................................................................................................21

6. Ratios of monthly to annual pan evaporation for each pan-evaporation 

zone used in the water-budget calculation for the Island of Hawaiÿi.......................23

7. Mean annual water-budget estimates for baseline and possible future 

conditions for each aquifer system on the Island of Hawaiÿi...................................30

8. Comparison of the baseline water budget calculated in this study with 

other studies for selected aquifer systems on the Island of Hawai‘i.......................38

9. Parameters used for the simulation of late-21st-century rainfall 

conditions on the Island of Hawai‘i.........................................................................40
x

10. Linear-regression statistics for normalized pan evaporation versus 

normalized rainfall used for the climate-change analysis for the 

Island of Hawai‘i.....................................................................................................41

11. Mean annual water-budget estimates for selected historical and hypothetical 

land-cover and rainfall conditions in the Kona area of the Island of Hawaiÿi...........43

12. Mean monthly water budgets during five time periods for the Kona area 

of the Island of Hawaiÿi...........................................................................................45

13. Results of sensitivity testing for selected water− budget parameters 

performed for Onomea, Keauhou, and Waimea aquifer systems on the 

Island of Hawai‘i.....................................................................................................47
Conversion Factors and Abbreviations

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

cubic foot per second (ft3

/s) 0.02832 cubic meter per second (m3/s)

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

/s)

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as follows:

°F = (1.8 × °C) + 32

Temperature in degrees Fahrenheit (°F) may be converted to degrees Celsius (°C) as follows:

°C = (°F − 32) ⁄ 1.8

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 Hawai‘i Commission on Water Resource Management

ET Evapotranspiration

GAP Gap Analysis Program

GIS Geographic Information System

HDWS County of Hawai‘i Department of Water Supply

IPCC Intergovernmental Panel on Climate Change

LUPAG County of Hawai‘i Land Use Pattern Allocation Guide

NCDC National Climatic Data Center

NWS National Weather Service

RAWS Remote Automated Weather Station

SCAN Soil Climate Analysis Network

USDA U.S. Department of Agriculture

USGS U.S. Geological Survey

WRPP State of Hawai‘i Water Resource(s) Protection Plan

 xi
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A Water-Budget Model and Assessment of 

Groundwater Recharge for the Island of Hawai‘i

By John A. Engott

Abstract

Concern surrounding increasing demand for groundwater on the Island of Hawai‘i, caused by a growing population 

and an increasing reliance on groundwater as a source for 

municipal and private water systems, has prompted a study 

of groundwater recharge on the island using the most current 

data and accepted methods. For this study, a daily waterbudget model for the entire Island of Hawai‘i was developed 

and used to estimate mean recharge for various land-cover 

and rainfall conditions, and a submodel for the Kona area 

was developed and used to estimate historical groundwater 

recharge in the Kona area during the period 1984–2008. 

Estimated mean annual recharge on the Island of Hawai‘i 

is 6,594 million gallons per day, which is about 49 percent of 

mean annual rainfall. Recharge is highest on the windward 

slopes of Mauna Loa, below the tradewind inversion, and 

lowest on the leeward slopes of Kohala and Mauna Kea. Local 

recharge maxima also occur on (1) windward Kohala, with the 

exception of the northern tip, (2) windward Mauna Kea below 

the tradewind inversion, (3) windward Kïlauea, (4) the middle 

elevations of southeastern Mauna Loa, and (5) the lowermiddle elevations of leeward Mauna Loa and southwestern 

Hualälai, in the Kona area. Local recharge minima also occur 

on (1) Mauna Kea and Mauna Loa, above the tradewind inversion, (2) the northern tip of Kohala, (3) leeward Kïlauea, (4) 

the southern tip of Mauna Loa, and (5) the northwestern slopes 

of Mauna Loa and Hualälai.

In 18 of the 24 aquifer systems on the island, estimated mean annual recharge for baseline conditions was 

higher than the recharge estimates used in the 2008 State 

of Hawai‘i Water Resource Protection Plan (2008 WRPP). 

Baseline conditions for this study were 2008 land cover and 

mean annual rainfall from the period 1916–1983. Estimates 

of recharge for the Mähukona, Waimea, and Häwï aquifer 

systems, however, were between 29 and 38 percent lower 

than the 2008 WRPP estimates, mainly because of much 

higher evapotranspiration estimates in this study compared 

to the 2008 WRPP. For the drought simulation (1991–95 

rainfall), the estimates of recharge for these three aquifer 

systems were only 15 to 33 percent of the sustainable yields 

(maximum allowable pumping rates) set by the 2008 WRPP. 

This may be cause for concern, as these areas are experiencing a rapid growth in development and a related growth in 

water demand.

Recent projections of change in rainfall owing to effects 

of ongoing climate change generally indicate a slight increase 

in islandwide rainfall, and estimates of annual recharge in the 

late 21st century are higher than baseline estimates for every 

aquifer system, except ÿAnaehoÿomalu. On average, these 

aquifer-system recharge estimates are higher by about 8 percent compared to baseline estimates. 

In the Kona area, estimated groundwater recharge during 

the period 1984–2008 was highest during 2004–8 and lowest 

during 1999–2003, with the 1999–2003 recharge being about 

50 percent of the 2004–8 recharge. These extremes in recharge 

coincided with the periods of lowest and highest mean rainfall, 

respectively. No seasonal pattern in recharge is discernible. 

Spatially, the highest recharge occurred in a belt about 4 miles 

wide running parallel to the coast about 2 miles inland.

The sensitivity of recharge estimates to input parameters 

is related to the climate and land-cover conditions of the particular area of study. For the wet, forested areas characteristic 

of the windward side of the island, recharge was most sensitive 

to the ratio of runoff to rainfall. For the dry, grassland areas 

characteristic of the northwestern leeward side of the island, 

recharge was most sensitive to root depth. For the Kona area, 

characterized by moderate rainfall and a wide variety of land 

cover, recharge was most sensitive to the pan coefficient and 

canopy-evaporation rates in forests.

Introduction

The rate of groundwater withdrawals from aquifer sys

tems on the Island of Hawai‘i likely will increase substantially 
2 A Water-Budget Model and Assessment of Groundwater Recharge for the Island of Hawai‘i

in the near future. This increase will result from growth of 

resident population and from extension of the municipal 

water system by the County of Hawai‘i Department of Water 

Supply (HDWS) and other, private systems that will include a 

greater reliance on groundwater sources. From 1990 to 2008, 

the resident population of the island grew from 120,317 to 

175,784 (U.S. Census Bureau, 2009). The resident population is projected to be 217,718 in 2020 (County of Hawai‘i, 

2005), an increase of about 81 percent from the 1990 population. Excluding sugarcane-related use, reported groundwater 

withdrawals increased from about 73 million gallons per day 

(Mgal/d) in 1988 (State of Hawai‘i, 1989) to about 96 Mgal/d 

in 2005 (County of Hawai‘i, 2006). Sugarcane irrigation and 

processing operations used about 31 Mgal/d of groundwater in 

1988, but sugarcane-related activities had completely ceased 

before 2005. In some aquifer systems, future water demands 

are projected to approach or exceed sustainable yields set by 

the State of Hawai‘i (2008), depending on the population projection method used by the County of Hawai‘i (2006).

The County of Hawai‘i has a goal to replace current 

surface-water sources with groundwater sources for its municipal water systems, wherever feasible (County of Hawai‘i, 

2006). The County has established the investigation and 

development of additional groundwater sources as a “course of 

action” for each district of the island in the County’s General 

Plan (County of Hawai‘i, 2005). Groundwater currently is the 

main source of domestic water across the island. However, 

surface water provides water for many households, particularly 

in the Waimea and Hilo areas (fig. 1), and rain catchments also 

provide water for many households, particularly in the Puna 

and Ka‘ü Districts (fig. 2). Groundwater sources generally 

are preferred over surface-water sources because groundwater 

requires less treatment and is more reliable in both quantity 

and quality than surface water. 

A better understanding of recharge will help in assessing 

the availability of groundwater within island aquifer systems. 

The rate and distribution of groundwater recharge to island 

aquifer systems is a controlling factor for the availability 

of groundwater supplies. Accurate estimation of the spatial 

distribution of groundwater recharge on the Island of Hawai‘i 

has been identified as a critical need by the State of Hawai‘i 

Commission on Water Resource Management (CWRM) (State 

of Hawai‘i, 2008). 

A better understanding of recharge will also help in the 

development of accurate groundwater-flow models. Estimates 

of historical groundwater recharge in the Kona area during the 

period 1984–2008 are needed for the development and calibration of a groundwater model for the area.

Purpose and Scope

This report documents the (1) development of a daily 

water-budget model for computing groundwater recharge for the 

entire Island of Hawai‘i, (2) application of the model to estimate 

long-term mean annual recharge for various land-cover and 

rainfall conditions, and (3) development and application of a 

Kona-area submodel to estimate historical groundwater recharge 

in the Kona area during the period 1984–2008. Recharge 

estimates from this study are compared to previously published 

recharge estimates, and the sensitivity of recharge estimates to 

selected water-budget parameters is evaluated.

Previous Investigations

Previous investigations that calculated water budgets for 

areas on the Island of Hawai‘i are listed in table 1. The present water-budget investigation covers both the entire island 

and the Kona area. The two previous water-budget investigations that covered the entire island, State of Hawai‘i (1990) 

and Giambelluca and Sanderson (1993), used an annual time 

step. The one previous investigation for the Kona area (Oki, 

1999) also used an annual time step. Use of monthly or annual 

computational time steps can lead to biased recharge estimates 

(Giambelluca and Oki, 1987; Oki, 2008). This water-budget 

study uses a daily time step, which provides a more realistic 

simulation of short-duration events, such as daily irrigation 

and episodic rainfall, than annual or monthly time steps (Izuka 

and others, 2005). Kanehiro and Peterson (1977), Oki (2002), 

and Pacific Hydrogeologic, LLC (unpublished 2006 report 

titled “Water budget and numerical analysis of Mahukona 

aquifer system, North and South Kohala, Hawai‘i”) used daily 

time steps in their water budgets, which covered various parts 

of the island.

Acknowledgments

The author thanks Larry Beck (County of Hawaiÿi 

Department of Water Supply) and Lenore Ohye (State of 

Hawaiÿi Commission on Water Resource Management) for 

providing data and information used in this report. Jeff Perreault, Sarah Rosa, and Tracy Ibarra Saguibo of the U.S. 

Geological Survey provided valuable assistance preparing data 

sets used in this report.

Description of the Island of Hawaiÿi

Physical Setting

The Island of Hawaiÿi lies at the southeastern end of the 

Hawaiian Archipelago in the tropical North Pacific Ocean 

between longitude 154°48'W and 156°04'W and between 

latitude 18°54'N and 20°17'N (fig.1). Comprising an area of 

about 4,030 square miles (mi2), it is nearly twice as large as the 

combined areas of the other Hawaiian Islands (Macdonald and 

Abbott, 1970). The island consists of five volcanoes: Kohala, 

Mauna Kea, Hualälai, Mauna Loa, and Kïlauea. Mauna Kea 

is the highest of these volcanoes, rising to an elevation of 

13,796ft, and Mauna Loa is the largest by volume. With the 
Figure 1. Major geographical features and the generalized extent of the surface rocks of the five volcanoes (colors) that 

form the Island of Hawaiÿi. (Modified from State of Hawai‘i, 2008).

156°

155°

155°20'

155°40'

20°

19°40'

19°20'

19°

0 10 20 Miles

0 10 20 Kilometers

EXPLANATION

Elevation contour, in feet above 

sea level—Contour interval 1,000 feet

Major road

Perennial stream

Intermittent stream

Kona water-budget area

7,000

Base modified from U.S. Geological Survey 

National Hydrography Dataset, 1:24,000,

Universal Transverse Mercator projection, 

zone 5, NAD83 datum.

MAUNA LOA

MAUNA KEA

HUALÄLAI

KÏLAUEA

KOHALA

1,000

2,000

3,000

4,000

5,000

7,000

7,000

9,000

11,000

11,000

2,000

4,000

Q

Q

Q

13,681 ft

13,796 ft

8,271 ft

Kïlauea

Caldera

Wailuku R

Waiäkea Str

Honoliÿi Str

Hakalau 

Pöhaku

Kaÿula Gl

Str

Kamakoa Gl

Waiÿaha Str

Kiÿilae Str

Nïnole Gl

Hïlea Gl

Waikoloa Str

Pololü Str

Str

puka

Hawi

Kawaihae

Waikoloa 

 Village

Waimea

Honokaÿa

Hilo

Kailua

Captain Cook

Volcano

Pähala

Näÿälehu

Mountain 

View Pähoa

22 ̊

20 ̊

160 ̊ 158 ̊ 156 ̊

Kaua‘i

Ni‘ihau

O‘ahu

Maui

Moloka‘i

Lāna‘i

Kaho‘olawe

Hawai‘i

HAWAI‘I

Pacific Ocean

Hilo

Bay

Kealakekua

 Bay

Kailua

 Bay

Honoköhau

 Bay

Kïholo 

 Bay

Kawaihae Bay

Waipiÿo

 Bay

Honuÿapo

 Bay

Kaÿaluÿalu

 Bay

Description of the Island of Hawaiÿi 3
Figure 2. Aquifer systems (State of Hawaiÿi, 2008), judicial districts, and the Kona water-budget area.

156°

155°

155°20'

155°40'

20°

19°40'

19°20'

19°

0 10 20 Miles

0 10 20 Kilometers

EXPLANATION

Judicial district

Aquifer system 

(State of Hawaiÿi, 2008)

Kona water-budget area

PUNA

Näÿälehu

KAÿÜ

SOUTH 

 KONA

NORTH 

KONA

NORTH 

KOHALA

SOUTH 

KOHALA

NORTH 

HILO

SOUTH HILO

PUNA

HÄMÄKUA

Hilo

Waimea

Näÿälehu

Pähoa

Keaÿau

ÿÖlaÿa

Kaÿapuna

Onomea

ÿAnaehoÿomalu

Manukä

Kïholo

Ka Lae

Kalapana

Hakalau

Paÿauilo

Kealakekua

Keauhou

Keaïwa

Honokaÿa

Mähukona

Hilina

Häwï

Waimanu

Kapäpala

Hawi

Kawaihae

Waikoloa 

Village

Waimea

Honokaÿa

Hilo

Kailua

Captain Cook

Volcano

Pähala

Näÿälehu

Mountain 

View

Pähoa

Base modified from U.S. Geological Survey 

National Hydrography Dataset, 1:24,000,

Universal Transverse Mercator projection, 

zone 5, NAD83 datum.

4 A Water-Budget Model and Assessment of Groundwater Recharge for the Island of Hawai‘i
Table 1. Previous water-budget investigations for the Island of Hawai‘i.

Reference Area Time step

Pacific Hydrogeologic, LLC (2006, unpub.) Mähukona aquifer system daily

Waimea Water Services (2004) South Kona and western Ka‘ü districts monthly

Oki (2002) Hawi area daily

Oki (1999) Kona area annual

Shade (1995) Kohala monthly

Giambelluca and Sanderson (1993) entire island annual

State of Hawai‘i (1990) entire island annual

Kanehiro and Peterson (1977) part of northwestern coast daily

Description of the Island of Hawaiÿi 5

exception of the northeastern slopes of Kohala and Mauna Kea, 

the geologically youthful land surface still retains a broadly 

rounded, shield-shaped morphology that slopes undissected 

from the volcanic summits to the ocean, except where cinder 

cones have formed and where erosion from watercourses has 

created shallow valleys. On the northeastern sides of Kohala 

and Mauna Kea, large streams, resulting from heavier rainfall, 

have carved deep valleys in these relatively older volcanoes.

Climate

The climate on the Island of Hawai‘i is extremely 

diverse—lava deserts, tropical rain forests, and snow-capped 

mountain peaks all exist. Using the Thornthwaite climatic 

classification, the island has semiarid, subhumid, humid, and 

perhumid zones (Giambelluca and Sanderson, 1993). The 

average annual air temperature of the island ranges from 

about 73 ̊F near the coast to less than 43 ̊F near the summits 

of Mauna Kea and Mauna Loa (Nullet and Sanderson, 1993). 

Average annual rainfall ranges from about 9 in. near Kawaihae to about 240 in. just west of Hilo, on the eastern slope of 

Mauna Kea (fig. 3).

Climate is primarily controlled by a complex topography, a temperature inversion, and the location of the North 

Pacific anticyclone, which produces persistent northeasterly 

winds that are known as tradewinds. During the summer (May 

through September), tradewinds blow 80 to 95 percent of the 

time, and during the winter (October through April), when 

the anticyclone moves southward, tradewinds blow 50 to 80 

percent of the time (Blumenstock and Price, 1967; Sanderson, 

1993). A temperature inversion, which marks the lower extent 

of dry air subsiding in the North Pacific anticyclone, exists at 

a mean elevation of about 6,560 ft over Hawaiÿi (Schroeder, 

1993). This inversion, commonly referred to as the tradewind 

inversion, greatly influences the climate and vegetation on the 

mountain slopes. Diurnal and annual variability in climatic 

variables such as solar radiation, air temperature, and humidity, are affected by the elevation of the inversion (Giambelluca 

and Nullet, 1991). 

The tradewind inversion restricts the upward flow of air 

(Mendonca and Iwaoka, 1969), forcing the tradewinds around, 

instead of over, Mauna Loa and Mauna Kea. Tradewind flow 

around the mountains generates a quasi-stationary cyclonic 

eddy at the northern end of the leeward side of the island 

and a stationary anticyclonic eddy at the southern end of the 

leeward side (Pratzert, 1969; Yang and Chen, 2003). Lowlevel convergence of these counter-rotating eddies over the 

ocean generates a moisture-enhanced return flow of air to the 

Kona area, which lies in the wake of Hualälai and Mauna Loa 

(Yang and Chen, 2003). Daytime solar heating of the island 

interior creates a diurnal sea-breeze/land-breeze circulation on 

both the windward and leeward sides of the island, with sea 

breezes occurring during the day and land breezes occurring 

at night. The interaction of the tradewind flow pattern with the 

diurnal sea-breeze/land-breeze circulation determines local 

wind conditions. Because the Kona area is sheltered from the 

tradewinds by Hualälai and Mauna Loa, the daily weather 

there is frequently dominated by a well-developed diurnal seabreeze/land-breeze circulation. 

Orographic lifting of onshore winds is the primary 

rainfall-producing mechanism on the Island of Hawai‘i 

(Giambelluca and others, 1986). Rainfall generally is greatest on the northeastern and eastern sides of the volcanoes that 

are exposed to persistent, moist tradewind flow off the ocean, 

sometimes enhanced by the sea-breeze/land-breeze circulation. Maximum rainfall along the Kona coast occurs where 

the convective onshore sea breeze is enhanced by the moist 

return flow (Yang and Chen, 2003). Except in the Kona area, 

the wettest months on the island occur during the winter, 

when migratory storm systems bring additional, widespread 

rain. Because the main rainfall-producing mechanism in the 

Kona area is related to the convergence of the counter-rotating 

eddies generated by the tradewinds, which are most persistent 

in the summer, rainfall in the Kona area is greatest in the summer months (Giambelluca and others, 1986).

On the Island of Hawai‘i, mountain fog commonly occurs 

during periods of onshore, upsloping winds and is associated 

with rainfall. However, it can also occur in the absence of 

rainfall, especially during the summer when the more frequent 
Figure 3. Mean annual rainfall and locations of rain gages used in the water-budget calculation for the Island of Hawaiÿi.

156°

155°

155°20'

155°40'

20°

19°40'

19°20'

19°

0 10 20 Miles

0 10 20 Kilometers

Base modified from U.S. Geological Survey 

National Hydrography Dataset, 1:24,000,

Universal Transverse Mercator projection, 

zone 5, NAD83 datum.

PREVAILING

WIND

DIRECTION

120

EXPLANATION

Thiessen polygon (used to estimate 

areal influence of rain gage)

Line of equal mean annual rainfall, 

in inches—Interval varies (modified from 

Giambelluca and others, 1986)

Kona water-budget area

Rain gage and National Weather

Service number (all 4-digit numbers begin 

with prefix 51, see note below regarding

USGS, SCAN, and CWRM gages)

8638

1

120

120

80

60

80

30

40

60

20

30

40

80

80

80

160

120

80

240

60

40

30

10

20

20

200

160

120

80

60

20

8830

1339 4680

8548

1864

6270 USGS

0134

3077

3078

SCAN 

Waimea

Plain

4928

4938 SCAN 

Kukuihaele

5761

1856

08407204

7312

4815

8422

7131

SCAN Island Dairy

8780

4459

8067

1701

0905

1955

8000

7711

0910

1960

7721

150105

8550

SCAN

Pua 

Akala

USGS

1065

1484 1492

9025

3510 4764

3872

6522

8638 7457

1300

3367

5525

3368

2894

4080

1303

496009 3300

7437

7421

8600

2249

6588

2568 4625

8650

3054

8652

6304

7166

3977

6697

1665

2327

2751

6268 1562

CWRM

Naohueleelelua

499906

499907

8555

8346

4765

9142

3911

1880

5330

2887

2156

6198

8063

CWRM 

Kemole

5011

496006

5018

8186

a

b

1

1

1

1

1

11

1

1

1

1

11

1

1

1

11

1

1

11

1 1

1

1

1 1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

11

1

1

1

1

1

1

1

1

1 1 1 1 1

1 1

11

11

1

1 1

11

111

1

1

1

1 111

1

1

1

1

1

1 1

1

1

1

1

1 1

1

1

NOTE

USGSa, USGS station number 200518155405801, http://waterdata.usgs.gov/hi/nwis/ 

USGSb

, USGS station number 194117155174801, http://waterdata.usgs.gov/hi/nwis/

SCAN, soil climate analysis network, http://www.wcc.nrcs.usda.gov/scan/

CWRM, State of Hawaiÿi Commission on Water Resource Management, http://hawaii.gov/dlnr/cwrm/

6 A Water-Budget Model and Assessment of Groundwater Recharge for the Island of Hawai‘i
Description of the Island of Hawaiÿi 7

presence of the tradewind inversion limits the vertical development of the orographic cloud. This type of fog can persist with 

relatively high wind velocities, resulting in extremely large 

volumes of water passing near the ground (Juvik and Ekern, 

1978). The interception of fog by vegetation is an important 

source of water for high-elevation forests in Hawai‘i, particularly during the drier summer months (Juvik and Nullet, 1995).

Hydrogeology

The Island of Hawaiÿi is formed primarily by the 

shield-stage volcanic rocks of Mauna Loa and Kïlauea and 

the shield- and postshield-stage volcanic rocks of Kohala, 

Hualälai, and Mauna Kea (Langenheim and Clague, 1987). 

The volcanic rocks can be divided into three main groups on 

the basis of modes of emplacement—lava flows, dikes, and 

pyroclastic deposits. In general, lava flows that erupt from 

the central caldera and the rift zones of each volcano are less 

than 10 ft thick and are either pahoehoe, which is characterized by smooth, ropy surfaces, or aÿa, which contains a 

massive central core typically sandwiched between rubbly 

clinker layers. A‘a flows typically are more abundant at 

greater distances from eruptive sources (Lockwood and Lipman, 1987). Dikes are thin, near-vertical sheets of massive 

rock that intrude existing rocks, commonly lava flows. Dikes 

are commonly exposed by erosion within the rift zones of 

older volcanoes (see for example Takasaki and Mink, 1985), 

including Kohala on the island of Hawaiÿi. 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. Within the central part 

of a dike complex, the dike rocks typically compose 10 percent or more of the total rock volume. At the outer part of the 

dike complex, within the marginal dike zone, dikes usually 

constitute less than 5 percent of the total rock volume (Takasaki and Mink, 1985). Pyroclastic rocks are composed of 

fragments of volcanic rocks that form by explosive volcanic 

activity and that are deposited by transport processes related 

to this activity. Pyroclastic rocks, such as ash, cinder, and 

spatter, can be deposited during all of the subaerial stages of 

eruption but probably form less than 1 percent of the mass of 

a Hawaiian volcano (Wentworth and Macdonald, 1953).

The high primary porosity and lack of weathering in the 

youthful, voluminous lava flows erupted during the shield 

stage on the Island of Hawai‘i provide an aquifer that has 

relatively high permeability, particularly in the dike-free flanks 

that slope away from the summits and rift zones. For example, 

estimates of the hydraulic conductivity for flank lava flows 

on the west side of the island are as high as several thousand 

feet per day (Oki, 1999). 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. The freshwater lens is thin in most areas, owing to the 

high permeability of the aquifer. The water table is near sea 

level at the coast and rises gently from less than a foot to a few 

feet per mile in the inland direction (Stearns and Macdonald, 

1946). Natural discharge from the freshwater-lens system 

generally occurs as diffuse seepage near the coast.

The permeability of volcanic rocks is variable and 

depends on the type (lava flows, intrusive dikes, or pyroclastic deposits), amount of weathering, and the thickness of the 

rocks. 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 of magnitude lower than that of dike-free 

flank lavas (Oki, 1999). Some 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 high-permeability 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 to several 

thousand feet above sea level (Stearns and Macdonald, 1946).

Soils

About 39 percent of the land surface on the Island of 

Hawai‘i is categorized as lava flow or rock land (U.S. Department of Agriculture, 2008). Little to no soil cover exists in 

these areas. The remainder of the land surface is covered by 

148 different soils from 6 soil orders: andisols, aridisols, entisols, histosols, inceptisols, and mollisols (U.S. Department of 

Agriculture, 2008). The most prevalent soil order on the island 

is andisols, which are derived from volcanic ash. Andisols 

cover most of Mauna Kea and parts of all the other volcanoes. 

Histosols, derived from organic material, are the second most 

prevalent and exist mainly on the lower flanks of Mauna Loa, 

Hualälai, and Kïlauea. The thickness of soil on the island is 

spatially variable and depends on many local factors, including 

(1) the age of the bedrock (lava flows), (2) the rate of bedrock 

weathering, (3) the amount and type of vegetation, and (4) the 

topography of the area (Jenny, 1994).

Land Cover

Land cover on the Island of Hawai‘i reflects the extreme 

diversity of climate, recent and ongoing volcanism, and the 

influence of human activity. Large tracts of forest, generally 

dominated by the native canopy species Metrosideros polymorpha (ohia lehua) (Loope, 1998), exist in the wetter areas of 

the island, with shrubland and grassland in the drier areas (fig. 

4). Sparsely vegetated land generally exists on lava flows that 

have not been sufficiently weathered to allow for plant colonization. Native plant species are being replaced by invasive 

alien species at varying rates in different locations. Asner and 
Figure 4. Land cover on the Island of Hawaiÿi (modified from U.S. Geological Survey, 2006). Coffee-farm, golfcourse, and water/wetland land covers are difficult to see at this scale.

156°

155°

155°20'

155°40'

20°

19°40'

19°20'

19°

0 10 20 Miles

0 10 20 Kilometers

Diversified agriculture

Eucalyptus plantation

Golf course

Low-intensity developed

High-intensity developed

Sparsely vegetated

Water/wetland

EXPLANATION

Closed native forest

Open native forest

Alien and mixed forest

Shrubland

Grassland

Macadamia orchard

Coffee farm

Boundary of aquifer system

Base modified from U.S. Geological Survey 

National Hydrography Dataset, 1:24,000,

Universal Transverse Mercator projection, 

zone 5, NAD83 datum.

8 A Water-Budget Model and Assessment of Groundwater Recharge for the Island of Hawai‘i
Canopy 

Evaporation

PLANT-ROOT ZONE

Groundwater 

Recharge

Runoff

Total

Evapotranspiration

FOREST CANOPY

Transpiration Ground 

Evaporation

Rainfall

Fog 

Interception

Throughfall Stemflow

Net 

Precipitation

FOR FOREST LAND COVERS

(modified from McJannet and others, 2007)

Evapotranspiration

Irrigation Fog 

Interception Rainfall

PLANT-ROOT ZONE

Groundwater 

Recharge

Runoff

FOR NONFOREST LAND COVERS

Water-Budget Model 9

others (2008) described the ongoing invasion of native forest 

by Falcataria moluccana, Fraxinus uhdei, Hedychium gardnerianum, Morella faya, and Psidium cattleianum at five locations on Mauna Kea and Kïlauea. These invasions are fundamentally changing the hydrology of the island. For most of the 

20th century, sugarcane cultivation dominated the coastal areas 

of windward Mauna Kea, southeastern Mauna Loa, and northern Kohala. Much of this land was native forest before being 

converted to agriculture. Since the demise of the sugarcane 

industry in the 1990s, former sugarcane lands that have not 

switched to diversified agriculture have become dominated by 

mostly alien grassland (U.S. Geological Survey, 2006). Along 

the leeward coast, from near Kawaihae to Captain Cook, 

urbanization is occurring at a rapid pace. Large-scale resorts 

that include hotels, condominiums, luxury houses, shopping 

centers, and golf courses are being developed, affecting large 

stretches of coastline.

Water-Budget Model

Conceptual Model 

The daily 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 basic structure of the 

model is the same as that used for other recent U.S. Geological 

Survey (USGS) recharge studies in the Hawaiian Islands (Oki, 

2002; Izuka and others, 2005; Engott and Vana, 2007), except 

that canopy evaporation in forests is explicitly considered in 

this model. Figure 5 displays the two generalized flow diagrams used in this study—one for nonforest land covers and 

one for forest land covers. Both conceptual models employ a 

plant-root zone reservoir. The forest model includes a second 

reservoir consisting of the forest canopy. 

The volume of the plant-root zone reservoir is based 

on plant and soil properties. The model accounts for water 

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

zone reservoir on a daily basis. At the end of a given 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 due to evapotranspiration (ET) 

processes, the reservoir overflows. This overflow is counted as 

groundwater recharge by the model. 

The forest-canopy reservoir is not treated as a true 

reservoir in the model calculations, as the volume of water 

within the reservoir is not tracked. Instead, net precipitation, 

which is the output from the reservoir that becomes input to 

the plant-root zone reservoir, is calculated using a relation to 

fog interception and rainfall that is developed from results in 

published studies. Canopy evaporation is then calculated as the 

difference between the combined rainfall and fog interception 

volume and net precipitation.

Figure 5. Generalized water-budget flow diagrams for both 

forest and nonforest land covers.

Model Exclusions and Assumptions

Several exclusions and assumptions are made to simplify 

the water-budget model. Recharge from streambed seepage 

is not explicitly considered, although direct runoff from each 

basin is modeled using best available information. Also, the 

variability of soil moisture with regard to depth within the soil 

root zone is not considered. In general, stationarity is assumed 

for climatological statistics. For example, the rainfall statistics 

computed for the period 1916–83 by Giambelluca and others 
10 A Water-Budget Model and Assessment of Groundwater Recharge for the Island of Hawai‘i

(1986) and the pan-evaporation statistics computed using data 

from various time periods by Ekern and Chang (1985) are 

assumed to be representative of and valid for all time periods 

considered in the model, except where noted.

Model Calculations

Groundwater recharge for the Island of Hawai‘i was 

computed using the daily water-budget model and input data 

that quantify the spatial and temporal distribution of rainfall, 

fog interception, irrigation, evaporation, runoff, soil type, and 

land cover. Areas of homogeneous properties, termed “subareas,” are generated by merging datasets that characterize the 

spatial and temporal distribution of rainfall, fog, irrigation, pan 

evaporation, runoff, soil type, and land cover in a geographical information system (GIS). For each subarea, recharge is 

calculated by the water-budget model. At the end of a simulation period, results for the subareas are summed over larger 

areas of interest, which can include entire aquifer systems. 

In the water-budget model for the Island of Hawai‘i there are 

467,805 subareas with an average area of 5.51 acres.

For each subarea at the start of each day, the model calculates an interim moisture storage. 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 zone from 

the previous day. For the first day of the simulation, a value 

for the amount of water already in the zone from the previous 

day (initial soil moisture) is selected by the user. For nonforest 

subareas, interim moisture storage is given by the equation 

 Xi

 = Pi + Fi + Ii + Wi − Ri + Si-1, (1a)

where

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

Pi = rainfall for current day [L], 

Fi = fog interception for current day [L], 

Ii = irrigation for current day [L], 

Wi = excess water from the impervious fraction of an 

urban area distributed over the pervious fraction 

[L],

Ri = runoff for current day [L],

Si-1 = moisture storage at the end of the previous day 

(i-1) [L], and

i = subscript designating current day.

For forest subareas, interim moisture storage is given

by the equation 

 Xi = (NP)i − Ri + Si-1, (1b)

where

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

For forest subareas, net precipitation is computed as the 

sum of rainfall and fog interception less canopy evaporation, 

which is the amount of water from rainfall and fog that collects on the leaves, stems, and trunks of trees and subsequently 

evaporates. The equation is

 (NP)i = Pi + Fi − (CE)i, (2)

where

 (CE)i = canopy evaporation [L]. 

For urbanized subareas, which in this study include the 

land-cover categories low-intensity developed and high-intensity 

developed (fig. 4), the interim equation includes the factor Wi, 

which is a function of the fraction of urban subareas that are estimated to be impervious (see equation 1a). In nonurban subareas 

where there is no impervious fraction, Wi is zero. Urbanized 

subareas are assigned a fraction (z) that is impervious. This fraction is used to separate, from the total rain that falls in an urbanized subarea, a depth of water that is treated computationally as 

though it fell on an impervious surface. Based on this impervious 

water fraction, some water is subtracted to account for direct 

evaporation. The remainder of the water (Wi) is added to the 

water budget of the pervious fraction of the model subarea. Thus, 

for the pervious fraction of an urban subarea, the total daily water 

input includes an excess of water from the impervious fraction.

For an urbanized model subarea, excess water, Wi

, and 

water storage (ponded water) on the surface of impervious 

areas were determined using the following conditions:

 X1i = Pi − Ri + Ti-1 , (3)

 for X1i ≤ N, 

 Wi = 0, and X2i = X1i,

 for X1i > N, 

 Wi = (X1i − N)z / (1-z), and X2i = N, (4)

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 interception capacity (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 > Vi, 

 Ti = X2i-Vi, and 

 for X2i ≤ Vi

, 

 Ti = 0, (5)

where

Vi = pan evaporation for current 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

). A vegetated surface loses water to 
Water-Budget Model 11

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

available. At all sites, potential ET was assumed to be equal to 

pan evaporation multiplied by an appropriate vegetation factor, 

termed a pan coefficient. For moisture contents greater than or 

equal to a threshold value, Ci

, the rate of ET was assumed to be 

equal to the potential-ET rate. For moisture contents less than 

Ci, ET was assumed to occur at a reduced rate that declines 

linearly with soil-moisture content:

for S ≥ Ci, ,

 E = (PE)i , and

for S < Ci and Ci > 0,

 E = S × (PE)i ⁄ Ci , (6)

where

E = instantaneous rate of evapotranspiration [L/T],

(PE)i = potential-evapotranspiration rate 

for the current day [L/T],

S = instantaneous moisture storage [L], and

Ci = threshold moisture storage for the current day 

below which evapotranspiration is less than the 

potential-evapotranspiration rate [L].

The threshold moisture storage, Ci, was estimated using the 

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

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

fraction of maximum moisture storage that can be depleted from 

the root zone before moisture stress causes a reduction in ET. 

The threshold moisture, Ci, is estimated from p by the equation

 Ci = (1 − p) × Sm, (7)

where 

 Sm = moisture-storage capacity of the plant-root zone [L]. 

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

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

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 wiltingpoint moisture content: 

 Sm = D × φ, (8)

where

D = plant root depth [L],

φ = θfc- θwp [L3/L3], 

θfc = volumetric field-capacity moisture 

content [L3/L3], and

θwp = volumetric wilting-point moisture 

content [L3/L3].

Values for p depend on vegetation type and can be 

adjusted to reflect different potential-ET rates. In this study, p

values were based on data in Allen and others (1998). 

In the water-budget model, the ET rate from the plantroot 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 threshold moisture content (Ci). By recognizing that 

E = - dS /dt, the total depth of water removed by ET during a 

day, Ei, was determined as follows:

 for Xi > Ci and Ci > 0,

 Ei = (PE)iti + Ci{1-exp[-(PE)i(1-ti)/Ci]},

 for Xi > Ci and Ci = 0,

 Ei = (PE)iti,

 for Xi ≤ Ci and Ci > 0,

 Ei = Xi{1-exp[-(PE)i / Ci]},

and

 for Xi = Ci, and Ci = 0,

 Ei = 0, (9)

where

Ei = evapotranspiration from the plant-root zone 

during the day [L], 

ti = time during which moisture storage is above Ci

[T]. It ranges from 0 to 1 day and is computed as 

follows:

for (Xi – Ci)< (PE)i(1 day)

 ti

 = (Xi − Ci)/(PE)i, 

and

for (Xi – Ci) ≥ (PE)i(1 day),

 ti = 1. (10)

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

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

interim moisture storage, and any moisture remaining above 

the maximum moisture storage was assumed to be recharge. 

The daily rate of direct recharge from anthropogenic sources is 

also added to daily recharge at this point. Recharge and moisture storage at the end of a given day were assigned according 

to the following conditions:

for Xi-Ei ≤ Sm, Qi = DR, and 

 Si = Xi-Ei , 

and

for Xi-Ei > Sm, Qi = (Xi-Ei-Sm) + DR, and 

 Si = Sm, (11)

where

Qi = groundwater recharge during the day [L], and 

Si = moisture storage at the end of the current day (i) 

[L], and

DR = daily rate of direct recharge [L] (a constant).

Moisture storage at the end of the current day, expressed 

as a depth of water, is equal to the root depth multiplied by the 

difference between the volumetric soil-moisture content within 

the root zone at the end of the current day and the volumetric 

wilting-point moisture content: 

 Si = D × (θi- θwp), (12)

where

θi = volumetric soil-moisture content at the end of 

the current day, i, [L3/L3]. 
12 A Water-Budget Model and Assessment of Groundwater Recharge for the Island of Hawai‘i

Model Input

Land-Cover Map

The base land-cover map for this study is from the 

Hawai‘i Gap Analysis Program (GAP) (U.S. Geological Survey, 2006). Modifications to the base map were performed in a 

geographic information system (GIS). Modifications included 

converting the map from a raster dataset to a vector dataset, 

combining features smaller than the minimum mapping unit 

area of 0.36 ha (U.S. Geological Survey, 2006) with adjoining features, and combining feature classes. Agricultural lands 

in GAP are not categorized into individual crops. Although 

agricultural land does not make up a major part of the island, 

distinguishing between crops is important for water-budget 

calculations. Agricultural lands in the modified GAP landcover map were categorized by crop using digital satellite 

imagery, first-hand visual identification, and a digital land-use 

map (State of Hawai‘i, 1980). Golf courses are not explicitly 

identified in GAP. Similar to agricultural fields, golf courses 

do not make up a major part of the island. However, golfcourse irrigation can have an important effect on water-budget 

calculations. Features on the modified GAP land-cover map 

were classified as golf courses using digital satellite imagery 

in a GIS. Additionally, several recently constructed developments along the Kona coast were not identified on the GAP 

land-cover map. These were delineated on the modified GAP 

land-cover map on the basis of recent digital satellite imagery 

in a GIS. Finally, the Kohanaiki development, adjacent to 

Kaloko-Honoköhau National Historical Park and currently 

(2011) under construction, was superimposed on the modified GAP land-cover map using a digital map provided in a 

consultant report (Hunsaker and Associates Irvine, Inc., 2007) 

in a GIS. 

The finalized land-cover map described here is termed 

“2008 land cover” throughout the remainder of this report. 

For the transient Kona-area submodel, the golf courses and 

developments were added chronologically to create land-cover 

maps representative of the several time periods. These maps 

are termed “1988 land cover,” “1993 land cover,” “1998 land 

cover,” and “2003 land cover” throughout the remainder of 

this report.

Rainfall

Mean Rainfall

Maps of mean monthly rainfall for the Island of Hawai‘i 

(Giambelluca and others, 1986) were digitized and used to 

define the spatial and temporal distribution of rainfall. Figure 

3 shows mean annual rainfall in the study area for the period 

1916–83. In the model, areas between lines of equal monthly 

rainfall were assigned the average values of the bounding 

lines. To generate daily rainfall values for the model, 95 rain 

gages were selected on the basis of completeness of daily 

record and location. Thiessen polygons were used to spatially extrapolate the daily rainfall patterns indicated by the 

gages. Rainfall data were obtained from the National Climatic Data Center (NCDC), the Remote Automated Weather 

Station (RAWS) network, the Soil Climate Analysis Network (SCAN), the State of Hawai‘i Commission on Water 

Resources Management (CWRM), and the USGS. 

Daily rainfall was synthesized by disaggregating the 

monthly rainfall values using the method of fragments (see, 

for example, Oki, 2002). The method creates a synthetic 

sequence of daily rainfall from monthly data by imposing the 

rainfall pattern from a rain gage with daily data. Fragments 

were created by dividing each daily rainfall measurement for 

a particular month by the total rainfall for that month. This 

created 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 created 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. The fragment set to be used for a given 

gage for a given month was selected randomly from among all 

available sets for that gage for that month of the year. Synthesized daily rainfall for a given month was created by multiplying total rainfall for that month by each fragment in the set, 

thereby providing daily rainfall, Pi

, for equation 1a or 1b. 

Temporal Variability

The interannual variability of rainfall was factored into 

the water-budget model to provide a more realistic estimation of long-term mean groundwater recharge. This was 

accomplished by running the water-budget model for a period 

of 25 years and by dividing the island into seven regions of 

similar rainfall characteristics, including rates, mechanisms 

(orographic, convective, and so forth), and seasonal patterns 

(fig. 6). For each region, data from one gage were used to represent how rainfall varied from year to year within that entire 

region. This gage was selected on the basis of completeness 

of record. Except for the region that includes gage 519412 on 

the northwestern side of the island (fig. 6), the 25-year period 

1955–1979 was chosen as the period from which to generate 

the interannual variability of rainfall across the island. The 

rainfall records are very complete during this time period, 

owing to extensive cultivation of sugarcane. For the region that 

includes gage 519412, the period 1976–2000 was used instead, 

owing to the lack of available data before that time. For each 

gage, the observed annual rainfall for each year during the 

25-year time period was divided by the average annual rainfall 

for that time period (table 2), creating a series of 25 weighting factors for each rainfall region. Rainfall for a given month 

was calculated by multiplying the mean monthly value, based 

on Giambelluca and others (1986), by the weighting factor 

appropriate for the year and the rainfall region.

For the Kona water-budget submodel, which is designed 

to simulate historical recharge during the time period 1984–

2008, the observed monthly rainfall data for eight gages 
Figure 6. Rain-gage stations (diamonds with gage numbers) and the seven rainfall-variability zones used to 

simulate annual variability of rainfall in the Island of Hawaiÿi water-budget model and the rain-gage stations used 

to simulate monthly variability in the Kona water-budget submodel.

156°

155°

155°20'

155°40'

20°

19°40'

19°20'

19°

0 10 20 5 Miles

0 12.5 Kilometers 25

511339

519142

511665

517312

511303

517421

516198

1

2

3

4

7

6

5

156°

155°40'

19°20'

19°40'

0 105 Miles

0 12.5 Kilometers

511665

516198

516304

517166

513911

511557

512156

514765

1

1

1

1

1

1 1

1

1

1

1

1

1

1

1

ISLAND OF HAWAIÿI WATER-BUDGET KONA WATER-BUDGET

MODEL AREA SUBMODEL AREA

Model Input 13

during this time period were used to simulate the historical 

rainfall pattern. Monthly weighting factors—ratios of observed 

monthly rainfall to mean monthly rainfall—were computed for 

the entire period, 1984–2008, for each gage. Mean monthly 

rainfall values for each gage were obtained from the Western 

Regional Climate Center (2009). Monthly weighting factors were applied spatially over the Kona study area using an 

inverse-distance-squared weighting method (Dirks and others, 

1998). Rainfall for a given month was calculated by multiplying the mean monthly value from Giambelluca and others 

(1986) by the monthly weighting factor for that specific area. 

Daily rainfall was then calculated using the method of fragments, as described above.

Fog Interception

Fog is often persistent on the mid-elevation mountain 

slopes of Hawai‘i, 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 on the Island of Hawai‘i (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 inversion-base 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; 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 
14 A Water-Budget Model and Assessment of Groundwater Recharge for the Island of Hawai‘i Table 2. Ratios of observed rainfall to mean rainfall for rain gages used to simulate interannual variability in the water-budget model for the Island of Hawai‘i. [Mean rainfall from 1916 through 1983 based on Giambelluca and others (1986); interannual rainfall variability ratios used for drought scenario are shown in red; NWS ID, National Weather Service coopera- tive identification number] Rainfall- variability zone NWS ID Year Period with lowest 5-year average Lowest 5-year average 1955 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79

1 511339 1.05 1.26 1.24 1.46 1.14 0.97 0.74 0.50 0.83 1.04 0.76 0.81 0.91 1.33 1.20 1.17 0.88 0.82 0.86 0.88 0.93 0.92 0.96 1.03 1.30 1961–65 0.77

2 517312 0.92 1.09 1.18 1.26 1.00 1.07 0.89 0.35 0.80 1.14 0.75 0.99 1.13 0.97 1.64 1.42 0.58 0.81 0.90 0.69 0.69 1.07 0.92 1.15 1.60 1971–75 0.73

3 511303 0.97 1.19 1.00 0.75 1.01 0.83 0.88 0.55 0.93 1.20 0.94 0.92 1.07 0.98 1.09 1.07 1.85 0.79 0.84 0.99 1.04 1.08 0.88 0.87 1.29 1958–62 0.80

4 517421 1.16 1.29 0.89 0.77 1.12 0.54 0.79 0.81 1.06 0.63 1.32 1.03 1.39 1.65 0.77 0.73 1.25 1.03 0.75 0.84 1.16 0.97 0.57 0.91 1.57 1960–64 0.77

5 516198 1.03 1.78 1.04 0.78 1.47 0.69 0.77 0.52 1.28 0.72 1.09 1.11 1.42 1.67 0.63 0.67 0.92 0.96 0.84 1.18 0.71 0.75 0.50 0.92 1.54 1960–64 0.80

6 511665 0.95 0.58 0.54 0.80 0.78 0.61 0.88 0.66 0.89 0.61 1.40 0.94 1.42 1.12 1.29 1.09 1.36 0.99 0.64 1.70 1.12 1.22 0.92 1.31 1.18 1956–60 0.66

Year

1976 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 2000

7 519412 0.93 0.62 0.96 1.89 1.77 0.65 1.94 0.78 0.71 0.91 1.65 0.99 1.43 0.69 0.86 1.10 0.31 0.92 0.72 0.40 2.73 0.63 0.64 0.44 0.60 1991–95 0.69
Model Input 15

The fog-catch efficiency for native open forest, native closed 

forest, mixed forest, alien forest, and forest (eucalytptus) 

agriculture was set to 1. The fog-catch efficiency for shrubland 

and coffee was set to 0.5, to account for the shorter stature of 

these land covers compared to forest. 

Irrigation

Agricultural Irrigation

Daily irrigation was applied to all agricultural land covers in the water-budget model except forest (eucalyptus) and 

fallow/grassland. Daily irrigation was similarly applied to the 

golf-course land cover. These irrigated areas total only about 

3 percent of the island. Hence, the effect of irrigation on the 

regional water budget is small. However, the local effects of 

irrigation could be important. Irrigation was calculated as the 

difference between monthly potential ET and rainfall and was 

applied uniformly over each day in the month. This is similar 

to the approach used for a recent water budget of central and 

west Maui (Engott and Vana, 2007). Calculation is as follows:

for (PE)m– Pm > 0, Im = ((PE)m– Pm) / dm, 

and 

for (PE)m– Pm ≤ 0, Im = 0, (14)

where

Im = the amount of daily irrigation for month m [L],

Pm = the amount of rainfall for month m [L], 

	 (PE)m = the potential evapotranspiration for month m

(varies by land cover) 

 [L], and

dm = the number of days in month m [dimensionless].

Urban-Landscape Irrigation

Daily irrigation was also applied to both the low-intensity 

and high-intensity developed land covers to simulate the 

watering of lawns and landscaped areas. This irrigation was 

also applied uniformly over each day of the month. Irrigation 

in these areas was applied at a rate 0.6 times the rate calculated using equation 14. The factor 0.6 is a calibration factor 

based on irrigation water use reported in the Water Use and 

Development Plan Update (County of Hawai‘i, 2006). 

Runoff

In this study, “runoff” is synonymous with the term “direct 

runoff” and is defined as the fraction of rainfall that does not 

contribute to net moisture gain within the plant-root zone 

(fig.5). Direct runoff consists of overland surface flow and interflow (water that flows in the shallow subsurface and is eventually discharged to a stream or other surface-water body). 

To assist in runoff analysis, the Island of Hawai‘i was 

divided into runoff zones on the basis of climate, 

and biotic variables, including the duration and frequency of 

fog periods, wind speed and direction, liquid water content of 

fog, and structural characteristics of the forest, such as height, 

size, spatial pattern, and 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 Hawai‘i and worldwide. 

In Hawai‘i water budgets, fog interception is often 

applied spatially within defined fog zones by using a relation 

to rainfall. One common method of estimating this relation is 

to compare the amount of cloud water collected in a mechanical fog gage to the amount of rainfall collected in a rain gage 

in the same area during concurrent periods. Juvik and Ekern 

(1978) developed relations between mechanical fog interception and rainfall for both the windward and leeward sides of 

Mauna Loa. These relations were used in the water-budget 

model. The windward Mauna Loa relation was spatially 

extended to include Kïlauea, southeastern Mauna Loa, windward Mauna Kea, and windward Kohala (fig. 7). The leeward 

Mauna Loa relation was spatially extended to include Hualälai. Data from a CWRM rain gage and mechanical fog gage at 

Kemole (fig. 3) were used to develop a relation of fog interception to rainfall that was used for leeward Mauna Kea. Table 

3 displays the ratios of mechanical fog interception to rainfall 

used in the water-budget model. On the basis of the Juvik and 

Ekern (1978, p. 24) report, it was assumed that no fog interception occurs below an elevation of 2,500 ft. Also, it was 

assumed that no fog interception occurs on leeward Kohala.

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). For this study, a fog-catch efficiency parameter 

(table 4) was introduced to account for the efficiency with 

which each land-cover category intercepts fog water. It is a 

ratio of the amount of fog intercepted by the land cover to 

the amount of fog intercepted by a mechanical collector. To 

calculate the total amount of fog interception for a given day, 

the following equation was used:

 Fi = Pi × FIR × FCE (13)

where

Fi = the amount of fog interception for day i [L],

Pi = the amount of rainfall for day i [L],

FIR = the fog interception-to-rainfall ratio 

[dimensionless], which is assumed to be 

constant within a month, and

FCE = the fog-catch efficiency for the land cover 

[dimensionless].

In the water-budget model, fog interception was considered hydrologically significant only for land covers with trees 

and shrubs (see figs. 4 and 7). Other land-cover categories did 

not receive fog interception in the water-budget calculations. 
156°

155°

155°20'

155°40'

20°

19°40'

19°20'

19°

EXPLANATION

Elevation contour, 

in feet above sea 

level—Contour interval 

 1,000 feet.

Major road

Kona water-budget area

Fog zone 1 

(data from Juvik and Ekern, 1978)

Fog zone 2 

(data from Juvik and Ekern, 1978)

Fog zone 3 

(data from CWRM Kemole Station, 

http://hawaii.gov/dlnr/cwrm/

monitoringdata/rainfog_kemole.pdf)

Areas of fog contribution—Darker 

 shade indicates forest and lighter 

 shade indicates shrubland)

7,000

1,000

2,000

3,000

4,000

5,000

7,000

7,000

9,000

11,000

11,000

2,000

4,000

Häwï

Kawaihae

Waikoloa 

Village

Waimea

Honokaÿa

Hilo

Kailua

Captain Cook

Volcano

Pähala

Näÿälehu

Mountain 

View Pähoa

Q

Q

Q

13,681 ft

13,796 ft

8,271 ft

0 10 20 Miles

0 10 20 Kilometers

Base modified from U.S. Geological Survey 

National Hydrography Dataset, 1:24,000,

Universal Transverse Mercator projection, 

zone 5, NAD83 datum.

Figure 7. Areas of fog contribution to the water budget on the Island of Hawaiÿi.

16 A Water-Budget Model and Assessment of Groundwater Recharge for the Island of Hawai‘i
Model Input 17

Table 3. Ratios of fog interception to rainfall used in the water-budget model for the Island of Hawai‘i.

[See figure 7 for locations of fog zones; ft, feet above mean sea level]

Elevation (ft) Jan Feb Mar Apr May June July Aug Sept Oct Nov Dec

Fog zone 1 

Leeward Mauna Loa and Hualälai

2,500 to 2,999 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02

3,000 to 3,999 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.12

4,000 to 4,999 0.21 0.21 0.21 0.21 0.21 0.21 0.21 0.21 0.21 0.21 0.21 0.21

5,000 to 5,999 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31 0.31

6,000 to 6,999 0.40 0.40 0.40 0.40 0.40 0.40 0.40 0.40 0.40 0.40 0.40 0.40

7,000 to 7,999 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50

8,000 to 8,999 0.60 0.60 0.60 0.60 0.60 0.60 0.60 0.60 0.60 0.60 0.60 0.60

9,000 and above 0.69 0.69 0.69 0.69 0.69 0.69 0.69 0.69 0.69 0.69 0.69 0.69

Fog zone 2 

Windward sides of Kohala and Mauna Kea, windward and southeastern Mauna Loa, and all of Kīlauea

2,500 to 2,999 0.01 0.01 0.02 0.04 0.05 0.07 0.10 0.13 0.11 0.09 0.05 0.03

3,000 to 3,999 0.04 0.05 0.07 0.12 0.16 0.22 0.30 0.39 0.31 0.25 0.16 0.10

4,000 to 4,999 0.14 0.14 0.16 0.20 0.30 0.36 0.51 0.66 0.51 0.40 0.27 0.25

5,000 to 5,999 0.23 0.25 0.28 0.35 0.53 0.66 0.83 0.91 0.68 0.51 0.37 0.36

6,000 to 6,999 0.34 0.39 0.49 0.68 0.93 1.31 1.41 1.09 0.77 0.52 0.42 0.40

7,000 to 7,999 0.41 0.49 0.70 0.87 1.09 1.59 1.68 1.17 0.85 0.60 0.51 0.51

8,000 to 8,999 0.43 0.54 0.82 0.97 1.10 1.57 1.65 1.11 0.83 0.62 0.58 0.57

9,000 to 9,999 0.37 0.49 0.73 0.86 0.78 0.88 0.98 0.73 0.58 0.51 0.59 0.48

10,000 and above 0.40 0.56 0.78 0.79 0.45 0.42 0.51 0.37 0.35 0.46 0.60 0.48

Fog zone 3 

Leeward Mauna Kea

2,500 and above 0.42 0.73 0.56 0.38 0.42 0.32 0.32 0.34 0.18 0.15 0.16 0.39

physiography, available data from stream-gaging stations, and 

previous water-budget studies. This approach is similar to that 

employed in water budgets by Shade (1995), Oki (2002), and 

Engott and Vana (2007). Each zone was assigned a runoff-torainfall ratio for each calendar month, and this ratio was applied 

over the entire zone. Ideally, runoff ratios are calculated on the 

basis of data from continuous-record stream-gaging stations 

with long periods of record. However, perennial streams are 

relatively few on the island, and continuous streamgage records 

generally are sporadic or nonexistent. Other sources or methods 

used for assigning monthly runoff ratios (in order of preference) 

were: (1) ratios for the same area from previously published 

reports, (2) ratios for comparable areas from previously 

published reports, (3) averaging of ratios from the same area or 

from comparable areas, or (4) estimation based on geomorphology and climate of the area.

Runoff Zones

The island was divided into 17 runoff zones (fig. 8). 

Runoff zones 1, 2, and 3 are on the windward side of Kohala 

Mountain and are based on areas delineated and used in the 

water budgets by Shade (1995) and Oki (2002). Zone 1 is the 

area below the 400-ft elevation contour and west of Pololü 

Valley. Zone 2 is the area above the 400-ft elevation contour 

and west of Pololü Valley. Zone 3 consists of Pololü and 

Waipiö Valleys and all the valleys between them. Abundant 

rainfall in this area, ranging from about 70 in/yr to 160 in/yr, 

supports numerous perennial streams that have created deeply 

incised valleys. 

Runoff zones 4 through 7 are on the windward side of 

Mauna Kea. Zone 4 is the area (1) below the 6,560-ft elevation contour, the typical base of the tradewind inversion and 

(2) having mean annual rainfall less than 118 in. Some streams 

in this area are perennial at lower elevations but intermittent 

at higher elevations. Zone 5 is the area that lies above the 

6,560-ft elevation contour, or the tree line as defined by the 

boundary between grassland and forested land covers, on the 

eastern side of Mauna Kea (fig. 4). The climate here is much 

drier than in other parts of windward Mauna Kea, hence less 

weathering and erosion of the land surface has occurred in this 

zone. For the remaining area of windward Mauna Kea, runoff 
Table 4. Land-cover parameters used in water-budget calculations for the Island of Hawaiÿi.

Land-cover description Root depth 

(inches)

Pervious 

fraction

Depletion 

fraction Pan coefficient Fog-catch efficiency

Open native forest 25 1 0.50 0.84c

, 0.44d 1

Closed native forest 30 1 0.50 0.84c

, 0.44d 1

Alien forest 60 1 0.50 1.68c

, 0.88d 1

Mixed native/alien forest 45 1 0.50 1.68c

, 0.88d 1

Shrubland 12 1 0.50 0.85 0.5

Agriculture

Macadamia 60 1 0.50 0.77 1

Coffee 48 1 0.40 0.81 0.5

Diversified 12 1 0.35 0.85 0

Forest (eucalyptus) 60 1 0.50 1.10 1

Fallow/Grassland 39 1 0.60 0.81 0

Golf course 30 1 0.50 0.72 0

Low-intensity developed 12 0.8a 0.50 1.00 0

High-intensity developed 12 0.15b 0.50 1.00 0

Grassland 39 1 0.60 0.81 0

Sparsely vegetated 5 1 0.50 1.00 0

Wetland vegetation 6 1 0.50 1.00 0

Water body 0 1 1.00 1.00 0

a

Value is based on "residential" land cover in Engott and Vana (2007).

b

Value is based on "industrial and commercial complexes" land cover in Engott and Vana (2007).

c

Value used outside the fog zone to compute the combination of transpiration and ground evaporation. Canopy evaporation is

calculated separately.

d

Value used inside the fog zone to compute the combination of transpiration and ground evaporation. Canopy evaporation is

calculated separately.

18 A Water-Budget Model and Assessment of Groundwater Recharge for the Island of Hawai‘i

zones 6 and 7 were delineated on the basis of rainfall. In zone 

6, mean annual rainfall is greater than 118 in. and less than 

157 in. In zone 7, mean annual rainfall is greater than 157 in. 

In zones 6 and 7, annual rainfall is the highest on the island, 

and numerous perennial streams exist, some of which have 

carved deep valleys.

Runoff zone 8 is the windward part of Mauna Loa below 

the 6,560-ft elevation contour. This area includes relatively 

young land surfaces, with some lava flows as recent as 1984. 

Some streams exist owing to the high annual rainfall—as much 

as about 240 in/yr. Runoff zone 9 includes the surface lavas of 

Kïlauea, which generally are the youngest on the island. The 

land surface is extremely porous, allowing for very little runoff, except during the most intense rainstorms. Runoff zone 

10 is the southeastern side of Mauna Loa below the 6,560-ft 

elevation contour. Annual rainfall on this part of the island 

is quite high, ranging from about 49 in. to 138 in. Several 

streams have perennial reaches at elevations where rainfall is 

high and groundwater springs exist, but they are intermittent 

at lower and higher elevations where rainfall is less intense. 

Runoff zone 11 is the part of Mauna Loa that lies above the 

6,560-ft elevation contour, the typical base of the tradewind 

inversion. The land surface in this area is relatively young, 

with some lava flows as recent as 1984, and the climate is 

very dry. The relatively unweathered lavas are extremely 

porous and not conducive to producing large amounts of 

runoff. Runoff zone 12 is the southwestern part of leeward 

Mauna Loa lying below the tradewind inversion, and runoff 

zone 13 includes the surface rocks of Hualälai. Some shallow 

watercourses exist on the relatively young surfaces of these 

two zones. However, despite encompassing areas in which 

mean annual rainfall exceeds 80 in., no perennial streams 

flow, according to USGS streamgage data. Runoff zone 14 is 

the northwestern part of leeward Mauna Loa. This area is dry, 

and the surface rocks are relatively unweathered. Only a few, 

ill-defined watercourses exist, and these likely flow only during periods of heavy rain.

Runoff zone 15 is leeward Mauna Kea, the driest area 

of the island. No perennial streams exist in this area, only a 

network of shallow valleys and intermittent streams. Runoff 

zones 16 and 17 are on the leeward side of Kohala Mountain. 

The leeward slope of Kohala Mountain has a very steep rainfall gradient. Annual rainfall at the coast is about 10 in. near 

Kawaihae, whereas annual rainfall at the crest is about 120 in., 

a difference of 110 in. over less than 7 miles. Zone 17 is the 

area of leeward Kohala where mean annual rainfall exceeds 60 

in. In this zone, reaches of several streams flow perennially. 
156°

155°

155°20'

155°40'

20°

19°40'

19°20'

19°

EXPLANATION

Runoff zone

Kona water-budget area

Drainage basin

Perennial stream

Intermittent stream

USGS stream-gaging station

and abbreviated number—

 Complete numbers begin 

 with prefix 16

4

# 701750

#

#

#

#

#

#

#

#

#

1

2

3

4

5 6 7

8

9

10

11

12

13

14

15

16

17

717800

717600

717000

700000

770500

759300

759800

767000

701750

Häwï

Kawaihae

Waikoloa 

Village

Waimea

Honokaÿa

Hilo

Kailua

Captain Cook

Volcano

Näÿälehu

Mountain 

View

Pähoa

0 10 20 Miles

0 10 20 Kilometers

Base modified from U.S. Geological Survey 

National Hydrography Dataset, 1:24,000,

Universal Transverse Mercator projection, 

zone 5, NAD83 datum.

Figure 8. Runoff zones defined for the water-budget calculation on the Island of Hawaiÿi.

Model Input 19
20 A Water-Budget Model and Assessment of Groundwater Recharge for the Island of Hawai‘i

Flows in these streams diminish as they traverse zone 16, 

becoming intermittent before reaching the coast.

Runoff-to-Rainfall Ratios

Table 5 displays the monthly runoff-to-rainfall ratios 

assigned to each runoff zone for this water-budget model. It 

also summarizes the method or source used to assign the ratio. 

If runoff ratios were calculated using streamgage data, table 5 

shows the gaging-station number, stream, drainage-basin area, 

number of days used in the hydrograph-separation program, 

and period of record.

In zones where streamgage data were used to calculate ratios, mean monthly direct runoff for a drainage basin 

was divided by the long-term mean monthly rainfall over 

that basin (Giambelluca and others, 1986). Although actual 

monthly rainfall during the periods of record of the streamgaging stations may differ from the long-term mean monthly 

rainfall, this method is assumed to be valid for stream-gaging 

stations with relatively long periods of record and is consistent with other recent water-budget studies in the Hawaiian 

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

2007). For this water-budget model, two drainage basins, Älia 

(16717600) and Wai‘aha (16759300) (fig. 8), had streamgaging stations with periods of record deemed too short for the 

above assumption to hold. Älia Stream had only 10 years of 

record and Wai‘aha Stream only 11 years (table 5). For these 

basins, rainfall data from a nearby rain gage concurrent with 

the streamflow data were used instead of the long-term mean. 

For Älia Stream, NWS# 511960 was used, and for Wai‘aha, 

NWS# 511557 was used.

Computation of Runoff from 

Streamgage Data

Streamflow is composed of both direct runoff and base 

flow, which is groundwater that discharges into the stream. 

To separate the base-flow and direct-runoff components, the 

hydrograph-separation program of Wahl and Wahl (1995) 

was used. This computerized method removes much of the 

subjectivity associated with manual hydrograph-separation 

techniques, and it provides repeatable results if the two input 

parameters required by the method are held constant. The 

program is commonly used by the USGS in Hawai‘i (see for 

example, Fontaine, 2003; Izuka and others, 2005; and Engott 

and Vana, 2007). In the method, the two parameters that must 

be input are N (number of days) and f (turning-point test factor). The separation method divides the daily streamflow data 

into distinct, nonoverlapping periods, each N days long, and 

determines the minimum flow in each period. The program 

computes f times the central minimum and compares that to 

the adjacent minimums. If f times the central minimum is 

less than the adjacent minimums, then the central minimum 

is made a pivot (or turning point) on the base-flow hydrograph. Straight lines drawn on semilogarithmic paper between 

turning-point discharge plotted versus the central time of the 

corresponding period defines the base-flow hydrograph. The 

recommended value of f, 0.9 (Wahl and Wahl, 1995), was used 

for all base-flow separations. Conceptually, the variable N

represents the number of days following a storm before direct 

runoff generally ceases (Fontaine, 2003). N is determined 

separately for each stream-gaging station. To determine N for 

each stream-gaging station, base flow was first estimated for 

each value of N between 1 and 10 days. The ratio of base flow 

to total flow during the time period of N days, or base-flow 

index, was then plotted against N. As the value for N increases 

from 1, estimated base flow declines sharply because the portion of direct runoff in the total flow is reduced as the effect 

of storms dissipate during the larger time period. At a critical value of N, the portion of direct runoff will be negligible 

and estimated base flow will drop only slightly, becoming 

essentially linear with increasing N. This critical N value was 

then used to estimate base flow for the stream-gaging station 

being analyzed (table 5). Hydrograph separation was not used 

for Pa‘au‘au and Ninole Streams in runoff zone 10 because 

the base-flow component of streamflow is negligible in both 

streams. For runoff zone 10, the ratio of runoff to rainfall was 

calculated using total flow.

Evapotranspiration

Evapotranspiration (ET) is a collective term for all of the 

evaporative processes occurring in a plant-soil system. These 

processes can be grouped into three main types: (1) canopy 

evaporation, which is evaporation of intercepted rain and fog 

from the surface of vegetation; (2) ground evaporation, which 

is evaporation 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 as 

it exits at plant pores (Viessman and Lewis, 2003, p. 143). 

These processes are difficult to quantify individually and are 

commonly combined together in water budgets. Water budgets 

for Hawaiÿi, including all of those listed in table 1, have 

treated ET in this manner (for example, Giambelluca, 1983; 

Izuka and others, 2005; and Engott and Vana, 2007). A more 

rigorous treatment of ET may be appropriate for some areas 

because ET processes tend to operate on much different time 

scales and vary in relative importance according to prevailing 

meteorological conditions and land-cover setting. Canopy and 

ground evaporation operate on the order of hours, whereas 

transpiration operates on the order of weeks or longer, depending on soil depth (Savenije, 2004). 

Canopy evaporation can be very important in forests. 

Because of the height of trees, turbulent diffusion is much 

more efficient at removing intercepted water from forests 

than from other land-cover types, and this enhanced rate of 

evaporation from wet canopy makes realistic estimates of ET 

from forests possible only if transpiration and canopy evaporation are evaluated separately (Shuttleworth, 1993). In this 

study, ET in forests is calculated by separately estimating 
Table 5. Ratios of runoff to rainfall used in the water-budget model for the Island of Hawaiÿi.

[See figure 8 for locations of runoff zones; Avg., average; N, number of days used for determining minimum flows in the hydrograph-separation program (Wahl and Wahl, 1995); –, blank field; N/A, not applicable]

Runoff 

zone

Ratio of runoff to rainfall Method or data source 

used to calculate 

runoff-to-rainfall ratios

Gagingstation 

number

Stream/river

Basin 

area 

(acres)

N

Periods of 

record used in 

calculation Jan Feb Mar Apr May June July Aug Sept Oct Nov Dec Avg.

1 0.110 0.070 0.120 0.120 0.060 0.010 0.070 0.090 0.010 0.060 0.110 0.110 0.078 Shade (1995), area B, zone 5 – – – – –

2 0.180 0.170 0.180 0.180 0.070 0.070 0.080 0.080 0.060 0.070 0.170 0.180 0.124 Shade (1995), area B, zones 1 and 7 – – – – –3 0.270 0.260 0.400 0.390 0.340 0.320 0.410 0.300 0.250 0.320 0.350 0.330 0.328 Shade (1995), area A – – – – –4 0.180 0.170 0.180 0.180 0.070 0.070 0.080 0.080 0.060 0.070 0.170 0.180 0.124 Shade (1995), area B, zones 1 and 7 – – – – –5 0.021 0.010 0.025 0.012 0.005 0.002 0.007 0.016 0.001 0.003 0.020 0.020 0.012 USGS stream-gaging station 16701750 Wailuku 28,923 4 1965–82

6 0.383 0.395 0.419 0.422 0.283 0.213 0.253 0.248 0.204 0.221 0.413 0.369 0.319 Average of runoff zones 4 and 7 – – – – –

7 0.586 0.621 0.657 0.664 0.496 0.356 0.426 0.417 0.348 0.371 0.656 0.558 0.513 Average 

of 3 USGS stream-gaging stations

16717000 Honoli‘i 7,549 3 1911–12, 1967–200616717600 Älia 395 3 1962–7116717800 Pöhakupuka 1,824 3 1962–79

8 0.025 0.025 0.027 0.025 0.025 0.016 0.017 0.021 0.021 0.022 0.026 0.026 0.023 USGS stream-gaging station 16700000 Waiäkea 10,989 4 1931–90

9 0.025 0.025 0.027 0.025 0.025 0.016 0.017 0.021 0.021 0.022 0.026 0.026 0.023 USGS stream-gaging station 16700000 Waiäkea 10,989 4 1931–90

10 0.208 0.136 0.076 0.087 0.092 0.082 0.106 0.106 0.062 0.075 0.184 0.110 0.110 Average 

of 2 USGS streamgaging stations

16770500 Pä‘au‘au 1,033 N/A 1962–78, 2001–0616767000 Nïnole 3,502 N/A 1966–82

11 0.010 0.010 0.010 0.010 0.010 0.010 0.010 0.010 0.010 0.010 0.010 0.010 0.010 Estimate – – – – –

12 0.045 0.054 0.059 0.079 0.081 0.057 0.064 0.053 0.054 0.037 0.052 0.041 0.056 USGS stream-gaging station 16759800 Ki‘ilae 609 4 1958–82

13 0.013 0.008 0.021 0.035 0.022 0.019 0.019 0.039 0.024 0.039 0.027 0.011 0.023 USGS stream-gaging station 16759300 Wai‘aha 5,583 4 1960–70

14 0.010 0.010 0.050 0.005 0.005 0.000 0.005 0.000 0.005 0.000 0.020 0.005 0.010 Engott and Vana (2007), region 4 – – – – –

15 0.010 0.010 0.050 0.005 0.005 0.000 0.005 0.000 0.005 0.000 0.020 0.005 0.010 Engott and Vana (2007), region 4 – – – – –

16 0.130 0.070 0.100 0.060 0.020 0.010 0.010 0.020 0.010 0.030 0.110 0.080 0.054 Shade (1995), area C, zone 4 – – – – –

17 0.440 0.450 0.450 0.470 0.540 0.410 0.380 0.490 0.210 0.230 0.430 0.560 0.422 Shade (1995), area C, zone 3 – – – – –

Model Input 21
Figure 9. Analysis of the linear 

relation between net precipitation 

and fog interception in forests, based 

on data from studies in the Hawaiian 

Islands and similar tropical locations 

around the world.

0 20 40 60 80 100

 0

 20

 40

 60

 80

100

120

140

160

Net precipitation, in percent of rainfall

Fog interception, in inches per year

NET PRECIPITATION = 0.70 x FOG INTERCEPTION + 73.45

R2 = 0.895

Queensland, Australia–3 sites (McJannet and others, 2007)

Leeward Mauna Kea, Hawai‘i (Juvik and Nullet, 1995)

Windward Kohala, Hawai‘i (DeLay, 2005)

Puerto Rico (Schellekens and others, 1998)

Peru (Gomez-Peralta and others, 2008)

Average of 29 sites in non-fog forests: 12 from 

 Bruijnzeel (2001), 3 from Mair (2009), 12 from 

 Gaskill (2004), 1 from McJannet and others (2007), 

 and 1 from Gomez-Peralta and others (2008). The 

 regression line is forced through this intercept point.

EXPLANATION

22 A Water-Budget Model and Assessment of Groundwater Recharge for the Island of Hawai‘i

canopy evaporation and combined ground evaporation and 

transpiration. These two terms are then added together to yield 

a total ET rate. For all other land covers, ET is calculated 

using a more traditional approach, commonly used in agricultural practice and other water budgets for Hawaiÿi, in which 

no separate estimates of canopy evaporation and combined 

ground evaporation and transpiration are made. The concept 

of potential ET, combined with soil-moisture limiting, is used 

to estimate ground evaporation and transpiration in forests 

and total ET for all other land covers. Canopy evaporation in 

forests is estimated using data from published studies.

Canopy Evaporation and Net Precipitation

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

droplets will strike and collect on the leaves, trunks, or stems 

of the vegetation in a process known as canopy interception. 

Additional moisture from fog interception may also enhance 

the volume of this collected water, which commonly is called 

“canopy storage.” Canopy storage is partitioned into three 

fractions: (1) that which remains on the vegetation and is 

evaporated after or during rainfall, called “canopy evaporation” in this study; (2) that which flows to the ground along 

trunks or stems, commonly called “stemflow;” and (3) that 

which drips from the canopy and falls to the ground between 

the various components of the vegetation (Crockford and 

Richardson, 2000). The fraction of rain that does not contact vegetation on the way to the ground combined with the 

fraction described in (3) commonly is called “throughfall.” 

The amount of water that reaches the soil surface, commonly 

called “net precipitation,” is the sum of throughfall and 

stemflow. Canopy interception occurs in all vegetated land 

covers, but research primarily has been limited to forests. 

Direct measurements of canopy evaporation are very difficult 

to obtain and rarely attempted. Instead, it is far more common for researchers to collect net precipitation on the floor 

of a forest, beneath the canopy, and compare it to rainfall 

collected contemporaneously above the forest canopy or in a 

nearby open field. Therefore, net precipitation commonly is 

reported as a percentage of rainfall, regardless of whether or 

not fog interception is occurring in the forest. In areas where 

fog interception occurs, it is possible for net precipitation to 

be greater than 100 percent of rainfall.

For the water-budget model, net precipitation in forests 

was estimated using published studies listed on figure 9. 

Nearly one-half of the sites investigated in these studies are 

in the Hawaiian Islands—17 of 36. The rest of the sites are 

in similar tropical locations. For forests outside of the fog 

zone (see figure 7), the average net-precipitation value of 29 

sites, 73.45 percent of rainfall, was used, For forests in the fog 

zone, a linear regression was applied to net-precipitation and 

fog-interception data from the published studies (figure 9). 

For the point on the graph where fog interception equals zero 

(the y-intercept), the aforementioned average net-precipitation 

value of the 29 nonfog forest sites was used. The regression 

line was forced through this value. As expected, net precipitation increases with increasing fog interception. The linear relation is strong, as shown by a coefficient of determination (R2

) 

of 0.895. However, there is a large gap in the data between 

the site with the highest fog-interception and that with the 

second highest. More data from sites where fog interception is 

between about 30 in/yr and 90 in/yr would increase confidence 

in the regression.
Table 6. Ratios of monthly to annual pan evaporation for each pan-evaporation zone used in the water-budget 

calculation for the Island of Hawaiÿi.

[See figure 10 for locations of pan-evaporation zones; sta, station]

Panevaporation 

zone

Ratio of monthly to annual pan evaporation

Source station or reference

Jan Feb Mar Apr May June July Aug Sept Oct Nov Dec

1 0.08 0.08 0.08 0.09 0.09 0.08 0.09 0.08 0.08 0.09 0.08 0.08 Kainaliu SCAN 

(solar radiation variability)

2 0.07 0.07 0.06 0.07 0.08 0.09 0.12 0.11 0.10 0.09 0.08 0.07 Waikoloa 95.8 

(interpolated values in italics)

3 0.07 0.07 0.08 0.08 0.09 0.10 0.10 0.10 0.10 0.08 0.07 0.07 Hawi 168

4 0.07 0.07 0.09 0.08 0.09 0.09 0.09 0.09 0.09 0.08 0.08 0.07 Ähualoa 215.3

5 0.06 0.06 0.08 0.08 0.10 0.11 0.10 0.10 0.10 0.08 0.07 0.06 Hämäkua Makai 221.3

6 0.07 0.08 0.09 0.09 0.10 0.10 0.09 0.09 0.09 0.08 0.06 0.05 Juvik and Nullet (1994) 

sta. 1,130 m (3,707 ft.)

7 0.08 0.07 0.08 0.09 0.09 0.10 0.10 0.09 0.09 0.08 0.06 0.07 Hilo Airport 87

8 0.07 0.07 0.08 0.09 0.09 0.09 0.10 0.10 0.09 0.08 0.07 0.07 Pähala 21

9 0.09 0.07 0.08 0.11 0.11 0.10 0.10 0.09 0.07 0.07 0.06 0.07 Minyard and others (1994) 

sta. 3,000 m (9,842 ft.)

Model Input 23

Potential Evapotranspiration

The maximum rate at which water can be removed from 

the plant-root zone by ET, if soil-moisture is nonlimiting, is 

termed “potential ET” (Giambelluca, 1983). The actual rate 

of ET 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 more 

strongly, 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. 

The actual rate of ET is a function of potential ET, soil-moisture 

content, and threshold-moisture content (see equation 9).

Potential evapotranspiration is controlled by prevailing atmospheric conditions (solar radiation, air temperature, 

humidity, and wind) and land-cover characteristics (reflectance, roughness, and plant physiology) (Giambelluca, 1983). 

Potential-ET data for Hawai‘i are fairly sparse; however, a 

significant amount of pan-evaporation data has been collected 

over many years by sugar plantations. Measurements of pan 

evaporation, although highly correlated with atmospheric 

conditions, are poorly correlated with land-cover characteristics. To account for land-cover characteristics, previous studies 

developed pan coefficients for Hawai‘i based on vegetative 

cover (Ekern and Chang, 1985; Oki, 2002, Izuka and others 

2005, Engott and Vana, 2007). A pan coefficient is an empirically derived ratio of potential ET to pan evaporation. In this 

study, potential ET for an area with a particular land cover is 

estimated by multiplying pan evaporation for the area by the 

appropriate pan coefficient. 

Pan Evaporation 

Mean rates of pan evaporation vary across the island 

according to location and time of year. To accommodate this 

variability, the study area was divided into pan-evaporation 

zones (pan zones) on the basis of (1) the mean annual rate of 

pan evaporation, (2) the monthly variability of pan evaporation, and (3) the source of data for monthly variability (fig. 10). 

Mean annual pan evaporation was derived from the map by 

Ekern and Chang (1985). In the model, areas between lines of 

equal pan evaporation were assigned the average values of the 

bounding lines. 

To estimate monthly variability in each zone, ratios of 

monthly to annual pan evaporation were computed (table 6). 

Mean monthly pan-evaporation data (Ekern and Chang, 1985) 

for pan-evaporation stations within each zone were used. For 

pan zones in which pan-evaporation data were unavailable, 

alternate methods of estimating monthly variability were used. 

For pan zone 1, solar radiation data were used as a proxy for 

pan evaporation, because pan evaporation is well correlated 

with solar radiation (Ekern and Chang, 1985; Bean and others, 

1994). For pan zone 6, Penman-Monteith evaporation from 

Juvik and Nullet (1994) calculated for a station at 1,130 m 

(3,707 ft.) on windward Mauna Loa was used. For pan zone 9, 

which includes areas on Mauna Kea and Mauna Loa that are 

above the 8,500-ft contour, evaporimeter data from Minyard 

and others (1994) for a station at 3,000 m (9,842 ft.) on Haleakalä, Maui, were used.

For climate-change scenarios, future mean pan evaporation was estimated by deriving a relation between historical pan evaporation and rainfall and applying the relation 

to projected future mean rainfall. Details of this methodology are given in the “Climate Change” subsection of the 
Figure 10. Mean annual pan evaporation (modified from Ekern and Chang, 1985) and pan-evaporation zones defined for 

the water-budget calculation on the Island of Hawaiÿi.

156°

155°

155°20'

155°40'

20°

19°40'

19°20'

19° 20–30

30–40

40–50

50–60

60–70

70–80

80–90

90–100

100–110

EXPLANATION

Pan-evaporation zone

Kona water-budget area

Pan-evaporation station

 and state key number

Climate station and

 reference letter

Mean pan 

evaporation, in 

inches per year

087

A

3

A− Kainaliu SCAN (soil climate

 analysis network) station,

 http://www.wcc.nrcs.usda.gov/scan/

B− Windward Mauna Loa station at

 3,707 ft (1,130 m) in Juvik and

 Nullet (1994)

0

0

0

0

0

0

168

215.3

B

A

21

87

95.8

221.3

7

9

8

9

1

2

3

4

5

6

8,500-ft elevation countour

8,500-ft elevation countour

2,000-ft elevation countour

0 10 20 Miles

0 10 20 Kilometers

Base modified from U.S. Geological Survey 

National Hydrography Dataset, 1:24,000,

Universal Transverse Mercator projection, 

zone 5, NAD83 datum.

24 A Water-Budget Model and Assessment of Groundwater Recharge for the Island of Hawai‘i
Model Input 25

“Groundwater-Recharge Estimates” section of this report. 

For model scenarios in which mean rainfall (with interannual 

variability), historical rainfall, or estimated drought conditions 

were used, mean pan evaporation was not altered from that 

derived from the Ekern and Chang (1985) map, even though 

rainfall was not necessarily equal to mean rainfall in these 

scenarios. This approach is consistent with recent water-budget studies for the Hawaiian Islands (for example, Oki, 2002; 

Izuka and others, 2005; Engott and Vana, 2007); moreover, the 

relations between historical pan evaporation and rainfall were 

deemed to be too weak to justify altering the long-term mean 

pan-evaporation distributions of Ekern and Chang (1985) for 

these scenarios. For climate-change scenarios, it was decided 

that a mean pan-evaporation distribution different from the 

historical one described by Ekern and Chang (1985) must be 

projected. The pan evaporation-to-rainfall relations, although 

weak, were used for climate-change scenarios owing to the 

dearth of available projections of future pan evaporation and 

other associated climate variables, such as solar radiation, 

wind speed, temperature, and relative humidity.

Pan Coefficients

Pan coefficients are ratios of potential ET to pan evaporation for a given land cover. For each nonforest land-cover 

category, a pan coefficient was assigned on the basis of data 

from a variety of sources (table 4). In this study, a significant number of pan coefficients were derived from the “crop 

coefficients” of Allen and others (1998). In their model, 

potential ET is termed “reference-crop evapotranspiration” 

and is defined as the evapotranspiration from a hypothetical 

grass surface of specific characteristics, with no soil-moisture stress. Allen and others (1998) estimate reference-crop 

evapotranspiration using a modified version of the PenmanMonteith equation (Monteith, 1965). As suggested in Allen 

and others (1998), a ratio of reference-crop evapotranspiration to pan evaporation, kp, was used to convert their crop 

coefficients to the pan coefficients used in this study. The 

ratio kp was estimated using two methods. One method 

involved comparing sugarcane crop coefficients in Allen 

and others (1998) with data from the numerous sugarcane 

studies performed in Hawai‘i. In Allen and others (1998), the 

crop coefficient assigned to the mid-growth stage of sugarcane is 1.25, whereas the generally accepted pan coefficient 

in Hawaiian studies is 1.0 (Ekern, 1971; Fukunaga, 1978, 

Giambelluca, 1983). Using these two values, kp can be back 

calculated as 0.8 (1.0/1.25). A second method for estimating 

kp was based on concurrent pan-evaporation and PenmanMonteith measurements made by Bean and others (1994) on 

Mauna Loa. In their study, mean Penman-Monteith evaporation was found to be 90 percent of mean pan evaporation, 

implying a kp of 0.9. The average kp from these two methods, 

0.85, was used as kp in this study. Accordingly, all crop coefficients taken from Allen and others (1998) were converted 

to pan coefficients by multiplying by 0.85. This conversion 

was also applied to crop coefficients taken from the irrigation 

model of Fares (2008), which is based on the same underlying theories as Allen and others (1998). 

It is necessary for the water-budget model to estimate a 

pan coefficient for combined transpiration and ground evaporation in each forest land-cover category. In this study, forest 

land cover is separated into four categories: open native 

forest, closed native forest, mixed forest, and alien forest. 

In general, previous water budgets for the Island of Hawai‘i 

(table 1) and other Hawaiian islands (see for example, Izuka 

and others, 2005; Engott and Vana, 2007) placed all forested 

areas into a single land-cover category, failing to account 

for nonuniformity in forest structure and species. Owing to 

the recent publication of improved land-cover maps (U.S. 

Geological Survey, 2006) and ongoing studies of Hawaiian 

forest hydrology (Santiago and others, 2000; Giambelluca 

and others, 2009a; Giambelluca and others. 2009b; Kagawa 

and others, 2009), it has become feasible to attempt to 

distinguish differences in water-budget parameters among 

different, albeit broad, categories of forest structure and 

species. Evidence exists that forests frequently affected by 

low clouds and fog transpire less water than forests in drier 

areas because of lower canopy conductances (Bruijnzeel and 

Veneklaas, 1998). Accordingly, each of the forest categories 

is divided into fog and nonfog subcategories on the basis of 

whether it is inside or outside the fog zone.

Whereas most ET studies in Hawai‘i have focused on 

agricultural crops, neglecting the forested watershed, one 

recent study, undertaken by Giambelluca and others (2009b) 

on Kïlauea, examined the evaporation and energy balance of 

a closed Metrosideros polymorpha (ohia) native forest, the 

most common forest type on the Island of Hawai‘i. The site 

is located in the fog zone at an elevation of about 4,000 ft. 

They used eddy covariance measurements and a Bowen-ratio 

closure approach to estimate an annual total ET rate of 1,232 

mm (48.5 in.), which was about 51 percent of annual rainfall 

(94.5 in.). To determine the pan coefficient for combined transpiration and ground evaporation necessary to reproduce the 

same ratio of total ET to rainfall, the recharge model was run 

multiple times with the pan coefficient incrementally changed 

for each successive run. The values of all other input parameters were set to baseline conditions, which used 2008 land 

cover and mean annual rainfall from the period 1916–1983, 

and were not altered for successive model runs. The pan coefficient that reproduced the 51 percent total-ET-to-rainfall ratio 

was 0.44 (table 4). Thus, all native fog forests were assigned 

this value.

Santiago and others (2000) measured sapflow to estimate 

transpiration in a closed M. polymorpha forest on East Maui. 

They reported transpiration rates at three nonwaterlogged 

sites that were 79 to 89 percent of Penman-Monteith evaporation during the 5 days with the highest evaporative demand. 

Adding the estimated rate of daily ground evaporation of 0.10 

mm (0.004 in.) reported by Jordan and Heuveldop (1981) for 

tropical rainforest in Venezuela, results in values ranging from 

81 to 95 percent of Penman-Monteith evaporation. Converting 

to pan evaporation using a kp of 0.85 yields pan coefficients 
26 A Water-Budget Model and Assessment of Groundwater Recharge for the Island of Hawai‘i

for combined transpiration and ground evaporation ranging 

from 0.69 to 0.81, with an average value of 0.74 for the three 

sites. Although it was not explicitly stated in Santiago and 

others (2000), it could be assumed that during these 5-day 

periods the presence of fog was minimal. In a different study, 

Giambelluca and others (2009a) measured sapflow to estimate transpiration in a native M. polymorpha forest on the 

Island of Hawaiÿi during periods of wet and dry canopy. The 

mean transpiration rate during periods when the canopy was 

partially wet was reported to be 47 percent of transpiration 

during dry-canopy periods. If it is assumed that the result is 

representative of transpiration in native fog forests (partially 

wet canopy) and transpiration in native nonfog forests (dry 

canopy), then the pan coefficient for native nonfog forest 

could be computed from the pan coefficient for native fog 

forest (0.44) by dividing it by 0.47. The resulting value is 

0.94. In the water-budget model, 0.84 was used as the combined transpiration and ground-evaporation pan coefficient 

for native nonfog forest. This is the average of the values 

derived from the Santiago and others (2000) study and the 

Giambelluca and others (2009a) study.

In general, invasive alien species of trees consume 

more water through ET than native species (Calder and Dye, 

2001). On leeward Mauna Loa, Kagawa and others (2009) 

reported transpiration rates, as measured by sapflow, in an 

alien Eucalyptus saligna plantation and an alien Fraxinus 

uhdei (tropical ash) forest that were, respectively, about 1.3 

and 2.5 times the rate in a native M. polymorpha forest. The 

pan coefficient used in this study for alien forest inside the 

fog zone is 0.88, twice the pan coefficient for native forest 

inside the fog zone (0.44 x 2). This is also the pan coefficient used for mixed alien/native forest inside the fog zone. 

Outside the fog zone, the pan coefficient for both of these 

two forests types is 1.68 (0.84 x 2). The pan coefficient for 

agricultural forest (eucalyptus) is also 1.68. Agricultural forest (eucalyptus) only occurs outside the fog zone.

Differences in ET between open and closed canopy 

forests largely are a matter of degree of canopy openness 

or gap fraction (Tobon Marin and others, 2000). ET rates 

in forests are highly localized. In more open forest settings, 

individual trees may have high rates of ET owing to higher 

aerodynamic roughness and increased insolation, whereas 

closed forests generally have more trees that may intercept 

and transpire more water in total. Owing to this indeterminacy and lack of applicable studies, no distinction is made 

in the water-budget model between open and closed forests 

with regard to pan coefficients.

For other land-cover categories in this study, the pan 

coefficients assigned are based on total ET. Both shrubland 

and diversified agriculture were assigned a pan coefficient 

of 0.85, the same as in Izuka and others (2005) and Engott 

and Vana (2007). Pan coefficients for wetland vegetation, 

fallow/grassland, golf course, and grassland were derived 

from Allen and others (1998). The golf-course pan coefficient is based on the warm-season turfgrass listing. The pan 

coefficient for macadamia was derived from Fares (2008), 

and the pan coefficient for coffee is the average of the coefficients derived from Allen and others (1998) and Fares 

(2008). Pan coefficients for low-intensity and high-intensity 

developed land are based on the urban category in Giambelluca (1983). The sparsely vegetated land-cover category 

mainly consists of recent, unvegetated, lava flows (U.S. Geological Survey, 2006). Owing to a dearth of studies on the 

evaporation properties of bare lava, this category was treated 

like a bare soil, the same approach used by Contor (2004) for 

a study of recharge beneath lava flows in Idaho. Results from 

Contor (2004) were subsequently used in a recharge assessment for parts of Idaho and Washington (Bartolino, 2007). 

Penman (1948) reported the rate of bare-soil evaporation to 

be 90 percent of pan evaporation. Ekern (1966) reported that 

a bare latosol soil on O‘ahu exhibited an evaporation rate 

that was 36 percent of a fully vegetated surface. However, 

this soil displays a self-mulching action (Ekern, 1966) that is 

unlikely to occur in bare lava. Allen and others (1998) suggests a pan-coefficient range of 0.9 to 1.1 (converted using 

kp) for bare soil. On the basis of Allen and others (1998) 

and the assumption that bare lava and bare soil share similar 

evaporation properties, a pan coefficient of 1.0 was assigned 

to sparsely vegetated land in this study.

Moisture-Storage Capacity

Moisture-storage capacity was computed as the product 

of available water capacity and root depth (equation 8). Figure 

11 displays the distribution of moisture-storage capacities on 

the Island of Hawai‘i.

Available water capacity varies by soil type and is a 

measure of the maximum depth of water per unit depth of soil 

available for consumption by plants. Previously published soil 

maps and corresponding tables of available water capacities 

(U.S. Department of Agriculture, 2008) were used to distribute 

available water capacity over the study area. The published 

tables list available water capacities for each soil type as minimum and maximum values at various ranges of depth. In this 

study, a depth-weighted average available water capacity was 

then computed and assigned to each soil type.

Root depth varies by land-cover category (table 4). In 

this study, assignments of root depths were based on previously published information. The root depth for open native 

forest is the same as in Giambelluca (1983) for dry forest and 

in Shade (1995) for open koa forest. The root depth for closed 

native forest is the same as in Shade (1995) for closed ohia/

fern forest and in Oki (2002) for forest with canopy coverage greater than 25 percent. The root depth for alien forest is 

the average root depth given for young and old eucalyptus in 

Fares (2008). The root depth for mixed forest is the average 

of the root depths for closed native forest and alien forest. 

The root depth for shrubland is the same as in Giambelluca 

(1983) for dry scrub. The root depths for macadamia, coffee, 

and diversified agriculture are based on Fares (2008). Root 
Figure 11. Calculated moisture-storage capacity on the Island of Hawai‘i.

0

0.01–2.00

2.01–5.00

5.01–10.00

10.01–23.52

EXPLANATION

Moisture-storage capacity, in inches

Kona-area boundary

156°

155°

155°20'

155°40'

20°

19°40'

19°20'

19°

Häwï

Kawaihae

Waikoloa 

Village

Waimea

Honokaÿa

Hilo

Kailua

Captain Cook

Volcano

Pähala

Näÿälehu

Mountain 

View

Pähoa

0 10 20 Miles

0 10 20 Kilometers

Base modified from U.S. Geological Survey 

National Hydrography Dataset, 1:24,000,

Universal Transverse Mercator projection, 

zone 5, NAD83 datum.

Model Input 27
28 A Water-Budget Model and Assessment of Groundwater Recharge for the Island of Hawai‘i

depths for fallow/grassland, golf course, and grassland are 

based on Allen and others (1998). The golf-course root depth 

is based on the warm-season turfgrass listing. Root depths 

for low-intensity and high-intensity developed land are based 

on the urban category in Giambelluca (1983). The root depth 

for sparsely vegetated land is the average of the high and low 

values suggested by Allen and others (1998) for bare soil. The 

root depth for wetland vegetation is the same as in Engott and 

Vana (2007).

Direct Recharge

In this study, “direct recharge,” DR, is defined as water that 

passes directly to the groundwater system, completely bypassing the plant-soil zone (see equation 11). Direct recharge is not 

subject to runoff or ET. Three important anthropogenic sources 

of direct recharge on the Island of Hawai‘i are (1) cesspool leakage, (2) water-main leakage, and (3) the disposal pit for treated 

effluent from the Kealakehe Wastewater Treatment Plant. 

Cesspool leakage was calculated on the basis of censusblock population maps (State of Hawai‘i, 2001) of areas served 

by wastewater treatment plants (County of Hawai‘i, 2009) and 

an estimated rate of daily domestic water use of 100 gallons per 

capita per day (County of Hawai‘i, 2006). Areas of the island 

not serviced by wastewater treatment plants were assumed to 

be areas exclusively using cesspools. The rate of leakage in 

the cesspool areas was computed as the population of that area 

multiplied by the rate of daily domestic water use. The resulting 

rate was applied uniformly over the entire area.

Water-main leakage was calculated on the basis of maps 

of county and private water mains in the County of Hawai‘i 

(2006) Water Use and Development Plan Update and information on the amount of water that goes unmetered and is assumed 

lost in the public water system, according to the HDWS (Larry 

Beck, HDWS, written commun., 2009). For this study, the total 

amount of water-main leakage on the island was estimated to be 

1.2 Mgal/d and was applied at a uniform rate along the length of 

each water main.

The Kealakehe Wastewater Treatment Plant serves part 

of the Kona area in and around the town of Kailua (fig. 1). 

Effluent from the plant is disposed in a pit located just east of 

Honoköhau Bay. The estimated rate of effluent disposal used in 

this study was 1.5 Mgal/d, based on information in a County of 

Hawai‘i (2008) Planning Department report. 

Another source of direct recharge is seepage from the 

2,052 dry wells on the island that are used to dispose of runoff 

from paved surfaces. The drainage area of each dry well and the 

volumetric rate of water disposed are largely unknown. Hence, 

estimation of direct recharge from dry wells is not attempted in 

this report; however, it could be important to the local quality 

and quantity of recharge (Izuka and others, 2009).

Other Input

In addition to the water-budget inputs already discussed, 

several other inputs are required. The initial moisture storage was set at 50 percent of capacity; the rainfall-interception 

capacity for impervious surfaces was set at 0.25 in.; and the 

rate of groundwater recharge from surface-water bodies was 

set at 12 in/yr. The values assigned to these parameters are 

consistent with those for other recent Hawai‘i water budgets 

(Izuka and others, 2005; Engott and Vana, 2007). The effects 

of these parameters on regional-scale recharge generally are 

minor because they either pertain to only a small area or are 

applicable during only a small fraction of time. 

Model Randomness

The selection of monthly rainfall fragment sets (see 

“Rainfall” section) introduces randomness into the water-budget model. To account for this randomness, the water-budget 

model was run multiple times, and the results were averaged. 

To determine the appropriate number of simulations to run, 

the water-budget model for the Island of Hawai‘i was run 50 

times. The marginal, absolute percentage change in groundwater recharge for each of the 467,805 subareas was averaged 

for each number of simulations and is shown on figure 12. 

After 20 simulations, the average percentage change did not 

exceed 0.1 percent. This very small value, 0.1 percent, was 

determined to be adequate for this study. Accordingly, for each 

model scenario, the water-budget model was run 20 times, and 

the results were averaged.

Figure 12. The average absolute percentage change in 

recharge of all the water-budget subareas with each 

successive model simulation.

0.0

0.2

0.4

0.6

0.8

1.0

0 10 20 30 40 50

Number of simulations

Average absolute change in recharge

 from previous simulation, in percent

0.1 percent
0 10 20 30 40 50 100 200150 300

156°

155°

155°20'

155°40'

20°

19°40'

19°20'

19°

0 10 20 Miles

0 10 20 Kilometers

EXPLANATION

Mean annual groundwater recharge, in inches

Hilo

Waimea

Näÿälehu

Pähoa

Keaÿau

ÿÖlaÿa

Kaÿapuna

Onomea

ÿAnaehoÿomalu

Manukä

Kïholo

Ka Lae

Kalapana

Hakalau

Paÿauilo

Kealakekua

Keauhou

Keaïwa

Honokaÿa

Mähukona

Hilina

Häwï

Waimanu

Kapäpala

Base modified from U.S. Geological Survey 

National Hydrography Dataset, 1:24,000,

Universal Transverse Mercator projection, 

zone 5, NAD83 datum.

Model Randomness 29

Figure 13. The distribution of mean annual groundwater recharge for baseline conditions on the Island of Hawaiÿi 

calculated using the water-budget model. Areas of zero recharge appear as white. Boundaries of named aquifer systems 

(State of Hawaiÿi, 2008) are shown in gray. 
Table 7. Mean annual water-budget estimates for baseline and possible future conditions for each aquifer system on the 

Island of Hawaiÿi.

[Baseline condition is 2008 land cover with mean rainfall from Giambelluca and others (1986); drought condition is 2008 land cover with lowest observed 5-year 

average rainfall; urbanization I is land cover based on full development of parcels zoned for urban use by Hawaiÿi County (2007) with mean rainfall from Giambelluca and others (1986); urbanization II is land cover based on full development of urban parcels in the Land Use Pattern Allocation Guide (LUPAG) (County of 

Hawaiÿi, 2005) with mean rainfall from Giambelluca and others (1986); the alien-forest-to-native scenario is baseline conditions with alien-forest and mixed-forest 

land covers changed to open-canopy native forest; climate change I is land cover based on full development of urban parcels in the LUPAG (County of Hawaiÿi, 

2005) with estimated rainfall for late 21st century based on the upper margin of the 95-percent statistical confidence interval of the six-model ensemble from Timm 

and others (2009); climate change II is land cover based on full development of urban parcels in the LUPAG (County of Hawaiÿi, 2005) with estimated rainfall for 

late 21st century based on the mean of the six-model ensemble from Timm and others (2009); climate change III is land cover based on full development of urban 

parcels in the LUPAG (County of Hawaiÿi, 2005) with estimated rainfall for late 21st century based on the lower margin of the 95-percent statistical confidence interval of the six-model ensemble from Timm and others (2009); Mgal/d, million gallons per day; Irr, irrigation; DR, direct recharge; ET, evapotranspiration exclusive of 

canopy evaporation; CEvap, canopy evaporation in forested areas; Rech, recharge; WRPP, Water Resources Protection Plan (State of Hawaiÿi, 1990)]

Aquifer 

system

Aquifer 

code

Hypothetical

condition

Water-budget estimate (Mgal/d) WRPP

recharge 

(Mgal/d) Rain Fog Irr DR Runoff ET CEvap Rech

Häwï 80101 Baseline 172.23 2.03 2.20 0.45 22.10 108.82 24.84 21.09 29.9a

Drought 133.35 1.58 3.28 0.45 17.11 92.51 19.52 9.74

Urbanization I 172.23 2.03 2.18 0.45 22.10 108.76 24.79 21.19

Urbanization II 172.23 2.03 2.94 0.45 22.11 109.78 24.24 21.48

Alien forest to native 172.23 2.03 2.20 0.45 22.10 106.55 24.84 23.33

Climate change I 198.67 2.46 1.39 0.45 24.67 119.76 28.32 30.17

Climate change II 183.32 2.16 1.99 0.45 23.59 112.84 26.33 25.08

Climate change III 167.93 1.85 2.72 0.45 22.51 104.75 24.24 21.40

Waimanu 80102 Baseline 442.91 39.45 0.01 0.12 148.16 117.28 63.81 153.09 147

Drought 342.96 30.55 0.03 0.12 114.71 108.00 56.31 94.17

Urbanization I 442.91 39.45 0.01 0.12 148.16 117.29 63.79 153.11

Urbanization II 442.91 39.45 0.01 0.12 148.16 117.30 63.77 153.13

Alien forest to native 442.91 39.45 0.01 0.12 148.16 113.18 63.81 157.19

Climate change I 513.50 47.83 0.00 0.12 171.57 122.98 63.95 202.81

Climate change II 471.23 41.81 0.01 0.12 157.66 119.37 65.32 170.67

Climate change III 428.77 35.76 0.02 0.12 143.69 114.59 64.12 142.12

Mähukona 80103 Baseline 194.95 10.20 5.27 0.46 45.59 129.22 13.08 23.22 38

Drought 130.96 6.85 6.04 0.46 30.61 99.35 10.91 5.59

Urbanization I 194.95 10.20 7.16 0.46 45.59 130.83 13.07 23.50

Urbanization II 194.95 10.18 13.43 0.46 45.59 136.88 12.97 23.78

Alien forest to native 194.95 10.20 5.27 0.46 45.59 128.46 13.08 23.97

Climate change I 194.95 10.20 5.27 0.46 45.59 129.22 13.08 23.22

Climate change II 194.95 10.20 5.27 0.46 45.59 129.22 13.08 23.22

Climate change III 194.95 10.20 5.27 0.46 45.59 129.22 13.08 23.22

Honokaÿa 80201 Baseline 294.99 1.58 0.35 0.56 39.97 168.42 25.53 63.33 71

Drought 216.40 1.16 0.58 0.56 29.29 145.41 18.81 25.50

Urbanization I 294.99 1.58 0.40 0.56 39.97 168.29 25.38 63.65

Urbanization II 294.99 1.58 0.61 0.56 39.97 167.99 24.25 65.30

Alien forest to native 294.99 1.58 0.35 0.56 39.97 161.02 25.53 70.73

Climate change I 358.20 1.93 0.20 0.56 48.46 183.89 30.89 97.39

Climate change II 301.31 1.61 0.34 0.56 40.98 169.71 26.05 66.84

Climate change III 244.78 1.29 0.57 0.56 33.52 151.72 21.22 40.55

Paÿauilo 80202 Baseline 534.97 21.40 0.66 0.24 97.34 270.29 68.34 120.86 136

Drought 392.53 15.70 1.02 0.24 71.43 234.71 53.29 49.65

Urbanization I 534.97 21.40 0.68 0.24 97.34 270.20 68.23 121.08

Urbanization II 534.97 21.40 0.79 0.24 97.34 270.04 67.74 121.85

Alien forest to native 534.97 21.40 0.66 0.24 97.34 258.06 68.34 133.11

Climate change I 649.31 26.05 0.43 0.24 117.96 294.65 79.35 183.62

Climate change II 546.70 21.76 0.65 0.24 99.72 272.09 69.48 127.62

Climate change III 444.17 17.50 1.00 0.24 81.46 243.88 58.56 78.63

30 A Water-Budget Model and Assessment of Groundwater Recharge for the Island of Hawai‘i
Model Randomness 31

Table 7. Mean annual water-budget estimates for baseline and possible future conditions for each aquifer system on the 

Island of Hawaiÿi.—Continued

Aquifer 

system

Aquifer 

code

Hypothetical

condition

Water-budget estimate (Mgal/d) WRPP

recharge 

Rain Fog (Mgal/d) Irr DR Runoff ET CEvap Rech

Hakalau 80203 Baseline 1,182.62 125.98 0.33 0.26 522.49 227.35 194.06 364.81 341

Drought 867.66 92.43 0.35 0.26 383.32 214.51 172.53 188.65

Urbanization I 1,182.62 125.98 0.33 0.26 522.49 227.37 193.73 365.12

Urbanization II 1,182.62 125.98 0.32 0.26 522.49 227.40 193.67 365.15

Alien forest to native 1,182.62 125.98 0.33 0.26 522.49 223.28 194.06 368.88

Climate change I 1,436.51 153.39 0.15 0.26 633.94 236.00 200.67 519.22

Climate change II 1,206.97 128.00 0.32 0.26 534.32 228.07 195.39 377.30

Climate change III 976.44 102.47 0.79 0.26 434.34 216.73 179.46 248.98

Onomea 80204 Baseline 1,184.30 125.58 0.09 0.55 481.42 234.94 176.48 417.08 335

Drought 868.94 92.14 0.06 0.55 353.23 224.37 158.78 222.76

Urbanization I 1,184.30 125.58 0.09 0.55 481.42 235.01 176.24 417.25

Urbanization II 1,184.30 125.58 0.08 0.55 481.42 235.31 175.65 417.55

Alien forest to native 1,184.30 125.58 0.09 0.55 481.42 232.44 176.48 419.60

Climate change I 1,439.06 152.95 0.04 0.55 584.28 242.12 180.22 585.39

Climate change II 1,208.06 127.55 0.09 0.55 492.08 235.52 177.61 430.44

Climate change III 976.23 102.00 0.23 0.55 399.58 225.83 164.53 288.48

Waimea 80301 Baseline 286.02 13.52 6.59 0.52 3.31 255.83 12.50 35.62 54

Drought 192.01 9.07 7.29 0.52 2.20 191.72 8.89 10.18

Urbanization I 286.02 13.52 11.88 0.52 3.31 260.77 12.49 35.96

Urbanization II 286.02 13.52 20.42 0.52 3.31 268.83 12.48 36.45

Alien forest to native 286.02 13.52 6.59 0.52 3.31 255.82 12.50 35.63

Climate change I 286.01 13.52 6.59 0.52 3.31 255.83 12.49 35.62

Climate change II 286.01 13.52 6.59 0.52 3.31 255.83 12.49 35.62

Climate change III 286.01 13.52 6.59 0.52 3.31 255.83 12.49 35.62

Hilo 80401 Baseline 1,070.00 122.17 0.01 2.22 24.45 195.44 159.25 815.16 793

Drought 859.26 98.14 0.04 2.22 19.59 189.18 145.31 605.09

Urbanization I 1,070.00 122.17 0.00 2.22 24.43 194.10 155.93 819.85

Urbanization II 1,070.00 122.17 0.00 2.22 24.39 193.54 153.72 822.66

Alien forest to native 1,070.00 122.17 0.01 2.22 24.45 186.46 159.25 824.14

Climate change I 1,197.72 132.08 0.01 2.22 27.95 195.82 166.94 941.24

Climate change II 1,116.05 126.00 0.01 2.22 25.78 195.09 162.72 860.59

Climate change III 1,034.19 119.92 0.01 2.22 23.60 194.18 156.65 781.82

Keaÿau 80402 Baseline 1,331.14 119.46 0.04 1.07 30.30 291.62 214.83 914.71 898

Drought 1,069.19 95.97 0.20 1.07 24.34 284.66 191.00 665.27

Urbanization I 1,331.14 119.46 0.04 1.07 30.30 291.06 213.50 916.60

Urbanization II 1,331.14 119.46 0.04 1.07 30.30 292.05 204.63 924.50

Alien forest to native 1,331.14 119.46 0.04 1.07 30.30 259.44 214.83 946.92

Climate change I 1,499.69 129.55 0.04 1.07 34.69 292.16 228.13 1,075.11

Climate change II 1,394.11 123.34 0.04 1.07 31.98 291.49 220.67 974.16

Climate change III 1,288.04 117.12 0.04 1.07 29.25 290.61 211.06 875.10

Ölaÿa 80501 Baseline 629.94 91.15 0.12 0.17 13.87 130.12 123.08 454.01 284

Drought 505.70 73.22 0.21 0.17 11.14 127.74 111.50 327.43

Urbanization I 629.94 90.96 0.12 0.17 13.87 130.25 122.83 453.93

Urbanization II 629.94 90.86 0.12 0.17 13.87 130.36 122.69 453.87

Alien forest to native 629.94 91.15 0.12 0.17 13.87 119.62 123.08 464.57

Climate change I 704.44 99.19 0.12 0.17 15.88 129.52 128.17 530.06

Climate change II 655.47 94.20 0.12 0.17 14.62 129.39 125.54 480.11

Climate change III 606.46 89.23 0.12 0.17 13.35 129.24 121.36 431.73
32 A Water-Budget Model and Assessment of Groundwater Recharge for the Island of Hawai‘i

Table 7. Mean annual water-budget estimates for baseline and possible future conditions for each aquifer system on the 

Island of Hawaiÿi.—Continued

Aquifer 

system

Aquifer 

code

Hypothetical

condition

Water-budget estimate (Mgal/d) WRPP

recharge 

Rain Fog (Mgal/d) Irr DR Runoff ET CEvap Rech

Kapäpala 80502 Baseline 170.16 27.49 0.11 0.00 3.44 62.49 14.99 116.81 44

Drought 136.41 22.05 0.15 0.00 2.76 59.71 12.81 83.32

Urbanization I 170.16 27.49 0.11 0.00 3.44 62.49 14.99 116.81

Urbanization II 170.16 27.49 0.11 0.00 3.44 62.49 14.99 116.81

Alien forest to native 170.16 27.49 0.11 0.00 3.44 62.10 14.99 117.20

Climate change I 186.05 29.19 0.11 0.00 3.91 62.86 16.03 132.52

Climate change II 174.17 27.82 0.11 0.00 3.60 62.42 15.42 120.64

Climate change III 162.50 26.48 0.11 0.00 3.30 61.89 14.71 109.17

Näÿälehu 80503 Baseline 939.10 151.37 8.73 0.26 89.29 343.83 189.75 476.19 268

Drought 724.69 116.87 12.35 0.26 68.45 327.88 157.55 299.32

Urbanization I 939.10 151.37 8.87 0.26 89.29 343.87 189.63 476.40

Urbanization II 939.10 151.37 9.14 0.26 89.29 344.11 189.44 476.62

Alien forest to native 939.10 151.37 8.73 0.26 89.29 339.85 189.75 480.16

Climate change I 1,082.68 174.20 6.30 0.26 106.91 349.95 212.58 593.59

Climate change II 951.24 153.10 8.16 0.26 91.93 343.24 193.66 483.54

Climate change III 821.65 132.44 10.82 0.26 77.15 334.53 171.49 381.63

Ka Lae 80504 Baseline 277.72 18.48 0.48 0.09 28.86 133.10 28.17 106.61 71

Drought 213.84 14.18 0.73 0.09 22.13 117.83 22.65 66.50

Urbanization I 277.72 18.48 0.48 0.09 28.86 133.10 28.17 106.61

Urbanization II 277.72 18.48 0.48 0.09 28.86 133.10 28.17 106.61

Alien forest to native 277.72 18.48 0.48 0.09 28.86 132.66 28.17 107.04

Climate change I 325.16 22.25 0.32 0.09 34.61 143.14 32.65 137.38

Climate change II 283.12 19.11 0.45 0.09 29.71 134.48 28.95 109.60

Climate change III 241.75 16.06 0.62 0.09 24.90 124.19 25.00 84.42

Manukä 80601 Baseline 341.63 9.97 2.11 0.23 19.22 147.35 27.27 160.11 56b

Drought 226.26 6.60 5.12 0.23 12.73 128.41 18.81 78.37

Urbanization I 341.63 9.97 2.11 0.23 19.22 147.35 27.27 160.11

Urbanization II 341.63 9.97 2.18 0.23 19.22 147.43 27.22 160.14

Alien forest to native 341.63 9.97 2.11 0.23 19.22 147.35 27.27 160.11

Climate change I 450.44 13.14 0.86 0.23 25.13 161.24 34.69 243.63

Climate change II 379.99 11.10 1.55 0.23 21.32 152.98 29.97 188.62

Climate change III 309.40 9.07 2.74 0.23 17.49 142.53 25.04 136.40

Kaÿapuna 80602 Baseline 433.46 37.16 0.16 0.15 19.70 178.14 75.57 197.47 133b

Drought 301.73 25.30 0.45 0.15 13.19 161.55 53.49 99.35

Urbanization I 433.46 37.16 0.16 0.15 19.70 178.14 75.57 197.47

Urbanization II 433.46 37.16 0.16 0.15 19.70 178.14 75.57 197.47

Alien forest to native 433.46 37.16 0.16 0.15 19.70 176.83 75.57 198.78

Climate change I 527.08 46.78 0.05 0.15 25.35 181.47 93.36 273.84

Climate change II 460.49 40.25 0.10 0.15 21.66 177.78 81.99 219.52

Climate change III 394.68 33.79 0.23 0.15 18.01 172.37 69.73 168.71

Kealakekua 80603 Baseline 356.25 35.09 0.19 0.74 16.61 145.98 50.04 179.58 87b

Drought 246.94 24.59 0.40 0.74 11.11 134.82 35.55 91.26

Urbanization I 356.25 35.09 0.20 0.74 16.61 145.88 50.03 179.70

Urbanization II 356.25 35.09 0.20 0.74 16.61 145.95 50.01 179.66

Alien forest to native 356.25 35.09 0.19 0.74 16.61 144.89 50.04 180.66

Climate change I 436.27 42.08 0.09 0.74 21.39 149.64 61.00 247.09

Climate change II 379.94 36.94 0.15 0.74 18.27 146.86 53.68 198.90

Climate change III 324.15 31.83 0.25 0.74 15.18 142.33 45.93 153.49
Model Randomness 33

Table 7. Mean annual water-budget estimates for baseline and possible future conditions for each aquifer system on the 

Island of Hawaiÿi.—Continued

Aquifer 

system

Aquifer 

code

Hypothetical

condition

Water-budget estimate (Mgal/d) WRPP

recharge 

Rain Fog (Mgal/d) Irr DR Runoff ET CEvap Rech

ÿAnaehoÿomalu 80701 Baseline 315.68 11.64 7.00 0.11 3.41 145.34 4.07 181.69 69

Drought 222.19 7.90 7.52 0.11 2.38 126.58 2.86 106.39

Urbanization I 315.68 11.64 11.48 0.11 3.41 149.73 4.04 181.81

Urbanization II 315.68 11.64 30.74 0.11 3.41 168.63 3.95 182.25

Alien forest to native 315.68 11.64 7.00 0.11 3.41 145.34 4.07 181.69

Climate change I 308.80 11.58 7.00 0.11 3.35 144.16 4.07 176.00

Climate change II 308.80 11.58 7.00 0.11 3.35 144.16 4.07 176.00

Climate change III 308.80 11.58 7.00 0.11 3.35 144.16 4.07 176.00

Pähoa 80801 Baseline 1,552.70 26.06 0.07 2.25 36.74 368.01 265.22 910.93 994

Drought 1,248.01 20.95 0.22 2.25 29.53 355.41 217.23 668.45

Urbanization I 1,552.70 24.17 0.07 2.25 36.74 370.39 261.39 910.49

Urbanization II 1,552.70 23.92 0.07 2.25 36.74 372.33 255.64 914.06

Alien forest to native 1,552.70 26.06 0.07 2.25 36.74 353.70 265.22 925.26

Climate change I 1,772.78 28.32 0.07 2.25 42.38 371.99 299.11 1,089.78

Climate change II 1,639.31 27.03 0.07 2.25 38.95 369.91 278.69 980.95

Climate change III 1,505.21 25.73 0.07 2.25 35.49 367.31 257.71 872.59

Kalapana 80802 Baseline 880.50 9.69 0.33 0.24 21.04 288.55 93.35 487.76 359

Drought 707.65 7.78 0.61 0.24 16.90 271.67 76.06 351.48

Urbanization I 880.50 9.69 0.36 0.24 21.03 288.68 92.86 488.15

Urbanization II 880.50 9.69 0.36 0.24 21.03 288.68 92.82 488.19

Alien forest to native 880.50 9.69 0.33 0.24 21.04 286.39 93.35 489.92

Climate change I 1,014.45 10.62 0.32 0.24 24.46 293.76 106.06 601.28

Climate change II 932.41 10.07 0.32 0.24 22.35 291.01 98.35 531.27

Climate change III 851.19 9.53 0.32 0.24 20.26 287.60 90.56 462.80

Hilina 80803 Baseline 115.03 1.20 0.00 0.00 2.83 39.31 1.14 72.95 20

Drought 92.45 0.97 0.00 0.00 2.27 36.01 0.94 54.21

Urbanization I 115.03 1.20 0.00 0.00 2.83 39.31 1.14 72.95

Urbanization II 115.03 1.20 0.00 0.00 2.83 39.31 1.14 72.95

Alien forest to native 115.03 1.20 0.00 0.00 2.83 39.27 1.14 72.99

Climate change I 135.92 1.35 0.00 0.00 3.37 40.92 1.31 91.68

Climate change II 122.97 1.26 0.00 0.00 3.03 39.98 1.21 80.00

Climate change III 110.12 1.17 0.00 0.00 2.70 38.89 1.10 68.61

Keaïwa 80804 Baseline 157.36 0.74 2.11 0.00 3.85 61.99 0.75 93.61 39

Drought 126.50 0.59 2.52 0.00 3.10 57.22 0.60 68.70

Urbanization I 157.36 0.74 2.11 0.00 3.85 61.99 0.75 93.61

Urbanization II 157.36 0.74 2.11 0.00 3.85 61.99 0.75 93.61

Alien forest to native 157.36 0.74 2.11 0.00 3.85 61.96 0.75 93.65

Climate change I 184.94 0.82 1.99 0.00 4.56 64.15 0.87 118.16

Climate change II 167.97 0.77 2.05 0.00 4.13 62.91 0.79 102.96

Climate change III 151.00 0.72 2.15 0.00 3.69 61.44 0.72 88.01

Keauhou 80901 Baseline 339.01 13.78 3.50 2.17 8.02 158.64 40.13 151.62 86b

Drought 224.41 9.12 6.13 2.17 5.30 144.33 27.47 64.94

Urbanization I 339.01 13.78 3.29 2.17 8.02 158.27 39.73 152.18

Urbanization II 339.01 13.78 10.48 2.17 8.02 164.90 38.52 153.95

Alien forest to native 339.01 13.78 3.50 2.17 8.02 157.07 40.13 153.19

Climate change I 447.59 18.15 2.12 2.17 10.50 167.14 51.42 240.91

Climate change II 377.78 15.33 2.92 2.17 8.93 162.28 44.26 182.69

Climate change III 308.35 12.51 4.14 2.17 7.36 155.06 36.80 127.92
34 A Water-Budget Model and Assessment of Groundwater Recharge for the Island of Hawai‘i

Table 7. Mean annual water-budget estimates for baseline and possible future conditions for each aquifer system on the 

Island of Hawaiÿi.—Continued

Aquifer 

system

Aquifer 

code

Hypothetical

condition

Water-budget estimate (Mgal/d) WRPP

recharge 

Rain Fog (Mgal/d) Irr DR Runoff ET CEvap Rech

Kïholo 80902 Baseline 176.04 7.75 3.44 0.08 3.95 99.21 7.96 76.19 42

Drought 116.53 5.13 4.06 0.08 2.63 83.19 5.51 34.77

Urbanization I 176.04 7.75 3.65 0.08 3.95 99.41 7.96 76.19

Urbanization II 176.04 7.75 7.11 0.08 3.95 102.84 7.93 76.27

Alien forest to native 176.04 7.75 3.44 0.08 3.95 99.21 7.96 76.19

Climate change I 231.79 10.18 2.93 0.08 5.16 110.19 10.09 119.55

Climate change II 195.55 8.60 3.25 0.08 4.39 103.84 8.74 90.52

Climate change III 158.96 7.02 3.61 0.08 3.61 95.22 7.29 63.58

a

This recharge value was used in the 2008 WRPP (State of Hawaiÿi, 2008) based on Oki (2002).

b

This recharge value was used in the 2008 WRPP (State of Hawaiÿi, 2008) based on Oki (1999).

Groundwater-Recharge 

Estimates

Baseline Recharge

Estimated mean annual recharge on the Island of Hawai‘i 

is 6,594 Mgal/d for baseline conditions. Baseline conditions 

for this study were 2008 land cover and mean annual rainfall (1916–1983) based on Giambelluca and others (1986). 

Recharge is about 49 percent of rainfall and about 46 percent 

of total water inflow (sum of rainfall, fog interception, and 

irrigation). The spatial distribution of estimated mean annual 

recharge for baseline conditions is displayed on figure 13 and 

tabulated by aquifer system on table 7. 

Estimated mean annual recharge on the Island of Hawai‘i 

is highest on the windward slopes of Mauna Loa, below the 

tradewind inversion, and lowest on the leeward slopes of Kohala 

and Mauna Kea. Local recharge maxima also occur on (1) the 

higher elevations of windward Kohala, (2) windward Mauna 

Kea below the tradewind inversion, (3) windward Kïlauea, 

(4) the middle elevations of southeastern Mauna Loa, and 

(5) the lower middle elevations of leeward Mauna Loa and 

southwestern Hualälai, in the Kona area. Local recharge minima 

also occur on (1) Mauna Kea and Mauna Loa, above the 

tradewind inversion, (2) the northern tip of Kohala, (3) leeward 

Kïlauea, (4) the southern tip of Mauna Loa, and (5) the northwestern slopes of Mauna Loa and Hualälai. The aquifer systems 

receiving the most estimated recharge are, in order, Kea‘au, 

Pähoa, and Hilo. The aquifer systems receiving the least estimated recharge are, in order, Häwï, Mähukona, and Waimea.

A pronounced discontinuity in recharge distribution 

occurs along the boundary of the Onomea and Hilo aquifer 

systems. This discontinuity is due to the difference in runoff 

properties between Mauna Kea, of which the Onomea aquifer 

system is part, and Mauna Loa, of which the Hilo aquifer 

system is part. Rainfall, pan-evaporation, fog-interception, and 

land-cover characteristics are comparable in the two aquifer 

systems; however, runoff in the Onomea aquifer system is 

markedly higher. The surface of Mauna Kea, being older than 

Mauna Loa, is more eroded and less permeable.

Another noticeable feature of figure 13 is the belt of 

lower recharge running parallel to the coast about 2 to 5 miles 

inland in the Hakalau and Onomea aquifer systems, This 

feature occurs where forest exists below the lower extent of 

the fog zone, which was set at 2,500 ft for this study. Within 

the belt, relatively high rates of ET occur because of canopy 

evaporation. West of the belt, in the fog forest, estimated 

recharge is higher because of fog interception and lower ET 

rates associated with lower transpiration in fog forests. East of 

the belt, in the grassland and agricultural land covers, estimated recharge is higher because of lower ET rates associated 

with the absence of canopy evaporation. Whereas the elevation 

of the lower extent of the fog zone (2,500 ft) was somewhat 

arbitrarily set and is certainly debatable, the eastern boundary 

is indisputably the edge of the forest land, documented in the 

GAP land-cover map (U.S. Geological Survey, 2006). This 

shows that forested land does not necessarily provide more 

groundwater recharge than grassland and agricultural land. 

Figure 14 shows the estimated fraction of total water 

inflow—rainfall, fog interception, and irrigation—that 

becomes groundwater recharge. The areas with the highest 

fraction, greater than 80 percent, mainly occur in the wettest areas of the highly permeable slopes of Mauna Loa and 

Kïlauea. In these areas, runoff is very low and the moisturestorage capacity is relatively low (fig. 11). Areas with a 

low fraction, less than 20 percent, include the northern and 

southern tips of the island, leeward Kohala and Mauna Kea, 

the saddle between Kohala and Mauna Kea, coastal areas of 

northeastern Mauna Kea and Kohala, and the forested areas of 
Figure 14. Estimated fraction of total water inflow that becomes groundwater recharge in the water-budget simulation 

for mean annual recharge for baseline conditions on the Island of Hawai‘i. Boundaries of named aquifer systems (State of 

Hawai‘i, 2008) are shown in gray.

156°

155°

155°20'

155°40'

20°

19°40'

19°20'

19°

0 5 10 20 Miles

0 12.5 25 Kilometers

Hilo

Waimea

Näÿälehu

Pähoa

Keaÿau

ÿÖlaÿa

Kaÿapuna

Onomea

ÿAnaehoÿomalu

Manukä

Kïholo

Ka Lae

Kalapana

Hakalau

Paÿauilo

Kealakekua

Keauhou

Keaïwa

Honokaÿa

Mähukona

Hilina

Häwï

Waimanu

Kapäpala

EXPLANATION

Fraction of water inflow (rain, fog, 

interception, and irrigation) that 

becomes recharge, in percent

Less than 20

20–39

40–59

60–79

80 and greater

Base modified from U.S. Geological Survey 

National Hydrography Dataset, 1:24,000,

Universal Transverse Mercator projection, 

zone 5, NAD83 datum.

Groundwater-Recharge Estimates 35
36 A Water-Budget Model and Assessment of Groundwater Recharge for the Island of Hawai‘i

eastern Mauna Kea below the fog zone (2,500 ft.). These areas 

generally correspond to areas of high pan evaporation and/or 

high moisture-storage capacity. In the forested areas of eastern 

Mauna Kea below the fog zone, the low fractions are caused 

by high rates of canopy-interception loss.

Comparison to Water Resources 

Protection Plan

In 1990, CWRM published the Water Resources Protection 

Plan (WRPP). The WRPP (State of Hawai‘i, 1990) assigned 

estimates of sustainable yield to each aquifer system in the 

State. Sustainable yield refers to the forced groundwater-withdrawal rate that could be sustained indefinitely without affecting 

either the quality of the pumped water or the volume rate of 

pumping (State of Hawai‘i, 1990). The estimation of sustainable yield in the 1990 WRPP was based on a simple formula 

that required estimates of recharge, among other parameters. In 

2008, CWRM published an updated WRPP (State of Hawai‘i, 

2008), which used a revised methodology for calculating 

sustainable yield that also required recharge estimates. Most 

recharge estimates from the 1990 WRPP were carried over 

to the 2008 WRPP; however, some were revised on the basis 

of recent studies by the USGS (Oki, 1999; Oki, 2002). Values for recharge estimates are not explicitly given in the 2008 

WRPP. Table 7 compares the estimates of baseline groundwater 

recharge from this study to the estimates published in the 1990 

WRPP. Where noted, recharge values that were used in the 2008 

WRPP (Lenore Ohye, CWRM, written commun., 2009) are 

used for comparison instead of the 1990 values. 

For most of the island, recharge estimates computed using 

the methods of this study are substantially higher than those 

estimated in the 1990 WRPP and carried over to the 2008 

WRPP (table 7; figure 15). The reasons for differences in the 

recharge estimates are related to the methods used to estimate 

the individual water-budget components. A brief, generalized 

description of the methods used in the estimation of waterbudget components is given in the 1990 WRPP. From this 

description it is difficult to ascertain the exact approach used for 

each aquifer system. Therefore, discussion of the differences 

between the 1990 WRPP methods and the methods used in this 

study is limited to generalities. The key general differences are 

as follows: (1) The 1990 WRPP water budget was calculated by 

using an annual time step, whereas this study uses a daily time 

step. In general, a finer time step will generate a more realistic 

recharge estimate than a coarser time step (Oki, 2008). (2) The 

1990 WRPP water budget omitted estimates of fog interception, 

whereas this study includes them. All other factors being equal, 

the inclusion of fog interception results in a higher estimate of 

total water inflow. (3) The 1990 WRPP water budget estimated 

runoff from streamflow measurements without subtracting 

base flow, whereas this study subtracts base flow, generating 

a lower runoff estimate. (4) The 1990 WRPP water budget 

estimated annual ET as potential (maximum) ET, whereas this 

study calculates daily ET on the basis of available soil moisture, 

vegetative cover, and soil type. In general, this approach will 

generate a lower ET estimate than the 1990 WRPP. In summary, 

the methods used in this study tend to result in a higher estimate 

of water input than the 1990 WRPP, a lower estimate of runoff, 

and a lower estimate of ET. The net effect is the generally 

higher recharge estimates in this study.

Mähukona, Waimea, and Häwï aquifer systems are three 

notable exceptions in which groundwater recharge estimated in 

this study is lower than the WRPP recharge estimate (table 7; 

figure 15)—estimated recharge is 38, 34, and 29 percent lower, 

respectively. For the Mähukona aquifer system, both runoff 

and ET are much higher in this study than in the 1990 WRPP 

water budget (table 8). The runoff and ET estimates are so much 

higher, in fact, that they completely offset the much higher rainfall estimate in this study and also the inclusion of fog interception and irrigation. An unpublished consultant report by Pacific 

Hydrogeologic, LLC (2006) titled “Water budget and numerical 

analysis of Mahukona aquifer system, North and South Kohala, 

Hawai‘i,” which calculated recharge using methods similar to 

this study, gives an even lower estimated mean annual recharge 

for the Mähukona aquifer system (table 8). Estimates from this 

study for rainfall and runoff compare very well to that Pacific 

Hydrogeologic consultant report, providing some confidence 

that this study may have better estimates for these components 

than the 1990 WRPP. For the Waimea aquifer system, the ET 

estimate in this study is about 54 percent higher than that used 

in the 1990 WRPP water budget (table 8), The much higher ET 

estimate is primarily responsible for the estimate of recharge 

in this study being lower than the 1990 WRPP, even despite a 

higher total water inflow. For the Häwï aquifer system, recharge 

estimated in this study is about 29 percent lower than the 2008 

WRPP estimate, which was based on a water budget calculated 

by Oki (2002) using methods similar to the water-budget model 

in this report. A likely source of this discrepancy is that Oki 

(2002) did not directly account for canopy-interception loss in 

forested areas, whereas this study does. 

Drought Conditions

Analysis of the effect of drought conditions on the Island 

of Hawai‘i made use of the rainfall-variability zones described 

in the “Rainfall” section of this report (fig. 6). For each 

rainfall-variability zone, the time period with the lowest 5-year 

average rainfall was selected as the drought period (table 2). 

The water-budget model was run using the same input as the 

baseline simulation, except that rainfall from the historical 

drought periods was used instead of mean rainfall.

The spatial distribution of groundwater recharge for 

drought conditions is shown on figure 16. The relative distribution of recharge is similar to the baseline simulation; 

however, the overall rates of recharge are lower because of 

the lower rainfall associated with the drought condition. A 

large area of zero recharge occurs at the middle elevations 

of leeward Mauna Kea and in the saddle between Mauna 

Kea and Kohala, mostly within the Waimea aquifer system. 
Figure 15. Relative difference, by aquifer system, between the recharge calculated in this study and the recharge used in 

the Water Resource Protection Plan (State of Hawai‘i, 2008).

Hilo

Waimea

Näÿälehu

Pähoa

Keaÿau

ÿÖlaÿa

Kaÿapuna

Onomea

ÿAnaehoÿomalu

Manukä

Kïholo

Ka Lae

Kalapana

Hakalau

Paÿauilo

Kealakekua

Keauhou

Keaïwa

Honokaÿa

Mähukona

Hilina

Häwï

Waimanu

Kapäpala

− 29

+4

− 38

− 11

− 11

+7

+24

− 34

+3

+2

+60

+166

+78

+49

+183

+73

+108

+207

− 8

+36

+264

+140

+77

+84

EXPLANATION

Difference in estimated recharge 

relative to estimate from Water 

Resource Protection Plan 

(State of Hawai‘i, 2008), in percent

Less than zero

Greater than zero

and less than 100

Greater than 100

0 10 20 Miles

0 10 20 Kilometers

Base modified from U.S. Geological Survey 

National Hydrography Dataset, 1:24,000,

Universal Transverse Mercator projection, 

zone 5, NAD83 datum.

Groundwater-Recharge Estimates 37
Table 8. Comparison of the baseline water budget calculated in this study with other studies for selected aquifer 

systems on the Island of Hawai‘i.

[Mgal/d, million gallons per day; 1990 WRPP, 1990 Water Resource Protection Plan (State of Hawai‘i, 1990); Irr, irrigation; RO, runoff; ET, evapotranspiration; Rech, recharge; –, value not given in referenced report]

Aquifer 

system Study Water-budget estimate (Mgal/d)

Rain Fog Irr RO ET Rech

Mähukona 1990 WRPP 135.52 0.00 0.00 5.42 92.15 38.00

Pacific Hydrogeologic, LLC (2006, unpub.) 195.60 – – 43.81 – 22.60

Baseline, this study 194.95 10.20 5.27 45.59 142.3a 23.22

Waimea 1990 WRPP 241.68 0.00 0.00 13.43 174.55 54.00

Baseline, this study 286.02 13.52 6.59 3.31 268.33a 35.62

Häwï Oki (2002) – – – – – 29.90

Baseline, this study 172.23 2.03 2.20 22.10 133.66a 21.09

a

Includes canopy evaporation from forests (see table 7).

38 A Water-Budget Model and Assessment of Groundwater Recharge for the Island of Hawai‘i

Overall recharge in the Waimea aquifer system is substantially 

reduced, from 35.62 Mgal/d for baseline conditions to 10.18 

Mgal/d for drought conditions (table 7). This recharge estimate 

is considerably less than the sustainable yield of 24 Mgal/d 

set in the 2008 WRPP (State of Hawai‘i, 2008). Large areas 

of zero recharge also occur on the leeward slopes of Kohala 

within the Mähukona aquifer system. Overall recharge in 

the Mähukona aquifer system also is substantially reduced, 

from 23.22 Mgal/d for baseline conditions to 5.59 Mgal/d for 

drought conditions (table 7). This recharge estimate is considerably less than the sustainable yield of 17 Mgal/d set in 

the 2008 WRPP (State of Hawai‘i, 2008). Other large areas 

of zero recharge occur in the Häwï aquifer system and the Ka 

Lae aquifer systems.

Replacement of Alien Forest 

with Native Forest

In general, native forests transpire less water than alien 

and mixed forests (see “Pan Coefficients” section). To analyze 

the effect of replacing alien forest species with native forest 

species, the alien forest and mixed native/alien forest land-cover 

categories were replaced by open native forest (table 4) in the 

2008 land-cover map. Otherwise, the water-budget model was 

run under baseline conditions. Little change in groundwater 

recharge is observed for most aquifer systems (table 7). However, in every aquifer system in which alien and/or mixed forest 

were replaced, there is an increase in recharge. The three aquifer 

systems with the largest increases are Honokaÿa, Häwï, and 

Paÿauilo, with increases of 12, 11, and 10 percent, respectively.

Future Urbanization

Analysis of the effect of future urbanization on the 

Island of Hawai‘i made use of Hawai‘i County zoning maps 

(County of Hawai‘i, 2007) and the Land Use and Pattern 

Allocation Guide (LUPAG) (County of Hawai‘i, 2005). For 

the Urbanization I simulation (table 7), all parcels on the 

Hawai‘i County zoning maps designated for an urban use were 

given a low-intensity-developed land-cover code (table 4) and 

superimposed on the baseline 2008 land-cover map. For the 

Urbanization II simulation (table 7), all parcels in the LUPAG 

designated for an urban use were given a low-intensitydeveloped land-cover code (table 4) and superimposed on the 

baseline 2008 land-cover map. The water-budget model was 

then run using the same rainfall conditions as in the baseline 

simulation.

Because the areas of the urban parcels are very small 

compared to the overall areas of the aquifer systems, little 

change in recharge occurs as a result of simulated future 

urbanization on an aquifer-system basis (table 7). Although the 

water-budget model tends to enhance recharge for urban land 

covers because of associated irrigation, cesspool leakage, and 

water-main leakage, these effects simply are on a spatial scale 

too small to be fully described in this regional study. Enhancement of recharge in urban areas is consistent with the analysis 

of Shade and Nichols (1996) for southern O‘ahu. However, 

considerable uncertainty exists in the estimation of recharge 

for urban areas. In urban areas with storm-drain systems, the 

water-budget model likely overestimates recharge because the 

capture of runoff from impervious areas by storm drains is not 

included in the model.

Climate Change

Analysis of the effect of climate change on the Island 

of Hawai‘i made use of published rainfall projections. Timm 

and Diaz (2009) used statistical downscaling to estimate 

changes in seasonal rainfall across the Hawaiian Islands 

during the late 21st century. These estimates were based on 

an ensemble of climate models and emission projections 
0 10 20 30 40 50 100 200150 300

EXPLANATION

Mean annual groundwater recharge, in inches

156°

155°

155°20'

155°40'

20°

19°40'

19°20'

19°

0 10 20 Miles

0 10 20 Kilometers

Hilo

Waimea

Näÿälehu

Pähoa

Keaÿau

ÿÖlaÿa

Kaÿapuna

Onomea

ÿAnaehoÿomalu

Manukä

Kïholo

Ka Lae

Kalapana

Hakalau

Paÿauilo

Kealakekua

Keauhou

Keaïwa

Honokaÿa

Mähukona

Hilina

Häwï

Waimanu

Kapäpala

Base modified from U.S. Geological Survey 

National Hydrography Dataset, 1:24,000,

Universal Transverse Mercator projection, 

zone 5, NAD83 datum.

Groundwater-Recharge Estimates 39

Figure 16. Distribution of mean annual groundwater recharge for drought conditions on the Island of Hawaiÿi calculated 

using the water-budget model. Areas of zero recharge appear as white. Boundaries of named aquifer systems (State of 

Hawaiÿi, 2008) are shown in gray.
40 A Water-Budget Model and Assessment of Groundwater Recharge for the Island of Hawai‘i

from the Intergovernmental Panel on Climate Change 

(IPCC) Fourth Assessment Report (2007). Late-21st-century 

projections for specific rain-gage stations are published 

online (Timm and others, 2009). In general, precipitation is 

projected to increase slightly for most areas of the island. 

Projected late-21st-century rainfall changes from Timm and 

others (2009) were applied to each rainfall-variability zone in 

the water-budget model (table 9), except for zone 7, an area 

for which no climate-change projections were published.

The effect of climate change on pan evaporation was 

analyzed for each pan-evaporation zone by developing a linear 

regression of historical pan evaporation versus historical 

rainfall for stations in each zone (table 10). For this particular 

analysis, pan-evaporation and rainfall data were normalized 

by dividing the annual or monthly observed values by the 

mean values for the particular pan-evaporation or rain-gage 

station published in Ekern and Chang (1985) or Giambelluca 

and others (1986), respectively. For the linear regression, a 

basic assumption was made that annual or monthly periods of 

mean pan evaporation should correspond to annual or monthly 

Table 9. Parameters used for the simulation of late-21st-century rainfall conditions on the Island of Hawai‘i.

[See figure 6 for locations of rainfall-variability zones; column (A) is the ratio of mean seasonal rainfall from Timm and others (2009) to the mean seasonal 

rainfall derived from Giambelluca and others (1986); columns (B), (C), and (D) are estimated rainfall-change factors based on the means and lower and upper 

margins of the 95-percent statistical confidence interval for a six-model ensemble for the late 21st century from Timm and others (2009); columns (E), (F), and 

(G) are the factors used to adjust mean rainfall in each rainfall-variability zone in the water-budget model to simulate late 21st century climate; SKN, state key 

number; NWS ID, National Weather Service cooperative identification number, HVNP HQ, Hawai‘i Volcanoes National Park headquarters; –, no data given in 

Timm and others (2009)]

Rainfallvariability 

zone

Rain-gage

station and

SKN

NWS

ID

Mean

rainfall

adjustment

factor 

(A)

Mean 

change 

factor 

(B)

Lower 95% 

confidence 

change

factor 

(C)

Upper 95%

confidence 

change

factor

(D)

Overall

adjustment

factor for

mean change

(E) = (A) x (B) 

Overall

adjustment

factor for lower 

95% confidence 

change 

(F) = (A) x (C) 

Overall

adjustment 

factor for upper 

95% confidence 

change 

(G) = (A) x (D) 

Wet Season (November to April)

1 Häwï 168 511339 1.070 – – – 1.070 1.070 1.070

2 Pa‘auilo 221 517312 0.996 1.033 0.852 1.214 1.029 0.849 1.209

3 HVNP HQ 54 511303 1.056 1.028 0.890 1.166 1.086 0.940 1.232

4 Nä‘älehu 14 516588 0.998 1.027 0.860 1.195 1.025 0.858 1.193

5 Külani Mauka 76 515018 0.975 – – – 0.975 0.975 0.975

6 Hölualoa 70 511557 1.089 1.012 0.799 1.226 1.102 0.870 1.335

7 No estimates for this zone – – – – 1.000 1.000 1.000

Dry Season (May to October)

1 Häwï 168 511339 1.014 1.040 0.818 1.261 1.054 0.829 1.279

2 Pa‘auilo 221 517312 0.941 1.070 0.839 1.300 1.007 0.790 1.224

3 HVNP HQ 54 511303 1.011 – – – 1.011 1.011 1.011

4 Kapäpala Ranch 36 513300 1.009 1.039 0.867 1.212 1.048 0.875 1.223

5 Külani Mauka 76 515018 0.847 – – – 0.847 0.847 0.847

6 Hölualoa 70 511557 1.097 1.044 0.843 1.244 1.145 0.924 1.364

7 No estimates for this zone – – – – 1.000 1.000 1.000

periods of mean rainfall. Hence, each regression line was 

forced through the point (1,1) on the plot of normalized pan 

evaporation versus normalized rainfall. The equation for each 

regression line is given by

PAN/(PAN)mean – 1 = a(P/Pmean – 1) (15)

where

PAN = pan evaporation [L], 

(PAN)mean = mean pan evaporation [L],

a = slope of the regression line [dimensionless],

P = rainfall [L], and

Pmean = mean rainfall [L].

Solving equation 15 for pan evaporation (PAN) yields:

 PAN = (a(P/Pmean – 1) + 1)(PAN)mean (16)

Late-21st-century mean pan evaporation in each panevaporation zone was estimated by using equation 16 and the 

following variable definitions:
Table 10. Linear-regression statistics for normalized pan evaporation versus normalized rainfall used for the climatechange analysis for the Island of Hawai‘i. 

[SCAN, Soil Climate Analysis Network; sta., station]

Panevaporation 

zone

Pan-evaporation

station or reference

Rain-gage station

or reference

Annual or 

monthly 

data

Period used 

in 

calculation

Slope of 

linear regression line, a a

Coefficient of 

determination of 

linear 

regression

1 Kainaliu SCANb 511665 Monthly 1/2006–10/2007 − 0.0326 0.0265

2 95.8 519142 Monthly 12/1975–7/1976 − 0.1140 0.5715

3 168 511339 Annual 1964–1974 − 0.0402 0.0047

4 215.3 514928 Annual 1965–1972 − 0.0686 0.0465

5 221.3 517312 Annual 1964–1981 − 0.1840 0.2143

6 Juvik and Nullet (1994),

sta. 1,130 m

Juvik and Nullet (1994),

sta. 1,130 m

Monthly 9/1991–8/1993 − 0.0646 0.0338

7 87 511492 Annual 1956–1968 − 0.1290 0.3199

8 21 517421 Annual 1931–1944 − 0.1210 0.5094

9 Minyard and others (1994),

sta. 3,000 m

Minyard and others (1994),

sta. 3,000 m

Monthly 4/1990–5/1992 − 0.0760 0.2416

a

Regression lines were forced through the point (1,1) such that periods with mean rainfall would coincide with mean pan evaporation. Slope is dimensionless.

b

Solar-radiation data from the Kainaliu SCAN station were used to develop a relation with pan evaporation based on pan-evaporation maps from Ekern 

and Chang (1985).

Groundwater-Recharge Estimates 41

PAN = late-21st-century mean pan evaporation [L], 

(PAN)mean = mean pan evaporation based on Ekern and 

Chang (1985) [L],

a = slope of the regression line for the panevaporation zone (table 10) [dimensionless],

P = late-21st-century mean rainfall based on Timm 

and others (2009) [L], and 

Pmean = mean rainfall based on Giambelluca and others 

(1986) [L].

As shown in table 10, the slope of the linear regression 

is negative in each zone, supporting a basic assumption that 

rainfall and pan evaporation are inversely related. However, 

the coefficients of determination for the linear regressions 

generally are low, implying that relations between pan evaporation and rainfall are poor. These relations generally are poor 

regardless of whether monthly or annual rates are used. Given 

the lack of other reliable information for projecting future pan 

evaporation, it was decided to use the pan evaporation/rainfall 

relations in table 10, despite the low coefficients of determination. Using these equations creates additional uncertainty in 

projected recharge, but the inverse relation between rainfall 

and pan evaporation is preserved.

For the climate-change simulations (table 7, fig. 17), the 

same land cover was used as in the Urbanization II scenario 

to account for the increased urbanization that will likely 

have occurred by the end of the 21st century. All parcels in 

the LUPAG designated for an urban use were given a lowintensity-developed land-cover code (table 4) and superimposed on the baseline 2008 land-cover map. The water-budget 

model was then run using projected late-21st-century rainfall 

and pan-evaporation conditions based on the upper margin of 

the 95-percent confidence interval (climate change I), mean 

(climate change II), and lower margin of the 95-percent confidence interval (climate change III) of the six-model ensemble 

from Timm and others (2009).

Except for ÿAnaehoÿomalu, recharge estimates from the 

climate-change-II simulation (mean scenario) are the same as 

or higher than the baseline estimates for each aquifer system 

(table 7), with the average difference being about 8 percent. 

Recharge estimates for the climate-change-III simulation 

(lower 95-percent scenario) are lower than the baseline estimates for all but the Häwï aquifer system, which is only 1.5 

percent higher. In all aquifer systems, the recharge estimates 

for the drought scenario are substantially lower than the 

estimates for the climate-change-III scenario, with the average 

difference being about 13 percent.

Kona-Area Submodel

Historical 

1984–2008

The water budget for the Kona area during the time 

period 1984–2008 was estimated using 5 scenarios, each 5 

years in duration: 1984–88, 1989–93, 1994–98, 1999–2003, 

and 2004–8. The highest mean recharge, 538 Mgal/d, occurred 

during the 2004–8 period, whereas the lowest mean recharge, 

270 Mgal/d, occurred during the 1999–2003 period (fig. 

18; table 11). These extremes coincided with the periods 
Hilo

Waimea

Näÿälehu

Pähoa

Keaÿau

ÿÖlaÿa

Kaÿapuna

Onomea

ÿAnaehoÿomalu

Manukä

Kïholo

Ka Lae

Kalapana

Hakalau

Paÿauilo

Kealakekua

Keauhou

Keaïwa

Honokaÿa

Mähukona

Hilina

Häwï

Waimanu

Kapäpala

0 10 20 5 Miles

0 12.5 Kilometers 25

EXPLANATION

Mean annual groundwater

recharge, in inches

0

200

150

50

100

40

30

20

10

300

MEAN

(II)

LOWER 95%

CONFIDENCE

(III)

UPPER 95%

CONFIDENCE

(I)

Base modified from U.S. Geological Survey 

National Hydrography Dataset, 1:24,000,

Universal Transverse Mercator projection, 

zone 5, NAD83 datum.

42 A Water-Budget Model and Assessment of Groundwater Recharge for the Island of Hawai‘i

Figure 17. Three possible distributions of mean annual groundwater recharge during the late 21st century based on the 

mean (II) and the upper (I) and lower (III) margins of the 95-percent confidence interval of the projected rainfall changes 

from the six-model ensemble in Timm and others (2009). Areas of zero recharge appear as white. Boundaries of named 

aquifer systems (State of Hawai‘i, 2008) are shown in gray. 
0

100

200

300

400

500

600

1984–88 1989–93 1994–98 1999–2003 2004–8

Recharge, in million gallons per day

Figure 18. Estimated groundwater recharge during five 

historical time periods for the Kona area of the Island of Hawai‘i.

Table 11. Mean annual water-budget estimates for selected historical and hypothetical land-cover and rainfall conditions 

in the Kona area of the Island of Hawaiÿi.

[Mgal/d, million gallons per day; Irr, irrigation; DR direct recharge; RO, runoff; ET, evapotranspiration exclusive of canopy evaporation; CEvap, canopy evaporation from forested areas, Rech, recharge; LUPAG, Land Use Pattern Allocation Guide (County of Hawaiÿi, 2005)]

Scenario

Water-budget estimate (Mgal/d)

Explanation

Rain Fog Irr DR RO ET CEvap Rech

Historical

1984–88 1,025 72 5 5 36 509 132 429 1988 land cover and 1984–88 rainfall 

1989–93 1,078 76 6 5 37 498 134 497 1993 land cover and 1989–93 rainfall

1994–98 938 65 7 5 33 467 120 397 1998 land cover and 1994–98 rainfall

1999–2003 755 53 9 5 26 427 99 270 2003 land cover and 1999–2003 rainfall

2004–8 1,152 81 10 5 41 521 147 538 2008 land cover and 2004–8 rainfall

Hypothetical 

Baseline 1,004 71 11 5 35 490 128 437 2008 land cover and 1984–2008 rainfall

Drought 733 52 14 5 26 422 98 260 2008 land cover and 1998–2002 rainfall

Urbanization I 1,004 71 11 5 35 490 128 437

Land cover based on full development of parcels 

zoned for urban use by Hawaiÿi County (2007) 

with 1984–2008 rainfall

Urbanization II 1,004 71 27 5 35 505 127 439 Land cover based on full development of urban 

parcels in LUPAG with 1984–2008 rainfall

Groundwater-Recharge Estimates 43

of highest and lowest mean rainfall, 1,152 Mgal/d and 755 

Mgal/d, respectively. 

On a monthly basis, average recharge was highest in 

January, 604 Mgal/d, and lowest in August, 287 Mgal/d (table 

12). Interestingly, these extremes do not coincide with the 

months of highest and lowest rainfall or total water inflow—

the sum of rainfall, fog interception, and irrigation. The 

extremes do, however, relate inversely to the general seasonal 

trend in ET, with ET being lower in the winter and higher in 

the summer. Despite this particular inverse relation, no overall 

seasonal pattern in recharge is discernible.

The spatial distributions of mean annual recharge in 

the Kona area for the time periods spanning 1984–2008 (fig. 

19) indicate that the highest recharge occurs in a belt about 4 

miles wide running parallel to the coast about 2 miles inland. 

The relative spatial distribution of recharge remains fairly 

consistent throughout the five time periods, with the magnitude of recharge changing depending on the magnitude of 

rainfall during the period (table 11).

Hypothetical Scenarios

Baseline

Baseline groundwater recharge for the Kona-area submodel was calculated using 2008 land cover, which was modified from U.S. Geological Survey (2006) and rainfall from the 

period 1984–2008. The baseline scenario was designed to simulate mean conditions over the 1984-2008 time period and be 

used as a basis of comparison for other hypothetical scenarios.

Drought Conditions

Analysis of the effect of drought conditions in the Kona 

area made use of the rainfall-variability gages described in the 

“Rainfall” section of this report (fig. 6). The average ratio of 

observed to mean annual rainfall for the eight rainfall-variability gages was computed for each year during the period 1984–

2008 (fig. 20), and the time period with the lowest 5-year average rainfall, 1998–2002, was selected as the drought period. 

To estimate recharge during drought conditions in the Kona 
Figure 19. Distribution of estimated mean annual groundwater recharge during five time periods between 1984 and 2008

calculated using the water-budget model for the Kona area of the Island of Hawaiÿi. Areas of zero recharge appear as white.

155 ̊40’

155 ̊50’

156 ̊

19 ̊40’

19 ̊50’

19 ̊30’

19 ̊20’

EXPLANATION

Mean annual groundwater 

recharge, in inches

0

150

50

100

40

30

20

10

0 10 Miles

0 10 Kilometers

1984–88 1989–93 1994–98

1999–2003 2004–08

Base modified from U.S. Geological 

Survey National Hydrography Dataset, 

1:24,000, Universal Transverse Mercator 

projection, zone 5, NAD83 datum.

44 A Water-Budget Model and Assessment of Groundwater Recharge for the Island of Hawai‘i
Groundwater-Recharge Estimates 45

Table 12. Mean monthly water budgets during five time periods for the Kona area of the Island of Hawaiÿi.

[Mgal/d, million gallons per day; evapotranspiration is inclusive of canopy evaporation in forests; positive values for change in moisture storage indicate an 

increase in moisture and negative values indicate a decrease in moisture; direct recharge occurs at a uniform monthly rate of 5 Mgal/d during all periods]

Waterbudget 

component

Period

Water-budget estimate (Mgal/d)

Jan Feb Mar Apr May June July Aug Sept Oct Nov Dec

Rain 1984–88 766 818 761 1,480 977 1,152 958 793 1,499 920 1,142 1,048

1989–93 1,518 1,249 977 1,164 783 813 1,236 995 1,040 1,352 1,179 638

1994–98 1,269 716 1,032 837 591 1,414 922 957 1,376 836 838 473

1999–2003 649 537 415 644 811 947 700 755 1,035 841 1,183 552

2004–8 1,231 1,323 1,282 1,317 1,324 1,215 1,125 1,017 1,132 867 986 1,027

average 1,087 928 893 1,088 897 1,108 988 904 1,217 963 1,066 748

Fog 1984–88 55 60 53 109 63 78 62 60 110 67 78 69

interception 1989–93 110 85 68 86 50 59 83 76 75 91 83 42

1994–98 80 50 72 58 37 94 63 74 104 61 59 30

1999–2003 49 39 31 46 53 62 45 59 82 59 79 37

2004–8 93 94 89 101 82 79 76 74 90 65 63 70

average 78 66 63 80 57 74 66 69 92 69 72 50

Irrigation 1984–88 8 9 6 3 5 3 5 6 3 6 3 5

1989–93 4 7 6 8 6 6 5 5 5 3 5 7

1994–98 8 9 5 8 8 2 7 5 4 7 6 10

1999–2003 10 12 12 12 7 6 11 9 9 8 4 10

2004–8 9 9 9 11 8 6 10 11 14 13 9 10

average 8 9 7 9 7 5 8 7 7 8 5 8

Runoff 1984–88 19 22 26 68 44 39 38 32 55 31 39 23

1989–93 36 28 35 57 32 29 48 41 37 48 39 14

1994–98 27 16 35 40 26 48 37 40 52 29 28 11

1999–2003 17 13 16 30 32 31 27 32 40 29 39 11

2004–8 33 32 42 67 56 41 47 41 45 30 34 24

average 27 22 31 53 38 38 39 37 46 33 36 17

Evapo- 1984–88 493 518 537 792 689 688 696 625 809 656 647 536

transpiration 1989–93 664 586 582 678 579 580 744 683 691 737 608 438

1994–98 529 481 584 594 502 741 674 665 773 601 545 350

1999–2003 451 420 365 510 542 602 554 579 676 591 618 408

2004–8 611 662 649 748 753 728 767 701 696 623 575 510

average 550 533 544 664 613 668 687 650 729 642 599 448

Recharge 1984–88 357 332 250 684 335 478 318 212 720 358 530 587

1989–93 924 732 438 532 239 274 516 337 401 664 650 276

1994–98 799 291 461 280 128 645 317 319 647 323 353 205

1999–2003 255 168 91 150 285 343 200 199 395 323 601 231

2004–8 685 703 684 630 590 515 416 369 506 325 455 593

average 604 445 385 455 315 451 353 287 534 399 518 379

Change in 1984–88 − 34 19 11 53 − 19 32 − 23 − 5 33 − 47 13 − 20

moisture 1989–93 14 0 1 − 4 − 6 0 22 21 − 5 3 − 25 − 36

storage 1994–98 6 − 9 34 − 5 − 14 82 − 32 17 17 − 43 − 18 − 48

1999–2003 − 9 − 8 − 10 17 18 45 − 20 18 21 − 29 12 − 47

2004–8 9 33 9 − 10 20 21 − 15 − 4 − 6 − 27 − 1 − 15

average − 3 7 9 10 0 36 − 13 9 12 − 29 − 4 − 33
Ratio of observed annual rainfall to mean annual rainfall

5-year moving average of rainfall

Rainfall

Recharge

EXPLANATION

Note: Darker bars represent the period with the lowest 5-year 

average rainfall, used to simulate drought. Mean rainfall is from 

Giambelluca and others (1986) for the period 1916–83.

Recharge, in million gallons per day

1,000

800

600

400

200

0

1.2

1.4

1.0

0.8

0.6

0.4

0.2

0.0

1984 1986 1988 1990 1992 1994 1996

Year

1998 2000 2002 2004 2006 2008

46 A Water-Budget Model and Assessment of Groundwater Recharge for the Island of Hawai‘i

area, the water-budget model was run using 2008 land cover 

and rainfall from the period 1998–2002. Mean groundwater 

recharge for drought conditions was estimated to be 41 percent 

lower than baseline recharge (table 11).

Future Urbanization

Analysis of the effect of future urbanization in the Kona 

area made use of Hawai‘i County zoning maps (County of 

Hawai‘i, 2007) and the LUPAG (County of Hawai‘i, 2005). 

For the Urbanization I simulation (table 11), all parcels on 

the Hawai‘i County zoning maps designated for an urban use 

were given a low-intensity-developed land-cover code (table 

4) and superimposed on the baseline 2008 land-cover map. 

For the Urbanization II simulation (table 11), all parcels in the 

LUPAG designated for an urban use were given a low-intensity-developed land-cover code (table 4) and superimposed on 

the baseline 2008 land-cover map. The water-budget model 

was then run using the same rainfall conditions as in the Konaarea baseline simulation.

Because the areas of the urban parcels are very small compared to the overall areas of the aquifer systems, little change in 

recharge occurs as a result of future urbanization on a regional 

basis (table 11). Although the water-budget model tends to 

enhance recharge for urban land covers because of associated irrigation, cesspool leakage, and water-main leakage, 

these effects are on a spatial scale simply too small to be fully 

described in this regional study. In urban areas with storm-drain 

systems, the water-budget model for this study likely overestimates recharge because the capture of runoff from impervious 

areas by storm drains is not included in the model.

Climate Change

Because of an insufficient number of rainfall-change projections in Timm and others (2009) for gages in the Kona area, 

the Kona-area submodel was not used for climate-change estimation. Climate-change projections for the aquifer systems in 

the Kona area—Kiholo, Keauhou, Kealakekua, and Ka‘apuna—

were obtained using the islandwide model (table 7).

Sensitivity Analysis

Uncertainty exists in many of the water-budget inputs 

used in this study. The values used in the water-budget model 

were deemed to be those most reasonable. To analyze the 

Figure 20. Average ratio of observed to mean annual rainfall for the eight gages used to simulate historical 

rainfall for the Kona-area water-budget submodel. See figure 6 for rain-gage locations.
Table 13. Results of sensitivity testing for selected water− budget parameters performed for Onomea, Keauhou, and 

Waimea aquifer systems on the Island of Hawai‘i.

[See figure 2 for the locations of the Onomea, Keauhou, and Waimea aquifer systems]

Parameter Adjusted parameter 

value

Percent difference in recharge relative to baseline estimate

Onomea aquifer 

system

Keauhou aquifer 

system

Waimea aquifer 

system

Available water capacity Low reported valuea 1.0 5.4 12.2

High reported valuea − 0.5 − 2.2 − 8.5

Fog-catch efficiency 150% of baseline 16.8 1.9 6.5

50% of baseline − 16.8 − 1.9 − 6.1

Ratio of fog interception to rainfall 150% of baseline 16.6 2.0 6.4

50% of baseline − 16.9 − 1.9 − 6.1

Root depth 150% of baseline − 1.3 − 2.8 − 19.3

50% of baseline 2.4 4.6 47.6

Ratio of runoff to rainfall 150% of baseline − 39.4 − 2.3 − 1.8

50% of baseline 55.9 2.2 1.7

Pan coefficient 120% of baseline − 19.2 − 18.4 − 15.3

80% of baseline 1.4 4.5 15.4

Net-precipitation rate in forests

(as percentage of rainfall)

20 percentage units higher 

than baseline 33.1 14.5 6.0

20 percentage units lower 

than baseline − 25.3 − 13.1 − 4.4

a

High and low values reported in U.S. Department of Agriculture (2008).

Groundwater-Recharge Estimates 47

effect that uncertainty in water-budget inputs has on estimated 

recharge, the water budget was rerun while changing one input 

value at a time within a reasonable range. A range of recharges 

for each test was computed by holding all other inputs at their 

original values and varying the test input. For three aquifer 

systems representative of three important climate regions on 

the Island of Hawai‘i, the resulting recharge estimates were 

compared to baseline recharge (table 13). Onomea aquifer 

system is representative of windward areas of the island with 

forested land cover and high, primarily orographic rainfall; 

Keauhou aquifer system is representative of the Kona area, 

with mixed forest and grassland land cover and moderate, 

primarily convective rainfall; and Waimea aquifer system is 

representative of leeward areas of the island with pasture and 

grassland and low rainfall. The parameters tested were (1) 

available water capacity, (2) fog-catch efficiency, (3) ratio of 

fog interception to rainfall, (4) root depth, (5) ratio of runoff to 

rainfall, (6) pan coefficient, and (7) the net-precipitation rate 

in forests. For most parameters, baseline values were increased 

by 50 percent and decreased by 50 percent. For available water 

capacity, the range chosen for testing was between the high 

and low values published in U.S. Department of Agriculture 

(2008). For pan coefficients, baseline values were increased 

by 20 percent and decreased by 20 percent. For the net-precipitation rate in forests, which is measured as a percentage 

of rainfall, baseline values were increased by 20 percent and 

decreased by 20 percent.

For the Onomea aquifer system, the parameter with 

the largest effect on recharge is the ratio of runoff to rainfall 

(table 13). This result is not surprising, given the very large 

amount of runoff that occurs in this area. Because of the large 

amount of forested area, it is also not surprising that changes 

to the net-precipitation rate had a large effect. Changes to the 

fog-efficiency ratio and ratio of fog interception to rainfall had 

substantial effects, owing to the large amount of forested area 

within the fog zone and the high mean annual rainfall. Increasing the pan coefficient also had a considerable effect. Changes 

to root depth and available water capacity had smaller 

effects—less than 10 percent—on groundwater recharge.

For the Keauhou aquifer system, the parameters with the 

largest effect on recharge are the pan coefficient and the netprecipitation rate (table 13). This result indicates the important 

role of ET and forests in the overall Kona-area water budget. 

The other parameters have small effects—less than 10 percent—on groundwater recharge.

For the Waimea aquifer system, the parameter with the 

largest effect on recharge is root depth (table 13). This result 

indicates the importance of moisture-storage capacity, which 

is directly related to root depth, and shows that it is extremely 

important in leeward areas of the island where rainfall 
48 A Water-Budget Model and Assessment of Groundwater Recharge for the Island of Hawai‘i

commonly is light and sporadic and grass roots are relatively deep. The pan coefficient also has a substantial effect, 

indicating the importance of ET for this region of the island. 

Changes to available water capacity have the largest effects 

in the Waimea aquifer system, compared to the other two 

systems tested. This is further indication of the importance of 

moisture-storage capacity to the water budget of the area. The 

other parameters have small effects—less than 10 percent—

on groundwater recharge.

Suggestions for Future Study 

and Additional Data Collection

The water-budget model described in this report is limited by the quality, density, and availability of data needed to 

develop model input—land cover, rainfall, fog interception, 

irrigation, runoff, soil properties, and ET. Continued research 

into all of these subjects would improve overall confidence 

in recharge estimates. Updated rainfall distribution maps, 

using more recent data, would certainly increase the accuracy of recharge calculations. A better understanding of 

fog interception and continued research into the calibration 

of mechanical fog catch to different forest types would be 

useful. More continuous-record stream-gaging stations from 

which to gather data relevant to developing runoff estimates 

and relations to rainfall and other parameters would increase 

the accuracy of recharge estimates, especially in wet areas, 

as shown in the section on “Sensitivity Analysis.” Updated 

soil maps that include better information for nonagricultural 

areas would be useful. More research into the ET properties of different forest types would also be useful and could 

produce better pan-coefficient values and net-precipitation 

rates, which are very important in the Kona Area, as shown 

in the “Sensitivity Analysis” section. The ET properties of 

sparsely vegetated land, which on the Island of Hawai‘i 

generally means bare lava flow, remain uncertain. This landcover category makes up a large fraction of the island (fig. 

4). Improved information on root depths would be useful, 

especially in the leeward Kohala and leeward Mauna Kea 

areas, where the sensitivity analysis shows the importance of 

this parameter. Investigation into recharge through streambeds would also be very useful, especially in the Mähukona 

and Waimea aquifer systems. Reaches of several streams in 

this area flow perennially at high elevations. Flows in these 

streams diminish as they traverse the Mähukona and Waimea 

aquifer systems, becoming intermittent before they reach 

the coast. Most of this loss in flow is due to seepage into 

the streambed. A study of urban runoff is needed, because 

that would help partition the volume of rain that falls on 

impervious surfaces into flows to dry wells, storm drains, 

and pervious surfaces. This would increase the confidence of 

urban-recharge estimates.

The estimation of recharge using methods other than a 

water budget could provide an important comparison. The 

nature of groundwater recharge in Hawai‘i is such that direct 

regional measurements are not possible at this time. As such, 

the water-budget model cannot be calibrated in a traditional 

manner. One way to gain confidence in recharge estimates 

from this model would be to compare them to recharge estimates from another method. Unfortunately, most rechargeestimation methods used on continents are ineffective for 

the Hawaiian Islands. However, studies using chloride mass 

balance, stable isotopes of water, and geophysical methods 

may produce some data that are usable for comparison to 

model results.

Summary and Conclusions

Concern surrounding increasing demand for groundwater on the Island of Hawai‘i, caused by a growing population and an increasing reliance on groundwater as a source 

for municipal and private water systems, has prompted 

a study of groundwater recharge on the island using the 

most current data and accepted methods. This report documents the development of a daily water-budget model for 

computing groundwater recharge on the Island of Hawai‘i 

and the application of the model to estimate mean recharge 

for various land-cover and rainfall conditions. A submodel 

for the Kona area was developed and applied to estimate 

historical groundwater recharge in the Kona area during the 

period 1984–2008. Recharge estimates from this study were 

compared to recharge estimates in the 2008 Water Resource 

Protection Plan (WRPP) (State of Hawai‘i, 2008), and the 

sensitivity of recharge estimates to selected water-budget 

parameters was evaluated.

Estimated mean annual recharge for baseline conditions 

on the Island of Hawai‘i is 6,594 Mgal/d, which is about 49 

percent of rainfall. Baseline conditions for this study were 

2008 land cover and mean annual rainfall from the period 

1916–83. Recharge is highest on the windward slopes of 

Mauna Loa below the tradewind inversion and lowest on the 

leeward slopes of Kohala and Mauna Kea. Local recharge 

maxima also occur on (1) the higher elevations of windward 

Kohala, (2) windward Mauna Kea below the tradewind 

inversion, (3) windward Kïlauea, (4) the middle elevations of 

southeastern Mauna Loa, and (5) the lower middle elevations 

of leeward Mauna Loa and southwestern Hualälai, in the 

Kona area. Local recharge minima also occur on (1) Mauna 

Kea and Mauna Loa, above the tradewind inversion, (2) the 

northern tip of Kohala, (3) leeward Kïlauea, (4) the southern 

tip of Mauna Loa, and (5) the northwestern slopes of Mauna 

Loa and Hualälai. 

Analysis of estimated recharge with respect to land 

cover reveals some results that may be inconsistent with 

popular notions. Because of potentially high rates of canopy 

evaporation, forested land does not necessarily provide more 

recharge than grassland or agricultural land. Urban land 

appears to enhance recharge because of irrigation, cesspool 
References Cited 49

leakage, and water-main leakage. However, the water-budget 

model likely overestimates recharge for urban areas with 

storm-drain systems, because the capture of runoff from 

impervious areas by storm drains is not included in the model.

In 18 of the 24 aquifer systems on the island, mean 

annual recharge estimated in this study for baseline conditions was higher than the recharge estimates used in the 

2008 WRPP. The higher estimates in this study generally are 

attributable to differences in the methods used to estimate 

runoff and evapotranspiration, the inclusion of fog interception in this study, and the shorter computational time 

step used in this study. The substantially lower estimates of 

recharge in this study for the Mähukona, Waimea, and Häwï 

aquifer systems—38, 34, and 29 percent lower, respectively—compared to the estimates used in the 2008 WRPP 

may be of concern. These areas are experiencing a growth in 

development and a related growth in demand for water. For 

the drought simulation, which used historical rainfall from 

the period 1991–95, the estimates of recharge for all three 

of these aquifer systems were substantially less than the sustainable yields of the aquifer systems set by CWRM. 

Recent projections of rainfall change owing to effects of 

ongoing climate change generally indicate a slight increase 

in islandwide rainfall, and estimates of annual recharge in 

the late 21st century are higher than baseline estimates for 

every aquifer system, except ÿAnaehoÿomalu. On average, 

these aquifer-system recharge estimates are higher by about 

8 percent compared to baseline estimates.

In the Kona area, groundwater recharge was highest during 2004–8 and lowest during 1999–2003. These extremes 

in recharge coincided with the periods of highest and lowest 

rainfall, respectively. On a monthly basis, average recharge 

during 1984–2008 was highest in January and lowest in 

August; however, no seasonal pattern is discernible. Spatially, the highest recharge occurred in a belt about 4 miles 

wide running parallel to the coast about 2 miles inland. 

Sensitivity of recharge estimates to input parameters 

is related to the climate and land-cover conditions of the 

particular area of study. For the wet, forested areas characteristic of the windward side of the island, recharge was 

most sensitive to the ratio of runoff to rainfall. For the dry, 

grassland areas characteristic of the northwestern leeward 

side of the island, recharge was most sensitive to root depth. 

For the Kona area, characterized by moderate rainfall and a 

wide variety of land cover, recharge was very sensitive to pan 

coefficients and the net-precipitation rate in forests.

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