U.S. Department of the Interior

U.S. Geological Survey

Scientific Investigation Report 2017–5100

Prepared in cooperation with The Nature Conservancy and Salt River Project

Preliminary Synthesis and Assessment of Environmental 

Flows in the Middle Verde River Watershed, Arizona
COVER

View looking northwest of the Verde River north of Clarkdale, Arizona. River flow is toward the 

viewer. U.S. Geological Survey streamgage 09504000 stilling well and cable way are located on the 

bank. (U.S. Geological Survey photograph by Anne M.D. Brasher.)

BACK COVER

A desert sucker (Catostomus clarki) from West Clear Creek, a tributary to the Verde River near Camp 

Verde, Arizona (U.S. Geological Survey photograph by Nicholas V. Paretti).
Preliminary Synthesis and Assessment of 

Environmental Flows in the Middle Verde 

River Watershed, Arizona

By Nicholas V. Paretti, Anne M.D. Brasher, Susanna L. Pearlstein, Dena M. Skow, 

Bruce Gungle, and Brad D. Garner

Prepared in cooperation with The Nature Conservancy and Salt River Project

Scientific Investigation Report 2017–5100

U.S. Department of the Interior

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

RYAN K. ZINKE, Secretary

U.S. Geological Survey

James F. Reilly II, Director

U.S. Geological Survey, Reston, Virginia: 2018

For more information on the USGS—the Federal source for science about the Earth, its natural and living 

resources, natural hazards, and the environment—visit http://www.usgs.gov or call 1–888–ASK–USGS.

For an overview of USGS information products, including maps, imagery, and publications, 

visit http://www.usgs.gov/pubprod/.

Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the 

U.S. Government.

Although this information product, for the most part, is in the public domain, it also may contain copyrighted materials 

as noted in the text. Permission to reproduce copyrighted items must be secured from the copyright owner.

Suggested citation:

Paretti, N.V., Brasher, A.M.D., Pearlstein, S.L., Skow, D.M., Gungle, Bruce, and Garner, B.D., 2018, Preliminary synthesis and assessment of environmental flows in the middle Verde River watershed, Arizona: U.S. Geological Survey 

Scientific Investigations Report 2017–5100, 104 p., https://doi.org/10.3133/sir20175100.

ISSN 2328-0328 (online)
iii

Acknowledgments

This project was developed and funded in cooperation with The Nature Conservancy (TNC). Dan 

Campbell (retired), Jeanmarie Haney, and Kimberly Schoneck at TNC provided crucial support 

and expertise regarding the Verde River watershed. Additional funding from the Salt River Project and the U.S. Geological Survey (USGS) WaterSMART program made possible the extension 

of the project to the development of study sites, sampling, and sample analysis.

Twice during the project, we invited a work group to meet and provide comments and suggestions concerning the direction and focus of our work to keep it relevant to the goals of developing information useful for resource policy and management. Jeanmarie Haney (TNC), Shaula 

Hedwall (U.S. Fish and Wildlife Service), Charles Paradzick (Salt River Project), John Rasmussen 

(Yavapai County Water Advisory Committee Coordinator), Patti Spindler (Arizona Department 

of Environmental Quality, ADEQ), Abe Springer (Northern Arizona University), and David Ward 

(USGS Grand Canyon Monitoring and Research Center) contributed many insights that strengthened the project.

Data and analyses directly incorporated into the report or used as background information were 

generously shared by agencies and individuals. Charlie Cave (Yavapai County Flood Control 

District) provided aerial photographs and detailed topographic maps commissioned by Yavapai 

County; the hydrological consulting firm HDR, with the permission of Yavapai County, provided 

a detailed report documenting their hydraulic modeling for the county. Patti Spindler (ADEQ) and 

Andy Clark (Arizona Game and Fish Department) generously shared valuable macroinvertebrate 

and fish datasets that were crucial to the report’s primary analyses. Jocelyn Gretz provided 

valuable support for field work and planning. Steve Wiele provided much valuable assistance 

and support in the development of the project generally and to the section on surface water and 

groundwater in particular.
iv

Contents

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

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

Environmental Flows ............................................................................................................................3

ELOHA Framework.......................................................................................................................3

Purpose and Scope .......................................................................................................................................6

Physical Setting..............................................................................................................................................6

Surface Water and Groundwater................................................................................................................7

Surface-Water Hydraulic Models......................................................................................................7

Groundwater Models ...........................................................................................................................8

Northern Arizona Groundwater Flow Model...........................................................................8

Model Construction............................................................................................................8

Use of NARGFM for Environmental Flow Studies .........................................................8

Spatial Resolution......................................................................................................8

Temporal Resolution................................................................................................10

NARGFM Stream-Flow Predictions ......................................................................10

Estimates of Monthly Streamflow at Ungaged Locations............................................................11

Riparian Vegetation .....................................................................................................................................15

Life Histories and Ecological Needs of Cottonwood and Willow Species ...............................18

Non-native Riparian Species............................................................................................................19

Assessment of Current Riparian Vegetation Status......................................................................19

Division of Reaches...................................................................................................................19

Remote Sensing of Evapotranspiration..................................................................................20

Imagery........................................................................................................................................20

Vegetation Digitizing and Classification.................................................................................20

Geomorphology............................................................................................................................................22

Geomorphic Classification of River Features.................................................................................22

Bedload Transport at the Paulden Streamgage ............................................................................29

Fish and Macroinvertebrates.....................................................................................................................31

Analysis Framework...........................................................................................................................31

Fish and Macroinvertebrate Data Sources and Processing..............................................31

Statistical Analysis and Methods ...........................................................................................31

Description of Hydrologic Metric Determination and Flooding Classification................34

Reach Classification..................................................................................................................35

Fish.................................................................................................................................................................42

Introduction and Background...........................................................................................................42

Adaptation of Native Fish to the Flow Regimes of Desert Streams ..................................42

Non-native Fish of the Verde ...................................................................................................45

Native Fish of the Verde and Habitat Requirements............................................................45

Temporal and Spatial Considerations of Fish Data Collected in the Middle Verde 

Watershed ..............................................................................................................................47

Distribution of Fish Using Basin Characteristic Reach Characterization..................................47

Distribution of Fish Using Flow-Alteration Reach Characterization...........................................50

Relation of Flow Metrics to Fish Community Metrics and Assemblages to Flow Metrics.....52
v

Pilot Study—Native and Non-native Fish Microhabitat...............................................................55

Fish Data Collection Methods for Pilot Microhabitat Study ...............................................61

Microhabitat Characterization Methods for Pilot Microhabitat Study.............................61

Pilot Microhabitat Study Sampling Locations.......................................................................62

Total Fish Assemblages in Pilot Study....................................................................................62

Microhabitat Characteristics by Pilot Study Sampling Site ...............................................62

Pilot-Study Fish Characteristics..............................................................................................67

Native and Non-native Fish Use of Available Microhabitat in Pilot Study.......................67

Fish Abundance by Available Microhabitat at Each Pilot-Study Sampling Site .............73

Macroinvertebrates.....................................................................................................................................81

Macroinvertebrate Metrics ..............................................................................................................86

Watershed Macroinvertebrate Distribution Using a Reach Characterization with 

Multiagency Data..................................................................................................................86

Associations Among Flow Metrics and Macroinvertebrate Metrics ........................................88

Macroinvertebrate Quantile Regression ........................................................................................88

Macroinvertebrate Pilot Study .........................................................................................................93

Conclusion and Future Directions.............................................................................................................93

References Cited..........................................................................................................................................97

Figures

1. Map of the Verde River watershed, Arizona......................................................................................4

2. Hydrograph for U.S. Geological Survey streamgage Verde River near Clarkdale, AZ water 

year 2005 demonstrating flow-regime components ...............................................................5

3. Diagram showing a conceptual model of environmental flows.....................................................5

4. Diagram showing a conceptual model of abiotic and biotic ecosystem drivers ........................6

5. Map of northern Arizona showing area covered by the Northern Arizona Regional Groundwater Flow Model.........................................................................................................................9

6. Aerial photograph showing the length of an example sampling site near Reitz Ranch on 

the Verde River, Arizona, relative to the Northern Arizona Regional Groundwater Flow 

Model grid spacing.....................................................................................................................10

7. Latitude/longitude-gridded images of Northern Arizona Groundwater Flow Model predictions of groundwater-streamflow interactions on river reaches in the middle Verde 

River watershed, Arizona ..........................................................................................................12

8. Map image showing weighted flow-accumulation grid generated from Basin Characteristics Model predictions of local runoff for February 1993 for the middle Verde River 

watershed, Arizona ....................................................................................................................14

9. Example hydrograph showing monthly streamgage data at the Oak Creek near Sedona 

gage compared to combined Northern Arizona Groundwater Flow Model base flow 

and uncalibrated Basin Characteristics Model local runoff predictions and combined 

NARGFM base flow and calibrated BCM predictions..........................................................15

10. Graph showing monthly streamflow statistics at the Oak Creek gage in the middle Verde 

River watershed, Arizona ..........................................................................................................16

11. Graph showing monthly streamflow statistics at the Wet Beaver Creek gage in the middle 

Verde River watershed, Arizona...............................................................................................16

12. Graph showing monthly streamflow statistics at the Dry Beaver Creek gage in the middle 

Verde River watershed, Arizona...............................................................................................17
vi

13. Graph showing monthly streamflow statistics at the West Clear Creek gage in the middle 

Verde River watershed, Arizona...............................................................................................17

14. Graph showing monthly streamflow statistics at tributary confluences in the middle Verde 

River watershed, Arizona ..........................................................................................................18

15. Graphs showing actual and potential evapotranspiration of the Verde River, Arizona, from 

2000–2012 using the Moderate Resolution Imaging Spectroradiometer enhanced vegetation index product.................................................................................................................21

16. Graph and pie chart showing distribution of vegetation along the upper-middle Verde River, 

Arizona..........................................................................................................................................23

17. Graph and pie chart showing distribution of vegetation along the lower-middle Verde River, 

Arizona..........................................................................................................................................24

18. Graph and pie chart showing distribution of vegetation along Oak Creek, Arizona, from 

confluence with Verde River to sampling site 17.45 miles upstream.................................25

19. Graph and pie chart showing distribution of vegetation along West Clear Creek, Arizona, 

from confluence with Verde River to sampling site 11 miles upstream ............................26

20. Graph showing upper-middle Verde River, Arizona, geomorphology class distribution per 

river mile.......................................................................................................................................27

21. Graph showing lower-middle Verde River, Arizona, geomorphology class distribution per 

river mile.......................................................................................................................................27

23. Graph showing West Clear Creek, Arizona, geomorphology class distribution per 

river mile.......................................................................................................................................28

22. Graph showing Oak Creek, Arizona, geomorphology class distribution per river mile..........28

24. Graphs showing nondimensionalized channel properties, flow properties, and sediment 

flux plotted as a function of the nondimensionalized water-discharge and bedload 

transport calculated at the Verde River near Paulden gage, Arizona...............................30

25. Map showing State of Arizona and Federal agency fish survey locations on the upper-middle and lower-middle Verde River, Arizona, and tributaries color coded by percentage 

of native fish present..................................................................................................................32

26. Map showing State of Arizona and Federal agency macroinvertebrate survey locations on 

the upper-middle and lower-middle Verde River, Arizona, and tributaries.......................33

27. Graphs showing mean daily stream discharge at the Verde River near Camp Verde, Verde 

River near Clarkdale, and Verde River near Paulden gages on the middle Verde River, 

Arizona..........................................................................................................................................38

28. Map showing reach classification by basin characteristics and nonmetric multidimensional scaling plot of reaches for the middle Verde River watershed, Arizona...............43

29. Map showing reach classification by streamflow alteration for the middle Verde River 

watershed, Arizona ....................................................................................................................44

30. Plots showing the distribution of fish-survey data collection for the middle Verde River 

watershed, Arizona ....................................................................................................................48

31. Graph showing boxplots of the percent native fish species collected from the middle Verde 

River, Arizona, from 1995 to 2011..............................................................................................49

32. Diagram showing nonmetric multidimensional scaling ordination of fish-species similarities across all samples from the middle Verde River, Arizona............................................50

33. Graphs showing boxplots of native fish from the middle Verde River, Arizona .......................51

34. Diagram showing nonmetric multidimensional scaling (NMDS) ordination for fish assemblages labeled by basin characteristic reaches for the middle Verde River, Arizona....52

35. Graphs showing boxplots of percent native fish for each geomorphic channel unit classification and each family percentage within each GCU classification for samples 

collected on the middle Verde River, Arizona........................................................................53
vii

36. Graphs showing boxplots of native fish in the middle Verde River, Arizona ............................54

37. Diagrams showing nonmetric multidimensional scaling ordination plots of multivariate 

centroids of fish group assemblages, NMDS ordination of assemblages with vector 

overlay of fish species labeled by reach, and NMDS ordination of assemblages with 

vector overlay of fish families labeled by degree of diversion for the middle Verde 

River, Arizona...............................................................................................................................56

38. Graphs of relative abundance of suckers and sunfish and respective locally weighted 

scatterplot smoothing trend lines, total abundance of suckers and sunfish and LOWESS trend lines, and relative abundance of suckers and sunfish plotted as boxplots 

categorized by reach and flood condition for the middle Verde River, Arizona...............57

39. Graph of significant correlations between 90- and 365-day hydrologic metrics and select 

fish metrics for the for the middle Verde River, Arizona.......................................................58

40. Graphs showing quantile regression lines, intercepts, and slopes of the 0.10, 0.25, 0.50, 

0.75, and 0.90 quantiles for significantly correlated 365-day hydrologic and fish metrics 

for the middle Verde River, Arizona .........................................................................................59

41. Graphs showing quantile regression lines, intercepts, and slopes of the 0.10, 0.25, 0.50, 

0.75, and 0.90 quantiles for significantly correlated 90-day hydrologic and fish metrics 

for the middle Verde River, Arizona .........................................................................................60

42. Diagrams showing nonmetric multidimensional scaling ordination plot of assemblages 

collected from West Clear Creek in 1995–2011 for the middle Verde River watershed, 

Arizona..........................................................................................................................................61

43. Graph showing percent of geomorphic channel units identified at the five fish microhabitat 

study reaches in the middle Verde watershed, Arizona. .....................................................64

44. Graphs showing native and non-native fish distribution in the middle Verde River watershed, Arizona...............................................................................................................................65

45. Graphs showing boxplots of the distribution of water velocity, water depth, median substrate size, and riparian cover for each fish-microhabitat sample reach in the middle 

Verde River watershed, Arizona...............................................................................................68

46. Graphs showing nonparametric density estimates of fish observations for sample reaches 

in the middle Verde River watershed, Arizona, plotted as a smooth, nonparametric 

bivariate surface representing the density of observations for a given velocity and 

depth .............................................................................................................................................69

47. Graphs showing boxplots of the distribution of native and non-native fish species relative 

to where observed in each microhabitat in sample reaches in the middle Verde River 

watershed, Arizona ....................................................................................................................70

48. Graphs showing fish length, water depth, and water velocity relations among select fish 

species from sample reaches in the middle Verde River, Arizona.....................................72

49. Graphs of available velocity and velocity use by native and non-native fish in sample 

reaches in the middle Verde River and two tributary streams, Arizona............................75

50. Graphs of available depth and depth use by native and non-native fish in sample reaches 

in the middle Verde River and two tributary streams, Arizona............................................77

51. Graphs of available substrate and substrate use by native and non-native fish in sample 

reaches in the middle Verde River and two tributary streams, Arizona............................79

52. Graphs showing both available microhabitat types and microhabitat types used by native 

and non-native fish at Verde River below Granite Creek in the middle Verde River 

watershed, Arizona ....................................................................................................................80

53. Graphs showing both available microhabitat types and microhabitat types used by native 

and non-native fish at Verde River at Paulden in the middle Verde River watershed, 

Arizona..........................................................................................................................................82
viii

54. Graphs showing both available microhabitat types and microhabitat types used by native 

and non-native fish at Verde River at Perkinsville in the middle Verde River watershed, 

Arizona..........................................................................................................................................83

55. Graphs showing both available microhabitat types found and microhabitat types used 

by native and non-native fish at Oak Creek in the middle Verde River watershed, 

Arizona..........................................................................................................................................84

56. Graphs showing both available microhabitat types and microhabitat types used by 

native and non-native fish at West Clear Creek in the middle Verde River watershed, 

Arizona..........................................................................................................................................85

57. Graphs showing three macroinvertebrate metrics split into flood-magnitude category 

and plotted by month and index for the middle Verde River and two tributary streams, 

Arizona..........................................................................................................................................87

58. Graphs showing boxplots of macroinvertebrate-assemblage composition and functional 

feeding groups for the upper-middle and lower-middle Verde River, Arizona, and major 

tributaries.....................................................................................................................................89

59. Plot showing nonmetric multidimensional scaling of multivarite centroids for macroinvertebrate assemblages from the upper-middle and lower-middle Verde River, Arizona, and 

tributaries.....................................................................................................................................90

60. Graphs showing the statistically significant relations among 30-day hydrologic metrics 

and select macroinvertebrate metrics for the Oak Creek, Wet Beaver Creek, and West 

Clear Creek tributaries of the middle Verde River, Arizona .................................................91

61. Graphs showing quantile regression lines, intercepts, and slopes of the 0.10, 0.25, 0.50, 0.75, 

and 0.90 quantile regression lines for significantly correlated hydrologic and macroinvertebrate metrics for the middle Verde River and two tributary sites, 

Arizona..........................................................................................................................................94

62. Diagram showing nonmetric multidimensional scaling ordination plot of assemblages 

and macroinvertebrate metric pie plots of percent mayflies, percent caddisflies, and 

percent true flies for the middle Verde River, Arizona..........................................................95

Tables

1. U.S. Geological Survey mainstem and tributary streamflow gaging stations in the middle 

Verde River watershed, Arizona.................................................................................................7

2. Numbers of model stream cells predicted by the Northern Arizona Groundwater Flow Model 

to be gaining, losing, or dry in reaches of the upper-middle and lower-middle Verde 

River, Arizona, in 1910 and 2006................................................................................................11

3. Base flows in cubic feet per second determined by the Northern Arizona Groundwater Flow 

Model and used in the monthly streamflow estimates for the middle Verde River watershed, Arizona...............................................................................................................................11

4. Calibration coefficients used to relate combined Northern Arizona Groundwater Flow Model 

and Basin Characteristics Model predictions of local runoff to streamgage data for the 

middle Verde River watershed, Arizona..................................................................................13

5. Nash-Sutcliffe efficiency coefficients for the fit of the combined Northern Arizona Groundwater Flow Model and calibrated Basin Characteristics Model predictions with 

respect to streamgage data for the middle Verde River watershed, Arizona..................15
ix

6. Vegetation classes used to digitize satellite and aerial imagery along the Verde River, 

Arizona..........................................................................................................................................20

7. Geomorphic channel units used in this study of the middle Verde River, Arizona....................29

8. Streamflow metrics computed by the Environmental Flow Allocation and Statistics 

Calculator.....................................................................................................................................36

9. Fish microhabitat data-category quantiles and ranges for five middle Verde River, Arizona, 

study reaches..............................................................................................................................63

10. Fish-microhabitat study-reach length and geomorphic channel unit sequence for the 

middle Verde watershed, Arizona............................................................................................64

11. Number and percent of native and non-native fish species at each sample reach in the 

middle Verde River watershed, Arizona..................................................................................66

12. Fish microhabitat categories for water velocity, water depth, and substrate, as well as subcategory ranges, descriptors, and quantiles for sample reaches in the middle Verde 

River and two tributary streams, Arizona ...............................................................................86

13. Macroinvertebrate metrics significantly greater in reaches of the middle Verde River and 

two tributaries, Arizona, that have water diversions and were collected during the 

spring or fall index period, collected after large magnitude floods or no large flooding 

events, and collected on the Verde River or a tributary.......................................................92

14. Kendall tau correlations between macroinvertebrate metrics and hydrologic metrics for 

the middle Verde River, Arizona, and tributaries ...................................................................93

15. Unique taxa observed in the six macroinvertebrate assemblages collected from the Verde 

River in the upper part of the middle Verde River watershed, Arizona .............................96
x

Multiply By To obtain

Length

inch (in.) 25.4 millimeter (mm)

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

Area

acre 4,047 square meter (m2)

acre 0.4047 hectare (ha)

acre 0.4047 square hectometer (hm2) 

acre 0.004047 square kilometer (km2)

square foot (ft2) 0.09290 square meter (m2)

square mile (mi2) 259.0 hectare (ha)

square mile (mi2) 2.590 square kilometer (km2) 

Flow rate

acre-foot per year (acre-ft/yr) 1,233 cubic meter per year (m3/yr)

acre-foot per year (acre-ft/yr) 0.001233 cubic hectometer per year (hm3/yr)

foot per second (ft/s) 0.3048 meter per second (m/s)

cubic foot per second (ft3/s) 0.02832 cubic meter per second (m3/s)

Conversion Factors

U.S. customary units to International System of Units

International System of Units to U.S. customary units

Multiply By To obtain

Length

micrometer (μm) 0.00003937 inch (in.)

millimeter (mm) 0.03937 inch (in.)

meter (m) 3.281 foot (ft) 

kilometer (km) 0.6214 mile (mi)

Area

square meter (m2) 0.0002471 acre 

hectare (ha) 2.471 acre

square hectometer (hm2) 2.471 acre

square kilometer (km2) 247.1 acre

square meter (m2) 10.76 square foot (ft2) 

hectare (ha) 0.003861 square mile (mi2) 

square kilometer (km2) 0.3861 square mile (mi2)

Flow rate

cubic meter per year (m3/yr) 0.000811 acre-foot per year (acre-ft/yr) 

cubic hectometer per year (hm3/yr) 811.03 acre-foot per year (acre-ft/yr)

meter per second (m/s) 3.281 foot per second (ft/s) 

cubic meter per second (m3/s) 35.31 cubic foot per second (ft3/s)

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

°F = (1.8 × °C) + 32.

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

°C = (°F – 32) / 1.8.
xi

Datum

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).

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

Supplemental Information

Concentrations of chemical constituents in water are given in grams per liter (g/L).
xii

ADEQ Arizona Department of Environmental Quality

AZGFD Arizona Game and Fish Department 

acre-ft/yr acre-feet per year

BCM Basin Characteristic Model

BFR base-flow recession

ft3/s cubic feet per second

ft/s foot per second

DOY day of year

EFASC Environmental Flow Allocation and Statistics Calculator 

ELOHA Ecological Limits of Hydrologic Alteration

EMAP EPA Environmental Monitoring and Assessment Program

EPA U.S. Environmental Protection Agency

ET evapotranspiration

EVI enhanced vegetation index

ft foot

g/L gram per liter

GCU geomorphic channel unit

GIS geographic information system

GPS Global Positioning System

HEC-RAS Hydrologic Engineering Center River Analysis System 

km kilometer

LOWESS locally weighted scatterplot smoothing

m meter

mm millimeter

MODFLOW USGS Modular Finite-Difference Flow Model

MODIS Moderate Resolution Imaging Spectroradiometer

NARGFM Northern Arizona Groundwater Flow Model

NAU Northern Arizona University

NAWQA USGS National Water Quality Assessment program

NMDS nonmetric multidimensional scaling

NRMF normalized range of monthly flow

NWIS USGS National Water Information System

PrAMA Prescott Active Management Area

PRISM Parameter-Elevation Regressions on Independent Slopes Model

TNC The Nature Conservancy

USFS U.S. Forest Service

USGS U.S. Geological Survey

τ Kendall’s tau correlation coefficient

Abbreviations and Acronyms
Preliminary Synthesis and Assessment of Environmental 

Flows in the Middle Verde River Watershed, Arizona

By Nicholas V. Paretti, Anne M.D. Brasher, Susanna L. Pearlstein, Dena M. Skow, Bruce Gungle, and Brad D. 

Garner

Abstract

A 3-year study was undertaken to evaluate the suitability 

of the available modeling tools for characterizing environmental flows in the middle Verde River watershed of central 

Arizona, describe riparian vegetation throughout the watershed, and estimate sediment mobilization in the river. Existing 

data on fish and macroinvertebrates were analyzed in relation 

to basin characteristics, flow regimes, and microhabitat, and 

a pilot study was conducted that sampled fish and macroinvertebrates and the microhabitats in which they were found. 

The sampling for the pilot study took place at five different 

locations in the middle Verde River watershed. This report 

presents the results of this 3-year study.

The Northern Arizona Groundwater Flow Model 

(NARGFM) was found to be capable of predicting long-term 

changes caused by alteration of regional recharge (such as 

may result from climate variability) and groundwater pumping in gaining, losing, and dry reaches of the major streams 

in the middle Verde River watershed. Over the period 1910 to 

2006, the model simulated an increase in dry reaches, a small 

increase in reaches losing discharge to the groundwater aquifer, and a concurrent decrease in reaches gaining discharge 

from groundwater. Although evaluations of the suitability 

of using the NARGFM and Basin Characteristic Model to 

characterize various streamflow intervals showed that smallerscale basin monthly runoff could be estimated adequately 

at locations of interest, monthly stream-flow estimates were 

found unsatisfactory for determining environmental flows.

Orthoimagery and Moderate Resolution Imaging Spectroradiometer data were used to quantify stream and riparian 

vegetation properties related to biotic habitat. The relative 

abundance of riparian vegetation varied along the main channel of the Verde River. As would be expected, more upland 

plant species and fewer lowland species were found in the 

upper-middle section compared to the lower-middle section, 

and vice-versa. Vegetation changes within the upper-middle 

and lower-middle reaches are related to differences in climate and hydrology. In general, the riparian vegetation of the 

middle Verde River watershed is that of a healthy ecosystem’s 

mixed age, mixed patch structure, likely a result of the mostly 

unaltered disturbance regime.

The frequency of in-river hydrogeomorphic features 

(pool, riffle, run) varied along the middle Verde River channel. There was a greater abundance of riffle habitat in the 

upper-middle reach; the lower-middle reach included more 

pool habitat. The Oak Creek tributary was more homogenous 

in geomorphic stream habitat composition than West Clear 

Creek, where runs dominated the upper reaches and pools 

dominated many of the lower reaches.

On the basis of the period of record and discharges 

recorded at 15-minute intervals, five flows were found to 

reach the gravel-transport threshold. Sediment mobilization 

computed with flows averaged over daily time steps yielded 

just three flows that reached the gravel-transport threshold, 

and monthly averaged flows yielded none. In the middle Verde 

River watershed, 15-minute data should be used when possible 

to evaluate sediment transport in the river system.

Data from more than 300 fish surveys conducted from 

1992 to 2011 were analyzed using two schemes, one that 

divided the river into five reaches based on basin characteristics, and a second that divided the river into five reaches 

based on degree of flow alteration (specifically, diversions). 

Fish community metrics and assemblage data were used to 

analyze patterns of species composition and abundance in 

the two approaches. Overall, native and non-native species 

were regularly interacting and probably competing for similar 

resources. Fish abundances were also analyzed in response to 

floods and other flow metrics. Although the data are limited, 

native fish abundances increased more rapidly than non-native 

fish abundances in response to large floods. The basin-characteristic reach analysis showed native fish in greater abundance 

in the upper-middle reaches of the Verde River watershed and 

generally decreasing with downstream distance. The median 

relative abundance of native fish decreased by 50 percent 

from reach 1 to reach 5. Using the reach scheme based on 

degree of flow alteration, nondiverted reaches were found to 

have a greater abundance of native fish than diverted reaches. 

In heavily diverted reaches, non-native species outnumbered 

native species.

Fish metrics and stream-flow metrics for the 30, 90, and 

365-day periods before collection were computed and the 

results analyzed statistically. Only abundance of all fish species was associated with the 30-day flow metrics. The 90-day 
2 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

flow metrics were generally positively associated with fish 

metrics, whereas the 365-day flow metrics had more negative 

correlations. In particular, significant relations were found 

between fish metrics and the magnitude and frequency of 

high flows, including maximum monthly flow, median annual 

number of high-flow events, and median annual maximum 

streamflow. Native sucker (Catostomidae) populations tended 

to decrease in periods of extended base flow, and fish in the 

non-native sunfish family (Centrarchidae) decreased in periods 

of flashy, high magnitude flows.

A pilot study surveyed fish at five locations in the upper 

part of the middle Verde River watershed as a means to 

measure microhabitat availability and quantify native and 

non-native fish use of that available microhabitat. Results 

indicated that native and non-native species exhibit some clear 

differences in microhabitat use. Although at least some native 

and non-native fish were found in each velocity, depth, and 

substrate category, preferential microhabitat use was common. 

On a percentage basis, non-native species had a strong preference for slow-moving and deeper water with silt and sand 

substrate, with a secondary preference for faster moving and 

very shallow water and a coarse gravel substrate. Native species showed a general preference for somewhat faster, moderate depth water over coarse gravel and had no clear secondary 

preference.

Macroinvertebrate-variables index period, high-flow year, 

and collection location (upper-middle Verde River, lowermiddle Verde River, or Verde River tributaries) were found to 

be important explanatory variables in differentiating among 

community metrics. Overall richness (number of unique 

taxa), Shannon’s diversity index, and the percent of the most 

dominant taxa were all highly correlated, but their response to 

each macroinvertebrate variable was different. The percentage 

of mayfly (order Ephemeroptera) taxa was significantly higher 

in Oak Creek and the upper-middle and lower-middle Verde 

River reaches, locations which have higher flows and more 

urbanization than other reaches. When community metrics 

were related to hydrologic metrics, caddisfly (order Trichoptera) populations appeared to increase and mayfly populations 

to decrease in response to less flashy and more stable streamflows. Conversely, caddisfly populations appeared to decrease 

and mayfly populations to increase in response to greater flow 

variability.

Six locations along the Verde River were sampled for 

macroinvertebrates as part of a pilot study associated with this 

report—(1) below Granite Creek, (2) near Campbell Ranch, 

(3) at the U.S. Geological Survey Paulden gage, (4) at the Perkinsville Bridge, (5) at the USGS Clarkdale gage, and (6) near 

the Reitz Ranch property. A nonmetric multidimensional scaling ordination of macroinvertebrate assemblages showed that 

the Verde River below Granite Creek site was different from 

the five other sites and that the Perkinsville Bridge and near 

Reitz Ranch samples had similar community structure. The 

near Campbell Ranch and Paulden gage locations had similar 

microhabitat characteristics, with the exception of riparian 

cover, yet the assemblage structure was very different. The different community composition at Verde River below Granite 

Creek was likely due to it having the smallest substrate sizes, 

lowest velocities, shallowest depths, and most riparian cover 

of the six sites.

Introduction

The Verde River (fig. 1) is among the largest streams 

in Arizona, providing about 40 percent of the surface water 

delivered to the Phoenix metropolitan area by the Salt River 

Project (The Nature Conservancy, 2009). Its watershed covers 

4.2 million acres in central Arizona, and includes about 500 

miles of perennial streams, including the Verde River, and 

is the only watershed in the State with designated “wild and 

scenic” reaches as described in the Wild and Scenic Rivers Act 

(1968), Public Law 90-542; 16 U.S.C. 1271 et seq. (National 

Wild and Scenic Rivers System, 2016a; National Wild and 

Scenic Rivers System, 2016b). It was listed in the 2006 edition of America’s Most Endangered Rivers (American Rivers, 

2006) based on the apparent threat groundwater pumping 

may pose to Verde River base flows. Historically, at least 13 

native fish species lived in the watershed, including seven that 

are now threatened or endangered (The Nature Conservancy, 

2009). The Verde River watershed supports one-third of the 

breeding areas for the desert-nesting bald eagle (Haliaeetus 

leucocephalus), populations of the southwestern willow flycatcher (Empidonax traillii extimus) and yellow-billed cuckoo 

(Coccyzus americanus), and more than 200 other bird species 

that use the river’s riparian habitat (The Nature Conservancy, 

2009). The flows that occur in the middle Verde River watershed are largely unregulated and are less affected by urban 

use, urban and agricultural runoff, and channelization than in 

the lower Verde River watershed.

The Verde River is central to the way of life for the many 

towns and communities located in the watershed and is part 

of the ancestral home for the Yavapai-Apache Nation, the 

Fort McDowell Yavapai Nation, and other tribes (The Nature 

Conservancy, 2009). Although large parts of the Verde River 

watershed remain undeveloped and are administered by the 

U.S. Forest Service (USFS), there is considerable commercial 

and residential development occurring in the Prescott area 

and in the Verde Valley (Blasch and others, 2006). The related 

population growth will likely result in an increased demand on 

the region’s water resources, and there is concern about how 

these growing human water needs will continue to be met in 

the upper and middle Verde River watersheds while preserving 

its important ecological values (Haney and others, 2008).

For example, the City of Prescott has statutory rights to 

pump up to 14,000 acre-ft of groundwater annually from Big 

Chino Valley, although the Director of the Arizona Department of Water Resources (ADWR) issued a determination in 

2008 that recognized 8,067.4 acre-ft as the annual volume to 

which the City of Prescott is entitled (Arizona Department of 

Water Resources, 2014). Additional groundwater is legally 

available to municipalities in the Prescott AMA as retired 

historically irrigated acres (Arizona Department of Water 
Introduction 3

Resources, 2014). Prescott currently plans to collaborate with 

Prescott Valley to pump water from the Big Chino Valley and 

transport it to their respective municipalities (Marder, 2009; 

Auer, 2010). The Salt River Project, which is the main water 

utility for the metropolitan Phoenix area, has claims to Verde 

River surface water that predate Arizona statehood (Marder, 

2009). Garner and others (2013) found that base flow at the 

Clarkdale gaging station has declined by about 4,900 acre-ft/

yr as a result of human stresses placed on the flow system. For 

the future, model simulations show a decrease in Verde River 

base flow (Garner and others, 2013; Jaeger and others, 2014) 

as well as decreased stream connectivity (Jaeger and others, 

2014). This is the result of both climate forecasts that project 

increased aridity in the southwest (Williams and others, 2010) 

and increased human stress from pumping and diversions 

(Garner and others, 2013). 

Environmental Flows

“Environmental flows” is a term that has gained currency 

over the past 15 years. It has evolved from a focus on minimum flows required for species preservation to one that recognizes the importance of natural flow regimes. It is based on the 

concept that the natural dynamic character of the flow regime 

of a river or stream is necessary to sustain riverine ecosystems intact. Streams altered by human modifications, such as 

dams, diversions, or channel engineering, can also be managed 

to mimic an environmental flow regime that meets ecological and social objectives (Acreman and others, 2014). The 

flow characteristics necessary to sustain riverine ecosystems, 

specifically species’ habitats and thus health and diversity, are 

thus referred to as the river’s “environmental flows.”

To understand the consequences to the ecosystem of various water-use scenarios, it is necessary to understand the system’s environmental flows—the interactions between hydrology and ecology that form the basis for the water needs of the 

ecosystem. Ecosystem water needs include, but are not limited 

to, consumptive use by riparian vegetation and habitat requirements of in-stream biota (fish and macroinvertebrates). The 

hydrologic characteristics that affect ecosystem water needs 

include both streamflow regime (magnitude, frequency, timing, and variability of flow) and groundwater conditions (such 

as depth to groundwater and annual groundwater fluctuations) 

(Poff and others, 2010; Konrad and others 2008a).

The first step in establishing environmental flows is 

to develop scientifically credible estimates of flow regimes 

that sustain properly functioning ecosystems. The natural 

hydrologic regime of a river or stream can be divided into 

four components—floods, high flow pulses, base flows, and 

extreme low flows. Each of these flow components has different ecological functions, and thus all are likely to be important for ecosystem integrity (fig. 2). To represent these flow 

components of the natural flow regime of any stream system, 

measures of magnitude, timing, duration, frequency, and rate 

of change must be developed (Poff and others, 1997). The 

magnitude of an event refers to the volume of water passing 

a given point over a period of time. Timing is the predictability or seasonality of a given magnitude. The duration is the 

amount of time a given magnitude persists. Frequency refers 

to how often a magnitude occurs over a specific period of 

time, and the rate of change is how quickly a flow goes from 

one state to another. Hydrologic alteration can refer to changes 

in any of these components.

Southwestern desert streams, including those of the Verde 

River watershed, are characterized by large variations in flow 

magnitude, including large floods originating from highintensity summer thunderstorms and extended winter frontalprecipitation events (fig. 2; Poff and others, 1997; Blasch and 

others, 2006). However, the Verde River and its tributaries are 

frequently in a base-flow regime—streamflow is supported 

entirely by groundwater discharge to the stream channel, 

including discharge from numerous springs. The spatial 

connectivity of flowing reaches in the Verde River also vary 

seasonally, with more connectivity in the winter and less in the 

late spring and early summer, and this has specific implications for aquatic species (Jaeger and others, 2014). This makes 

the flow regimes of semiarid southwestern streams like the 

Verde River highly dependent on groundwater/surface-water 

interactions, and as a result, groundwater conditions such as 

depth to groundwater and annual groundwater level fluctuations need to be incorporated into any analysis of streamflow.

ELOHA Framework

Flow regime is a primary determinant of the structure 

and function of aquatic and riparian ecosystems. The Ecological Limits of Hydrologic Alteration (ELOHA) is a framework 

that incorporates scientific information on hydrology and 

biotic-habitat requirements with a decision-making process 

based on societal values and management needs (Richter 

and others, 2003; Richter and others, 2006; Poff and others, 

2010). Part of this process includes quantifying flow-ecology 

relations that can be used as the basis for determining environmental flows.

The ELOHA framework is based on a spatially comprehensive hydrologic foundation and generalized flow-ecology 

relations that can be applied across a region to establish 

environmental flow standards. The purpose of environmentalflow standards is to protect entire ecosystems and the range 

of conditions required for the success of aquatic communities 

rather than maintenance of a minimum flow threshold to sustain individual species. Once the hydrologic foundation has 

been defined (fig. 3, step 1) and the river or stream classified 

(fig. 3, step 2), the ecological responses to hydrologic (flow) 

alteration can be defined (fig. 3, step 3). Then explicit societal 

decisions about the level of protection (which can vary by 

river or stream) can be made and administrative mechanisms 

(water permits, land-use planning, water trusts) implemented 

for flow standards (fig. 3, social process) (Poff and others, 

2010). Various studies have addressed steps 1 and 2 (for 

example, Wirt, 2004; Wirt and others, 2005; Blasch and others, 2006; Springer and Haney, 2008; Garner and Bills, 2012). 
4 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

Big Chino

Was h

Walnut Creek

Williamson Va lley

Wash

Granite Creek

Hell Canyon

Oak Creek

Wet Beaver Creek

DryB eaver Creek

We st C lear Creek

Verde

River

09506000

09505800

09505350

09505200

09504500

09504420

09504000

09503700

09503500

09503300

09503000

09502960

09502800

09502750

#

#

##

##

#

# #

#

#

#

#

#

0

0

25

25

MILES

KILOMETERS

111°30'

112°

112°30'

113°

35°30'

35°

34°30'

34°

Base from U.S. Geological Survey 1 arc second, 30 meter, National Elevation Dataset (NED) digital data, 2009

09502800 Williamson Valley Wash near Paulden, AZ

09502900 Del Rio Springs near Chino Valley, AZ

09502960 Granite Creek at Prescott, AZ 

09503000 Granite Creek near Prescott, AZ 

09503300 Granite Creek below Watson Lake near Prescott, AZ

09503700 Verde River near Paulden, AZ 

09504000 Verde River near Clarkdale, AZ

09504420 Oak Creek near Sedona, AZ 

09504500 Oak Creek near Cornville, AZ 

09505200 Wet Beaver Creek near Rimrock, AZ

09505350 Dry Beaver Creek near Rimrock, AZ 

 

 

09505800 West Clear Creek near Camp Verde, AZ

09506000 Verde River near Camp Verde, AZ

Mormon Pocket

Stillman Lake

Paulden

Cottonwood

Camp Verde

Clarkdale

Perkinsville Sedona

Bitt e r

Creek

General study boundary

Hell Canyon subwatershed

Granite Creek subwatershed

EXPLANATION

# USGS streamgaging station and 9-digit station identification

Map area

Sycamore Creek subwatershed

Oak Creek subwatershed

Beaver Creek subwatershed

West Clear Creek subwatershed

Syca m ore Creek

ARIZONA

Figure 1. Map of the Verde River watershed, 

Arizona, including streamgaging stations, 

major towns, and tributary subwatersheds 

that are referred to in this report.
Introduction 5

100

1,000

10,000

10/01/2004 12/01/2004 02/01/2005 04/01/2005 06/01/2005 08/01/2005 10/01/2005

Extreme 

Low flow

Summer runoff 

(convective storms)

Winter runoff 

(synoptic storms)

Floods

Base flow

High flow 

pulses

Winter Spring Summer Fall

Spring runoff

Discharge, in cubic feet per second

Fall

09504000 Verde River near Clarkdale, AZ

Flow generating mechanism

Flow timing or season

Event magnitude, duration, and 

frequency

EXPLANATION

Figure 2. Hydrograph for U.S. Geological Survey streamgage Verde 

River near Clarkdale, AZ (09504000) water year 2005 demonstrating 

flow-regime components. AZ, Arizona.

Social process

Adaptive adjustments

Implementation Environmental

flow standards

Societal

values and

management needs

Ecological data

for each

analysis node

Flow-ecology

hypotheses for

each river type

Analysis of

flow

alteration

Flow data and

modeling

Developed

hydrographs

Baseline

hydrographs River type

Geomorphic

subclassification

Hydrologic

classification

Measures of

flow

alteration

Flow alteration-ecological

response relationships

for each river type

Acceptable

ecological

conditions

Monitoring

Step 1. Hydrologic foundation Step 2. River classification (for each analysis node)

Step 3. Flow alteration (for each analysis node)

Step 4. Flow-ecology linkages

Scientific process

Figure 3. Diagram showing a conceptual model of environmental flows (from Poff and others, 2010).
6 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

The present study addresses step 3, the scientific process of 

defining ecological responses to hydrologic alteration.

Purpose and Scope

The purpose of this report was to compile existing hydrological and ecological data to better understand environmental 

flows in the setting of the middle Verde River watershed. To 

accomplish this, the connection between abiotic and biotic 

ecosystem drivers and how each relates to the factors that 

make up environmental flows in the Verde River was investigated. In addition, hydrologic regime and the associations of 

hydrologic characteristics with biotic communities were quantified. This report summarizes a 3-year project investigating 

the connection between abiotic and biotic ecosystem drivers 

and how each relates to the factors that make up environmental flows in the Verde River (fig. 4). It also quantifies hydrologic regime and the associations of hydrologic characteristics 

with biotic communities. This project consists largely of 

obtaining and summarizing existing biological and hydrological data, as well as conducting initial analyses and pilot studies 

on riparian vegetation characteristics, microhabitat use by 

fish, and macroinvertebrate-community structure. Geomorphic 

features related to habitat were mapped and quantified, and 

mobilization of bed sediments was examined at sites where 

sufficient data were available. Additional related components 

were the evaluation of the Northern Arizona Regional Groundwater Flow Model (NARGFM) as an aid in ecological studies 

and the estimation of monthly streamflow budgets in the Verde 

River and its major tributaries.

Our objectives were to improve understanding of flow 

ecology (hydrology and ecological associations) in semiarid 

watersheds and to develop and quantify associations between 

hydrologic alteration and ecological responses to provide 

a scientific foundation for ecologically sustainable water 

management. The study was intended to serve as a resource to 

other agencies for developing techniques and methods widely 

applicable across the Southwest.

Physical Setting

The Verde River is located in Central Arizona and flows 

for 189 miles from below Sullivan Dam, near the town of 

Paulden, past the towns of Cottonwood and Camp Verde, 

eventually passing through Horseshoe and Bartlett Reservoir, 

and ultimately to its confluence with the Salt River near Fort 

McDowell (The Nature Conservancy, 2009; Garner and others, 

2013; fig. 1). The headwaters begin in the region of largely 

ephemeral washes in the Prescott Valley and Chino Valley area 

and in the Big Chino Wash drainage. Perennial flow begins in 

the upper Verde River just below Sullivan Lake with additions to base flow coming from springs near the confluence 

Stream-bed disturbance

Recharge

Low steady flow

Ground

water

Stream

baseflow

Invertebrates

Fish

Climate

Precipitation

Surface

water

stormflow

Habitat

Temperature

Riparian

vegetation

Birds and

terrestrial

animals

Human

stressors

Pumping

Diversions

Range of event

based flows

Timing and

magnitude

Figure 4. Diagram showing a conceptual model of abiotic and biotic ecosystem drivers.
Surface Water and Groundwater 7

with Granite Creek, about 2 miles downstream of the town of 

Paulden (Springer and Haney, 2008). Major intermittent and 

ephemeral tributaries in this section of the river include Big 

Chino Wash, Williamson Valley Wash, Walnut Creek, Granite 

Creek, and Hell Canyon. The lower-middle Verde River begins 

at the U.S. Geological Survey (USGS) Clarkdale gaging station 

(09504000) (Blasch and others, 2006). Major tributaries in this 

section are Sycamore Creek, Oak Creek, Beaver Creek, and 

West Clear Creek. Perennial flow for the upper 26 miles of the 

Verde River is largely fed by inflow from the Big Chino and 

Little Chino aquifers (Wirt and others, 2005), which underlie 

grasslands to the north, west, and south. Additional groundwater enters the mainstem near Perkinsville and Mormon Pocket 

from consolidated rock aquifers on the southern Colorado Plateau. Streamflow in the lower-middle Verde River is sustained 

by surface runoff, groundwater discharge from the basin-fill 

aquifer in the Verde Valley, and contributions from the tributaries in the lower-middle Verde River watershed (Springer and 

Haney, 2008). In the Verde Valley, the river’s major tributaries are largely fed by springs that drain the C and RedwallMuav aquifers, which collect water above the Mogollon Rim 

(Springer and Haney, 2008).

The upper and middle Verde River watersheds have a 

semiarid climate. Precipitation in central Arizona tends to be 

strongly seasonal, dominated by low-intensity, long-duration 

winter storms and shorter, high-intensity local summer storms 

during the North American monsoon (Adams and Comrie, 

1997; Blasch and others, 2006). As drainage area increases, 

relative magnitude of streamflow generated by intense convective storms decreases (House and Hirschboeck, 1997). Winter 

storms produce the most and largest floods because of stronger orographic effects and more frequent passing of frontal 

storms (House and Hirschboeck, 1997), whereas snowmelt 

in the spring can provide the river with steady high flows. An 

abundance of microclimates exists due to elevation, slope, 

and canyon width and depth, which all affect sun exposure 

in a particular area (Blasch and others, 2006). Detailed and 

comprehensive discussions of Verde River hydrology and its 

ecological associations have been presented by Springer and 

Haney (2008) and Blasch and others (2006).

Surface Water and Groundwater

In establishing environmental flows, all features of the 

stream hydrograph are of interest. Biota are affected by and 

adapted to the full range and timing of flows. Flows can originate from different mechanisms such as synoptic, tropical, or 

convective precipitation events. Discharge changes can also be 

generated by seasonal shifts that will result in snowmelt runoff 

when temperatures increase. In periods of high temperatures 

and low precipitation, groundwater contributions will sustain 

base-flow conditions in the stream channel.

Metrics of flow frequency, rate of change, magnitude, 

and duration can be used in classifying environmental flows 

(fig. 2). The USGS operates multiple stream-gaging stations 

on the upper and middle Verde River and its tributaries from 

Sullivan Dam to below Camp Verde (table 1). The Salt River 

Project operates a low-flow gage at Campbell Ranch near the 

Verde River perennial headwaters. The Yavapai County Flood 

Control District operates flood warning sensors throughout 

the upper and middle Verde River watersheds, including one 

at Perkinsville. Discharge in lower Granite Creek is heavily 

affected by reservoirs near Prescott, and the discharge in the 

Verde River below Camp Verde is affected by diversions in 

Cottonwood. Diversions upstream from the Oak Creek near 

Cornville stream-gaging station (09504500) affect the discharge record there as well.

Surface-Water Hydraulic Models

In-channel stream habitat is closely linked to flow properties. Hydraulic models can be used to predict how those flow 

properties vary with discharge to help assess how in-stream 

habitat is affected by a range of discharges. One-dimensional 

Table 1. U.S. Geological Survey mainstem and tributary streamflow gaging stations in the middle Verde River watershed, Arizona.

Streamgage name Station number Years of record Mean streamflow over period of 

record, in cubic feet per second

Verde River near Paulden, AZ 09503700 48 43

Verde River near Clarkdale, AZ 09504000 49 178

Verde River near Camp Verde, AZ 09506000 34 400

Granite Creek at Prescott, AZ 09502960 16 6

Granite Creek near Prescott, AZ 09503000 32 7

Granite Creek below Watson lake near Prescott, AZ 09503300 12 4

Oak Creek near Sedona, AZ 09504420 29 82

Oak Creek near Cornville, AZ 09504500 67 87

Dry Beaver Creek near Rimrock, AZ 09505350 50 42

Wet Beaver Creek near Rimrock, AZ 09505200 45 32

West Clear Creek near Camp Verde, AZ 09505800 45 61
8 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

hydraulic models have been completed for reaches of the 

Verde River in Clarkdale and Cottonwood. Ross and others 

(2010) constructed a flow model as part of a study of diversions of Verde River water in that area. The model computes 

steady, cross-sectionally averaged stage and velocity as functions of specified discharge. The model was used by Ross and 

others (2010) to examine the effects of stream-flow diversions 

in Verde Valley and included monitoring of water-surface 

levels near diversions.

The Yavapai County Flood Control District commissioned HDR, Inc., to construct a one-dimensional model for 

the reach of the Verde River between the Clarkdale and Camp 

Verde gages, the reach that includes the cities of Clarkdale, 

Cottonwood, and Camp Verde (HDR, Inc., 2011). This model 

was designed and implemented for delineation of flood-inundation levels. In addition to developing the model, HDR, Inc. 

(2011), developed stream-flow statistics for the Verde River to 

supply discharges at specified recurrence intervals.

Groundwater Models

Base flow is a crucial component of environmental flows, 

especially in a watershed with ephemeral and intermittent 

reaches, such as in the Verde River watershed. Groundwater 

discharge to stream courses is the source of base flow, and 

reductions in groundwater discharge will reduce base flow 

and can expand the length of dry reaches and increase persistence of dry reaches over time. Groundwater-flow models 

can be used to study the effects groundwater withdrawals or 

reductions in recharge (such as could result from changes in 

climate) might have on base flow.

The Arizona Department of Water Resources (ADWR) 

developed a groundwater model of the Prescott Active Management Area (PrAMA; Corkhill and Mason, 1995) which has 

since been updated (Nelson, 2002; Timmons and Springer, 

2006). The model domain is bounded by the PrAMA, and does 

not extend into the perennial section of the Verde River near 

the confluence with Granite Creek. The model has been used 

to study predevelopment conditions and the effects of groundwater pumping on groundwater levels within the PrAMA.

Northern Arizona Groundwater Flow Model

The Northern Arizona Groundwater Flow Model 

(NARGFM; Pool and others, 2011) was developed by the 

USGS in response to growing concerns about groundwater 

resources in the northern part of the State. Pool and others 

(2011) list two primary uses for the model—(1) identification 

of data needs and (2) prediction of changes in groundwater 

levels and groundwater discharge to streams, springs, and 

riparian vegetation as a result of groundwater use and management practices. The construction of a numerical model of a 

complicated system provides a rigorous framework for assembling information about the physical system. The groundwater 

model can also be used to predict system responses to changes 

in recharge and groundwater withdrawals over time.

Model Construction

NARGFM extends from Kane County in southern 

Utah to the north, from just east of the California border to 

the west, east into McKinley, Cibola, and Catron County of 

western New Mexico, and south to the Verde River and Salt 

River watersheds (fig. 5). The construction of NARGFM was 

preceded by a study of the upper and middle Verde River 

watershed hydrology (Blasch and others, 2006) in which an 

extensive dataset was compiled that included surface-water 

discharges, groundwater-well levels, precipitation, geochemistry, and geological features. NARGFM predicts groundwater 

contributions to streams but does not include surface runoff 

into streams. Consequently, only changes to base flow can 

be represented by the model; flows that are a direct result of 

snowmelt or precipitation runoff must be considered independently. Major streams are represented in the model, including 

the Verde River and its major tributaries.

The complex geology in northern Arizona is represented 

by three layers in the model. Parameters (hydraulic conductivity, specific storage, and specific yield) and the topography 

and layer thickness vary over the model domain to represent 

variations in hydraulic properties. Model parameters were calibrated primarily with well water levels and streamflow data. 

The calibration process and results are extensively described 

by Pool and others (2011), with comparisons between model 

predictions and data. Areas where information is sparse 

become especially apparent in the calibration process if 

information is insufficient to define parameter values to within 

reasonable ranges. Pool and others (2011) describe in detail 

where and what types of new data would improve the model 

calibration. Model limitations are also discussed in detail.

The model has both steady-state and transient applications. The steady-state version has no time dependence and 

computes an equilibrium condition; this application was used 

to retrodict predevelopment conditions in 1910. The transient 

applications (model predictions vary in time in response to 

varying recharge and pumping stresses) were applied from 

1910 to 2006.

Use of NARGFM for Environmental Flow Studies

Spatial Resolution

NARGFM-predicted near-channel water levels could be 

a guide for general response of near-stream water levels to 

varying stresses but on a scale appropriate for the model (fig. 

6). The model cannot represent steep gradients nor variations 

in near-stream water levels on a scale smaller than the 1-kilometer (km) grid due to purely numerical considerations (fig. 

6). In other words, NARGFM would be useful for evaluating 

kilometer (or greater) scale trends but not for subkilometer 

scale trends. In addition, Quaternary alluvium is not included 

in the model, and stream-aquifer properties are represented in 

the model on an even coarser spacing than the grid spacing. 

Consequently, the model can reasonably predict near-stream 
Surface Water and Groundwater 9

34o

112o

0 50 KILOMETERS

0 50 MILES

Base from U.S. Geological Survey

digital data, 1:100,000, 1982

Universal Transverse Mercator

projection, Zone 12

Flagsta

Gallup

Prescott

N A V A J O

C O U N T Y

A PA C H E

C O U N T Y

C I B O L A C O U N T Y

G I L A

C O U N T Y

YA V A PA I A

C O U N T Y

M O H A V E

C O U N T Y

C O C O N I N O

C O U N T Y

Prescott

Active

Management

Area

MCKINLEY

COUNTY

CATRON CO UNTY

40

ELEVATION, IN METERS

ABOVE NGVD:

EXPLANATION

3,850

2,500

2,000

1,500

1,000

500

230

3,000

3,500

40

17

Camp Verde

36o

110o

C rad o o o

l

Ri r ve

Phoenix Metropolitan Area

Upper and middle Verde River watersheds study area

Mogollon Rim

Sedona

Willians

Payson

Cottonwood

Clarkdale

K A N E

C O U N T Y

U TA H

A R I Z O N A

A R I Z O N A

NEW M E X I C O

C

tle it L

Riv re

S

R

V

r Ri ve

erde

alt

iv r e

o a

od or l

C

River

o

ado

or l

ARIZONA

Upper and middle 

Verde River 

watersheds 

study area 

Figure 5. Map of northern Arizona showing area covered by the Northern Arizona Regional Groundwater Flow Model.
10 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

water levels over a minimum scale of no less than several 

kilometers.

Temporal Resolution

When operating in transient mode (time varying), the 

USGS Modular Finite-Difference Flow Model (MODFLOW) 

allows the user to specify both stress periods and time steps. A 

stress period is a time during which a set of boundary conditions, or model inputs such as recharge or well pumping, are 

held constant. A new set of boundary conditions is typically 

specified in succeeding stress periods. A time step is a timedependent solution over a time equal to or less than the stress 

period. Having time steps smaller than the stress period allows 

the model to better represent the time derivatives in the governing equations with its numerical approximation.

The transient NARGFM starts with conditions that 

occurred in 1910 followed by a transient period extending 

from 1910 to 1938. Subsequent stress periods are 10 years, 

except for the last, which is 6 years long. The stress periods 

are further divided into five time steps of varying length. The 

model does not represent any seasonal variations and only 

represents groundwater contributions to streamflow.

NARGFM Stream-Flow Predictions

Because NARGFM predicts groundwater contributions to streamflow, base flow can be estimated from model 

results. However, some of the hydrograph components that 

are important for ecological considerations are not represented 

by the NARGFM model. Variations in streamflow that results 

from storms must be considered independently of NARGFM. 

Survey locations near Reitz Ranch

Flow direction

1 kilometer

1 kilometer

Verde River

Figure 6. Aerial photograph showing the length of an example sampling site near Reitz Ranch on the Verde River, Arizona, relative to 

the Northern Arizona Regional Groundwater Flow Model grid spacing. The red pixels are sample survey points, whereas the white lines, 

which are 1 kilometer apart, show the computational grid used by the model.
Surface Water and Groundwater 11

The alluvial aquifer, which generally consists of more permeable loosely consolidated fluvial sediments, is not represented 

in the model, either. Consequently, the interactions between 

streamflow and groundwater occur on a larger scale consistent 

with the hydraulic properties of the aquifer; modifications to 

local streamflow that are a result of groundwater flow through 

alluvial sediments are not part of the model.

The model predicts stream reaches on the scale of kilometers that gain flow from groundwater, lose flow to groundwater, or are dry (table 2; fig. 7). The interaction between 

groundwater and streamflow predicted by the model are the 

average conditions during the model time step. The model 

predicts some increase in losing and dry reaches between the 

end of the initial steady-state time period ending in 1910 (fig. 

7A) and the end of the transient time period ending in 2006 

(fig. 7B). For example, the model predicts dry reaches in Wet 

Beaver Creek in 2006 that were generally perennial in 1910.

Estimates of Monthly Streamflow at Ungaged 

Locations

Streamgages are located on the middle and upper Verde 

River and some of its tributaries, but other tributaries and 

subbasins are ungaged (fig. 1). Consequently, tools to estimate 

streamflow at ungaged sites can be useful for filling in spatial 

gaps in discharge records at study sites. In this study, we used 

results from two existing models, the Basin Characteristic 

Model (BCM; Flint and Flint, 2007) and NARGFM (Pool and 

others, 2011) to estimate monthly streamflow at ungaged subbasins in the Verde River watershed.

Streamflow can be divided into two components—base 

flow and storm-generated runoff. Base flow can vary over 

time in response to variations in large-scale natural or artificial 

recharge or in response to groundwater pumping. Base flow 

can vary spatially as a result of the accumulation of groundwater inflow along a channel, variability in geologic strata adjacent to a river, and local variations in the shape and volume 

of an alluvial aquifer. Storm-generated runoff results from the 

accumulation of overland flow during storms and generates 

streamflow responses on a smaller time scale than base-flow 

responses to regional groundwater flows.

The BCM provides distributed estimates of potential evapotranspiration, soil moisture storage, and in-place 

recharge and in-place runoff (Flint and Flint, 2007). “In place” 

refers to model predictions of infiltration and runoff in a cell; 

flow is not routed by the model over the land surface or into 

the subsurface. Model predictions are based on vegetation, 

topography, geology, soil properties, and precipitation and 

temperature estimates. The precipitation and temperature 

inputs to the BCM are derived from Parameter-Elevation 

Regressions on Independent Slopes Model (PRISM) estimates 

(Daly and others, 1994). The BCM operates on a 270-km grid 

and a monthly time step. The BCM predictions of in-place 

infiltration have been used to provide recharge inputs for 

groundwater modeling and for initial recharge estimates that 

were modified during the calibration process of NARGFM 

(Pool and others, 2011). Flint and others (2012) developed 

a water budget for the San Diego River basin that incorporated BCM estimates of both recharge and runoff, and the 

runoff component was used to estimate monthly streamflow 

at ungaged sites. In this study, BCM predictions of in-place 

runoff were used to estimate monthly streamflow at ungaged 

sites in the tributaries of the upper-middle and lower-middle 

Verde River between 1940 and 2006. The same BCM output 

(that included both in-place recharge and in-place runoff) used 

by Pool and others (2011) for initial estimates of recharge was 

used for this study.

NARGFM routes groundwater flow into streams, and 

model predictions can be directly used to estimate base flow 

(table 3). The Verde River, Oak Creek, Wet Beaver Creek, 

and West Clear Creek are represented in NARGFM with the 

MODFLOW Streamflow package (Prudic and others, 2004). 

The Streamflow package tracks inflow and outflow between 

a stream path and groundwater flow, and modeled predictions 

of base flow can be directly extracted from the Streamflow 

package output. Other tributaries, including Hell Canyon and 

Sycamore Creek, are not included in the current version of 

NARGFM. Adding other tributaries to NARGFM was beyond 

the scope of this project, but would be a straightforward process for studies focused on those areas.

Initial estimates of monthly streamflow were obtained 

by summing up BCM predictions of in-place runoff at each 

cell along stream paths defined by topographic gradients 

Type of 

streamflow 1910 2006 Difference Percent difference

Gaining 721 664 –57 –8

Losing 549 552 3 0.5

Dry 348 402 54 14

Table 2. Numbers of model stream cells predicted by the 

Northern Arizona Groundwater Flow Model to be gaining, losing, 

or dry in reaches of the upper-middle and lower-middle Verde 

River, Arizona, in 1910 and 2006.

Location Base flow, in cubic 

feet per second

Oak Creek near Sedona gage 20

Oak Creek confluence 10

Wet Beaver Creek gage 1.5

Wet Beaver Creek confluence 1

West Clear Creek gage 17

West Clear Creek confluence 7.3

Table 3. Base flows in cubic feet per second determined by 

the Northern Arizona Groundwater Flow Model and used in 

the monthly streamflow estimates for the middle Verde River 

watershed, Arizona.
12 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

Camp Verde

Cottonwood

Flagstaff

Sedona

Oak Creek

Verde River

Prescott

Wet Beaver Creek

We st C lear Creek

112°44'

34°19'

112°31' 112°05' 111°52' 111°26' 111°13'

34°41'

34°30'

34°52'

35°14'

35°03'

35°25'

Gaining reach

EXPLANATION

Losing reach

Dry reach

Model-predicted aquifer-stream interaction 1910

112°18' 111°39'

A

Figure 7. Latitude/longitude-gridded images of Northern Arizona Groundwater Flow Model predictions of groundwater-streamflow 

interactions on river reaches in the middle Verde River watershed, Arizona, showing reaches in (A) 1910 and (B) 2006 that were gaining 

discharge or losing discharge to groundwater and reaches that were dry.

Camp Verde

Cottonwood

Flagstaff

Sedona

Gaining reach

EXPLANATION

Losing reach

Dry reach

Verde River

Prescott

112°44'

34°19'

112°31' 112°05' 111°52' 111°26' 111°13'

34°41'

34°30'

34°52'

35°14'

35°03'

35°25'

Model-predicted aquifer-stream interaction 2006

112°18' 111°39'

B

Oak Creek

Wet Beaver Creek

West Clear Creek
Surface Water and Groundwater 13

using ArcGIS. Text files containing monthly BCM potential 

runoff data from 1940 to 2006 for the southwestern United 

States were converted to grids using a geographic information system (GIS) conversion tool. To decrease processing 

time, each potential-runoff grid was clipped to the study area 

boundary (fig. 8). A GIS flow-accumulation tool was then used 

to compute a weighted flow-accumulation grid for each month 

using a National Hydrography Dataset Plus flow direction grid 

(U.S. Environmental Protection Agency and the U.S. Geological Survey, 2006). A standard flow-accumulation grid is 

calculated using a flow direction grid to count the number of 

cells upstream of a given cell, giving each upstream cell equal 

weight. Using a potential-runoff grid to apply a weight to 

each cell in the flow-direction grid produces a weighted flowaccumulation grid that models a continuous surface model of 

accumulated potential runoff but does not account for interception, infiltration, or evaporation. A GIS tool to extract cell 

values at specified locations was then used to obtain accumulated potential-runoff data from the monthly weighted flowaccumulation grids for points of interest.

Various processes, such as the temporary storage of 

precipitation as snow or infiltration of runoff down-gradient, 

can affect the timing and magnitude of streamflow derived 

from the predicted in-place runoff. Because the BCM predicts in-place runoff and not streamflow, adjustment of the 

summed BCM predictions was required. The streamgages at 

Oak Creek near Sedona, and Wet Beaver Creek, Dry Beaver 

Creek, and West Clear Creek were used for the calibration. 

Gages on Granite Creek and Oak Creek near Cornville were 

not used because they are affected by reservoirs and diversions. The monthly gage data over the period of record minus 

the local base flow from NARGFM was plotted as a function 

of the BCM predictions at that gage location. Lines were fit to 

the plotted data for each month over the period of record and 

were used as corrections for the BCM predictions (table 4). 

A linear trend line constant of 0 was initially tried in all four 

locations and retained in three. A nonzero constant can cause 

a step change in calculated flow if the BCM predicts runoff 

for a particular month. The step change can be especially 

significant if the base flow is low or 0. Reasonable fits could 

not be achieved at Oak Creek near Sedona without a constant 

added, so the constant was included in the line equation for 

that site. In one case with considerable scatter in the relation 

between streamgage data and BCM predictions at Wet Beaver 

Creek, a linear fit produced poor results, and a power fit was 

substituted. During some months at some streamgages, there 

was insufficient flow in excess of base flow to fit a line, and 

the monthly predicted total streamflow is estimated to be base 

flow.

Adjusted BCM values were computed and the 

NARGFM-derived base flow added to form the predicted 

monthly streamflow from the combined NARGFM and BCM 

predictions (fig. 9). The Nash-Sutcliffe Efficiency Coefficient 

(Nash and Sutcliffe, 1970) was used to test the predictive 

power of the combined NARGFM and BCM results (table 5). 

This coefficient can vary between negative infinity and 1. Negative values indicate that the data mean is a better predictor 

than the model results. An efficiency of 1 indicates a perfect 

fit of the data to the model, whereas an efficiency of 0 indicates that the model results are as accurate as the data mean. 

An efficiency between 0 and 1 then indicates that the modeled 

values are positively correlated with measured values, and the 

closer the efficiency is to 1 the stronger the correlation. NashSutcliffe Efficiency Coefficients for four tributaries varied 

from 0.49 to 0.72 (Dry Beaver Creek monthly streamflow was 

predicted from BCM only).

Month

Oak Creek near Sedona Dry Beaver Creek Wet Beaver Creek West Clear Creek

C S R2 C S R2 C S R2 C S R2

1 -5.2 1.31 0.52 0 2.06 0.57 0 15.45 0.59 0 3.14 0.57

2 -5.8 1.45 0.8 0 1.77 0.66 0 1.38 0.15 0 1.39 0.75

3 57.48 0.58 0.59 0 1.03 0.49 82.11* 0.14* 0.23 0 0.75 0.47

4 75.76 0.07 0.1 0 0.4 0.16 0 0.32 0.15 0 0.31 0.32

5 4.8 0.03 0.59 0 0.11 0.44 0 0.08 0.51 0 0.1 0.51

6

7

8 0 3.63 0.94 0 1.13 0.75

9 11.07 0.59 0.86 0 4.43 0.85 0 3.69 0.22

10 8.03 0.07 0.34 0 1.04 0.93 0 1.88 0.77

11 -8.09 0.89 0.75 0 1.27 0.51 0 0.52 0.41

12 -59.38 2.38 0.7 0 2.73 0.29 0 2.41 0.43

Table 4. Calibration coefficients used to relate combined Northern Arizona Groundwater Flow Model and Basin Characteristics Model 

predictions of local runoff to streamgage data for the middle Verde River watershed, Arizona.

[Fits are linear except where noted. The line constant is represented by C, the slope (or exponent in one case) is represented by S, and R-squared, the standard indicator 

of goodness-of-fit, R2. Blank spaces indicate insufficient runoff was measured or predicted to generate a relation. *, Values represent the constant and exponent in a 

power function]
14 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

EXPLANATION

Accumulated potential runoff

0

0

25

25

MILES

KILOMETERS

111°30'

112°

112°30'

113°

35°30'

35°

34°30'

34°

Base from U.S. Geological Survey 1 arc second, 30 meter, National Elevation Dataset (NED) digital data, 2009

Map area

ARIZONA

Figure 8. Map image showing weighted flow-accumulation grid generated from Basin Characteristics Model predictions of local 

runoff for February 1993 for the middle Verde River watershed, Arizona.
Riparian Vegetation 15

The combined NARGFM and calibrated BCM values 

were used to estimate total monthly discharges at ungaged 

sites in subbasins of the Verde River where the tributaries are 

included in NARGFM (Wet Beaver Creek and West Clear 

Creek), and the calibrated BCM values were used to estimate runoff values in tributaries that are not represented in 

NARGFM (Hell Canyon and Sycamore Creek) (fig. 1). The 

combined NARGFM base flows and calibrated BCM runoff 

predictions of monthly streamflow and streamgage data were 

used to compute exceedance discharges at the 80th, 50th, and 

20th percentiles (figs. 10–13). The computed values generally show better agreement with streamgage data at the two 

streams with higher base flow and discharges (Oak Creek 

near Sedona and West Clear Creek). With the accumulations 

of BCM predicted local runoff and with monthly calibration 

functions, smaller-scale basin monthly runoff could then be 

estimated at locations of interest (fig.14).

Hydrologic simulation resolution is always a factor in 

assessing streamflow alteration and determining the environmental flows appropriate to the scale of the measured ecology. 

Regional-scale models at the monthly time step can assist with 

regard to climate-scale impacts on streamflow and species 

distributions, whereas high-resolution models can address 

effects to reach-scale assemblages. Both can be leveraged to 

provide a comprehensive picture of changing ecosystems, 

while balancing the conservation of water for long-term 

human needs (Caldwell and others, 2015). Regardless of the 

approach, the hydrologic simulation is only as accurate as the 

hydrogeological understanding and the surface-water, groundwater and climate data that go into the model. The long time 

step of the BCM and NARFGM provide stream averages that 

cannot capture the variability in magnitude and duration of 

runoff events, particularly in watersheds with highly variable 

discharge such as that of the Verde River. Many processes 

relevant to in-steam ecology and thus environmental flows 

more generally, such as sediment transport, involve discharge 

thresholds and nonlinear responses to streamflow. Many other 

regions in United States can use monthly streamflow estimates 

in environmental flows studies (Herkinson and others, 2006; 

Archfield and others, 2014; Kennen and others, 2014), but 

the constraints of this ecological dataset require streamflow 

data recorded at daily or shorter time steps in order to relate 

streamflow to in-stream habitat.

Riparian Vegetation

Riparian forests (forests along river corridors) occupy 

less than 2 percent of the land area in the southwestern United 

States and less than 1 percent of the desert landscape but are 

generally considered the most productive and valuable land 

in the region (Folliott and others, 2004; Kirkpatrick, 2008). 

Riparian areas are critically important for wildlife (DeBano 

and Schmidt, 2004). For example, riparian woodlands support more than 50 percent of the breeding birds in the desert 

southwest (Kirkpatrick and others, 2008). The Verde River 

EXPLANATION

Year

0

1982 1987 1993 2004

200

400

600

800

1,000

1,200

1,400

1,600

1,800

Discharge, in cubic feet per second

Gage data

NARGFM and uncalibrated BCM

NARGFM and calibrated BCM

Figure 9. Example hydrograph showing monthly streamgage 

data at the Oak Creek near Sedona gage compared to 

combined Northern Arizona Groundwater Flow Model 

(NARGFM) base flow and uncalibrated Basin Characteristics 

Model (BCM) local runoff predictions and combined NARGFM 

base flow and calibrated BCM predictions.

Table 5. Nash-Sutcliffe efficiency coefficients 

for the fit of the combined Northern Arizona 

Groundwater Flow Model and calibrated Basin 

Characteristics Model predictions with respect 

to streamgage data for the middle Verde River 

watershed, Arizona.

Location Coefficient

Oak Creek near Sedona 0.72

Dry Beaver Creek 0.66

Wet Beaver Creek 0.49

West Clear Creek 0.64
16 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona Discharge, in cubic feet per second Discharge, in cubic feet per second Discharge, in cubic feet per second

Month

1 2 3 4 5 678 9 10 11 12

0

20

40

60

80

100

120

0

20

40

60

80

100

120

140

160

180

200

0

50

100

150

200

250

300

350

400

450

Gage data

BCM and NARGFM

EXPLANATION

A

B

C

Discharge, in cubic feet per second Discharge, in cubic feet per second Discharge, in cubic feet per second

Month

0

2

4

6

8

10

12

14

16

18

0

5

10

15

20

25

30

35

40

45

50

0

20

40

60

80

100

120

140

160

180

200

1 2 3 4 5 6 7 8 9 10 11 12

Gage data

BCM

EXPLANATION

A

B

C

Figure 10. Graph showing monthly streamflow statistics 

at the Oak Creek gage in the middle Verde River watershed, 

Arizona, determined from gage data and combined Basin 

Characteristics Model (BCM) and Northern Arizona 

Groundwater Flow Model (NARGFM) predictions. The 

plots show the (A) 80-, (B) 50-, and (C) 20-percent monthly 

exceedance discharges.

Figure 11. Graph showing monthly streamflow statistics at the 

Wet Beaver Creek gage in the middle Verde River watershed, 

Arizona, determined from gage data and combined Basin 

Characteristics Model (BCM) and Northern Arizona Groundwater 

Flow Model (NARGFM) predictions. The plots show the (A) 80-, (B) 

50-, and (C) 20-percent monthly exceedance discharges.
Surface Water and Groundwater 17

Discharge, in cubic feet per second Discharge, in cubic feet per second Discharge, in cubic feet per second

Month

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

0

20

40

60

80

100

120

140

0

50

100

150

200

250

300

14

1 2 3 4 5 6 7 8 9 10 11 12

Gage data

BCM

EXPLANATION

A

B

C

Gage data

BCM and NARGFM

Discharge, in cubic feet per second Discharge, in cubic feet per second Discharge, in cubic feet per second

Month

1 234 5 6 7 8 9 10 11 12

0

5

10

15

20

25

30

35

0

20

40

60

80

100

120

140

0

50

100

150

200

250

300

350

EXPLANATION A

B

C

Figure 12. Graph showing monthly streamflow statistics at the Dry 

Beaver Creek gage in the middle Verde River watershed, Arizona, 

determined from gage data and Basin Characteristics Model (BCM) 

predictions. The plots show the (A) 80-, (B) 50- , and (C) 20-percent 

monthly exceedance discharges.

Figure 13. Graph showing monthly streamflow statistics 

at the West Clear Creek gage in the middle Verde River 

watershed, Arizona, determined from gage data and 

combined Basin Characteristics Model (BCM) and Northern 

Arizona Groundwater Flow Model (NARGFM) predictions. The 

plots show the (A) 80-, (B) 50-, and (C) 20-percent monthly 

exceedance discharges.
18 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona Discharge, in cubic feet per second Discharge, in cubic feet per second Discharge, in cubic feet per second

Month

0

10

20

30

40

50

60

70

80

90

100

0

50

100

150

200

250

300

350

0

200

400

600

800

1,000

1,200

1,400

1234567 8 9 10 11 12

Hell Canyon

Sycamore Creek

Oak Creek

Wet Beaver Creek

West Clear Creek

EXPLANATION

A

B

C

watershed contains some of the most extensive acreage of 

Fremont cottonwood (Populus fremontii)-Goodding willow 

(Salix gooddingii) forest—found only in the southwestern 

United States and Mexico—and mixed broadleaf riparian 

forest in Arizona. The current, relatively unregulated flow 

of the Verde River means the riparian vegetation is of mixed 

ages. Mixed-age stands are instrumental to increasing forest 

resiliency and act as key areas where studies can be conducted 

on the conditions needed for tree establishment. The Verde 

River watershed is home to special-status species such as the 

yellow-billed cuckoo and the southwestern willow flycatcher 

(Stevens and others, 2008). The plant communities of the 

Verde River watershed that support these rare birds are subject 

to the same stresses that are changing plant communities 

throughout the Southwest, such as increasing pressures from 

agriculture and population density, as well as small-scale river 

regulation through the use of irrigation ditches. Work on other 

streams has shown that changing the natural flow regime of a 

river affects both aquatic and riparian species (Poff and others, 

1997; Stromberg and others, 2007).

Riparian forest response to streamflow regime and depthto-groundwater fluctuations have been extensively studied 

in southwestern rivers. Reduced base flow is known to alter 

aquatic habitat, with some reaches changing from perennial to 

intermittent (Haney and others, 2008). In addition, the average 

annual depth from the land surface to saturated soils typically increases as base flow declines. Under these conditions 

it is hypothesized that there will be declines in willow and 

cottonwood abundance, decreases in structural diversity, and 

increases in non-native species such as tamarisk (Stromberg, 

1993, 2008; Shafroth and others, 1998; Stromberg and others, 

2007). Such vegetation changes would likely cause shifts in 

the bird community, with reductions or loss of some species.

The main woody riparian species found within the 

study area (described below) included Fremont cottonwood, 

Goodding’s willow, Arizona cypress (Cupressus arizonica), 

Colorado pinyon pine (Pinus edulis), Utah juniper (Juniperus 

osteosperma), and mesquite forests of velvet mesquite (Prosopis velutina), screwbean mesquite (Prosopis pubescens), 

and honey mesquite (Prosopis glandulosa). Cattail (Typha 

spp.) were also prevalent in the study area. Non-native species 

including Russian olive (Elaeaganus angustifolia), giant cane 

(Arundo donax), tamarisk or salt cedar (Tamarix ramosissima), and tree of heaven (Alianthus altissima) also occur in 

the study area.

Life Histories and Ecological Needs of 

Cottonwood and Willow Species 

Individual trees in cottonwood-willow gallery forests that 

grow along low-elevation rivers in the southwestern United 

States typically have a life span of 100 to 150 years (Stromberg, 1993). Cottonwood and willow trees are obligate phreatophytes–they have deep roots and will only grow in areas 

where they have constant access to groundwater (DiTomaso, 

Figure 14. Graph showing monthly streamflow statistics at 

tributary confluences in the middle Verde River watershed, 

Arizona, determined by Northern Arizona Groundwater Flow 

Model (NARGFM) predictions of base flow, where available, 

and calibrated Basin Characteristics Model (BCM) predictions 

of runoff. The plots show the (A) 80-, (B) 50-, and (C) 20-percent 

monthly exceedance discharges.
Riparian Vegetation 19

1998). Both cottonwoods and willows are also pioneer species, 

meaning they can colonize disturbed areas; flooding is the 

main disturbance in the areas where they grow. Both species 

are prolific seed producers, reproducing mostly by seeds rather 

than asexually, although both species can sprout shoots from 

buds on branches laid out by floods. Germination is timed to 

coincide with large flood events during the spring and early 

summer, which helps seedlings to establish above the zone of 

frequent subsequent flooding (Stromberg, 1993). Recruitment 

(seedling survival to maturity) typically occurs once every 10 

to 15 years with some geographic variability. Both Fremont 

cottonwood and Goodding’s willow seeds are viable for 1 to 

5 weeks after dispersal and germinate in 24 to 48 hours once 

proper conditions have been met (moist, unvegetated mineral 

soil or alluvium) (Fenner and others, 1984, 1985; Stromberg, 

1993). Drought and summer and fall floods are the main 

causes of mortality for both cottonwood and willow seedlings (Stromberg, 1993). Several studies have suggested that 

a water-table drop of about 1.5 meters (m) can result in adult 

cottonwood mortality (Stromberg and others, 1996; Scott and 

others, 1999; Shafroth and others, 2000).

Non-native Riparian Species

Non-native riparian species compete with native species 

for sites with access to water and can cause broader changes 

in the riparian community. The most abundant non-native tree 

species on the Verde River was Russian olive. Russian olive 

was the most abundant non-native tree in this area probably 

due to the higher elevation in the upper-middle Verde River, 

resulting in cold winter temperatures that meet Russian olive’s 

chilling requirement for seed germination and bud break 

(Guilbault, 2011; Shafroth and others, 2010a). The phenological (seasonal lifecycle) and reproductive needs of Russian 

olive are not well understood; however, it is known to spread 

rapidly once established, competing for space with native vegetation. As a result, Russian olive is a threat to the rare gallery 

forests of the Verde River and is thus a significant management concern.

Other major vegetation-management concerns include 

giant cane, tamarisk or salt cedar, and tree of heaven. Relative 

percentages of all the different non-native species are currently 

unknown, although the Friends of the Verde River Greenway 

have done some mapping of their location and extent along 

specific reaches of the river (Fred Phillips Consulting, 2011). 

Tamarisk on the Verde River was found to make up about 8 

percent of the total plant community, which is a relatively 

small percentage compared to the extent of tamarisk’s range in 

other western riparian corridors (Johnson and others, 2009). 

Tamarisk is a halophyte, a drought- and salt-tolerant 

plant that can complete its entire life cycle under saline 

conditions. Some work suggests that tamarisk can negatively 

affect aquatic macroinvertebrates (Bailey and others, 2001; 

Webb and others, 2007). Both cottonwood and willow trees 

are glycophytes—they prefer soils with minimal salt content. 

Past studies have shown these species experience upwards of 

50-percent reduction in growth when soil salinity reaches 5 

grams per liter (g/L) (Glenn and others, 1998; Shafroth and 

others, 2010a). Johnson and others (2009) reported that in the 

upper-middle Verde River watershed, areas where tamarisk 

grew had higher abundance of all plant species than areas 

where tamarisk did not grow. This suggests that tamarisk may 

be subjected to the same limiting factors to growth as other 

plants. In the study area, tamarisk has been noted growing 

in the cottonwood understories (beneath the forest canopy), 

which is not a typical pattern for the species (Shafroth and 

others, 2010a).

Cottonwood trees have been shown to have complex 

symbiotic relations with mycorrhizal fungi that grow on their 

roots and assist in nitrogen fixation in exchange for other 

nutrients (Beauchamp and others, 2005). Beauchamp and others (2005) found that tamarisk grown in pots with cottonwood 

had a 15-percent reduction of pot biomass when inoculated 

with mycorrhizal fungi; this may tend to limit tamarisk growth 

near established cottonwoods.

Giant cane is part of the Arundineae family thought to 

be native to eastern Asia. It is one of the largest grass species 

and is abundant along the Verde River, especially along Oak 

Creek. It is a clonal plant that grows densely and can out compete other plants. The non-native species group of the World 

Conservation Union lists giant cane in the top 100 “worst 

invaders of the world” (Lowe and others, 2000). Giant cane is 

a hydrophyte; it grows best near water and is adapted to living 

in waterlogged soil (California Invasive Plant Council, 2011). 

Under laboratory settings, it was found that leaf defoliation or 

leaf damage did not significantly affect or alter the growth of 

giant cane (Spencer, 2012). Potential vegetative destruction 

that results from the tamarisk leaf beetle (Diorhabda spp.) 

and biological controls for Russian olive (the subject of U.S. 

Department of Agriculture research) may create more ecological and physical room for other non-native plants such as giant 

cane (rather than for just native species); it is thus possible that 

giant cane could become more widespread in the middle Verde 

River watershed in the future.

Assessment of Current Riparian Vegetation 

Status

Division of Reaches

The physical area of the vegetation study extended from 

river mile 191 at the headwaters of the Verde River (below 

Granite Creek confluence) to mile 109, just below Camp 

Verde. Analysis was also conducted on two tributaries below 

Clarkdale—Oak Creek, where the vegetation survey was conducted at a transect 17.5 miles upstream from the confluence 

with the Verde River, and West Clear Creek, where analysis 

was conducted at a transect 11 miles upstream from its confluence with the Verde River.

For the purposes of the vegetation analysis, the study area 

on the Verde River was divided into two sections, one above 
20 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

and the other below the town of Clarkdale, Arizona (uppermiddle reach and lower-middle reach, respectively). This 

designation was made because of the differences in land use, 

elevation, and sinuosity between the upper and lower section 

of the study area. The upper-middle reach is from Sullivan 

Dam, near the Verde headwaters, to the town of Clarkdale, 

covering river miles 191 to 144. In the upper-middle reach, the 

river starts in a broad floodplain, then enters narrow, winding canyons and has nine tributaries entering the main stream. 

Most of the human population along the upper-middle reach is 

near Chino Valley, and there is little habitation along the rest of 

this section.

The lower-middle reach extends from the town of Clarkdale to the town of Cottonwood, covering river miles 143 to 

109. Below Clarkdale, the river is wider than in the upper-middle reach. There are eleven tributaries along this reach and the 

towns of Clarkdale, Cottonwood, and Camp Verde are located 

here, making the lower-middle reach the more populated of the 

two study reaches. The general land uses in this reach are agriculture, recreation, and residential (Hazelton, 2011). Some of 

the agricultural land has been converted to private residences 

that retain their agricultural water right.

Remote Sensing of Evapotranspiration

Remote sensing of evapotranspiration (ET) is a useful 

tool for land managers interested in vegetation change through 

time. Products from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat sensors provide free satellite 

imagery and were used for this study. Collection of ground 

data for calculating ET or leaf area index on the Verde River 

were beyond the scope of this study. Measurements such as the 

enhanced vegetation index (EVI) are effective measurements 

of plant vigor in the study area. This study uses the MODIS 

instrument on the Aqua satellite to calculate EVI, which is 

then used to calculate ET (fig. 15A and B). EVI is a measure 

of greenness but has the advantage of not getting saturated at 

higher levels of greenness (Huete and others, 2002). At the 

time of download, MODIS EVI data (MOD13Q1 from Oak 

Ridge National Laboratory, http://daac.ornl.gov/) were available from day of year (DOY) 49 of 2000 to DOY 65 of 2012.

Imagery

Orthoimagery was obtained from Yavapai County in 2010 

for the area of the Verde River that extends from just above 

Clarkdale to Sycamore Creek East and in 2007 for Oak Creek 

and Wet Beaver Creek. The resolution of the Yavapai County 

orthoimagery is 0.5 feet (ft). Dense areas of vegetation were 

assumed to be mixed stands of cottonwood, willow species, 

and possibly non-native plants such as tamarisk. For areas 

of the Verde River north of Clarkdale and West Clear Creek, 

where imagery was not available from Yavapai County, aerial 

imagery was obtained by importing Bing Maps into ArcMap 

10. These aerials have slightly coarser resolution and a different projection than the Yavapai County aerials, and digitizing 

methods were adjusted accordingly. The time of year these 

aerial images were obtained is unknown. Based on the greenness of vegetation species such as mesquite, it is assumed that 

the images were taken during a time of year with rapid growth. 

Deep, incised channels with high, steep banks of some parts of 

the upper-middle Verde River caused much of the vegetation to 

be shaded, reducing accuracy when digitizing those areas.

Ground-truthing was conducted at Tuzigoot National 

Monument (along the Verde River near Clarkdale), Dead 

Horse Ranch State Park (along the Verde River near Cottonwood), and Campbell Ranch (near the Verde River headwaters). Ground-truthing was done in July, September, and 

December of 2011 by identifying plant species, marking 

their locations with a Global Positioning System (GPS) and 

then importing those points into ArcMap and comparing the 

ground-identified vegetation with the map imagery.

Vegetation Digitizing and Classification

Vegetation along the Verde River in the study area was 

identified from the imagery within a buffer extending out 

328 ft (100 m) from both sides of the wetted channel. At 

locations where the channel split, one polygon encompassed 

both branches of the wetted channel. Seven vegetation classifications were used—mesquite, cottonwood, mixed canopy, 

mixed shrub, pinyon-juniper, agriculture, and emergent aquatic 

vegetation (table 6).

Vegetation class Description

Mesquite (Prosopis spp.) dominant Dead and brushy appearance; may include other shrubs and subtrees.

Cottonwood (Populus spp.) dominant Tallest trees observed with large, readily identifiable shadows and distinctive shapes.

Mixed canopy Mixed species growing in close proximity, including willow (Salix spp.). Includes trees that could 

not be accurately identified individually.

Mixed shrub Appear similar to mesquite trees but smaller and of mixed species.

Pinyon-juniper

(Pinus spp. and Juniperus spp.)

In the uplands areas, circular and dark green.

Agriculture Includes both planted and fallow fields; both were assumed to be in use. 

Emergent aquatic plants Plants near the edge of the wetted channel.

Table 6. Vegetation classes used to digitize satellite and aerial imagery along the Verde River, Arizona.
Riparian Vegetation 21

2000200120022003200420052006200720082009201020112012

Year

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

Evapotranspiration

Actual (ET) and Potential (ETo) Evapotranspiration—Lower-Middle Verde River, 2000–2012

ETo

ET

2000200120022003200420052006200720082009201020112012

Year

Actual (ET) and Potential (ETo) Evapotranspiration—Upper-Middle Verde River, 2000–2012

ETo

ET

0

1

2

3

4

5

6

Evapotranspiration, millimeters per day

B

A

EXPLANATION

EXPLANATION

Figure 15. Graphs showing actual and potential evapotranspiration of the Verde River, Arizona, from 2000–2012 using the 

Moderate Resolution Imaging Spectroradiometer (MODIS) enhanced vegetation index (EVI) product. A, Lower-middle Verde River; 

B, upper-middle Verde River.
22 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

Mesquite and cottonwood have separate classes because 

there is enough confidence in their distinctive shapes and 

greenness at the time images were flown to specifically 

identify them. Because of the current, relatively unregulated 

flow of the Verde River, the riparian vegetation is of mixed 

ages. This is important in class designation because younger 

cottonwood trees did not have the distinctive canopies of the 

older cottonwood trees digitized in the Cottonwood class and 

are thus accounted for in the mixed-canopy class. Other species in this class are the many species of willow and the other 

trees, such as the non-native tamarisk, that we were not able to 

identify separately on the aerial imagery.

The mixed-shrub and the mesquite classes are the only 

vegetation classes that include bare soil between plants. This 

is because the increased irregularity in the size of the mixedshrub and mesquite vegetation with similarly irregular patches 

of bare soil in between plants made it inefficient to exclude 

bare soil, but likewise inefficient to make bare soil its own 

class. A fifth vegetation class was added for the pinyon-juniper 

vegetation type that is prevalent in the upper reach. The 

pinyon-juniper stands have a distinctive circular shape, are 

green year round, and grow above the riparian zone at higher 

elevations including the upper part of the river. The sixth vegetation class is agriculture and the seventh class is for emergent aquatic vegetation. In some river miles, the percentages 

of vegetation add up to less than 100 percent. For these areas, 

the remaining percentage is either bare soil or developed land, 

neither of which were digitized.

Figures 16 and 17 show the distribution of vegetation 

classes along the upper-middle (fig. 16) and lower-middle 

(fig. 17) Verde River. As would be expected, due to the higher 

elevation and narrower channel, the upper-middle section has 

more upland plant species, such as pinyons and junipers, and 

fewer lowland species, such as cottonwoods, compared to 

their abundance in the lower-middle sections (figs. 16 and 17). 

Differences in vegetation within the upper-middle and lowermiddle reaches are more likely related to differences in climate 

and hydrology than to human alterations. Both Oak Creek (fig. 

18) and West Clear Creek (fig. 19) are dominated by mixed 

shrub and mixed canopy, but Oak Creek has a greater percentage of cottonwoods and mesquite than West Clear Creek. This 

may be in part because of the habitat provided by the steeper 

and narrower active channel of West Clear Creek, as well as 

its predominantly east-west orientation.

Because of the relatively unregulated flow and relatively 

unaltered disturbance regime, particularly of the upper-middle 

Verde River watershed, the riparian vegetation is of a mixed 

age, mixed patch structure, which is a sign of a healthy ecosystem (Shafroth and others, 2010b). Alteration of hydraulic 

regime can negatively affect the current cottonwood-willow 

gallery forest, as well as any future forest establishment by 

preventing seedling establishment, lowering the groundwater levels needed to maintain the current vegetation, and 

by making non-native expansion possible into areas where 

native plants can no longer survive due to decreased groundwater levels. Continued reduction of base flows in the Verde 

River also has the potential to facilitate the establishment of 

additional non-native plant species and to expand the current 

populations of tamarisk, Russian olive, tree of heaven, and 

giant cane.

Geomorphology

The physical setting of in-stream habitat is defined by 

geomorphic processes. Channel planform, depths, and velocity 

distributions are largely determined by valley relief, sediment 

supply and caliber, and discharge. Pearthree (1993, 1996, 

and 2008) described the Verde River geomorphology with 

an emphasis on the ages of channel deposits and includes a 

comparison of channel positions over time taken from aerial 

photos. Using the categories of Rosgen (1996), Neary and 

others (1996) classified reaches of the upper Verde River in 

relation to riparian habitat. Moody and others (2003) estimated 

bank full discharge and bank stability through cross-sectional 

surveys. Pearthree (2008) noted the predominance of coarse 

bed material and pool-riffle-rapid sequences, that low-flow and 

flood channels are typically well defined, and that riffles form 

at low flow around alternating gravel bars but are washed out 

at higher discharges.

Sullivan Dam, located near Paulden, is upstream of the 

confluence of the Verde River and Granite Creek. The effect of 

Sullivan Dam on sediment transport through the Verde River 

is unknown. The reservoir behind the dam filled with sediment, but the reduction in slope upstream of the dam would 

tend to promote deposition of sediment and thereby limit 

sediment supply below the dam. The extent to which this is 

occurring now or whether the effect has been significant in the 

past is unknown. Steep-gradient tributaries draining the highlands continue to supply sediment as is evident in the coarse 

deposits at the confluence of the Verde River with Granite 

Creek and in the sand-filled pools observed below the Granite 

Creek confluence. Bed material may also be supplied by bank 

and overbank material. Pearthree (2008) distinguishes between 

channel alluvium based on age and notes that the younger 

deposits are more susceptible to scour.

Geomorphic Classification of River Features

Water depth and velocity, which are controlled by 

channel geomorphology, can be determining factors in the 

suitability of in-channel habitat for certain fish and macroinvertebrates. In the middle Verde River, geomorphic units were 

determined from observations made directly from orthoimagery. Because the Yavapai County orthoimages were taken in 

October, before snowmelt, the stream is assumed to have been 

close to base flow. Three types of aquatic habitat features were 

classified—riffles, runs, and pools (Arend, 1999). Methods 

used to characterize the water surface features are modified 

from Konrad and others (2008a). Classes of riffle, run, and 

pool (table 7) were determined in areas of high resolution on 
Riparian Vegetation 23

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000

Area, in square meters

River mile

144 147 150 153 156 159 162 165 168 171 174 177 180 183 186 189 191

Emergent aquatic vegetation

Agriculture

Cottonwood

Mesquite

Juniper

Mixed shrub

Mixed canopy

Mixed canopy

29 percent

Mixed shrub

21 percent

Juniper

34 percent

Mesquite

11 percent

Cottonwood

4 percent

Agriculture

1 percent Emergent aquatic

vegetation

<1 percent

EXPLANATION

B

A

Verde River at Sycamore Creek Sullivan Dam

Clarkdale

Cottonwood

Sedona

Camp Verde

Paulden

Chino Valley

Flagstaff

Sullivan dam

C 112°30'0" W

35°0'0" N

34°30'0" N

112°0'0" W 111°30'0" W

0 5 10 20

5 10 20

MILES

0 KILOMETERS

Figure 16. Graph and pie chart showing distribution of 

vegetation along the upper-middle Verde River, Arizona 

(river miles 144–191). A, Graph of vegetation-class area 

per river mile; B, pie chart of percentage break-down 

of vegetation classes. C, Study area map showing river 

reach in yellow (black line, watershed boundary; see 

fig. 1 for map location). See table 6 for description of 

vegetation classes.
24 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona Area, in square meters

River mile

Emergent aquatic vegetation

Agriculture

Cottonwood

Mesquite

Juniper

Mixed shrub

Mixed canopy

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000

109 111 113 115 117 119 121 123 125 127 129 131 133 135 137 139 141 143

Mixed canopy

48 percent

Mixed shrub

Juniper 17 percent

1 percent

Cottonwood

10 percent

Agriculture

4 percent

Emergent aquatic

vegetation

1 percent

Mesquite

19 percent

EXPLANATION

A

B

Verde River at Oak Creek Verde River at Sycamore Creek

C

Clarkdale

Cottonwood

Sedona

Camp Verde

Paulden

Chino Valley

Flagstaff

112°30'0" W

35°0'0" N

34°30'0" N

112°0'0" W 111°30'0" W

0 5 10 20

5 10 20

MILES

0 KILOMETERS

Figure 17. Graph and pie chart showing 

distribution of vegetation along the lower-middle 

Verde River, Arizona (river miles 109–143). A, Graph 

of vegetation-class area per river mile; B, pie chart 

of percentage break-down of vegetation classes. 

C, Study area map showing river reach in yellow 

(black line, watershed boundary; see fig. 1 for map 

location). See table 6 for description of vegetation 

classes.
Riparian Vegetation 25

Area, in square meters

River mile

0

50,000

100,000

150,000

200,000

250,000

300,000

12345678 9 10 11 12 13 14 15 16 17 18

Emergent aquatic vegetation

Cottonwood

Mesquite

Mixed shrub

Mixed canopy

Mixed canopy

53 percent

Mixed shrub

24 percent

Mesquite

19 percent

Cottonwood

4 percent

Emergent aquatic

vegetation

<1 percent

EXPLANATION

A

B

Clarkdale

Cottonwood

Camp Verde

Paulden

Chino Valley

Flagstaff

C

Sedona

112°30'0" W

35°0'0" N

34°30'0" N

112°0'0" W 111°30'0" W

0 5 10 20

5 10 20

MILES

0 KILOMETERS

Near Verde River

Figure 18. Graph and pie chart showing 

distribution of vegetation along Oak Creek, Arizona, 

from confluence with Verde River to sampling 

site 17.45 miles upstream. A, Graph of vegetationclass area per river mile; B, pie chart of percent 

break-down of vegetation types. C, Study area 

map showing river reach in yellow (black line, 

watershed boundary; see fig. 1 for map location). 

See table 6 for description of vegetation classes.
26 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona Area, in square meters

River mile

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000

12345678 9 10 11

Cottonwood

Mesquite

Mixed Shrub

Mixed Canopy

Cottonwood

1 percent

Mixed Canopy

81 percent

Mixed Shrub

18 percent

Mesquite

<1 percent

EXPLANATION

A

B

Clarkdale

Cottonwood

Sedona

Camp Verde

Paulden

Chino Valley

Flagstaff

C 112°30'0" W

35°0'0" N

34°30'0" N

112°0'0" W 111°30'0" W

0 5 10 20

5 10 20

MILES

0 KILOMETERS

Near Verde River

Figure 19. Graph and pie chart showing 

distribution of vegetation along West Clear Creek, 

Arizona, from confluence with Verde River to 

sampling site 11 miles upstream. A, Graph of 

vegetation-class area per river mile; B, pie chart 

of percent break-down of vegetation types. C, 

Study area map showing river reach in yellow 

(black line, watershed boundary; see fig. 1 for 

map location). See table 6 for description of 

vegetation classes.

the images provided by Yavapai County Flood Control District 

and Bing Maps as linked to the ArcGIS base map. Geomorphic channel features were identified by visual characteristics, 

such as whether the water surface was rough or smooth, the 

channel width and sinuosity, and obstructing features that 

might cause a backwater. Pools were identified by smooth 

water surfaces and wider channel widths and were typically 

found where a downstream obstruction created a backwater. 

Runs were identified as generally smooth water surfaces with 

narrower stream widths than pools. Riffles were identified by 

rough water surfaces with steeper gradients than pools and 

runs and were typically found where the river flowed over 

gravel bars (Konrad and others, 2008a).

Figures 20 and 21 show the distribution of geomorphic 

units throughout the middle Verde River; the upper-middle 

reach had more riffle habitat and less pool habitat than the 

lower-middle reach. The tributary Oak Creek (fig. 22) and 

West Clear Creek reaches (fig. 23) were also digitized. The 

Oak Creek reach was more homogenous in geomorphic 

stream-habitat composition than the West Clear Creek reach. 
Geomorphology 27

Runs dominated in the upper sections of West Clear Creek, 

and pools were more dominant in many of the lower sections; 

riffle habitat was more common in the upper sections than in 

lower sections. This difference between the two reaches was 

likely related to the greater slope and sinuosity of the West 

Clear Creek channel and floodplain. In some areas such as 

lower West Clear Creek, canopy cover can occasionally block 

channel visibility on aerial imagery, and the accuracy of the 

fluvial geomorphic descriptor classification can be reduced. 

As with the analysis of the distribution of riparian vegetation, 

this distribution of geomorphic units can be used as a basis for 

analysis of in-stream habitat.

Area, in square meters

River mile

Pool

Run

Riffle

0

10,000

20,000

30,000

40,000

50,000

60,000

144146148150152154156158160162164166168170172174176178180182184186188190

EXPLANATION

Verde River at Sycamore Creek Sullivan Dam

Geomorphic

channel units

Area, in square meters

River mile

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

109111113115117119121123125127129131133135137139141143

Verde River at Oak Creek Verde River at Sycamore Creek

Pool

Run

Riffle

EXPLANATION

Geomorphic

channel units

Figure 20. Graph showing upper-middle Verde River, Arizona, geomorphology class distribution per river mile.

Figure 21. Graph showing lower-middle Verde River, Arizona, geomorphology class distribution per river mile.
28 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

Area, in square meters

River mile

Pool

Run

Riffle

EXPLANATION

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

Geomorphic 

channel units

Near Verde River

0

5,000

10,000

15,000

20,000

25,000

30,000

1 2 3 4 5 6 7 8 9 10 11

Area, in square meters

River mile

Pool

Run

Riffle

EXPLANATION

Geomorphic 

channel units

Near Verde River

Figure 22. Graph showing Oak Creek, Arizona, geomorphology class distribution per river mile.

Figure 23. Graph showing West Clear Creek, Arizona, geomorphology class distribution per river mile.
Geomorphology 29

Bedload Transport at the Paulden Streamgage

Models of flow and sediment transport have been used 

to interpret the fluvial geomorphic processes that affect the 

mechanisms that influence habitat development, water quality 

(suspended sediment), and organism abundance and distribution (Wiele and others, 2007). As a first step toward such 

an understanding of the fluvial geomorphology of the Verde 

River, the usefulness of the Hydrologic Engineering Center 

River Analysis System (HEC-RAS) model sediment transport 

output for the Verde River was evaluated at different time 

steps (U.S. Army Corp of Engineers, 2018).

In general, sand-bedded channels can be readily reworked 

even at moderate and low discharges. At high flows, significant scour and fill can occur in the channel, and the sediment 

load can vary significantly as a function of discharge depending on sediment supply. In contrast, gravel-bed channels, 

which dominate the upper-middle and lower-middle Verde 

River, tend to be far less active and provide a more stable 

framework for in-stream organisms, although sand-sized sediment is still deposited in pools. Hydraulic properties tend to 

vary smoothly with water-discharge, but sediment transport, 

especially in gravel-bedded rivers such as the Verde, tends to 

be minimal until a threshold is reached. As water-discharge 

increases beyond this threshold, sediment transport increases 

sharply as a nonlinear function of bed stress. Available data 

were used to estimate the gravel-transport threshold and transport rate as a function of water-discharge at the Verde River 

near Paulden gage. Flow and channel properties and bedload 

flux at the Paulden gage were estimated from existing data in 

combination with data from field samples. Hydraulic properties were estimated from a peak-flow study conducted by the 

USGS, and bed-material size distribution was determined from 

recent pebble counts.

Given the abundance of bed material and the tendency 

toward infrequent and short duration high flows, a relation 

between water-discharge and bedload derived from sediment 

transport can be used to estimate the history of sediment transport at the Paulden gage. A similar relation could not be used 

for fine sediment in the Verde River because transport of fine 

sediment is likely constrained by supply. Discharge records 

at 15-minute intervals are available from 1987 onwards from 

the USGS National Water Information System (NWIS; https://

waterdata.usgs.gov/nwis). To directly compare how channel properties, flow properties, and sediment flux varied with 

water-discharge, these values were nondimensionalized so 

that all were 0 at the lowest discharge computed and 1 at the 

highest discharge computed (fig 24A). The sediment flux 

was relatively dormant until the water-discharge reached a 

nondimensional threshold value of about 0.2, beyond which 

sharply elevated sediment transport occurred. This nondimensional water-discharge value (0.2) corresponded to the 

real sediment-discharge of 0.01 cubic feet per second (ft3/s) 

shown in figure 24B.

The sediment transport computed for 22 discharges 

modeled with the HEC-RAS computer program were used 

as a linearly interpolated table to compute sediment transport 

over the 15-minute gage hydrographs. Mobilization of bed 

material has been an infrequent and irregularly timed event at 

the Paulden gage since 1987. Five events exceeded the elevated sediment (or gravel) transport threshold (sediment-discharge of 0.01 ft3

/s) from water year 1987 through water year 

2011 (fig. 24B, 15-minute data). A gap of 11 years occurred 

between the 1993 and 2004 events in which channel-bed 

material was not disturbed; that period ended with two events 

exceeding the gravel transport threshold only 5 months apart. 

The poor sorting and angularity of bed sediment near the 

Paulden gage is consistent with infrequent transport. 

The sensitivity of sediment transport to discharge makes 

the temporal resolution of discharge records worth considering. Fifteen-minute resolution is generally sufficient to 

capture the rise, peak, and fall of runoff events even in the 

hydrologically volatile arid Southwest. However, 15-minute 

data can be cumbersome to work with, may not be available, 

and may not be compatible with some software. On the other 

hand, using average daily discharges (red plot in fig. 24B) to 

compute bedload transport at the Paulden gage yielded just 

3 of the 5 events evident in the 15-minute calculations (blue 

line in fig. 24B), which yields much lower estimates of transport rate. Monthly average discharge data yielded no months 

that exceeded the gravel-transport threshold; neither can 

monthly records of streamflow capture the channel-forming 

processes that are a fundamental part of habitat development 

and maintenance. Daily flows are a significant improvement from monthly averages, but considering the volatility 

of storm runoff in the Verde River watershed, the impact 

of some events could be obscured by averaging discharge 

over daily time steps. When possible, 15-minute data should 

be used to evaluate sediment transport in the Verde River 

system.

Use of cross sections and roughness estimates obtained 

following the 1993 peak of record (22,300 ft3/s) degrade 

the accuracy of the calculations over the 24-year discharge 

record because the peak flow altered the channel, and channel 

properties have changed over time. Vegetation was removed 

during the 1993 flood, so the channel was likely smoother 

than at other times, and the channel configuration has likely 

been altered from its previous shape by the 1993 flows and by 

the subsequent high flows. However, for ecological considerations, the estimates of frequency, intensity, and duration of 

channel-forming events are still useful.

Geomorphic 

channel unit Description

Riffle Turbulent flow; shallow, coarse-grained substrate.

Run Laminar flow, less turbulent; variable depth and 

substrate.

Pool Very low current velocity; relatively deep, depositional accumulations of fine sediment particles.

Table 7. Geomorphic channel units used in this study of the 

middle Verde River, Arizona (Moulton and others, 2002).
30 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

0.001

0.01

0.10

1.00

15minute

Daily

Threshold of elevated

sediment transport

EXPLANATION

Sediment discharge, in cubic feet per second

A

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0 0.2 0.4 0.6 0.8 1.0

No

Date

ndimensional discharge

Depth

Velocity

Sediment transport

Top width

EXPLANATION

B

10/1/1987

6/27/1990

3/23/1993

12/18/1995

9/13/1998

6/9/2001

3/5/2004

11/30/2006

8/26/2009

Nondimensional functions of discharge

Figure 24. Graphs showing 

(A) nondimensionalized 

channel properties, 

flow properties, and 

sediment discharge 

plotted as a function of the 

nondimensionalized waterdischarge and (B) bedload 

transport calculated at the 

Verde River near Paulden 

gage, Arizona (15-minute 

and average daily sediment 

discharges). The significant 

sediment transport line of 

0.01 cubic feet per second 

is also shown. Date format 

is month/day/year.
Fish and Macroinvertebrates 31

Fish and Macroinvertebrates

Analysis Framework

The middle Verde River watershed is a unique and 

important resource that provides large areas of undeveloped 

habitat to a diverse range of animal species. The middle Verde 

River is one of the few remaining free-flowing reaches found 

on large rivers in Arizona and is recognized by local, State, 

and Federal environmental- and natural-resource agencies as 

a sensitive and vulnerable resource. Although the USGS, U.S. 

Environmental Protection Agency (EPA), United States Fish 

and Wildlife Service, USFS, Arizona Game and Fish Department (AZGFD), and Arizona Department of Environmental 

Quality (ADEQ) have all conducted research and monitoring 

in the Verde River watersheds, not all information is compatible for compilation because of differences in objectives, time, 

space, and scale. Research to understand how non-native species and water quality have been changing over time has been 

ongoing for many decades, but much less work has been completed that directly relates the hydrologic and flow alteration 

characteristics of the main Verde River and tributaries to the 

function of ecological communities. These different agency 

data sources and data types were compiled here to be used in 

a preliminary analysis of fish and macroinvertebrate communities in relation to hydrologic and habitat characteristics in 

the middle Verde River watershed. The different data sources 

required the consideration of factors related to the timing of 

collection (the year and season), the location of collection 

with respect to scale (watershed, reach, and microhabitat), and 

streamflow conditions before collection (timing and magnitude 

of recent flooding events).

In addition to analyzing existing data, a fish pilot study 

and a macroinvertebrate pilot study were done. The intent of 

these pilot studies was to provide information about the design 

and implementation of ecological flow studies and about how 

a study could be scaled up to investigate the ecological and 

hydrological relations between biotic assemblages and habitat 

data. The pilot studies were (1) a collaboration between Northern Arizona University (NAU) and the USGS for the purpose 

of better understanding the eco-hydrology relations of fish 

communities at the reach scale and (2) a USGS macroinvertebrate and habitat analysis in the upper-middle Verde River. 

Fish and Macroinvertebrate Data Sources and 

Processing

There were 312 fish surveys conducted in the Middle 

Verde River watershed between 1992 and 2011 and of the 

312 surveys, 292 were conducted along the Verde River from 

below Stillman Lake (near the confluence with Granite Creek) 

to the stream gaging station Verde River near Camp Verde 

(09506000; fig. 25). The other 20 surveys were conducted at 

West Clear Creek, Wet Beaver Creek, and Oak Creek. Macroinvertebrate samples used in the analysis were all collected 

between 1992 and 2010 and came exclusively from riffle habitat (generally the faunistically richest in-stream habitat type) 

along the upper-middle and lower-middle Verde River and 

many of its tributaries. Of the 183 riffle samples analyzed, 27 

were from the upper-middle Verde River, 19 from the lowermiddle Verde River, 11 from Sycamore Creek, 5 from Bitter 

Creek, 47 from Oak Creek, 8 from Spring Creek, 29 from Wet 

Beaver Creek, and 37 from West Clear Creek (fig. 26).

Most fish surveys that have been completed along the 

Verde River were conducted by the AZGFD, and methods can 

be found at http://www.azgfd.gov/w_c/tech_reports.shtml. 

A part of the Verde River and all of the West Clear Creek 

fish surveys were collected by the USGS using EPA methods 

(Peck and others, 2006) or USGS National Water Quality 

Assessment (NAWQA) program protocols (Moulton and others, 2002). Sampling methods consisted of either backpack 

or canoe electrofishing, and species identification and counts 

were completed in the field. The assemblage data collected 

were specific to each agency’s objectives and were not specifically collected for the intended purpose of an environmentalflows investigation.

Existing macroinvertebrate data were compiled and 

compared for a combined analysis. Macroinvertebrate samples 

were collected using ADEQ methods (Arizona Department of 

Environmental Quality, 2006), EPA Environmental Monitoring 

and Assessment Program (EMAP) methods (Peck and others, 

2006), or NAWQA program protocols (Moulton and others, 

2002). A detailed comparison between ADEQ and EMAP 

methods can be found in Spindler and Paretti (2009). Samples 

were collected using a net with a 500-micrometer mesh from 

riffles within a given stream reach (coarse substrate), which 

generally provide habitat for the faunistically richest communities (Moulton and others, 2002). Samples were collected 

within a defined area to standardize the sampling effort and 

make it possible to compare sites. Samples were identified 

by Aquatic Biology Associates, EcoAnalysts, or the USGS 

National Water Quality lab to species or genus level using a 

fixed-count of 300 or 500 organisms.

The macroinvertebrate data were combined and processed through the software package Invertebrate Data 

Analyses System to resolve the occurrences of ambiguous 

taxa (Cuffney, 2003). Ambiguous taxa are those taxa whose 

identifications cannot accurately be determined to the lowest 

common taxonomic level. Commonly this is a result of either 

damaged or immature individuals. For this study, taxa were 

only identified to order to maintain consistency between various agency data.

Statistical Analysis and Methods

Several descriptive, univariate, and multivariate statistical approaches were applied to describe and summarize biotic 

metrics and assemblages and to develop abiotic associations 

with assemblage data. In the following sections, descriptive statistics are presented mostly as visual distributions in 

the form of boxplots and as summary statistics in the form 
32 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

Map area

Prescott

Clarkdale

Chino

Valley

Sedona

Camp Verde

Cottonwood

Flagstaff

Creek

Sycamore

Creek

Bitter

Oak

Creek

Beaver

Dry

Wet

Beaver

West Clear

Creek

Ditch sdno ami D sdno ami D

hcti DedreV hcti DedreV

Duff

Tavasci

hcti D

OK Ditch

Ditch

Eureka Back Ditch

V Bar VDitch

35°00'

34°15'

112°45' 112°15'

Base from U.S. Census Bureau cartographic boundary files, 2000

Universal Transverse Mercator projection, Zone 12

North American Datum of 1983

0 10

0 10

5

5

15 MILES

15 KILOMETERS

Ditch or diversion

Fish—Percent native

0 to 11

12 to 34

35 to 58

59 to 80

81 to 100

Streamflow gage

EXPLANATION

Perkinsville

Paulden

Pilot study locations

89A

89

260

40

17

17

ARIZONA

Figure 25. Map showing State of Arizona and Federal agency 

fish survey locations on the upper-middle and lower-middle Verde 

River, Arizona, and tributaries color coded by percentage of native 

fish present.
Fish and Macroinvertebrates 33

Map area

Prescott

Clarkdale

Chino

Valley

Sedona

Camp Verde

Cottonwood

Flagstaff

Creek

Sycamore

Creek

Bitter

Oak

Creek

Beaver

Dry

Wet

Beaver

West Clear

Creek

40

17

17

260

Ditch sdno ami D sdno ami D

hcti DedreV hcti DedreV

Duff

Tavasci

hcti D

OK Ditch

Ditch

Eureka Back Ditch

V Bar VDitch

35°00'

34°15'

112°45' 112°15'

Base from U.S. Census Bureau cartographic boundary files, 2000

Universal Transverse Mercator projection, Zone 12

North American Datum of 1983

0 10

0 10

5

5

15 MILES

15 KILOMETERS

Ditch or diversion

Macroinvertebrate 

sample site

Streamflow gage

EXPLANATION

Granite

Creek

Macroinvertebrate

pilot site

Perkinsville

Paulden Paulden

streamgage

sample

Perkinsville

sample location Clarkdale

streamgage

sample 

Reitz Ranch

Property sample

Salt River

Project low-flow

Streamgage sample

Verde below 

Granite Creek

sample

89A

89

260

40

17

17

ARIZONA

Figure 26. Map showing State of Arizona and Federal agency 

macroinvertebrate survey locations on the upper-middle and lower-middle 

Verde River, Arizona, and tributaries.
34 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

of mean, median, percentiles, and standard deviation. Nonparametric statistics were used to compare groups and trends, 

again to avoid normal data-distribution assumptions required 

for parametric statistics. Pairwise Wilcoxon rank-sums test 

was used for statistical comparisons between groups; monotonic relations between flow metrics and biota were analyzed 

using a nonparametric Kendall’s tau (τ)correlation procedure, 

which again makes no assumptions about the normality of 

the data distribution. Nonparametric regression procedures, 

such as spline fitting and locally weighted scatterplot smoothing, were used to understand trends and biotic responses to 

abiotic variables such as hydrologic metrics and stream habitat 

measures.

Assemblage data were examined using a robust nonmetric multidimensional scaling (NMDS) multivariate analysis 

procedure. NMDS was used to examine patterns in assemblage datasets. The NMDS analysis was performed on a BrayCurtis similarity matrix and plotted in two-dimensional space 

to aid in interpretation of multivariate patterns. A measure of 

stress is provided from the NMDS analysis as a diagnostic to 

determine how well the data are fitting the NMDS ordination. 

Lower stress values are desired, and stress values below 0.20 

generally indicate that the NMDS plot is providing an accurate 

representation of the data in multivariate space. Many times, 

a multivariate centroid analysis was used to further simplify 

the visualization of the NMDS structure. This procedure 

essentially sums the distances of each observation (sample 

assemblage) relative to the observations within a group (within 

group sum of squares) and compares the distances to all other 

observations in all other groups (total sum of squares), and the 

measure of central location for the group constitutes a centroid location for that group, which can then be used in group 

comparisons.

Vector overlays were added to NMDS graphical outputs 

as an additional exploratory tool to visualize potential linear or 

monotonic relations between influential taxa and the ordination axes. Spearman rank correlations were restricted to a vector length of ±0.50 or greater, with ±1.0 indicating complete 

correlation. The length and direction of each vector indicates 

the strength and sign, respectively, of the relation between the 

taxa and the NMDS axes (Anderson and others, 2008). Similar 

exploratory visualizations were presented as bubble plots, 

where habitat and flow variables were superimposed onto the 

NMDS plot to better visualize patterns between the community and influential habitat features. Each bubble represents 

the site assemblage, and the size of the bubble represents the 

magnitude of the habitat variable measured at the site. The 

purpose for this procedure is to visualize patterns and associations between abiotic measures and assemblage data that may 

not be obvious in bivariate space.

A subset of fish and macroinvertebrate metrics that were 

significantly correlated (p<0.05) to hydrological metrics were 

used in quantile regression analysis. Fish and macroinvertebrate datasets commonly display a “wedge shaped” response 

to an explanatory habitat variable, indicating unequal rates of 

changes at different quantiles and a threshold or limit of the 

response to that variable (Terrell and others, 1996; Konrad and 

others, 2008b). Quantile regression fits a continuous function 

through the local (with respect to the independent variable) 

value of the quantile of a dependent variable to account for 

variation in the quantile with the independent variable. The 

method quantifies the rate of change in the dependent variable, 

which includes the upper and lower ends, whereas a leastsquares regression analysis quantifies the mean response in 

relation to the explanatory variable (Cade and others, 1999). 

In this analysis, the quantiles (0.1, 0.25, 0.50, 0.75, and 0.90) 

of the response variable (biotic metric) were fitted as linear 

functions of the explanatory variable (hydrological metric), 

similar to the method described in Kail and others (2012). The 

regression line with the largest quantile with the narrowest 

90-percent confidence intervals for the regression-line slope 

that did not include zero was selected as the limiting threshold 

in the biotic response (Cade and others, 1999). The quantiles 

were tested for statistical significance in terms of the probability that the slope and intercept were zero.

Description of Hydrologic Metric Determination 

and Flooding Classification

Discharge records from the gaging stations on the Verde 

River and its tributaries were used to examine the relations 

between biota properties and streamflow. Streamflow properties that are potentially significant to biotic communities are 

represented by metrics that are measures of flow magnitude, 

duration, variability, and rates of change. For this study, sampling sites within 10 km of a gaging station were chosen for 

comparing biotic and streamflow metrics.

The hydrologic metrics computed by EFASC (Konrad, 

2011; table 8) were used in the analyses. The metrics that 

represent biotic properties may be functions of antecedent 

flow conditions; however, the most significant time periods are 

unknown before analysis and may vary among taxa. Consequently, metrics were calculated over a range of time periods 

preceding and concurrent with the sampling dates. Metrics 

were calculated for 10-, 30-, 90-, 365-, and 1,095-day periods 

before the sampling dates if the discharge record was largely 

complete over that time period. However, in the end, only 30-, 

90-, and 365-day periods before the sampling dates were used; 

the metrics computed by EFASC were not meaningful for the 

shortest and longest time periods.

EFASC was intended for the analysis of long-term 

streamgage records but can be used for selected time periods 

extracted from longer records (Konrad, 2011). In this application, EFASC is first applied to the period of record to compute 

streamflow threshold values that are specified as input for 

applications to shorter time periods. Flow metrics represent 

the ecologically significant characteristics—magnitude, timing, frequency, duration, and rate of change (Richter and others, 1996; Poff and others, 1997).

Large floods have been shown to be beneficial for the 

succession of fish species native to the Southwest (Rinne 
Fish and Macroinvertebrates 35

2005; Propst and Gido (2004), and biota that have evolved 

under conditions of such variable discharge will return to a 

proper functioning condition following a flood. The magnitude 

and timing of a large flood are important to know because they 

affect the characteristics of the succession period that follows. 

Because the timing of sample collection is an important factor 

in ecological studies, individual hydrographs were evaluated 

to determine recent flow conditions for each year respective 

of when surveys and samples were collected. Flooding will 

typically mobilize woody debris and bed substrate, evacuating 

fish, macroinvertebrates, and algae, effectively resetting the 

river ecosystem and biotic communities. The establishment 

of a new community will vary depending on the flood characteristics, as well as the location and season. It is important to 

consider these factors when conducting a community analysis.

Samples collected in a given year were classified into 

three major flood-event categories—low, moderate, and highflood years. The classification was modified from Minckley 

and Meffe (1987) who observed significant flooding effects, 

specifically species removal, on non-native populations at two 

orders of magnitude greater flow than the average discharge 

for a given station. Samples collected in years with flows that 

exceeded two orders of magnitude greater than the average discharge were identified as high-flood years, samples 

collected in years with flows that exceeded one order of 

magnitude greater than the average discharge were classified 

moderate-flood years, and samples collected in years with 

flows less than one order of magnitude greater than the average discharge were classified as low-flood years. Research 

pertaining to the characteristics of large flood events and 

beneficial effects to aquatic biota is scarce. Research is especially lacking in the quantification of the magnitude, duration, 

timing, and number of peaks necessary to promote native species success. The classifications presented in this investigation 

are meant to serve as a way to help distinguish the effects of 

natural events from other factors related to changes in biotic 

communities (fig. 27).

Reach Classification

To assess the difference in effect of physical variability 

from human impacts, two approaches were used in the analysis of existing fish and macroinvertebrate data—(1) sample 

locations classified into separate reaches based on the physical basin characteristics of the river (fig. 28) and (2) sample 

locations classified into separate reaches based on human 

alteration of river flow (fig. 29). River reach characterization 

is a statistical process in which segments of stream miles are 

differentiated by physical, climatic, and hydrological characteristics. This classification process provides a physical 

standard condition for comparing the aquatic biota observed in 

each classified reach. First characterizing the stream reaches 

by physical conditions provides an initial framework for identifying background ecological conditions so that subsequent 

relations between ecological metrics and flow alteration can 

be developed (Arthington and others, 2006). For example, the 

physiography and climate of the upper-middle Verde River near 

the confluence with Granite Creek is very different from the 

lower-middle Verde River near the confluence with West Clear 

Creek, and this spatial variability is reflected in the biotic communities that inhabit the different stream reaches. Two important ecosystem drivers—mean annual precipitation and mean 

elevation—can vary as much as 10 inches and 3,000 ft within 

the study area, respectively.

Reaches were differentiated based on differences in the 

physio-climatic characteristics in order to better understand 

the ecological response to measures of hydrologic changes or 

alteration throughout the study area. The USGS StreamStats 

program was used to compute basin characteristic statistics for 

each fish and macroinvertebrate sampling location. A preliminary correlation and scatter plot analysis was used to reduce the 

large number of 50 basin characteristic variables to a table of 

nonredundant variables that could be used to classify reaches. 

Highly correlated variables were removed using a Kendall’s tau 

correlation coefficient scatter plot (τ≥0.7). Next a multivariate 

principal component analysis with a varimax rotation was used 

to identify six nonredundant basin characteristics that differentiated reaches along a principal component gradient. The first 

and second principle components explained 97 percent of the 

variation in the dataset. The basin characteristics influential 

along this component axis included watershed stream density, 

mean annual precipitation, percent forest, percent upland herbaceous shrubs, soil permeability, and soil water capacity. The 

reaches were defined using these variables, and breakpoints 

were usually determined where a major contributing tributary 

entered the upper-middle and lower-middle Verde River (fig. 

28).

Multivariate centroids were determined for a matrix of 

the six variables and plotted using NMDS. In an NMDS plot, 

centroids that plot closer together are more similar. The NMDS 

plot (fig. 28, inset) thus showed that reaches 1 and 2 were more 

similar because both are within the upper-middle Verde River 

where similar geomorphology and climate distinguish these 

reaches from downstream locations of the lower-middle Verde 

River. The upper-middle Verde River has more small, contributing tributaries with more herbaceous uplands and less sandy 

soils than the lower-middle Verde River. The water capacity 

and storage of the upper Verde River is therefore greater too. 

Lower in the watershed (reaches 4 and 5) water is draining 

from the higher elevation forested areas of the watershed. The 

lower-middle Verde River (beginning with reach 3) widens 

markedly from the upper-middle Verde River, and basin characteristics change greatly. These basin characteristics affect 

surface-water runoff, storage capacity, and water chemistry 

which in turn affect the biotic communities using those river 

reaches. A new reach was generally defined at the watershed 

entry point of each subsequent major tributary. For example, 

reach 3 extends from Sycamore Creek (near the Clarkdale 

streamgage (09504000)) to the confluence with Oak Creek, 

reach 4 is between Oak Creek and West Clear Creek, and reach 

5 is between West Clear Creek and the Camp Verde streamgage 

(09506000) (fig. 28). Reaches 3 and 4 cover most of the 
36 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

Metric name Description

Mean streamflow Mean streamflow for the period of analysis: (Σd=1 to D Qd

)/D, where d is each day and D is the number of 

days in the period of analysis.

Q01 Streamflow equaled or exceeded 1 percent of the period of analysis

Q10 Streamflow equaled or exceeded 10 percent of the period of analysis

Q25 Streamflow equaled or exceeded 25 percent of the period of analysis

Q50 Streamflow equaled or exceeded 50 percent of the period of analysis

Q75 Streamflow equaled or exceeded 75 percent of the period of analysis

Q90 Streamflow equaled or exceeded 90 percent of the period of analysis

Q99 Streamflow equaled or exceeded 99 percent of the period of analysis

50th percentile of absolute value of percent 

daily change

The median absolute value of percent daily change in streamflow. Percent daily change is calculated for 

each day (d); ((Qday1–Qday0)/Qday0. No-flow days are not included in the calculation. For odd-numbered 

series, the median is determined by ranking all values for day 1 to day d in a series from highest to lowest 

and selecting the value at the d/2+1 place. For even-numbered series, the value is the midpoint between 

the integer part of d/2+1 and the next (smaller) value.

Coefficient of variation of 

daily flows

Standard deviation of daily streamflow divided by mean streamflow.

Coefficient of variation of 

log-transformed daily 

flows

Coefficient of variation of log-transformed streamflow: (10(Var(log(Q))-1)0.5, where Var(log(Q)) is the variance 

of the series of log-transformed daily values. No-flow days are not included in the calculation.

Coefficient of variation of 

log-transformed annual 

maximum flow

Coefficient of variation of log-transformed streamflow: (10(Var(log(Qmax))-1)0.5, where Var(log(Qmax)) is the variance of the annual (water year) series of log-transformed maximum daily values. Years when Qmax=0 are 

not included in the calculation.

Median annual maximum 

streamflow

Median annual (water year) maximum daily streamflow.

Qmax/Q50 Median annual (water year) maximum daily streamflow (Qmax) divided by median streamflow (Q50).

Median annual number of 

high-flow events

Median of the annual (water year) number of periods when streamflow exceeds the high-flow threshold.

Median duration of the 

annual longest highflow event

Median number of days of the annual (water year) longest period of time when streamflow exceeds the 

high-flow threshold.

Number of months with 

annual probability 

greater than 0.5 of having a high-flow event

Number of months (October, November, December, ... , September) that had flows exceeding the high-flow 

threshold in more than one-half of the water years of the period of analysis. Values range from 0 to 12.

Mode of highest streamflow monthMost common month of maximum monthly mean streamflow. The time series of monthly mean streamflow 

is calculated for the period of analysis. The month with the highest monthly mean is determined for each 

year. A value of 1 indicates that January was most often the month with the highest mean streamflow for 

the year.

Median annual minimum 

streamflow

Median annual (low-flow year) minimum daily streamflow.

Qmin/Q50 Median annual (low-flow year) minimum daily streamflow (Qmin) divided by median streamflow (Q50).

Coefficient of variation 

of annual minimum 

streamflow

Standard deviation of the annual (water year) series of minimum daily streamflow divided by mean annual 

minimum daily streamflow.

Table 8. Streamflow metrics computed by the Environmental Flow Allocation and Statistics Calculator (Konrad, 2011).
Fish and Macroinvertebrates 37

Table 8.—Continued.

Metric name Description

Median annual number of 

low-flow periods

Median of the annual (low-flow year) number of periods when streamflow is less than the low-flow threshold.

Median duration of the 

annual longest lowflow period

Median number of days of the annual (low-flow year) longest period of time when streamflow is less than 

the low-flow threshold.

Number of months with 

annual probability 

greater than 0.5 of having a low-flow period

Number of months (October, November, December, ... , September) that had flows less than the low-flow 

threshold in more than one-half of the low-flow years of the period of analysis. Values range from 0 to 

12.

Mode of lowest flow 

month

Most common month of minimum monthly mean streamflow. The time-series of monthly mean streamflow 

is calculated for the period of analysis. The month with the lowest monthly mean is determined for each 

year. A value of 1 indicates that January was most often the month with the lowest mean streamflow for 

the year.

Fraction of years with 

no-flow days

Fraction of years with days that had no flow.

Mean number of no-flow 

days in years with noflow days

The total number of days with no flow averaged over years with no-flow days. Years with streamflow on all 

days are not included in the calculation. No-flow days are calculated for each lowflow year.

Coefficient of variation of 

annual mean streamflow

Standard deviation of mean annual (water year) streamflow divided by mean streamflow.

Storm-flow recession 

coefficient

The 10th percentile of percent daily change for days when streamflow was steady (no change) or receding. 

The 10th percentile represents a relatively fast recession rate indicative of storm-flow recession because 

the values are negative.

Base-flow recession coefficientThe median annual (water year) value of the median percent daily change for days when streamflow was 

steady (no change) or receding. The median represents a typical recession rate indicative of base-flow 

conditions.

Maximum monthly 

streamflow

The maximum of means for January, February, March, ... , December.

Minimum monthly 

streamflow

The minimum of means for January, February, March, ... , December.

Maximum coefficient of 

variation of monthly 

streamflow

The coefficient of variation of annual values of mean streamflow for each month (January, February, March, 

... , December) is calculated and the maximum value is used. The maximum value represents the month 

with the lowest predictability in streamflow magnitude.

Minimum coefficient of 

variation of monthly 

streamflow

The coefficient of variation of annual values of mean streamflow for each month (January, February, March, 

... , December) is calculated and the minimum value is used. The minimum value represents the month 

with the highest predictability in streamflow magnitude.

Normalized range of 

monthly streamflow

Median annual (water year) value of the difference between maximum monthly mean streamflow and 

minimum monthly mean streamflow divided by annual mean streamflow. If the annual mean streamflow 

is zero, then the normalized range of monthly streamflow is zero.

log(Q10/Q90) Logarithm (base 10) of the streamflow exceeded 10 percent of the time divided by streamflow exceeded 90 

percent of the time. 
38 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

10

100

1,000

10,000

10

100

1,000

10,000

10

100

1,000

10,000

10/01/1992

Date

01/01/1993 04/01/1993 07/01/1993 10/01/1993 01/01/1994 04/01/1994 07/01/1994 10/01/1994 01/01/1995 04/01/1995 07/01/1995 10/01/1995 01/01/1996 04/01/1996 07/01/1996 10/01/1996

EXPLAN

ATION

Macroinvertebrate sample

Fish sampleFish and macroinvertebrate sample

Sample influcenced by high flow

Sample influcenced by moderate flow

Sample influcenced by mean- or base-flow

Two orders of magnitude above average flow2-year flood frequency magnitudeOne order of magnitude above average flow

Discharge at Verde River near Paulden 

(09503700), in cubic feet per second 

Discharge at Verde River near Camp Verde 

(09506000), in cubic feet per second 

Discharge at Verde River near Clarkdale 

(09504000), in cubic feet per second 

A

Figure 27. Graphs showing mean daily stream discharge at the Verde River near Camp Verde, Verde River near Clarkdale, and Verde River near Paulden gages on the middle Verde River, Arizona. Fish sampling dates and flow conditions at the time of sampling are also shown. 

A, October 1, 1992, to 

October 1, 1996; 

B, October 1, 1996, to July 1, 2001; C, October 1, 2001, to July 

1, 2006; D, October 1, 2006, to July 1, 2011. Date format is month/day/year.
Fish and Macroinvertebrates 39

Figure 27.—Continued

10

100

1,000

10,000

10

100

1,000

10,000

10

100

1,000

10,000

10/01/1996 04/01/1997 07/01/1997 10/01/1997 01/01/1998 04/01/1998 07/01/1998 10/01/1998 01/01/1999 04/01/1999 07/01/1999 10/01/1999 01/01/2000 04/01/2000 07/01/2000 10/01/2000 01/01/2001 04/01/2001 07/01/2001

Discharge at Verde River near Paulden 

(09503700), in cubic feet per second 

Discharge at Verde River near Camp Verde 

(09506000), in cubic feet per second 

Discharge at Verde River near Clarkdale 

(09504000), in cubic feet per second 

Date

B
40 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

10

100

1,000

10,000

10

100

1,000

10,000

10

100

1,000

10,000

10/01/2001 04/01/2002 07/01/2002 10/01/2002 01/01/2003 04/01/2003 07/01/2003 10/01/2003 01/01/2004 04/01/2004 07/01/2004 10/01/2004 01/01/2005 04/01/2005 07/01/2005 10/01/2005 01/01/2006 04/01/2006 07/01/2006

Discharge at Verde River near Paulden 

(09503700), in cubic feet per second 

Discharge at Verde River near Camp Verde 

(09506000), in cubic feet per second 

Discharge at Verde River near Clarkdale 

(09504000), in cubic feet per second 

C

Date

Figure 27.—Continued
Fish and Macroinvertebrates 41

10

100

1,000

10,000

10

100

1,000

10,000

10

100

1,000

10,000

10/01/2006 04/01/2007 07/01/2007 10/01/2007 01/01/2008 04/01/2008 07/01/2008 10/01/2008 01/01/2009 04/01/2009 07/01/2009 10/01/2009 01/01/2010 04/01/2010 07/01/2010 10/01/2010 01/01/2011 04/01/2011 07/01/2011

Discharge at Verde River near Paulden 

(09503700), in cubic feet per second 

Discharge at Verde River near Camp Verde 

(09506000), in cubic feet per second 

Discharge at Verde River near Clarkdale 

(09504000), in cubic feet per second 

D

Date

Figure 27.—Continued
42 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

significant diversions plus the urbanized areas of the study 

area, and the percent impervious surface is about 2 percent 

more than the other reaches.

The second reach-characterization approach was based 

on the type and amount of human alteration to reach flow. Following the classification scheme of Garner and Bills (2012), 

sampling locations were grouped based on known diversions in order to compare reaches of varying flow alteration 

(fig. 29). These reaches are indicated by Roman numerals as 

opposed to reaches defined by basin characteristics shown in 

figure 28.

Human activities such as groundwater pumping, surfacewater diversions, flood control, and development in the 

floodplain can each cause alterations to the river’s natural flow 

regime (Springer and Haney, 2008). Groundwater pumping 

eventually captures water that would otherwise discharge to a 

stream (Filippone and Leake, 2005; Leake and others, 2008; 

Garner and others, 2013), thus reducing the magnitude of base 

flow. Surface-water diversions also reduce the magnitude of 

base flow (Garner and others, 2013) and can increase the duration of extreme low flows. In some cases, diversion structures 

can result in dewatered reaches below the structure (Brasher, 

2003). Flood-control structures and development in the floodplain may cause higher peak flows due to constriction of the 

flood plain and increased volume and velocity of runoff due 

to increased impervious cover. Springer and Haney (2008), 

Blasch and others (2006), Wirt and others (2005), and Alam 

(1997) all provide data, summaries, and discussion of groundwater pumping and surface-water diversion and their resulting 

impacts on the flow regime in the Verde River.

Synoptic base-flow surveys, or seepage runs, were 

conducted in the Verde Valley in June 2007 and February 

2011 (Garner and Bills, 2012). Both surveys were conducted 

between the Clarkdale gaging station (09504000) and the 

Camp Verde gaging station (09506000), a distance of 51 river 

miles. These data were used to understand spatial variability in 

gaining and losing reaches and the effects that human alterations of the surface-water system have on base flow (Garner 

and Bills, 2012). The dozens of surface-water diversions, 

including several large gravity-fed ditch diversions, had an 

obvious influence on Verde River discharge. Results also 

showed that surface water contributed to the Verde River; the 

perennial tributaries of Oak Creek, Beaver Creek, and West 

Clear Creek were a major factor in explaining perennial flow 

in the Verde River.

The seepage-run investigation completed by Garner and 

Bills (2012) defined reaches in the middle Verde River watershed based on degree of surface-water diversions (fig. 29). 

Reach I–II begins below the Clarkdale gaging station and ends 

at the Tavasci Ditch and has no major surface-water divisions. 

Reach II–III includes the Tavasci, Hickey, and Cottonwood 

ditch diversions, and streamflow can be reduced by as much 

as 65 ft3/s in summer months. Reach III–IV is about 6 river 

miles where there are no diversions, and streamflow increases. 

Reach IV–V is a highly diverted stretch where the OK, 

Eureka, Verde, and Diamond S ditches can divert streamflow 

as much as 96.5 ft3/s in summer months. Reach V–VI has no 

major surface-water diversions. It begins at the Verde Ditch 

return and continues to the Camp Verde gaging station (fig. 29).

Fish

Introduction and Background

The native fish of the Southwest are historically lacking 

in numbers and variety of species and are uniquely adapted 

to a range of conditions that include extreme temperatures, 

unpredictable flood flows, and sediment-laden waters. Historically, native fish frequently would experience periods with 

high flows or droughts that would locally diminish or extirpate 

populations, but following these major events there would be a 

relatively quick recolonization from tributary flow or isolated 

backwaters and pools. As a result, native fish continued to 

thrive into the 20th century. It was not until humans began to 

alter the landscape and introduce non-native species that native 

species began to decline and disappear. Specifically, native fish 

in the Verde River watershed have been declining since the 

introduction of non-native fish species nearly a century ago. 

Added to this are the reductions in base flow from increased 

water usage and the ongoing drought that began in the first 

decade of the 2000s. Together, these factors have led to rapid 

degradation of the in-stream habitat of native fish in the Verde 

River.

Adaptation of Native Fish to the Flow Regimes of 

Desert Streams

The flow regime in perennial streams in the American 

Southwest varies greatly seasonally and has shaped the evolution of native fish species (Deacon and Minckley, 1974). These 

perennial Southwestern streams have long periods near base 

flow, with higher flows and flooding associated with large-scale 

winter storms or more local summer monsoon storms that can 

cause flashy, intense floods. Though the months of snowmelt 

and the monsoon are predictable, the magnitude, timing, and 

rate of change are unpredictable (Bain and others, 1988; Poff 

and others, 1997). As a result, native fishes have become highly 

adapted to a varied flow regime (Lytle and Poff, 2004).

These fish can exhibit behavioral, morphological, or lifehistory traits that aid in their survival during flood and drought 

events (Lytle and Poff, 2004). When streams are regulated, 

peak flows decrease in magnitude and duration, and native 

fishes adapted to the natural flow regime may begin to decline 

in numbers. Non-native fishes, which are often adapted to moderate flows, are able to thrive in these circumstances, allowing 

them to prey on and outcompete native fishes (Bain and others, 

1988; Poff and others, 1997).

Physical factors are likely more important than biotic 

interactions in determining fish assemblages in a variable 

stream environment such as that in the semiarid Southwest. 
Fish and Macroinvertebrates 43

Map area

Prescott

Clarkdale

Chino

Valley

Sedona

Camp Verde

Cottonwood

Flagstaff

Creek

Sycamore

Creek

Bitter

Oak

Creek

Beaver

Dry

Wet

Beaver

West

Granite

Clear

Creek

Creek

89A

40

17

17

260

89

35°00'

34°15'

112°45' 112°15'

Base from U.S. Census Bureau cartographic boundary files, 2000

Universal Transverse Mercator projection, Zone 12

North American Datum of 1983

0 10

0 10

5

5

15 MILES

15 KILOMETERS

Streamflow gage

EXPLANATION

Stream reaches based

 on simlar basin 

characteristics 

Reach 1 Reach 2

Reach 3

Reach 4

Reach 5

Reach 3

Reach 1

Reach 2

Reach 4

Reach 5

2D Stress: 0

Greater basin:

average precipitation

percent land cover that is Forest

soils of high permeability

Greater basin:

drainage density

percent land cover that is upland 

herbaceous shrubs

soil that have high water capacity

NMDS ordination of basin

characteristic reach centroids.

NMDS axis 2

NMDS axis 1

Perkinsville

Verde River

89A

260

40

17

ARIZONA

Figure 28. Map showing reach classification by basin characteristics 

and nonmetric multidimensional scaling (NMDS) plot of reaches (inset) 

for the middle Verde River watershed, Arizona.
44 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

Map area

Sedona

Camp Verde

Cottonwood

Clarkdale

Cr

Sycamore

Creek

Bitter

Oak

keer C

Beaver

Dry

Wet

Beaver

st We

rael C

Creek

Fossil

ek re C ek re C

Ditch

sdno ami D sdno ami D

hcti Dedre V hcti Dedre V

Duff Ditch

Tavasci

hcti D

Jordan Ditch

OK Ditch

EurekaDitch

Back Ditch V Bar V Ditch

Reach V–VI

Reach IV–V

Reach III–IV

Reach II–III

34°45'

34°30'

112°30' 112°15'

0 4

0 4

6

6

2

2

8 MILES

8 KILOMETERS

Base from U.S. Census Bureau cartographic boundary files, 2000

Universal Transverse Mercator projection, Zone 12

North American Datum of 1983

Ditches

Streamflow gage

EXPLANATION

Seepage run reaches modified

 from Garner and Bills, 2012

Reach I–II

Upper-middle 

Verde River reaches

near Perkinsville

ARIZONA

Figure 29. Map showing reach classification by streamflow alteration for the 

middle Verde River watershed, Arizona (modified from Garner and Bills, 2012).
Fish 45

However, biotic interactions become more important when 

streams become stable, such as in a regulated flow environment (Ross and others, 1985; Power and others, 1988). 

Stream-channel drying can exacerbate predation and competition as habitat area and complexity decline. When stream 

drying occurs, both abiotic and biotic factors change, which 

can in turn affect the species diversity and the species density. 

Many streams in the desert Southwest naturally go dry or flow 

is reduced to pools sometimes connected by shallow riffles or 

runs (Capone and Kushlan, 1991; Magoulick, 2000). Bigger 

fish tend to be found in the deeper waters of pools to avoid 

terrestrial, diving predators (Power, 1988), whereas small fish 

tend to stay in shallow water with complex habitat in which 

they hide to avoid swimming predators (Power, 1984; Harvey 

and Stewart, 1991; Magoulick, 2000). Harvey and Stewart 

(1991) have shown that as water volume and depth decline in 

drying streams, susceptibility of prey to predation increases. 

Zaret and Rand (1971) found that fish showed increased 

competition for food in drying stream pools in Panama due to 

overlap in habitat.

Increases in native fish populations have been documented after large floods in desert streams (Rinne, 2005; 

Rinne and Miller, 2006). One possible explanation is that these 

fish change their habitat use in the presence of higher velocity 

flow. Rinne (1989) found that the habitat use of the loach minnow (Tiaroga cobitis) in the Gila River was directly correlated 

with velocity. In higher velocities, the loach minnow tended to 

use larger substrate. Native desert fishes will essentially hide 

behind large substrate to avoid being swept downstream with 

the current. Other behavioral adaptations to flow include fish 

moving to safe stream margins when they sense increasing 

stream velocity (Bain and others, 1988; Lytle and Poff, 2004). 

In flume experiments comparing two fish species common in 

Arizona streams, the non-native western mosquito fish (Gambusia affinis) did not share the ability of the Sonoran topminnow (Poeciliopsis occidentalis) to react quickly to an increase 

in velocity and retreat to safer habitat (Meffe, 1984). In the 

short term, the ability to find low-velocity habitat in the stream 

during high flows or the ability to change substrate use during 

high flow could explain why native fishes in the Verde River 

increase in abundance following floods. Ultimately, as floods 

wash out non-native fish, this results in an increased reproductive success for native fish.

Non-native Fish of the Verde

Since the beginning of the 20th century, streams of the 

southwestern United States have been the focus of many 

efforts to introduce new fish species, and non-native fish 

continue to be stocked for sport fishing, as bait fish, and for 

biological control (Rinne and Janisch, 1995; Schade and 

Bonar, 2005; Lomnicky and others, 2007; Whittier and Peck, 

2008). Intentional sport-fish stocking began toward the end 

of the 19th century with the introduction of common carp 

(Cyprinis carpio), channel catfish (Ictalurus punctatus), and 

various bass species (Micropterus spp.). Many more species 

have been introduced for sport fishing since then, including 

other catfish (Ictalurus spp., Pylodictis spp., Ameiurus spp.), 

northern pike (Esox lucius), crappies (Pomoxis spp.), sunfish 

(Lepomis spp.), rainbow trout (Oncorhynchus mykiss), brown 

trout (Salmo trutta), and brook trout (Salvelinus fontinalis) 

(Rinne and Janisch, 1995). Those brought in as bait fish often 

include smaller species such as fathead minnow (Pimephales 

promelas), red shiner (Cyprinella lutrensis), and golden shiner 

(Notemigonus crysoleucas). The most notable case of a species brought in for biological control was the introduction of 

western mosquito fish (Gambusia affinis), which was introduced for the purpose of controlling mosquitos (Hubbs and 

others, 1991).

Non-native species are a threat to native species in the 

Verde River, as well as in other streams in the American 

Southwest (Minckley and Meffe, 1987; Rinne and Minckley, 

1991), and have been since their introduction more than a 

century ago. Non-native fish have directly contributed to the 

decline and extirpation of native fish populations through 

predation, competition, and hybridization (Minckley and 

Marsh, 2009; Deacon, 1988; Miller and others 1989; Rinne 

and Miller, 2006; Schade and Bonar, 2005). For example, the 

western mosquitofish has eliminated the Sonoran topminnow 

in New Mexico and in many areas of Arizona (Hubbs and others, 1991) by preying on its eggs, larvae, and juveniles (Courtenay and Meffe, 1989). Both predation risk and competition 

can alter the behavior of native species by forcing the native 

species to move to less desirable habitat.

Rinne and Miller (2006) found a marked decrease in 

native fish accompanied by a significant increase in non-native 

fish in the upper-middle reach of the Verde River. They related 

this trend to changes in channel morphology, lower base flows, 

and reduced number of floods. A natural flow regime consisting of variable flows throughout the year can assist native 

populations by maintaining lower non-native populations 

(Rinne, 2005; Olden, 2006; Poff and others, 2007; Gido and 

Propst, 2012).

Native Fish of the Verde and Habitat 

Requirements

Fish taxonomic diversity has always been lower in the 

Southwest than in other parts of North America due to the 

unpredictable flow regimes found there (Moyle and Light, 

1996; Minckley and Marsh, 2009). Rapid extirpation and 

recolonization is an adaptation of native desert fish, and 

interconnected fish populations within a larger basin are called 

metapopulations and are very important for species that may 

be locally extirpated. Metapopulations provide a source for 

recolonization following localized extirpations resulting from 

extreme flooding or drought conditions. Rinne and Miller 

(2006) state that the native fishes in southwestern desert 

streams consist of 95 percent Cypriniformes and 5 percent 

other taxa. Included in the Cypriniformes are the families 

Catostomidae (suckers) and Cyprinidae (minnows and dace).
46 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

Rinne (2005) and Rinne and Miller (2006) provide the 

most complete summary of native and non-native fish in the 

Verde River. A number of species had already been extirpated 

by the time comprehensive surveys were beginning in 1994. 

From 1994 to 2005, Rinne and Miller (2006) collected fish at 

seven sites in the upper-middle Verde River by electrofishing 

and seining and found the following six native species—desert sucker (Catostomus clarki), Sonora sucker (Catostomus 

insignis), longfin dace (Agosia chrysogaster), speckled dace 

(Rhynichthys osculus), roundtail chub (Gila robusta), and 

spikedace (Meda fulgida). Abundance estimates declined 

sharply during their population surveys. For example, longfin dace numbered more than 1,300 in 1994 and then were 

reduced by nearly three orders of magnitude by 1999. Desert 

sucker saw a similar decline, from 2,644 in 1994 to 126 by 

1998. By 1997 non-native fish had become the dominant 

component in the Verde. A flood event occurred in 1995, but 

through the end of the Rinne and Miller (2006) study (through 

2005), no further flooding occurred.

The life history of native fish in the Verde River watershed is closely related to the unpredictable hydrologic regime 

which is the primary determinant for ecosystem structure and 

function in desert aquatic ecosystems. Aquatic-habitat requirements and use will vary greatly by species and are related to 

morphological characteristics such as body size and shape, 

feeding habits, and spawning requirements (Lytle and Poff, 

2004). Understanding the habitat characteristics required by 

native species is necessary for understanding how these species will be affected by habitat alteration related to changes in 

streamflow. In the following discussion regarding habitat use, 

we focus on the five common native species remaining in the 

Verde River—desert sucker, Sonora sucker, roundtail chub, 

speckled dace, and longfin dace (Rinne, 2005; Rinne and 

Miller, 2006).

Desert sucker young are generally observed in slow 

velocity gravel riffles, whereas the adults tend to feed and live 

in fast velocity riffles at night and use other types of riffle and 

pool habitat during the day (Rinne and Minckley, 1991; Rinne, 

1992). The Sonora sucker spawns from late winter to early 

summer and requires coarse gravel for egg burial and hatching (Lee and others, 1981). These fish are found under banks, 

boulders, and debris in moderately shallow, sandy, gravelly 

pools during the day, and like the desert suckers, move to riffles and runs at night (Minckley, 1973; Lee and others, 1981; 

Rinne, 1992). The roundtail chub spawns in late spring to 

early summer. Chub typically occur in deep, slow water over 

a range of substrate associated with cover (Rees and others, 

2005). The two dace species, longfin and speckled, are generally found in shallow water. Speckled dace typically occur in 

turbid high-velocity gravel/pebble riffles, whereas longfin dace 

use slower velocity riffles with sand/gravel substrates (Rinne, 

1992).

There are three non-native fish species that have significant populations and impacts on native fish populations 

in the Verde River (Rinne, 2005)—red shiner, green sunfish 

(Lepomis cyanellus), and smallmouth bass (Micropterus 

dolomieu). Red shiner have been found to consume larvae of 

Cypriniformes (specifically roundtail chub, speckled dace, and 

bluehead sucker) in the Yampa and Green Rivers (Ruppert and 

others, 1993). None of the other non-native fishes examined, 

including sand shiner, channel catfish, and fathead minnow, 

consumed fish larvae. Red shiner occupy shallow areas used as 

nursery habitat by other fishes. Red shiner prefer invertebrates 

as prey but are opportunistic feeders and have been found 

to eat other fish (piscivorous) when preferred food was not 

readily available (Ruppert and others, 1993). Green sunfish 

are known to be piscivorous and do prey on chub species. 

Predation on Gila chub by green sunfish has been observed by 

Dudley and Matter (2000). In areas with green sunfish, mostly 

large adult Gila chub were observed, likely because they were 

too large for green sunfish to eat. Roundtail chub of all life 

stages have been found in Turkey Creek in New Mexico above 

falls that prevented the invasion of smallmouth bass, but 

below the falls only adult roundtail chub were found, suggesting juveniles were preyed on by smallmouth bass (Bestgen 

and Propst, 1989).

Magoulick (2000) studied the influence of abiotic factors on fish assemblages in the pools of drying streams and 

found that fish species and the size of the individuals observed 

in the pools were related to water depth and surface area, 

habitat heterogeneity, and density of canopy cover. Capone 

and Kushlan (1991) found that pool persistence in drying 

streams was an important factor in determining fish assemblage when streamflow returned. Abiotic factors have been 

shown to be more important in unstable environments than 

in homeostatic environments, where biotic pressures may 

be more influential on fish community structure (Matthews 

and Styron, 1981; Schlosser, 1982). Magoulick (2000) also 

indicated that pool depth is an important abiotic factor for 

maintaining native fish in streams that lose significant base 

flow and dewater significant parts of the stream reach. Small 

fish such as speckled dace and longfin dace immediately suffer 

from the loss of shallow riffle habitat, being forced into pools 

with larger predator species (Haney and others, 2008). If the 

pools are deep and contain cover, then the risk of predation 

will be less, whereas if the pools are shallow, predation from 

large predators is likely imminent. Similarly, larger fish would 

suffer from a lack of deep pools by being unable to hide from 

terrestrial predators. Should base flow continue to decrease 

in the Verde River, several of native desert fishes could be at 

an even greater risk for extirpation. Fagan and others (2002) 

found that habitat fragmentation of Sonoran Desert fishes was 

much more likely to increase extinction risk than population 

declines alone. In fact, the number of species’ occurrences had 

no additional effect on extinction risk once fragmentation had 

been factored out.

Fish assemblages are also affected by high-flow events. 

Rinne (2005) demonstrated that native fish species showed 

significant population growth during high flow years, and this 

has also been documented elsewhere in the Southwest. In the 

San Juan River, Gido and Propst (2004) found that native dace 

and sucker species increased in numbers in years following 
Fish 47

high spring discharge (greater than 494 ft3/s) and non-native 

species, such as red shiner, Western mosquito fish, and common carp, benefited from low flow periods and declined in 

numbers during the high flows. Non-native species are not 

adapted to the flash floods that commonly occur during the 

North American summer monsoon. High flows are one of the 

last remaining natural defenses native fish have to non-native 

fish pressures.

Temporal and Spatial Considerations of Fish 

Data Collected in the Middle Verde Watershed

After reviewing fish-population surveys conducted by 

different agencies and evaluating the differences in sampling 

efforts among agencies, sampling efforts were determined 

to be mostly similar with a majority of the data provided by 

AZGFD. Independent of the timing of collection, the assemblage data showed interesting spatial patterns with greater 

percentages of native-fish populations in the upper-middle 

river reaches (fig. 25) than in the lower-middle reaches. However, there were areas upstream of Perkinsville that had lower 

percentages of native fish, similar to parts of the river adjacent 

to Cottonwood and Camp Verde. To determine the cause of 

this spatial pattern, other factors and sampling conditions 

must be considered (for example, timing, location, habitat, 

and flow conditions; fig. 30). The data collection (population 

surveys) distributions (fig. 30) indicate that more than half of 

the fish-population surveys occurred between 2004 and 2008 

and during the summer months (June–August) with moderate 

to no flooding conditions before sampling. More than half the 

collections occurred in the upper-middle Verde River (drainage area 2,000–3,000 square miles) in run habitat that was 

minimally affected by diversions.

Some fish collections did occur following large flow 

events and during extended periods of low flow (fig. 27). The 

duration of beneficial effects to native fish following a large 

flood are largely unknown, as is the magnitude that is necessary to initiate these beneficial conditions. Following a large 

flood in 1995 that exceeded 20,000 ft3/s (peak flow at Clarkdale gage), median percentages of native fish made up almost 

50 percent of the total fish population but then declined by 

about two-thirds by 2002 until 2005 when another large flow 

occurred exceeding 25,000 ft3/s (peak flow at Clarkdale gage; 

fig. 31). Following the 2005 event, the native-fish percentages 

rebounded until multiple years of moderate to low magnitude 

flooding conditions reduced the median native-fish percentages to less than 10 percent in 2009. The years of moderate 

flooding had variable effects on the percentages of native fish.

The timing, flow regime, and location of the fish surveys 

need to be considered when trying to understand the effects 

of flow alteration, although data can be difficult to interpret 

because of the large number of confounding human and environmental factors. One way to reduce the variability caused by 

environmental factors is to classify stream reaches based on 

basin characteristics. This classification scheme will be used 

first (fig. 28) and then followed by an evaluation using the 

flow-alteration reach classification scheme (fig. 29).

Distribution of Fish Using Basin Characteristic 

Reach Characterization

General spatial patterns, independent of time, from the 

312 fish surveys conducted between 1992 and 2011 indicate 

that native species generally were a greater percentage of the 

total fish population in the upper-middle than in the lowermiddle Verde River and decreased with downstream distance 

(fig. 25). Similar patterns were reported by Rinne (2005), and 

this pattern may be related to many factors including flow 

alteration (surface-water diversions and ground-water pumping), habitat, water quality, water chemistry, and (or) flow variability and volume (Rinne and Miller, 2006). It is likely that 

declining native-fish populations are related to a combination 

of stressors, including both anthropogenic factors and pressure 

from non-native fish through competition and predation. There 

were negative correlations between native-sucker families and 

non-native sunfish, minnow, and catfish families (τ= –0.53, 

–0.14, –0.17; all p <0.001). The NMDS ordination of species 

data showed that certain non-native species occurred in similar 

abundances and in similar locations with native species. 

Native and non-native fish regularly interact, suggesting that 

they compete for the same habitat resources (fig. 32). Predatory catfish and sunfish clustered near the native suckers and 

chub. Such use of similar habitat increases competition and 

the potential for predation. Similarly, the native-dace species 

cluster near red shiners and mosquito fish.

The five reaches (defined by basin characteristics) of 

the upper-middle and lower-middle Verde River described 

previously were used to compare the composition of fish 

assemblages (fig. 33). The reach designation showed that 

native fish were greater in the upper reaches of the watershed, 

where reaches are characterized with smaller drainages, less 

precipitation, and less flow. The trend of native-fish abundance decreasing with downstream distance was apparent as 

well. The median abundance of native fish decreased about 

50 percent from reach 1 to reach 5 (fig. 33A). The median 

percentage of native fish decreased by about 10–15 percent 

from reach 1 to 2, 15–20 percent from reach 2 to 3, and 20–25 

percent from reach 4 to 5. Differences were only statistically 

significant from reach 1 to 3 and reach 4 to 5. The percentages 

of native fish, as well as family composition (fig. 33B), were 

most similar in reaches 3 and 4, although the NMDS indicated 

larger differences in the basin characteristics than the other 

adjacent reaches, 1–2 and 4–5. The similarities in fish composition between reaches 3 and 4 may be related to the effects of 

basin urbanization and diversions, and these effects potentially 

predominate in these reaches. Land-use changes can alter the 

stream habitat by reducing flow and increasing sedimentation, 

and these habitat changes can lead to an increase in non-native 

fish species, such as bass and sunfish, that tend to spawn in 

low-velocity, pool habitats (Coles and others, 2012).
48 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona Drainage area, in sqaure miles

Y

Geomorphic channel unit sampled 

ear of sample of collection 

Number of samples Number of samples Number of samples

0

1,000

2,000

3,000

4,000

5,000

21

0

0

0

54

131

22

32

16

8

28

Not

Determined

Pool

Riffle

Run

26

54

45

169

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

0

2

3

1

11

0

25

12

10

21

49

36

32

37

13

26

28

6

3

4

0

2

Year of sample collection 

Prior flood condition 

Number of samples Number of samples

Month of sample of collection 

0

2

28

99

96

51

17

14

4

1

High flood

Moderate flood

Average or 

base flow

38

86

184

0 ft3/s

0 to 5 ft3

/s

0 to 5 ft3

/s

37 to 65 ft3

/s

8 to 96.5 ft3

/s

None

8

52

1

24

24

203

Number of samples

Degree of diversion in reach,

in cubic feet per second

Reach above Clarkdale 

gage, reach above 

Perkinsville, and reach I–II

Reach II–III

Reach III–IV

Reach VI–V

Reach V–VI

Perkinsville 

Dec

Nov

Sep

Oct

Aug

Jul

Jun

May

Apr

Mar

187

Figure 30. Plots showing the distribution of fish-survey data collection for the middle Verde River watershed, Arizona, by drainage 

area, geomorphic channel units, year of collection, month of collection, flow condition, and degree of diversion. ft3/s, cubic feet per 

second.
Fish 49

0

25

50

75

100

1995 1996 1997 1998 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

1 11 24 12 8 47 36 11 25 27 3

Mean daily discharge, in cubic feet per second at Verde River at Clarkdale

Percent native fish

Water year EXPLANATION

Largest value within 1.5 times 

interquartile range above 75th 

percentile

Outside value—Value is >1.5 and 

<3 times the interquartile range 

beyond either end of the box

75th percentile

Smallest value within 1.5 times 

interquartile range below 25th 

percentile

25th percentile

50th percentile (median)

Interquartile 

range

Hydrograph

36 Number of values

Sample influcenced by one or more 

high flows (two orders of magnitude

above average flow)

Sample influcenced by moderate flow

(2-year flood frequency magnitude)

Sample influcenced by mean- or base-flow

(less than mean flow)

100

200

300

400

500

600

700

800

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

10,000

20,000

Box color classification from figure 27

19 36 32

Figure 31. Graph showing boxplots of the percent native 

fish species collected from the middle Verde River, Arizona, 

from 1995 to 2011. Boxplots are color coded according to flood 

magnitude classes—high (green), moderate (blue), and low 

(yellow) flood years.

The transition to greater proportions of sunfish started 

in reach 2, where the percentage is similar to suckers and 

becomes significantly greater by reach 3. At reach 5 the 

median percent of sunfish is 10 times that of the suckers (fig. 

33B). The minnow and catfish families stayed relatively consistent throughout the entire middle Verde River reach (from 

2 to 10 percent), and the mosquito fish and rainbow trout (not 

shown) had very minor contributions. The feeding guilds 

in reach 1 and 2 are more evenly distributed than the other 

reaches. Piscivores were about twice as common as other feeding groups in reaches 3, 4, and 5 where the piscivore feeding 

guild was made up primarily of sunfish species (fig. 33C). 

Predation from non-native fish is among the many stressors 

affecting native fish populations in the Verde River.

The patterns in the NMDS ordination supported that 

specific Verde River reaches were an important factor in fish 

assemblages (fig. 34). Fish assemblages for reaches 1 and 

2 (or the upper-middle Verde River) are grouped separately 

from fish in reaches 3, 4, and 5. The native sucker families 

and the catfish were more strongly associated with reaches 1 

and 2, whereas the sunfish were more closely associated with 

reaches, 3, 4, and 5. Reach 5 had the lowest proportion of 

native fish, and fish in this reach plotted furthest away from 

all other reaches.

Geomorphic channel units were assigned to each Verde 

River sampling location using aerial imagery. One of three 

class options, pool, run, or riffle, was assigned to each 

sampling location on the Verde River. This type of habitat characterization is a general estimation of geomorphic 

descriptors, although results appeared to be sensitive enough 

to distinguish between flow-substrate and presence of different families (fig. 35A). The median of percent native fish was 

significantly greater (p=0.0070, Wilcoxon rank sums pairwise 

test) in stream reaches classified as run than in those classified as pool. Non-native fish were more often found using 

pool habitat (p=0.0022, Wilcoxon rank sums pairwise test) 

than native fish. Family differences reflected the differences 

among native and non-native fish, because all suckers are 

native (found most often in runs) and all the sunfish are nonnative (most often found in pools, fig. 35B). The minnow and 

catfish families were found in all pool, riffle, and run habitat 

equally.
50 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

Non-native fish

Native fish

black bullhead

bluegill

brown bullhead

channel

catfish

common carp

desert sucker

flathead catfish

green sunfish

largemouth bass longfin dace

mosquitofish

rainbow trout

razorback sucker

red shiner

redear sunfish

rock bass

roundtail chub

smallmouth

bass

sonora sucker

speckled dace

yellow bullhead

Two-dimensional stress: 0.08

EXPLANATION

NMDS axis 2

NMDS axis 1

Groups idendified by

cluster analysis of 

species observed in

similar abundances

and locations

Transformation: fourth root

Resemblance matrix: Bray Curtis similarity matrix

Centrarchidae 

(sunfish family)

Cyprinidae

(minnow family)

Ictaluridae 

(catfish family)

Catostomidae

(sucker family)

Figure 32. Diagram showing nonmetric multidimensional scaling (NMDS) ordination of fish-species 

similarities across all samples from the middle Verde River, Arizona. Species are identified by family (except 

for trout and mosquitofish) and native and non-native identification. Significant clusters are highlighted with 

circle outlines. Common and scientific names for native fish species: desert sucker (Catostomus clarki), 

razorback sucker (Xyrauchen texanus), Sonora sucker (Catostomus insignis), roundtail chub (Gila robusta), 

speckled dace (Rhinichthys osculus), longfin dace (Agosia chrysogaster). Common and scientific names for 

non-native fish species: largemouth bass (Micropterus salmoides), smallmouth bass (Micropterus dolomieu), 

rock bass (Ambloplites rupestris), green sunfish (Lepomis cyanellus), redear sunfish (Lepomis microlophus), 

brown bullhead (Ameiurus nebulosus), black bullhead (Ameiurus melas), yellow bullhead (Ameiurus natalis), 

channel catfish (Ictalurus punctatus), flathead catfish (Pylodictis olivaris), common carp (Cyprinus carpio), red 

shiner (Cyprinella lutrensis), rainbow trout (Oncorhynchus mykiss), western mosquitofish (Gambusia affinis).

Distribution of Fish Using Flow-Alteration Reach 

Characterization

In the second scheme, reaches were defined by degree 

of alteration from ditches and diversion (Garner and Bills, 

2012). Fish data collected in the reaches of the lower-middle 

Verde River were also compared to fish data collected in 

the upper-middle Verde River watershed, above and below 

Perkinsville (minor diversions below Perkinsville, see fig. 28) 

and the major tributaries to the Verde River—Oak Creek, Wet 

Beaver Creek, and West Clear Creek (fig. 29). Fish data were 

collected over the course of many years and during different 

months.

There was a significant decrease in the median percentage of native fish from the upper-middle Verde River reaches, 

where fewer diversions exist, to reach II–III, which is characterized as a highly diverted reach (p<0.001, Wilcoxon 

pairwise test) (fig. 36A). Reach III–IV is a short section of 

river where diverted water is returned to the river and no other 

major diversions exist. In this nondiverted reach, the median 

percentage of native fish increased about 20 percent. In reach 

IV–V, where water is diverted to the OK, Eureka, Verde, and 

Diamond S ditches the median percentage of native fish then 

decreased by about 10 percent and was significantly less than 

in the upper-middle reaches. The percentage of native fish 

continued to decrease in reach V–VI (p<0.001, Wilcoxon 

pairwise test), at which point a large volume of water has been 

diverted from the Verde River. Native-fish percentage was 

significantly less here than in any of the other reaches further 

upstream. In the undiverted upper reaches of the Middle Verde 

River watershed, native suckers made up the greatest proportion of fish assemblages (fig. 36B). In the downstream reaches 

of the river, where there are more diversions, the proportion of 

suckers was reduced and the percentage of non-native sunfish 

increased. However, the median percentage of minnows and 

catfish did not increase beyond that of the suckers until reach 

V-VI.

The NMDS ordination of the reach-assemblage multivariate centroids (fig. 37A) supports the changes observed in 

fish-assemblage composition when proportions of native fish 

are evaluated from upstream to downstream along the middle 

Verde River. Note that figure 37B and figure 37C are the 

same NMDS ordination plot, but different categorical information is superimposed on to each assemblage. In fig. 37B, 
Fish 51

A

B

Native fish, in percent

Native fish families, in percent

0

20

40

60

80

100

Family

Suckers

Sunfishes

Minnows

Catfish

EXPLANATION

Reach 1 Reach 2 Reach 3 Reach 4 Reach 5

Reach 1 Reach 2 Reach 3 Reach 4 Reach 5

Verde River West Clear Creek

0

20

40

60

80

100 Feeding guild, in percent

Feeding guild (dominant source)

Herbivore (plant diet)

Insectivore (insect diet)

Insectivore/Piscivore (insect and fish diet)

Omnivore (plant and anmimal diet)

Piscivore (fish diet)

EXPLANATION

Reach 1 Reach 2 Reach 3 Reach 4 Reach 5

West Clear Creek

0

20

40

60

80

100

131

131

31

31 17

32

32 * 

21

21

Verde River

C

36 Number of samples

EXPLANATION

Largest value within 1.5 times 

interquartile range above 75th 

percentile

Outside value—Value is >1.5 and 

<3 times the interquartile range 

beyond either end of the box

Smallest value within 1.5 times 

interquartile range below 25th 

percentile

Interquartile 

range

Wilcoxon pairwise tests-significant difference ( p≤0.05) a, b, c.

Kruskal-Wallis Test, chi square * (p≤0.05).

a

a, b

b b

c

* * * 

77

77

131 77 32 21 31 17

In A, a bar labeled "a" is significantly different from bars that 

include labels without the letter "a" (b; c; b,c) but is not 

significantly different from any labeled with an "a" (a; a,b; a,c); 

likewise for b and c.

75th percentile

25th percentile

50th percentile (median)

Figure 33. Graphs showing boxplots of native fish from the middle Verde River, Arizona, in 

percent (A) grouped by basin characteristic reaches, (B) divided into family classifications (see 

figure 32 for scientific family names), and (C) divided into feeding-guild classifications.
52 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

the assemblage for each location in the seepage-run is color 

coded by reach and related to correlated species; in fig. 37C, 

the color coding was assigned by the degree of diversion and 

correlated with four dominant fish families. West Clear Creek, 

which joins the Verde River upstream of reach V–VI, was 

included to demonstrate where a mostly undiverted tributary 

(above the West Clear Creek campground, fig. 29) would plot 

in relation to the Verde River reaches (fig. 37B). Although 

West Clear Creek fish assemblages were more similar to the 

minimally diverted reaches of the upper-middle Verde River 

than to diverted reaches in the lower-middle Verde River, there 

are also habitat considerations that contribute to the similarities in assemblages (fig. 37C). The percentage of non-native 

sunfish was more correlated with reaches having significant 

surface-water diversions than were percentages of either 

native suckers or minnows. There was also overlap of nonnative fish—mostly largemouth bass, channel catfish, flathead 

catfish, and green sunfish—in the diverted reaches II–III and 

V–VI.

The percent suckers and percent sunfish and overall abundance of each as reported in the available studies were plotted 

against the location (river mile) where they were observed 

along the middle Verde River. There was a statistically significant decrease in the percentage and abundance of suckers and 

a statistically significant increase in the percentage of sunfish 

with distance downstream (fig. 38A, B). In the upper-middle 

reaches, suckers were often at or above 50 percent of the fish 

population, whereas in the lower-middle reaches, suckers were 

mostly below 50 percent and sunfish were consistently at or 

above 50 percent of the population (fig. 38C). Samples collected after large and moderate floods in diverted reaches were 

limited, but there is some evidence to suggest that in highly 

diverted reaches during larger flood years, native sucker 

abundance was lower than in undiverted reaches (fig. 38B). 

Below the most highly diverted reaches (II–III and IV–V), the 

percentage of suckers was significantly lower than the percentage of sunfish.

Relation of Flow Metrics to Fish Community 

Metrics and Assemblages to Flow Metrics

Fish metrics were calculated for a subset of samples that 

were near a streamgage, and flow metrics were computed 

for 30, 90, and 365 days before the collection. Correlation 

scatter plots were used to identify significant relations using a 

Kendall’s tau coefficient (p≤0.05). Overall, most flow and fish 

metric correlations showed weak associations (τ<0.3).

Fish total abundance (total number of all fish collected) 

was the primary fish metric associated with the 30-day flow 

metrics. More significant associations were identified with the 

365-day flow metrics (fig. 39) than with the 30-day or 90-day 

flow metrics. There were also more negative correlations with 

the 365-day flow metrics (particularly with minnows and 

Greater percentage of

suckers

Greater percentage of minnows

Greater percentage of catfish

Greater percentage of sunfish 

Transformation: Fourth root

Resemblance matrix: Bray Curtis similarity matrix

Two-dimensional stress: 0.21

Sites located in reach 1

Sites located in reach 2

Sites located in reach 3

Sites located in reach 4

Sites located in reach 5

NMDS axis 2

NMDS axis 1

EXPLANATION

Figure 34. Diagram showing nonmetric multidimensional scaling (NMDS) ordination for fish assemblages labeled by basin 

characteristic reaches for the middle Verde River, Arizona. Fish families are shown as correlation vectors (see figure 32 for 

scientific family names).
Fish 53

A

B Fish family, in percent

Native fish, in percent

0

20

40

60

80

100 54 45 169

54 45 169

Pool Riffle Run

Pool Riffle Run

0

20

40

60

80

100

Family

Suckers

Sunfishes

Minnows

Catfish

a

a, b

a b

c c

a a

b

 b

b

a

a

b

b

36 Number of samples

EXPLANATION

Largest value within 1.5 times 

interquartile range above 75th 

percentile

Outside value—Value is >1.5 and 

<3 times the interquartile range 

beyond either end of the box

Smallest value within 1.5 times 

interquartile range below 25th 

percentile

Interquartile 

range

Wilcoxian pairwise tests significant difference ( p≤0.05) a, b, c.

A bar labeled "a" is significantly different from bars that 

include labels without the letter "a" (b; c; b,c) but is not 

significantly different from any labeled with an "a" 

(a; a,b; a,c); likewise for b and c.

75th percentile

25th percentile

50th percentile (median)

Figure 35. Graphs showing boxplots of (A) percent native fish for each geomorphic channel unit (GCU-pool, riffle, run) classification 

and (B) each family percentage (see figure 32 for scientific family names) within each GCU classification for samples collected on the 

middle Verde River, Arizona.
54 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona Native fish, in percent

c

A

BFish family, in percent

Fish family

Suckers

Sunfishes

Minnows

Catfish

Oak

 Creek

Beaver

Creek

West Clear

Creek

OK, Eureka, Damond, 

and Verde Ditches

Tavasci, 

Hickey, and 

Cottonwood 

Ditches

Discharge, in cubic feet per second

0

20

40

60

80

100

0

50

100

200

150

a

a

b

a,b

b

February 2011

seepage run

June 2007

seepage run

50 60 70 80 90

Distance downstream of Sulliven Dam, in miles

II–III III–IV IV–V V–VI

II–III III–IV IV–V V–VI

0

20

40

60

80

100

156 52 24 8 24 28

156 52 24 8 24 28

36 Number of samples

EXPLANATION

Largest value within 1.5 times 

interquartile range above 75th 

percentile

Outside value—Value is >1.5 and 

<3 times the interquartile range 

beyond either end of the box

Smallest value within 1.5 times 

interquartile range below 25th 

percentile

Interquartile 

range

Wilcoxon pairwise tests-significant difference ( p≤0.05) a, b, c.

Upper-middle 

Verde River above 

Perkinsville 

Upper-middle 

Verde River below 

Perkinsville 

Upper-middle 

Verde River above 

Perkinsville 

Upper-middle 

Verde River below 

Perkinsville 

Reach

Reach

A bar labeled "a" is significantly different from bars that include 

labels without the letter "a" (b; c; b,c) but is not significantly 

different from any labeled with an "a" (a; a,b; a,c); likewise for 

b and c.

75th percentile

25th percentile

50th percentile (median)

Figure 36. Graphs showing boxplots of native fish in the 

middle Verde River, Arizona, in percent (A) and grouped by 

streamflow alteration reaches as defined by Garner and Bills 

(2012) and (B) divided into family classifications (see figure 32 

for scientific family names).
Fish 55

catfish) than with the 90-day metrics which were generally 

positively associated with fish metrics (particularly sunfish). 

More responsive (significant relation) high-flow metrics 

included those associated with magnitude and frequency, such 

as maximum monthly flow, median annual number of highflow events, and median annual maximum streamflow. More 

responsive low-flow metrics included those associated with 

flow magnitude and frequency of discrete low-flow periods, 

including minimum monthly flow and median annual number 

of low-flow periods. Other responsive flow metrics were those 

describing the rate of change or the variable flow conditions 

related to flooding “flashiness” of the streamflow. These 

include the base-flow recession coefficient, 50th percentile 

of absolute value of percent daily change, and coefficient of 

variation of the log-transformed daily flows.

Several flow metrics were plotted against the fish metrics 

using quantile regression (figs. 40 and 41). Significant ceiling 

and floor thresholds (quantile thresholds at the largest quantile 

with narrowest confidence intervals for regression line slope) 

were analyzed for directionality of the association with the 

fish metrics. For the 365-day metrics, the percent of native 

suckers responded more positively to the ratio of the median 

annual minimum daily streamflow and median streamflow 

(Qmin/Q50; fig. 40A) at the higher quantiles. At about the 0.80 

quantile was the greatest slope and approximate threshold 

of the sample distribution. This metric is a measure of seasonal streamflow variation during periods of low flow. The 

sucker response was negative to the median annual number of 

low-flow periods (fig. 40B), but the slopes were an order of 

magnitude less than Qmin/Q50 slopes indicating about the same 

response (2–5 percent decrease) from 1 to 6.5 low-flow events. 

The greatest response (slopes) was similar between the 0.50, 

0.75, and 0.90 quantiles. This suggests that suckers are sensitive to variability in low-flow periods and are somewhat less 

sensitive to the number of periods. Sunfish population proportions, which are negatively correlated to sucker proportions, 

responded positively to the minimum monthly streamflow (fig. 

40C). This response was greatest at the 0.50-quantile threshold, and slopes were relatively small, about a 0.5–1 percent 

response change. Although sunfish respond more positively 

to higher minimum monthly streamflows, suckers (not shown 

in graph) appear to have a greater upward response at lower 

minimum values but then decrease as the minimum monthly 

streamflow increases.

The significant fish-metric responses to the 90-day flow 

metrics were primarily related to variability (fig. 41). The 

inverse relation between suckers and sunfish is more prominent in the 90-day flow metric relations (suckers, fig. 41A and 

41B; sunfish, fig. 41C and D). For example, the percentage 

of suckers had negative responses with greater slopes for the 

0.75–0.90 quantiles for the hydrologic metrics—coefficient of 

variation of log-transformed daily streamflow (fig. 41A) and 

the normalized range of monthly streamflow (fig. 41B). The 

normalized range of monthly flow (NRMF) is the difference 

between the maximum and minimum monthly flow each year 

divided by the mean flow for that year. The percentage of 

sunfish increased with increasing coefficient of variation of 

log-transformed daily flows and NRMF (fig. 41C and 41D, 

respectively), but the greatest slopes occurred at about the 0.60 

coefficient of variation of log-transformed daily flows and 

0.30 (NRMF) quantiles. These two metrics represent measures 

of daily and seasonal variability, respectively. With the relation 

of coefficient of variation of log-transformed daily flows, the 

percentages of suckers decrease by more than 50 percent for 

three quarters of the sample distribution (fig.41A), whereas 

the sunfish distribution increases by 10–20 percent as coefficient of variation of log-transformed daily flows increases. 

The coefficient of variation of log-transformed daily flows 

may be susceptible to differing results (slope direction change) 

depending on the time interval used for calculation of flow 

metrics. A similar pattern to coefficient of variation of logtransformed daily flows is occurring with suckers and sunfish 

in relation to the NRMF metrics suggesting that NRMF and 

coefficient of variation of log-transformed daily flows might 

be correlated because they are both measures of variability.

The relations among flow metrics, diversions, and other 

stressors, such as non-native fish is a complex and dynamic 

one. It can be difficult to detect the signal of flow alterations 

within the noise (variability) created by confounding variables 

in large scale studies. West Clear Creek is the only tributary 

with fish-assemblage data collected over several years and 

no flow alteration. The fish community has changed since the 

early 1990s to a more introduced-species dominated stream. 

A NMDS ordination shows how assemblages have changed 

over time, with the percentage of native fish declining in the 

early 2000s but increasing in samples collected in 2004, 2007, 

2008, and 2011 (fig. 42A). Figure 42B shows the same NMDS 

ordination but with median number of high-flow events plotted instead of native fish. The high-flow overlay suggests the 

increased number of flows may be influencing the community 

shifts in the fish assemblages from 1995–2000 to 2009–2011.

Pilot Study—Native and Non-native Fish 

Microhabitat

A fish microhabitat pilot study was developed and executed to investigate native and non-native fish and their associations to microhabitat and flow characteristics in the Verde 

River and its major tributaries. The main objectives of the pilot 

study were to compare abundance and distribution of native 

and non-native fish at five sites in the Verde River watershed 

and to describe microhabitat use by native and non-native fish. 

With a protocol for understanding microhabitat requirements 

of aquatic biota developed for the five sites, it can then be used 

in the future to understand microhabitat requirements in other 

areas in the upper-middle and lower-middle Verde River.

The life histories of native fish in the Verde River 

watershed are closely related to the unpredictable hydrologic 

regime. This is the primary determinant for ecosystem structure and function in desert aquatic ecosystems. Aquatic microhabitat requirements and use will vary greatly by species, and 
56 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

Percentage of fish in 

the sucker family

Percentage of fish

in the catfish family

Percentage of fish 

in the minnow family

Percentage of fish in the 

sunfish family 

A

B

C

Two-dimensional stress: 0.21

Site degree of diversion (fig. 37C)

Minimal

Moderate

Significant

Bluegill

channel catfish

common carp

desert sucker flathead catfish

green sunfish

largemouth bass

roundtail chub

smallmouth bass

Sonora sucker

speckled dace

yellow bullhead

longfin dace

Sites within each reach (figs. 37A and B)

Upper-middle Verde River

Upper-middle Verde River 

above Perkinsville

V–VI

IV–V

III–IV

II–III

West Clear Creek

Two-dimensional stress: 0

Two-dimensional stress: 0.21

Decreasing surface water diversions Increasing surface water diversions

Upper-middle 

Verde River

Upper-middle Verde

above Perkinsville

V–VI

IV–V

III–IV

II–III

West Clear Creek

Transformation: Fourth root on all plots

Resemblance: Bray Curtis similarity matrix on all plots

NMDS axis 2

NMDS axis 1

NMDS axis 2

NMDS axis 1

NMDS axis 2

NMDS axis 1

EXPLANATION

Figure 37. Diagrams showing nonmetric 

multidimensional scaling (NMDS) 

ordination plots of (A) multivariate 

centroids of fish group assemblages, (B) 

NMDS ordination of assemblages with 

vector overlay of fish species labeled 

by reach, and (C) NMDS ordination of 

assemblages with vector overlay of fish 

families (see figure 32 for scientific fish 

names) labeled by degree of diversion for 

the middle Verde River, Arizona. 
Fish 57

A

0 20 40 60 80 100

Distance, in miles

0950370009504000

Reach IIReach IIIReach IV

09506000

Percent suckers Percent sunfish

0

20

40

60

80

100

0

20

40

60

80

100

τ=0.1901,

p<0.0001

τ=−0.1643,

p<0.0001

τ=−0.2051

p<0.0001

0 20 40 60 80 100

10

100

10

100

1

1

Streamflow conditions at site of fish collection

High

Moderate

Low

B

0

10

20

30

40

50

60

70

80

90

100

Percent 

Upper-middle Verde River Upper-middle Verde River 

below Perkinsville Reach II–III Reach III–IV Reach IV–V Reach V–09506000

Low flow Moderate

flood (6)

*

*

*

* * *

* *

*

*

* Significant difference ( p≤0.05)

Sunfishabundance

Suckersabundance

Reach I

Reach V

Suckers

Sunfish

EXPLANATION

Largest value within 1.5 times 

interquartile range above 75th 

percentile

Outside value— Value is >1.5 and 

<3 times the interquartile range 

beyond either end of the box

Smallest value within 1.5 times 

interquartile range below 25th 

percentile

Interquartile 

range

LOWESS line

Highly diverted reach

(36) Number of samples

C

(108)

Low flow

(23) (33) (2)

Moderate

flood (25)

High flood Low flow

(13) (7)

High flood Low flow

(2) (17)

Moderate High flood Low flow flood (6)Moderate

flood (17) (6)

Low flow Moderate

flood (17)

Moderate

flood (11)

75th percentile

25th percentile

50th percentile (median)

Figure 38. Graphs of (A) relative abundance (percent of total count of individuals) of 

suckers (family Catostomidae) and sunfish (family Centrarchidae) and respective locally 

weighted scatterplot smoothing (LOWESS) trend lines, (B) total abundance (total count 

of individuals in family) of suckers and sunfish and LOWESS trend lines, and (C) relative 

abundance of suckers and sunfish plotted as boxplots categorized by reach and flood 

condition for the middle Verde River, Arizona. 09503700, Verde River near Paulden; 09504000, 

Verde River near Clarkdale, AZ; 09506000, Verde River near Camp Verde, AZ. τ, Kendall’s tau 

correlation coefficient presented for trend significance at p<0.05.
58 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona Percent suckers Percent sunfish Percent minnows Percent catfish Percent native 50th percentile of absolute value of percent daily change Base-flow recession coefficient (BFR) Coefficient of variation of annual minimum streamflow Coefficient of variation of log-transformed annual maximum flow LOG(Q10/Q90) Maximum monthly streamflow Mean streamflow Median annual minimum streamflow Median annual maximum streamflow Median annual number of low-flow periods Median annual number of high-flow events Median duration of the annual longest low-flow period Median duration of the annual longest high-flow event Minimum monthly streamflow Normalized range of monthly streamflow Number of months with annual probability >0.5 of having a low flow-flow period

Q01

Q10Q25Q50Q75Q90Q99

Qmin/Q50

Storm-flow recession coefficient (SFR)

Coefficient of variation of daily flows

Coefficient of variation of log-transformed daily flows

LOG(Q10/Q90)

Maximum monthly streamflow

Mean streamflow

Median annual maximum streamflow

Median annual number of low-flow periods

Median annual number of high-flow events

Median duration of the annual longest high-flow event

Normalized range of monthly streamflow

Number of months with annual probability >0.5 of having a high flow

Q01

Q99

Q

max/Q50

−0.3 −0.1 0.0 0.1 0.2 0.3 −0.3 −0.1 0.0 0.1 0.2 0.3 −0.3 −0.1 0.0 0.1 0.2 0.3 −0.3 −0.1 0.0 0.1 0.2 0.3 −0.3 −0.1 0.0 0.1 0.2 0.3

90-day metrics365-day metrics

Hydrologic metrics

Kendall’s tau

Figure 39. Graph of significant correlations (Kendall’s tau (

τ) correlation 

coefficient, 

p≤0.05) between 90- and 365-day hydrologic metrics and select 

fish metrics for the for the middle Verde River, Arizona. See figure 32 for scientific family names. 
Fish 59

80

60

40

20

-20

0

0.2 0.4 0.6 0.8

100

75

25

50

0

0.2 0.4 0.6 0.8

100

75

50

25

0

0.2 0.4 0.6 0.8

2.5

0

-5.0

-2.5

-7.5

0.2 0.4 0.6 0.8

Percent suckers

0

20

40

60

80

100

0 0.2 0.4 0.6 0.8 1.0

Percent suckers

0

20

40

60

80

100

0 1 2 3 4 5 6 7

Quantile Quantile Quantile Quantile Intercept Slope

Intercept

Slope

A B

60

40

20

0

0.2 0.4 0.6 0.8

Quantile

Intercept

1.5

1.0

-0.5

0.5

0

0.2 0.4 0.6 0.8

Quantile

Percent sunfish

0

20

40

60

80

100

Minimum monthly streamflow (365 days prior)

0 10 20 30 40 50

C

Slope

Quantile

0.1

0.25

0.5

0.9

Blue bands represent 

95-percent confidence 

intervals

EXPLANATION

0.75

Median annual (low-flow year) minimum daily streamflow 

(Qmin) divided by median streamflow (Q50), 365 days prior to 

sample period (unitless)

Median annual number of low-flow periods, 365 days prior to 

sample period

Figure 40. Graphs showing quantile regression lines, 

intercepts, and slopes of the 0.10, 0.25, 0.50, 0.75, and 

0.90 quantiles for significantly correlated 365-day 

hydrologic and fish metrics for the middle Verde River, 

Arizona. A, percentage of suckers (Catostomidae) 

and minimum flow divided by the median flow; B, 

percentage of suckers and median annual number of 

low-flows, and C, percentage of sunfish (Centrarchidae) 

and the minimum monthly streamflow.
60 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

100

80

60

40

20

0

0.2 0.4 0.6 0.8

50

0

-50

-100

0.2 0.4 0.6 0.8

80

60

40

20

0

0.2 0.4 0.6 0.8

10

0

-20

-10

-30

0.2 0.4 0.6 0.8

Percent suckers

0

20

40

60

80

100

Coefficient of variation of log-transformed daily flows (90 days prior)

0 0.2 0.4 0.6 0.8 1.0 1.2

Percent suckers

0

20

40

60

80

100

0 0.5 1.0 1.5 2.0 2.5 3.0 3.5

Normalized range of monthly flow (90 days prior)

Quantile Quantile Quantile Quantile

Intercept

Slope

Intercept

Slope

A B

80

60

40

20

0

0.2 0.4 0.6 0.8

Quantile

Intercept

100

0

50

-50

0.2 0.4 0.6 0.8

Quantile

80

60

40

20

0

0.2 0.4 0.6 0.8

Quantile

40

0

-20

-20

0.2 0.4 0.6 0.8

Quantile

Percent sunfish

0

20

40

60

80

100

Coefficient of variation of log-transformed daily flows (90 days prior)

0 0.2 0.4 0.6 0.8 1.0 1.2

Percent sunfish

0

25

50

75

100

0 0.5 1.0 1.5 2.0 2.5 3.0 3.5

Normalized range of monthly flow (90 days prior)

C D

Quantile

0.1

0.25

0.5

0.9

EXPLANATION

0.75

Blue bands represent 95-percent 

confidence intervals

Figure 41. Graphs showing quantile regression lines, intercepts, and slopes of the 0.10, 0.25, 

0.50, 0.75, and 0.90 quantiles for significantly correlated 90-day hydrologic and fish metrics for 

the middle Verde River, Arizona. A, percentage of suckers (Catostomidae) and coefficient of 

variation of the log-transformed mean daily flows ; B, percentage of suckers and the normalized 

range of monthly flow (NRMF); and C, percentage of sunfish (Centrarchidae) and coefficient of 

variation of the log-transformed mean daily flows; and D, percentage of sunfish and NRMF.
Fish 61

are related to morphological characteristics, such as body size 

and shape, feeding habits, and spawning requirements (Lytle 

and Poff, 2004). Understanding the microhabitat characteristics required by native species is necessary for understanding 

how these species will be affected by microhabitat alteration 

related to changes in streamflow.

Fish Data Collection Methods for Pilot 

Microhabitat Study

The microhabitat pilot study was conducted in 2012 

as part of a collaborative effort between NAU and USGS. 

Research focused on fish and macroinvertebrate data collection, geomorphology, hydrology, and microhabitat at five locations within the Verde River watershed—three upper-middle 

Verde River watershed locations (Verde River below Granite 

Creek, Verde River at Perkinsville, and the Verde River near 

Paulden gaging station) and two large tributaries (West Clear 

Creek near Camp Verde gaging station and Oak Creek Near 

Cornville gaging station) (fig. 25).

Fish data were collected using three methods—(1) electrofishing using a backpack electrofisher, (2) seining, and (3) 

visual underwater identification while snorkeling. Snorkeling 

and seining methods were used where conditions permitted. 

Electrofishing took place in subreaches where microhabitat 

types had high water velocities or there was too much suspended sediment for visual identification. Electrofishing took 

place in all five sample reaches but not microhabitat types. 

Fish were measured for total length using a metric ruler then 

returned unharmed to the stream away from electrofishing 

activity once they regained mobility. When snorkeling, fish 

were identified to species (Reynolds, 1983), and total fish 

length was estimated using a ruler underwater. The snorkeler dropped a numbered, weighted float where a fish was 

observed, so that microhabitat measurements could be made 

later at the location of the identified fish. Pools and runs were 

snorkeled at West Clear Creek and Oak Creek. Seining was 

also used as a sampling method to collect fish in deep pools. 

Seines were used as block nets in the high-velocity riffles at 

the Paulden and Perkinsville Verde River locations. The specific location where each fish was collected or observed was 

revisited within 30 minutes following fish identification for 

microhabitat data collection.

Microhabitat Characterization Methods for Pilot 

Microhabitat Study

Microhabitat measurements were made at the point where 

a fish was collected or observed during the snorkeling, electrofishing, and seining surveys, as well as from 50 randomly 

A

B

1.5

1.5

1.5

1

1

0.5

0.5

6

3

3

1

2

Two-dimensional stress: 0.06

Two-dimensional stress: 0.06

Percent native fish

Median annual number 

of high-flow events (365 days)

10

40

70

100

1995

1996

1997

2000

2002

2003

2004

2004

2007

2008

2009

2010

2011

2011

0.6

2

4

6

0

0

NMDS axis 2

NMDS axis 1

Late spring sample

Fall sample

Late spring sample

Fall sample

EXPLANATION

EXPLANATION

Figure 42. Diagrams showing 

nonmetric multidimensional 

scaling (NMDS) ordination 

plot of assemblages collected 

from West Clear Creek in 

1995–2011 for the middle Verde 

River watershed, Arizona. A, 

Percent native fish species is 

superimposed as a bubble plot. 

B, Same years as A but median 

annual number of high-flow 

events is shown.
62 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

selected points selected from a mapped grid of each reach (45 

points at Perkinsville) (table 9). Microhabitat data collected in 

this study included water velocity, water depth, substrate size 

(b-axis) measurements, and riparian canopy cover. A velocity measurement was taken using the six-tenths depth method 

(Buchanan and Somers, 1969) at the location of each fish, as 

well as at each of the randomly selected points using a MarshMcBirney flow meter, Pygmy meter model 6205, or SonTek 

flow-tracker. Velocities were measured to hundredths of a foot 

per second and depths to tenths of a foot. River habitat was 

described using established fluvial geomorphology classifications (Flosi and others, 2010), along with several common 

monitoring and assessment protocols (Peck and others, 2006; 

Moulton and others, 2002). Habitat types were classified as 

pool (wide, deep, slow moving), glide (fast moving, smooth 

water surface, wide, shallow), run (fast moving, smooth water 

surface, narrow, deep), riffle (fast moving, steep, shallow, 

high Froude number, rough water surface), or rapid (rapid and 

turbulent, surface with intermittent whitewater with breaking waves) (Flosi and others, 2010; Peck and others, 2006; 

Moulton and others, 2002; Arend, 1999). Along with each 

velocity and depth measurement, a modified Wolman Pebble 

Count (Wolman, 1954) was conducted for substrate by measuring the b-axis of 15 randomly selected pebbles. Ripariancanopy cover percentages were measured using a concave 

spherical densiometer. The riparian cover was recorded 

facing upstream, downstream, at the left and right banks, and 

then averaged. The presence of woody debris, algae, aquatic 

vegetation, and undercut banks was recorded to indicate the 

availability of cover for fish.

To compare how native and non-native species were 

using aquatic microhabitat, randomized microhabitat measurements were collected as a way to represent the potential 

available microhabitat. Categories for velocity and depth 

were developed using quantile divisions in the random data 

distribution [for example, the 25th, 50th (or median), and 

75th percentile]. Substrate categories were established using 

published ranges for common substrate sizes (Peck and others, 

2006) (see table 9 for specific subcategory ranges, descriptors, 

and quantiles).

Pilot Microhabitat Study Sampling Locations

Similar to the microhabitat categories, subreaches were 

classified as geomorphic channel units (GCUs)—a quick 

visual identification of pool, glide, run, riffle, and rapid—to 

ensure that multiple microhabitat types are represented in a 

chosen stream reach (fig. 43). Sampling reaches were chosen 

to have between 5 and 9 alternating GCUs. This was generally 

achieved using 20 times the stream-bank full width or 40 times 

the average wetted width at base flow, but not less than 492 ft 

(150 m) (Moulton and others, 2002; Peck and others, 2006). 

Total reach length ranged from a minimum of 656 ft (200 m) 

to a maximum of 1,312 ft (400 m; table 10). However, total 

reach length did not necessarily correlate with total number 

of GCUs. For example, in West Clear Creek, there were eight 

alternating GCUs—run, riffle, glide, riffle, run, riffle, glide, 

pool. Each GCU was relatively short and the entire sample 

reach was about 820 ft (250 m). In the Oak Creek reach there 

were just five alternating GCUs—glide, run, riffle, glide, 

pool—but the GCUs were considerably longer in length, and 

the entire sample reach was about 1,148 ft (350 m).

Total Fish Assemblages in Pilot Study

A total of 15 fish species were identified during the 2012 

collection period across all sites (table 11; fig. 44A). Five were 

native and 10 were non-native species. The five native species 

were desert sucker, Sonora sucker, speckled dace, longfin 

dace, and roundtail chub. The 10 non-native species collected 

were western mosquito fish, black bullhead, red shiner, rainbow trout, largemouth bass, smallmouth bass, green sunfish, 

rock bass, common carp, and yellow bullhead. Certain species 

were only found at specific locations. For example, longfin 

and speckled dace were only collected at the Perkinsville site, 

whereas rock bass, black bullhead, and common carp were 

only collected at Oak Creek. The percentage of non-native 

species was greater at the Paulden location and at the tributaries, Oak Creek and West Clear Creek (fig. 44B). The Verde 

River below Granite Creek and the Perkinsville sites were 

most similar relative to percent native fish, but the Verde River 

below Granite Creek and the Paulden sites were most similar 

relative to fish assemblage (fig. 44C, left to right along NMDS 

axis 1). The assemblage change from the Verde River below 

Granite Creek to Perkinsville is related to a reduction in red 

shiners and an increase in the two dace species.

Microhabitat Characteristics by Pilot Study 

Sampling Site

The depth, velocity, substrate, and riparian-cover microhabitat characteristics of the fish-microhabitat study sites 

varied somewhat (figs. 45A, B, C, D; table 9), although there 

was no significant difference in median depth among the five 

locations. The Verde River below Granite Creek location had 

the slowest moving water of the five sites and was shallow 

with the finest substrates (silt and sand) and nearly 40 percent riparian cover. There was little difference overall in the 

microhabitat characteristics at the Paulden, Perkinsville, and 

Oak Creek sites, where stream-flow velocity is generally slow 

to moderate and depth is shallow to very shallow with gravel 

substrates. However, the waters are faster at Paulden and the 

riparian cover greater at Oak Creek. The waters at West Clear 

Creek were of moderate velocity and shallow with gravel and 

cobble substrates and significant riparian cover.

Median velocities at the Verde River below Granite Creek 

site (about 0.13 foot per second, ft/s) were significantly slower 

than all other sites, and at Paulden (1.39 ft/s) they were significantly faster than all other sites except West Clear Creek (fig. 

45A). There was no statistically significant difference among 

the median velocities at Perkinsville, Oak Creek, and West
Fish 63

Table 9. Fish microhabitat data-category quantiles and ranges for five middle Verde River, Arizona, study reaches.

[Categories include velocity, depth, median substrate, and percent riparian cover.]

Quantile, 

in percent All Stations

Verde River 

below Granite 

Creek

Verde River 

near Paulden 

(09503700)

Verde River at 

Perkinsville

Oak Creek 

near Cornville 

(09504500)

West Clear Creek 

near Camp Verde 

(09505800)

Velocity, in feet per second

Minimum 0.00 0.00 0.00 0.00 0.00 0.00

10 0.03 0.01 0.20 0.04 0.07 0.07

25 0.10 0.03 0.68 0.09 0.10 0.15

50 (median) 0.52 0.13 1.39 0.38 0.48 0.49

75 1.20 0.59 1.85 0.93 1.09 1.38

90 2.23 0.88 2.30 2.02 1.77 2.78

Maximum 4.13 2.81 4.13 3.73 3.08 3.61

Depth, in feet

Minimum 0.20 0.20 0.32 0.30 0.20 0.30

10 0.50 0.50 0.65 0.52 0.56 0.45

25 0.75 0.70 0.89 0.75 0.90 0.68

50 (median) 1.10 1.03 1.10 1.00 1.30 0.98

75 1.50 1.99 1.40 1.30 1.70 1.53

90 2.32 2.98 1.79 1.74 2.34 2.64

Maximum 5.00 3.25 3.12 3.00 5.00 3.20

Median substrate, in millimeters

Minimum 0.00 0.00 0.00 0.00 0.00 0.00

10 0.00 0.00 2.00 0.00 0.00 9.10

25 2.00 0.00 5.00 0.00 2.00 41.25

50 (median) 16.00 2.00 16.00 29.00 20.00 76.00

75 66.00 2.00 43.75 100.00 61.00 114.75

90 104.40 2.00 69.80 118.80 79.00 139.60

Maximum 294.00 40.00 90.00 150.00 90.00 294.00

Riparian cover, in percent

Minimum 0.0 0.0 0.0 0.0 0.0 0.0

10 0.0 0.0 0.0 0.0 0.0 31.3

25 1.5 11.1 1.5 0.0 0.0 58.8

50 (median) 32.4 41.2 6.7 8.8 55.9 74.3

75 72.1 72.5 17.3 32.4 79.0 96.0

90 96.2 97.0 40.8 53.2 99.9 100.0

Maximum 100.0 100.0 76.5 100.0 100.0 100.0
64 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

 0

 25

 50

 75

100

Pool

Glide

Run

Riffle

Rapid

EXPLANATION

Geomorphic channel units, in percent

Verde River below 

Granite Creek

Verde River 

near Paulden

Verde River 

near Perkinsville

Study reach

Oak Creek West Clear Creek

Figure 43. Graph showing percent of 

geomorphic channel units (pool, glide, 

run, riffle, rapid) identified at the five fish 

microhabitat study reaches in the middle 

Verde watershed, Arizona.

Table 10. Fish-microhabitat study-reach length and geomorphic channel unit 

sequence for the middle Verde watershed, Arizona.

Study reach

Reach 

length, in 

feet

Geomorphic channel unit 

type present

Verde river below Granite Creek 985 pool, glide, run

Verde River near Paulden (09503700) 1,148 pool, glide, rapid, riffle, run

Verde River at Perkinsville 985 pool, glide, riffle, run

Oak Creek near Cornville (09504500) 985 pool, glide, riffle, run

West Clear Creek near Camp Verde 

(09505800)

820 pool, glide, rapid, riffle, run
Fish 65

Clear Creek. The single highest instantaneous value (4.13 ft/s) 

was recorded at Paulden. Oak Creek was the deepest site overall due to deeper pools (median depth 1.3 ft), and West Clear 

Creek was the shallowest (median depth 0.98 ft) (fig. 45B). 

Minimum depths ranged from 0.20 to 0.32 ft and maximum 

depths from 3 to 5 ft.

Substrate median size increased from upstream to downstream on the upper-middle Verde River (fig. 45C). The Verde 

River below Granite Creek sample reach was comprised of 

substrate significantly smaller in size (mainly sand and silt, ≤2 

millimeter, mm) than at the other four sites, and at West Clear 

Creek the substrate was significantly larger than the other sites 

(76 mm), and included the greatest number of cobbles and 

boulders. Paulden, Perkinsville, and Oak Creek all had gravel 

substrates (16 mm, 29 mm, and 22 mm, respectively) and were 

statistically similar. Median percent riparian cover was significantly greater (p<0.0001–0.0203, Wilcoxon pairwise comparisons) at the Verde River below Granite Creek, Oak Creek, and 

Verde River near Paulden

Verde River near Perkinsville

Oak Creek

West Clear Creek

EXPLANATION

Verde river below Granite 

Creek

0

25

50

75

100

 Desert sucker

 Sonora sucker

 Roundtail chub

 Longfin dace

 Speckled dace

 Black bullhead

 Yellow bullhead

 Common carp

 Green sunfish

 Largemouth bass

 Smallmouth bass

 Rock bass

 Mosquito fish

 Rainbow trout

 Red shiner

A

Individual species, in percent

Native fish Non-native fish

0

10

20

30

40

50

60

70

80

90

100

Verde River Oak Creek

 near Paulden

Verde River

near Perkinsville

West Clear

Creek

Total fish collected

 at all locations

Native and non-native fish, in percent

Study reach

Native

Non-native

EXPLANATION

B

Verde river below 

Granite Creek

Figure 44. Graphs showing native and 

non-native fish distribution in the middle 

Verde River watershed, Arizona. A, Percent 

of individual species by location; B, percent 

of native and non-native fish by location; 

and C, assemblage by location shown as a 

nonmetric multidimensional scaling (NMDS) 

ordination plot and bubble overlay with total 

abundance of native and non-native fish. 

See figure 32 for scientific fish names.
66 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

C

2 dimensional Stress= 0

Oak Creek

Verde River at Paulden

Verde River at Perkinsville

Verde River below Granite Creek

West Clear Creek

NMDS axis 1

NMDS axis 2

Fourth root transformation

Bray Curtis similarity resemblance matrix

Abundance of non-native fish

EXPLANATION

120

20

65

135

59

53

44

Abundance of native fish

3

53

87

69

31

Table 11. Number and percent of native and non-native fish species at each sample reach in the middle Verde River watershed, 

Arizona.

[See figure 32 for scientific fish names. %, percent]

Figure 44.—Continued

Species

Verde River 

below Granite 

Creek

Verde River 

near Paulden 

(09503700)

Verde River at 

Perkinsville

Oak Creek 

near Cornville 

(09504500)

West Clear Creek 

near Camp Verde 

(09505800)

Total Abundance

Native

Desert sucker 9 39 10 1 14 73

Sonora sucker 58 13 26 2 16 115

Roundtail chub 2 1 4 0 1 8

Longfin dace 0 0 27 0 0 27

Speckled dace 0 0 20 0 0 20

Non-native

Black bullhead 0 0 0 2 0 2

Yellow bullhead 0 1 5 0 0 6

Common carp 0 0 0 8 0 8

Green sunfish 10 10 6 7 0 33

Largemouth bass 13 0 0 15 0 28

Smallmouth bass 6 2 8 12 41 69

Rock bass 0 0 0 2 0 2

Mosquito fish 24 6 0 18 0 48

Rainbow trout 0 0 0 0 3 3

Red shiner 0 116 40 1 0 157

 Total 122 188 146 68 75 599

Native versus non-native

Native 69 53 87 3 31 243

Non-native 53 135 59 65 44 356

Percent native 57% 28% 60% 4% 41% 41%

Percent non-native 43% 72% 40% 96% 59% 59%
Fish 67

West Clear Creek sites than at Paulden and Perkinsville due 

to the narrower stream channels (fig. 45D). West Clear Creek 

had significantly more cover—74 percent—than all of the 

other sites, whereas Paulden and Perkinsville had just 7 and 9 

percent, respectively.

Pilot-Study Fish Characteristics

The pilot-study analysis focused on similarities and differences in habit use by native and non-native fish species. 

Fish observations were plotted in relation to depth and velocity measurements collected at the respective observation location and visualized using a nonparametric density plot to show 

a smooth, nonparametric bivariate surface that describes the 

density of all observations. Velocities measured at the same 

depths where fish were observed showed the highest density 

of total fish presence in waters flowing less than 1 ft/s and at 

depths between 0.5 and 2.0 ft (fig. 46A). Native fish presence was most often found in slow, deep waters (1–3 feet and 

less than 1 ft/s; fig. 46B), and non-native fish were found in 

slow, shallow waters (0.5–2.0 ft and less than 1 ft/s; fig. 46C). 

Several native fish were also found in waters with velocities 

of about 2 ft/s in very shallow to moderate depths (0.5–1.5 

ft). Fewer non-native fish were also collected in this velocity 

range, but native fish appeared to be found more often and in a 

wider range of depths.

Median water velocities ranged from about 0.01 ft/s for 

mosquito fish to 2.3 ft/s for speckled dace (fig. 47A). Many of 

the small fish species (longfin dace, red shiner, and speckled 

dace) were found in a wider range of velocities. Of the more 

common fish observed in the pilot study, smallmouth bass, 

Sonora suckers, and green sunfish were more often found in 

areas of slower velocities related to deeper waters, and desert 

suckers and red shiners were found in faster waters (fig. 47B). 

Longfin dace occurred in the shallowest waters (0.2 ft), and 

common carp occurred in the deepest waters (5 ft). Although 

their sample size was small, roundtail chub occurred across a 

wide range of depths. Desert suckers used the largest substrate (median 51 mm) and occurred over the widest range of 

substrate diameters (2 to 210 mm; fig. 47C). Sonora suckers 

and green sunfish were observed near the smallest median 

substrates (6 mm). Roundtail chub and red shiners were 

located near coarse gravel substrates; roundtail chub also used 

cobbles.

Although some fish, such as smallmouth bass, green 

sunfish, desert sucker, Sonora sucker, roundtail chub, and 

longfin dace were observed in a range of velocities and depths, 

it should be noted that age class was not taken into account 

in the microhabitat-use analysis for the study. The lengths of 

the individual fish were measured and used as a coarse proxy 

to determine the distribution of age class and occurrence in 

different microhabitat types. Figure 48 shows the significant 

relations for species where depth or velocity explained a part 

of the variability between fish length and presence in microhabitat at the location of collection. For the species shown in 

the linear regression plots, the length and potentially the age of 

a fish appears to affect the its distribution in relation to depth 

and velocity. There was general pattern of larger fish (>150 

mm), both native and non-native, found in deeper waters (1–3 

ft). Velocity relations were less clear. In future studies, the 

variation attributable to age class should be taken into account.

Native and Non-native Fish Use of Available 

Microhabitat in Pilot Study

Under the null hypothesis, the preferential use of microhabitat type by fish would be distributed across all depths, 

velocities, and substrates consistent with microhabitat availability. Although at least some native and non-native fish were 

found in each velocity, depth, and substrate category, preferential microhabitat use was common (figs. 49, 50, 51; table 

12). On a percentage basis (figs. 49A, 50A, 51A), non-native 

species had a strong preference for slow-moving and deeper 

water with silt and sand substrate, with a secondary preference 

for faster moving and very shallow water and a coarse gravel 

substrate. Native species showed a general preference for 

moderately fast, moderately deep water over coarse gravel and 

had no clear secondary preference. The density curves (fig. 

49B, 50B, 51B) are a function of the number of items in each 

of the bins in the figures 49A, 50A, and 51A. This results in a 

somewhat different shape to the density curve when compared 

to the quantile histogram, especially for figure 51B versus 

figure 51A.

Native fish disproportionately used slow velocity microhabitat (>0.10–0.52 ft/s) compared to the availability of this 

microhabitat type in the field (fig 49A). Moderate velocities 

(>0.52–1.12 ft/s) accounted for 24 percent of the available 

microhabitat and 23 percent of the native species, but only 7 

percent of the nonnative species were found there. Another 27 

percent of the available velocity microhabitat was in standing 

water (0.10 ft/s or slower), and native fish used that velocity 

less than 10 percent of the time, whereas non-native fish were 

found there 43 percent of the time. Standing water therefore 

accounted for the greatest contrast between microhabitat availability and its use by non-native fish (fig. 49A). The median 

stream velocity associated with the native fish species was 

significantly faster than the median velocity associated with 

the non-native fish species and likewise faster than the median 

velocity found in the available microhabitat. The median 

stream velocity associated with the non-native fish was significantly slower than that of the available microhabitat (fig. 

49C). Although non-native species showed strong affinity for 

standing water and native species showed more of an affinity 

for slow to moderate velocities, use was different for different 

native species. For example, Sonora suckers consistently used 

slower velocities (mainly <1.0 ft/s), whereas speckled dace 

were more common in faster velocity microhabitat (>2.0 ft/s; 

fig. 47A). Non-native red shiners were found in greater velocities (median=1.75 ft/s) than most other non-native species.

Native species were significantly more likely to be found 

in deeper water than non-native species (median difference=0.2 ft). Thirty-one percent of non-native and 19 percent 
68 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

Figure 45. Graphs showing boxplots of 

the distribution of (A) water velocity, (B) 

water depth, (C) median substrate size, 

and (D) riparian cover for each fishmicrohabitat sample reach in the middle 

Verde River watershed, Arizona. 

36 Number of samples

EXPLANATION

Largest value within 1.5 times 

interquartile range above 75th 

percentile

Outside value—Value is >1.5 and 

<3 times the interquartile range 

beyond either end of the box

Smallest value within 1.5 times 

interquartile range below 25th 

percentile

Interquartile 

range

A

B

C

Wilcoxon pairwise tests-significant difference ( p≤0.05) a, b, c.

Velocity, in feet per second

c

b

a

c

b, c

Depth, in feet

50 50 45 50 50

Verde River Oak Creek

 near Paulden

Verde River

near Perkinsville

West Clear

Creek

Median particle size, in millimeters

Study reach

c

b

a

c

c

Verde River 

below Granite 

Creek

0

1

2

3

4

5

0

1

2

3

4

5

6

0

50

100

150

A bar labeled "a" is significantly different from bars that include 

labels without the letter "a" (b; c; b,c) but is not significantly 

different from any labeled with an "a" (a; a,b; a,c); likewise for 

b and c.

75th percentile

25th percentile

50th percentile (median)

a

a

a

a a
Fish 69

Figure 45.—Continued

Velocity, in feet per second

Velocity, in feet per second

B. Native fish presence C. Non-native fish presence

A. Total fish presence

Depth, in feet

Velocity, in feet per second

.1 .2 .3 .4 .5 .6 .7 .8 .9 Quantile density contours

Fish observation

Depth, in feet

0

1

2

3

4

1 2 3 4 5

0

1

2

3

4

1 2 3 4 5

EXPLANATION

0

1

2

3

4

1 2 3 4 5

Depth, in feet

Figure 46. Graphs showing nonparametric density 

estimates of fish observations for sample reaches in 

the middle Verde River watershed, Arizona, plotted as a 

smooth, nonparametric bivariate surface representing the 

density of observations for a given velocity and depth. A, 

Total fish presence; B, native fish presence; C, non-native 

fish presence. The contour lines are quantile contours in 

5-percent intervals and colors correspond to the labeled 

quantile.

Riparian cover, in percent

50 50 50 50

D

Verde River Oak Creek

near Paulden

Verde River

near Perkinsville

West Clear

Creek

a

b

b

c

0

25

50

75

100

Verde River 

below Granite 

Creek

45

a

Study reach
70 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

Water depth, in feet

Water velocity, in feet per second

3

8

48

157

6

2

69

2

28

33

8

115

73

20

27

A

B

Non-native fish

Native fish

 Desert sucker

 Sonora sucker

 Roundtail chub

 Longfin dace

 Speckled dace

 Black bullhead

 Yellow bullhead

 Common carp

 Green sunfish

 Largemouth bass

 Smallmouth bass

 Rock bass

 Mosquito fish

 Rainbow trout

 Red shiner

0 1 2 3 4 5

0 1 2 3 4 5 6

 Desert sucker

 Sonora sucker

 Roundtail chub

 Longfin dace

 Speckled dace

 Black bullhead

 Yellow bullhead

 Common carp

 Green sunfish

 Largemouth bass

 Smallmouth bass

 Rock bass

 Mosquito fish

 Rainbow trout

 Red shiner

3

8

48

157

6

2

69

2

28

33

8

115

73

20

27

Non-native fish

Native fish

Median

Median

Median

Median

Median

Median

36 Number of samples

EXPLANATION

Largest value within 1.5 times 

interquartile range above 75th 

percentile

Outside value—Value is >1.5 and 

<3 times the interquartile range 

beyond either end of the box

Smallest value within 1.5 times 

interquartile range below 25th 

percentile

Interquartile 

range

75th percentile

25th percentile

50th percentile (median)

Figure 47. Graphs showing 

boxplots of the distribution 

of native and non-native fish 

species relative to where 

observed in each microhabitat 

in sample reaches in the middle 

Verde River watershed, Arizona. 

A, Water velocity; B, water 

depth; C, substrate median 

particle size; D, percent cover. 

See figure 32 for scientific fish 

names.
Fish 71

Figure 47.—Continued

3

8

48

157

6

69

2

28

33

115

73

20

27

Non-native fish

Native fish

 Desert sucker

 Sonora sucker

 Roundtail chub

 Longfin dace

 Speckled dace

 Black bullhead

 Yellow bullhead

 Common carp

 Green sunfish

 Largemouth bass

 Smallmouth bass

 Rock bass

 Mosquito fish

 Rainbow trout

 Red shiner

Median substrate particle size, in millimeters

C

D

0 50 100 150 200 250

2

8

3

8

48

157

6

2

69

2

28

33

8

115

73

20

27

Non-native fish

Native fish

 Desert sucker

 Sonora sucker

 Roundtail chub

 Longfin dace

 Speckled dace

 Black bullhead

 Yellow bullhead

 Common carp

 Green sunfish

 Largemouth bass

 Smallmouth bass

 Rock bass

 Mosquito fish

 Rainbow trout

 Red shiner

Cover, in percent

0 25 50 75 100

Median

Median

Median

Median

Median
72 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

Figure 48. Graphs showing fish length, water depth, and water velocity relations among select fish species from sample reaches in the middle Verde River, Arizona—

A, red shiner; 

B, Sonora sucker; 

C, speckled dace; 

D, desert sucker; 

E, smallmouth bass. See figure 32 for scientific fish names.

otal length, in millimeters T otal length, in millimeters T

0

50

400

350300250200150100

0 0.5 1 1.5 2

0

50

400350300250200150100

0.5 1 1.5 2 2.5 3

Velocity, in feet per second

Depth, in feet

B. Sonora sucker

otal length, in millimeters T

908070605040302010

100

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5

Velocity, in feet per second

C. Speckled dace

otal length, in millimeters T

50

300250200150100

0.5 1 1.5 2 2.5 3

Depth, in feet

D. Desert sucker

otal length, in millimeters T

0

50

450400350300250200150100

0.5 1 1.5 2 2.5 3

Depth, in feet

E. Smallmouth bass

90807060504030

-0.5 0 0.5 1 1.5 2 2.5 3 3.5 4

Velocity, in feet per second

otal length, in millimeters T otal length, in millimeters T 908070605040

30

0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2

Depth, in feet

All regression fits p 

≤ 0.05

EXPLAN

ATON

Regression fitLOWESS line

A. Red shiner
Fish 73

of native fish used water less than 0.75 ft deep. On the other 

hand, 6 percent of non-native and 16 percent of native fish 

were found in water deeper than 2.3 ft (fig. 50A). It was significantly more likely for the median depth where native species 

were found to be deeper than the median depth of available 

microhabitat, whereas for non-native species it was not (fig. 

50C). Nonetheless, there was much overlap in use between 

native and non-native fish. For example, both native dace species were observed using shallow depths (less than 1.0 ft) and 

the two sucker species and roundtail chub were found using 

depths of about 1.0 to 2.0 ft. This depth use was also common 

for green sunfish, largemouth bass, and smallmouth bass.

The density curves show that non-native fish used the 

lowest velocity microhabitat (0 to about 0.3 ft/s), water from 

0.5 to 1.5 ft deep, and the smallest diameter substrate (0 to 

about 25 mm) and the substrate from about 40 to 70 mm diameter. Native fish were found more commonly than non-native 

fish in about 0.3 to 1.5 ft/s and 2 to 3.1 ft/s velocity microhabitat, water from about 2.3 to 3.6 ft deep, and using substrate of 

25 to 40 mm and 100 to 160 mm diameter.

Both native and non-native species used all size substrate 

(fig. 51C). Non-native fish used silt and sand substrates more 

commonly than native fish and at a rate higher than its availability, whereas native fish were found over gravels at a rate 

higher than its availability (fig. 51A). Both native and nonnative fish were less commonly found over cobbles. In general, native fish were significantly more likely to use coarser 

substrates (in particular, gravels and cobbles) than non-native 

fish (figs. 51 A, C). The substrate used by non-native fish was 

of significantly smaller diameter than that of the available 

substrate, whereas the substrate used by native fish was not 

significantly different in diameter from that of the available 

substrate.

Fish Abundance by Available Microhabitat at 

Each Pilot-Study Sampling Site

The five sample reaches varied in the relative availability of microhabitat types and in whether the sample reach 

was dominated by native or non-native species (fig. 44; 

figs. 52–56). The Verde River below Granite Creek site was 

characterized by mostly slower moving water (fig. 52A). Fifty 

percent of the microhabitat sampled had water velocities of 

0.10 ft/s or less (standing water), and 98 percent of the water 

velocities sampled were slower than about 1.12 ft/s (standing, 

slowly, or moderately moving water). More than 80 percent 

of non-native fish at the Verde River below Granite Creek site 

were found in standing water, whereas native fish were found 

in all velocity categories except for very fast. Fifty percent 

of native species were collected in water faster than 0.52 

ft/s. More than 50 percent of available depth at this location 

consisted of water 1.1 ft deep or less (shallow to very shallow) 

(fig. 52B). Seventy-one percent of non-native species but only 

10 percent of native species used these shallow depths. Fiftytwo percent of native fish used moderate depth microhabitat 

(>1.1–1.5 ft).

The Verde below Granite Creek sample reach differed 

from other reaches by having 96 percent sandy and silty 

substrate (≤2 mm), and the remaining substrate sampled was 

coarse gravel (>16–64 mm) (fig. 52C). Ninety-four percent of 

native and 98 percent of non-native fish were found on sand 

and silt. Overall, native species were more common than nonnative species here (fig. 44). Sonora suckers were the predominant native species at this site; desert sucker and roundtail chub were also present (table 11). Non-native fish were 

dominated by western mosquito fish. The larger predators and 

competitors—largemouth bass, smallmouth bass, and green 

sunfish—were also found there but in lower numbers (table 

11). Overall, non-native species at the Verde below Granite 

Creek site preferred very shallow, standing water, but otherwise tended to use microhabitat as it was available. Native fish 

species tended to use somewhat more specific microhabitats 

(fig. 52).

The Verde River at Paulden sampling reach was predominantly middle-range in all microhabitat categories—66 

percent of microhabitat had moderate or fast water, more than 

65 percent had shallow or moderate depths, and 70 percent 

had fine or coarse gravel. Both native and non-native species 

used some microhabitat types preferentially. For example, 

only 4 percent of non-native fish were found in moderatevelocity water, whereas 39 percent were found in standing 

water, although standing water made up just 8 percent of the 

available microhabitat. Sixty percent of native fish were found 

in the fastest-moving waters (>1.12 ft/s), which made up 58 

percent of the available microhabitat (fig. 53A). Twenty-three 

percent of the native fish species were found in very deep 

water, and 2 percent of the non-native fish were found in very 

deep water. Six percent of the available microhabitat was very 

deep. On the other hand, 74 percent of non-native fish were 

found in shallow or moderate depths, and 58 percent of native 

fish were found in this same middle range (fig. 53B). Silt and 

sand accounted for 18 percent of the available microhabitat. 

More than 52 percent of the non-native species were found 

over silt or sand, and 6 percent of native fish were found over 

silt or sand. Only 1 percent of non-native fish used fine gravel 

microhabitat at Paulden, even though it accounted for 32 

percent of the available microhabitat (fig. 53C). Five species 

of non-native fish were collected in Paulden, constituting 72 

percent of the fish collected at that site. Red shiner was the 

dominant species. Green sunfish, western mosquito fish, smallmouth bass, and yellow bullhead were also collected there. 

Thirty-nine desert sucker, 13 Sonora sucker, and 1 roundtail 

chub were the native species observed at Paulden (table 11).

The Verde River at Perkinsville sample reach had 

predominantly lower water velocities (60 percent slow or 

standing), shallower depths (82 percent moderate, shallow, 

and very shallow), and a mix of primarily silt (33 percent) and 

cobbles (40 percent), plus 16 percent coarse gravel. Nonnative species preferred faster water at this site. Fifty-four 

percent of the non-native fish were found in very fast water 

(>2.23 ft/s), although the very fast velocity areas made up only 

9 percent of the available microhabitat at Perkinsville. Native
74 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

0

10

20

30

40

50

Velocity quantiles, in feet per second

Availability or use, in percent

Standing Slow Moderate Fast Very fast

0.00–0.10 >0.10–0.52 >0.52–1.12 >1.12–2.23 >2.23

EXPLANATION

Habitat available

Native fish use

Non-native use

A

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

0.5 1 1.5 2 2.5 3 3.5 4

EXPLANATION

Native fish use density

Non-native fish use density

Available habitat density

B

Velocity, in feet per second

Standardized proportion, unitless

More non-native use

More native use

Use is similar
Fish 75

Figure 49. Graphs of available velocity and velocity use by native and non-native fish in sample reaches in the middle Verde River and 

two tributary streams, Arizona. A, Velocity microhabitat quantiles by percent availability or use; B, velocity microhabitat availability and 

native and non-native fish use as a continuous standardized proportion; and C, boxplots of velocity microhabitat availability and native 

and non-native fish median use.

EXPLANATION

Largest value within 1.5 times 

interquartile range above 75th 

percentile

Outside value—Value is >1.5 and 

<3 times the interquartile range 

beyond either end of the box

Smallest value within 1.5 times 

interquartile range below 25th 

percentile

Pairwise tests significant difference ( p≤0.05) a, b, c.

C

Velocity, in feet per second

Available Non-native

b

c

a

0

1

2

3

4

5

Native

Habitat type

A bar labeled "a" is significantly different from bars that 

include labels without the letter "a" (b; c; b,c) but is not 

significantly different from any labeled with an "a" 

(a; a,b; a,c); likewise for b and c.

75th percentile

25th percentile

50th percentile (median)
76 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

0.0–0.75 >0.75–1.1 >1.1–1.5 >1.5–2.3 >2.3

Depth quantiles, in feet 

EXPLANATION

Habitat available

Native fish use

Non-native use

A

0

5

10

15

20

25

30

35

Availability or use, in percent

Very shallow Shallow Moderate Deep Very deep

Depth, in feet 

EXPLANATION

Native fish use density

Non-native fish use density

Available habitat density More non-native use

More native use

Use is similar

B

Standardized proportion, unitless

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5
Fish 77

Figure 50. Graphs of available depth and depth use by native and non-native fish in sample reaches in the middle Verde River and two 

tributary streams, Arizona. A, Depth-habitat quantiles by percent availability or use; B, depth microhabitat availability and native and 

non-native fish use as a continuous standardized proportion; and C, boxplots of depth microhabitat availability and native and nonnative fish median use. 

C

Depth, in feet 

Available Native

Habitat type

Non-native

a

b

b

EXPLANATION

Largest value within 1.5 times 

interquartile range above 75th 

percentile

Outside value—Value is >1.5 and 

<3 times the interquartile range 

beyond either end of the box

Smallest value within 1.5 times 

interquartile range below 25th 

percentile

Pairwise tests significant difference ( p

0

≤0.05) a, b, c.

1

2

3

4

5

A bar labeled "a" is significantly different from bars 

that include labels without the letter "a" (b; c; b,c) 

but is not significantly different from any labeled 

with an "a" (a; a,b; a,c); likewise for b and c.

75th percentile

25th percentile

50th percentile (median)
78 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

0.00–0.06 >0.06–2 >64–250

Availability or use, in percent

EXPLANATION

Habitat available

Native fish use

Non-native use

Median substrate groups, in millimeters

A

0

5

10

15

20

25

30

35

Silt Sand Fine gravel Coarse gravel Cobble

>2–16 >16–64

Substrate, in millimeters

EXPLANATION

Native fish use density

Non-native fish use density

Available habitat density

B

0.000

0.005

0.010

0.015

0.020

0.025

50 100 150 200 250 300

Standardized proportion, unitless

More non-native use

More native use

Use is similar
Fish 79

Figure 51. Graphs of available substrate and substrate use by native and non-native fish in sample reaches in the middle Verde River 

and two tributary streams, Arizona. A, Substrate-habitat groups by percent availability or use; B, substrate microhabitat availability and 

native and non-native fish use as a continuous standardized proportion; and C, boxplots of substrate microhabitat availability and native 

and non-native fish median use. 

a

a

b

EXPLANATION

Largest value within 1.5 times 

interquartile range above 75th 

percentile

Outside value—Value is >1.5 and 

<3 times the interquartile range 

beyond either end of the box

Smallest value within 1.5 times 

interquartile range below 25th 

percentile

Pairwise tests significant difference ( p≤0.05) a, b, c. Median substrate, in millimeters

C

0

50

100

150

200

250

300

Available Native

Habitat type

Non-native

A bar labeled "a" is significantly different from bars that 

include labels without the letter "a" (b; c; b,c) but is not 

significantly different from any labeled with an "a" 

(a; a,b; a,c); likewise for b and c.

75th percentile

25th percentile

50th percentile (median)
80 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona Depth quantiles, in feet 

Availability or use, in percent

Availability or use, in percent

70%60%50%

Median substrate groups, in millimeters

A

B

C

EXPLAN

ATION

Habitat available

Native fish use

Non-native use

0

70

605040302010

0

70

60504030

2010

Silt

Sand

Fine gravel Coarse

gravel

Cobble

Very shallow Shallow Moderate Deep Very deep

0.0–0.75 >0.75–1.1 >1.1–1.5 >1.5–2.3 >2.3

0.00–0.06 >0.06–2 >2–16 >16–64 >64–250

0

80604020

100

Velocity quantiles, in feet per second

Availability or use, in percent

>2.23 0.00–0.10 >0.10–0.52 >0.52–1.12 >1.12–2.23

Standing Slow Moderate Fast Very fast

Figure 52. Graphs showing both available microhabitat types and microhabitat types used by native and non-native fish at Verde River below Granite Creek in the middle Verde River watershed, Arizona—

A, water-velocity 

quantiles; 

B, water-depth quantiles; and 

C, 

substrate groups.
Macroinvertebrates 81

fish species were relatively evenly distributed from slow to 

very fast microhabitats (>0.10 ft/s). Standing water made up 

31 percent of the microhabitat but was used by 2 percent of 

non-native and 6 percent of native fish (fig. 54A). Both nonnative and native fish preferred both the very shallowest and 

the deep water at Perkinsville, whereas available microhabitat 

was predominantly very shallow. In particular, deep and very 

deep water (>1.5 ft) accounted for 17 percent of the available 

microhabitat; 25 percent of native fish species and 39 percent 

of non-native fish species were found in deep water (>1.5–2.3 

ft). However, no fish were observed in very deep water (fig. 

54B). Seventy-two percent of both native and non-native fish 

were collected over gravels, which accounted for 23 percent 

of the available microhabitat. Thirty-three percent of the 

available microhabitat was silt, and 11 percent of native fish 

species were found there. Less than 5 percent of the available microhabitat at Perkinsville was sand, and no native fish 

and just a few non-native fish were found there (fig. 54C). 

All five species of native fish observed during this study were 

found at the Perkinsville location; 60 percent of fish observed 

were native (fig. 44). This was the only site where speckled 

dace and longfin dace were found. Red shiners were the most 

abundant non-native fish species (40 individuals), followed by 

smallmouth bass, green sunfish, and yellow bullhead.

The fish assemblage, microhabitat type, and physical 

surroundings at Oak Creek were quite different from the other 

sample reaches. Oak Creek had the highest proportion of nonnative species (96 percent) of all sample reaches (fig. 44). The 

Oak Creek sample reach was comprised of only 3 individual 

native fish—one desert sucker and two Sonora suckers. Nonnative species collected here but not in any other stream reach 

included common carp, rock bass, and black bullhead. The 

only non-native species found elsewhere in this study but not 

at the Oak Creek site were rainbow trout and yellow bullhead 

(table 11). Oak Creek was characterized by a broad range of 

velocity microhabitats and variable depths and substrate. The 

native fish were collected in slowly flowing, moderately deep 

or very deep water over coarse gravel and cobble. Non-native 

fish preferred standing water (83 percent) and silt substrate (74 

percent) in Oak Creek, but used all depths as available (figs. 

55A–C).

Thirty-four percent of velocity microhabitat in West Clear 

Creek was slow-moving water (fig. 56A), and both native and 

non-native fish disproportionately preferred this slow-velocity 

flow (77 and 66 percent, respectively). The percent of available water depths declined steadily with increasing depth, 

from very shallow (36 percent) to very deep (8 percent). Nonnative fish preferred depths that were moderate to deep in West 

Clear Creek (82 percent), even though this represented only 

32 percent of the available microhabitat. Native fish preferred 

deep and very deep water (71 percent), which represented 

even less of the available microhabitat (22 percent). Thirty-six 

percent of the available microhabitat was very shallow, but 

non-native fish used this only 2 percent of the time, and native 

fish did not use it at all (fig. 56B).

West Clear Creek had the greatest median substrate size 

of all sample reaches (fig 45C), with 26 percent of the substrate coarse gravel and 60 percent cobble (fig. 56C). Nonetheless, non-native fish were most commonly found over finegravel (36 percent), and native fish coarse gravel (42 percent). 

Silt and sand were the least common microhabitat at 4 percent 

each. However, neither native nor non-native fish were found 

over silt. West Clear Creek had more non-native fish (59) than 

native fish (41) (fig. 44). The native-fish assemblage was comprised of the two sucker species and one individual roundtail 

chub; the non-native fish were dominated by smallmouth bass 

plus three rainbow trout.

Non-native fish were most abundant at the Verde River 

at Paulden study reach by number (135 individuals) and at 

Oak Creek by percent (96 percent). Oak Creek also had the 

greatest variety of non-native species (8 total). The study reach 

with the fewest non-native species by number was West Clear 

Creek (44 individuals). The greatest abundance of native fish 

was at Perkinsville by both number and percent (87 individuals, 60 percent of fish collected). Perkinsville also had the largest number of native species (5 species). The fewest individual 

native fish were collected at Oak Creek (3 suckers), and this 

was also the site with the fewest number of native species (2 

species).

Oak Creek is different from the other sites in that only 3 

individual native fish were present and 8 of the 10 non-native 

fish species collected during the study occurred there (table 

11, fig. 44). The only non-native fish species not collected 

there were yellow bullhead and rainbow trout. This site was 

also heavily impacted by human use. Part of the stream was 

diverted, situated near a hatchery, stocked with brown, brook, 

and rainbow trout (although none of these species were found 

while sampling Oak Creek), and located next to a recreational 

vehicle park and campgrounds. The stocking of non-native 

sport fish and the presence of predatory, competitive nonnative species not found in other sample reaches could be 

affecting native fish presence in Oak Creek (Minckley and 

Douglas, 1991; Rinne and Janisch, 1995).

Macroinvertebrates

Benthic macroinvertebrates live on streambed substrates, 

such as cobble, gravel, and sand. Macroinvertebrates play a 

crucial role in the food web of a stream ecosystem by acting 

as an intermediary between primary producers and vertebrates. 

Because macroinvertebrates are relatively sessile and live 

extended life cycles (a year or more), the macroinvertabrate 

assemblage is often a function of past stream conditions (Peck 

and others, 2006). As such, macroinvertebrate assemblages are 

useful in assessing the status or trend of the ecological condition of a stream. In addition, their function or role in the larger 

community can be used as a quantitative measure to assess 

ecological conditions and relate to other stream characteristics. 
82 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona Depth quantiles, in feet 

Availability or use, in percent

Availability or use, in percent

Median substrate groups, in millimeters

A

C

EXPLAN

ATION

Habitat available

Native fish use

Non-native use

B

0

60

5040302010

0

605040302010

Silt Sand Fine gravel Coarse

gravel

Cobble

Very shallow Shallow Moderate Deep Very deep

0.0–0.75 >0.75–1.1 >1.1–1.5 >1.5–2.3 >2.3

0.00–0.06 >0.06–2 >2–16 >16–64 >64–250

0

605040302010

Velocity quantiles, in feet per second

Availability or use, in percent

>2.23 0.00–0.10 >0.10–0.52 >0.52–1.12 >1.12–2.23

Standing Slow Moderate Fast Very fast

Figure 53. Graphs showing both available microhabitat types and microhabitat types used by native and non-native fish at Verde River at Paulden in the middle Verde River watershed, Arizona—

A, water-velocity quantiles; 

B, waterdepth quantiles; and 

C, substrate groups.
Fish 83

Depth quantiles, in feet 

Availability or use, in percent

Availability or use, in percent

Median substrate groups, in millimeters

A B

C

EXPLANATION

Habitat available

Native fish use

Non-native use

0

60

5040302010

0

60

5040302010

Silt Sand Fine gravel Coarse

gravel

Cobble

Very shallow Shallow Moderate Deep Very deep

0.0–0.75 >0.75–1.1 >1.1–1.5 >1.5–2.3 >2.3

0.00–0.06 >0.06–2 >2–16 >16–64 >64–250

0

60

5040302010

Velocity quantiles, in feet per second

Availability or use, in percent

>2.23 0.00–0.10 >0.10–0.52 >0.52–1.12 >1.12–2.23

Standing Slow Moderate Fast Very fast

Figure 54. Graphs showing both available microhabitat types and microhabitat types used by native and non-native fish at Verde River at Perkinsville in the middle Verde River watershed, Arizona—A, water-velocity quantiles; B, water-depth quantiles; and C, substrate groups.
84 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona Depth quantiles, in feet 

Availability or use, in percent

Availability or use, in percent

Median substrate groups, in millimeters

A

B

C

EXPLAN

ATION

Habitat available

Native fish use

Non-native use

0

80

70605040302010

0

70

605040302010

Silt Sand Fine gravel Coarse

gravel

Cobble

Very shallow Shallow Moderate Deep

Very deep

0.0–0.75 >0.75–1.1 >1.1–1.5 >1.5–2.3 >2.3

0.00–0.06 >0.06–2 >2–16 >16–64 >64–250

0

80604020

100

Velocity quantiles, in feet per second

Availability or use, in percent

>2.23 0.00–0.10 >0.10–0.52 >0.52–1.12 >1.12–2.23

Standing

Slow

Moderate Fast Very fast

Figure 55. Graphs showing both available microhabitat types found and microhabitat types used by native and non-native fish at Oak Creek in the middle Verde River watershed, Arizona—

A, 

water-velocity quantiles; 

B, water-depth quantiles; 

and 

C, substrate groups.
Fish 85

Depth quantiles, in feet 

Availability or use, in percent Availability or use, in percent

Median substrate groups, in millimeters

A B

C

EXPLANATION

Habitat available

Native fish use

Non-native use

0

60

5040302010

0

70

605040302010

Silt Sand Fine gravel Coarse

gravel

Cobble

Very shallow Shallow Moderate Deep Very deep

0.0–0.75 >0.75–1.1 >1.1–1.5 >1.5–2.3 >2.3

0.00–0.06 >0.06–2 >2–16 >16–64 >64–250

0

8070605040302010

Velocity quantiles, in feet per second

Availability or use, in percent

>2.23 0.00–0.10 >0.10–0.52 >0.52–1.12 >1.12–2.23

Standing

Slow

Moderate Fast Very fast

Figure 56. Graphs showing both available microhabitat types and microhabitat types used by native and non-native fish at West Clear Creek in the middle Verde River watershed, Arizona—A, water-velocity quantiles; B, water-depth quantiles; and C, substrate groups.
86 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

Macroinvertebrate Metrics

Macroinvertebrate communities are useful indicators of 

water quality because of their rapid and consistent response 

to changes in physical and chemical characteristics of 

streamflow. However, detecting a population response to any 

one variable can be difficult because many environmental 

factors can limit population size. Several environmental factors acting in concert can elicit a unique response making the 

task of identifying a single responsible factor very difficult. 

Thus, variables in addition to streamflow should be considered when trying to understand macroinvertebrate relations.

Macroinvertebrate communities have been shown to 

be different depending on the time of year they are sampled 

(Spindler, 2001). A given sampling time is referred to as 

an index period and typically spans a season, such as fall 

or spring (fig. 57). Samples collected following high flow 

events may be nonrepresentative of stable macroinvertebrate 

populations because of the slow recovery of some species 

and (or) the rapid recovery of more opportunistic species. 

Community differences can also be attributed to low-flow 

years where species may be highly competitive (fig. 57). 

Community metrics were compared temporally and spatially—(1) between spring and fall index periods, (2) among 

years of significant flow, (3) among the Verde River and its 

tributaries, and (4) among areas with and without significant 

diversions (table 12). Richness and diversity measures are 

significantly different between spring and fall index periods, 

especially in years where high flows have occurred (fig. 57). 

The purpose of such analyses is to better understand major 

hydrologic differences before relating community metrics 

to flow metrics. About 12 macroinvertebrate metrics were 

found to be significantly different between one or more of 

the variables tested (index period, high-flow or low-flow 

sample, diversions present, or if the sample is from the Verde 

River or a tributary; table 12).

The variables providing the greatest differentiation 

among community metrics were index period, high-flow 

year, and collection location (Verde River or tributary). Most 

of the effects observed were with richness (total number of 

taxa) and diversity measures (for example, Shannon’s diversity index or percentage of abundance comprised of the most 

dominant taxa). Although richness, caddisfly (order Trichoptera) richness, Shannon’s diversity index, and the percent 

of the most dominant taxa are all highly correlated, their 

response to each variable was different. The percentage of 

mayfly abundance (order Ephemeroptera) was significantly 

higher in the upper-middle and lower-middle reaches of the 

Table 12. Fish microhabitat categories for water velocity, water 

depth, and substrate, as well as subcategory ranges, descriptors, 

and quantiles for sample reaches in the middle Verde River and 

two tributary streams, Arizona.

[Table 12 is available online only as a comma separated value (.csv) file and 

an Excel (.xlsx) file at https://doi.org/10.3133/sir20175100 ]

Verde River and in Oak Creek, which also have higher flows 

and more urbanization than other reaches. The other tributary 

reaches tended to have higher richness-metric measures and 

greater caddisfly and midge (order Diptera) taxa richness. An 

earlier study at Oak Creek demonstrated that spring discharge 

plays a selective role in larval success and diversity in caddisflies (Blinn and Ruiter, 2009) and supports the idea that 

long-term monitoring should rely on a single, consistent index 

period. Many of the variables analyzed are related to each 

other as well as to streamflow and should be considered in 

future studies.

Watershed Macroinvertebrate Distribution 

Using a Reach Characterization with 

Multiagency Data

Macroinvertebrate samples were collected from the 

upper-middle and lower-middle reaches of the Verde River and 

from the major Verde River tributaries of Oak Creek, Wet Beaver Creek, and West Clear Creek. The samples were compiled 

and analyzed for each reach. Four relative abundance (percent) 

metrics and five feeding guilds were selected to characterize 

the macroinvertebrate community of each reach. The orders 

Ephemeroptera, Trichoptera, and Diptera represent mayfly, 

caddisfly, and true fly taxa, respectively. Non-insect macroinvertebrate taxa consist of snails, clams, scuds, crayfish, 

water mites, and aquatic worms. These community metrics are 

often used to assess sensitivity to or tolerance of water quality 

condition. Likewise, the feeding guild metrics can provide 

information on functional composition of the community as 

macroinvertebrates respond to factors such as nutrient loading and sedimentation. Water quality is partially a function 

of flow and partially a function of habitat conditions making 

flow characteristics an important factor affecting community 

structure. The metrics selected effectively are the response to a 

myriad of physical and chemical conditions. 

General patterns among the Verde River reaches and 

the major tributaries of Oak Creek, Wet Beaver Creek, and 

West Clear Creek (fig. 58A) showed that median relative 

abundance of mayfly taxa (order Ephemeroptera) is 36 to 48 

percent of the overall composition of all macroinvertebrates 

collected in the upper-middle and lower-middle Verde River 

and Oak Creek. The percentage of taxa that are true flies 

(order Diptera) was higher in the tributaries than in the Verde 

River reaches and comprised a third or more of the median 

relative abundance at each. Caddisfly (order Trichoptera) and 

non-insect taxa had similar percentages among all the reaches 

suggesting that mayfly and true fly taxa are more influential to 

function of macroinvertebrate community in the middle Verde 

River watershed. Macroinvertebrates were also analyzed as 

functional feeding guilds. Trophic composition and nutrient 

cycling play a major role in stream ecosystem processes. The 

feeding guilds were compared at the same Verde River reaches 

and tributary sites (fig. 58B). Collector-gatherers were the 

most abundant feeding group found at all the reaches followed 
Macroinvertebrates 87

High-flood sample collection Moderate-flood or average-flow sample collection

10

20

30

40

50

60

70

80

Moderate-flood or average-flow sample collection

10

20

30

40

50

60

0246 8 10 12 Spring Fall 0246 8 10 12 Spring Fall

Month Index Month Index

0246 8 10 12 Spring Fall 0246 8 10 12 Spring Fall

Month Index Month Index

0246 8 10 12 Spring Fall 0246 8 10 12 Spring Fall

Month Index Month Index

High-flood sample collection Moderate-flood or average-flow sample collection

0

10

20

30

40

50

Richness, total number

 of unique taxa

Percent of single

most dominant taxa Percent caddisflies

(23) (34) (50) (28)

**

*

**

**

*

* p ≤0.01

** p ≤0.001

LOWESS line

36 Number of samples

EXPLANATION

Largest value within 1.5 times 

interquartile range above 75th 

percentile

Outside value—Value is >1.5 and 

<3 times the interquartile range 

beyond either end of the box

25th percentile

Smallest value within 1.5 times 

interquartile range below 25th 

percentile

75th percentile

50th percentile (median)

Interquartile 

range

Kruskal-Wallis Test, chi square 

High-flood sample collection

A

B

C

Figure 57. Graphs showing three macroinvertebrate 

metrics split into flood-magnitude category and 

plotted by month (number) and index (spring and fall) 

for the middle Verde River and two tributary streams, 

Arizona. A, Total richness (number of unique taxa); B, 

percentage of abundance represented by the single, 

most dominant taxa; and C, percent of individuals that 

are caddisflies (order Trichoptera). See figure 27 for 

graphs of mean daily stream discharge rates.
88 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

by the filterers-collectors. Although the composition of the 

feeding guilds was mostly similar among reaches, the tributaries showed greater percentages of scrapers and shredders. 

This is because the smaller tributary streams have a greater 

percent area with shallow substrates than does the Verde River. 

As a result, more light reaches the bed of the shallow streams, 

which leads to greater algae growth for consumption by the 

scrapers. There is also a greater concentration of canopy detritus along the margins of the smaller streams, and this provides 

more food material for the shredders. Overall, the community 

metrics did not indicate major differences that could be attributed to differences in flow conditions.

Macroinvertebrate assemblages were investigated 

because the community metrics were mostly similar among 

the primary reaches. Additional tributary reaches that had 

fewer samples were added to the assemblage analysis to determine how similar the species are at each reach. The NMDS 

ordination of assemblages showed separation between the 

tributaries and Verde River reaches and similarities in assemblage structure among most of the tributaries except for Bitter 

Creek, which plotted furthest from the other study reaches (fig. 

59). The West Clear Creek, Oak Creek, and Wet Beaver Creek 

tributaries all have similar relative abundances of each of the 

taxa groups presented. The Verde River reaches were differentiated by greater abundances of different mayfly taxa, whereas 

Bitter Creek showed higher abundances of different true fly 

(order Diptera), midge (family Chironomidae), and noninsect 

taxa. Bitter Creek is affected by wastewater contributions, and 

the creek has low dissolved oxygen and high nutrients, which 

are likely the cause for these more environmentally tolerant 

groups comprising more than half of the taxa composition (fig. 

59).

Associations Among Flow Metrics and 

Macroinvertebrate Metrics

Sampling locations where streamflow data were available to compute flow metrics were mainly located along the 

major tributaries of the Verde River—Oak Creek, Wet Beaver 

Creek, and West Clear Creek. Flow metrics were computed 

for 30, 90, and 365 days before the collection of macroinvertebrate samples. Correlation scatter plots were used to identify 

significant relations using a Kendall’s tau coefficient (p≤0.05). 

Significant relations were associated between macroinvertebrates and the 30-day flow metrics, unlike the fish which were 

mostly correlated with the longer period flow metrics. This 

time-correlation difference between fish and macroinvertebrates is likely related to the rapid colonization and lifecycle 

of macroinvertebrates (Konrad and others, 2008b; Wiele and 

others, 2012). Correlation analysis of 30-day flow metrics 

with macroinvertebrate metrics identified several flow metrics 

related to magnitude and rate-of-change that may influence 

community structure. Correlated flow-metric examples include 

the coefficient of variation of daily flows, median maximum annual streamflow, and normalized range of monthly 

streamflow.

Oak Creek had the largest number of significant associations between macroinvertebrate and flow metrics (fig. 60; 

table 13). Among the correlations, total richness and caddisfly 

richness had a negative association to maximum monthly 

streamflow, normalized range of monthly streamflow, and the 

50th percentile of absolute value of daily change in streamflow, 

which suggests some limiting threshold for caddisfly diversity 

and relative abundance for certain magnitude flows and rate-ofchange in streamflow. The increase in the overall richness was 

positively associated with the base-flow recession coefficient. 

The flow and macroinvertebrate relations are confounded by 

the timing of index sampling period and richness—the fall 

subset of samples has lower richness than the spring samples.

Wet Beaver Creek samples had a similar pattern of caddisfly richness as Oak Creek but showed increasing associations 

between total richness and mayfly relative abundance. Functional feeding-group relations were also significant at Wet Beaver Creek, but this may be related to trophic patterns related to 

season rather than flow as shown by the separation (along the 

y-axis) between fall and spring samples (fig. 60). The percentage of collector-gatherers relative to overall taxa richness was 

greater in the fall, and the percentage of scrapers relative to 

overall taxa richness was greater in the spring. This seasonal 

difference was also evident in the general plot of percentage 

of individuals that comprise the caddisfly order compared by 

index period (fig. 57).

West Clear Creek had the least number of significant 

relations among macroinvertebrate and hydrologic metrics. 

Caddisfly relative abundance and taxa showed significant relations to multiple discharge exceedance thresholds (25th, 50th, 

75th, 90th, and 99th percent), which suggests a general overall 

decrease of caddisfly abundance to increased flow and no 

threshold to a specific magnitude of flow.

Macroinvertebrate Quantile Regression

The quantile-regression analysis helped to show the 

response of macroinvertebrate metrics in relation to flow 

metrics that was not apparent using least squares regression. 

The relative abundance and richness measures of most of the 

taxa and community metrics other than caddisflies and mayflies were not significantly related to most of the hydrologic 

metrics analyzed. Several of the hydrologic metrics developed 

to measure flow variability were correlated, so only the logtransformed median annual maximum flows (30 days before 

sampling) were evaluated using quantile regression. The 

median annual maximum flows (30 days before and after log 

transformation) are shown in relation to the relative abundance 

of caddisflies and mayflies for all gaged locations (fig. 61A, B). 

Although caddisflies and mayflies showed significant responses 

to hydrologic metrics, they are inversely related (τ=–0.38, 

p=0.0009) and as a result, the response to the hydrologic 

metrics was also inversely related. The relative abundance of 

caddisflies decreased in response to the hydrologic metrics 

representing streamflow variability, including median annual 
Macroinvertebrates 89

Macroinvertebrate assemblage, in percent

Study reach

Macroinvertebrate functional feeding groups, in percent

Study reach

Upper-middle

Verde River

Lower-middle

Verde River

Oak

Creek

Wet Beaver

Creek

West Clear

Creek

Macroinvertebrates

Mayflies (Ephemeroptera)

Caddisflies (Trichoptera)

True flies (Diptera)

Non-insect taxa

Functional feeding group

Predators

Collector gatherers

Filterers-Collectors

Scrapers

Shreders

0

20

40

60

80

0

20

40

60

80

100

27 19 47 29 37

A

B

Upper-middle

Verde River

Lower-middle

Verde River

Oak

Creek

Wet Beaver

Creek

West Clear

Creek

36 Number of samples

EXPLANATION

Largest value within 1.5 times 

interquartile range above 75th 

percentile

Outside value—Value is >1.5 and 

<3 times the interquartile range 

beyond either end of the box

25th percentile

Smallest value within 1.5 times 

interquartile range below 25th 

percentile

75th percentile

50th percentile (median)

Interquartile 

range

Figure 58. Graphs showing boxplots of macroinvertebrate-assemblage composition and 

functional feeding groups for the upper-middle and lower-middle Verde River, Arizona, and major 

tributaries. A, Macroinvertebrate-assemblage composition in percent; B, macroinvertebrate 

functional feeding groups in percent.
90 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

Transformation: Fourth root

Resemblance matrix: Bray Curtis

Bitter Creek

Sycamore Creek

Lower-middle Verde River

Upper-middle Verde River

West Clear Creek

Wet Beaver Creek Oak Creek

Spring Creek

Two-dimensional stress: 0.03

NMDS axis 2

NMDS axis 1

Figure 59. Plot showing nonmetric multidimensional scaling (NMDS) of multivarite centroids for 

macroinvertebrate assemblages from the upper-middle and lower-middle Verde River, Arizona, and tributaries. 
Macroinvertebrates 91

B. Wet Beaver Creek

A. Oak Creek Richness (total number of taxa) Caddisfly richness Caddisfly richness 

30-day base-flow recession

coefficient (BFR)

30-day maximum monthly streamflow,

in cubic feet per second

30-day normalized range

of monthly streamflow

30-day base-flow recession

coefficient (BFR)

30-day maximum monthly streamflow, in 

cubic feet per second

30-day normalized range

of monthly streamflow

 Log 30-day median annual

maximum streamflow

-0.1 -0.08 -0.06 -0.04 -0.02 0 0 50 100 150 200 250 300 0 0.5 1 1.5

-0.1 -0.08 -0.06 -0.04 -0.02 0 0 50 100 150 200 250 300 0 0.5 1 1.5

1 1.5 2 2.5 3

10

15

20

25

30

35

40

45

50

55

10

15

20

25

30

35

40

45

50

55

10

15

20

25

30

35

40

45

50

55

1

2

3

4

5

6

7

8

9

10

1

2

3

4

5

6

7

8

9

10

1

2

3

4

5

6

7

8

9

10

1

2

3

4

5

6

7

8

9

10

τ=−0.557

τ=0.555 p=0.0052

p=0.0104

τ=−0.517

p=0.0104

τ=−0.472

p=0.0126

τ=−0.373

p=0.0467

τ=0.427

p=0.0353

τ=−0.446

p=0.0091

C. West Clear Creek

0

5

10

15

20

0 0.5 1 1.5 2

Coefficient of variation of daily flows

(30 days before sampling)

10

20

30

40

50

60

70

80

1 1.5 2 2.5

Log maximum monthly streamflow

(30 days before sampling)

τ=0.339

p =0.0377

Percent gatherers-collectors

Percent scrapers

τ=−0.363

p=0.0282

-5

0

5

10

15

20

25

30

35

40

Percent caddisflies

1.1 1.15 1.2 1.25 1.3 1.35 1.4 1.45

Log discharge that exceeded the 75th percentile 

of the 30-day period before sampling

τ =−0.325

p =0.0171

EXPLANATION

Spring sample

Fall sample

LOWESS line

Figure 60. Graphs showing the statistically significant relations among 

30-day hydrologic metrics and select macroinvertebrate metrics for the (A) 

Oak Creek, (B) Wet Beaver Creek, and (C) West Clear Creek tributaries of the 

middle Verde River, Arizona. Caddisfly (order Trichoptera) richness measured 

as number of unique Trichoptera taxa present. Percent gatherers-collectors 

and percent scrappers—percent of overall taxa in the functional feeding 

group. Percent caddisflies—percent of overall taxa that are caddisflies. τ, 

Kendall’s tau correlation.
92 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

maximum flows 30-days before sampling (fig. 61A), while 

relative abundance of mayfly increased (fig. 61B).

A majority of the caddisfly relative-abundance density 

decreased (quantiles 0.25–0.60) with increasing median annual 

maximum flow values. A proportion of the density (>0.75) 

is less responsive the higher median annual maximum flow 

values, possibly indicating certain species of caddisflies are 

less affected by the larger median annual flows (fig. 61A). 

The mayflies relative abundance showed that about half of the 

density (quantiles 0.50–0.90) responded similarly, increasing 

with increased median annual maximum flow values 30-days 

before sampling , indicating preference for flow variability 

(fig. 61B).

Caddisfly population relative to median annual maximum 

flows 30-days before sampling showed no floor and a poorly 

defined ceiling, following more of the classic wedge-shaped 

scatterplot distribution (Konrad and others, 2008b; Wang and 

others, 2007; Kail and others, 2011). In other words, caddisflies were more common in lower flows but did not tolerate 

the highest flows (fig. 61A). This implies that at lower median 

annual maximum flows other factors predominate in limiting 

overall caddisfly abundance. At higher flows, median annual 

maximum flow plays a greater role in limiting their relative 

population.

Ceilings and floors (Konrad and others, 2008b) were both 

evident in the mayfly data (fig. 61B). The ceiling (decreasing 0.90 quantile) implies that additional factors other than 

antecedent streamflow conditions alone limit the presence of 

these macroinvertebrates at low median annual maximum flow 

values. In low flows (<1.0 median annual maximum flows, 30 

days before sampling), no more than 50 to 60 percent of total 

macroinvertebrates per sample were mayflies. On the other 

hand, higher median maximum annual flow values may be 

more of a limiting factor for macroinvertebrate species other 

Macroinvertebrate metric Stream diversion Index period Large-flood year Mainstem or tributary

Total number of taxa 

(richness)

-- Greater in the fall Greater after no large-magnitude floodingGreater in the samples collected in tributaries

Total mayfly (Ephemeroptera) taxa-- -- -- Greater in the samples collected in the mainstem

Total caddisfly (Trichoptera) taxa-- Greater in the fall -- --

Percent of abundance 

composed of mayflies

-- -- Greater after large-magnitude 

flooding

Greater in the samples collected in the mainstem

Percent of abundance 

composed of caddisflies

-- Greater in the fall -- --

Percent of abundance 

composed of true flies 

(Diptera)

-- Greater in the spring -- Greater in the samples collected in tributaries

Percent of abundance 

composed of non-biting midges (Orthocladiinae)

-- -- Greater after no large-magnitude floodingGreater in the samples collected in tributaries

Percent of abundance 

composed by noninsects

Greater in diverted 

reaches

-- Greater after no large-magnitude flooding--

Percent of abundance 

composed by worms in 

the subclass Oligochaetes

Greater in diverted 

reaches

-- -- --

Shannon diversity index -- Greater in the fall Greater after no large-magnitude flooding--

Total abundance -- Greater in the spring -- Greater in the samples collected in the mainstem

Percent of abundance 

composed by pollution 

tolerant taxa

-- -- Greater after no large-magnitude floodingGreater in the samples collected in tributaries

Table 13. Macroinvertebrate metrics significantly greater (p≤0.05) in reaches of the middle Verde River and two tributaries, Arizona, 

that have water diversions and were collected during the spring or fall index period, collected after large magnitude floods or no large 

flooding events, and collected on the Verde River or a tributary.

[--, no significant difference]
Conclusion and Future Directions 93

than mayflies, which could allow mayflies to outcompete these 

species. This would explain the increasing percent of mayflies 

with median maximum annual flow , 30 days before sampling 

in even the lowest quantile (floor) (fig. 61B).

Caddisfly populations appeared to be responding to less 

flashy and more stable streamflows, whereas the opposite was 

true for mayfly populations. The results of the quantile regression also suggest that estimating effects of hydrologic metrics 

based on only the mean may underestimate or overestimate the 

effects observed by quantiles above the mean.

Macroinvertebrate Pilot Study

In 2010, six macroinvertebrate samples were collected 

from the Verde River in the upper part of its middle watershed using USGS protocols (Moulton and others, 2002). The 

six locations were the Verde River below Granite Creek, 

Salt River Project low-flow streamgage, USGS Verde River 

at Paulden gage, Perkinsville Bridge, USGS Verde River 

at Clarkdale gage, and Reitz Ranch property (fig. 26). The 

NMDS ordination of macroinvertebrate assemblages showed 

that the Verde River below Granite Creek site was different 

than all the other sites sampled and that Perkinsville and Reitz 

Ranch samples had similar community structure (fig. 62). The 

Verde below Granite Creek had the largest percentage of caddisfly taxa, lowest mayfly taxa, and lowest diversity (Shannon 

diversity index of 0.91; largest Shannon diversity index of 

1.29 was at Clarkdale) of all the locations. Several taxa were 

observed at the Verde River below Granite Creek that were not 

found at any of the other five locations (table 14). Paulden had 

high mayfly taxa percentages but very low midge taxa percentages, whereas the other four stations were similar in overall 

diversity and caddisfly taxa percentages.

Superimposing microhabitat variables on the NMDS 

ordination revealed differences between sites and the communities found there (fig. 62). The differences in community 

composition at the Verde River below Granite Creek location compared to the other sites are likely due to the smaller 

substrate sizes, lower velocities, shallow depths, and highest 

riparian cover. The Campbell Ranch and Paulden locations 

had similar microhabitat characteristics, with the exception of 

riparian cover, yet the assemblage structure was very different.

Conclusion and Future Directions

The middle Verde River watershed is complex in ecological function exhibiting characteristics of an undisturbed flow 

Table 14. Kendall tau correlations between macroinvertebrate 

metrics and hydrologic metrics for the middle Verde River, 

Arizona, and tributaries.

[Table 14 is available online only as a comma separated value (.csv) file and 

an Excel (.xlsx) file at https://doi.org/10.3133/sir20175100 .]

regime in the upper part and an altered flow regime in the 

lower part, a result of surface-water diversions and groundwater withdrawal. Relatively unaltered flow in the upper-middle 

watershed maintains a healthy ecosystem, with a mixed age, 

mixed patch vegetative structure. In the river, more riffle 

habitat and fewer diversions were present in the upper-middle 

part of the watershed, whereas more pools and diversions were 

present in the lower-middle part. In heavily diverted reaches, 

non-native fish outnumbered native fish, whereas more native 

fish species were found in the nondiverted reaches. Generally, 

the greatest number and relative abundance (percentage) of 

native fish were also found in the upper-middle reaches, and 

non-native fish generally declined in presence with distance 

downstream. Consistent with these observations is that across 

five locations sampled in the middle Verde watershed, native 

fish preferred slow to moderate velocity moderately deep 

water over coarse gravel, whereas non-native fish preferred 

standing, deeper water over silt and sand, although non-native 

species were also found in faster, shallow water over coarse 

gravel. Native suckers (desert and Sonora) in particular decline 

during periods of extended base flow, whereas non-native sunfish (bass species and green sunfish) in contrast decline during 

periods of flashy, high flows. Among macroinvertebrates, caddisfly populations appeared to prefer less flashy, more stable 

streamflows, whereas mayfly populations responded to less 

stable, more flashy streams. Overall, it appears that unaltered 

disturbance regimes with fewer diversions and more flashy 

and somewhat higher velocity flows are generally preferred by 

native species in the middle Verde River watershed.

The statistically based empirical relations determined 

in this report can be used to develop the basis for a conceptual model of environmental flows in the middle Verde River 

watershed. A robust conceptual model can provide the foundation for developing physically based, quantitative and predictive models of environmental flows for this semiarid southwestern river. Such models can improve the understanding of 

the effects of increased stresses from climate variability and 

increased demands on the water supply of the Verde River.

Spring snowpack across the western United States 

(including the Southwest) is predicted to decrease sharply 

through the 21st century, leading to reductions in soil moisture 

and substantially lower spring-summer runoff and base flow 

(Cayan and others, 2013). These conditions could result in 

increased flow intermittency (of both area and frequency), 

as well as an increase in the total time reaches remain dry. 

Increased intermittency would affect in-stream biota, including macroinvertebrates (Miller and Brasher, 2011). In addition, 

a changing climate could affect the magnitude, as well as timing, of all components of the hydrograph (Cayan and others, 

2013; Jaeger and others, 2014), further stressing a system that 

already faces reduction in streamflow as a result of groundwater withdrawals and surface-water diversions. Changes to the 

flow regime will alter the frequency, timing, and intensity of 

the mobilization of the bed sediments that form the microhabitat framework. Alterations to hydrologic characteristics have 

been shown to influence in-stream microhabitat (Brasher and 
94 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona Percent caddisflies

0

5

10

15

20

25

30

35

40

1.0 1.5 2.0 2.5 3.0 3.5

Logarithm of median maximum annual flow (30 days before sampling)

Percent mayflies

0

10

20

30

40

50

60

70

80

1.0 1.5 2.0 2.5 3.0 3.5

Quantile

0.1

0.25

0.5

0.9

Blue bands represent 

95-percent confidence 

intervals

EXPLANATION

0.75

A

B

Logarithm of median maximum annual flow (30 days before sampling)

40

 0

20

20

0.2 0.4 0.6 0.8

Quantile

40

30

20

10

 0

0.2 0.4 0.6 0.8

Quantile

Intercept

Slope

5

0

-10

-5

-15

0.2 0.4 0.6 0.8

Quantile

Slope

40

30

20

10

 0

0.2 0.4 0.6 0.8

Quantile

Intercept

Figure 61. Graphs showing quantile 

regression lines, intercepts, and 

slopes of the 0.10, 0.25, 0.50, 0.75, 

and 0.90 quantile regression lines for 

significantly correlated hydrologic 

and macroinvertebrate metrics for 

the middle Verde River and two 

tributary sites, Arizona. A, Relative 

abundance of caddisflies (percent of 

overall taxa that are order Trichoptera) 

and the log-transformed median 

annual maximum flow 30 days before 

sampling. B, Relative abundance of 

mayflies (percent of overall taxa that 

are order Ephemeroptera) and the logtransformed median annual maximum 

flow 30 days before sampling. Blue 

band represent the 95-percent 

confidence intervals for each plot.
Conclusion and Future Directions 95

A

B 

C

A. Percent mayflies (Ephemeroptera)

0 to 60 percent

B. Percent caddisflies (Trichoptera)

0 to 60 percent

C. Percent true flies (Diptera)

0 to 60 percent

Minimum depth

Median velocity

Interquartile range of velocity

Median pebble size

NMDS axis 1

NMDS axis 2

Square-root transformation

Bray Curtis similarity resemblance matrix

Two-dimensional stress= 0

Direction and degree of Pearson 

correlation to NMDS axis (ρ between −1 to 1)

Median riparian cover

Verde River below 

Granite Creek

Verde River near Paulden

Verde River at Clarkdale Verde River at

Perkinsville

Verde River

at Reitz Ranch

Verde River at low-flow Salt River 

Project streamgage

EXPLANATION

(ρ=−1 axis 2)

(ρ=1 axis 2)

(ρ=−1 axis 1)

(ρ=1 axis 1)

Figure 62. Diagram showing nonmetric multidimensional scaling (NMDS) ordination plot of assemblages and 

macroinvertebrate metric pie plots of percent mayflies, percent caddisflies, and percent true flies (as a percent of overall 

taxa) for the middle Verde River, Arizona. Pie plots are located at the respective NMDS assemblage point for Verde below 

Granite Creek, Salt River Project low-flow streamgage, Paulden streamgage, Perkinsville Bridge, Clarkdale streamgage, 

and Reitz Ranch property sampling sites on the middle Verde River, Arizona. Size of pie sector corresponds to percent of (A) 

mayflies, (B) caddisflies, (C) true flies. Vector Spearman correlation lines are plotted (rho, ρ, >0.8) of median riparian cover, 

minimum depth, median pebble size, median velocity, and interquartile range of velocity.
96 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

Taxa level identification Abundance Site Taxa order Common name

Gomphidae 92 Salt River Project low-flow 

streamgage

Odonata clubtail dragonflies

Culoptila sp. 4 Salt River Project low-flow 

streamgage

Trichoptera caddisfly

Tanytarsus sp. 5 USGS Clarkdale streamgage Diptera non-biting midge

Sublettea sp. 27 USGS Clarkdale streamgage Diptera non-biting midge

Heptageniidae 11 USGS Clarkdale streamgage Ephemeroptera mayfly

Capniidae 19 USGS Clarkdale streamgage Plecoptera stonefly, small winter stoneflies

Centroptilum sp. 12 USGS Paulden streamgage Ephemeroptera mayfly, small Minnow Mayflies

Ambrysus sp. 48 USGS Paulden streamgage Hemiptera creeping water bugs

Hirudinea 2 Verde river below Granite Creek Annelida leech

Corynoneura sp. 2 Verde river below Granite Creek Diptera European non-biting midges

Paratanytarsus sp. 2 Verde river below Granite Creek Diptera European non-biting midges

Stictochironomus sp. 2 Verde river below Granite Creek Diptera non-biting midge

Tipula sp. 5 Verde river below Granite Creek Diptera crane fly

Cricotopus bicinctus group 10 Verde river below Granite Creek Diptera midge

Physa sp. 5 Verde river below Granite Creek Gastropoda left-handed or sinistral, airbreathing freshwater snails

Sigara sp. 5 Verde river below Granite Creek Hemiptera water boatmen

Ostracoda 14 Verde river below Granite Creek Ostracoda seed shrimp

Pisidium sp. 3 Verde river below Granite Creek Veneroida minute freshwater clams known 

as pill clams or pea clams

Microtendipes pedellus group 12 Verde river near Reitz Ranch Diptera midge

Eukiefferiella brehmi group 15 Verde river near Reitz Ranch Diptera non-biting midge

Pseudorthocladius sp. 15 Verde river near Reitz Ranch Diptera European non-biting midges

Table 15. Unique taxa observed in the six macroinvertebrate assemblages collected from the Verde River in the upper part of the 

middle Verde River watershed, Arizona.

others, 2004; Konrad and others, 2008; Brasher and others, 

2010), and thus fish and macroinvertebrate assemblage structure (Konrad and others, 2008b; Brasher and others, 2010). 

Additional research can begin to ascertain the hydrological 

requirements of those plant and animal species that are reliant 

on the Verde River system.

The primary link between groundwater withdrawals, 

diversions, and climate change on the one hand and their 

effects on riparian and in-stream microhabitats on the other is 

through streamflow. Streamflow alteration caused by human 

stressors and climate change will manifest in changes to the 

riparian habitat and streamflow regime. These changes will 

ultimately lead to shifts in the structure and function of the 

biotic communities that rely on these habitats. Measuring 

these changes, attributing causative mechanisms, and developing models to represent future conditions will be challenging. A common approach has been to mine data for correlative 

associations between biota and streamflow characteristics in 

an attempt to define the habitat thresholds of species and 

communities. A more holistic synthesis of the biological 

and physical components of the middle Verde River watershed (including many of the habitat, biologic, and hydraulic 

characteristic discussed in this report) would complement the 

correlative approach and give resource managers a processbased understanding of the links between the geomorphology 

and microhabitats of the middle Verde River watershed. This 

would also provide a physical basis for understanding the role 

of climate change in the development and alteration of riparian 

and aquatic microhabitat.

Models of flow and sediment transport have been used to 

examine environmentally damaged and vulnerable rivers (for 

example, Wiele and others, 2007) and improve management 

of environmental recovery (for example, Wiele and Torizzo, 

2005). Calculations of the hydraulic properties of in-stream 

microhabitat have been used to examine seasonal variations and effects of dam operation on in-stream microhabitat 

(Korman and others, 2004). Calculations of the hydraulic 

geometry and sediment transport at a streamgage site on the 

upper-middle Verde River have provided insight into the timing and magnitude of the river’s response to significant runoff 

events and the relation between sedimentary processes and 

in-stream microhabitat. Models can be used to extrapolate 

information from small-scale hydraulic studies to facilitate a 

better understanding of relations among low- and mediumscale flows and microhabitat properties, as well as estimate 

critical flows for reworking of the channel. Recent advances 
References Cited 97

in hydrological field techniques and environmental modeling 

will also contribute to unraveling these complex linkages (for 

example, Korman and others, 2004). Research using acoustic 

Doppler technology (Klaar and others, 2009; Klaar and others, 

2011) has provided a means of linking changes in in-stream 

discharge with the availability of in-stream microhabitat by 

measuring small-scale near-bed flow fields. These data provide 

a direct, physical link between discharge and channel properties that was not possible to obtain with cross sectionally or 

vertically averaged flow velocities or with coarser velocity 

measurements made with mechanical meters. When these 

data are combined with microhabitat preferences of fish and 

macroinvertebrates, it is possible to ascertain how microhabitat availability will change with changing river base flow, and 

hence identify environmental flow levels and timings that are 

crucial for species survival.

During this study, pilot studies were conducted to begin 

to identify associations among hydrologic and biologic 

metrics. Additional studies would enable the quantification 

of the response of in-stream and riparian biota to hydrologic 

conditions and link aquatic-community structure with flowalteration scenarios. Hydrologic and biologic metrics that are 

most responsive to flow-alteration could then be identified, 

and models for flow alteration-ecological response scenarios 

could be developed.

References Cited

Acreman, Mike, Arthington, A.H., Colloff, M.J., Couch, Carol, 

Crossman, N.D., Dyer, Fiona, Overton, Ian, Pollino, C.A., 

Stewardson, M.J., and Young, William, 2014, Environmental flows for natural, hybrid, and novel riverine ecosystems 

in a changing world: Frontiers in Ecology and the Environment, v. 12, no. 8, p. 466–473.

Adams, D. K. and Comrie, A. C., 1997, The North American 

monsoon: Bulletin of the American Meteorological Society, 

v. 78, no. 10, p. 2197-2213.

Alam, J., 1997, Irrigation in the Verde Valley—A report of the 

irrigation diversion improvement project: Verde Natural 

Resource Conservation District, 96 p.

American Rivers, 2006, America’s most endangered rivers of 

2006: American Rivers, accessed May 5, 2017, at https://

s3.amazonaws.com/american-rivers-website/wp-content/

uploads/2016/02/24220916/2006-mer-report.pdf.

Anderson, M.J., Gorley, R.N., and Clarke, K.R., 2008, PERMANOVA+ for PRIMER—Guide to Software and Statistical Methods: Plymouth, U.K., PRIMER-E, 214 p.

Archfield, S.A., Kennen, J.G., Carlisle, D.M., and Wolock 

D.M., 2014, An objective and parsimonious approach for 

classifying natural flow regimes at a continental scale: River 

Research and Applications, v. 30, no. 9, p.1166–1183. [Also 

available at http://onlinelibrary.wiley.com/doi/10.1002/

rra.2710/epdf.]

Arend, K.K., 1999, Macrohabitat identification, in Bain, 

M.B., and Stevenson, N.J., eds., Aquatic habitat assessment—Common methods: Bethesda, Md., American 

Fisheries Society, p. 75–93.

Arizona Department of Environmental Quality, 2006, A 

manual of procedures for the sampling of surface waters: 

Arizona Department of Environmental Quality Technical 

Bulletin TB06–02, 335 p.

Arizona Department of Water Resources, 2014, Central 

Highlands planning area water supply—Groundwater: Arizona Department of Water Resources web page, accessed 

on September 5, 2017 at 

http://www.azwater.gov/AzDWR/StatewidePlanning/

WaterAtlas/CentralHighlands/PlanningAreaOverview/

WaterSupply-Groundwater.htm .

Arthington, A.H., Bunn, S.E., Poff, N.L., and Naiman, R.J., 

2006, The challenge of providing environmental flow rules 

to sustain river ecosystems: Ecological Applications, v. 16, 

no. 4, p. 1311–1318.

Auer, C.M., 2010, A critique of the student note entitled “The 

battle to save the Verde: How Arizona’s water law could 

destroy one of its last free-flowing rivers”: Environmental 

Law Reporter, v. 40, p. 10212-10221.

Bailey, J.K., Schweitzer, J.A., Whitham, T.G., 2001, Salt 

cedar negatively affects biodiversity of aquatic macroinvertebrates: Wetlands, v. 21, no. 3, p. 442–447.

Bain, M.B., Finn, T.F., and Brooks, J.E., 1988, Stream flow 

regulation and fish community structure: Ecology, v. 69, 

no. 2, p. 382–392.

Beauchamp, V.B., Stomberg, J.C., and Stutz, J.C., 2005, 

Interactions between Tamarix ramosissima (saltcedar), 

Populus fremontii (cottonwood), and mycorrhizal fungi—

Effects on seedling growth and plant species coexistence: 

Plant and Soil, v. 275, p. 221–231.

Bestgen, K.R., and Propst, D.L., 1989, Distribution, status 

and notes on the ecology of Gila robusta (Cyprinidae) in 

the Gila River drainage, New Mexico: Southwestern Naturalist, v. 34, p. 402–412.

Blasch, K.W., Hoffmann, J.P., Graser, L.F., Bryson, J.R., and 

Flint, A.L., 2006, Hydrogeology of the upper and middle 

Verde River watersheds, central Arizona: U.S. Geological 

Survey Scientific Investigations Report 2005–5198, 102 

p., 3 plates. [Also available at https://pubs.er.usgs.gov/

publication/sir20055198 .]

Blinn, D.W., and Ruiter, D.E., 2009, Caddisfly (Trichoptera) 

assemblages along major river drainages in Arizona: Western North American Naturalist, v. 69, no. 3, p. 299–308.

Brasher, A.M.D., 2003, Impacts of human disturbances on 

biotic communities in Hawaiian streams: BioScience, v. 

53, no. 11, p. 1052–1060.
98 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

Brasher, A.M.D., Konrad, C.P., May, J.T., Edmiston, C.S. 

and Close, R.N., 2010, Streamflow characteristics and 

benthic invertebrate assemblages in streams across the 

western United States: U.S. Geological Survey Fact Sheet 

2010–3110, 4 p. [Also available at https://pubs.usgs.gov/

fs/2010/3110/ .]

Brasher, A.M.D., Wolff, R.H., and Luton, C.D., 2004, Associations among land use, habitat characteristics, and invertebrate community structure in nine streams on the island of 

Oahu, Hawaii, 1999–2001: U.S. Geological Survey WaterResources Investigations Report 03–4256, 47 p. [Also available at https://pubs.usgs.gov/wri/wri034256/ .]

Buchanan, T.J., and Somers, W.P., 1969, Discharge measurements at gaging stations: U.S. Geological Survey Techniques 

of Water-Resources Investigations, book 3, chap. A8, 65 p. 

[Also available at https://pubs.usgs.gov/twri/twri3a8/ .]

Cade, B.S., Terrell, J.W., and Schroeder, R.L., 1999, Estimating 

effects of limiting factors with regression quantiles, Ecology, 

v. 80, no. 1, p. 311–323.

Caldwell, P.V., Kennen, J.G., Sun, G., Kiang, J.E., Butcher, 

J.B., Eddy, M.C., Hay, L.E., LaFontaine, J.H., Hain, E.F., 

Nelson, S.C., and McNulty, S.G., 2015, A comparison of 

hydrologic models for ecological flows and water availability: Ecohydrology, v. 8, no. 8, p. 1525–1546. [Also available 

at https://doi.org/10.1002/eco.1602 .]

California Invasive Plant Council, 2011, Prioritizing regional 

response to invasive plants in the Sierra Nevada: California Invasive Plant Council, 179 p., accessed on April 01, 

2015, at http://www.cal-ipc.org/docs/ip/mapping/sierra/

pdf/0SierraFrontMatterWeb.pdf .

Capone, T.A., and Kushlan, J.A., 1991, Fish community structure in dry season stream pools: Ecology, v. 72, p. 983–992.

Cayan, D.R., Tyree, Mary, Kunkel, K.E., Castro, Chris, Gershunov, Alexander, Barsugli, Joseph, Ray, A.J., Overpeck, 

Jonathan, Anderson, Michael, Russell, Joellen, Rajagopalan, 

Balaji, Rangwala, Imtiaz, and Duffy, Phil, 2013, Future climate—Projected average, chap 6 of Garfin, G., Jardine, A., 

Merideth, R., Black, M., and S. LeRoy, S., eds., Assessment 

of climate change in the southwest United States—A report 

prepared for the National Climate Assessment: Washington, 

D.C., Island Press, A report by the Southwest Climate Alliance, p. 101–125.

Coles, J.F., McMahon, Gerard, Bell, A.H., Brown, L.R., 

Fitzpatrick, F.A., Scudder Eikenberry, B.C., Woodside, 

M.D., Cuffney, T.F., Bryant, W.L., Cappiella, Karen, FraleyMcNeal, Lisa, and Stack, W.P., 2012, Effects of urban 

development on stream ecosystems in nine metropolitan 

study areas across the United States: U.S. Geological Survey 

Circular 1373, 138 p. [Also available online at https://pubs.

usgs.gov/circ/1373/ .]

Corkhill, E.F., and Mason, D.A., 1995, Hydrogeology and 

simulation of groundwater flow Prescott Active Management Area, Yavapai County, Arizona—Modeling report no. 

9: Arizona Department of Water Resources, 213 p.

Courtenay, W.R., Jr., and Meffee, G.K., 1989, Small fishes in 

strange places—A review of introduced poeciliids, in Meffee, G.K., and Snelson, F.F., Jr., eds., Ecology and evolution 

of livebearing fishes (Poeciliidae): Prentice Hall, Englewood Cliffs, New Jersey, p. 319–331.

Cuffney, T.F., 2003, User’s manual for the National WaterQuality Assessment Program Invertebrate Data Analysis 

System (IDAS): U.S. Geological Survey Open-File Report 

03–172, 103 p.

Daly, C., Neilson, R.P., and Phillips, D.L., 1994, A statisticaltopographic model for mapping climatological precipitation 

over mountainous terrain: Journal of Applied Meteorology, 

v. 33, p. 140–158.

Deacon, J.E., 1988, The endangered woundfin and water 

management in the Virgin River, Utah, Arizona, Nevada: 

Fisheries, v. 13, no. 1, p. 18–24.

Deacon, J.E., and Minckley, W.L., 1974, Desert fishes, in

Brown, G.W., ed., Desert biology II: New York, New York, 

Academic Press, p. 385-488.

DeBano, L.F., and Schmidt, L.J., 2004, Definitions and classifications, in Baker, M.B., Jr., Folliott, P.F., DeBano, L.F., 

and Neary, D.G., eds., Riparian areas of the southwestern 

United States hydrology ecology and management: Boca 

Raton, Fla., CRC Press, p. 11–27.

DiTomaso, J.M., 1998, Impact, biology, and ecology of saltcedar (Tamarix spp.) in the southwestern United States: Weed 

Technology, v. 12, p. 236–336.

Dudley, R.K., and Matter, W.J., 2000, Effects of small green 

sunfish (Lepomis cyanellus) on recruitment of Gila chub 

(Gila intermedia) in Sabino Creek, Arizona: The Southwestern Naturalist, v. 45, no. 1, p. 24–29.

Fagan, W.F., Unmack, P.J., Burgess, C., and Minckley, W.L., 

2002, Rarity, fragmentation and extinction risk in desert 

fishes: Ecology, v. 83, no. 12, p. 3250–3256.

Fenner, Pattie, Brady, W.W., and Patton, D.R., 1984, Observations on seeds and seedlings of Fremont Cottonwood: 

Desert Plants, v. 6, no. 1, p. 55–58.

Fenner, Pattie, Brady, W.W., and Patton, D.R., 1985, Effects 

of regulated water flows on regeneration of Fremont Cottonwood: Journal of Range Management, v. 38, no. 2, p. 

135–138.
References Cited 99

Filippone, C., and Leake, S.A., 2005, Time scales in the sustainable management of water resources: Southwest Hydrology, v.4, no. 1, p. 16–17, 26.

Flint, A.L., and Flint, L.E., 2007, Application of the Basin 

Characteristic Model to estimate in-place recharge and runoff potential in the Basin and Range carbonate-rock aquifer 

system, White Pine County, Nevada, and adjacent areas in 

Nevada and Utah: U.S. Geological Survey Scientific Investigations Report 2007–5099, 21 p. [Also available at https://

pubs.usgs.gov/sir/2007/5099/pdf/sir20075099.pdf .]

Flint, L.E., Flint, A.L., Stolp, B.J., and Danskin, W.R., 2012, 

A basin-scale approach for assessing water resources in a 

semiarid environment—San Diego region, California, and 

Mexico: Hydrology and Earth System Sciences, v. 16, p. 

3817–3833, doi: 10.5194/hess-16-3817-2012, 2012.

Flosi, Gary, Downie, Scott, Hopelain, James, Bird, Michael, 

Coey, Robert, and Collins, Barry, 2010, California salmonid 

stream habitat restoration manual, 4th ed., part III—State 

of California: California Department of Fish and Game, 

Wildlife and Fisheries Division, 57 p.

Folliott, P.F., Baker, M.B., Jr., DeBano, L.F., and Neary, 

D.G., 2004, Introduction, in Baker, M.B., Jr., Folliott, P.F., 

DeBano, L.F., and Neary, D.G., eds., Riparian areas of the 

southwestern United States—Hydrology, ecology, and management: Boca Raton, FL, CRC Press, p. 1–10.

Fred Phillips Consulting, 2011, Verde River Cooperative 

Invasive Plant Management Plan: Prepared by Fred Phillips 

Consulting and submitted to Friends of the Verde River Greenway, 25 p., accessed March 15, 2016, at https://verderiver.

org/wp-content/uploads/2017/12/verde-river-cooperativeinvasive-plant-management-plan.pdf.

Garner, B.D., and Bills, D.J., 2012, Spatial and seasonal variability of base flow in the Verde Valley, central Arizona, 

2007 and 2011: U.S. Geological Survey Scientific Investigations Report 2012–5192, 33 p., accessed June 26, 2017, at 

https://pubs.usgs.gov/sir/2012/5192/.

Garner, B.D., Pool, D.R., Tillman, F.D., and Forbes, B.T., 

2013, Human effects on the hydrologic system of the Verde 

Valley, central Arizona, 1910–2005 and 2005–2110, using a 

regional groundwater flow model: U.S. Geological Survey 

Scientific Investigations Report 2013–5029, 47 p., accessed 

June 26, 2017, at https://pubs.usgs.gov/sir/2013/5029/.

Gido, K.B., and Propst, D.L., 2012, Long-term dynamics of 

native and nonnative fishes in the San Juan River, New 

Mexico and Utah, under a partially managed flow regime: 

Transactions of the American Fisheries Society, v. 141, no. 

3, p. 645–659.

Glenn, E., Tanner, R., Mendez, S., Kehret, T., Moore, D., 

Garcia, J., and Valdes, C., 1998, Growth rates, salt tolerance, 

and water use characteristics of native and invasive riparian 

plants from the delta of the Colorado River, Mexico: Journal 

of Arid Environments, v. 40, p. 281–294.

Guilbault, K., 2011, The influence of chilling requirement 

on the southern distribution limit of exotic Russian olive 

(Elaeagnus angustifolia) in western North America: Colorado State University, Master’s thesis, 69 p.

Haney, J.A., Turner, D.S., Springer, A.E., Stromberg, J.C., Stevens, L.E., Pearthree, P.A., and Supplee, V., 2008, Ecological 

implications of Verde River flows: Arizona Water Institute, 

The Nature Conservancy, and the Verde River Basin Partnership, 114 p.

Harvey, B.C., and Stewart, A.J., 1991, Fish size and habitat 

depth relationships in headwater streams: Oecologia, v. 87, 

p. 336–342.

Hazelton, A.F., 2011. How will hydrologic change alter riparian 

plant communities of the arid and semi-arid Southwest? The 

Problem Approached from Two Perspectives: Tempe, Ariz., 

Arizona State University, Master’s thesis, 90 p.

HDR, Inc., 2011, Verde River flood hazard assessment—Floodplain redelineation Clarkdale through Beasley Flat, Yavapai 

County, Arizona: HDR, Inc., report prepared for Yavapai 

County Flood Control District, v. 3, 52 p.

Henriksen, J.A., Heasley, J., Kennen, J.G., and Niewsand, S. 

2006, Users’ manual for the hydroecological integrity assessment process software (including the New Jersey Assessment Tools): U.S. Geological Survey Open-File Report 

2006–1093, 71 p. [Also available at https://www.fort.usgs.

gov/sites/default/files/products/publications/21598/21598.

pdf .]

House, P.K., and Hirschboeck, K.K., 1997, Hydroclimatological and paleohydrological context of extreme winter flooding 

in Arizona, 1993, in Larson, R.A., and Slosson, J.E., eds., 

Storm–induced geological hazards—Case histories from the 

1992–1993 winter storm in southern California and Arizona: 

Boulder, Colorado, Geological Society of America Reviews 

in Engineering Geology, v. XI, p. 1–24.

Hubbs, C., Edwards, R.J., and Garrett, G.P., 1991, An annotated checklist for the freshwater fishes of Texas, with keys 

to identification of species: The Texas Journal of Science, 

Supplement, v. 43, no. 4, p. 1–56.

Huete, A., Didan, K., Miura, T., Rodriguez, E.P., Gao, X., 

and Ferreira, L.G., 2002, Overview of the radiometric and 

biophysical performance of the MODIS vegetation indicies: 

Remote Sensing of Environment, v. 83, p. 195–213.
100 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

Jaeger, K.L., Olden, J.D., and Pelland, N.A., 2014, Climate 

change poised to threaten hydrologic connectivity and 

endemic fishes in dryland streams: Proceedings of the 

National Academy of Sciences, v. 111, no. 38, p. 13894-13899

Johnson, T.D., Kolb, T.E., and Medina, A.L., 2009, Do riparian plant community characteristics differ between Tamarix

(L.) invaded and non-invaded sites on the upper Verde River, 

Arizona?: Biological Invasions, v. 12, no. 8, doi: 10.1007/

s10530-009-9658-2, p. 2487–2497.

Kail, J., Arle, J., and Jahnig, S.C., 2011, Limiting factors and 

thresholds for macroinvertebrate assemblages in European 

rivers—Empirical evidence from three datasets on water quality, catchment urbanization, and river restoration: Ecological 

Indicators, v. 18, p. 63–72.

Kennen, J.G., Riva-Murray, K., and Beaulieu, K.M., 2010, 

Determining hydrologic factors that influence stream macroinvertebrate assemblages in the northeastern US: Ecohydrology 

v. 3, no. 1, p. 88–106. [Also available at http://onlinelibrary.

wiley.com/doi/10.1002/eco.99/full .]

Kirkpatrick, C., Conway, C.J., and LaRoche, D., 2008, Quantifying impacts of ground water withdrawal on avian communities in desert riparian woodlands of the southwestern U. 

S.: Department of Defense, Legacy Resource Management 

Program, Project 07–290, 48 p.

Klaar, M.J., Hill, D.F., Maddock, I. and Milner, A.M., 2011, 

Interactions between in stream wood and hydrogeomorphic 

development within recently deglaciated streams in Glacier Bay National Park, Alaska: Geomorphology, v. 130, p. 

208–220.

Klaar, M.J., Maddock, I. and Milner, A.M., 2009. The development of hydraulic and geomorphic complexity in recently 

formed streams in Glacier Bay National Park, Alaska: River 

Research and Applications, v. 25, p. 1331–1338.

Konrad, C.P., 2011, Environmental flow allocation and statistics calculator: U.S. Geological Survey Open-File Report 

2011–1166, 46 p. [Also available at https://pubs.usgs.gov/

of/2011/1166/ .]

Konrad, C.P., Black, B., Voss, F., and Neale, C., 2008a, Integrating remotely acquired and field data to assess effects of 

setback levees on riparian and aquatic habitats in glacialmelt water rivers: River Research and Application, v. 24, p. 

355–372.

Konrad C.P., Brasher, A.M.D., and May, J.T., 2008b, Assessing streamflow characteristics as limiting factors on benthic 

invertebrate assemblages in streams across the western 

United States: Freshwater Biology v. 53, p. 1983–1998.

Korman, J., Wiele, S.M., and Torizzo, M., 2004, Modeling 

the effect of discharge on habitat quality and dispersal of 

juvenile humpback chub (Gila cypha) in the Colorado River 

in Grand Canyon: River Research and Applications, v. 20, 

no. 4, p. 379–400.

Leake, S.A., Pool, D.R., and Leenhouts, J.M., 2008, Simulated 

effects of ground-water withdrawals and artificial recharge 

on discharge to streams, springs, and riparian vegetation 

in the Sierra Vista Subwatershed of the Upper San Pedro 

Basin, southeastern Arizona: U.S. Geological Survey Scientific Investigations Report 2008–5207, 14 p. [Also available 

at https://pubs.usgs.gov/sir/2008/5207/ .]

Lee, D.S., Gilbert, C.R., Hocutt, C.H., Jenkins, R.E., Callister, 

D.E., and Stauffer, J.R., eds., 1981, Atlas of North American freshwater fishes: Raleigh, N.C., North Carolina State 

Museum of Natural History, 854 p.

Lomnicky, G.A., Whittier, T.R., Hughes, R.M., and Peck, 

D.V., 2007, Distribution of nonnative aquatic vertebrates in 

western U.S. streams and rivers: North American Journal of 

Fisheries Management, v. 27, no. 4, p. 1082–1093.

Lowe, S., Browne, M., Boudjelas, S., and De Poorter, M., 

2000, 100 of the world’s worst invasive alien species a 

selection from the global invasive species database: The 

Invasive Species Specialist Group (ISSG), a specialist 

group of the Species Survival Commission (SSC) of the 

World Conservation Union (IUCN), 12 p. [Updated and 

reprinted version, November 2004, first published in Aliens 

12, December 2000.]

Lytle, D.A., and Poff, N.L., 2004, Adaptation to natural flow 

regimes: Trends in Ecology and Evolution, v. 190, p. 1–7.

Magoulick, D.A., 2000, Spatial and temporal variation in fish 

assemblages of drying stream pools—The role of abiotic 

and biotic factors: Aquatic Ecology, v. 34, p. 29–41.

Marder, M.K., 2009, The battle to save the Verde—How Arizona’s water law could destroy one of its last free-flowing 

rivers: Arizona Law Review, v. 51, no. 175, p. 175–210.

Matthews, W.J., and Styron, J.T., Jr., 1981, Tolerance of 

headwater vs. main-stream fishes for abrupt physiochemical 

changes: American Midland Naturalist, v. 105, p. 149–158.
References Cited 101

Meffe, G.K., 1984, Effects of abiotic disturbance on coexistence of predator-prey fish species: Ecology, v. 65, p. 

1525–1534. 

Miller, M.P., and Brasher, A.M.D., 2011, Differences in macroinvertebrate community structure in streams and rivers 

with different hydrologic regimes in the semi-arid Colorado 

Plateau: River Systems, v. 19, no. 3, p. 225–238.

Miller, R.R., Williams, J.D., and Williams, J.E., 1989, Extinctions of North American fishes during the past century: 

Fisheries, v. 14, no. 6, p. 22–48.

Minckley, W.L., and Meffe, G.K., 1987, Differential selection 

by flooding in stream-fish communities of the arid American 

Southwest, in Matthews, W.J., and Heins, D.C., eds., Community and evolutionary ecology of North American stream 

fishes: Norman, Okla., University of Oklahoma Press, p. 

93–104.

Minckley, W.L., 1973, Fishes of Arizona: Phoenix, Ariz., Arizona Game and Fish Department, p. 158–159.

Minckley, W.L., and Douglas, M.E., 1991, Discovery and 

extinction of western fishes—A blink of the eye in geologic 

time, in Minckley, W.L., and Deacon, J.E., eds., Battle 

against extinction—Native fish management in the American West: Tucson, Ariz., University of Arizona Press, p. 

7–17.

Minckley, W.L., and Marsh P.C., 2009, Inland fishes of the 

greater Southwest—Chronicle of a vanishing biota: Tucson, 

Ariz., University of Arizona Press, 426 p.

Moody, T., Wirtanen, M., and Yard, S.N., 2003Regional relationships for bankfull stage in natural channels of the arid 

southwest, Natural Channel Design, Inc. Flagstaff, AZ, 

38 p.

Moulton, S.R., II, Kennen, J.G., Goldstein, R.M., and Hambrook, J.A., 2002, Revised protocols for sampling algal, 

invertebrate, and fish communities as part of the National 

Water-Quality Assessment Program: U.S. Geological 

Survey Open-File Report 02–150, 75 p. [Also available at 

https://pubs.usgs.gov/of/2002/ofr-02-150/ .]

Moyle, P.B., and Light, T., 1996, Fish invasions in California—Do abiotic factors determine success?: Ecology, v. 77, 

no. 6, p. 1666–1670.

Nash, J.E., and J.V. Sutcliffe, 1970, River flow forecasting 

through conceptual models, part I—A discussion of principles: Journal of Hydrology, v. 10, no. 3, p. 282–290.

National Wild and Scenic Rivers System, 2016a, Fossil Creek, 

Arizona: National Wild and Scenic Rivers System website, 

accessed March 3, 2016, at http://www.rivers.gov/rivers/

fossil.php.

National Wild and Scenic Rivers System, 2016b, Verde River, 

Arizona: National Wild and Scenic Rivers System website, 

accessed March 3, 2016, at http://www.rivers.gov/rivers/

verde.php.

Neary, A.P., Rinne, J.N., and Neary, D.G., 1996, Physical 

habitat use by spikedace in the upper Verde River, Arizona: 

Hydrology and Water Resources in Arizona and the Southwest, v. 26, p. 23–28.

Nelson, K., 2002, Application of the Prescott Active Management Area Groundwater Flow Model Planning Scenario 

1999–2025, modeling report no.12: Arizona Department of 

Water Resources, 49 p.

Olden, J.D., 2006, Life-history strategies predict fish invasions and extirpations in the Colorado River Basin: Ecological Monographs, v. 76, no. 1, p. 25–40.

Pearthree, P.A., 1993, Geologic and geomorphic setting of the 

Verde River from Sullivan Lake to Horseshoe Reservoir: 

Arizona Geological Survey Open-File Report 93-04, 25 p. 

and 5 sheets, scale 1:24,000.

Pearthree, P.A., 1996, Historical geomorphology of the Verde 

River: Arizona Geological Survey Open-File Report 96-13, 

26 p.

Pearthree, P.A., 2008, Fluvial geomorphology and flood 

history of the Verde River, in Haney, J.A., Turner, D.S., 

Springer, A.E., Stromberg, J.C., Stevens, L.E., Pearthree, 

P.A., and Supplee, V., 1995, Ecological implications of 

Verde River flows— Arizona Water Institute, The Nature 

Conservancy, and the Verde River Basin Partnership, 114 p.

Peck, D.V., Herlihy, A.T., Hill, B.H., Hughs, R.M., 

Kaufmann, P.R., Klemm, D., Lazorchak, J.M., McCormick, 

F.H., Peterson, S.A, Ringold, P.L., Magee, T., and Cappaert, M., 2006, Environmental monitoring and assessment 

program-surface waters western pilot study—Field operations manual for wadeable streams: Washington, D.C., U.S. 

Environmental Protection Agency, EPA/620/R-06/003, 276 

p.

Poff, N.L., Allan, J.D., Bain, M.B., Karr, J.R., Prestegaard, 

K.L., Richter, B.D., Sparks, R.E., and Stromberg, J.C., 

1997, The natural flow regime: Bioscience, v. 47, no. 11, p. 

769–784.

Poff, N.L., Olden, J.D., Merritt, D.M., and Pepin, D.M., 

2007, Homogenization of regional river dynamics by 

dams and global biodiversity implications: Proceedings 

of the National Academy of Sciences, v. 104, no 14, p. 

5732–5737.
102 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

Poff, N.L., Richter, B.D., Arthington, A.H., Bunn, S.E., 

Naiman, R.J., Kendy, E., Acreman, M., Apse, C., Bledsoe, B.P., Freeman, M.C., Henriksen, J., Jacobson, R.B., 

Kennen, J.G., Merritt, D.M., O’Keeffe, J.H., Olden, J.D., 

Rogers, K., Tharme, R.E., and Warner, A., 2010, The ecological limits of hydrologic alteration (ELOHA)—A new 

framework for developing regional environmental flow 

standards: Freshwater Biology, v. 55, no. 1, p. 147–170.

Pool, D.R., Blasch, K.W., Callegary, J.B., Leake, S.A., and 

Graser, L.F., 2011, Regional groundwater-flow model of 

the Redwall-Muav, Coconino, and alluvial basin aquifer 

systems of northern and central Arizona: U.S. Geological Survey Scientific Investigations Report 2010–5180, 

v. 1.1, 101 p. [Also available at https://pubs.usgs.gov/

sir/2010/5180/ .]

Power, M.E, Stout, R.J., Cushing, C.E., Harper, P.P., Hauer, 

F.R., Matthews, W.J., Moyle, P.B., Statzner, B., and Wais 

De Badgen, I.R., 1988, Biotic and abiotic controls in river 

and stream communities: Journal of the North American 

Benthological Society, v. 7, no. 4, p. 456–479.

Power, M.E., 1984, Depth distributions of armored catfish—

Predator-induced resource avoidance: Ecology, v. 65, no. 2, 

p. 523–528.

Propst, D.L., and Gido, K.B., 2004, Responses of native and 

non-native fishes to natural flow regime mimicry in the San 

Juan River: Transactions of the American Fisheries Society, 

v. 122, p. 922–931.

Prudic, D.E., Konikow, L.F., and Banta, E.R., 2004, A new 

stream-flow routing (SFR1) package to simulate streamaquifer interaction with MODFLOW-2000: U.S. Geological Survey Open-File Report 2004–1042, 104 p., accessed 

June 26, 2017, at https://pubs.usgs.gov/of/2004/1042/.

Rees, D.E., Ptacek, J.A., and Miller, W.J., 2005, Roundtail 

chub (Gila robusta)—A technical conservation assessment: U.S. Department of Agriculture Forest Service, 

Rocky Mountain Region, 26 p., accessed April 21, 2012, 

at https://www.fs.usda.gov/Internet/FSE_DOCUMENTS/

stelprdb5206785.pdf.

Reynolds, J.B., 1983, Electrofishing, in Nielsen, L.A., and 

Johnson, D.L., eds., Fisheries techniques: Bethesda, Md., 

American Fisheries Society, p. 147–163.

Richter, B.D., Baumgartner, J.V., Powell, Jennifer, and Braun, 

D.P., 1996, A method for assessing hydrologic alteration 

within ecosystems: Conservation Biology, v. 10, no. 4, p. 

116–1174.

Richter, B.D., Mathews, R., Harrington, D.L., and Wigington, 

R., 2003, Ecologically sustainable water management—

Managing river flows for ecological integrity: Ecological 

Applications, v. 13, p. 206–224.

Richter, B.D., Warner, A.T., Meyer, J.L., and Lutz, K., 2006, A 

collaborative and adaptive process for developing environmental flow recommendations: River Research Applications, v. 22, p. 297–318.

Rinne, J.N., 1989, Physical habitat use by loach minnow, 

Tiagroa cobitis (Pisces: Cyrinidae), in southwestern desert 

streams: Southwestern Naturalist, v. 34, no. 1, p. 109–117.

Rinne, J.N., 1992, Physical habitat utilization of fish in a 

Sonoran Desert stream, Arizona, southwest United States: 

Ecology of Freshwater Fish, v. 1, p. 35–41.

Rinne, J.N., 2005, Changes in fish assemblages, Verde River, 

Arizona, 1974–2003: American Fisheries Society Symposium, v. 45, p. 115–126. 

Rinne, J.N., and Janisch, J., 1995, Coldwater fish stocking and 

native fishes in Arizona—Past, present and future: American 

Fisheries Society Symposium, v. 15, p. 397–406.

Rinne, J.N., and Miller, D., 2006, Hydrology, geomorphology 

and management—Implications for sustainability of native 

southwestern fishes: Reviews in Fisheries Science, v. 14, p. 

91–110.

Rinne, J.N., and Minckley, W.L., 1991, Native fishes of arid 

lands—A dwindling resource of the desert southwest: U.S. 

Forest Service General Technical Report RM-206, 45 p.

Rosgen, D.L., 1996, Applied River Morphology: Pagosa 

Springs, Colo., Wildland Hydrology, Inc., 378 p.

Ross, R., Springer, A.E., and Schlinger, C., 2010, Verde Valley 

hydraulic model project: Report to Yavapai County Water 

Advisory Committee, 51 p.

Ross, S.T., Matthews, W.J., and Echelle, A.A., 1985, Persistence of stream fish assemblages—Effects of environmental 

change: American Naturalist, v. 126, p. 24–40.

Ruppert, J.B., Muth, R.T., and Nesler, T.P, 1993, Predation on 

fish larvae by adult red shiner, Yampa and Green Rivers, 

Colorado: The Southwestern Naturalist, v. 38, no. 4, p. 

397–399.

Schade, C.B., and Bonar, S.A., 2005, Distribution and abundance of non-native fishes in streams of the western United 

States: North American Journal of Fisheries Management, v. 

25, no. 4, p. 1386–1394.

Schlosser, I.J., 1982, Fish community structure and function 

along two habitat gradients in a headwater stream: Ecological Monographs, v. 52, p. 395–414.

Scott, M.L., Shafroth, P.B., and Auble, G.T., 1999, Responses 

of riparian cottonwoods to alluvial water table declines: 

Environmental Management, v. 23, no. 3, doi: 10.1007/

s002679900191, p. 347–358.
References Cited 103

Shafroth, P.B., Auble, G.T., Stromberg, J.C., and Patten, D.T., 

1998, Establishment of woody riparian vegetation in relation to annual patterns of streamflow, Bill Williams River, 

Arizona: Wetlands, v. 18, no. 4, p. 577–590.

Shafroth, P.B., Brown, C.A., and Merritt, D.M., 2010a, Saltcedar and Russian Olive control demonstration act science 

assessment: U.S. Geological Survey Scientific Investigations 

Report 2009–5247, 143 p. [Also available at https://pubs.

usgs.gov/sir/2009/5113/ .]

Shafroth, P.B., Stromberg, J.C., and Patten, D.T., 2000, Woody 

riparian vegetation response to different alluvial water table 

regimes: Western North American Naturalist, v. 60, no. 1, p. 

66–76.

Shafroth, P.B., Wilcox, A.C., Lytle, D.A., Hickey, J.T., Andersen, D.C., Beauchamp, D.C., Hautzinger, A., McMullen, 

L.E., and Warner, A., 2010b, Ecosystem effects of environmental flows: Modeling and experimental floods in a dryland 

river: Freshwater Biology, v. 55, no. 1, p. 68–85.

Spencer, D.F., 2012, Response of Arundo donax L. (giant reed) 

to leaf damage and partial defoliation: Journal of Freshwater 

Ecology, v. 27, no. 1, p. 77–87.

Spindler, P.H., and Paretti, N.V., 2009, A Comparison of 

macroinvertebrate and habitat methods of data collection in 

the Little Colorado River watershed, Arizona 2007: Arizona 

Department of Environmental Quality, 48 p.

Spindler, P.H., 2001, Macroinvertebrate community distribution among reference sites in Arizona: Arizona Department of 

Environmental Quality Open-File Report 00–05, 20 p.

Springer, A.E., and Haney, J.A., 2008, Hydrology of the 

upper and middle Verde River, in Haney, J.A., Turner, D.S., 

Springer, A.E., Stromberg, J.C., Stevens, L.E., Pearthree, 

P.A., and Supplee, V., Ecological implications of Verde River 

flows: Arizona Water Institute, The Nature Conservancy, and 

the Verde River Basin Partnership, 114 p.

Stevens, L.E., Turner, D.S., and Supplee, V., 2008, Wildlife and 

flow relationships in the Verde River watershed, chap. 5 of

Ecological implications of Verde River flows: Arizona Water 

Institute, The Nature Conservancy, and the Verde River Basin 

Partnership, p. 51–70.

Stromberg, J.C., 1993, Fremont cottonwood-Goodding willow riparian forests—A review of their ecology, threats, and 

recovery potential: Journal of the Arizona-Nevada Academy 

of Science, v. 27, no. 1, p. 97–110.

Stromberg, J.C., 2008, Stream flow regimes and riparian vegetation of the Verde River, chap. 4 of Ecological implications of 

Verde River flows: Arizona Water Institute, The Nature Conservancy, and the Verde River Basin Partnership, p. 33–50.

Stromberg, J.C., Lite, S.J., Marler, R., Paradzick, C., Shafroth, 

P.B., Shorrock, D., White, J.M., and White, M.S., 2007, 

Altered stream-flow regimes and invasive plant species—

The Tamarix case: Global Ecology and Biogeography, v. 16, 

p. 381–393.

Stromberg, J.C., Tiller, R., and Richter, B., 1996, Effects of 

groundwater decline on riparian vegetation of semiarid 

regions—The San Pedro, Arizona: Ecological Applications, 

v. 6, no. 1, p. 113–131, doi: 10.2307/2269558.

Terrell, J.W., Cade, B.S., Carpenter, Jeanette, and Thompson, J.M., 1996, Modeling stream fish habitat limitations 

from wedge-shaped patterns of variation in standing stock: 

Transactions of the American Fisheries Society, v. 125, p. 

104–117.

The Nature Conservancy, 2009, Verde River watershed conservation plan: Tucson, Ariz., The Nature Conservancy, 50 p.

Timmons, D., and Springer, A.E., 2006, Prescott AMA groundwater flow model update report: Northern Arizona University, prepared for Arizona Department of Water Resources 

final report, 77 p.

U.S. Army Corps of Engineers, 2018, HEC-RAS [Hydrologic 

Engineering Center’s River Analysis System]: U.S. Army 

Corps of Engineers website, accessed February 23, 2018, at 

https://www.hec.usace.army.mil/software/hec-ras/.

U.S. Environmental Protection Agency and the U.S. Geological Survey, 2006, The National Hydrography Dataset 

Plus—NHDPlus, version 1.0: U.S. Environmental Protection 

Agency and the U.S. Geological Survey, accessed November 

2011 at http://www.horizon-systems.com/nhdplus/index.php.

Wang, L., Lyons, J., and Kanehl, P., 2003, Impacts of urban 

land cover on trout streams in Wisconsin and Minnesota: 

Transactions of the American Fisheries Society, v. 132, p. 

825–839.

Wang, L., Robertson, D.M., Garrison, P.J., 2007, Linkages 

between nutrients and assemblages of macroinvertebrates 

and fish in wadeable streams—Implication to nutrient 

criteria development: Environmental Management, v. 39, p. 

194–212.

Webb, R.H., Leake, S.A., and Turner, R.M., 2007, The ribbon 

of green—Change in riparian vegetation in the southwestern United States: Tucson, Ariz., The University of Arizona 

Press, 462 p.

Whittier, T.R., and Peck, D.V., 2008, Surface area estimates of 

streams and rivers occupied by nonnative fish and amphibians in the western USA: North American Journal of Fisheries Management, v. 28, no. 6, p. 1887–1893.
104 Preliminary Synthesis and Assessment of Environmental Flows in the Middle Verde River Watershed, Arizona

Wiele, S.M., and Torizzo, M., 2005, Modeling of sand deposition in archeologically significant reaches of the Colorado 

river in Grand Canyon, USA, in Bates, P.D., Lane, S.N., and 

Ferguson, R.I., eds., Computational fluid dynamics—Applications in environmental hydraulics: Hoboken, N.J., John 

Wiley and Sons, Ltd., p. 357–394.

Wiele, S.M., Brasher A.M.D., Miller, M.P., May J.T., and 

Carpenter, K.D., 2012, Biotic, water-quality, and hydrologic metrics calculated for the analysis of temporal trends 

in National Water Quality Assessment Program data in the 

western United States: U.S. Geological Survey Open-File 

Report 2012–1203, 11 p. and data tables. [Also available at 

https://pubs.usgs.gov/of/2012/1203/ .]

Wiele, S.M., Wilcock, P.R., Grams, P.E., 2007, Reachaveraged sediment routing model of a canyon 

river: Water Resources Research, v. 43, 16 p., doi: 

10.1029/2005WR004824.

Williams, A.P., Allen, C.D., Millar, C.I., Swetnam, T.W., 

Michaelsen, Joel, Still, C.J., and Leavitt, S.W., 2010, 

Forest responses to increasing aridity and warmth 

in southwestern North America: Proceedings of the 

National Academy of Sciences of the United States of 

America, v. 107, no.50, p. 21289–21294. [Also available at http://www.pnas.org/ content/107/50/21289.full.

pdf+html.]
Menlo Park Publishing Service Center, California

Manuscript approved for publication September 7, 2017

Edited by James W. Hendley II

Layout and design by Vivian Nguyen
Paretti and others—Preliminary Synthesis and Assessment of Environmental Flows, Middle Verde River Watershed, Arizona—Scientific Investigation Report 2017–5100

ISSN 2328-0328 (online)

http://dx.doi.org/10.3133/sir20175100

Desert sucker (Catostomus clarki) from West Clear Creek, a tributary to the Verde River