Introduction Study Area

U.S. Department of the Interior

U.S. Geological Survey

Fact Sheet 2011–3127

March 2012

Introduction

General Circulation Model (GCM) simulations of future 

climate through 2099 project a wide range of possible scenarios 

(Intergovernmental Panel on Climate Change, 2007). To determine the sensitivity and potential effects of long-term climate 

change on the freshwater resources of the United States, the 

U.S. Geological Survey Global Change study, “An integrated 

watershed scale response to global change in selected basins 

across the United States” was started in 2008. The long-term 

goal of this national study is to provide the foundation for 

hydrologically based climate-change studies across the nation.

Fourteen basins for which the Precipitation Runoff Modeling System (PRMS) has been calibrated and evaluated were 

selected as study sites. PRMS is a deterministic, distributedparameter watershed model developed to evaluate the effects 

of various combinations of precipitation, temperature, and land 

use on streamflow and general basin hydrology. Output from 

five GCMs and four emission scenarios were used to develop 

an ensemble of climate-change scenarios for each basin. These 

ensembles were simulated with the corresponding PRMS 

model. This fact sheet summarizes the hydrologic effect and 

sensitivity of the PRMS simulations to climate change for the 

Clear Creek Basin near Coralville, Iowa (U.S. Geological Survey streamflow-gaging station 05454300; fig. 1) presented in 

the project summary report (Markstrom and others, 2012) and a 

journal article (Hay and others, 2011).

Study Area

The Clear Creek Basin is located in east-central Iowa, 

includes parts of Iowa and Johnson Counties, and is a tributary 

to the Iowa River. The basin is oriented in a general west-east 

direction and drains 254 square kilometers(km2). The topography of the Clear Creek Basin is characterized by uplands 

dissected by tributary streams (Schwob, 1964). The Clear 

Creek Basin has a wide and broad flood plain, with a meandering channel except along reaches that have been straightened 

(Barnes and Eash, 1990). Land use predominantly is agricultural with a growing urbanization in Johnson County, Iowa. 

The Iowa Department of Natural Resources (IDNR) and the 

Natural Resources Conservation Service (NRCS) created the 

Clear Creek Watershed Enhancement Project (Iowa Department of Natural Resources, 2011). The goal of this project is 

to use data from U.S. Geological Survey streamflow-gaging 

stations 05454220 and 05454300 in decisionmaking that will 

help restore Clear Creek water-quality to natural conditions.

Watershed Scale Response to Climate Change—Clear Creek 

Basin, Iowa
General Circulation ModelsGeneral Circulation Models Given the uncertainty in climate modeling, it is desirable to use more than one GCM to obtain a range of potential future climatic 

conditions. Monthly precipitation and temperature output from five GCMs were processed (table 1).

High 4,314

Low -79

EXPLANATION

Base from U.S. Geological Survey digital data, 2011 1:100,000

Albers Equal-Area Conic projection

Standard parallels 29°30'N and 45°30'N

Central meridian 96°00'W, Latitude of origin 23°00'N

Horizontal coordinate information is referenced to the

World Geodetic System of 1984 (WGS 84)

Elevation in meters

U.S. Geological Survey streamflow-

 gaging station and identifier

Clear Creek

0 1 2 3 4 MILES

0 1 2 3 4 KILOMETERS

92°

41°46'

44'

58'

41°40'

56' 54' 52' 50'

48' 46' 44' 42' 40'

38'

91°36'

42'

05454300

05454220

05454300

INDEX MAP

Study area

IOWA

Figure 1. Precipitation Runoff Modeling System study locations, Clear Creek Basin, Iowa, and location of U.S. Geological 

Survey streamflow gaging station 05454300 with a drainage area of 254 square kilometers and elevation range from 205 to 

261 meters.

Table 1. General Circulation Model (GCM) projections used in this study.

GCM Center and country of origin

BCC–BCM2.0 Bjerknes Centre for Climate Research, Norway

CSIRO–Mk3.0 Australia’s Commonwealth Scientific and Industrial Research Organization, Australia

CSIRO–Mk3.5 Australia’s Commonwealth Scientific and Industrial Research Organization, Australia

INM–CM3.0 Institute for Numerical Mathematics, Russia

MIROC3.2 National Institute for Environmental Studies, Japan
Results

Climate-change fields were derived by calculating the 

change in climate from current (water years 1988–1999) to 

future conditions simulated by each GCM. The 20C3M simulation for water years 1988–1999 was used to represent current 

climatic conditions. This 12-year period of record was chosen 

based on the overlap of the available historical records from 

the 14 basins included in the national study. Climate change 

fields (percentage changes in precipitation and degree changes 

in temperature) were computed for 12-year moving window 

periods (from 2001–2099) using the 20C3M (1988–1999) and 

the A1B, B1, and A2 emission scenarios. A 12-year moving 

window, starting in 2001 and ending in 2099, results in 1,320 

future scenarios [(88, 12-year climatologies, 1 per year starting 

with 2001–2012 and ending with 2088–2099) x (3 emission 

scenarios) x (5 GCMs)].

Climate-change scenarios were generated for PRMS by modifying PRMS precipitation and temperature inputs with the mean 

monthly climate change fields derived from the GCMs, resulting 

in 1,320 PRMS-input files. Table 3 shows the change (slope) 

and adjusted R2 (adjR2) for the least squares fit to the trend line 

for selected output variables from the PRMS projections. The 

slope indicates the change in the selected variable by year. The 

adjusted R2 value gives an indication of the variability in the 

central tendency of the trend line.

Figure 2 shows a summary of the projected range in 11-year 

moving mean daily values of maximum temperature (fig. 2A), 

minimum temperature (fig. 2B), and precipitation (fig. 2C) by 

emission scenario. The first year of each 12-year simulation 

was used as PRMS initialization and is not included in the 

results. The three solid-colored lines indicate the 11-year moving mean values (x-axis indicates center of 11-year window) 

for the three future emission scenarios (central tendency of the 

five GCMs for each emission scenario). The projected range 

shown for each emission scenario indicates the range of potential future climatic conditions simulated by the five GCMs. All 

GCM simulations project steady increases in maximum and 

minimum temperature (table 3), with uncertainties associated with these GCM projections increasing with time. Both 

maximum and minimum temperatures show the smallest projected changes for the B1 scenario. The wide range and lack 

of significant trend in the precipitation projections indicates a 

large amount of uncertainty in the GCM scenarios used in this 

study (table 3).

Results

PRMS simulates spatially distributed streamflow, components of flow (surface, subsurface, and groundwater), snowpack 

conditions, and many other hydrologic components of interest. 

Figure 3 shows the projected range in 11-year moving mean 

daily values of streamflow (fig. 3A) and the component of flow 

(figs. 3B–3D) by emission scenario. The central tendencies of 

the PRMS simulations using the three emission scenarios project 

decreases in mean annual streamflow for the A1B and A2 emission scenarios (table 3), though the uncertainties associated with 

these streamflow projections are large. In general, projections 

of surface, subsurface, and groundwater flow indicate the same 

decreasing pattern as the annual mean streamflow.

Changes in precipitation can be examined on a monthly basis 

(fig. 4). The solid red lines in figure 4 show PRMS-simulated 

mean monthly baseline conditions (1989–1999) for precipitation. The box plots represent the range in the mean monthly 

outputs for the five GCMs and three future emission scenarios 

for 2030 (green, 2025–2035), 2060 (tan, 2055–2065) and 2090 

(blue, 2085–2095). Projections indicate that the months associated with the lowest precipitation amounts (September through 

April) have minimal changes with low variability. In contrast, 

the months associated with the highest precipitation amounts 

(May through August) show both increasing and decreasing 

precipitation with much larger uncertainties.

The GCM outputs were obtained from the World Climate Research Programme’s Coupled Model Intercomparison Project 

phase 3 multi-model dataset archive, which was referenced in the Intergovernmental Panel on Climate Change Fourth Assessment 

Special Report on Emission scenarios (Intergovernmental Panel on Climate Change, 2007). For each GCM, one current (water 

years 1988–1999) and three future emission scenarios were used and are described in table 2. 

Table 2. Climate-change emission scenarios simulated by the General Circulation Models in this study.

Emission scenario Description/assumptions

20C3M 20th century climate used to determine baseline (1989–1999) conditions

A1B Rapid economic growth, a global population that peaks in mid-21st century and rapid introduction of new and 

more efficient technologies with a balanced emphasis on all energy sources

B1 Convergent world, with the same global population as Emission scenario A1B, but with more rapid changes in 

economic structures toward a service and information economy that is more ecologically friendly

A2 Heterogeneous world with high population growth, slow economic development, and slow technological change
Related streamflow variables produced by PRMS are summarized in Markstrom and others (2008). Analysis of these 

intermediate states may indicate areas of the water balance 

most susceptible to changes in climate. For example, figure 5 

shows the projected change in simulated basin mean annual 

values of soil moisture, an important indicator variable for 

effect in agricultural regions. The central tendency for the A1B 

and A2 emission scenarios shows a decrease in soil moisture 

over time (table 3). Based on these results, the likelihood of 

an increase in annual mean soil moisture are minimal. However, the uncertainty associated with decreasing soil moisture 

increases over time.

Center of 11-year window

Maximum temperature,

degrees Celsius

A. Basin mean maximum temperature

2020 2040 2060 2080

10

12

14

16

18

10

12

14

16

18

Center of 11-year window

Minimum temperature, degrees Celsius

B. Basin mean minimum temperature

2020 2040 2060 2080

0

2

4

6

8

0

2

4

6

8

Center of 11-year window

Precipitation, millimeters per day

C. Basin mean precipitation

2020 2040 2060 2080

2.5

3.0

3.5

4.0

2.5

3.0

3.5

4.0

Center of 11-Year Window

Maximum temperature,

degrees Celsius

A. Basin mean maximum temperature

2020 2040 2060 2080

10

12

14

16

18

10

12

14

16

18

Center of 11-Year Window

Minimum temperature,

degrees Celsius

B. Basin mean minimum temperature

2020 2040 2060 2080

0

2

4

6

8

0

2

4

6

8

Center of 11-Year Window

Precipitation, millimeters per day

C. Basin mean precipitation

2020 2040 2060 2080

2.5

3.0

3.5

4.0

2.5

3.0

3.5

4.0 EXPLANATION

Emission Scenarios

A2 A1B B1

Maximum

Mean from five General Circulation Models

Minimum

Figure 2. Projected range in 11-year moving mean daily values 

of (A) maximum temperature, (B) minimum temperature, and 

(C) precipitation by emission scenario. 

Table 3. Projected change by year (slope) and adjusted R2

 (adjR2) based on the central tendencies of the five General Circulation Models for the three 

carbon emission scenarios for selected Precipitation Runoff Modeling System (PRMS) output variables.

[Blue indicates a significant negative trend and yellow indicates a significant positive trend (p<0.05) accounting for lag-1 autocorrelation]

PRMS output variable

Emission scenario

A1B

Emission scenario

A2

Emission scenario

B1

slope adjR2 slope adjR2 slope adjR2

Maximum temperature in degrees Celsius 0.041 0.99 0.051 0.99 0.023 0.96

Minimum temperature in degrees Celsius 0.039 0.99 0.046 0.99 0.022 0.96

Precipitation in millimeters per day 0.0008 0.14 -0.0018 0.25 0.0006 0.02

Streamflow in cubic meters per second -0.0101 0.73 -0.0169 0.86 -0.0065 0.48

Surface runoff in cubic meters per second -0.00213 0.64 -0.00396 0.79 -0.00125 0.26

Subsurface flow in cubic meters per second -0.00448 0.71 -0.00745 0.84 -0.00311 0.53

Groundwater flow in cubic meters per second -0.00349 0.80 -0.00550 0.91 -0.00217 0.57

Soil moisture in millimeters per day -0.3386 0.93 -0.5071 0.95 -0.1537 0.55
Center of 11-year window

Streamflow,

cubic meters per second

A. Basin mean streamflow

2020 2040 2060 2080

0

1

2

3

4

5

0

1

2

3

4

5

Center of 11-year window

Surface runoff,

cubic meters per second

B. Basin mean surface runoff

2020 2040 2060 2080

0.2

0.4

0.6

0.8

1.0

1.2

1.4

0.2

0.4

0.6

0.8

1.0

1.2

1.4

Center of 11-year window

Subsurface flow,

cubic meters per second

C. Basin mean subsurface flow

2020 2040 2060 2080

0.0

0.5

1.0

1.5

2.0

0.0

0.5

1.0

1.5

2.0

Center of 11-year window

Groundwater flow,

cubic meters per second

D. Basin mean groundwater flow

2020 2040 2060 2080

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

Figure 3. Projected range in 11-year moving mean daily values of (A) streamflow, (B) surface runoff, (C) subsurface flow, and (D) groundwater flow by emission scenario.

Month

Precipitation, millimeters per day

Basin mean precipitation

 Feb. Apr. June Aug. Oct. Dec.

2

4

6

8

10

2

4

6

8

10

EXPLANATION

Baseline

Conditions

(1989-1999)

2030

(2025-2035)

2060

(2055-2065)

2090

(2085-2095)

Whisker, 90th percentile

Upper quartile line, 75th percentile

Median line, 50th percentile

Lower quartile line, 25th percentile

Whisker, 10th percentile

Outlier

Figure 4. Mean daily precipitation values by month for baseline conditions and projected range (2030, 2060, and 2090) using the five General 

Circulation Models and three emission scenarios.

Center of 11-year window

Soil moisture, millimeters

Basin mean soil moisture

2020 2040 2060 2080

80

100

120

140

160

180

80

100

120

140

160

180

EXPLANATION

Emission Scenarios

A2 A1B B1

Maximum

Mean from five General Circulation Models

Minimum

Figure 5. Projected range in 11-year moving mean daily values of soil moisture by emission scenario.
Conclusion and

 Discussion Selected

Conclusion and Discussion References In the Clear Creek Basin, agricultural water consumption and 

population growth will result in increasing water demand. The 

broader-scale effects of climate change on the flow regime of the 

Clear Creek Basin indicates an overall slight drying of the basin 

as a consequence of increased evapotranspiration, but the uncertainty associated with the magnitude of this drying is large.

These results did not consider potential future population 

growth and land-use changes. They also do not answer the 

question of whether the potentially adverse effects because of 

climate change can be mitigated with careful land-use planning 

in the Clear Creek Basin.

The combined effects of climate change and urbanization in 

the Clear Creek Basin may alter both the quantity and timing 

of streamflow and have the potential to change the conditions 

of water- quality that supports biological diversity in aquatic 

communities. The scientific techniques described in the fact 

sheet can be augmented with other techniques in developing the 

science needed to address the combined effects of climate and 

land-cover dynamics on streamflow regimes.

Selected References

Barnes, K.K., and Eash, D.A., 1990, Flood of June 17, 1990, in 

the Clear Creek Basin, east-central Iowa: U. S. Geological 

Survey Open-File Report 94–78, 16 p.

Hay, L.E., Markstrom, S.L., and Ward-Garrison, C.D., 2011, 

Watershed-scale response to climate change through the 

twenty-first century for selected basins across the United 

States, Earth Interactions, v. 15, 37 p.

Iowa Department of Natural Resources, 2011, Clear Creek 

watershed enhancement project, accessed June 2011, at http://

www.iowadnr.gov/water/watershed/clearcreek/index.html.

Intergovernmental Panel on Climate Change, 2007, Summary 

for policymakers, in Climate change 2007—The physical 

science basis, Contributions of Working Group 1 to the 

Fourth Assessment Report of the Intergovernmental Panel 

on Climate Change: Cambridge and New York, Cambridge 

University Press, 18 p.

Markstrom, S.L., Niswonger, R.G., Regan, R.S., Prudic, D.E., 

and Barlow, P.M., 2008, GSFLOW—Coupled ground-water 

and surface-water flow model based on the integration of the 

Precipitation-Runoff Modeling System (PRMS) and the Modular Ground-Water Flow Model (MODFLOW–2005): U.S. 

Geological Survey Techniques and Methods 6–D1, 240 p.

Markstrom, S.L., Hay, L.E., Ward-Garrison, C.D., Risley, J.C., 

Battaglin, W.A., Bjerklie, D.M., Chase, K.J., Christiansen, 

D.E. Dudley, R.W., Hunt, R.J., Koczot, K.M., Mastin, M.C., 

Regan, R.S., Viger, R.J., Vining, K.C., and Walker, J.F., 2012, 

An integrated watershed scale response to climate change 

for selected basins across the United States: U.S. Geological 

Survey Scientific Investigations Report 2011–5077, 142 p.

Schwob, H.H., 1964, Water resources of the English River, Olds 

Mans Creek, and Clear Creek basins in Iowa: U. S. Geological Survey Open-File Report 64–141, 57 p.

By Daniel E. Christiansen, Lauren E. Hay, and Steven L. Markstrom

For more information visit the following Web sites:

http://wwwbrr.cr.usgs.gov/projects/SW_MoWS/

http://ia.water.usgs.gov/

http://www.usgs.gov/climate_landuse/