A STUDY OF HYDROLOGIC RESPONSE TO THE RESTORATION OF

TROUT CREEK, CENTRAL SIERRA NEVADA, CALIFORNIA

________________

A Thesis

Presented to the

Faculty of

San Diego State University

________________

In Partial Fulfillment

of the Requirements for the Degree

Masters of Science

in

Geography

________________

by

Scott Alexander Valentine

Fall 2006

SAN DIEGO STATE UNIVERSITY

The Undersigned Faculty Committee Approves the

Thesis of Scott Alexander Valentine:

A Study of Hydrologic Response to the Restoration of Trout Creek, Central Sierra

Nevada, California

______________________________________________Christina Tague, Chair

Geography

______________________________________________Sergio J. ReyGeography

______________________________________________Helen Regan

Ecology_______________________________

Approval Date

Copyright © 2006

by

Scott Alexander Valentine

All Rights Reserved

iii

DEDICATION

I would like to thank Dr. Betsy Julian for leading me back to school, for sharing her

enthusiasm of outdoor learning opportunities, for teaching me how to teach, and most

importantly I genuinely thank her for being an incredible mentor and friend.

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ABSTRACT OF THE THESIS

A Study of Hydrologic Response to the Restoration of Trout Creek, Central Sierra Nevada, California

byScott Alexander Valentine

Masters of Science in GeographySan Diego State University, 2006

Anthropogenic activities and poor land use management practices in riparian and aquatic ecosystems have altered flow regimes, causing ecologic damage and natural resource degradation throughout much of the United States. The importance of intact, functioning, and self-sustaining ecosystems has lead resource managers to seek out environmental solutions such as ecologic restoration. The reestablishment of hydrologic and ecologic processes is now seen as a primary goal of modern restoration science. Restoration methods involving channel modifications have been known to improve ecologic elements, but there has been little published research, as to how restoration influences hydrologic processes and flow regimes in these sensitive environments.

The restoration of Trout Creek provides an opportunity to study streamflow responses following the restoration of a 10,000-foot stream segment in Lake Tahoe, California. The proposed research will investigate (1) how streamflow hydrograph characteristics below the Trout Creek restoration site have been affected by restoration and (2) whether the relationship between groundwater and streamflow below the site has changed as a result of these ecosystem improvements. Streamflow gages located above and below the site, groundwater well monitoring data, and meteorological data collected before and after restoration will provide the necessary information needed to analyze the pre and post restoration flow regime.

Using methods that help to remove the variability caused by climate, sets of different hydrologic-based metrics will be estimated, and differences before and after restoration will be examined and tested for statistical significance. Pre-restoration data, and data derived from snowpack and the stream gage above the restoration site will be used to help build the regression models that will evaluate differences between predicted and observed datasets. The hydrograph characteristics that will be analyzed will include annual peak flow, August and September baseflow totals, and the minimum 7-day running average for August and September, and the mean slope of the hydrograph recession limb. A graphical analysis of groundwater and streamflow data will also help to visually evaluate the changes caused by restoration.The information gathered from this analysis will help researchers understand how channel modifications affect flow regimes in aquatic and riparian environments. This type of research will help to explain how ecosystems respond to restoration, but more importantly, this study may also provide the insight needed to broaden the scientific understanding of hydrologic and ecologic processes in riverine environments. An increase in research and reporting in

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restoration science will serve to advance the field, and contribute to the success of future restorations.

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TABLE OF CONTENTS

PAGE

ABSTRACT...............................................................................................................................v

LIST OF TABLES.................................................................................................................viii

LIST OF FIGURES..................................................................................................................ix

ACKNOWLEDGEMENTS......................................................................................................xi

CHAPTER

INTRODUCTION...................................................................................................1

Background Leading to the Hydrologic Analysis of Trout Creek...............2

Hydrologic Processes.............................................................................4

Alteration of the Flow Regime........................................................4

Restoration of the Flow Regime......................................................5

The Restoration of Trout Creek.............................................................6

Hydrologic Analysis............................................................................10

Research Questions and Hypotheses.........................................................11

METHOD OF STUDY..........................................................................................13

Data Collection and Sampling Strategy.....................................................13

Analysis and Statistical Tests.....................................................................14

Assumptions and Limitations....................................................................16

Data Adjustments.......................................................................................18

RESULTS AND DISCUSSION............................................................................19

Research Question #1................................................................................19

Hypothesis #1.......................................................................................19

Annual Peak Discharge..................................................................19

August and September Baseflow Totals........................................21

Minimum 7-Day Running Average Discharge for August and September......................................................................................24

Hypothesis #2.......................................................................................26

Hypothesis #3.......................................................................................29

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Research Question #2................................................................................30

Hypothesis #4.......................................................................................31

SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS FOR FUTURE RESEARCH AND MANAGEMENT.............................................................39

Summary of Findings.................................................................................39

Conclusions................................................................................................40

Research Recommendations......................................................................42

Management Recommendations................................................................43

REFERENCES............................................................................................................44

APPENDIX A..............................................................................................................48

DATES AND VALUES FOR MISSING SNOW DEPTH DATA.......................48

APPENDIX B..............................................................................................................50

RESULTS OF THE SHAPIRO-WILK TEST FOR NORMALITY.....................50

APPENDIX C..............................................................................................................52

LINEAR MODEL RESULTS AND R2 VALUES................................................52

APPENDIX D..............................................................................................................54

TYPE OF TESTS APPLIED AND RESULTS OF STATISTICAL SIGNIFICANCE..............................................................................................54

APPENDIX E..............................................................................................................56

Additional Figures.................................................................................................56

viii

LIST OF TABLES

PAGE

Table 1. Peak Discharge for Each Water Year at Upper and Lower Gages................20

Table 2. Well Location Information............................................................................34

Table 3. Analysis of Wells Located Between Old and New Channel Alignments......35

ix

LIST OF FIGURES

PAGE

Figure 1. Location map of Trout Creek.........................................................................8

Figure 2. Trout Creek Meadow before restoration........................................................9

Figure 3. Trout Creek Meadow after restoration...........................................................9

Figure 4. Graph depicting the peak discharge relationship between upper and lower gages for before and after restoration periods. Trend lines were not applied because one or more datasets were not normally distributed..........................21

Figure 5. Graphs showing the relationship between upper and lower gages during before and after restoration periods for August and September baseflow totals.22

Figure 6. Boxplots of observed baseflow totals for before and after restoration periods in August and September.................................................................................23

Figure 7. Boxplots of before and after restoration error differences for August and September baseflow totals...............................................................................24

Figure 8. Graph showing the relationship between upper and lower gages during before and after restoration periods for the minimum seven-day running average discharge in August and September...................................................25

Figure 9. Boxplots of observed minimum seven-day running average discharge totals in August and September for before and after restoration periods..................25

Figure 10. Boxplots of before and after restoration error differences for the minimum seven-day running average for August and September discharges.................26

Figure 11. Graph showing the mean slope of the hydrograph recession limb for each water year. Trend lines were not applied because one or more datasets were not normally distributed...................................................................................28

Figure 12. Boxplots of the mean slope of the hydrograph recession limb before and after restoration................................................................................................28

Figure 13. Graph depicting the relationship between the annual peak 15 day running average for snow depth and the minimum 15 day running average streamflow discharge during before and after restoration periods at the lower gage for each water year. Trend lines were not applied because one or more datasets were not normally distributed..........................................................................30

Figure 14. Bar graph showing the before and after restoration distribution of groundwater depth to discharge correlation coefficients for before and after restoration periods............................................................................................32

x

Figure 15. Map showing groundwater well locations and pre and post restoration stream alignments............................................................................................33

Figure 16. Graph showing the before and after restoration distribution of groundwater depth to discharge correlation coefficients and distance to the channel..........35

Figure 17. Graphs showing the before and after restoration distribution of groundwater depth to discharge for before and after restoration periods. This cluster of graphs depicts wells located between the old channel and the new channel, where distance to the channel decreased after restoration.................37

Figure 18. Graphs showing the before and after restoration distribution of groundwater depth to discharge for before and after restoration periods. This cluster of graphs depicts wells located between the old channel and the new channel, where distance to the channel increased after restoration.................38

Figure 19. Boxplots of relative before and after restoration differences for August and September baseflow totals...............................................................................57

Figure 20. Boxplots showing a ratio of before and after restoration differences for August and September baseflow totals............................................................57

Figure 21. Boxplots of relative before and after restoration differences for the minimum seven-day running average for August and September baseflows..58

Figure 22. Boxplots showing a ratio of before and after restoration differences for the minimum seven-day running average for August and September baseflow.. .58

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ACKNOWLEDGEMENTS

First I would like to thank Dr. Christina Tague for providing the invaluable support

and guidance that was necessary for the completion of this project. I would also like to thank

my other committee members, Dr. Sergio Rey and Helen Regan for their comments and

suggestions. I would like to acknowledge Russell Wigart at the City of South Lake Tahoe,

Matt Kiesse at River Run Consulting, Dr. Jon Warrick at the USGS, Swanson Hydrology and

Geomorphology, the UC Berkeley Central Sierra Snow Lab, and the Ecosystem Restoration

Department at the US Forest Service’s Lake Tahoe Basin Management Unit for the copious

amounts of data and advise need to make this thesis a success. Finally, I would like to thank

my family, friends, and the faculty and staff in the Geography Department at San Diego State

University.

xii

CHAPTER 1

INTRODUCTION

Human impacts and management strategies over the last several centuries have

played a role in the degradation of natural resources throughout the United States. Riparian

environments in particular have been subject to overgrazing, stream channelization and

fragmentation (NRC 1992, Kauffman et al. 1997). Along with bank erosion and diminished

habitat and water quality, mismanagement has often altered hydrologic processes affecting

groundwater levels and streamflows (Poff et al. 1997). Water level fluctuations in stream

environments can play a critical role in determining riparian ecosystem structure and function

(Ward et al. 2002). To help prevent further natural resource degradation, ecological

restoration is now being explored as a way to counteract the damages inflicted by human

activities.

The National Research Council (1992) defines restoration as “the return of an

ecosystem to a close approximation of its natural condition prior to disturbance” while

maintaining “a functioning, self-regulating, system that is integrated with the ecological

landscape in which it occurs.” Hydrologic process has now been recognized as a critical

element in maintaining ecologic function in natural and restored environments (Kauffman et

al. 1997, Poff et al. 1997, NRC 1992). This type of process-based restoration is slowly

replacing older methods involving structural engineering and simple habitat enhancement,

which no longer meet restoration criteria (Goodwin, Hawkins, and Kershner 1997, NRC

1992). The growth and evolution of restoration science is being fueled by an increasing

understanding of ecosystem processes, but restoration science, as with any emergent field, is

presented with a variety of obstacles and limitations (Palmer et al. 2005, Kauffman et al.

1997, Poff et al. 1997, Goodwin, Hawkins, and Kershner 1997). Although the primary goal

of ecologic restoration is to return an ecosystem to its natural condition, it may be impossible

to fully recreate physical, chemical, and biologic processes (NRC 1992). Extreme variability

in hydrologic and climatic processes coupled with inadequate monitoring, infrequent

reporting, and the relatively low number of adequate sites has directly affected the amount of

1

scientific information available for restoration research (Moerke and Lamberti 2004). An

increase in research and reporting in restoration science would contribute to a broader

understanding in the field and serve to benefit future restoration projects.

The Trout Creek Stream Restoration and Wildlife Enhancement Project in Lake

Tahoe, California provides researchers a unique opportunity to study ecosystem responses to

restoration. Upon its completion in 2001, the Trout Creek Stream Restoration and Wildlife

Enhancement Project had reconstructed over 10,000 channel feet of stream, enhanced

sinuosity, and raised the channel bed to address ecologic concerns. At this point, it is still

unclear how streamflows below the site have been affected by restoration. An analysis of

streamflow, groundwater measurements, and meteorological data will help explain how

Trout Creek has responded to restoration. This study will also provide insight to future

restoration projects and enhance the understanding of ecosystem processes in their response

to restoration. This research will investigate (1) how streamflow hydrograph characteristics

below the Trout Creek restoration site have been affected by the prescribed restoration, and

(2) whether the relationship between groundwater and streamflow below the site has changed

as a result of this management activity.

BACKGROUND LEADING TO THE HYDROLOGIC ANALYSIS OF TROUT CREEK

Population increases and intensified development throughout the United States has

lead to extensive ecologic degradation of the nation’s riparian and aquatic resources (NRC

1992). It has been estimated that 70%-90% of all natural riparian areas in the United States

have been extensively altered (Kauffman et al. 1997). It is now recognized that the utilization

of rivers, riparian zones, and wetlands has come at great environmental, social, and economic

cost (Poff et al. 1997). Land use practices such as agricultural, mining, livestock grazing,

channelization, timber harvesting, dredging, and other forms of water diversion and

development have extensively altered the state of aquatic resources (NRC 1992). These

management decisions have disrupted the physical, chemical, and biological processes within

riparian and aquatic ecosystems. These decisions have often resulted in more frequent and

intense flooding, contributed to a decline in water quality, and degraded or reduced habitat

for fish and wildlife, groundwater recharge capabilities, aesthetic values, and other beneficial

water uses including drinking, swimming, and fishing (NRC 1992). The resulting decreases

2

in diversity, function, and productivity of riparian and aquatic environments have limited

their future integrity, value, and use (Kauffman et al. 1997).

The degradation of aquatic and riparian environments have raised important societal

concerns since these environments are among the nation’s most highly valued, yet highly

threatened natural ecosystems (Ward et al. 2002, Goodwin, Hawkins, and Kershner 1997,

Kauffman et al. 1997, Poff et al. 1997, NRC 1992). Riparian and aquatic ecosystems are

ecologically important for their ability to attenuate floods, purify water, recycle nutrients,

augment and maintain streamflow, recharge ground water, and provide habitat for wildlife

and recreation for people (NRC 1992). The use and management of rivers, riparian zones,

and wetlands throughout history has contributed to the social well-being and material wealth

of society and there is broad social and political support for maintaining the economic

viability of aquatic resources and an increasing interest in protecting intrinsic values,

ecologic integrity, and the self-sustaining productivity of these ecosystems (Kauffman et al.

1997, Poff et al. 1997). There is a clear interest today in riparian issues and the proper

management of riparian ecosystems as a response to the degraded status of our nation’s

aquatic resources (Goodwin, Hawkins, and Kershner 1997).

Solutions such as ecological restoration are now being used to mitigate some of the

past degradation of these ecosystems (Palmer et al. 2005, Moerke and Lamberti 2004, Ward

et al. 2002, Goodwin, Hawkins, and Kershner 1997, Kauffman et al. 1997, Poff et al. 1997,

NRC 1992). Categories of restoration have varied in scope from bank stabilization to fish

reintroduction to water quality improvement. Ecological restoration, however, is viewed by

many as the reestablishment of processes, functions, and related biological, chemical, and

physical linkages in an ecosystem to a close approximation of their original condition prior to

disturbance (Kauffman et al. 1997, NRC 1992). There is an important distinction between

this view of process-based restoration and restoration philosophies of the 1970s, 80s, and

90s, which often times emphasized simple habitat enhancement or the restoration of one

environmental component (Palmer et al. 2005). The fundamental element of Pprocess-based

restoration is dependent upon a firm understanding of the processes that create and maintain

riparian ecosystems (Goodwin, Hawkins, and Kershner 1997, Poff et al. 1997).

3

Hydrologic ProcessesHydrology is arguably the most important process regulating the ecologic integrity of

riparian and aquatic ecosystems (Ward et al. 2002, Malard et al. 2002, Poff et al. 1997). The

existence of these (often highly specialized) environments is largely dependent upon the

natural dynamic character of regional hydrologic processes (Ward et al. 2002). Studies have

shown that surface and subsurface waters are linked through the continuous exchange of

water, nutrients, organic matter, and organisms (Malard et al. 2002, Woessner 2000). Spatial

and temporal variability in the hydrologic cycle leads to differences in flow duration,

frequency, magnitude, and discharge timing, ultimately affecting surface and subsurface

hydrologic exchanges. In areas with highly seasonal climates, spring peak flows, low

summertime flows, and the rate of surface and groundwater attenuation can dictate habitat

type and structure in riparian environments (Malard et al. 2002, Smakhtin 2000). Peak flows

are typically responsible for transporting sediment and organic matter through the channel

thereby affecting the stream’s morphologic and biological community structure (Poff et al.

1997). Low summertime baseflows, predominantly supported by groundwater sources, help

to support aquatic and terrestrial flora and fauna during drier months (Smakhtin 2000). The

rate of streamflow attenuation (often described by the slope of the hydrograph recession) can

also affect riparian community structure by influencing seedling germination, rooting depth,

and the length of the growing season for plants (Ward et al. 2002, Poff et al. 1997). The

preservation of the natural flow regime is important in maintaining the processes that support

biodiversity in riparian and aquatic ecosystems, but unfortunately, anthropogenic activities

commonly disrupt the natural flow regime, altering habitat dynamics, frequently creating

conditions to which native biota may be poorly adapted (Malard et al. 2002, Ward et al.

2002, Smakhtin 2000, Poff et al. 1997, Riggs 1972).

ALTERATION OF THE FLOW REGIME

There are natural inter and intra annual variations in flow regimes, but flow regimes

and hydrograph elements such as peak flow, baseflow, and streamflow attenuation have been

shown to be sensitive to human disturbances (Poff et al. 1997). Channel modification is one

of the most common ways humans impact the flow regime (NRC 1992). Channel alterations

for flood control, grazing, agriculture, timber harvesting, and urbanization are the primary

4

causes of alterations of flow regimes (Poff et al. 1997, NRC 1992). Slight changes in channel

morphology can result in floodplain isolation, channel incision, and bank instability (NRC

1992). Morphological changes such as these play a role in increasing flood intensities,

altering streamflow recession rates, and even prompting the reduction of baseflows during

dryer periods (Poff et al. 1997). High flows in confined channels rapidly erode banks and

channel bottoms further confounding the problem and further altering the flow regime.

Channel incision reduces the frequency of overbank flows and also reduces baseflows by

lowering the local water table to the point of incision (Poff et al. 1997). It may take centuries

for hydrologic and morphologic equilibrium to be attained in these altered environments, and

in many cases, physical restoration may be the only way for these degraded ecosystems to

recover (Poff et al. 1997).

RESTORATION OF THE FLOW REGIME

If degraded ecosystems are not resilient enough to recover on their own, physical

restoration methodologies may have to be employed. Many restoration scientists support the

notion that enhanced geomorphic form brings enhanced hydrologic function (LTBMU 2004,

SHG 2004, Lindquist and Wilcox 2000, Hillman 1998, De Laney 1995). Since flow regimes

are altered by morphologic disturbances it is assumed that positive channel modifications

will also yield positive effects on the flow regime (LTBMU 2004, SHG 2004, Lindquist and

Wilcox 2000, Hillman 1998, Poff et al. 1997, De Laney 1995, NRC 1992). Preliminary

studies in some stream and meadow restoration projects have indicated that reengineered

channels, which successfully raise groundwater levels and reconnect with their floodplains,

exhibit extended periods of discharge following snowmelt periods (SHG 2004, Lindquist and

Wilcox 2000). These studies have also shown that channel modifications, resulting from

restoration, have been able to moderate the magnitude and duration of peak flow events and

reduce seasonal ground water fluctuations (SHG 2004, Lindquist and Wilcox 2000).

Although the effects of restoration on the flow regime appear promising, there are

some inherent difficulties in restoring natural hydrologic processes. Researchers attempting

to restore and enhance hydrologic functions have limited information to assist them

(Woessner 2000). Advanced ecologic research is needed to increase the breadth of

knowledge required to properly restore riverine environments. The availability of scientific

5

information is scarce, and a literature review by Goodwin, Hawkins, and Kershner (1997),

found that restoration science is “hindered by one obvious fact: there have been few true

restorations.” Moerke and Lamberti (2004) also point out that even if proper restoration

techniques are being implemented, few are being studied, evaluated, or even reported. The

relatively small amount of literature available in the field of restoration science is mainly

dominated by studies which focus on the effects of urbanization, species recovery, or habitat

enhancement (Walsh, Fletcher, and Ladson 2005, Martin and Chambers 2002, Budelsky and

Galatowitsch 2000). There is even less literature involving restoration and hydrologic

recovery following channel modification (Moerke and Lamberti 2004, Goodwin, Hawkins,

and Kershner 1997, NRC 1992). Which is why, in this proposal, the analysis of streamflow

characteristics following the restoration of Trout Creek will provide useful information to

resource managers and researchers in the field of restoration science.

The Restoration of Trout CreekTrout Creek, located in South Lake Tahoe, California is one of the largest tributaries

feeding Lake Tahoe. Over the last century channelization, logging, grazing, and urbanization,

once seen as common land-use practices in California, have resulted in the degradation of

habitat and water quality in the Trout Creek watershed and the entire Lake Tahoe Basin.

Reclamation practices during the Comstock era of California’s development, from the 1860s

to the early1900s, lead to the impairment of stream channels and floodplain environments

throughout Lake Tahoe. The reduced function of floodplains as filters and the increase in

transport rates of sediment and nutrients to the lake have been recognized as a significant

contributing factor to the steady decline in lake clarity over the last few decades (SHG 2004).

During the Comstock era, Trout Creek was straightened and deepened in order to control

drainage for the timber industry and provide irrigation for cattle grazing. The change

effectively shortened and steepened the stream reach, leaving it susceptible to increased flow

velocities and erosive forces (SHG 2004, Goodwin, Hawkins, and Kershner 1997). As a

result of increased erosion the channel grew wider, deeper, and more isolated from its

floodplain leading to the impairment of habitat, water quality, and the desiccation of the

meadow as the local water table dropped (SHG 2004). In 2001, the City of South Lake Tahoe

6

restored a significant portion of the Trout Creek Meadow (Figure 1) to enhance habitat and

restore natural geomorphic form and process to the stream and its floodplain.

Upon completion, the Trout Creek Stream Restoration and Wildlife Enhancement

Project had reconstructed over 10,000 channel feet of stream. The channel design enhanced

sinuosity, modified riffle/pool morphology, and raised the channel bed in an attempt to

reestablish hydrologic connectivity between the steam and its former floodplain (SHG 2004).

(Figures 2 and 3 show before and after photos of meadow restoration at the Trout Creek

Site.) As a result of these efforts there have been documented ecologic improvements

including increases to invertebrate and fish populations, an increased in productivity of

meadow vegetation, and improvements to aquatic and riparian habitats (SHG 2004, Wigart

2004). Although there have been substantial studies to support these findings of ecologic

improvement in Trout Creek, there has been no analysis regarding streamflow characteristics

or the relationship between groundwater and streamflow following restoration. The study

proposed here will analyze the post-restoration effects on peak flow and baseflow conditions,

streamflow attenuation, and changes to the surface and subsurface hydrologic relationship.

This type of analysis has yet to be done on a restoration project of this nature.

Although there has been a lack of hydrologic analysis following the restoration of

Trout Creek, there is evidence to suggest that this type of channel modification has altered

the flow regime below the restoration site (LTBMU 2004, SHG 2004, Lindquist and Wilcox

2000, Hillman 1998, De Laney 1995, NRC 1992). Channel geometry has been restored to

Trout Creek, and the enhanced channel width, depth, slope, sinuosity, and riffle/pool

characteristics have been created to (1) raise the overall water table and (2) increase the

likelihood of overbank flooding throughout the meadow (SHG 2004). These two design

objectives are likely to affect the natural flow regime thereby altering streamflows below the

Trout Creek meadow (LTBMU 2004, SHG 2004, Lindquist and Wilcox 2000, Hillman 1998,

De Laney 1995, NRC 1992). Resource managers hypothesize that the raised channel bed will

reduce streamflow variability during extreme high flow and low flow periods, discourage the

rapid drainage of groundwater in the meadow, and prolong streamflow recession periods.

Streamflow magnitudes and velocities diminish as floodwaters are dispersed and infiltrated

throughout the floodplain and meadow surface (LTBMU 2004, SHG 2004, Lindquist and

Wilcox 2000, Poff et al. 1997). Frequent overbank flows and enlarged infiltration areas have

7

QuickTime™ and aTIFF (Uncompressed) decompressor

are needed to see this picture.

Figure 1. Location map of Trout Creek.

8

Figure 2. Trout Creek Meadow before restoration.

Figure 3. Trout Creek Meadow after restoration.

9

been linked to increases in groundwater storage in meadow and floodplain environments

(Hillman 1998, De Laney 1995, Lindquist and Wilcox 2000). Increased floodplain storage

capacities act to attenuate and dampen streamflow peaks and play a role in maintaining

streamflows following snowmelt conditions (Smakhtin 2000, Poff et al. 1997). In addition to

the information known about stream and floodplain interactions, the restored Trout Creek

channel is also likely to alter hydrologic characteristics because the groundwater table will be

elevated to that of the new streambed thereby increasing the local groundwater storage

capacity (SHG 2004). Based on this information it seems likely that the restoration at Trout

Creek will affect the flow regime below the meadow.

Hydrologic AnalysisA variety of analytical techniques have been utilized to predict, monitor, and assess

hydrologic responses following land use change (Riggs 1968). Changes to the flow regime

that result from channel modifications or changes in land use management practices are

sometimes overlooked or misinterpreted because they can easily be confounded with climatic

variations (Poff et al. 1997). Flow regimes (especially those in snowmelt-dominated

watersheds) exhibit inter and intra annual variations due to seasonal changes in climate

(Lindquist and Wilcox 2000, Smakhtin 2000, Poff et al. 1997, Riggs 1968). An important

component of any hydrologic analysis is to consider how climate influences streamflows

from year to year (Tague and Grant 2004, Poff et al. 1997, Riggs 1968). Climatic variations

can sometimes be accounted for if climate and streamflow records for the study site are

comprehensive enough to represent a range of climate types over and extended period of time

(Riggs 1968). However, in a watershed analysis, the most common way to isolate human-

caused changes to the flow regime is to conduct a paired watershed experiment (Brown et al.

2005).

Paired watershed experiments typically involve the use of two watersheds with

similar physical attributes to study the effects of land use change. In such a study, one of the

watersheds is subjected to a treatment while the other remains as a control. This strategy

allows the climatic variability to be accounted for in the analysis (Brown et al. 2005). After

the effects of climate have been accounted for, changes in water yield can then be attributed

to the changes in management. Most of the applicable knowledge about forests and water

10

yield has so far come from paired watershed experiments (Brown et al. 2005, Bosch and

Hewlett 1982, Hewlett 1971). The paired watershed experiment remains the surest way to

furnish each region with practical knowledge of land use and water yield relationships

(Hewlett 1971). Hydrologic research, utilizing a paired watershed approach, has been used to

analyze streamflow responses to fire, urbanization, timber harvesting, and various geologic

factors (White and Greer 2006, Tague and Grant 2004, Groffman et al. 2003, Loaiciga,

Pedreros, and Roberts 2001, Keppeler 1998, Keppeler, Zeimer, and Robert 1990).

A paired watershed approach, which utilizes streamflow and meteorological data, at

the Trout Creek site will enhance the understanding of how ecosystem processes respond to

restoration. Stream gages located above and below the restoration site enable this study to

analyze streamflow in a way similar to that of a paired watershed experiment. There is a

distinct advantage in doing this type of experiment at Trout Creek. Most arguments against

paired watershed studies have been attributed to the uncertainties associated with site

selection and the corresponding differences between site characteristics and physical

attributes (Brown et al. 2005). Uncertainties of this kind would be significantly reduced in

the analysis of Trout Creek because the two USGS stream gages that would be used in the

analysis are within the same watershed and are separated by approximately 10,000 feet of

stream channel. Many of the physical, biological, and chemical parameters associated with

each gaging site are the same or similar enough in nature to be deemed insignificant (SHG

2004).

RESEARCH QUESTIONS AND HYPOTHESES

Each research question will be answered and analyzed according to the structure

provided by the hypotheses listed below.

Research Question #1How has the streamflow below the Trout Creek Restoration Site been affected by the

prescribed restoration, as measured by (a) annual peak discharge, (b) August and September

baseflow conditions, and (c) the slope of the hydrograph recession limb?

11

Hypothesis #1There is no statistically significant change in the relationship between streamflow

from USGS stream gages located above and below the Trout Creek Restoration Site

following restoration. Streamflow measurements taken for water years 1991-2005 will

include annual peak discharge, August and September baseflow totals, and the minimum 7-

day running average for August and September.

Hypothesis #2There is no statistically significant change in the mean annual slope of the hydrograph

recession limb between pre and post restoration periods. Streamflow measurements taken for

water years 1961-2005 will be obtained from the USGS stream gage located below the Trout

Creek Restoration Site.

Hypothesis #3There is no statistically significant change in the relationship between the annual peak

15-day running average for snow depth and annual peak discharge, August and September

baseflow totals, and the annual minimum 7-day running average for August and September

following the restoration of Trout Creek. Snow depth and streamflow measurements taken

for water years 1961-2005 will be taken from the Central Sierra Snow Lab located near

Donner Pass, California and the USGS stream gage located below the Trout Creek

Restoration Site respectively.

Research Question #2How does the relationship between the meadow groundwater table and the

streamflow below the Trout Creek Restoration Site change after restoration?

Hypothesis #4There is no statistically significant change between the pre and post restoration

periods in the correlation between groundwater elevations and streamflow for 90% of the

groundwater wells monitored during water years 2000-2003.

12

CHAPTER 2

METHOD OF STUDY

The Trout Creek study site is located in the southern portion of the Lake Tahoe Basin

in El Dorado County, California. The site lies just north of Pioneer Trail and south of Martin

Avenue in the City of South Lake Tahoe. The 105-acre meadow is at approximately 6,255

feet above mean sea level and is comprised of vegetation indicative of high altitude montane

environments in the Sierra Nevada. Plant community structure varies throughout the meadow

system and includes a variety of riparian vegetation bounded by dryer upland sites mainly

comprised of coniferous trees. The meadow substrate is comprised of well-sorted alluvial and

glacial deposits. Cold Creek, a lesser tributary, flows into Trout Creek at roughly the

midpoint of the restored meadow reach. Trout Creek then flows north to join the Upper

Truckee River just prior to its discharge into Lake Tahoe. In the Lake Tahoe area, most

precipitation occurs in the winter, and summer drought is typical. The annual mean

streamflow near the Trout Creek Restoration Site varies between 10 and 60 cubic feet per

second (cfs).

DATA COLLECTION AND SAMPLING STRATEGY

The U.S. Geological Survey (USGS) has operated a streamflow gaging station on

Trout Creek (station number 10226780), just downstream of the project site at the Martin

Ave. crossing, continuously since October 1, 1960. A second USGS gage (station number

10226775), located upstream of the project site at the Pioneer Trail crossing, has been

providing continuous streamflow data since October 1, 1990. The period of record for this

analysis is defined by the operational starting date for each gage and ends on the last day of

the water year (September 30th) in 2005. Mean daily streamflow (cfs) has been derived from

samples taken every 15 minutes throughout the day by an automated stream stage data

recorder.

The Central Sierra Snow Lab, a field station operated by the University of California,

Berkeley, located near Donner Pass, CA, will provide the meteorological data needed for this

13

analysis. The field station is situated 6883 feet above mean sea level and is approximately 30

miles from the Trout Creek study site. Despite the laboratory’s distance from the study site,

the Central Sierra Snow Lab exhibits similar precipitation patterns to those found near Trout

Creek and possesses the longest continuous record of snow depth in the region. Snow depth

(ft) is measured once daily from a permanent snow depth stake, or from two automated depth

sensors when direct observation is not possible. The data obtained at this site will coincide

with the period of record for USGS gage # 10226780 (October 1st, 1960 to September 30th,

2005).

Groundwater data was collected by the City of South Lake Tahoe from 24

piezometers situated within the meadow. The monitoring wells were installed in October of

1999 and were arranged into 6 transects oriented perpendicular to the stream channel.

Piezometers were constructed out of perforated PVC pipe 6 feet in length, and monitored by

lowering a hydrolight until the water table was detected. Samples were taken on a bimonthly

basis from November of 1999 to June of 2003.

ANALYSIS AND STATISTICAL TESTS

Sets of different hydrologic-based metrics (described in detail below) will be

estimated from pre-restoration data sets, and differences before and after restoration will be

examined and tested for statistical significance. All data sets will be tested for normality

using the Shapiro-Wilk Test. If normality is determined, the Welch Two-Sample t-Test can

be used to test for statistical significance provided that the F Test is capable of showing a

difference between sample variances. The classical Two-Sample t-Test can be used for

normally distributed data if sample variances do not differ. If the data sets are not normal, the

Wilcoxon Sign-Rank Test will be used to test for statistical significance between samples

(Helsel and Hirsch 1991). Data compilation and analysis will be done in “R”, a computerized

system for statistical computation and graphics. Pre and post restoration data will also be

analyzed and interpreted graphically. This graphical analysis will help support statistical

findings and also help to visually evaluate the changes caused by restoration. The methods

and analytical strategies for each hypothesis are outlined below in greater detail.

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Hypothesis #1Using a method similar to those utilized in a paired watershed experiment,

streamflow data from the gage located above the restoration site will be compared to the

streamflow data obtained below the site from the gage affected by restoration. This strategy

will help account for the year-to-year variation caused by climate. To quantify the

relationship between gages located above and below the restoration site a linear regression

model will be utilized as follows:

y = mx + b

where y is the predicted value given a value of x, x is the independent variable, b the y-

intercept, and m is the regression coefficient. Mean daily streamflow data will be used to

establish this relationship. The regression coefficient and the y-intercept for the analysis will

be derived from pre-restoration data. The regression model will then be used to predict daily

streamflow for the lower gage from the upper gage over the period of record (water years

1991-2005). This time series of predicted flows will be used to compute errors in estimating

annual peak discharge, August and September baseflow totals, and the minimum 7-day

running average for August and September for each year prior to and after restoration. I will

then test for a significant difference in errors in predicting summer flow measurements

between pre and post restoration years.

Hypothesis #2Mean daily streamflow data will be used to establish pre and post restoration trends in

recession characteristics at the lower gage. The mean slope of the recession limb, defined by

a period exhibiting a minimum 15-day day consequtive decline in streamflow, will then be

computed for each water year. Instead of comparing streamflows at the lower gage with

those of the upper gage as in Hypothesis #1, the mean slope of the recession limb for each

water year can be analyzed solely at the lower gage because hydrograph recession is

considered to be a function of watershed characteristics, and not necessarily a factor

influenced by climatic variation. This time series of mean recession characteristics for each

year over the period of record (water years 1961-2005) will be used to analyze the difference

in means before and after restoration at the lower gage. I will then test for a significant

difference in the population mean recession characteristics between pre and post restoration

years.

15

Hypothesis #3Daily snow depth measurements taken from the Central Sierra Snow Lab and mean

daily streamflow measurements recorded at the USGS stream gage located below the Trout

Creek Restoration Site will be used in this analysis. The annual peak 15-day running average

for snow depth and the annual minimum 15-day running average for streamflow will be used

to establish a trend between snow depth and streamflow at the lower gage during the period

prior to restoration. The regression coefficient and the y-intercept can be derived from this

pre-restoration data relationship because studies have shown that snowpack is strongly

correlated with seasonal streamflows in the Sierra Nevada Mountains (Godsey and Kirchner

2004). If a linear trend is found, snow depth can then be used to predict values of streamflow

at the lower gage. Similar to the methods described by Hypothesis #1, this regression model

will be used to derive errors between predicted and observed values for the period prior to

and following restoration. Errors in estimates of annual peak discharge, August and

September baseflow totals, and the annual minimum 7-day running average for August and

September, as predicted from snow depth, will be computed for water years 1961-2005.

Differences in errors prior to and after restoration will then be examined and tested for

statistical significance.

Hypothesis #4The pre and post restoration relationship between the groundwater wells and

streamflow below the project site will be interpreted graphically. This graphical analysis of

meadow groundwater wells and streamflow will help to visually evaluate the changes caused

by restoration. Significance will be determined if changes can be detected in 90% of the

wells. This standard for significance was chosen because wells located at higher elevations

and farther from the streambed are less likely to exhibit any change.

ASSUMPTIONS AND LIMITATIONS This study is constrained by certain assumptions and limitations. Although the

hydrologic and meteorological data collected for this study represents the best data available

for this region, certain uncertainties must be assumed. Extreme environmental conditions or

technical difficulties with regards to sampling equipment or personnel may result in missing

16

data values. In this case, an averaged data value, taken from preceding and subsequent

values, will replace missing data entries. Aside from data collection limitations, certain

assumptions will have to be made when analyzing data. Averaging data values is a common

statistical tool and is frequently employed throughout this study. In using this technique, I am

assuming that the variability typical of hydrologic data is not as important as the averaged

value for the same time period in certain instances. The time periods for the 7-day running

average (used to analyze baseflows) and the 15-day running average (used to analyze

snowpack) were arbitrarily chosen to coincide with weekly and bi-monthly time periods even

though it is well understood that the number of samples, when averaged for a particular time

period, can affect the analytical outcome of the study.

Some assumptions will also have to be made in using the hydrograph elements

outlined in this analysis. The highest peak streamflow for each water year will be used in the

statistical computations even though some water years may exhibit several distinct peaks

within a snowmelt period. August and September baseflows, which are typical of snowmelt-

dominated watersheds of the Sierra Nevada Mountain Range, will be studied in this analysis

even though the onset and timing of baseflow conditions can vary between wet and dry years.

The mean slope of the recession limb, arbitrarily defined by a period exhibiting a minimum

15-day decline in streamflow, was chosen to reduce the chance of analyzing mid-winter

recession limbs or spring snowmelt periods that exhibit more than one peak streamflow

event. In doing this I am accepting that I may also be excluding the steepest, uppermost

portion of the hydrograph recession limb from the analysis.

Although I will be utilizing the most acceptable methods to isolate and remove the

impacts of inter and intra annual climatic variations, hydrologic impacts resulting from

weather are not fully understood and can vary from place to place. The regression analyses

used to assess streamflow conditions below the site between upper and lower gages, and

between snowpack and streamflow both assume that there is a relationship between these two

elements, and that that relationship is linear. Other interpretative strategies will have to be

employed if this is not the case.

And lastly, the number of groundwater wells within the meadow cannot possibly

capture all of the spatial variability inherent throughout the105 acre site. The nineteen

groundwater wells, located within the Trout Creek Meadow, are assumed to be a

17

representative sample of water table elevations. It is fair to assume that there is a hydrologic

link between groundwater and the stream channel at this particular site, but the strength of

this relationship is difficult to assess. I am assuming that a graphical analysis of each

groundwater well will be sufficient enough to visually assess the changes that have occurred

as a result of restoration.

DATA ADJUSTMENTS

Approximately 1% of the snow depth data obtained from the Central Sierra Snow Lab

had missing data values for the period October 1st, 1960 to September 30th, 2005. Out of the

16,436 total possible observations for this period, 182 data values had to be adjusted for the

purposes of statistical analysis. Fortunately, 124 of the missing data values, most of which

occurred during summer where no snow was present (and the preceding and subsequent

measurement was also zero), could easily be interpreted as having a zero value. Of the 58

remaining missing values, the average snow depth of the preceding and subsequent

measurement was used to make the data adjustment for each case. Only 0.35% of the total

values for snow depth have been adjusted in this fashion. It has been concluded that this

small fraction of adjusted values, compared to the entire dataset, will not have a significant

effect on the outcome of the study. The table in Appendix A shows the date and value for

each adjustment.

Due to incomplete records, five groundwater wells were omitted from this study

because they had been damaged due to vandalism or destroyed during the construction of the

new stream channel. Of the 24 original groundwater wells installed in the Trout Creek

Meadow, only 19 will be used in this analysis.

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CHAPTER 3

RESULTS AND DISCUSSION

Figures and tables displaying the results of the two research questions and their

hypotheses investigated in this study are presented in this chapter, along with discussion of

the results.

RESEARCH QUESTION #1How has the streamflow below the Trout Creek Restoration Site been affected by the

prescribed restoration, as measured by (a) annual peak discharge, (b) August and September

baseflow conditions, and (c) the slope of the hydrograph recession limb?

Hypothesis #1There is no statistically significant change in the relationship between streamflow

from USGS stream gages located above and below the Trout Creek Restoration Site

following restoration. Streamflow measurements taken for water years 1991-2005 will

include annual peak discharge, August and September baseflow totals, and the minimum 7-

day running average for August and September.

ANNUAL PEAK DISCHARGE

Peak discharge data was extracted from USGS stream gage data for the upper and

lower site for each water year 1991- 2005. These results are displayed in Table 1. Several

conclusions can be drawn from the information provided in this table. First, it should be

noted that 10 out of the 15 peak discharge dates at the upper gage do not coincide with the

peak discharge dates at the lower gage of the same water year. This presents a problem when

trying to conduct a statistical analysis on peak discharge at these sites. In addition, the dataset

containing pre-restoration peak discharges at the upper gage had a p-value of 0.016,

indicating a non-Gaussian distribution according to the Shapiro-Wilk Test for normality.

Results of the Shapiro-Wilk Test for all datasets can be viewed in the table located in

Appendix B. If the resultant p-values are less than 0.05 in this particular test it can be

19

concluded that the data were not normally distributed, and a linear model should not be

applied. The peak discharge relationship between upper and lower gages for pre and post

restoration periods is shown in Figure 4. By looking at this graph, a visual assessment can be

made regarding the effects of restoration on peak discharges below the project site. Post

restoration peak discharge data does not lie beyond what could be considered the normal

variability observed in the pre-restoration dataset. In this instance there was no statistically

significant change in the relationship between streamflow from USGS stream gages located

above and below the Trout Creek Restoration Site following restoration.

Table 1. Peak Discharge for Each Water Year at Upper and Lower Gages.

Water YearUpper Gage Lower Gage

Date Peak Discharge (cfs) Date Peak Discharge

(cfs)1991 3/4/91 60 5/4/91 911992 10/26/90 45 10/26/90 711993 5/31/93 138 5/31/93 1651994 5/12/94 33 4/20/94 471995 6/30/95 337 6/26/95 3191996 5/16/96 274 5/16/96 3031997 1/2/97 525 1/2/97 5351998 6/25/98 158 6/22/98 2291999 5/28/99 183 5/29/99 2692000 5/24/00 70 2/14/00 1052001 5/12/01 33 5/12/01 442002 6/1/02 49 4/15/02 692003 5/31/03 126 5/30/03 1422004 5/5/04 43 5/6/04 582005 5/20/05 146 5/29/05 197

- - Indicates where peak discharge occurred on different days at the upper and lower gage during each water year.

The discrepancies between peak discharge dates at the upper and lower gages could

have emerged as a result of the local hydrology within the meadow. The meadow area

between the two gages comprises an area capable of vast amounts of groundwater storage.

The infiltration capacity and amount of available storage within the meadow can vary

depending on the height of the groundwater table and whether saturated or unsaturated soil

conditions exist. Aside from normal snowmelt conditions, where peaks are oftentimes

observed at night or in late afternoon, other climatic variables which include the likelihood of

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rain on snow events, can greatly impact meadow storage capacities and peak discharge

timing. The timing of inputs from Cold Creek, which joins Trout Creek midway through the

meadow, can also affect peak discharges at the lower gage. The understanding of peak

discharge timing and magnitude below Trout Creek is infinitely more complex than this

study will allow.

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Figure 4. Graph depicting the peak discharge relationship between upper and lower gages for before and after restoration periods. Trend lines were not applied because one or more datasets were not normally distributed.

AUGUST AND SEPTEMBER BASEFLOW TOTALS

The analysis of August and September baseflow totals and the minimum 7-day

running average discharge for August and September was based upon the pre-restoration

discharge relationship between upper and lower gages. This relationship had a R-squared

value of 0.97 at the 99% confidence level, meaning that 97% of all the variability observed

within the data was accounted for by the linear model. R-squared values and the results for

all of the models run in this analysis can be found in the table located in Appendix C.

Predicted values for August and September baseflow totals were then extrapolated and

compared with observed values. Residual error differences between these two datasets were

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then computed and analyzed for statistical significance. The Shapiro-Wilk Test concluded

that all of the datasets for this part of the analysis were normally distributed.

The pre and post restoration discharge relationship between upper and lower gages

for the month of August both had a R-squared value of 0.99 at the 99% confidence level. A

graphical depiction of this linear model can be seen in Figure 5. The F-Test was used to

determine whether there was a difference between sample variances. Because the F-test for

pre and post restoration residual errors for August baseflow totals had a p-value of 0.022, and

the sample variances between datasets were shown to be different, the Welch Two Sample t-

Test was used to evaluate statistical significance. The p-value of the Welch Two Sample t-

Test was 0.071, showing that the residual errors for predicted and observed August baseflow

totals were significantly different after restoration at 93% confidence level. Results from the

F-Test, Welch Two Sample t-Test, and the Classical Two Sample t-Test for all of the datasets

tested can be seen in the table located in Appendix D.

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Figure 5. Graphs showing the relationship between upper and lower gages during before and after restoration periods for August and September baseflow totals.

The pre-restoration discharge relationship between upper and lower gages for the

month of September had a R-squared value of 0.99 at the 99% confidence level, and the post-

restoration discharge relationship between upper and lower gages for the month of September

had a R-squared value of 0.92 at the 95% confidence level. A graphical depiction of this

linear model can be seen in Figure 5. The F-test for pre and post restoration residual errors

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for September baseflow totals had a p-value of 0.087, meaning the sample variances between

datasets were shown to be similar. The Classical Two Sample t-Test was then used to

evaluate statistical significance. The resultant p-value of the Classical Two Sample t-Test

was 0.229, showing that the residual errors for predicted and observed September baseflow

totals were not significantly different after restoration above a 90% confidence level.

Boxplots showing the before and after observed baseflow totals and the before and

after error differences for August and September’s baseflow totals can be seen in Figures 6

and 7. It was originally expected, that with elevated groundwater levels following restoration,

an increase in summertime baseflows would be observed. This apparently was not the case.

Baseflow totals have been shown to decrease following restoration for both August and

September. Error differences between observed and predicted values for August were

significant, but were not for significant for the month of September. It is interesting to note

that this is still opposite of what was expected of baseflows following a restoration of this

type.

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Figure 6. Boxplots of observed baseflow totals for before and after restoration periods in August and September.

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Figure 7. Boxplots of before and after restoration error differences for August and September baseflow totals.

MINIMUM 7-DAY RUNNING AVERAGE DISCHARGE FOR AUGUST AND SEPTEMBER

The pre-restoration minimum 7-day running average discharge relationship between

upper and lower gages for August and September had a R-squared value of 0.96 at the 99%

confidence level, and the post-restoration discharge relationship between upper and lower

gages for August and September had a R-squared value of 0.96 at the 95% confidence level.

A graphical depiction of this linear model can be seen in Figure 8. The F-test on the pre and

post restoration residual errors for the minimum 7-day running average in August and

September had a p-value of 0.114, meaning that the sample variances between datasets were

shown to be similar. The Classical Two Sample t-Test was then used to evaluate for

statistical significance. The resultant p-value of the Classical Two Sample t-Test was 0.315,

showing that the residual errors for predicted and observed flows for this period were not

significantly different after restoration above a 90% confidence level.

Boxplots showing the before and after observed minimum 7-day running average

discharges in August and September, and the before and after error differences for August

and September, can be seen in Figures 9 and 10. As with the previous analysis of baseflow

totals, an increase in the minimum 7-day running average for this period was originally

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expected after restoration. This was also not the case. The minimum 7-day running average

discharge decreased following restoration.

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Figure 8. Graph showing the relationship between upper and lower gages during before and after restoration periods for the minimum seven-day running average discharge in August and September.

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Figure 9. Boxplots of observed minimum seven-day running average discharge totals in August and September for before and after restoration periods.

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Figure 10. Boxplots of before and after restoration error differences for the minimum seven-day running average for August and September discharges.

Hypothesis #2There is no statistically significant change in the mean annual slope of the hydrograph

recession limb between pre and post restoration periods. Streamflow measurements taken for

water years 1961-2005 will be obtained from the USGS stream gage located below the Trout

Creek Restoration Site.

The mean slope of the recession limb, defined by a period exhibiting a minimum 15-

day decline in streamflow, was computed for each water year at the lower gage. A graph

showing the mean slope of the hydrograph recession limb for each water year can be seen in

Figure 11. The pre restoration dataset for mean slopes of the hydrograph recession limb had a

p-value of 0.004 after the Shapiro-Wilk Test was used to test for normality. Since this dataset

did not have a normal distribution the Wilcoxon Sign-Rank Test was used to test for

statistical significance. The p-value of the Wilcoxon Sign-Rank Test was 0.525, showing that

the mean slopes of the recession limb for each water year after restoration were not

significantly different than those before restoration above a 90% confidence level. Boxplots

26

of the mean slope of the hydrograph recession limb before and after restoration can be seen

in Figure 12.

As seen in Figure 11, there is no real discrepancy between the mean slopes of the pre-

restoration dataset and the mean slopes of the post-restoration dataset. In theory, restoration

would have raised the groundwater table, increased water storage, and reduced the rapid

attenuation of streamflows throughout the summer months. As these streamflows diminished

more slowly, the slope of the hydrograph recession limb would have also decreased, but this

phenomenon was not observed in this study. Non-significance between datasets could be a

result of only choosing recession periods that exhibited a minimum 15-day decline in

streamflow. This decision was originally made so as to eliminate the calculation of recession

periods that occurred as a result of thunderstorms, rain on snow events, or because of

multiple snowmelt peaks. This method for obtaining the mean slope of the recession limb

could have been skewed towards slope values that occurred later in the summer. Much of the

spring snowmelt period (the steepest part of the hydrograph recession limb) would have been

missed in this analysis if there was a water year that exhibited multiple snowmelt peaks or a

snow/rainstorm in late spring that interrupted streamflow recessions. Given this information,

the effects of restoration on the hydrograph recession limb is still uncertain.

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Figure 11. Graph showing the mean slope of the hydrograph recession limb for each water year. Trend lines were not applied because one or more datasets were not normally distributed.

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Figure 12. Boxplots of the mean slope of the hydrograph recession limb before and after restoration.

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Hypothesis #3There is no statistically significant change in the relationship between the annual peak

15-day running average for snow depth and annual peak discharge, August and September

baseflow totals, and the annual minimum 7-day running average for August and September

following the restoration of Trout Creek. Snow depth and streamflow measurements taken

for water years 1961-2005 will be taken from the Central Sierra Snow Lab located near

Donner Pass, California and the USGS stream gage located below the Trout Creek

Restoration Site respectively.

The annual peak 15-day running average for snow depth and the annual minimum 15-

day running average for streamflow were used to establish a trend between snow depth and

streamflow at the lower gage during the period prior to restoration. Although studies have

shown that snowpack is strongly correlated with seasonal streamflows in the Sierra Nevada

Mountains (Godsey and Kirchner 2004), this correlation was not evident here. If a linear

trend had been found, snow depth could have been used to predict values of streamflow at

the lower gage. The Shapiro-Wilk Test for normality demonstrated that that the pre-

restoration dataset for the minimum 15-day running average discharge at the lower gage did

not have a normal distribution. Since this dataset departed from normality a linear model

could not be used in this analysis. Figure 13 is a graph depicting the relationship between the

annual peak 15-day running average for snow depth and the annual minimum 15-day running

average for streamflow for before and after restoration periods. From this graph it is easy to

see that there is not only a very weaek relationship between snow depth and streamflow, but

there is also very little discrepancy between pre and post restoration data values.

Even though studies have shown strong correlations between snowpack and seasonal

streamflow, several explanations can be offered as to why such a weaek correlation was

observed in this case. The first and most obvious reason is related to the distance between the

Central Sierra Snow Lab and the restoration site at Trout Creek. Since this observation post is

located outside of the Trout Creek watershed it is less likely to be correlated with the

streamflows at Trout Creek. Also, Lake Tahoe is an immense body of water that can have a

moderating affect on local weather. It is entirely possible that microclimates at either of these

sites had affected the correlation between the two variables. In addition, max snow depth

29

may be a weak indicator of summertime streamflows. For example, if the max snow depth

was recorded in January and was immediately followed by a rain on snow event, several

months of drought-like conditions, and a spring with multiple peak runoff events, summer

baseflows would be less likely to reflect the maximum recorded snow depth. In this case,

springtime snow depths may provide a better indicator of streamflow. Even still, this analysis

would be difficult, given that snow depth monitoring was not conducted within the Trout

Creek watershed.

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Figure 13. Graph depicting the relationship between the annual peak 15 day running average for snow depth and the minimum 15 day running average streamflow discharge during before and after restoration periods at the lower gage for each water year. Trend lines were not applied because one or more datasets were not normally distributed.

RESEARCH QUESTION #2How does the relationship between the meadow groundwater table and the

streamflow below the Trout Creek Restoration Site change after restoration?

30

Hypothesis #4There is no statistically significant change between the pre and post restoration

periods in the correlation between groundwater elevations and streamflow for 90% of the

groundwater wells monitored during water years 2000-2003.

The groundwater well data collected in the Trout Creek Meadow was correlated with

stream discharge for each of the dates monitored. This correlation between groundwater

depth and discharge was done to remove the climatic effects associated with wet years and

dry years. Correlation coefficients were then derived for each of the wells for the pre and

post restoration periods. A graph depicting this information is shown in Figure 14. Upon first

examination it appears that the groundwater elevation to discharge correlation has been

affected for every well monitored during the post-restoration period, leading one to believe

that groundwater elevations have risen throughout the meadow as a result of restoration. It is

important to realize however, that the geographic proximity of these wells to the stream

channel has changed. On average, 68% of the groundwater wells surveyed were located 198ft

closer to the stream channel after restoration. The remaining 32% of the wells surveyed,

ended up being 112ft further away (on average) from the channel then they were before

restoration. The map in Figure 15 shows how the wells in each of the monitoring transects is

oriented with respect to both the new and old stream alignment. Table 2 provides the

distances from each well to the old stream channel (pre-restoration) and the new stream

channel (post-restoration).

It would make sense that wells located closest to the stream channel would exhibit

higher groundwater elevations. For this reason, before and after comparisons at some of the

wells could not be reasonably assessed by looking solely at the results in Figure 14.

Coefficients were then graphed againstwith well distances to the stream for the before and

after restoration periods, as seen in Figure 16. This graph shows that although distances to

the new stream channel generally decreased, all of the wells were measurably affected by the

restoration. This graph also shows that there is a stronger correlation between groundwater

and surface water following restoration. By looking at these two graphs it could be concluded

that there was an overall increase in the groundwater table relative to streamflow for 100% of

the wells sampled following restoration.

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Figure 14. Bar graph showing the before and after restoration distribution of groundwater depth to discharge correlation coefficients for before and after restoration periods.

All of the wells were affected by restoration in some way or another, but still, the real

question is: which wells were affected by characteristics such as new channel geometry,

increased sinuosity and channel length, increases in surface and subsurface storage, the

increased likelihood of overland flooding, etc., and which wells were affected simply

because the channel was moved closer to the well? This question is not easily answerable,

but by looking at a few particular wells in depth, they might be able to provide some

explanation. Wells located equidistant between the old channel and the new channel should

be similarly affected by distance in pre and post restoration instances. It is assumed that any

changes in the correlation between groundwater and streamflow in these wells would have

resulted from the restoration, and not because of issues related to distance from the stream.

32

Figure 15. Map showing groundwater well locations and pre and post restoration stream alignments.

33

Table 2. Well Location Information.

WellName

Surface ElevationAt Well (ft)

Well Distance (ft) to:

OldChannel

NewChannel

T1W2 6252 75 132T1W4 6251 350 135T2W1 6255 197 122T2W3 6255 87 156T2W4 6252 254 329T3W3 6258 437 5T3W4 6257 592 159T4W1 6260 373 153T4W2 6261 245 20T4W3 6260 140 84T4W4 6261 36 191T5W1 6261 460 216T5W2 6261 328 78T5W3 6262 159 93T5W4 6263 47 203T6W1 6263 70 230T6W2 6265 102 57T6W3 6265 280 123T6W4 6265 431 273

- - Indicates wells that are located in between the old channel and the new channel.

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Figure 16. Graph showing the before and after restoration distribution of groundwater depth to discharge correlation coefficients and distance to the channel.

Table 3. Analysis of Wells Located Between Old and New Channel Alignments.

WellName

Well Distance (ft) to: Distance Moved

Correlation Coefficient: Percent Change Old

ChannelNew

Channel Before After

T1W2 75 132 57 -0.854 -0.939 110%T4W3 140 84 56 -0.523 -0.806 154%T4W4 36 191 155 -0.515 -0.808 157%T5W3 159 93 66 -0.123 -0.933 756%T5W4 47 203 156 -0.397 -0.789 199%T6W2 102 57 45 -0.162 -0.791 488%

- - Indicates well locations where the stream channel has moved farther away after restoration.

Only six wells were located in between the old channel and the new channel. These

six wells had similar distances to the stream channel both before and after restoration. After

construction of the new channel, three of these wells (T4W3, T5W3, and T6W2) ended up

slightly closer to the new channel (56, 66, and 45 ft respectively), and three wells (T1W2,

T4W4, and T5W4) ended up slightly farther away (57, 155, and 156 ft respectively). Table 3

shows before and after distances to the stream channel for each of these wells. It also shows

the correlation coefficients for before and after restoration periods with the percent increase

35

for each well. Graphs showing the relationship between groundwater depth and discharge for

the before and after restoration periods for these six wells, are shown in Figures 17 and 18.

There are a couple of unique features to point out when analyzing Table 3 and

Figures 17and 18. The first is that given similar streamflows and similar proximities to the

channel, the depth to groundwater decreased at all of these wells following restoration.

Correlation coefficients increased 310% on average after restoration. Secondly, the greatest

change in groundwater depth between pre and post restoration periods is observed when

flows increase. Four out of the six wells analyzed (T4W3, T4W4, T5W4, and to a lesser

extent T1W2) revealed that during low flow conditions there was little change in the

groundwater elevation before and after restoration. This phenomenon was only observed

during baseflows, and it became less apparent as flows increased. This could possibly explain

why the baseflow analyses in Hypothesis #1 were found to be insignificant. It appears that

the effects of restoration become more noticeable as flows increase. One other interesting

point to be made about Figures 17 and 18 is that as the post-restoration trend line for

groundwater depth reaches zero, the streamflow at the lower gage is at approximately 110 cfs

for each of the graphs. This is significant because the designed stream channel was

engineered so that water would leave the channel and flow out onto the floodplain at

approximately 105 cfs (SHG 2004).

36

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Figure 17. Graphs showing the before and after restoration distribution of groundwater depth to discharge for before and after restoration periods. This cluster of graphs depicts wells located between the old channel and the new channel, where distance to the channel decreased after restoration.

37

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Figure 18. Graphs showing the before and after restoration distribution of groundwater depth to discharge for before and after restoration periods. This cluster of graphs depicts wells located between the old channel and the new channel, where distance to the channel increased after restoration.

38

CHAPTER 4

SUMMARY, CONCLUSIONS, AND

RECOMMENDATIONS FOR FUTURE

RESEARCH AND MANAGEMENT

The answers to the two research questions are summarized in this chapter, and

conclusions and recommendations for future research and management are offered.

SUMMARY OF FINDINGS

Research Question #1: How has the streamflow below the Trout Creek Restoration Site

been affected by the prescribed restoration, as measured by (a) annual peak discharge, (b)

August and September baseflow conditions, and (c) the slope of the hydrograph recession

limb?

To answer the first research question I would like to briefly summarize some of my

findings as they relate to the first three hypotheses. Annual peak discharge could not be

statistically analyzed because peak flows at the upper and lower gage occurred on different

days and the data was not normally distributed. A graphical analysis of peak flows showed

that peak discharge values did not change after restoration. Baseflow levels in August and

September were expected to increase as a result of restoration, but just the opposite was

observed. August baseflow totals after restorations were found to be statistically significant

at the 93% confidence level, but still, this significant change in baseflows was opposite of

what was predicted. There was no significant change in September baseflow conditions.

There was also no significant change after restoration in the minimum 7-day running average

for August and September. There was no significant change in the slope of the hydrograph

recession limb following restoration, and the analysis of the relationship between snowpack

and streamflow could not be completed because the data was not normally distributed and the

relationship proved to be too week to yield meaningful results.

39

Research Question #2: How does the relationship between the meadow groundwater table

and the streamflow below the Trout Creek Restoration Site change after restoration?

In answer to the second question, the analysis of the relationship between the meadow

groundwater table and streamflow below the site did produce some interesting results. First,

the correlation between groundwater depth and streamflow became much stronger after

restoration and change was witnessed even as the distance from the well to the channel

increased. In observation wells were there was little change in distance to the stream channel

(6 wells out of the original 19), the correlation coefficients increased over 310% on average.

These six wells also exhibited the greatest change in groundwater depth between pre and post

restoration periods when flows increased. Values observed during baseflow conditions

showed only slight reductions in depth to groundwater after restoration, but before and after

differences became much more apparent as flows increased. It appears that the effects of

restoration become more noticeable as flows increase. It was also observed that as flows

increase and the depth to groundwater decreases, the point where the water table is at the

surface also reveals the approximated discharge where the channel is predicted to overflow

it’s banks.

CONCLUSIONS

By reviewing the results of this study, it is apparent that the meadow groundwater

table had been affected by restoration and that the relationship between groundwater depth

and streamflow became much stronger following restoration. However, I would like to offer

some clues to help explain why streamflows did not show any significant change in the post

restoration period. First, there were only 4 years of post restoration data. I feel that four years

was insufficient to fully capture all of the variability that could be attributed to the effects

incurred by restoration. There is what resource managers like to call a “break-in period”

following any restoration project (personal consultation with LTBMU and SHG). During this

time it is possible that fine grain particles could have filled larger pore spaces thereby

reducing water losses through the channel bed, freeze/thaw cycles and bioturbidation caused

by vegetation, wildlife, and micro-organisms could have increased meadow infiltration rates,

and the increases in vegetative mass could have affected water consumption rates throughout

the growing season. Vegetative growth and processes involving sediment sorting, channel

40

bed characteristics, and permeability are going to be heavily impacted by restoration, and

many resource managers have concluded that it sometimes takes 1 to 3 years before

stabilization of the new channel and the surrounding vegetation is fully reached (personal

consultation with LTBMU and SHG). Therefore, four years may be an insufficient amount of

time to monitor a stream restoration project of this type and magnitude.

Also, the changes in the plant community that occurred as a result of restoration

should be addressed. It is not the intent of this thesis to study the changing ecologic

components at the Trout Creek site, but it is difficult to conduct a hydrologic study without

giving mention to the role that vegetation plays in the hydrologic cycle. Plants utilize and

transpire large amounts of water throughout their life cycle. The transpiration rates of plants

can vary depending on many factors including species type, size, and location.

In a report by Western Botanical Services, Inc. (2003), a general trend towards a

wetter, or more hydric plant community was observed throughout the meadow, and most of

the mesic species present before restoration exhibited declines in cover values. By the time

the vegetative survey had been completed in 2002 vegetative cover of native perennial forbs

had almost doubled. An increase in plant diversity and vigor had occurred despite drought-

like conditions in the preceding years. It was concluded that these observations were likely a

result of the decreased depth to groundwater throughout the meadow (WBS 2003). At the

time of the survey willow density had not changed, but were still expected to increase as the

new cuttings grew and matured.

The observed increases in plant vigor, the transition from annuals to perennials and

mesic species to hydric species, the expectation that willow densities will increase, and the

overall expectation that these trends will continue may play an important role in affecting

hydrologic processes. Annual forbs and grasses tend to concentrate root growth and soil-

water utilization in the upper soil profile but native perennials in contrast, allocate a high

proportion of their biomass to the production of a deep root system, which allows them to

continue soil-water utilization well into the dry season (Holmes and Rice 1996). Given these

factors, it can be assumed that water consumption and transpiration rates have, and will

continue to increase throughout the site until equilibrium is reached. The increase in

transpiration over this time period is not known, and whether this change has affected

streamflows below the restoration site is also speculative, but this information might offer an

41

explanation as to why streamflows below the site did not show any signs of significant

change after restoration.

With and understanding of the role plants play in the hydrologic cycle, it is possible

to conclude that vegetation influenced streamflows below the Trout Creek Restoration Site,

especially during baseflow conditions late in season. With increases in the diversity, vigor,

and number of plants accessing the groundwater table late in the season, streamflows could

potentially be impacted. Baseflows were expected to increase following restoration due to

increases in storage and a moderated flood recession limb, but just the opposite was

observed. This decrease in flows could stem from the increased water utilization by plants

later in the season, but again, this claim is only speculative. It will be important for future

research to address the influences of vegetation upon hydrologic processes.

RESEARCH RECOMMENDATIONS

It is apparent from the results of this study that more post-restoration streamflow data

is needed to ascertain the effects that channel modification played on local hydrologic

processes. It is difficult to say with any certainty, that the post-restoration effects of surface

hydrology witnessed at Trout Creek were directly linked to the stream restoration project

because almost all of the observed data fell within the natural variability of pre-restoration

datasets. Additional post-restoration data gathered over the next few years would help to

resolve issues of statistical significance between datasets. It will also be important to further

assess the role plants play in water utilization, and whether a change in density and species

composition is likely to affect streamflow.

Although significant changes were observed as a result of restoration in the

relationship between groundwater and streamflow, additional pre and post groundwater

measurements would help to reinforce this claim. Also, research of this type would benefit

from additional groundwater wells being placed equidistant between the new and old

channels to help better evaluate the changes incurred by restoration. This will help to resolve

issues related to distance to the channel.

Research involving hydrologic and ecologic restoration should continue. Only then

will we be able to improve upon the methods of restoration, and be able to better assess the

benefits gained by restoring these natural processes.

42

MANAGEMENT RECOMMENDATIONS

The results of this analysis help to provide natural resource managers with some

valuable insight regarding stream and riparian ecosystem restoration. Land managers can

begin to assess whether stream channel modification and habitat restoration is capable of

altering hydrologic and ecologic processes thereby improving ecosystem diversity, function,

and productivity in riparian environments. Restoring the natural hydrograph is now a

common goal for projects involving ecosystem restoration. There is still a great deal of

uncertainty associated with understanding hydrologic processes following restoration, but the

results of the Trout Creek analysis are promising. It is difficult to say whether restoration has

had a direct effect on streamflow below the project site, but there is evidence to suggest an

increase in the groundwater table following channel modification. This information, coupled

with the vegetation and wildlife data contributed by other consultants (WBS 2003, SHG

2004, Wigart 2004) at the Trout creek site is enough to deem the project a success (Wigart

2004). Similar methods of ecosystem restoration involving channel modification should be a

consideration in all future projects aimed at improving ecosystem health and diversity.

Restoration has brought about improvements in channel and meadow habitat and also raised

groundwater elevations throughout the meadow, altering vegetation, wildlife, and other

ecosystem components, regardless of whether streamflow below the site was measurably

impacted by this change.

43

REFERENCES

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Brown, Alice E., Lu Zhang, Thomas A. McMahon, Andrew W. Western, and Robert A. Vertessy. 2005. A review of paired catchment studies for determining changes in water yield resulting from alterations in vegetation. Journal of Hydrology 310(1-4): 28-61.

Budelsky, Rachel A. and Susan M. Galatowitsch. 2000. Effects of water regime and competition on the establishment of native sedge in restored wetlands. Journal of Applied Ecology 37(6): 971-985.

Central Sierra Snow Laboratory. Meteorological data 1960-2005. University of California, Berkeley. Received March 8th, 2006.

De Laney, T.A. 1995. Benefits to downstream flood attenuation and water quality as a result of constructed wetlands in agricultural landscapes Journal of Soil and Water Conservation 50(6): 620-626.

Godsey, S.E. and J.W. Kirchner. The relationship between snowpack and seasonal low flows in the Sierra Nevada: Climate change and water availability in California. Eos, Transactions, American Geophysical Union, 85(46), Fall Meet. Suppl., Abstract U53A-0704, 2004 (American Geophysical Union Fall Meeting, San Francisco, December 2004).

Goodwin, Craig N., Charles P. Hawkins, and Jeffrey L. Kershner. 1997. Riparian restoration in the Western United States: Overview and perspective. Restoration Ecology 5(4S): 4-14.

Groffman, Peter M., Daniel J. Bain, Lawrence E. Band, Kenneth T. Belt, Grace S. Brush, J. Morgan Grove, Richard V. Pouyat, Ian C. Yelsilonis, and Wayne C. Zipperer. 2003. Down by the riverside: urban riparian ecology. Front. Ecol. Environ. 1(6): 315-321.

Helsel, D.R. and R.M. Hirsch. 1991. Statistical methods in water resources. U.S. Geological Survey. Techniques of Water-Resources Investigation Book 4. Chapter A3.

Hewlett, John D. 1971. Comments of the catchment experiment to determine vegetal effects on water yield. Water Resources Bulletin 7(2): 376-381.

Hillman, G.R. 1998. Flood wave attenuation by a wetland following a beaver dam failure on a second-order boreal stream. Wetlands 18(1): 21-34.

Holl, Karen D. and R.B. Howarth. 2000. Paying for Restoration. Restoration Ecology 8(3): 260-267.

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Holmes, T.H. and K.J. Rice. 1996. Paterns of growth and soil-water utilization in some exotic annuals and native perennial bunchgrasses of California. Annals of Botany 78: 233-243.

Kauffman, J. Boone, Robert L. Beschta, Nick Otting, and Danna Lytjen. 1997. An ecological perspective of riparian and stream restoration in the Western United States. Fisheries 22(5): 12-24.

Keppeler, Elizabeth T. 1998. The summer flow and water yield response to timber harvest. USDA Forest Service General Techinical Report PSW-GTR-168-Web. Retrieved on February 12th, 2006 from http://www.fs.fed.us/psw/publications/documents/gtr-168/05-keppeler.html

Keppeler, Elizabeth, T. Ziemer, and R. Robert. 1990. Logging effects on streamflow: water yields and summer low flows at Caspar Creek in northwestern California. Water Resources Research 26(7): 1669-1679.

Lindquist, Donna S. and Jim Wilcox. 2000. New concepts for meadow restoration in the Northern Sierra Nevada. Feather River Coordinated Resource Management. Retrieved February 27, 2006 from http://www.feather-river-crm.org/publications/abstracts/ieca.htm

Loaiciga, Hugo A., Diego Pedreros, and Dar Roberts. 2001. Wildfire-streamflow interactions in a chaparral watershed. Advances in Environmental Research 5: 295-305.

[LTBMU] Lake Tahoe Basin Management Unit. 2004. Draft Environmental Assessment Big Meadow Creek: Cookhouse Meadow Stream Restoration Project. U.S. Forest Service (unpublished).

Malard, Florian, Klement Tockner, Marie-Jose Dole-Olivier, and J.V. Ward. 2002. A landscape perspective of surface-subsurface hydrological exchanges in river corridors. Freshwater Biology 47: 621-640.

Martin, David and Jeanne Chambers. 2002. Restoration of riparian meadows degraded by livestock grazing: above and belowground responses. Plant Ecology 163(1): 77-91.

McDonald, A., S.N. Lane, N.E. Haycock, and E.A. Chalk. 2004. Rivers of dreams: On the gulf between theoretical and practical aspects of an upland river restoration. Transactions of the Institute of British Geographers 29(3): 257-281.

Moerke, Ashley H. and Gary A. Lamberti. 2004. Restoring stream ecosystems: Lessons from a midwestern state. Restoration Ecology 12(3): 327-334.

[NRC] National Research Council. 1992. Restoration of aquatic ecosystems: science, technology, and public policy. Washington (DC): National Academy Press.

Palmer, M.A., E.S. Bernhardt, J.D. Allan, P.S. Lake, G. Alexander, S. Brooks, J. Carr, S. Clayton, C.N. Dahm, J. Follstad Shah, D.L. Galat, S.G. Loss, P. Goodwin, D.D. Hart, B. Hassett, R. Jenkinson, G.M. Kondolf, R. Lave, J.L. Meyer, T.K. O’Donnell, L. Pagano, and E. Sudduth. 2005. Standards for ecologically successful river restoration. Journal of Applied Ecology 42: 208-217.

45

Poff, N. LeRoy, J. David Allan, Mark B. Bain, James R. Karr, Karen L. Prestegaard, Brian D. Richter, Richard E. Sparks, and Julie C. Stromberg. 1997. The natural flow regime. BioScience 47(11): 769-784.

Riggs, H.C. 1968. Techniques of water-resources investigations of the United States Geological Survey: Some statistical tools in hydrology. Washington (DC): United States Printing Office.

Riggs, H.C. 1972. Techniques of water-resources investigations of the United States Geological Survey: Low-flow investigations. Washington (DC): United States Printing Office.

Smakhtin, V.U. 2001. Low flow hydrology: a review. Journal of Hydrology 240: 147-186.

[SHG] Swanson Hydrology and Geomorphology. 2004. Trout Creek Meadow Restoration: Geomorphic Monitoring Final Report 2001-2003. Santa Cruz, California.

Tague, C. and G.E. Grant. 2004. A geological framework for interpreting the low-flow regimes of Cascade streams, Willamette River Basin, Oregon. Water Resour. Res. 40: W04303, doi:10.1029/2003WR002629.

Trout Creek Gage #10336775 (Upper). USGS. National Water Information System. Retrieved on January 31, 2006 fromhttp://nwis.waterdata.usgs.gov/nwis/discharge?site_no=10336775&agency_cd=USGS&format=rdb&begin_date=10/01/1990&end_date=09/30/2005&period=

Trout Creek Gage #10336780 (Lower). USGS. National Water Information System. Retrieved on January 31, 2006 fromhttp://nwis.waterdata.usgs.gov/ca/nwis/discharge?site_no=10336780&agency_cd=USGS&format=rdb&begin_date=10/01/1960&end_date=09/30/2005&period=

Walsh, Christopher J., Tim D. Fletcher, and Anthony R. Ladson. 2005. Stream restoration in urban catchments through redesigning stormwater systems: looking to the catchment to save the stream. Journal of the North American Benthological Society 24(3): 690-705.

Ward, J.V., K. Tockner, D.B. Arscott, and C. Claret. 2002. Riverine landscape diversity. Freshwater Biology 47: 517-539.

[WBS] Western Botanical Services, Inc. 2003. Post Construction Vegetation Monitoring Report: Trout Creek Stream Restoration and Wildlife Enhancement Project. Prepared for the City of South Lake Tahoe. Reno, Nevada.

White, Michael D. and Keith A. Greer. 2004. The effects of watershed urbanization on the stream hydrology and riparian vegetation of Los Penasquitos Creek, California. Landscape and Planning 74(2006): 125-138.

Wigart, Russell. 2004. Trout Creek Final Report Summary (unpublished). City of South Lake Tahoe.

Wigart, Russell. 2004. Trout Creek groundwater monitoring data (unpublished). City of South Lake Tahoe. Received on January 20th, 2006.

46

Woessner, William W. 2000. Stream and fluvial plain groundwater interactions: Rescaling hydrogeologic thought. Groundwater 38(3): 423-4.

47

APPENDIX A

DATES AND VALUES FOR MISSING SNOW

DEPTH DATA

48

Date Adjusted Value10/26/61 to 10/28/61 011/17/61 to 11/30/61 010/14/62 to 10/16/62 0

11/3/63 to 11/7/63 06/7/64 0

6/10/64 06/5/65 to 6/8/65 0

11/12/65 011/19/67 to 11/27/67 0

6/7/68 011/23/68 3

11/18/69 to 12/7/69 05/16/70 0

11/1/70 to 11/6/70 611/13/70 to 11/26/70 8

6/2/71 to 6/13/71 010/23/71 to 10/31/71 0

5/7/72 to 5/9/72 05/18/73 to 5/19/73 0

10/7/73 010/27/73 to 10/29/73 011/9/73 to 11/10/73 011/4/75 to 11/5/75 0

4/30/76 04/13/77 010/28/79 04/30/81 05/20/81 09/27/82 0

11/11/82 to 11/17/82 136/27/83 010/24/85 011/9/85 05/20/87 05/26/87 04/5/88 0

4/15/88 05/6/88 0

10/31/90 011/6/90 011/26/95 0

11/1/96 to 11/5/96 011/7/96 to 11/22/96 511/24/96 to 12/5/96 14

9/19/97 010/7/97 010/29/97 011/13/97 210/31/98 110/31/01 06/9/02 06/9/04 0

- - Indicates adjusted snow depth values other than zero.

49

APPENDIX B

RESULTS OF THE SHAPIRO-WILK TEST FOR

NORMALITY

50

Dataset p-value

Pre-Restoration Peak Discharges at the Upper Gage 0.016*Post-Restoration Peak Discharges at the Upper Gage 0.20Pre-Restoration Peak Discharges at the Lower Gage 0.07Post-Restoration Peak Discharges at the Lower Gage 0.46

Pre-Restoration Residual Errors for August Baseflow Totals 0.36Post-Restoration Residual Errors for August Baseflow Totals 0.60

Pre-Restoration Residual Errors for September Baseflow Totals 0.41Post-Restoration Residual Errors for September Baseflow Totals 0.95

Pre-Restoration Residual Errors for Minimum 7-Day Running Averages in August and September 0.62

Post-Restoration Residual Errors for Minimum 7-Day Running Averages in August and September 0.71

Pre-Restoration Mean Slopes for the Recession Limb 0.004*Post-Restoration Mean Slopes for the Recession Limb 0.56

Pre-Restoration Max 15-Day Running Averages for Snow Depth 0.42Post-Restoration Max 15-Day Running Averages for Snow Depth 0.33

Pre-Restoration Min 15-Day Running Averages for Discharge 0.002*Post-Restoration Min 15-Day Running Averages for Discharge 0.17

*For p-values < 0.05, the dataset departs from normality and cannot be used in a linear model. In this case the Wilcoxon Sign-Rank Test will be used to test for statistical significance.

51

APPENDIX C

LINEAR MODEL RESULTS AND R2 VALUES

52

Dataset Adjusted R2 p-value

Pre-Restoration Discharge Relationship Between Upper and Lower Gages 0.97 2.2e-16***

Pre-Restoration Discharge Relationship Between Upper and Lower Gages for August 0.99 9.07e-11***

Post-Restoration Discharge Relationship Between Upper and Lower Gages in August 0.99 0.002***

Pre-Restoration Discharge Relationship Between Upper and Lower Gages in September 0.99 4.32e-10***

Post-Restoration Discharge Relationship Between Upper and Lower Gages in September 0.92 0.028**

Pre-Restoration Min 7-Day Running Average Relationship Between Upper and Lower Gages 0.96 4.96e-8***

Post-Restoration Min 7-Day Running Average Relationship Between Upper and Lower Gages 0.96 0.013**

Pre-Restoration Relationship Between Groundwater Depth and Discharge at Well T1W2 0.72 2.66e-10***

Post-Restoration Relationship Between Groundwater Depth and Discharge at Well T1W2 0.87 2.13e-7***

Pre-Restoration Relationship Between Groundwater Depth and Discharge at Well T4W3 0.25 0.002***

Post-Restoration Relationship Between Groundwater Depth and Discharge at Well T4W3 0.62 2.83e-4***

Pre-Restoration Relationship Between Groundwater Depth and Discharge at Well T4W4 0.24 0.003***

Post-Restoration Relationship Between Groundwater Depth and Discharge at Well T4W4 0.63 2.69e-4***

Pre-Restoration Relationship Between Groundwater Depth and Discharge at Well T5W3 -0.02 0.5

Post-Restoration Relationship Between Groundwater Depth and Discharge at Well T5W3 0.86 3.85e-7***

Pre-Restoration Relationship Between Groundwater Depth and Discharge at Well T5W4 0.13 0.024**

Post-Restoration Relationship Between Groundwater Depth and Discharge at Well T5W4 0.59 4.65e-4***

Pre-Restoration Relationship Between Groundwater Depth and Discharge at Well T6W2 -0.01 0.38

Post-Restoration Relationship Between Groundwater Depth and Discharge at Well T6W2 0.56 0.019**

For p-values < 0.1, 0.05, and 0.01, * represents 90% confidence, ** represents 95% confidence, and *** represents 99% confidence, respectively.

53

APPENDIX D

TYPE OF TESTS APPLIED AND RESULTS OF

STATISTICAL SIGNIFICANCE

54

Dataset F-Test p-value

Test Applied Applied Test p-value

Pre and Post-Restoration Residual Errors for August Baseflow Totals 0.022 Welch t-test 0.071*

Pre and Post-Restoration Residual Errors for September Baseflow Totals 0.087 Two Sample t-test 0.229

Pre and Post-Restoration Residual Errors for the Min 7-Day Running Average in August and September 0.114 Two Sample t-test 0.315

Pre and Post-Restoration Mean Slopes of the Hydrograph Recession Limb Non Normal Wilcoxon Sign-

Rank Test 0.525

For p-values < 0.1, 0.05, and 0.01, * represents 90% confidence, ** represents 95% confidence, and *** represents 99% confidence, respectively.

55

APPENDIX E

ADDITIONAL FIGURES

56

Additional Graphs for Hypothesis #1

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Figure 19. Boxplots of relative before and after restoration differences for August and September baseflow totals.

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Figure 20. Boxplots showing a ratio of before and after restoration differences for August and September baseflow totals.

57

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Figure 21. Boxplots of relative before and after restoration differences for the minimum seven-day running average for August and September baseflows.

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Figure 22. Boxplots showing a ratio of before and after restoration differences for the minimum seven-day running average for August and September baseflow.

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ABSTRACT OF THE THESIS

A Study of Hydrologic Response to the Restoration of Trout Creek, Central Sierra Nevada, California

byScott Alexander Valentine

Masters of Science in GeographySan Diego State University, 2006

Anthropogenic activities and poor land use management practices in riparian and aquatic ecosystems have altered flow regimes, causing ecologic damage and natural resource degradation throughout much of the United States. The importance of intact, functioning, and self-sustaining ecosystems has lead resource managers to seek out environmental solutions such as ecologic restoration. The reestablishment of hydrologic and ecologic processes is now seen as a primary goal of modern restoration science. Restoration methods involving channel modifications have been known to improve ecologic elements, but there has been little published research, as to how restoration influences hydrologic processes and flow regimes in these sensitive environments.

The restoration of Trout Creek provides an opportunity to study streamflow responses following the restoration of a 10,000-foot stream segment in Lake Tahoe, California. The proposed research will investigate (1) how streamflow hydrograph characteristics below the Trout Creek restoration site have been affected by restoration and (2) whether the relationship between groundwater and streamflow below the site has changed as a result of these ecosystem improvements. Streamflow gages located above and below the site, groundwater well monitoring data, and meteorological data collected before and after restoration will provide the necessary information needed to analyze the pre and post restoration flow regime.

Using methods that help to remove the variability caused by climate, sets of different hydrologic-based metrics will be estimated, and differences before and after restoration will be examined and tested for statistical significance. Pre-restoration data, and data derived from snowpack and the stream gage above the restoration site will be used to help build the regression models that will evaluate differences between predicted and observed datasets. The hydrograph characteristics that will be analyzed will include annual peak flow, August and September baseflow totals, and the minimum 7-day running average for August and September, and the mean slope of the recession limb. A graphical analysis of groundwater and streamflow data will also help to visually evaluate the changes caused by restoration.

The information gathered from this analysis will help researchers understand how channel modifications affect flow regimes in aquatic and riparian environments. This type of research will help to explain how ecosystems respond to restoration, but more importantly, this study may also provide the insight needed to broaden the scientific understanding of hydrologic and ecologic processes in riverine environments. An increase in research and reporting in restoration science will serve to advance the field, and contribute to the success of future restorations.