EXPLANATION

LOCATION OF PRINCIPAL PUBLISHED STUDIES

AVERAGE ANNUAL PRECIPITATION, 1961-1990, IN CENTIMETERS

Precipitation data modified from the Western Region Climatological Center, 

written commun., 2006, <http://www.wrcc.dri.edu/precip.htm>

Greater than 150

100 - 150

50 - 100

Less than 50

Ely, 2006 (basins)

Nolan and others, 2007

(wells)

Multi-state study

Coes and others, 2007

Delin and others, 2007

Gebert and others, 2007

Risser and others, 2005

Single-state or basin study

This Fact Sheetsummarizesthe significant research contributions

of recharge studies initiated by the GWRP in humid regions of the

United States. As defined for these studies, the humid region refers

to parts of the continental United States that receive greater than

about 50 centimeters of average annual precipitation (fig. 1), not

including some high-elevation areas of the Rocky Mountains.

Research priorities of this initiative included: (1) evaluating the

temporal and spatial variability in ground-water recharge and identifying factors that influence that variability; (2) developing recharge

estimates on a regionalscale; and (3) developing innovative methods

to estimate recharge and to quantify accuracy of estimates.

GWRP Recharge Studies

 Six studies were conducted in this initiative (fig. 1) including

four at basin- or statewide-scales:

• Minnesota (Delin and others, 2007),

• North Carolina (Coes and others, 2007),

• Pennsylvania (Risser and others, 2005),

• Wisconsin (Gebert and others, 2007).

Two studies were conducted with sites in multiple states:

• Sensitivity analysis of seven watershed models (Ely, 2006),

• Statistical analysis of samples collected at multiple National

Water Quality Assessment (NAWQA) sites (Nolan and others, 2007).

In addition to these principal publications, all or part of the

research documented in several other publications was completed as

part of this GWRP initiative and are noteworthy: Heppner and

Nimmo (2005) presented a computer program for predicting

recharge from water-table fluctuations; Dripps and others (2006)

presented estimates of recharge with analytic element models and

parameter estimation; Juckem and others (2005) evaluated scale

effects of hydrostratigraphy and recharge zonation on base flow;

Lorenz and Delin (2007)

presented a regression

model that was used to estimate recharge in Minnesota;

Heppner and others (2007)

compared multiple methods

for estimating recharge; and

Gebert and others (2005)

discussed the importance of

spatial and temporal variability of recharge.

Recharge Estimation

Methods

Ground-water recharge

in the six GWRP studies

was estimated using many

methods (table 1). The

methods are grouped on the

basis of the spatial scale:

local, representing 1 to

1,000s of square meters;

basin, representing 10 to

100s of square kilometers,

and regional, representing

100s to 1,000s of square

GROUND-WATER RESOURCES PROGRAM

Ground-Water Recharge in Humid Areas of the United States—A Summary

of Ground-Water Resources Program Studies, 2003-06

Geoffrey N. DelinandDennis W. Risser

Increased demands on water resources by a growing population

and recent droughts have raised awareness about the adequacy of

ground-water resourcesin humid areas of the United States. The spatial and temporalvariability of ground-water recharge are keyfactors

that need to be quantified to determine the sustainability of groundwater resources. Ground-water recharge is defined herein as the

entry into the saturated zone of water made available at the watertable surface, together with the associated flow awayfrom the water

tablewithin the saturated zone (Freeze and Cherry, 1979). In response

to the need for better estimates of ground-water recharge, the

Ground-Water Resources Program (GWRP) of the U.S. Geological

Survey (USGS) began an initiative in 2003 to estimate ground-water

recharge rates in the relatively humid areas of the United States.

Figure 1. Locations of U.S. Geological Survey Ground-Water Resources Program recharge studies in humid areas of

the United States and 1961-1990 average annual precipitation.

U.S. Department of the Interior

U.S. Geological Survey Printed on recycled paper

USGS Fact Sheet FS–2007-3007

March 2007
kilometers. Methods based on unsaturated-zone and surface-water

data provide estimates of potential or net recharge whereas those

based on ground-water data generally provide estimates of actual

recharge. The reader is referred to the individual reports for descriptions of these methods.

Contributions of the GWRP Recharge Research

This research initiative resulted in contributions to the science of

recharge estimation as follows:

New Methods

Two new computer routines were developed to estimate recharge

from water-table fluctuations. Both methods utilize a master recession curve for water levels in a well, which allows better recognition

of recharge during periods when the water level in the well is not

rising (Heppner and Nimmo, 2005; Delin and others, 2007).

Regional Estimates of Recharge

A new process was developed for regionalizing local- or basinscale recharge estimates in Minnesota (Lorenz and Delin, 2007).

Recharge based on this regional regression recharge (RRR) method

(fig. 2) compared favorably with results from local- and basin-scale

methods in Minnesota (table 1). The RRR rates were within 5 to

35 percent of the rates based on the unsaturated-zone water balance

(UZWB) method, the water-table fluctuation (WTF) method, age

dating of ground-water method, as well as those based on the computer code RORA (Rutledge, 1998).

A new process to estimate average annual base flow at ungaged

sites in Wisconsin was developed by multiple-regression analysis

using basin characteristics (Gebert and others, 2007). The equation

with the lowest standard error of estimate had drainage area, basin

storage, soil infiltration, and base-flow factor as independent variables.

Comparison of Methods and Factors Affecting Recharge

Estimates

• Estimates of long-term average recharge in the GWRP studies

ranged from 10 to 66 percent of precipitation (table 1).

Recharge estimates from the UZWB, Darcian, and chloride

methods were extremely variable because they represent local

recharge. Estimates of average recharge from the DarcianTable 1. Summary of recharge methods used in the six principal studies and the range of estimated recharge as a percent of precipitation.

Average values are in parentheses.

METHODS

GWRP STUDY SITES

Minnesota

(Delin and

others,

2007)

North Carolina

(Coes and

others,

2007)

Pennsylvania

(Risser and

others,

2005)

Wisconsin

(Gebert and

others,

2007)

NAWQAstudy

(Nolan and

others,

2007)

Model study

(Ely, 2006)

Local Scale

Water-table fluctuation (WTF) 6-56 (21) 25-94 (56) 19-48 (24)

Age dating of ground water 7-49 (24) 2-36 (12)

Unsaturated-zone water balance (UZWB) 25-60 (43)

Gravity-drainage lysimeters 25-33 (29)

Water-balance equation 25-32 (29)

Darcian flux 62-69 (66) 0.00-1,064 (64)

Chloride unsaturated-zone tracer 0.05-119 (10)

Chloride saturated-zone tracer 0.1-327 (17)

Basin Scale

Rorabaugh equations 8-44 (19) 16-27 (24) 24-33 (29)

Streamflow-hydrograph separation 21-28 (25) 3-54 (21)

Model analyses 0.3-63 (24)

Regional Scale

Regional or statewide regression equations 8-38 (21) 2-42 (20)

Figure 2. Average annual recharge rate to surficial materials

in Minnesota (1971-2000) estimated on the basis of the regional

regression recharge method (Lorenz and Delin, 2007)
flux method was large compared to the other methods; estimates based on the chloride methods were small, on average, 

compared to the other methods. 

• Watershed size affected base-flow estimates for some 

hydrograph-separation methods (Risser and others, 2005). If 

watersheds of various sizes are being compared, it may be 

advantageous to use the computer code PART (Rutledge, 

1998) or the local-minimum version of the computer code 

HYSEP (Sloto and Crouse, 1996) because these programs did 

not seem to be artificially affected by watershed scale.

• The spatial distribution of mean annual recharge from unsaturated-zone and ground-water data collected in the Coastal 

Plain of North Carolina was examined against seven environmental indicators, only two of which—the sand content and 

silt content of the surficial sediments—significantly correlated with estimated recharge (Coes and others, 2007). 

• In the multi-state study by Nolan and others (2007), recharge 

estimates using chloride-tracer methods were less variable 

and more strongly correlated with variables representing climate, hydrology, land use and management, and soil properties compared with Darcian-flux recharge estimates. The 

Darcian estimates had considerable uncertainty because of the 

nonlinear function of hydraulic conductivity with moisture 

content, and because of uncertainties in the pedotransfer functions used to estimate water-retention parameters. A nonlinear 

regression model explained 61 percent of the regional variation in ground-water chloride-tracer estimates of recharge 

(Nolan and others, 2007). 

• Model-sensitivity analysis indicated that large-scale climate 

and flow processes (mean annual runoff, air temperature, precipitation, and topographic wetness index) most influenced 

the recharge estimates derived from the precipitation-runoff 

modeling system (Ely 2006). 

Conclusions of the GWRP Recharge Research

The following conclusions were gleaned from this research initiative:

Comparison of multiple methods is recommended. The

GWRP recharge research demonstrated that no single recharge 

method can be assumed to be most appropriate in humid areas over 

all scales and time periods. This research confirms the results of previous studies that, because of the limitations and uncertainties of 

each method, the use of multiple recharge-estimation methods is 

beneficial.

For example, in the Coastal-Plain sediments of North Carolina, 

Coes and others (2007) found that mean annual potential and total 

recharge determined using ground-water age dating, Darcian flux, 

and WTF methods were as much as 250 percent greater than mean 

annual net recharge determined by the computer code RORA. The 

large disparity was primarily attributed to ground-water losses 

between recharge and discharge areas, leading to the conclusion that 

RORA probably underestimates recharge in this setting. In contrast, 

for Minnesota watersheds mantled with glacial sediments, Delin and 

others (2007) found that recharge rates using the computer code 

RORA were within the range of recharge estimated from the groundwater age dating, WTF, and UZWB methods.

Comparison of multiple methods at a small basin in Pennsylvania 

showed that the simple determination of long-term base flow can 

provide a useful estimate of recharge. In this study, base flow was 

within the range of variability of recharge estimates from the waterbalance equation, WTF method, and gravity-drainage lysimetersthat 

were considerably more difficult to apply (Risser and others, 2005). 

High-quality, long-term continuous hydrologic and climatic 

records are important. Because recharge can vary significantly 

year to year (Risser and others, 2005; Dripps and others, 2006; Delin 

and others, 2007), long-term continuous records of hydrologic 

(fig. 3) and climatic data are required to truly characterize recharge. 

Long-term continuousrecords are required for use ofsome computer 

programs that compute recharge from streamflow, ground-water levels, or hydrologic water-balance data. If missing values need to be 

estimated, an additional degree of uncertainty is added to the results. 

Ely (2006)showed that recharge estimated by five watershed models 

across the United States was sensitive to air temperature, emphasizing the importance of temperature data.

Delin and others (2007) showed that frequency of water-level 

measurements is important in applying the WTF method. Measurements made less frequently than about once per week resulted in as 

much as a 48 percent underestimation of recharge based on an hourly 

measurement frequency.

Local-scale estimates of recharge are highly variable and may 

be difficult to regionalize or transfer from one location to 

another. Numerous factors influence the spatial variability of 

recharge locally including physical characteristics of the soil, vegetation cover, land use, topography, water content ofsurface materials 

(fig. 4), depth of the confining layers and aquifers, and the present 

climate conditions. These localized,small-scale variations cannot be 

included in regionalized recharge estimates,such asthe RRR method 

(fig. 2). Low-permeability units at or near land surface and evapotranspiration effects in areas of shallow ground water could greatly 

reduce estimated local-scale recharge rates, for example. In contrast, 

focused recharge of water in depressional areas due to surface-water 

runoff from surrounding upland areas would result in higher estimates at those sites. Because of this spatial variability, local estimates of recharge are of limited use in estimating basin- or regionalscale recharge.

Temporal variability must be considered. Results clearly demonstrate recharge rates vary seasonally and annually at any given 

location (Risser and others, 2005; Dripps and others, 2006; Delin and 

others, 2007). Temporal variations of recharge stem from factors 

such asthe amount, intensity, and duration of precipitation; ET rates; 

and temperature. Changes in land use, such as agricultural practices, 

also can appreciably affect recharge.

Figure 3. Streamflow-gaging station in north-central 

Pennsylvania used to estimate ground-water recharge from 

streamflow records. 
Regionalized recharge estimates should be used with caution.

Recharge based on the regionalization of local- or basin-scale data 

should be used with caution for annual estimates of recharge because 

average values of precipitation, recharge, and other variables were 

used to construct the maps and regression equations. Actual recharge 

will vary from year to year depending on climate. Data collected at 

local and basin scales are necessarily averaged to make regionalized 

estimates of recharge. 

Differences in the positions of the surface-water and groundwater divide can make a large difference in average annual baseflow values averaged over the entire basin. Estimation of average 

recharge rates from stream base flow requires knowledge of the 

ground-water area contributing to base flow. Where the perimeter of 

the contributing ground-water area is defined by ground-water 

divides, the traces of the divides must be defined to compute a contributing area. Assuming that ground-water divides are coincident 

with overlying surface-water divides can result in erroneous estimates of recharge (Gebert and others, 2007). 

The WTF method requires extra caution in materials with 

low specific yield. Small absolute errors in estimating specific yield 

in low-storage fractured-rock aquifers can cause large errors in 

recharge estimates by the WTF method (Risser and others, 2005). 

Where possible, estimates from multiple observation wells should be 

used.

Acknowledgments

The authors would like to acknowledge the contributions of all 

USGS personnel who worked on this GWRP research initiative, 

most notably Alissa Coes, D. Matthew Ely, Richard Healy, Christopher Heppner, Randall Hunt, David Lorenz, John Nimmo, Thomas 

Nolan, and Thomas Winter. 

GWRP Information Products

Coes, A.L., Spruill, T.B., and Thomasson, M.J., 2007, Multiple-method 

estimation of recharge rates at diverse locations in the North Carolina 

Coastal Plain: Hydrogeology Journal, accessed Feb. 7, 2007, 

at http://dx.doi.org/10.1007/s10040-006-0123-3, 16 p. 

Delin, G.N., Healy, R.W., Lorenz, D.L., and Nimmo, J.R., 2007, Comparison of local- to regional-scale estimates of ground-water recharge 

in Minnesota, USA: Journal of Hydrology, v. 334, no. 1-2, p. 231-

249. 

Dripps, W.R., Hunt, R.J., and Anderson, M.P., 2006, Estimating 

recharge rates with analytic element models and parameter 

estimation: Ground Water, v. 44, no. 1, p. 47-55.

Ely, D.M., 2006, Analysis of sensitivity of simulated recharge to 

selected parameters for seven watersheds modeled using the precipitation-runoff modeling system: U.S. Geological Survey Scientific 

Investigations Report 2006-5041, 21 p.

Gebert, W.A., Kennedy, J.L., and Hunt, R.J., 2005, The importance of 

spatial and temporal variability in recharge, in Neff, B.P., Piggott, 

A.R., and Sheets, R.A., Estimation of shallow ground-water recharge 

in the Great Lakes Basin: U.S. Geological Survey Scientific Investigations Report 2005-5284, 20 p. 

Gebert, W.A., Radloff, M.J., Considine, E.J., and Kennedy, J.L., 2007, 

Use of streamflow data to estimate base flow/ground-water recharge 

for Wisconsin: Journal of the American Water Resources Association, v. 43, no. 1, p. 220-236.

Heppner, C.S., and Nimmo, J.R., 2005, A computer program for predicting recharge with a master recession curve: U.S. Geological Survey 

Scientific Investigations Report 2005-5172, 8 p. 

Heppner, C.S., Nimmo, J.R., Folmar, G.J., Gburek, W.J., and Risser, 

D.W., 2007, Multiple-methods investigation of recharge at a humidregion fractured rock site, Pennsylvania, USA: Hydrogeology Journal, accessed Feb. 7, 2007, at http://www.springerlink.com/content/

d245365625x8kj31/, 13 p. 

Juckem, P.F., Hunt, R.J., and Anderson, M.P., 2005, Scale effects of 

hydrostratigraphy and recharge zonation on base flow: Ground 

Water, v. 44, no. 3, p. 362-370. 

Lorenz, D.W., and Delin, G.N., 2007, A regression model to estimate 

regional ground-water recharge in Minnesota: Ground Water, v. 45, 

no. 2, p. 196-208. 

Nolan, B.T., Healy, R.W., Taber, P.E., Perkins, Kimberlie, Hitt, K.J., 

and Wolock, D.M., 2007, Factors influencing ground-water recharge 

in the eastern United States: Journal of Hydrology, v. 332, no. 1-2, 

p. 187-205. 

Risser, D.W., Gburek, W.J., and Folmar, G.J., 2005, Comparison of 

methods for estimating ground-water recharge and base flow at a 

small watershed underlain by fractured bedrock in the eastern United 

States: U.S. Geological Survey Scientific Investigations Report 

2005-5038, 31 p.

Other References

Freeze, R., and Cherry, J., 1979, Groundwater: Englewood Cliffs, N.J., 

Prentice-Hall, 604 p.

Rutledge, A.T., 1998, Computer programs for describing the recession 

of ground-water discharge and for estimating mean ground-water 

recharge and discharge from streamflow records – Update: U.S. Geological Survey Water-Resources Investigations Report 98-4148, 43 p.

Sloto, R.A., and Crouse, M.Y., 1996, HYSEP—A computer program for 

streamflow hydrograph separation and analysis: U.S. Geological 

Survey Water-Resources Investigations Report 96-4040, 46 p. 

Figure 4. Instrumentation installed in the unsaturated zone 

at a site near Bemidji, Minnesota, to estimate recharge using 

the UZWB method. 

For additional information on the activities of the USGS GroundWater Resources Program, visit our Web site at 

http://water.usgs.gov/ogw/gwrp/

or contact:

U.S. Geological Survey

Ground-Water Resources Program

411 National Center

Reston, VA 20192

Phone: 703-648-5001

Fax: 703-648-6693