Prepared in cooperation with the New Hampshire Department of Environmental Services and the 

New Hampshire Geological Survey

Preliminary Assessment of Trends in Static Water Levels 

in Bedrock Wells in New Hampshire, 1984 to 2007

Open-File Report 2010–1189

U.S. Department of the Interior

U.S. Geological Survey
Cover. Mosaic of well heads from bedrock wells from across New Hampshire (photographs courtesy of Marcel 

Belaval, U.S. Environmental Protection Agency; and James Degnan and Sarah Flanagan, U.S. Geological Survey).
Preliminary Assessment of Trends in Static 

Water Levels in Bedrock Wells in New 

Hampshire, 1984 to 2007

By Joseph D. Ayotte, Brandon M. Kernen, David R. Wunsch, Denise M. Argue, 

Derek S. Bennett, Thomas J. Mack

Prepared in cooperation with the New Hampshire Department of Environmental 

Services and the New Hampshire Geological Survey

Open-File Report 2010–1189

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

KEN SALAZAR, Secretary

U.S. Geological Survey

Marcia K. McNutt, Director

U.S. Geological Survey, Reston, Virginia: 2010

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reproduce any copyrighted materials contained within this report.

Suggested citation:

Ayotte, Joseph D., Kernen, Brandon M., Wunsch, David R., Argue, Denise M., Bennett, Derek S., Mack, Thomas J., 

2010, Preliminary assessment of water levels in bedrock wells in New Hampshire, 1984 to 2007: U.S. Geological 

Survey Open-File Report 2010–1189, 30 p., at http://pubs.usgs.gov/of/2010/1189.
iii

Acknowledgments

The authors acknowledge the support and input of the drilling and environmental-science 

communities in the development of this report. Special thanks are extended to the drilling 

industry for their effort in providing well-completion reports and to the NHDES staff, particularly 

Richard Schofield and Frederick Chormann, who have over the years carefully managed these 

data. Thanks also to Allen Shapiro, Rodney Sheets, Leslie DeSimone, and Dennis Risser of the 

USGS for discussion of data and analyses. Mary Ashman edited the report, M. Patricia Lee and 

Mark Bonito provided layout and graphic assistance.
This page has been left blank intentionally.
v

Contents

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

Introduction.....................................................................................................................................................2

Study Design and Methods..........................................................................................................................4

Static Water-Level and Well-Construction Data .............................................................................4

Ancillary Data........................................................................................................................................4

Statistical Analyses..............................................................................................................................6

Static Water Levels in Bedrock Wells in New Hampshire .....................................................................7

Relations among Static Water Levels, Precipitation, and Groundwater Recharge ..................9

Relation of Static Water Levels to Well-Construction Parameters.....................................................10

Total Depth, Casing Length, and Length of Casing in Bedrock ...................................................14

Elapsed Time and Yield ......................................................................................................................16

Hillslope Effects...................................................................................................................................16

Multiple Regression Analysis of Static Water Levels............................................................................18

Local-Scale Factors.....................................................................................................................................22

Local-Scale Geology ..........................................................................................................................22

Static Water Levels in Areas with Known Groundwater-Supply Concerns .............................22

Static Water Levels in Deepened and Replacement Wells.........................................................24

Summary and Conclusions.........................................................................................................................28

References Cited..........................................................................................................................................28

Figures

1. Map showing locations of 29,408 geolocated wells with static water level data in

New Hampshire ............................................................................................................................3

2. Graph showing mean annual static water level in bedrock wells in New Hampshire,

1984 through 2007; A) mean static water level per year, B) population in New 

Hampshire, 1984 through 2007; and C) mean annual static water level as a 

function of population ..................................................................................................................8

3. Graph showing mean quarterly static water levels in bedrock wells in New

Hampshire, 1984 through 2007....................................................................................................9

4. Graphs showing A) Mean annual precipitation at Portsmouth, Durham, and

Concord, New Hampshire, 1984–2005; B) third-quarter base flow at Beaver Brook,

Oyster River, and Soucook River; and C) mean quarterly static water levels,

1984–2007 .....................................................................................................................................11

5. Boxplots summarizing A) quarterly precipitation at Concord Municipal Airport;

B) quarterly base flow at Oyster River, near Durham, NH (01073000); and C) mean

quarterly static water level statewide by quarter, 1984− 2007............................................12

6. Graphs showing A) mean total well depth by year and quarter; B) mean casing

length, mean length of casing in bedrock, and mean bedrock depth by year and

quarter; C) mean total well depth and mean length of casing in bedrock as a

function of mean static water level; and D) mean length of casing in bedrock as a

function of mean total well depth ............................................................................................13

7. Graphs showing mean length of water column in bedrock wells in New Hampshire,

1984 through 2007 .......................................................................................................................15
vi

8. Boxplots summarizing A) mean static water level, B) mean total well depth, C)

mean casing length, D) mean length of casing in bedrock, E) mean bedrock depth,

and F) mean reported yield, for categories of elapsed time between well

construction and static water-level measurement...............................................................17

9. Boxplots summarizing A) mean static water level, B) mean total well depth, C)

mean casing length, D) mean length of casing in bedrock, E) mean bedrock depth,

and F) mean reported yield, for categories of height above the minimum elevation

within a 1,640-foot (500-meter) radius.....................................................................................19

10. Graphs showing mean elevation of well, mean slope at the well, and mean

height above minimum elevation within 1,640-foot (500-meter) radius by year and 

quarter, 1984−2007. .....................................................................................................................20

11. Boxplots summarizing A) mean quarterly static water level, B) mean total well

depth, and C) mean length of casing in bedrock for major lithologic groups in 

New Hampshire (groups from Robinson and Kapo, 2003) ...................................................23

12. Graphs showing relation of mean static water level to binary categories of height

of well above minimum elevation within a 1,640-foot (500-meter) radius of well 

(<100 feet (30 meters) and ≥ 100 feet (30 meters)) and aspect (N refers to ≥ 300

degrees and ≤ 60 degrees; S refers to > 60 degrees and < 300 degrees), by town.........25

13. Map showing locations of wells reported as replacement wells (black circles) or

deepened wells (green triangles) in New Hampshire, 1984−2007......................................26

14. Graphs showing A) mean static water level, B) mean total well depth, C) mean

elevation, and D) mean height above minimum elevation within a 1,640-foot 

(500-meter) radius, by categories of reported reason for well installation, New 

Hampshire, 1984−2007................................................................................................................27

Tables

1. Names and descriptions of fields in New Hampshire Department of Environmental

Services database of wells.........................................................................................................5

2. Types and sources of ancillary data tested in this study.......................................................6

3. Ten most frequently reported static-water levels, well depths, bedrock depths,

casing lengths, lengths of casing in bedrock, and yields for 56,437 wells in the New

Hampshire Department of Environmental Services database between 1984 and 2007 ...7

4. Summary of trend-test statistics for mean static water level and related well

parameters aggregated by year and quarter from 1984–2007 ............................................10

5. Spearman rank correlation coefficients for mean static water level and means of

selected physical and hydraulic parameters by year and quarter, 1984–2007 (n = 96) ..14

6. Correlation of mean static water level with year measured, mean total depth,

casing length, length of casing in bedrock, elapsed time, and yield, for grouted and

nongrouted wells by year and quarter, 1999–2007 (n = 36)..................................................16

7. Correlation of mean static water level with year measured, mean total depth,

casing length, length of casing in bedrock, elapsed time, and yield for categories

of elapsed time between construction and measurement of static water level;

aggregated by year and quarter, 1984–2007 (n = 96) ............................................................18

8. Comparison of mean quarterly values of selected variables for wells in igneous

and metamorphic rocks.............................................................................................................21

9. Multiple regression models on the means of logarithms of static water levels by major 

rock type in New Hampshire ....................................................................................................21
vii

Conversion Factors

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 0.004047 square kilometer (km2

)

square foot (ft2

) 0.09290 square meter (m2)

square mile (mi2

) 2.590 square kilometer (km2) 

Volume

gallon (gal) 3.785 liter (L) 

gallon (gal) 0.003785 cubic meter (m3

) 

Flow rate

gallon per minute (gal/min) 0.06309 liter per second (L/s)

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

°F=(1.8×°C)+32

Vertical coordinate information is referenced to the North American Vertical Datum of 1988 

(NAVD 88).

Horizontal coordinate information is referenced to the North American Datum of 1983 (NAD 83).

List of Acronyms

GPS Global positioning system

HAVB Height above minimum elevation (within a 1,640-ft (500-m) radius of a well)

NHDES New Hampshire Department of Environmental Services

NHGS New Hampshire Geological Survey

PART Streamflow partitioning program to estimate a daily record of base flow (groundwater discharge) from streamflow

SWL Static water level

WWB Water Well Board

WWI Water Well Inventory
This page has been left blank intentionally.
Preliminary Assessment of Trends in Static Water Levels

in Bedrock Wells in New Hampshire, 1984 to 2007

By Joseph D. Ayotte, Brandon M. Kernen,1 David R. Wunsch,2 Denise M. Argue, Derek S. Bennett,1 and 

Thomas J. Mack

Abstract

Analysis of nearly 60,000 reported values of static water level (SWL, as depth below land surface) in bedrock wells in 

New Hampshire, aggregated on a yearly basis, showed an apparent deepening of SWL of about 13 ft (4 m) over the period 

1984–2007. Water-level data were one-time measurements at each well and were analyzed, in part, to determine if they were 

suitable for analysis of trends in groundwater levels across the state. Other well characteristics, however, also have been 

changing over time, such as total well depth, casing length, the length of casing in bedrock, and to some extent, well yield. 

Analyses indicated that many of the well construction variables are significantly correlated; the apparent declines in water levels 

may have been caused by some of these factors. Information on changes in water use for the period was not available, although 

water use may be an important factor affecting water levels. 

Multiple regression models were used to determine the simultaneous effects of important variables on SWLs statewide. 

Models also were generated for each county, and the model-calculated results for counties were generally similar to the results 

for the state wide models.

The most significant predictors of mean SWL (aggregated by year and quarter) were total depth, the third quarter of 

the year (July–September), elevation, and height of well above minimum elevation within a 1,640-foot (500-meter) radius 

(hillslope factor). Casing length was a significant predictor of SWL for igneous-rock models and curvature of the land surface 

for metamorphic-rock models. Local geologic as well as landscape features appear to provide further explanation of SWL

variation. For example, SWLs in wells completed in specific granites appear to be deeper than in other granites; this relation was 

also observed for different groups of metamorphic rocks. 

A more detailed examination of data from six towns that report frequent complaints about low water supply from bedrock 

aquifer wells showed that hillslope position may play a role in the availability of water in wells. SWLs were commonly deeper 

(greater depth to water) for wells with more than 100 ft (30 m) of relief between the well and the lowest land-surface elevation 

within 1,640 ft (500 m) of the well. For these high-relief wells, the depth to SWL was commonly greater for those that were on 

generally south-facing slopes, compared to wells on north-facing slopes. 

Concerns about wells with very little water-producing capacity in localized areas of some towns may be better understood 

by considering some of the relations identified in this study. For example, the data show that the position of a well on a hillslope 

affects the SWL depth in that well; however, the data also indicate that the average yield of the well is lower for hillslope wells 

than for wells in lower relief areas. This relation indicates that as the hillslope factor increases (and SWLs become deeper), the 

amount of available water in the wells decreases. Knowledge of this relation indicates that deeper wells may be needed in areas 

of higher relief. 

In areas with less extreme relief, the overall depths of wells have increased substantially more than the depths to the SWL. 

This indicates that the amount of water stored in wells (wellbore storage) has increased, and thus more water is available for use 

in the average well. As a result, more water may be used because it is available, possibly adding to the problem of local well 

interference or exacerbating drought-related well problems.

These data provided an opportunity to examine groundwater-level conditions across the state; however, the bedrock wells 

used in this study would not be suitable for rigorous evaluation of trends in SWL across the state because the locations and 

characteristics of the wells vary with time. Further, these wells cannot substitute for a carefully designed network of wells 

selected for the sole purpose of monitoring trends in water levels over time. The SWL data may be useful in the design of a 

monitoring network, and continued collection of water-level data from the bedrock wells could be used to augment data from 

monitoring wells. 

1

 New Hampshire Department of Environmental Services.

2

 New Hampshire Geological Survey.
2    Preliminary Assessment of Trends in Static Water Levels in Bedrock Wells in New Hampshire, 1984 to 2007

Introduction

The New Hampshire Water Well Board (WWB) is responsible for the inventory of all water wells completed in New 

Hampshire (Wunsch and Bennett, 2004). Well-completion reports have been required for all new water wells installed in 

New Hampshire since 1984, and reports must be submitted by drillers within 90 days of completing an installation. The data 

are included in the New Hampshire Water Well Inventory (WWI) database, which is currently (2010) administered by the New 

Hampshire Geological Survey of the New Hampshire Department of Environmental Services. Data on well construction, well 

performance, and location were collected as part of this program. Nearly 60,000 New Hampshire well-completion reports, 

of which about 29,000 include geographic information (fig. 1), contain static water-level (SWL) and other well-construction 

measurements for the period 1984–2007. SWL is defined in this study as the depth, measured from land surface, in feet, to 

water in a well. All SWL data used in this report represent one-time measurements that were generally made on the day drilling 

was completed.

New Hampshire encompasses an area of approximately 9,000 mi2

 (23,310 km2) and had a population of 1.3 million people 

in 2008 (U.S. Census Bureau, 2009). Between 1980 and 2000, the population in the Seacoast region of southeastern New 

Hampshire increased 37 percent and is expected to increase another 25 percent by 2025 (Horn and others, 2007). The majority 

of New Hampshire’s population obtains drinking water from groundwater withdrawn from private- and public-supply wells 

(Ayotte and others, 2008). In densely populated areas of the state, such as the Seacoast region and southern towns, supply wells 

may be placed in close proximity to each other. As population density increases, each additional well may be competing with 

existing wells for a finite amount of water. Such competition could potentially lead to systematic declines in groundwater levels. 

Population growth in New Hampshire is expected to continue and with it the demand for water from the bedrock aquifer 

(Mack, 2009). The growth also could bring an increase in impervious-surface area through the building of new roads, parking 

lots, and homes, and increased use of sewering, which may further reduce recharge to the bedrock aquifer. The potential for 

widespread decline of bedrock groundwater levels has important implications for groundwater availability and the sustainability 

of water resources in New Hampshire. Modeling studies can be useful in determining the effects of changes in environmental 

factors on groundwater levels. A recent groundwater investigation in the Seacoast region of New Hampshire found that 

population growth, increased water demand, sewering, and climate change may all potentially lead to declining groundwater 

levels and base flows (Mack, 2009).

The potential effects of a changing climate on the groundwater resources of New Hampshire are also a concern. Recent 

research indicates that climate change has affected the hydrology of the northeastern U.S. (Hayhoe and others, 2007), and earlier 

spring runoffs have been correlated with rising air temperatures (Hodgkins and Dudley, 2006). Studies indicate that, in New 

England, base-flow discharge (groundwater discharge from aquifers) possibly has been declining, but none of the declines have 

been statistically significant (Hodgkins and others, 2005; Brutsaert, 2010). In one investigation, base flows correlated somewhat 

with precipitation (rather than temperature), but no consistent pattern was clear (Hodgkins and others, 2005). Actual water-level 

declines have been reported in other parts of the United States, for which the roles of global climate change or long-term cyclical 

climate patterns also are unclear (Skinner and others, 2007).

Understanding long-term trends in groundwater levels in New England’s bedrock aquifers is problematic because of the 

small number of long-term monitoring wells in these aquifers. A network of monitoring wells that was designed to assess 

climatic factors in New Hampshire is primarily monitoring unconsolidated aquifers. Examples from a recent groundwater study 

illustrate the need for long-term data to accurately assess trends in areas where small changes are expected, and suggest that it is 

premature to draw conclusions about drought or declines caused by increased water use or climate change on the basis of only a 

few decades of data (Brutsaert, 2010). 

Identification of declining groundwater levels and the factors associated with those apparent declines is vital to 

understanding the limitations of groundwater resources in bedrock aquifers. As an initial response to these concerns, a 

cooperative investigation involving the New Hampshire Department of Environmental Services (NHDES), New Hampshire 

Geological Survey (NHGS), and the U.S. Geological Survey (USGS) was initiated in 2008 to explore potential trends in SWL

and possible factors related to SWLs statewide, regionally, and locally. In this investigation statistical analyses were used to 

assess water-level, geohydrologic, climatic, and demographic data to provide a preliminary understanding of groundwater levels 

in New Hampshire’s bedrock aquifer. Multiple lines of evidence were used to develop hypotheses that might explain apparently 

deeper SWLs over time in wells used in the analysis. 

This report describes increases in depth to SWLs in bedrock aquifer wells in New Hampshire from 1984 to 2007. Data from 

the State of New Hampshire water-well inventory were analyzed to relate SWL data to time and well-construction data. This 

investigation was statewide to regional in scope and focused on SWLs in the bedrock aquifer. The analyses presented do not 

address site-specific hydrologic issues. Further investigation of these data may provide additional understanding of the nature of 

and factors related to SWL measurements in wells drilled in bedrock aquifers. 
Introduction    3

EXPLANATION

Well locations

Town boundaries

0 20 40 60 MILES

0 20 40 60 KILOMETERS MAINE

MASSACHUSETTS

VERMONT

VERMONT

MAINE

CANADA

MASSACHUSETTS

CONCORD

44 ̊

72 ̊

71 ̊

45 ̊

43 ̊

NASHUA

Goffstown KEENE

MANCHESTER

PORTSMOUTH

BERLIN

Plaistow

Kingston

Durham

Pelham

Bedford Windham

Derry

VERMONT

MAINE

CANADA

MASSACHUSETTS

44 ̊

72 ̊

71 ̊

45 ̊

43 ̊

INDEX BASIN MAP OF 

NEW HAMPSHIRE

Androscoggin

upper and lower

Upper Connecticut

Saco

Conn. Johns-Waits

Conn. Waits-White

Conn. White-Bellows

Conn. Bellows-Vernon

Conn. Vernon-Ashuelot

Conn. Millers

Salmon-Piscataqua

Winnipesaukee

Nashua

Merrimack

Contoocook

Pemigewasset

INDEX SUBBASIN MAP OF 

NEW HAMPSHIRE

VERMONT

MAINE

CANADA

MASSACHUSETTS

44 ̊

72 ̊

71 ̊

45 ̊

43 ̊

Soucook R.

Smith R.

Oyster R.

Beaver Bk.

Pemigewasset R.

INDEX COUNTY MAP OF 

NEW HAMPSHIRE

Coos

Grafton

Carroll

Sullivan

Cheshire

Hillsborough

Merrimack

Belknap

Rockingham

Strafford

Base maps from USGS and NH GRANIT

GIS digital data sources.

0 30 60 MILES

0 30 60 KILOMETERS

Gage location

Subbasins

EXPLANATION

Figure 1. Map showing locations of 29,408 geolocated wells with static water level data in New Hampshire.
4    Preliminary Assessment of Trends in Static Water Levels in Bedrock Wells in New Hampshire, 1984 to 2007

Study Design and Methods

For this study, relations between information in well-completion reports and trends in the data over the period 1984–2007 

were examined. Because the data were collected for tracking well installation and associated information and not for SWL-trend 

analysis, they do not include multiple measurements of SWL at individual wells over time; however, because of the large 

number of measurements, they could be used to determine general information about SWLs over time. Because the data also 

include information about well construction, they allow the relations between SWLs and factors such as well depth, casing, 

yield, as well as trends in such construction factors, to be determined. 

Static Water-Level and Well-Construction Data

The WWI database contained 111,745 well-completion reports, of which 56,437 included SWL data, as of 2007. Because 

latitude and longitude information for about 29,000 of these wells was available, it could be used to obtain additional ancillary 

data from geographic-information system (GIS) databases. When the well-completion reporting system was initiated, the WWB 

located wells to the nearest second (within an error range of approximately 100 ft (30 m) in New Hampshire) on topographic 

maps and manually transcribed coordinates for entry into the database. Currently, most well locations are determined either by 

the driller using global positioning system (GPS) devices or by the NHGS using desktop analysis of aerial photography. As a 

result, the number of wells with positions determined accurately each year has increased substantially. 

Well-completion reports include such information as: owner and address, driller, purpose (use) of well, well-completion 

date, depth to bedrock, depth drilled, type (setting) of well, length of casing, method of seal, yield, and SWL and date measured 

(table 1). Additional variables, such as the time elapsed between well completion and measurement of water level, are calculated 

from the original data. Similarly, the length of casing in bedrock was calculated as equal to the length of casing installed minus 

the reported depth to bedrock. 

The SWL and other data were self-reported by the professionals who construct water wells and install pumps. Whereas 

these data are sufficiently accurate for the purposes for which they were collected, the nature of the data may affect the 

assessment of trends in water levels in bedrock wells in New Hampshire; however, no direct information is available to evaluate 

the accuracy of these values. 

Ancillary Data

The New Hampshire SWL data were assessed with respect to ancillary data including demographic information, 

precipitation, streamflow, and geology (U.S. Geological Survey, 1993; U.S. Census Bureau, 2001; Robinson and Kapo, 2003; 

U.S. Geological Survey, 2004; U.S. Census Bureau, 2006; U.S. Geological Survey, 2008; National Climatic Data Center, 2009) 

(table 2). Annual total precipitation values for Concord, Manchester, and Portsmouth were obtained from National National 

Atmospheric and Oceanic Administration for the study period (National Climatic Data Center, 2009).

Changes in quarterly and annual estimated base flows for Beaver Brook (USGS streamgage 010965852) and the Oyster 

(01073000), Soucook (1089000), Smith (1078000), and Pemigewasset River (1076500) drainage basins were used for 

comparisons with water levels over the study period to provide an indication of groundwater recharge trends. These drainage 

basins were selected because they were gaged during the entire study period (U.S. Geological Survey, 2008), were relatively free 

from the effects of regulation, and represented the three physiographic provinces (Seaboard Lowland, New England Upland, 

and White Mountain) of New Hampshire (Flynn and Tasker, 2004). Base flows were calculated with hydrograph separation 

techniques from daily mean streamflow by the program PART (Rutledge, 1993, 1998).
Study Design and Methods    5

Table 1. Names and descriptions of fields in New Hampshire Department of 

Environmental Services database of wells.

Field Name Description

LICENSE_NUMBER Well driller's license number

WELL# Well number assigned by driller

WRB# Water Resources Board ID

ELEV Elevation of land surface

LATITUDE Latitude

LONGITUDE Longitude

LOCENT Entity responsible for location

LOCACC Estimate of the relative accuracy

FNAME First name of well owner

LNAME Last name of well owner

ST_NUMBER Street number of well location

ROAD Address of well location

ROAD2 Additional information about well location 

TOWN Town in which well is located

MAP Map page number 

PARCEL Parcel identifier 

DCOMP Date well was completed

USE Reason for constructing well

REASON Proposed use of well

TYPE Type of well

TOTD Total depth of well

BDKD Depth to bedrock

CASING Total length of casing

YTM Yield-test method

YTD Yield-test duration

YTQ Discharge (yield)

SWL Static water level

DMEAS Date of measurement of static water level

OB Type of overburden material

HYDRO_FRACT Hydrofractured

HF_YIELD_BEFORE Yield before hydrofractured

GROUTED Grouted

NOTE Special notes
6    Preliminary Assessment of Trends in Static Water Levels in Bedrock Wells in New Hampshire, 1984 to 2007

Statistical Analyses

In this study, statistical methods were used to investigate water-level trends in bedrock wells. The analyses were done in 

three parts: 1) trend and distributional analysis of the well-completion data, 2) correlation and multiple-comparison test analysis 

of the data, particularly for relation to SWL, and 3) multiple regression analysis to identify factors that explain variance in the 

SWL data. Factors not included in the well-completion reports, such as climatic, geologic, and demographic variables, also 

were used in the analyses, for the wells with location information. 

Kendall and seasonal Kendall tests were used to test for trends in SWL and other variables over the study period (Hirsch 

and Slack, 1984; Helsel and others, 2006). Spearman correlation analysis was used to indicate relations among the variables 

tested (Helsel and Hirsch, 1992; Helsel, 2005). A Spearman’s rho of about 0.7 or higher (or -0.7 or lower) was considered 

indicative of a strong correlation. The nonparametric Wilcoxon (two-sample) and Kruskal-Wallis tests were used to compare 

distributions of data (Helsel and Hirsch, 1992; Helsel, 2005). 

Multiple regression evaluates multiple variables simultaneously and was used to indicate which variables were the most 

significant predictors of SWL (Helsel and Hirsch, 1992). The model is of the form

ln(SWL) = β0

 + β1(X1) + β2(X2)...βn(Xn) + E,	 	 	 	 	 (1)

where 

ln(SWL) = natural log of the static water level,

β0

 = model intercept,

β1

 – βn = regression parameter estimates,

X1

 – Xn = independent variables, and

E = random error.

The SWL data are generally log-normally distributed. For nonparametric tests, the SWL data were rank-transformed prior 

to testing, whereas in the regression analyses, SWL data were log-transformed before analysis. A statistical test was considered 

significant when p-values were less than 0.05. For the regression model, a parameter estimate was considered significant if the 

p-value was less than 0.05. Regression model r-squared values of about 0.5 or higher were considered strong relations. All 

statistical tests and models were done with SAS System software (SAS Institute Inc., 2008).

 Because of the large amount of data and their variability, the data were aggregated at various time scales. Aggregation of 

the data can reduce well-to-well variability in the larger data set (Nolan and Hitt, 2006); therefore, most analyses were done on 

data aggregated by year or by year and quarter. In this report, the first quarter of the year was January through March, the second 

quarter April through June, and so on. In this way, summary statistics for the variables were generated for each quarter for the 

period 1984–2007. Graphical representations of the data also were used and, in some cases, ordinary least-squares regression 

was used to indicate relations among graphed variables, with the regression equation and the coefficient of determination (R2

) 

values shown on the graphs (Helsel and Hirsch, 1992). Also, cubic spline lines were used on some graphs to portray seasonal 

patterns (SAS Institue, 1999).

Table 2. Types and sources of ancillary data tested in this study.

Data type Source

Population and housing density U.S. Census Bureau, 2001, 2006

Monthly precipitation for Durham, Concord, and Portsmouth National Climatic Data Center, 2009

Monthly base-flow discharge calculated from streamflow U.S. Geological Survey, 2008

Data on elevation, slope, aspect, curvature, and rate of change 

of curvature from Digital Elevation Model

U.S. Geological Survey, 1993, 2004

Geologic data Robinson and Kapo, 2003
Static Water Levels in Bedrock Wells in New Hampshire    7

Static Water Levels in Bedrock Wells in New Hampshire

SWL data in the New Hampshire WWI represent one-time measurements of SWLs primarily in newly constructed wells, 

mostly within 3 days after the wells were constructed. More than 80 percent of SWL measurements were made on the day 

of construction. In many cases the SWL data values appear to have been rounded on the basis of several factors, such as 

measurement method, depth to water, and elapsed time between drilling and measurement; however, because of the large sample 

size, it is possible to see trends even in the data affected by rounding. Trends in the data were identified at yearly and quarterly 

aggregations of the SWL data.

The 10 most frequently reported values of SWL, well depth, bedrock depth, casing length, length of casing in bedrock, and 

yield for 56,437 wells in the New Hampshire WWI database between 1984 and 2007 are shown in table 3. It is notable that the 

10 most frequently reported values of data for parameters such as SWL and total depth of well typically end in zero or five; these 

10 values represent over 64 percent of the SWLs in the database. This coincidence indicates that some SWLs were estimated 

rather than directly measured. Historically, SWLs have been measured by a variety of methods including tapes, sonic indicators, 

wet marks on drilling rods, and by a method known as pebble drop (dropping a pebble and measuring the time until it hits the 

water surface) (R. Schofield, New Hampshire Department of Environmental Services, oral commun., 2010).

Some values for bedrock depth, casing length, length of casing in bedrock, and yield also appear to be rounded or 

estimated, but these values typically were obtained for wells drilled by equipment such as drill rods that are generally produced 

in even lengths. Thus, values for parameters related to drilling depth and casing are probably not rounded in the same way as 

SWL data. For casing length, anecdotal evidence indicates that depths ending in 1 are valid and may be related to the addition of 

a 1-ft drive shoe on the bottom of even-number intervals of casing. Also, many casing lengths were reported as even intervals, 

indicating that some lengths were reported with the drive shoe and some without, or that a drive shoe was not always used. 

Examination of yield data indicates that the most common values were rounded, and that low yields were reported without 

rounding. This would be expected, because the difference between 1 and 2 gal/min (3.8 to 7.6 L/min) can be important in 

terms of reliable supply. Despite these limitations, the variability of data in the database is sufficient for SWL patterns related to 

common explanatory variables to be discerned from the aggregated data. 

For yearly aggregated data, the mean SWL appears to have become deeper by about 13 ft (4 m) over the period 1984 

to 2007 (fig. 2A). The reason for the apparent increase in the mean depth to SWL could be related to many possible factors, 

including increasing population (fig. 2B, C) and associated water use, well hydraulics, well construction, land use, and climate 

change. For example, the change in mean SWL could be related to new homes being built in settings such as hillsides or ridges, 

where SWLs can be somewhat deeper than in valley settings. Another hypothesis is that continued development and associated 

increases in water use, particularly for lawn watering, have resulted in lower water levels locally and regionally. Alternatively, 

Table 3. Ten most frequently reported static-water levels, well depths, bedrock depths, casing lengths, lengths of casing in bedrock, 

and yields for 56,437 wells in the New Hampshire Department of Environmental Services database between 1984 and 2007.

Static water level

(feet below

land surface)

Total well depth

(feet below

land surface)

Bedrock depth

(feet below

land surface)

Casing length

(feet)

Length of casing in

bedrock

(feet)

Yield

(gallons

per minute)

Value Percent Value Percent Value Percent Value Percent Value Percent Value Percent

20 16.3 300 4.5 10 7.0 20 16.0 10 8.6 20 7.5

10 8.6 500 4.2 8 5.7 40 15.0 15 8.5 10 7.3

30 8.3 305 3.7 5 4.4 21 5.3 12 7.2 5 6.8

15 7.9 505 3.2 6 4.4 60 4.9 20 5.6 15 6.4

25 5.7 400 3.2 15 4.0 30 3.9 14 5.1 4 6.0

40 5.6 200 3.0 20 3.7 41 3.7 13 4.9 3 5.7

0 3.9 420 2.6 4 3.5 42 2.9 16 4.9 6 5.5

12 3.1 205 2.4 12 3.2 80 2.8 11 4.2 30 5.2

5 2.5 220 2.3 30 2.7 50 1.9 17 3.5 2 5.1

50 2.4 405 2.3 7 2.5 61 1.8 18 3.5 8 4.2

Total 64.3 31.4 41.3 58.2 56 59.7
8    Preliminary Assessment of Trends in Static Water Levels in Bedrock Wells in New Hampshire, 1984 to 2007 MEAN STATIC WATER LEVEL, IN FEET BELOW LAND SURFACE

20

22

24

26

28

30

32

34

36

38

40

1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008

A

.90

.95

1.00

1.05

1.10

1.15

1.20

1.25

1.30

1.35

1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008

20

22

24

26

28

30

32

34

36

38

40

.900 .950 1.00 1.05 1.10 1.15 1.20 1.25 1.30 1.35

POPULATION, IN MILLIONS

B

C

POPULATION, IN MILLIONS

R 2 = 0.825

R 2

 = 0.663

R 2

 = 0.921

MEAN STATIC WATER LEVEL, 

IN FEET BELOW LAND SURFACE

YEAR

YEAR

Figure 2. Graph showing mean annual static water level in bedrock wells in New Hampshire, 1984 through 

2007; A) mean static water level per year, B) population in New Hampshire, 1984 through 2007; and C) mean 

annual static water level as a function of population.
Static Water Levels in Bedrock Wells in New Hampshire    9

changes in drilling techniques with time, such as faster drilling rates or increased water-lifting capacity, may result in lower 

initial SWLs with no real change in water levels over longer periods. Also, increases in well depths may result in deeper 

SWLs, especially in groundwater-recharge zones, which likely occupy more land area than groundwater-discharge zones in 

New Hampshire. 

Changes in SWL appear to relate to statewide population growth; that is, as population increases, so does the depth to 

SWL (fig. 2C); however, the complexity of bedrock-aquifer hydrology and population demographics creates much uncertainty 

in this relation. Factors such as where the population is distributed on the landscape, water use associated with the population, 

drilling practices, landscape features, specific geological formations, and the highly variable nature of fractured bedrock are all 

suspected of influencing the depth to SWL across New Hampshire.

SWL data were aggregated by year and quarter for the period 1984 to 2007 (24 yr), generating 96 mean aggregated SWL 

values. The smallest number of wells used to compute a mean quarterly SWL was 136, and the largest was 1,182. More than 

90 percent of the mean quarterly values were based on more than 250 wells. Plotting the quarterly aggregated SWL shows that 

SWLs have become deeper with time and also that high and low SWLs have followed a seasonal cycle with generally greater 

depths to water during the summer-month growing season than during the winter nongrowing months (fig. 3). This pattern 

generally corresponds to the cycle of recharge over a year; mean quarterly SWLs in bedrock wells may reflect natural seasonal 

SWL variations. In a study in southeastern New Hampshire, typical bedrock SWLs varied seasonally by about 4 to 5 ft above 

or below annual median values in the absence of withdrawal stresses (Mack, 2009), a pattern that is consistent with observed 

fluctuations in mean quarterly SWLs (fig. 3).

Based on the quarterly mean SWL data, Kendall’s Tau was computed as a test of trend with time (Helsel and others, 2006). 

The test was also done as a seasonal Kendall, specifying two and four seasons. Both tests resulted in strong Tau values (0.747 

and 0.692, respectively) and adjusted p-values of less than 0.001 (table 4). Both show a trend slope of about 0.5 ft/yr (0.2 m/yr) 

per year of increased depth for the mean SWL.

Relations among Static Water Levels, Precipitation, and Groundwater Recharge

The amount, timing, form, and duration of precipitation affect the seasonal amount of groundwater recharge and ultimately 

SWLs. Average annual precipitation patterns from records from three stations in southern New Hampshire are shown on 

figure 4A. Kendall trend tests do not show trends in average annual precipitation over the time period of this study (for Durham, 

Kendall’s tau = 0.019, p = 0.9278; for Portsmouth, Kendall’s tau = -0.038, p = 0.8326; and for Concord, Kendall’s 

tau = 0.148, p = 0.3648). These results indicate that changes in precipitation may not be influencing the trends in SWL.

Estimates or indicators of recharge, however, rather than precipitation, may be better correlated to SWLs. Although 

groundwater recharge was not directly estimated for this study, groundwater-recharge patterns can be inferred from information 

on base flows from streams; base-flow patterns, in turn, can be indicative of patterns in water-table response in aquifers. Studies 

of base flow in the region, however, have noted small but not statistically significant third-quarter base-flow declines (Hodgkins 

and others, 2005). Furthermore, it is possible that shifts in the timing of peak flows in rivers in the region could be indicative of 

hydrologic changes that could affect SWLs (Hodgkins and Dudley, 2006). MEAN STATIC WATER LEVEL, IN FEET BELOW LAND SURFACE

15

20

25

30

35

40

45

50

1984 1986 1988 1990 1992 1994 1996

YEAR

1998 2000 2002 2004 2006 2008

Figure 3. Graph showing mean quarterly static water levels in bedrock wells in New Hampshire, 1984 through 2007.
10    Preliminary Assessment of Trends in Static Water Levels in Bedrock Wells in New Hampshire, 1984 to 2007

Table 4. Summary of trend-test statistics for mean static water level and related well parameters aggregated by year and quarter 

from 1984–2007.

Variable aggregated

by year and quarter

Number

of

years

Number

of

seasons

used in

trend test

Kendall’s Tau Adjusted

p-value

Trend

slope

Water-level data

Static water level 24 4 0.692 < 0.00001 0.4766

Static water level 24 2 0.747 < 0.00001 0.4765

Physical well properties

Total well depth 24 4 0.828 < 0.00001 6.068

Casing length 24 4 0.730 < 0.00001 0.8108

Length of casing in bedrock 24 4 0.894 < 0.00001 0.5996

Reported yield 24 4 0.332 0.0003 0.0841

Mean third-quarter base-flow estimates from Beaver Brook near North Pelham, the Oyster River near Durham, and the 

Soucook River near Concord are shown on figure 4B. Third-quarter values are shown because they are generally lower than 

base flows in other quarters and are representative of low-recharge conditions. If water levels were declining systematically, then 

it is possible that there would be corresponding declines in base flow, but this is not evident in the data shown in figure 4B. 

Kendall trend tests on base-flow data indicate that there are no measurable trends over the time period tested. For Beaver 

Brook, for example, a Kendall trend test on third-quarter base flows indicates no significant trend (Kendall’s tau = -0.057, 

p = 0.7398). Third-quarter data for the Oyster (Kendall’s tau = -0.058, p = 0.7098) and Soucook Rivers (Kendall’s tau = 0.105, 

p = 0.5376) also showed no trend. Kendall trend tests on third-quarter SWLs, however, indicated deepening of SWLs over time 

in the Beaver Brook (Kendall’s tau = 0.351, p = 0.0241) and Oyster River (Kendall’s tau = 0.412, p = 0.0235) Basins but not in 

the Soucook River Basin (Kendall’s tau = 0.052, p = 0.7626). The reason for the lack of similarity in trends of SWL and base 

flows in these three watersheds is unclear. 

Aggregated mean quarterly SWLs regressed against year have a relatively similar slope, but the intercepts for the four 

quarters differ (fig. 4C). The depth to mean SWL is largest (deeper water levels) for quarter 3 and smallest for quarter 1. These 

regression lines indicate that, whereas the trend with time (slope) is the same for each quarter, the magnitude of the effect 

varies by season. This result implies that the season when a well is drilled may be a significant explanatory factor for variation 

in SWLs.

Mean quarterly precipitation in the three watersheds in southern New Hampshire did not vary over time for quarters 2, 

3, and 4 but generally was lowest in quarter 1 (fig. 5A). Base-flow estimates and SWLs across the state do vary by season, 

however. Boxplots of the distributions of base flow by quarter (data only for the Oyster River are shown) show that recharge 

was lowest in quarter 3 and greatest in quarters 1 and 2 (fig. 5B). Correspondingly, mean SWLs were deepest in quarter 3 and 

shallowest in quarter 1 (fig. 5C). This shows that SWLs are deepest primarily during periods of low recharge. 

Relation of Static Water Levels to Well-Construction Parameters

Mean quarterly SWLs in bedrock wells were increasing (becoming deeper) over time, as were many other well parameters 

for the period 1984 to 2007. Previous studies found that well depths in New Hampshire also have been increasing with time 

(Chormann, 1990; Drew and others, 2001; Moore and others, 2002). The increase in well depth, in at least one study, has been 

attributed to increasing demand (Moore and others, 2002), which was met in part by increases in borehole storage provided by 

deeper wells. Between 1984 and 2007, the average depth of bedrock wells in the database increased by approximately 140 ft 

(43 m) (fig. 6A). In addition to increases in water demand, however, other factors also could explain the apparent increase 

in depth. These factors include improved drilling techniques, faster drilling equipment, and a desire for increased protection 

against wells going dry during droughts or periods of high-intensity use. 
Relation of Static Water Levels to Well-Construction Parameters    11

15

20

25

30

35

40

45

50

1984 1986 1988 1990 1992 1994 1996

YEAR

1998 2000 2002 2004 2006 2008

Mean SWL = -1026 + .526 * year; R-squared = .674 (quarter 1)

Mean SWL = -960 + .494 * year; R-squared = .733 (quarter 4)

Mean SWL = -1115+ .572 * year; R-squared = .640 (quarter 3)

Mean SWL = -959 + .494 * year; R-squared = .739 (quarter 2)

1

4

3

2

PRECIPITATION, IN INCHES

20

25

30

35

40

45

50

55

60

1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008

Portsmouth

Durham

Concord

A

.1

1

10

1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008

Soucook River

Oyster River

Beaver Brook

B

C

MEAN STATIC WATER LEVEL, 

IN METERS BELOW LAND SURFACE THIRD-QUATER BASE FLOW, IN INCHES

Figure 4. Graphs showing A) Mean annual precipitation at Portsmouth, Durham, and Concord, New Hampshire, 1984–2005; 

B) third-quarter base flow at Beaver Brook, Oyster River, and Soucook River; and C) mean quarterly static water levels, 

1984–2007.
12    Preliminary Assessment of Trends in Static Water Levels in Bedrock Wells in New Hampshire, 1984 to 2007

0

2

4

6

8

10

12

14

16

18

20

QUARTERLY PRECIPITATION, 

IN INCHES

A

0

1

2

3

4

5

6

7

8

9

18

20

22

24

26

28

30

32

34

 1 

JAN.−MAR.

 2

 APRIL−JUNE

 3

 JULY−SEPT.

 4

 OCT.−DEC.

EXPLANATION

75th percentile

Median

25th percentile

90th percentile

10th percentile

B

C

QUARTERLY BASE FLOW, 

IN INCHES

MEAN QUARTERLY STATIC WATER LEVEL, 

IN FEET BELOW LAND SURFACE

Figure 5. Boxplots summarizing A) quarterly 

precipitation at Concord Municipal Airport; 

B) quarterly base flow at Oyster River, near 

Durham, NH (01073000); and C) mean quarterly 

static water level statewide by quarter, 

1984− 2007.
Relation of Static Water Levels to Well-Construction Parameters    13 MEAN CASING LENGTH IN BEDROCK, IN FEET

MEAN OF VARIABLE, 

IN FEET

MEAN TOTAL WELL DEPTH, 

IN FEET BELOW LAND SURFACE

10

20

30

40

50

60

70

1984 1986 1988 1990 1992 1994 1996

YEAR

1998 2000 2002 2004 2006 2008

Mean bedrock depth, in feet below land surface

Mean length of casing in bedrock, in feet

Mean casing length, in feet

Mean bedrock depth = -314.194 + .174 * year and quarter; R-squared = .181

Mean length of casing in bedrock = -1218.721 + .621 * year and quarter; R-squared = .928

Mean casing length = -1532.915 + .795 * year and quarter; R-squared = .788

260

280

300

320

340

360

380

400

420

440

460

1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008

Mean total depth = -11570.564 + 5.976 * year and quarter; R-squared = .909

MEAN TOTAL DEPTH, IN

FEET BELOW LAND SURFACE

B

12

14

16

18

20

22

24

26

28

30

32

260 280 300 320 340 360 380 400 420 440 460

Mean length of casing in bedrock = 

-14.202 + .097 * mean total depth;

R-squared = .882

10

100

1,000

15 20 25 30 35 40 45 50

EXPLANATION

Mean total depth, in feet below land surface

Mean length of casing in bedrock, in feet

Mean total depth = 159.385 + 7.558 * mean SWL; 

R-squared = .638

Mean length of casing in bedrock = .29 + .763 * mean SWL; 

R-squared = .616

MEAN STATIC WATER LEVEL (SWL), 

IN FEET BELOW LAND SURFACE

EXPLANATION

A

C D

MEAN OF VARIABLE, 

IN FEET

Figure 6. Graphs showing A) mean total well depth by year and quarter; B) mean casing length, mean length of 

casing in bedrock, and mean bedrock depth by year and quarter; C) mean total well depth and mean length of casing 

in bedrock as a function of mean static water level; and D) mean length of casing in bedrock as a function of mean 

total well depth.
14    Preliminary Assessment of Trends in Static Water Levels in Bedrock Wells in New Hampshire, 1984 to 2007

Total Depth, Casing Length, and Length of Casing in Bedrock

Total depth, casing length, and casing length in the bedrock show strong trends with time. The slopes of these trends 

indicate that mean well depths increased at about 6 ft/yr (2 m/yr), and casing length and casing length in bedrock increased by 

about 0.8 ft/yr (0.24 m/yr) and 0.6 ft/yr (0.18 m/yr), respectively (table 4). Total depth, casing length, and length of casing in 

bedrock were correlated with each other (table 5). SWL also was correlated strongly with these well-construction factors 

(rho = 0.83 to 0.86, p < 0.0001) and with year measured, indicating the possibility that any of these factors could explain the 

apparent deepening of SWLs (table 5). The length of casing in bedrock has increased, although the regulatory casing-length 

requirement did not change during the study period. Improved awareness that additional casing in bedrock may help to protect 

well water from potential surface contaminants, as well as driller-education programs, may be partly responsible for the increase 

in casing length (Richard Schofield, New Hampshire Department of Environmental Services, oral commun., 2008).

Graphs of the well-construction data provide additional information about the relations among these variables. The lengths 

of casing and casing in bedrock increased significantly over the study period (fig. 6B); however, the mean bedrock depth, 

which is equivalent to the length of casing minus the length of casing in bedrock, has increased only slightly (fig. 6B). This 

comparison indicates that the apparent increases in casing length over time were primarily a result of a desire to increase the 

length of casing in bedrock. Mean total well depth has also increased substantially over time (fig. 6A). The combination of 

potentially lower heads at deeper aquifer depths coupled with a potentially diminishing proportion of water from overburden and 

near-surface fractures (as a result of a proportionally greater length of casing in bedrock) may result in deeper SWLs in bedrock 

wells. Mean total depth and mean length of casing length in bedrock are strongly related to mean SWL (fig. 6C). That both of 

Table 5. Spearman rank correlation coefficients for mean static water level and means of selected physical and hydraulic 

parameters by year and quarter, 1984–2007 (n = 96).

[Elapsed time is the time between completion of the well and measurement of the static water level. < less than; --, not applicable]

Mean

of

variable

Statistic Year

measured

Total

depth

Casing

length

Length of

casing

in rock

Yield,

reported

Static

water

level

Elapsed

time

Year measured Rho 1 0.9502 0.8688 0.9765 0.4929 0.8397 0.2951

p-value -- < 0.0001 < 0.0001 < 0.0001 < 0.0001 < 0.0001 0.0035

Total depth Rho 0.9502 1 0.8839 0.9436 0.4780 0.8639 0.2747

p-value < 0.0001 -- < 0.0001 < 0.0001 < 0.0001 < 0.0001 0.0068

Casing length Rho 0.8688 0.8839 1 0.8941 0.3799 0.8358 0.2614

p-value < 0.0001 < 0.0001 -- < 0.0001 0.0004 < 0.0001 0.0101

Length of casing in rock Rho 0.9765 0.9436 0.8941 1 0.4617 0.8290 0.2931

p-value < 0.0001 < 0.0001 < 0.0001 -- < 0.0001 < 0.0001 0.0038

Reported yield, Rho 0.4929 0.4780 0.3799 0.4617 1 0.5063 0.1051

p-value < 0.0001 < 0.0001 0.0004 < 0.0001 -- < 0.0001 0.3083

Static water level Rho 0.8397 0.8639 0.8358 0.8290 0.5063 1 0.2645

p-value < 0.0001 < 0.0001 < 0.0001 < 0.0001 < 0.0001 -- 0.0092

Elapsed time Rho 0.2951 0.2747 0.2614 0.2931 0.1051 0.2645 1

p-value 0.0035 0.0068 0.0101 0.0038 0.3083 0.0092 --
Relation of Static Water Levels to Well-Construction Parameters    15

these factors are increasing over time indicates that they could potentially be responsible for the apparent concurrent deepening 

of SWL. Thus, in this analysis, well-construction variables function as variables related to time. One difficulty, however, in 

assessing the relative effect of these variables on SWL is that the variables themselves are strongly correlated (illustrated by an 

example in fig. 6D). Thus it is possible that either factor or both could contribute to the observed trend in SWLs. 

Whereas SWLs have become deeper over time, the mean total well depth also has increased over time. Mean total well 

depth increased by about 140 ft (43 m) from 1984 to 2007 (fig. 6A) and the mean depth to SWL increased by about 13 ft (4 m) 

(fig. 2A). The net result is that the length of the water column in bedrock wells also has increased, leaving well owners with, 

on average, about 130 ft (40 m) more water (fig. 7), or about 200 gal (750 L) in a 6-in.-diameter (0.15-m) bedrock well under 

static (nonpumping) conditions. The amount of water in the borehole (wellbore storage) may not be a significant concern for 

high-yielding wells, but for wells with low yields (especially relative to common domestic-well pumping rates), the amount 

of the additional water in borehole storage is potentially significant; more water can be used for domestic purposes with a 

lower probability that the well might go dry. In addition, more water may be used because it is available, possibly adding to 

the problem of local well interference—where adjacent wells influence the availability of water to the well—or exacerbating 

drought-related well problems.

The length of casing in bedrock and the type of casing seal may limit the connectivity of the bedrock aquifer with the 

overburden aquifer. Casings seals can be formed by installing a drive shoe on the end of the casing and hammering the casing 

a few feet into the bedrock borehole. The void area outside the casing can be filled with cement, bentonite grout, or cuttings 

generated by the drilling process. Grout seals are required for wells that do not conform to siting requirements (R. Schofield, 

New Hampshire Department of Environmental Services, oral commun., 2010). The use of cement or bentonite grout may 

provide added protection against water entering the well from unconsolidated materials above the bedrock. Grout seals could 

have an effect on water levels in wells if they sealed out unconsolidated aquifer water from the bedrock well and reduced the 

hydraulic connection between the unconsolidated aquifer and the bedrock aquifer. Consistent reporting of grout seals appears 

in the WWI database by about 1999; as a result, analyses of the effects of grout on SWLs excluded data added prior to 1999. 

Correlations between SWLs for wells with grout seals and well-construction parameters are poorer than the correlations between 

SWLs for wells without grout seals and the same parameters (table 6). This result may imply that hydraulic connections between 

the bedrock and overburden aquifers are minimized by a grouted seal; conversely, the absence of a grout seal may allow better 

hydraulic connection between the bedrock and overburden. The lack of a correlation between SWLs and elapsed time (time 

elapsed between well construction and SWL measurement), particularly for wells without grouted seals, may be a further 

indication of hydraulic connection with the overburden flow system. 

240

260

280

300

320

340

360

380

400

420

1984 1986 1988 1990 1992 1994 1996

YEAR

1998 2000 2002 2004 2006 2008

R-squared = .939

MEAN LENGTH OF WATER 

COLUMN, IN FEET

Figure 7. Graphs showing mean length of water column in bedrock wells in New Hampshire, 1984 through 2007
16    Preliminary Assessment of Trends in Static Water Levels in Bedrock Wells in New Hampshire, 1984 to 2007

Table 6. Correlation of mean static water level with year measured, mean total depth, casing length, length of casing in bedrock, 

elapsed time, and yield, for grouted and nongrouted wells by year and quarter, 1999–2007 (n = 36).

 [Elapsed time is the time between completion of the well and measurement of the static water level]

Mean static

water level

Mean of

variable,

by year and

quarter

Year Total

depth

Casing

length

Length of

casing in

bedrock

Elapsed

time Yield

Grouted Rho 0.4733 0.2013 0.3346 0.4834 0.2489 0.2265

p-value 0.0036 0.2391 0.0461 0.0028 0.1432 0.1840

Nongrouted Rho 0.5323 0.4420 0.5493 0.5076 0.1115 0.3341

p-value 0.0008 0.0070 0.0005 0.0016 0.5175 0.0464

Elapsed Time and Yield

The SWL data were assessed to determine if depth to SWL may be influenced by time between well construction and 

measurement of the SWL (elapsed time). During the construction of a well, water is added or removed from the well as a 

result of the drilling process. The depth to SWL can change after drilling as the well becomes equilibrated to natural waterlevel conditions in the aquifer. The time required to reach equilibrium depends strongly on well hydraulics. Most (more than 

80 percent) of the SWLs in the NHDES database were measured within 3 days of well completion, with more than 98 percent 

measured within 30 days of well completion. Analysis of subsets of SWLs defined by ranges of elapsed time revealed 

differences in the strengths of correlation coefficients between SWL and other variables. Elapsed time was categorized as 0 

to 3 days and 3 to 30 days, and boxplots of the year-and-quarter-aggregated data show that there are differences between the 

distributions of data for several parameters. SWLs are generally deeper in wells with larger elapsed times between construction 

and SWL measurement (fig. 8A) as well as with total depth, casing length, and bedrock depth (figs. 8B, C, and E), although 

the mean length of casing in bedrock is not significantly different (fig. 8D). Wells with larger elapsed times were more likely to 

be deeper and have lower yields (fig. 8F). The combination of deeper wells and lower yields in the longer elapsed-time group 

indicates that SWLs can be lower than expected for deep low-yielding wells. 

Correlation coefficients for SWL and selected parameters for the two categories of elapsed time shown in table 7 indicate 

that the correlation between SWL and most variables decreases with greater elapsed time. Although mean SWL remains 

correlated with year for the 3-to-30-day elapsed-time category, the strength of the correlation is weaker than the correlation 

between SWL and year for the 0-to-3-day elapsed-time category. Also noteworthy is the reduction in the magnitude of the 

correlation coefficient with casing length and yield. This can be interpreted to mean that wells with longer elapsed times also 

are low-yield wells and that SWLs need long recovery times in order for the SWL to be representative.

Hillslope Effects

The position of a well relative to the topography of the surrounding land can influence the SWL in a well. A simplified 

metric was used to indicate the position of each well with respect to surrounding topography in order to assess hillslope effects. 

By using data from 24,000-scale DEMs (100-ft (30-m) grid spacing) (U.S. Geological Survey, 2004), the elevation of the well 

and the minimum elevation of the land surface within a 1,640-ft (500-m) radius around the well was determined. These data 

were used to compute the height of the well above that minimum elevation, termed height above valley bottom (HAVB). The 

median HAVB of all statewide data was about 66 ft (20 m), and the 25th- and 75th- percentile values were about 33 ft (10 m) 

and 100 ft (30 m), respectively. For the analysis of well factors shown in fig. 9, the data for HAVB were divided into categories 

of less than 66 ft (20 m) and greater than or equal to 66 ft. 

Mean SWL and mean total well depth were significantly deeper in wells with a HAVB greater than or equal to 66 ft (20 m) 

than in wells in areas of lower relief (HAVB less than 66 ft (20 m)) (fig. 9A, B). Mean values for casing length, length of casing 

in bedrock, and bedrock depth, however, were not different for the two HAVB groups (figs. 9C, D, and E). Mean well yield was 

significantly less (fig. 9F) in the higher HAVB category.
Relation of Static Water Levels to Well-Construction Parameters    17

MEAN BEDROCK DEPTH,

IN FEET

MEAN CASING LENGTH,

IN FEET

MEAN STATIC WATER LEVEL,

IN FEET BELOW LAND SURFACE

MEAN TOTAL DEPTH,

IN FEET

MEAN LENGTH OF CASING

IN BEDROCK, IN FEET

MEAN YIELD, IN GALLONS

PER MINUTE

A

EXPLANATION

Wilcoxon 2-sample test p-value = < 0.0001

Wilcoxon 2-sample test p-value = 0.0054 Wilcoxon 2-sample test p-value = 0.6867

Wilcoxon 2-sample test p-value = 0.0036 Wilcoxon 2-sample test p-value = < 0.0001

10

20

30

40

50

60

Wilcoxon 2-sample test p-value = 0.0034

250

300

350

400

450

500

550

30

40

50

60

70

80

10

20

30

40

20

30

40

50

60

0

10

20

30

Greater than 3 to 30 days between construction 

and static water-level measurement 

Less than 3 days between construction and 

static water-level measurement 75th percentile

Median

25th percentile

90th percentile

10th percentile

B

C D

E F

Figure 8. Boxplots summarizing A) mean static water level, B) mean total well depth, C) mean casing length, 

D) mean length of casing in bedrock, E) mean bedrock depth, and F) mean reported yield, for categories of 

elapsed time between well construction and static water-level measurement.
18    Preliminary Assessment of Trends in Static Water Levels in Bedrock Wells in New Hampshire, 1984 to 2007

Table 7.  Correlation of mean static water level with year measured, mean total depth, casing length, length of casing in bedrock, 

elapsed time, and yield for categories of elapsed time between construction and measurement of static water level; aggregated by 

year and quarter, 1984–2007 (n = 96). 

[The number of wells before aggregation was 46,184 for 0 to 3 days (d) and 9,019 for 3 to 30 d. N for correlates is variable; elapsed time is the time between 

completion of the well and measurement of the static water level. <, less than]

Mean 

water 

static 

level

Mean of 

variable, 

by year and 

quarter

Year Total depth Casing length

Length of 

casing in 

bedrock

Elapsed time Yield

0 to 3 d Rho 0.8050 0.8262 0.8082 0.7932 0.4214 0.5427

p-value < 0.0001 < 0.0001 < 0.0001 < 0.0001 < 0.0001 < 0.0001

3 to 30 d Rho 0.5688 0.6571 0.3204 0.6177 - 0.3427 0.1639

p-value < 0.0001 < 0.0001 0.0015 < 0.0001 < 0.0006 0.1106

These results indicate that for the wells on higher, steeper, or more irregular hillslopes, SWLs have a greater likelihood 

of being significantly deeper than their lower-HAVB counterparts. The corresponding lower yields for these wells may mean 

a reduced capacity to recover after pumping and a greater susceptibility to drought conditions than wells with lower values 

of HAVB. It is possible that drilling high-HAVB wells even deeper might reduce the potential for problems associated with 

drought or high-use periods. 

Hillslope position data indicate that there may be a trend with time; for example, there are observable short-term increases 

in the magnitudes of these factors followed by declines and subsequent increases from about 1995 to 2007. To illustrate 

this, mean elevation, mean slope, and mean HAVB are shown as functions of time for the periods 1984 through 1995 and 

1995 through 2007 (fig. 10). These graphs indicate that all three factors are increasing over time for the latter period of data 

(1995–2007). In general, there is an inverse trend with time in the first half of the data (1984–1994), although the relations 

are generally weaker and less significant than the positive relations in the latter half of the data (fig. 10). These observations 

indicate that, similar to well depth and length of casing in bedrock, hillslope factors are also time dependent. In this way, many 

of the physical well factors are surrogates for time and are thus, in part, trend variables. It is not clear, however, which variables 

are controlling the increase in depth to SWLs. 

Multiple Regression Analysis of Static Water Levels

Multiple regression analysis was used to examine the relative influence of numerous variables on aggregated SWL data 

statewide. The dependent variable was mean of the log of SWL by year and quarter. Independent variables consisted of all 

physical information about the wells (table 1) and data derived from GIS variables, including precipitation, recharge, digital 

elevation model and its derivative information, seasonal indicators, and geologic variables. Several models were developed, 

initially by stepwise regression methods, and then manually. 

The aggregated SWL data were first stratified by major geologic type (igneous or metamorphic rock) because Wilcoxon 

tests indicated that there were significant differences between the distributions of the SWL data by these major geologic types 

(table 8). Most SWL and well-construction parameters were greater in magnitude for the igneous-rock wells than for the 

metamorphic-rock wells. Multiple regression models were then run separately for wells in igneous and metamorphic rocks to 

determine the independent variables and parameter estimates by major rock type (table 9). 

Standardized parameter estimates also were calculated for the multiple regression models. Standardized estimates for a 

variable indicate the effect of change of one standard deviation in that variable and thus can be used to compare the relative 

effects of the variables (Menard, 2002). 

Mean total depth was strongly related to mean log SWL in both models (table 9); both measures indicated increasing depth 

over time. This result is consistent with common hydrologic conditions in aquifers in recharge areas where water in the upper 

aquifer flows toward deeper parts of the aquifer in response to hydraulic gradient. In order for recharge to occur, hydraulic 

head (indicated by water level) must be lower in deeper parts of the aquifer than in shallow parts. Thus, one explanation for 
Multiple Regression Analysis of Static Water Levels    19

Greater than or equal to 66 feet (20 meters) above minimum elevation

Less than 66 feet (20 meters) above minimum elevation

Height of land surface at well, above minimum 

elevation within a 1,640-foot (500-meter) radius of the well

Wilcoxon 2-sample test p-value < 0.0001 Wilcoxon 2-sample test p-value = < 0.0001

Wilcoxon 2-sample test p-value = 0.1882 Wilcoxon 2-sample test p-value = 0.4799

Wilcoxon 2-sample test p-value = 0.2050 Wilcoxon 2-sample test p-value = < 0.0001

10

20

30

40

50

60

200

250

300

350

400

450

500

20

30

40

50

60

70

80

10

20

30

40

10

20

30

40

50

0

10

20

30

40

EXPLANATION

A B

C D

E F

MEAN BEDROCK DEPTH,

IN FEET

MEAN CASING LENGTH,

IN FEET

MEAN STATIC WATER LEVEL,

IN FEET BELOW LAND SURFACE

MEAN TOTAL DEPTH,

IN FEET

MEAN LENGTH OF CASING

IN BEDROCK, IN FEET

MEAN YIELD, IN GALLONS

PER MINUTE

75th percentile

Median

25th percentile

90th percentile

10th percentile

Figure 9. Boxplots summarizing A) mean static water level, B) mean total well depth, C) mean casing 

length, D) mean length of casing in bedrock, E) mean bedrock depth, and F) mean reported yield, for 

categories of height above the minimum elevation within a 1,640-foot (500-meter) radius.
20    Preliminary Assessment of Trends in Static Water Levels in Bedrock Wells in New Hampshire, 1984 to 2007 MEAN ELEVATION, IN FEET ABOVE NGVD88 MEAN SLOPE MEAN HAVB, IN FEET

14

16

18

20

22

24

26

28

1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008

1995–2007

1984–1995

Mean HAVB = 322.011 - .152 * year and quarter; 

R-squared = .076 (1984–1995)

Mean HAVB = -1049.178 + .535 * year and quarter; 

R-squared = .754 (1995–2007)

2.5

3

3.5

4

4.5

5

1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008

Mean slope= 115.784 - .056 * year and quarter; 

R-squared = .299 (1984–1995)

Mean slope= -132.526 + .068 * year and quarter; 

R-squared = .540 (1995–2007)

200

300

400

500

600

700

800

900

1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008

Mean elevation = -43532.385 + 21.977 * year and quarter; 

R-squared = .598 (1995–2007) Mean elevaton = 37508.081 - 18.612 * year and quarter; 

R-squared = .506 (1984–1995)

EXPLANATION

YEAR

Figure 10. Graphs showing mean elevation of well, mean slope at the well, and mean height above minimum 

elevation within 1,640-foot (500-meter) radius of well (HAVB) by year and quarter, 1984−2007. 
Multiple Regression Analysis of Static Water Levels    21

Table 8. Comparison of mean quarterly values of selected variables for wells in igneous and 

metamorphic rocks.

[The letter A under Major rock group indicates that the distribution of the data for that variable is greater in magnitude than 

if it has the letter B; p-value indicates significance at the 95-percent confidence interval]

Variable

Major rock group p-value

two-sample

test Igneous Metamorphic

Static water level A B < 0.0001

Total depth A B < 0.0001

Bedrock depth A B 0.0001

Casing length A B 0.0015

Casing length in bedrock A A 0.1535

Yield B A 0.0066

Curvature (rate of change of slope) A B 0.0474

Slope A B < 0.0001

Height above minimum elevation 

within a 1,640-foot (500-meter) 

radius of well

A B < 0.0001

Elevation A B < 0.0001

Table 9. Multiple regression models on the means of logarithms of static water levels by major rock type in New Hampshire.

[R2, adjusted values of coefficient of determination; Dim., dimensionless; <, less than; --, not applicable; p-value indicates significance at the 95-percent 

confidence interval]

Adjusted

R2 Variable Units Mean Range Parameter

estimate

Standard

error

Standardized

parameter

estimate

p-value

Igneous rocks

0.5472 Intercept -- -- -- 2.14 0.1233 0 < 0.0001

Mean total depth Feet 378.00 274–492 0.0012 0.000366 0.3644 0.0015

Third quarter Binary -- -- 0.8284 0.02698 0.2185 0.0028

Mean elevation Feet 515.00 331–780 -0.0004856 0.000133 -0.31501 0.0004

Mean height above minimum 

elevation within a 1,640-foot 

(500-meter) radius of well

Feet 22.90 17.2–29.5 0.01761 0.00661 0.2435 0.0091

Mean casing length Feet 54.00 35–73 0.00429 0.00199 0.22403 0.0337

Metamorphic rocks

0.6309 Intercept -- -- -- 1.99506 0.08508 0 < 0.001

Mean total depth Feet 378.00 274–492 0.00199 0.000229 0.63479 < 0.001

Third quarter Binary -- -- 0.09375 0.02165 0.27159 < 0.001

Mean elevation Feet 515.00 331–780 -0.0002609 0.000112 -0.19943 0.0221

Mean height above minimum 

elevation within a 1,640-foot 

(500-meter) radius of well

Feet 22.90 17.2–29.5 0.01445 0.00528 0.26548 0.0074

Mean curvature Dim. 0.04 -0.0478–

0.1327

0.66998 0.3057 0.14079 0.031
22    Preliminary Assessment of Trends in Static Water Levels in Bedrock Wells in New Hampshire, 1984 to 2007

the relation is that, as well depth increases, the likelihood of encountering deeper water levels also increases. Variations in 

vertical flow gradients calculated by groundwater-flow models for bedrock aquifers in coastal New Hampshire indicate that 

gradients may not be sufficiently large to explain the SWL declines observed in this study (Mack, 2009); however, vertical 

gradients derived from flow models are not generally representative of gradients at individual wells. Another explanation is that 

because SWLs in wells are limited by the depth of the well (measured SWLs cannot exceed the well depth), deeper SWLs are 

increasingly possible because wells have become deeper over time.

Season (third quarter) was also a significant variable in both models. Quarter 3, which corresponds to July through 

September, was associated with deeper water levels. Recharge is also at its lowest magnitude at this time (fig. 5A), probably 

owing to maximum evapotranspiration during the summer growing season. Thus, low-recharge periods are related to 

deeper SWLs. 

As previously noted, larger HAVB values were related to deeper SWLs in wells. Mean elevation was a significant 

predictor of mean SWL in both igneous and metamorphic rocks, and, along with HAVB, may account for the general effects of 

topography and hillslope position. The elevation variable has a negative coefficient and may be reflective of higher precipitation 

with higher elevations. 

To determine if the statewide models reflect the general character of potential controlling factors, models were generated 

for each county in the state. The results for county-level models (not shown) were similar to those of the statewide models—

that is, mean total depth is the primary regressor. For the county models, season and hillslope position were also related to SWL, 

indicating that the statewide models capture the nature of the controls on SWL.

Local-Scale Factors

Much of the analysis presented has focused on the relation of SWLs to statewide, generalized explanatory variables. It 

is likely, however, that finer scale variation in these factors (particularly local geology, local topography, local hydraulics, and 

density of wells in an area) may have an effect on SWLs in a particular area. The finer scale variables include more specific 

categories of bedrock type, landscape features, known groundwater-supply-problem areas, and areas where well replacement or 

deepening has occurred. 

Local-Scale Geology

The models assessing SWLs described above were stratified by major bedrock geology groups (igneous and metamorphic) 

(table 9); however, it is possible that further refinement of the models to predict mean log SWL based on different geologic 

variables could be useful. A cursory analysis was done relating SWL data to the lithologic group in which each well is located. 

The lithologic group is a geologic variable representing differences in lithotectonic properties within the major geologic groups 

(Robinson and Kapo, 2003). The distributions of the data for mean quarterly SWL, total well depth, and length of casing in 

bedrock are shown by lithologic group and indicate that there may be significant differences between the mean log SWLs 

of some groups (fig. 11). For example, major differences can be seen among the lithologic groups that include granites; the 

alkali granites have lower SWLs than any other granite group. Wells in alkali granites, however, also have deeper overall 

well depths and longer casings in bedrock than wells in other rock types, indicating that the bedrock type itself may not be the 

only controlling factor. Differences between the mean log SWLs of metamorphic-rock groups, which include the calcpelite, 

pelitic rocks, and sulfidic schists, appear to be subtle. Thus, local-scale variation in SWLs can be expected in different bedrock 

formations. Future efforts to examine SWL variability by geology would likely be improved by a more rigorous examination of 

bedrock geologic data.

Static Water Levels in Areas with Known Groundwater-Supply Concerns

In some areas of the state and, specifically, in more densely developed towns, clusters of wells, commonly within the same 

geologic formation, have been reported to have deep SWLs and (or) limited yields (B. Kernen, New Hampshire Department 

of Environmental Services, written commun., 2010). In areas characterized by low-yield or deep-SWL wells, obtaining an 

adequate, reliable water supply can be problematic. Most of these areas are in the southern part of the state, where population 

pressures and demand for water are most intense. Towns in which water supply in specific areas has been reported to be limited 

include Derry, Plaistow, Pelham, Kingston, Bedford, and Windham. The limitations of the water supplies in these towns has 
Local-Scale Factors    23

10

100

MEAN STATIC WATER LEVEL,

IN FEET BELOW LAND SURFACE

100

1,000

MEAN TOTAL WELL DEPTH,

IN FEET

10

100

MEAN LENGTH OF CASING

IN BEDROCK, IN FEET

Alkali granite

Calcgranofels

Calcpelite

Felsic volcanics

Granite, other

Mafic rocks

Metamorphic rocks, other

Pelitic rocks

Peraluminous granite

Sulfidic schists

A

B

C

75th percentile

Median

25th percentile

90th percentile

10th percentile

EXPLANATION

Figure 11. Boxplots summarizing A) mean quarterly static water level, B) mean total well 

depth, and C) mean length of casing in bedrock for major lithologic groups in New Hampshire 

(groups from Robinson and Kapo, 2003).
24    Preliminary Assessment of Trends in Static Water Levels in Bedrock Wells in New Hampshire, 1984 to 2007

prompted concern about the possibilities of local-to-regional water-level declines and pumping-well interference (converging 

contributing areas or capture zones). In some of these towns, rates of increase (deepening) of the mean SWL are more than 

twice that of the statewide rate of about 0.5 ft/yr (0.15 m/yr). Unaggregated water-level data from individual wells in these six 

towns were used to examine relations of the mean SWL to possible controlling factors. 

As indicated by the statewide multiple regression models, mean SWL is deeper for wells higher on hillslopes relative to 

nearby low elevations (within 1,640 ft (500 m)) than for wells at lower elevations relative to the surrounding area. For this 

local analysis, individual wells were grouped into categories of HAVB and aspect. HAVB categories were less than 100 ft 

(30 m) HAVB and greater than or equal to 100 ft (30 m) HAVB, which represents the 75th percentile of the statewide values. 

Aspect indicates the azimuthal direction of the sloping face of the land surface, where north refers to greater than or equal to 

300 degrees to less than or equal to 60 degrees. South refers to greater than 60 degrees to less than 300 degrees. In general, 

for wells that were categorized as less than 100 ft (30 m) HAVB, there was no notable difference in the mean SWLs; however, 

SWLs in wells in the category of more than 100 ft (30 m) HAVB were deeper on dominantly south-facing hillslopes than on 

dominantly north-facing hillslopes (fig. 12). These relations were most pronounced for wells in Pelham, where the high-relief, 

south-facing wells had a mean SWL of 58.4 ft (17.8 m) compared to 40.5 ft (12.3 m) for the north-facing wells and less than 

30 ft (9.1 m) for either aspect category of the low-relief wells (fig. 12A). The same was true in Windham, where the mean SWL

in the high-relief south-facing wells was at least 10 ft (3 m) greater than in any other category (fig. 12B). SWLs in Bedford 

(fig. 12C) and Goffstown (fig. 12D) showed similar trends; however, there were too few wells for this analysis for Kingston 

(fig. 12E) and Plaistow (fig. 12F). 

Slope in the southerly direction is commonly steeper than the slope in the northerly direction, possibly causing SWLs 

to be deeper. This is consistent with landforms associated with glaciation in the region, where slopes are more gradual in the 

direction from which the glaciers advanced (generally the northwest) and steeper in the down-ice direction (generally southeast) 

(Flanagan and others, 1999). Another hypothesis is that the southern slopes have higher evapotranspiration rates, reducing 

recharge and leading to deeper SWLs. Other factors, such as aspect, slope-dependent overburden thickness, differential flow in 

unconsolidated and bedrock aquifers, or combinations of factors may act in concert to affect SWLs. 

Static Water Levels in Deepened and Replacement Wells

Wells throughout the state are occasionally replaced or deepened, commonly in response to a need for adequate or 

additional water supply. Characteristics of these wells may provide additional insight into how or why mean SWLs vary. The 

locations of the replacement and deepened wells from the WWI database are shown in fig. 13 and are a subset consisting 

of 3,519 wells that include 115 wells installed for additional supply or for increased well depth and 3,404 wells to replace a 

supply well (commonly a shallow dug well). Both replacement and deepened wells were installed across much of the state and 

commonly in the same areas (fig. 13).

The deepened and replacement wells were aggregated by year and quarter, yielding 96 mean values for new and 

replacement wells and 56 for deepened wells. The other wells (identified as new wells) in the WWI database (17,174) are 

included on the graphs for comparison purposes. Mean depth to SWL in the deepened wells is greater than in the replacement 

and all new wells (fig. 14A). Also, the mean total depth of well is greater in the deepened wells (fig. 14B). This result is 

consistent with the result that well depth is a significant control on SWL. The reason for this is unclear, but may be related to 

lower heads and yields in deeper wells (in recharge zones). Additional information can be drawn from data on elevation and 

local relief (represented by HAVB). For example, there is no significant difference in the mean elevations of these wells among 

the three well categories (fig. 14C), indicating that this variable is not a potential factor in explaining SWL differences. The 

mean HAVB, however, is significantly larger for wells that were deepened or drilled for additional yield (fig. 14D). This further 

indicates that local relief, as described for other analyses in this report, may play an important role in controlling depth to SWL.
Local-Scale Factors    25

0

10

20

30

40

50

60

70

< 30, S < 30, N ≥ 30, S ≥ 30, N

C Bedford

0

10

20

30

40

50

60

70 A Pelham

0

10

20

30

40

50

60

70

MEAN STATIC WATER LEVEL, IN FEET BELOW LAND SURFACE

B Windham

0

10

20

30

40

50

60

70

E Kingston

0

10

20

30

40

50

60

70

F Plaistow

0

10

20

30

40

50

60

70

D Goffstown

137 47

93

25

550

188

243

68

52

17

1

0

64 27

5

0

568

207

100

39

542

231

156

54

< 30, S < 30, N ≥ 30, S ≥ 30, N

< 30, S < 30, N ≥ 30, S ≥ 30, N < 30, S < 30, N ≥ 30, S ≥ 30, N

< 30, S < 30, N ≥ 30, S ≥ 30, N

< 30, S < 30, N ≥ 30, S ≥ 30, N

75th percentile

Median

25th percentile

90th percentile

Number of samples

10th percentile

EXPLANATION

64

Figure 12. Graphs showing relation of mean static water level to binary categories of height of well above minimum elevation 

within a 1,640-foot (500-meter) radius of well (< 100 feet (30 meters) and ≥ 100 feet (30 meters)) and aspect (N refers to ≥ 300 

degrees and ≤ 60 degrees; S refers to > 60 degrees and < 300 degrees), by town.
26    Preliminary Assessment of Trends in Static Water Levels in Bedrock Wells in New Hampshire, 1984 to 2007

EXPLANATION

Replacement well

Town boundaries

County boundaries

Deepened well

Atlantic Ocean

0 20 40 60 MILES

0 20 40 60 KILOMETERS

VERMONT

MAINE

CANADA

MASSACHUSETTS

44 ̊

72 ̊

71 ̊

45 ̊

43 ̊

Coos

Grafton

Carroll

Sullivan

Cheshire

Hillsborough

Merrimack

Belknap

Rockingham

Strafford

Coos

Grafton

Carroll

Sullivan

Cheshire

Hillsborough

Merrimack

Belknap

Rockingham

Strafford

Base from USGS and NH GRANIT

GIS digital data sources.

Figure 13. Map showing locations of wells reported as replacement wells (black circles) or deepened wells 

(green triangles) in New Hampshire, 1984−2007.
Local-Scale Factors    27

200

300

400

500

600

700

800

900

1,000

1,100

MEAN TOTAL WELL DEPTH,

IN FEET

MEAN TOTAL DEPTH

10

20

30

40

50

60

70

80

90

100

MEAN STATIC WATER LEVEL

New well

Replacement well

Deepened well

A

10

15

20

25

30

35

40

45

50

MEAN HAVB, IN METERES

MEAN HEIGHT ABOVE VALLEY BOTTOM (HAVB)

200

300

400

500

600

700

800

MEAN ELEVATION, IN FEET

ABOVE NGVD88

MEAN ELEVATION

EXPLANATION

75th percentile

Median

25th percentile

90th percentile

10th percentile

MEAN STATIC WATER LEVEL,

IN FEET BELOW LAND SURFACE

B

C D

Figure 14. Graphs showing A) mean static water level, B) mean total well depth, C) mean elevation, and D) mean height 

above minimum elevation within a 1,640-foot (500-meter) radius of well (HAVB), by categories of reported reason for well 

installation, New Hampshire, 1984−2007. 
28    Preliminary Assessment of Trends in Static Water Levels in Bedrock Wells in New Hampshire, 1984 to 2007

Summary and Conclusions

A cooperative investigation involving the New Hampshire Department of Environmental Services, the New Hampshire 

Geological Survey, and the U.S. Geological Survey was initiated in 2008 to explore potential trends in static water levels 

(SWLs) in wells and possible factors related to SWLs statewide, regionally, and locally. Analysis of nearly 60,000 reported 

values of SWL in new, deepened, and replacement bedrock wells in New Hampshire, aggregated on a yearly basis, showed an 

apparent deepening of SWL by about 13 feet over the period 1984–2007. These apparent declines are of concern because of 

the possible implications for water supply from the bedrock-aquifer system in New Hampshire. The same data also indicate 

that other well characteristics have also been changing over time, such as total well depth, casing length, the length of casing 

in bedrock, and to some extent, well yield. The average elevation of wells also has varied with time. In addition, SWLs were 

significantly lower in areas of high relief . Many of the well-construction variables are significantly correlated with SWLs. 

Because it is likely that several variables are needed to explain the variance in SWL over time, the main correlates (total depth, 

casing length, length of casing in bedrock, and well yield), as well as ancillary variables (season, hillslope position, elevation, 

recharge, precipitation, and geology), were considered in multiple regression analyses. 

The most significant predictors of mean SWL (as indicated by multiple regression models) were total depth, the third 

quarter of the year (July–September), elevation, and height above minimum elevation within a 1,640-foot (500-meter) radius of 

the well (hillslope factor). Casing length was a significant covariate for depth to SWL of wells in igneous rock and curvature of 

the land surface for wells in metamorphic rock. Most of the covariates were significant also for county-scale models, indicating 

that the statewide model sufficiently accounts for coarse-scale features that affect SWLs in bedrock wells. Local variations in 

geologic formations as well as landscape features appear to provide further explanation of SWL variation. For example, SWLs 

in wells completed in specific granites appear to be deeper than in other granites; a similar relation was also observed for groups 

of metamorphic rocks. 

A more detailed examination of data from six towns that report frequent complaints about lack of water from bedrockaquifer wells indicates that hillslope position may play a role in the availability of well water in these towns. SWLs were 

commonly deeper in wells with more than 100 ft (30 m) of relief between the well and the lowest land-surface elevation within 

a radius of 1,640 ft (500 m) of the well. Additionally, in these high-relief wells, the depth to SWL was commonly greater in 

wells on generally south-facing slopes than in wells on north-facing slopes. Although the reasons for this relation are not clear, 

it is possible that glacial morphology (steeper slopes facing south than north) and possibly evapotranspiration effects could play 

a role. 

Concerns about wells with low water-producing capacity in localized areas within towns may be better understood by 

considering some of the relations identified in this study. For example, the data show that the hillslope position of a well 

affects the SWL depth in that well; however, the data also indicate that the average yield of the well is lower for hillslope wells. 

These relations indicate that as the hillslope factor increases (and SWLs get deeper), the amount of available water in the wells 

decreases. Knowledge of this relation may lead to the drilling of deeper wells in areas of high hillslope variability. In areas with 

less extreme relief, the overall depth of wells has increased substantially more than the decrease in SWLs. This indicates that 

the amount of water stored in wells (wellbore storage) has increased and, thus, more water is available for use in the average 

well. As a result, more water may be used because it is available, possibly adding to the problem of local well interference—

where adjacent wells influence the availability of water to the well—or exacerbating drought-related well problems. This study 

did not, however, assess anthropogenic factors such as water-use patterns over time to explain apparent water-level observations; 

an accounting of these factors would be needed to more fully explain the water-capacity issues. 

These data provide an opportunity to examine groundwater-level conditions across the state, but they cannot substitute for 

a carefully designed network of wells selected for the sole purpose of monitoring SWLs. The data do allow for analysis that may 

be considered in the design of a monitoring network, and continued collection of water-well data from the bedrock wells could 

be used to augment data from monitoring wells. 

References Cited

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Ether (MTBE) in public and private wells in New Hampshire: occurrence, factors, and possible implications: Environ. Sci. 

Technol., v. 42, no. 3, p. 677–684.

Brutsaert, W., 2010, Annual drought flow and groundwater storage trends in the eastern half of the United States during the past 

two-third century: Theoretical and Applied Climatology, v. 100, no. 1, p. 93–103.
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Chormann, F.H., 1990, Bedrock water wells in New Hampshire: a statistical summary of the 1984-1990 inventory: New 

Hampshire Department of Environmental Services NHDES-WRD–90–3, 26 p.

Drew, L.J., Schuenenmeyer, J.H., Armstrong, T.R., and Sutphin, D.M., 2001, Initial yield to depth relation for water wells drilled 

into crystalline bedrock--Pinardville Quadrangle, New Hampshire: Ground Water, v. 39, no. 5, p. 676-684.

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Prepared by the Pembroke Publishing Service Center.

For more information concerning this report, contact:

Director

U.S. Geological Survey

New Hampshire-Vermont Water Science Center

331 Commerce Way, Suite 2

Pembroke, NH 03275

dc_nh@usgs.gov

or visit our Web site at:

http://nh.water.usgs.gov
Ayotte and others—Preliminary Assessment of Trends in Static Water Levels in Bedrock Wells in New Hampshire, 1984 to 2007—Open-File Report 2010–1189