![](media/image1.wmf){width="1.625in" height="0.5986111111111111in"}

**Land Use Change and Effects on Water Quality and Ecosystem Health in
the Lake Tahoe Basin, Nevada and California**

By William Forney^1^, Lora Richards^2^, Kenneth D. Adams^3^, Timothy B.
Minor^3^, Timothy G. Rowe^4^,

J. LaRue Smith^4^, and Christian G. Raumann^1^

# Open-File Report 01-418

2001

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

## U.S. Department of the Interior

**U.S. Geological Survey**

\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_

^1^U.S. Geological Survey, Menlo Park, California

^2^Raytheon, work performed under U.S. Geological Survey, Contract
1434-CR-97-CN-40274

^3^Desert Research Institute, University and Community College System of
Nevada, Reno, Nevada

^4^U.S. Geological Survey, Carson City, Nevada

**Land Use Change and Effects on Water Quality and Ecosystem Health**

**in the Lake Tahoe Basin, Nevada and California**

# ABSTRACT

Human activity in the Lake Tahoe Basin has increased substantially in
the past four decades, causing significant impacts on the quality and
clarity of the lake\'s famous deep, clear water. Protection of Lake
Tahoe and the surrounding environment has become an important activity
in recent years. A variety of agencies, including the Tahoe Regional
Planning Agency, Tahoe Research Group of the University of California at
Davis, Desert Research Institute of the University and Community College
System of Nevada, U.S. Geological Survey (USGS), and a host of State
(both Nevada and California) and local agencies have been monitoring and
conducting research in the Basin in order to understand how the lake
functions and to what extent humans have affected its landscape and
ecosystem processes. In spite of all of these activities, there remains
a lack of comprehensive land use change data and analysis for the Basin.

A project is underway that unites the land cover mapping expertise of
the USGS National Mapping Discipline with the hydrologic expertise of
the Water Resources Discipline to assess the impacts of urban growth and
land use change in the Lake Tahoe Basin. Three activities are planned
over the next 3 years: (1) mapping the current and historic state of the
land surface, (2) conducting analysis to document patterns, rates, and
trends in urbanization, land use change, and ecosystem health, and (3)
assessing the causes and consequences of land use change with regard to
water quality and ecosystem health. We hypothesize that changes in the
extent of urban growth and the corresponding increases in impervious
surfaces and decreases in natural vegetation have resulted in severe
impacts on ecosystem health and integrity, riparian zones and water
quality over time. We are acting on multiple fronts to test this
hypothesis through the quantification of landscape disturbances and
impacts.

# INTRODUCTION

## Background

Situated in the Sierra Nevada Mountains, the Lake Tahoe Basin (fig. 1)
has recently been recognized as an Outstanding Natural Resource for its
water clarity and its depth; at 501 meters, it is the 2nd deepest lake
in the United States and the 11^th^ deepest lake in the world. The lake
is suffering from severe degradation of its natural resources as a
result of human disturbance (Boughton and others, 1997; Byron and
Goldman, 1987). Classified as an oligotrophic lake, cultural
eutrophication is most clearly demonstrated by the trend of decreasing
water clarity (Sullivan and others, 1996). The lake has averaged an
annual reduction of 0.46 meters from a depth of 32 meters in 1968 to
21.5 meters in 1995 (TRPA, 1996). In addition to the suspended sediments
in the lentic regions, water clarity is a function of the primary
productivity of the lake. As primary productivity is a function of
nutrient loading, an overall decrease in water quality (which can be a
proxy for sediment and nutrient inputs) can lead to a decrease in water
clarity.

California, and the Sierra Nevada in particular, are experiencing rapid
population growth that shows no signs of slowing. Between 1970 and 1990,
population in the region doubled with more than 40 percent of the growth
occurring in just four counties that encompass the Tahoe Basin: Washoe,
Douglas, Placer, and El Dorado. In the City of South Lake Tahoe, the
population increased from 12,921 in 1970 to 22,850 in 1998 (CDOF, 1999).
For the Sierra Nevada as a region, the population is projected to triple
between 1990 and 2040 (Duane, 1996), with a significant proportion of
the growth occurring in and around the Tahoe Basin. Population growth
results in urbanization, which directly and indirectly affects natural
systems and landscape processes. Already this growth has exacerbated the
tension between people and the environment.

> ![](media/image2.jpeg){width="5.580555555555556in"
> height="8.128472222222221in"}
>
> **Figure 1**. Map of Lake Tahoe Basin showing tributary watersheds and
> locations of Lake Tahoe Interagency Monitoring Program (LTIMP)
> stations.

Rapidly growing counties, and particularly those emerging from rural to
urban, frequently lack the resources to adequately monitor and forecast
the impacts of land development on biologic, hydrologic, and social
resources. To further complicate monitoring and forecasting in the Tahoe
Basin, the proximity of the Tahoe Basin to the Sacramento Valley and San
Francisco Bay Area results in significant tourist population growth
because of the variety of available recreational opportunities (such as
casino gaming, skiing, golfing, water sports, hiking, and camping). More
than 8 million people live within a few hours drive to Lake Tahoe
(Boughton and others, 1997). Although the Basin supports a year-round
population of approximately 60,000, on any given weekend the population
can swell to over 300,000, with an annual total of 22 million visitors
(McCarthy, 1997).

This rapid population growth has resulted in a variety of impacts on the
Tahoe ecosystem. Specifically, studies have documented the correlation
between human disturbance, exponentially increasing algal productivity,
and corresponding decreasing water clarity in Lake Tahoe (Byron and
Goldman, 1989). A variety of causes are recognized as drivers of this
cultural eutrophication in the Basin, including the loss of wetlands,
erosion due to

development on steep slopes, discharge from septic and sewer systems,
and airborne discharge from vehicles and wood-burning stoves. Increased
sediment and nutrient loading is understood to be a primary factor in
reduced water quality in tributaries, thus reducing water clarity in the
lake (Boughton and others, 1997).

Alteration of the landscape and other human-caused disturbances has been
shown to be important factors affecting mass transport (loading) of
principal plant nutrients (nitrogen and phosphorus) and sediment to the
lake (Loeb, 1988). The increase of bioavailable nutrients over time is
suspected as a principal cause for the increase in algal growth in the
lake, with a concomitant decrease in water clarity. Data collected by
University of California at Davis scientists show that the clarity of
the lake, as measured by Secchi disk, has been declining at a rate of
over 1 foot per year (Goldman, 1988). Furthermore, because of its
physical configuration and mean residence time of 700 years for water
(TRPA, 1996), Lake Tahoe effectively traps inputs of chemical
constituents, particularly nitrogen and phosphorus, making them
potentially available for biological recycling within the lake or for
entrainment in sediments. Sediment in tributary runoff is known to
reduce the clarity of receiving waters and act as a carrier in the
transport of certain nutrients, particularly phosphorus and iron.

## Description of the Study Area

Located in the Sierra Nevada Range, the Lake Tahoe Basin is part of the
Truckee River watershed that occupies parts of both eastern California
and western Nevada (fig. 1, inset). The headwaters of the Truckee River
system originate in the Sierra Nevada above Lake Tahoe. Sixty-three
watersheds covering a land area of 314 square miles (813 square
kilometers) flow into the lake (fig. 1). The lake itself covers 192
square miles (497 square kilometers). The lake is a natural feature that
has been converted to a reservoir through the installation of a small
dam at the lake's outlet on the western shore at Tahoe City. From this
outlet, the waters of Lake Tahoe flow north through the town of Truckee
and then northeast to the terminus of the Truckee River system at
Pyramid Lake, NV (CDWR, 1991; Rowe and Allander, 2000).

Vegetation in the Tahoe Basin is primarily coniferous forest with
alders, aspen, and willows common along the stream zones (Cartier and
others, 1993). Precipitation occurs mostly in the form of winter snow
and ranges from 25 inches to more than 60 inches, with a general
decrease from west to east (Twiss and others, 1971).

## Permanent Human Settlement in the Lake Tahoe Basin

Although Native Americans inhabited the Sierra Nevada for thousands of
years prior to European arrival, not until the middle of the 19th
century did permanent human settlement commence and the impacts of major
land use change begin to unfold on the land. The Washoe peoples of the
eastern Sierra Nevada and western Nevada hunted, fished, gathered, and
traded throughout the Tahoe Basin and surrounding areas, but their
population numbers and settlement patterns were not as land-altering as
the European-Americans who arrived during the middle of the 19th
century[^1] (Richards, 1999; Duane, 1996).

Since 1844, overland migrants and expedition parties had used the
north-central Sierra Nevada region surrounding the Tahoe Basin as a
transportation corridor for westward movement to California (Howard,
1998). For nearly 20 years, various wagon roads were constructed to
allow gold seekers and other travelers over the formidable mountains;
however, permanent settlement in the central Sierra Nevada was
nonexistent (Hinkle and Hinkle, 1997). Not until the economic incentives
associated with construction of the first transcontinental railroad
arrived did permanent settlement begin (mid-1860s) (TDHS, 1994).

Development in the form of logging operations initially commenced to
supply the construction of the Central Pacific. A short time later,
rapid expansion of silver mines of the Comstock Lode located at Virginia
City fueled the expansion and stability of the logging operations
(Richards, 1999). To support this extractive industry, small towns
appeared throughout the Basin to house and supply mill workers. The
permanent population of the Tahoe Basin and the surrounding north
central Sierra Nevada was very modest in size even though the extent of
its logging operations was not. Throughout the 19th century, lumbering
and associated industries were strong and profitable (Irons, 1885; NDWP,
1997). Construction of the railroad not only created a local timber
market, but its transcontinental ties enabled regional timber products
to be supplied throughout the West and beyond (Wilson, 1992).

Mining activities at Virginia City declined rapidly in the late 1880s
(Goldstein, 1988), causing logging operations to slow somewhat, but
ultimately logging remained a prosperous business through the end of the
century (TDHS, 1994). By 1910, the large and abundant forests that
blanketed the north-central Sierra Nevada were largely exhausted from
almost nonstop logging operations. In California and other parts of the
United States, a land and forest preservation movement took hold. As a
result, the Lake Tahoe area, in addition to forested lands throughout
the northern Sierra Nevada, was placed into National Forests (Omarzu,
1999). As logging slowed, permanent population growth also slowed and
even decreased. The railroad also experienced decline as improved roads
and the personal automobile became available and affordable (Richards,
1999).

Tourism had been a part of the Tahoe economy since the first years of
settlement in the mid-1860s. During the railroad era (1860s-1920s),
magazines and newspapers promoted the mountain scenery and recreation
activities on a regular basis (Howard, 1998; TDHS, 1994). Rail
accessibility provided by the Central Pacific and feeder lines tied
Sacramento and San Francisco area communities to the Tahoe Basin. During
the 1930s and 1940s, the Tahoe area experienced the beginnings of a
sustained increase in tourism as gaming was legalized in Nevada (NDWP
1997) and winter carnivals and ski tournaments were held in towns in and
around the Basin (TDHS, 1994). Roads were improved, including the
Lincoln Highway[^2], the Nation's first transcontinental highway (which
traveled mostly alongside the same route as the Central Pacific) and the
use of snow removal equipment commenced, keeping roads cleared during
the winter months (Placer County Chamber of Commerce and Auburn Chamber
of Commerce, written commun., 1952). The mood of an era heavily
dominated by the World Wars and the Great Depression caused a partial
delay in tourism until the middle to late 1940s when service people
returned home from war and disposable incomes increased (Richards,
1999).

Following the Second World War, California emerged as one of the
strongest economic forces in the world. Much of the State's recreation
and tourism to take a permanent and long-lasting hold on the Tahoe Basin
and the Sierra Nevada in general (Richards, 1999). One of the most
significant events in the Basin's tourism development was the selection
of Squaw Valley (on the northwest side of the Basin between Truckee and
Tahoe City) for the 1960 Winter Olympics. The Olympics promoted the area
in a previously unparalleled fashion (Scott, 1957). Some \$20 million
(Lantis and others, 1989) in State expenditures and several million in
private monies were spent to construct hotels, population benefited from
this prosperity, especially in the San Francisco Bay Area (Bank of
America, 1996; Wollenberg, 1985). The growth of personal prosperity,
combined with infrastructure improvements, set the stage for
restaurants, shops, and a host of other service facilities.
Transportation improvements were funded too, which resulted in the
reconstruction of the old highway into a new interstate (I-80), enabling
the traveler to journey from San Francisco to the Sierra Nevada in
approximately 4 hours (NDWP, 1997).

With the necessary transportation infrastructure in place and Northern
California's growing population and economic prosperity, tourism
activity in the Tahoe Basin, as well as the greater Reno-Tahoe-Truckee
area, has continued to rapidly increase since the 1960s. Permanent
population numbers have surged in the last 30 years, several ski areas
have been constructed or expanded, and numerous residential and
commercial operations have been built. Seasonal home and recreational
cottage construction has also accelerated, causing dramatic changes to
the local landscape (Richards, 1999). The Tahoe Basin now has the
largest permanent population in the entire Sierra Nevada (more than
60,000 permanent residents). The tourist economy, which had previously
been characterized by uneven seasonal activity (Lantis and others,
1989), has evened out; winter and summer are no longer the only seasons
experiencing heavy tourist traffic. Air transport has expanded, as have
the marketing and promotion of events such as ski competitions, golf
tournaments, mountain biking challenges, rodeos, and so on (Richards,
1999).

As the area has grown to accommodate more tourists and a greater
permanent population, various concerns over air, water, and other
natural resources have followed. As Rothman (1998, p. 155) states, "The
inherent problem of communities that succeed in attracting so many
people is that the presence of those very people \[has the potential
to\] destroy the cultural and environmental amenities that make the
place unique."

As the Lake Tahoe Basin is a tourist- and recreation-driven economy, the
tension between a healthy ecosystem and a healthy economy is present in
every land use decision. Understanding the connection between landscape
changes, water quality, and ecosystem processes is essential to bringing
an ecological and sustainable perspective to public policy decisions
that affect local communities.

# Water Quality

During the 1980s, Tahoe Research Group (TRG) at the University of
California at Davis researchers related the level of land disturbance in
sampled basins to water quality in these basins (Byron and Goldman,
1989). They found increased water quality degradation with increased
levels of land disturbance. In 1998, TRG researchers correlated historic
land disturbance with sedimentation rates through the analysis of
sediment cores. The analysis results of five sediment cores from Lake
Tahoe showed that the average mass sedimentation rate during the
Comstock logging era (1860 to 1900) was 0.043 (± 0.011) g/cm^2^/yr. By
comparison, the average mass sedimentation rate for the recent period
(1970 to 1990) was 0.027 (± 0.006) g/cm^2^/yr. Both these rates are
significantly higher than the average sedimentation rate of 0.009
(±0.004) g/cm^2^/yr that occurred during the intervening period (1900 to
1970). The fact that mass sedimentation rates and biogenic silica flux
decreased shortly after the logging disturbance ended is testimony to a
rapid landscape stabilization with second-growth forest. It also
indicates that Comstock logging produced a pulse disturbance. By
contrast, the disturbance from urbanization, in particular roads and
other impervious surfaces, could persist as a chronic perturbation for a
considerable time (Reuter and others, 1997).

The Tahoe Regional Planning Association (TRPA), the USGS, and the TRG
are monitoring sediment from streams and nutrient loads from both the
streams and ground water aquifers in the Basin. An assessment of the
water quality impacts in the Basin due to land use change will use the
archive of scientific data on stream water quality and discharge, and
ground water levels, quality, and flow paths collected as part of the
Lake Tahoe Interagency Monitoring Program (LTIMP). Various historical
data related to the hydrologic and limnologic properties of ground and
surface water in the Basin have been collected.

Using LTIMP data and other ancillary sources, Rowe and Allander (2000)
found that ground water contributed 40 percent of streamflow in the
Upper Truckee River to Lake Tahoe, and in Trout Creek ground water
accounted for 5 percent. Furthermore, nitrate, ammonia, and
orthophosphorus concentrations were found to be higher in ground water
samples than in surface water samples (Rowe and Allander, 2000). In Ward
Valley, ground water accounted for 16 percent of the creek's volume and
10 percent of the total precipitation within the catchment. More
importantly, with respect to the surface flow, ground water contributed
49 percent of the total nitrate and 44 percent of the total soluble
phosphorous loads to Lake Tahoe (Loeb and Goldman, 1979). Because of
these analyses of ground water influence in various regions in the Tahoe
Basin, it is important to acknowledge the need to incorporate subsurface
processes of nutrient loading.

From the analysis of LTIMP, it has been found that 75 percent of annual
stream loading of phosphorous occurs during spring snowmelt. For
phosphorous concentrations, 45-88 percent occurs as particulate
phosphorous occluded to silt and clay, dissolved organic phosphorous
comprises 6-42 percent, and phosphate accounts for 6 percent to 16
percent (Hatch, 1997). Because of the correlation of discharge,
phosphorous load, precipitation, basin area and slope, and impervious
cover; Hatch hypothesized that the human impact on stream ecology was
likely, particularly during high precipitation years.

Many projects are documented in the literature that assess impacts on
water quality and water-based ecosystems caused by agricultural land use
practices (Brakebill, 2001; Martin and others, unpublished presentation,
1999; Bradbury and Van Metre, 1997; Mattikalli and Richards, 1996).
Although minimal agricultural practices persist in the Basin,
fertilizers used on lawns and golf courses mimic some components of
agricultural practices. Furthermore, the rationale of these studies and
the techniques they adopt to link certain land uses with impacts on
ecosystems afford insight to techniques that can be adapted to the
scenario in the Tahoe Basin.

Overall, water quality assessment is often viewed as an integrated
environmental indicator of ecosystem function and stress (Berka and
others, 1995). One of the present needs in scientific investigations is
to link together the disparate facts and analyses such as the ones
previously mentioned. This is especially pertinent in systems such as
Tahoe that are balancing between natural preservation and human utility.
Understanding how the Lake Tahoe Basin and watersheds such as the Upper
Truckee River and Trout Creek have evolved through time and what changes
have occurred on these systems is critical for placing water quality
studies into context. Furthermore, this understanding provides valuable
information for present and future restoration efforts along these
systems and throughout the Tahoe Basin.

## Ecosystem Health

One way to analyze the health of the Lake Tahoe ecosystem is to assess
well-documented hydrologic indicators, such as water quality. From an
ecologic and biologic perspective, another way to characterize ecosystem
health is through ecosystem integrity. The form or integrity of an
ecosystem is directly linked to its function, and its function is
directly related to its health. In addition to the previous section on
water quality, the following discussion will further clarify this by
demonstrating how different land cover types can be sources and/or sinks
of nutrients and sediments that are transported through a hydrologic
system.

Using an inorganic nitrogen budget in Ward Valley, Coats and others
(1976) found that well-developed conifer stands can assimilate almost
all of the inorganic nitrogen, but not if they have been disturbed.
Furthermore, they found that nitrification is more related to the
carbon-nitrogen ratio and stand basal area than to the pH of litter
decay. They also found that mountain alder stands (*Alnus tenuifolia*)
release nitrate to soil water in the fall and early winter as they enter
into senescence. As another example of the interdependence between land
cover types and ecosystem function, ground water nitrogen fluxes have
been found to be greatest in alder-rich systems and lowest in
grass-meadow land cover types of riparian zones (Merrill, 2001).
Furthermore, soils in the Sierra Nevada have been found to be sinks for
ammonium, hydrogen, and sulfate (Williams and Melack, 1991).

Disturbances to Stream Environment Zones (SEZ) have shown to have
deleterious impact on an ecosystem's ability to function. Riparian
ecosystems can be categorized by their nutrient dynamics and water
quality effects through processes that exist in the stream channel and
the hyporehic zone (Merrill, 2001). SEZs and riparian buffers can trap
sediment and uptake nutrients, a function that is compromised when they
are drained, altered, or encroached upon (Weller and others, 1997).
Furthermore, the TRPA code of ordinances forbids development in SEZs
(TRPA, 1999).

Steep slopes and erodible soils are also biogechemically linked to
ecosystem dysfunction; disturbances to steep slopes and erodible soils
have been shown to increase nitrate, total and soluble phosphorous, and
suspended sediment (Byron and Goldman, 1989). Many steep, erodible
slopes have been disturbed by road development around the Basin.

In addition to land cover types, different types of land uses have been
tied to impacts on water quality and ecosystem health. Historically,
because of spray disposal of secondary-treated sewage effluent, Heavenly
Valley Creek (a Trout Creek tributary) was enriched in nitrate.
Furthermore, the remnant disconnected septic tanks and fertilizers
applied to lawns and golf courses can contribute to nitrate enrichment
in shallow ground water around South Lake Tahoe (Coats and Goldman,
1993).

## Role of Impervious Surfaces

The intensity of land uses is an important characteristic in assessing
change and impacts (Berka, and others, 1995). One way to assess land use
intensity is to look at the imperviousness of the surface of the
landscape. Impervious surfaces (paved or built-upon areas) deny or
inhibit the infiltration of water into the soil underneath. Impervious
surfaces may vary substantially with land use and stage of urban
development (Cablk and Minor, 2001); however, in the urban environment,
most impervious surfaces are either transportation (roads, sidewalks,
parking lots, and so on) or rooftops (residential, commercial,
industrial, and so on) (Sleavin and others, 2000). Impervious cover
estimates for anthropogenic surfaces are incorporated directly into
sediment-loading models and used in threshold analysis by TRPA, the
principal regulatory agency in the Basin (Cablk and Minor, 2001).

The mapping of impervious ground cover is important for understanding
the transport of pollutants, in particular, into water bodies (Prisloe
and others, 2001; Brun and Band, 1999; Civco and Hurd, 1997). Various
researchers with Project NEMO at the University of Connecticut have
conducted numerous studies related to land use, impervious surfaces,
stormwater runoff, and water quality (Prisloe and others, 2001; Sleavin
and others, 2000; Civco and Hurd, 1997). Because these researchers have
conducted such extensive and varied projects related to land use change
and water quality, their project will be consulted and used as a
framework for our own work.

Forney's (1999) earlier research on erosion and land use in the Upper
Truckee watershed demonstrates that the human need for housing,
infrastructure, commerce, and recreation has altered the rainfall-runoff
and erosion dynamics of the landscape. Urbanization truncates the
flowpath of precipitation as ground water systems are not recharged and
the water that enters the system circulates through the watershed more
swiftly and with greater volume (Arnold and Gibbons, 1996). The land
cover disturbance and its spatial pattern alter the vegetative
communities and increase nutrient loading and sedimentation (Binford and
Buchenau, 1993). Furthermore, depending on the infiltration capacity of
the soil, impervious coverage increases the volume and potential erosive
capacity of the overland runoff, gully erosion, and channel incision,
particularly in areas sensitive to disturbance, such as erosive soil
types, steep slopes, and riparian zones (Binford and Buchenau, 1993;
Arnold and Gibbons, 1996; McMahon and Cuffney, 2000; Prisloe and others,
2001).

As part of the impervious surface component of the land use mapping,
special attention will be paid to temporal road mapping in the Tahoe
Basin. Previous studies conducted as part of the USGS Urban Dynamics
Research Program have demonstrated the importance of studying the
temporal road network to understand the regional implications of urban
growth (Clark and others, 1996; Bell and others, 1995). A historical
understanding of road construction and the progression from unpaved
roads to highways is necessary to properly examine the patterns, rates,
and trends of urbanization in the Tahoe Basin. Roadways are significant
because of their ability to move people between places, and in the Tahoe
Basin, transportation history and evolution are a significant part of
the area's historical geography. Beyond its human geographical
component, the temporal road mapping will focus on impervious qualities
and the relationship of roads to landscape fragmentation.

As part of the Sierra Nevada Ecosystem Project, McGurk and Davis (1996)
used temporal land use and road mapping to assess the hydrologic effects
of 50 years of land management practices in the Camp and Clear Creek
watersheds. Their study concluded that disturbances to the natural
systems have been caused primarily by logging, road building, and
residential development. In a similar fashion, the transportation
features in the Upper Truckee River and Trout Creek watersheds will be
mapped to assess impacts on water clarity and quality, as well as
ecosystem health.

## Ongoing and Related Activities

The project builds upon and complements research activities both within
and outside the USGS. Using geographic analysis and spatially referenced
data in a geographic information system (GIS) environment, the USGS
Center for Science Policy (CSP) conducts research to integrate
multidisciplinary science to inform social issues and policy questions.
Research focuses on ways to translate science and synthesize disciplines
into quantifiable metrics, efforts that involve the use and weighing of
economic values, natural resource processes, and statistical analyses.

The project complements another CSP research project; in conjunction
with the Desert Research Institute (DRI), the CSP is assessing the
effectiveness and utility of the TRPA's land use system. Furthermore,
they are in the process of developing the Tahoe Constrained Optimization
Model for TRPA to inform growth and restoration policy decisions, as
well as conduct "what if" scenarios of optimal suites of development and
preservation based on regulated load goals (Bernknopf and Forney, 2000).
These load goals are motivated by nonpoint Total Maximum Daily Loads
(TMDL) implemented through the U.S. Environmental Protection Agency
(EPA) (Tracy and others, 2000). Part of this research depends on an
accurate assessment of land use and land cover for commercial,
residential, industrial, and undeveloped parcels. Such an assessment
would aid the valuation of nonmarket goods for economic models, allow
the incorporation of additional water quality models, and improve the
monitoring of TRPA's impervious coverage threshold.

The USGS Urban Dynamics Program analyzes land use change in urban
environments with a focus on understanding causes and consequences.
Activities involve describing the current and historical land surfaces,
monitoring changes to the landscape, understanding the processes causing
change, predicting the consequences of change, and improving the
application of scientific information with regard to policymakers,
scientists, public trust managers, and land use management agencies.
Earlier studies have demonstrated the utility of temporal and historical
mapping, geographic analysis, and growth modeling (Acevedo and others,
1999; Clarke and Gaydos, 1998; Clarke and others, 1997; Acevedo and
others, 1996; Crawford-Tilley and others, 1996; Clark and others, 1996;
Bell and others, 1995; Kirtland and others, 1994). The proposed work
enhances the USGS Urban Dynamics Program by addressing integrated
science issues and societal concerns. Specifically, this project
addresses societal concerns outlined as critical for research: urban
growth and quality of life, ecological integrity and ecosystem health,
water quality and quantity concerns, and increased accessibility to
scientific information for education and decision-making purposes.

This work enhances and leverages funding to a variety of Tahoe Basin
activities underway through local, State, and Federal agencies. Notable
projects include ongoing water quality research, DRI's impervious
surface mapping and shorezone change studies, U.S. Forest Service\'s
forest and roads mapping projects, TRPA\'s SEZ mapping, the City of
South Lake Tahoe's Trout Creek Restoration Project, and the ones
mentioned below.

The Northern Nevada District Water Resources Office of the USGS has
ongoing surface and subsurface water monitoring and research activities.
The district office has been actively involved in numerous water quality
studies in the Lake Tahoe Basin and oversees the coordination of Federal
activities in the Basin (Rowe and Allander, 2000; Rowe, 1999; Smith and
others, 1999; Rowe, 1998; Rowe and Stone, 1997; Boughton and others,
1997). Work is currently underway on a report titled, "Estimating Loads,
Yields, and Trends of Nutrients, Suspended Sediment, and Streamflow from
Developed and Undeveloped Watersheds Tributary to Lake Tahoe,
California- Nevada, 1980-98." As part of that study, nested estimates of
sedimentation loading through Incline Creek have been conducted (Tim
Rowe, WRD Carson City, personal communication, March 28, 2001). One of
the problems faced in this study is a paucity of accurate land use data
for the past and present.

Recognizing that rapid population growth presents many social and
natural resource challenges, collaborators at the Sierra Business
Council are currently involved in projects that look to accommodate
growth while maintaining the environmental quality and small town appeal
that lure vast numbers of visitors to the Sierra Nevada. Using
indicators of natural, financial, and social capital, the Sierra
Business Council developed the Sierra Nevada Wealth Index in an attempt
to gain an integrated understanding of the state of the region (Sierra
Business Council, 2000, 1999, 1996). Specifically, their Town Planning
Services unit is engaged in long range urban planning for 21 counties in
the region. The mapping and analysis results conducted as part of this
project will serve as critical input to their planning and education
goals.

# RESEARCH APPROACH

The general approach to the project is threefold: (a) conduct temporal
high-resolution land cover mapping and classification with historical
digital orthophoto quadrangles (HDOQ) and IKONOS satellite imagery; with
that information (b) correlate land use and land cover (LULC) dynamics
to changes in water quality, and (c) assess the current state of
ecosystem health in the study area. The second and third tasks are
somewhat interdependent and will be conducted once the first task is
completed (Chart 1).

Chart 1. Schematic of research approach.

+---------------------+-------------------------+----------------------+
| **IKONOS** (25      | **HDOQs** (pilot        | Fieldwork            |
| km^2^ scene)        | watersheds)             |                      |
+---------------------+-------------------------+----------------------+
| **- Obtain          | **- Produce HDOQs.**    | \- LULC class        |
| imagery.**          |                         | definition           |
|                     | \- Produce temporal     |                      |
| **- Classify        | LULC datasets.          | \- Accuracy          |
| impervious cover.** |                         | assessments          |
|                     | \- Temporal             |                      |
| \- Classify natural | transportation layer    | \- Clarify mixed     |
| cover.              |                         | pixel problems.      |
+---------------------+-------------------------+----------------------+

Year 1 of the project (FY2001) is focused on conducting these activities
in a pilot area in the southern part of the Tahoe Basin. Specifically,
efforts are concentrating on the administrative needs of the project
team, creating the HDOQs, obtaining related datasets, such as GIS
coverages and LTIMP data, gathering more literature and techniques of
analysis, analyzing existing LULC classification systems, constructing a
LULC cover classification system appropriate to the needs of the
project, and conducting field work to help with classification efforts.
In subsequent years, we will conduct analysis for the pilot area and
expand the mapping, correlation of datasets, and analysis activities to
the rest of the Basin.

Specifically, the first part of the project will map land cover and use
for 1940, 1969, 1987, and 1998 using HDOQs. A test area for 2000 will
also be mapped from IKONOS satellite imagery. We will assess the
benefits of using HDOQs versus high-resolution satellite imagery
(compare costs, ease of acquisition, and utility in deriving land cover
and use information). In addition, we will test the utility of
quantitative landscape ecology metrics that characterize the temporal
land cover/use data. The statistics derived from the imageries with a
software package called FRAGSTATS will be used for three purposes: (1)
track how the structure and pattern of the landscape has changed over
time, (2) test the ability to link those statistical changes to
significant changes in the water quality parameters of the LTIMP data,
and (3) assess how those changes have affected the proper functioning
condition of the ecosystem.

An analysis of historical and contemporary land cover will provide
useful metrics and information on the patterns, rates, and trends of
change. Consideration of the rates and directions of land use change
will provide an understanding of impacts on natural systems.
Consequently, the development of quantitative metrics that characterize
LULC data is essential. Rates and directions of change in natural
systems, often the result of human activity, are a critical aspect to
quantify and link to other parameters of ecosystem sustainability
(Elliot-Fisk and others, 1996).

## Hypotheses of Research

To understand landscape change in the Tahoe Basin, we must understand
the current state of the land, the forces of change that have created
the current landscape, and the causes and consequences of the change.
Overall, the proposed project will examine 5 key integrated hypotheses:

1.  Changes in impervious cover have changed the form of the hydrographs
    for watersheds of the Lake Tahoe Basin.

2.  Changes in natural land cover types have changed the water quality
    for the watersheds of the Lake Tahoe Basin.

3.  Riparian areas tend to be preferentially urbanized, and SEZs are
    deleteriously affected.

4.  Ecosystem health has been deleteriously affected by land cover
    change and increased impervious cover.

5.  IKONOS data can be used to make finer distinctions between land use
    and land cover types than DOQ imagery techniques.

### Potential Criteria for the Validation of Hypotheses

1.  For watersheds with LTIMP streamflow gages, changes in impervious
    cover are correlated with changes in the form of the hydrograph.

2.  Changes in the nutrient or sediment loading over time in watersheds
    with LTIMP water quality gages are statistically correlated to
    historic landscape patterns.

3.  Evidence of encroachment into the alluvial flood plain, SEZs by
    urbanization over time, and changes in channel morphology are
    identified.

4.  Changes in landscape metrics and evidence of disturbance to
    ecosystem health indicators, such as the GIS data of forest
    mortality, old growth tree stands, and animal habitat are studied.

5.  After the accuracy of the IKONOS classification is established
    through analysis and fieldwork, tables of classification successes
    and error matrices with LULC datasets will be derived from the
    HDOQs.

## Pilot Area

High-resolution land cover mapping for the Lake Tahoe Basin includes
current and historic land use mapping. Because the Tahoe Basin occupies
a large area (506 square miles), a pilot area focused on the Upper
Truckee River and Trout Creek watersheds near the city of South Lake
Tahoe (fig. 2) has been chosen to test the methods and techniques
proposed by this study. The pilot area was chosen because the two
largest drainage systems, with correspondingly high sediment yields,
flow through the area (McCarthy, 1997; Heyvaert, 1998). In addition,
different landscape conditions and varying levels of imperviousness,
which represent a range of water quality influences throughout the
Basin, are represented here: from remote natural terrain to the most
urbanized and impervious areas around the lake. In addition, the USGS
has been involved with surface water studies in these watersheds since
1960, providing the longest record of streamflow and surface water
quality data in the Basin (Rowe and Allander, 2000).

> ![](media/image3.png){width="4.096527777777778in"
> height="5.513194444444444in"}
>
> **Figure 2**. Map of the pilot study area consisting of the Upper
> Truckee River and Trout Creek watersheds in South Lake Tahoe.

The Upper Truckee River occupies 18 percent (56.5 square miles) of the
land area tributary to Lake Tahoe and contributes the largest volume of
surface water to the lake. The Upper Truckee also has the largest human
population and urban development of any watershed in the Basin and may
be a significant source of the increased nutrient and sediment loading
to the lake. Trout Creek is immediately adjacent to the Upper Truckee
River and together these two watersheds make up most of the South Lake
Tahoe area. Historically, Trout Creek was at times a tributary to Upper
Truckee River; however, development of the Tahoe Keys residential area
resulted in the channelization of the river, separating it from the
creek. Trout Creek is the second largest watershed in the Tahoe Basin
and occupies 13 percent (41.2 square miles) of the total land area
tributary to the lake (Rowe and Allander, 2000). Conceptually, the study
area focuses on the Upper Truckee and Trout Creek catchments because
those can be considered complete ecosystem units.

## Data Sources

The mapping component of the project is being conducted using two
primary data sources that have nested, yet different, spatial extents:
HDOQs derived from aerial photography and high-resolution IKONOS
multispectral imagery from Space Imaging Corporation (fig. 3). The HDOQs
are being produced through an internal cooperative agreement between the
research and data production sections at the USGS Western Geographic
Science Center in

> ![](media/image4.jpeg){width="6.027777777777778in"
> height="6.055555555555555in"}

**Figure 3.** IKONOS scene covering a part of South Lake Tahoe. The
image was acquired August 10, 2000, and covers an area of approximately
9.6 square miles (25 square kilometers). The false-color composite
consists of 4-meter resolution multispectral bands sharpened with the
1-meter resolution panchromatic band.

Menlo Park, Calif. The IKONOS imagery was purchased commercially under a
multi-licensing agreement with partners at TRPA and DRI.

We will explore the usefulness of using high-resolution IKONOS satellite
imagery for detailed impervious surfaces and natural land cover mapping.
The project contributes to the development of new techniques for using
IKONOS data for land use applications. A component of this work will be
to investigate the tradeoffs between multispectral semiautomated
classification techniques and traditional manual interpretation.

### Historical DOQs

Aerial photography has historically been the primary source for deriving
high-resolution land cover information, whereas satellite imagery, such
as Landsat MSS or TM, has been used for applications not requiring a
high degree of spatial resolution. There has traditionally been a
tradeoff between higher spatial resolution (aerial photography) and
higher spectral resolution (Landsat and similar satellite platforms). As
satellite-imaging systems evolve to yield higher resolution
multispectral sensors (such as IKONOS with a 1-meter resolution
panchromatic band combined with a 4-meter resolution multispectral
band), there will be less need for relying on aerial photographs. In
today's computer analysis and GIS environments, aerial photographs are
typically scanned and processed into orthophotographs and therefore
require more manual processing than satellite-based imagery. Although
orthophotos are an ideal photographic source for deriving vector
information, the focus of this study in deriving land cover information
may dictate raster-based data as being more useful.

A scarcity of land use and land cover data for the Tahoe Basin requires
a significant and comprehensive data collection effort to commence this
project. Historical aerial photographs have been obtained for the pilot
area for the following time periods: 1940 (fig. 4), 1969, and 1987. DOQs
at a 1-meter resolution currently exist for 1992 and 1998. The selected
temporal resolution uses the best available photograph sources and
captures the landscape approximately every decade, with an increased
time step in the past 20 years when stream gage data were more
consistently available.[^3] This temporal resolution will also provide
enough data to document channel migration rates and other occurrences
that have affected the SEZs. Phenomena such as stream incision or
changes in gradient will be difficult to document, nevertheless, the
measurement and quantification of changes within the pilot area SEZs
over the last 60 years will be information otherwise unavailable.

Historical photographs will be orthorectified and processed by USGS DOQ
production staff at the Western Geographic Science Center in Menlo Park.
There are challenges and nuances associated with producing standard USGS
products using nontraditional data sources; however, initial processing
has shown that the process can be accomplished with a high degree of
success. The promise of a program dedicated to a product to document
landscape change over the past 60+ years is enormous. The popularity of
the DOQs for the Tahoe Basin representing two temporal snapshots (1992
and 1998) has been tremendous. Researchers and regulatory in the Tahoe
Basin have responded positively to the plan to offer HDOQs.

In addition to being the primary data to derive historical and current
LULC classifications, the HDOQs produced for this project---as well as
existing Tahoe Basin DOQs for 1992 and 1998---will serve as the primary
source for developing the temporal transportation layer.[^4] The
database describing the road network will identify roads as present
during a given time period or not. It will also indicate if a road is
paved or unpaved. Railroads will also be mapped but classified as
separate features from regular roadways. Impervious cover coefficients
will be associated with different road types to obtain accurate area
estimations (see McGurk and Davis, 1996). This dataset will provide
quantitative information on landscape structure and will assist in the
interpretation of land cover classes.

### High-Resolution Multispectral Imagery

Although DOQs are an excellent high-resolution data source, the time and
energy required to manually process, interpret, and classify the data
are immense. Therefore, we are testing IKONOS imagery as a possible
substitute to traditional aerial photographs. Because IKONOS imagery
consists of both 1-meter panchromatic data as well as 4-meter
multispectral data, we will assess if IKONOS is easier, more efficient,
less expensive, and more informative than DOQs. Furthermore, because we
have chosen a classification scheme that focuses on land cover, we will
assess

the ease, efficiency, and accuracy tradeoffs between manual
classification of DOQs and digital classification of satellite imagery.

![](media/image5.png){width="6.497916666666667in"
height="6.026388888888889in"}

**Figure 4.** Aerial photograph showing a part of the South Lake Tahoe
area in 1940. This view is before the construction of the Tahoe Keys in
the Truckee Marsh complex and the other urbanization that we see today
in western and southern South Lake Tahoe.

Because of the high purchase costs for the Space Imaging IKONOS data, a
small scene was acquired for a 9.65-square-miles (25-square-kilometer)
area. The scene is centered on the South Lake Tahoe area and is
substantial enough to represent a variety of land cover types in the
area (and the Basin). Once IKONOS has successfully been used to conduct
necessary project research, we will evaluate a data purchase for the
entire pilot area and the rest of the land area in the Basin. Other
high-resolution multispectral satellites (such as Earthwatch) will also
be considered for integration into the project, especially if their
purchase costs are lower for the same spatial resolution. Once the
techniques for both the historical and contemporary mapping of the pilot
area have been finalized, mapping will be expanded to include the
approximately 800-km^2^-land surface of the Basin.

Using ERDAS IMAGINE software, we will pay particular attention will be
paid to the development of multispectral classification techniques for
the following:

-   Discerning urban uses within the impervious cover classification
    system, such as commercial, residential, infrastructure, and
    industrial land use types.

-   Locating regions that act as sources of nutrients and sediment, such
    as forest areas of prescribed burns and high tree mortality, road
    cuts on steep slopes, degraded stream channels, and other specific
    natural land cover types.

-   Distinguish between natural land cover ecotones such as conifer,
    deciduous, alpine meadows, and riparian (FGDC, 1996).

The results of this work will help to answer the fifth hypothesis and
compare the utility of the two (the IKONOS --based and the HDOQ-based)
LULC classification system to other systems, such as the USGS National
Land Cover Dataset (NLCD), Gap Analysis, the U.S. Department of
Agriculture Watershed Assessment vegetation layer, and other Landsat-
and SPOT-derived systems. The utility will orient on classifications
that are indicative of relevant ecosystem processes. From previous
studies, it appears that IKONOS can resolve impervious surfaces to a
much greater accuracy than Landsat-based classification systems (Cablk
and Minor, 2001). Furthermore, the utility of IKONOS imagery to discern
natural cover types will be compared with that of HDOQs.

## Classification Considerations

Various potential classification schemes were considered for the
temporal LULC mapping component of this project. Some schemes
categorized LULC on the basis of imperviousness (Prisloe and others,
2001; Botsford and others, 2000; Sleavin and others, 2000; Crnojacki and
others, 1997; Civco and Hurd, 1997; Khorram and others, 1992) while
others concerned themselves with a mixture of land use and land cover
without an emphasis on imperviousness (Lorenz and Stoner, date unknown;
USGS, November 1999; NOAA-CSC, 1995; Anderson and others, 1976).

The classification of urban data must be sensitive to the research and
policy needs of others; therefore, we must go beyond the simple
classification of urban versus nonurban. A more detailed classification
of urban lands that distinguishes between residential, commercial,
industrial, and other uses is essential for understanding how urban
areas are growing and changing. Therefore, an integrated approach to
assembling land cover and land use data is essential. Urban data that
distinguishes between impervious and nonimpervious surfaces are critical
in order to meet the needs of water quality researchers (Civco and Hurd,
1997; Berka and others, 1995). The correlation of impervious cover with
associated land use is an important regulatory evaluation need of TRPA.
If planners and other local land use decision-making agencies such as
TRPA can combine their parcel information with actual land use data,
they can have a better understanding of the carrying capacity of the
land.

A hierarchical classification system will be used for land cover
mapping, which allows the classification of major land use types (urban,
forest, agriculture, rangeland, wetlands, water, and barren lands), as
well as minor land use types (residential, commercial, industrial, and
so on) and impervious surfaces (low-, medium-, and high-intensity
imperviousness) (Wilke and Finn, 1996; Lillesand and Kiefer, 1994;
Chuvieco and Congalton, 1988; and Anderson and others, 1976). To
maintain consistency with other land use and land cover mapping
activities of the USGS National Mapping Program, we will draft and
refine a hierarchical classification scheme that is a subset of the
scheme developed for the USGS National Land Cover Dataset (NLCD) 2000
mapping effort. This approach allows the capture of high-resolution
features from the aerial photographs in a system that can be aggregated
and compared on a regional basis. A stratified cluster sampling strategy
(Urban, 1999) will be applied through fieldwork with global positioning
system (GPS) units. This efficient sampling scheme will be used to
determine classification accuracy, and fix mixed-pixel problems.

## Analysis Techniques

Landscape ecology, as a relatively new discipline, focuses on broad
spatial scales and the ecological effects of the spatial patterning of
ecosystems. Specifically, it considers (1) the development and dynamics
of spatial heterogeneity, (2) the interactions and exchanges across
heterogeneous landscapes, (3) the influences of spatial heterogeneity on
biotic and abiotic processes, and (4) the management of spatial
heterogeneity (Pielou, 1975). The focus of the discipline is on
landscapes, which can be described by three primary components:
structure, function, and change.[^5] Quantitative methods are used to
compare, contrast, and track changes in and between landscapes, and to
relate these patterns to ecological function (Turner, 1989). This is the
most difficult part; to go beyond simply describing a landscape to
actually linking systems with appropriate metrics to determine
statistical relationships that can inform the tensions between land use
change, anthropogenic needs, and natural phenomena.

The ability to quantify landscape structure is a prerequisite to the
study of landscape function and change (McGarigal, 2001). To quantify
landscape structure, we will use spatial pattern analysis software known
as FRAGSTATS\*Arc. Landscape ecology emphasizes the study of landscape
patterns, the interactions among patches within a landscape mosaic, and
how these patterns and interactions change over time. FRAGSTATS\*Arc
provides metrics relating this information using spatial data such as
that being developed for this study. FRAGSTATS\*Arc metrics of interest
include area calculations, patch density, size and variability, edge and
shape quantifications, diversity values, and contagion and interspersion
metrics.

An additional part of this analysis will be to provide a socioeconomic
perspective of the motivators of urban growth. Population and related
socioeconomic data for the basin will be collected from literature and
other sources, including the U.S. Census and the California Department
of Finance. This ancillary information will be gathered with respect to
the geography and temporality of mapping activities.

## Analysis of Water Quality

Long-term data on the streamflow nutrient concentrations and suspended
sediment concentrations for streams entering the lake have been
collected since 1978, and streamflow volume measurements have been
collected since 1961. LTIMP, comprising a host of agencies, has
developed a significant database of continuous streamflow, nutrient and
suspended sediment concentrations, and water quality data for 10 sites
in 10 basins.[^6] LTIMP has also collected instantaneous streamflow
measurements with nutrient and suspended sediment concentrations, as
well as water quality data for an additional 14 sites. LTIMP hydrologic
and water quality data from water years 1980 to the present are also
readily accessible in electronic format in USGS databases. This project
will attempt to relate temporal changes in land use and spatial
differences in various physical factors to changes in nutrient and
suspended sediment concentrations, streamflow, temperature, and other
water quality characteristics.

In an attempt to test the first hypothesis, we will construct a water
balance to assess the function of the hydrologic cycle through time.
Starting in 1961, the gage at the base of Heavenly Valley (table 1)
possesses the longest streamflow record in the LTIMP database. This will
be used to assess how the interactions between runoff, infiltration,
evapotranspiration, and ground water have evolved through time.

In addition to creating a water balance, we will construct two
hydrographs from similar climatic and storm events: one from the 1960s
and one for the present. These hydrographs will then be related to
changes in impervious coverage area above and adjacent to the gages in
question. The theory regarding changes in hydrographs caused by
increasing impervious coverage is well documented (Borchardt and
Sperling, 1997; Chou and others, 1988; EPA, 1983), but empirically it
has not been well tested in the Tahoe Basin. As the theory states, a
hydrograph under urbanized conditions should have (a) a shorter time
interval between the inception of and peak flow, (b) a greater volume of
water at peak flow, and (c) a faster falling limb of the graph as the
precipitation event ends. A comparison of the two hydrographs will
provide a measure of impacts caused by land use change.

Part of the work in assessing the hydrologic impacts of land use change
will be to incorporate the Soil Conservation Service (SCS)
rainfall-runoff techniques to quantify increases in runoff associated
with urbanization (Chou and others, 1988; McClintock and others, 1995;
Bhaduri and others, 1997). This technique depends on the Curve Number
(CN) values associated with particular hydrologic soil groups, which can
be calculated from the NRCS soils coverage (table 3). In a GIS, excess
rainfall (*P~e~*) can be calculated using the equation:

> *P~e~ =* (*P-* 0.2*S*)^2^ / (*P* + 0.8*S*)

**Table 1**. Periods of record for daily streamflow, water-quality, and
suspended sediment data at current and historic USGS gaging stations and
sampling sites for Upper Truckee River and Trout Creek watersheds.
Adapted from Rowe and Allander (2000). (Water quality: NUT indicates
instantaneous nutrient samples; SC indicates daily specific conductance;
WT indicates daily water temperature. Suspended sediment: DAILY
indicates daily suspended sediment; INST indicates instantaneous
suspended sediment discharge \[abbreviations from U.S. Forest
Service\].)

+-----+-----------+-----------+----------+-----------+---------------+
| **S | **Site    | **Station | **Daily  | **Water   | **Suspended   |
| ite | Name**    | No.**     | Stre     | Quality** | Sediment**    |
| No  |           |           | amflow** |           |               |
| .** |           |           |          |           |               |
+-----+-----------+-----------+----------+-----------+---------------+
| 6   | Upper     | 10336610  | 1972-74, | WT:       | DAILY:        |
|     | Truckee   |           | 77, 78,  | 1972-74,  | 1972-74, 78,  |
|     | River at  |           | 80       | 78, 80-92 | 80-92         |
|     | Hwy 50,   |           | -current |           |               |
|     | South     |           |          | S         | INST:         |
|     | Lake      |           |          | C:1981-83 | 1993-current  |
|     | Tahoe     |           |          |           |               |
|     | (gage)    |           |          | NUT:      |               |
|     |           |           |          | 199       |               |
|     |           |           |          | 3-current |               |
+-----+-----------+-----------+----------+-----------+---------------+
| 17  | Upper     | 103366092 | 1990     | NUT:199   | INST:         |
|     | Truckee   |           | -current | 0-current | 1990-current  |
|     | River at  |           |          |           |               |
|     | Hwy 50    |           |          |           |               |
|     | above     |           |          |           |               |
|     | Meyers    |           |          |           |               |
|     | (gage)    |           |          |           |               |
+-----+-----------+-----------+----------+-----------+---------------+
| 20  | Upper     | 10336600  | 1        |           |               |
|     | Truckee   |           | 961-1986 |           |               |
|     | River     |           |          |           |               |
|     | near      |           |          |           |               |
|     | Meyers    |           |          |           |               |
|     | (inactive |           |          |           |               |
|     | gage)     |           |          |           |               |
+-----+-----------+-----------+----------+-----------+---------------+
| 43  | Upper     | 10336580  | 1990     | NUT:      | INST:         |
|     | Truckee   |           | -current | 199       | 1990-current  |
|     | River at  |           |          | 0-current |               |
|     | S. Upper  |           |          |           |               |
|     | Truckee   |           |          |           |               |
|     | Road      |           |          |           |               |
|     | (gage)    |           |          |           |               |
+-----+-----------+-----------+----------+-----------+---------------+
| 49  | Trout     | 10336790  |          | WT:       | DAILY:        |
|     | Creek at  |           |          | 1972-74,  | 1972-74,      |
|     | Hwy 50,   |           |          | 89-92     | 89-92         |
|     | South     |           |          |           |               |
|     | Lake      |           |          | NUT:      | INST:         |
|     | Tahoe     |           |          | 199       | 1993-current  |
|     |           |           |          | 3-current |               |
+-----+-----------+-----------+----------+-----------+---------------+
| 52  | Trout     | 10336780  | 1961     | WT:       | DAILY:        |
|     | Creek at  |           | -current | 1972-74,  | 1972-74, 78,  |
|     | Martin    |           |          | 78,       | 80-85, 88     |
|     | Ave near  |           |          | 80-85, 88 |               |
|     | Tahoe     |           |          |           | INST:         |
|     | Valley    |           |          | SC:       | 1990-current  |
|     | (gage)    |           |          | 1981-83   |               |
+-----+-----------+-----------+----------+-----------+---------------+
| 57  | Trout     | 10336775  | 1990     | NUT:      | INST:         |
|     | Creek at  |           | -current | 199       | 1990-current  |
|     | Pioneer   |           |          | 0-current |               |
|     | Trail     |           |          |           |               |
|     | near      |           |          |           |               |
|     | South     |           |          |           |               |
|     | Lake      |           |          |           |               |
|     | Tahoe     |           |          |           |               |
|     | (gage)    |           |          |           |               |
+-----+-----------+-----------+----------+-----------+---------------+
| 68  | Trout     | 10336770  | 1990     | NUT:      | INST:         |
|     | Creek at  |           | -current | 199       | 1990-current  |
|     | U.S.      |           |          | 0-current |               |
|     | Forest    |           |          |           |               |
|     | Service   |           |          |           |               |
|     | Road      |           |          |           |               |
|     | 12N01     |           |          |           |               |
|     | near      |           |          |           |               |
|     | Meyers    |           |          |           |               |
|     | (gage)    |           |          |           |               |
+-----+-----------+-----------+----------+-----------+---------------+

Where *P* equals precipitation and *S* equals some potential maximum
retention by soils. The precipitation can be obtained from the PRISM
data (PRISM precipitation maps, 2001) or SNOWTEL gages. Forest and
meadow infiltration rates for some soils in the Tahoe Basin have been
estimated (Burcar and others, 1994). For values of *S* that could not be
obtained from the literature, they can be estimated with the help of the
following equation:

> *S =* 1000/CN -- 10

Then, using the appropriate CN values, we could compare the natural
cover-type calculation of excess rainfall with the excess rainfall from
urbanization (Forney, 1999).

Mass balance equations have been used to derive concentration-discharge
relations under conditions of varying concentration, inflow, discharge,
volume, and dissolved load. Studies in the Tahoe Basin, particularly
Upper Truckee River and Trout Creek, have indicated that models can be
used to distinguish anthropogenic nitrate sources from the ionic pulse
associated with early snowmelt (Coats, 1992). These models, however, are
sensitive to variations in discharge: in base flow years with normal
spring-melt runoff conditions, discharge is more consistent, therefore
linear regressions can explain more of the variation. In nonbase flow
years, linear relationships are less likely to apply and alternative
methods will need to be considered. The spatially explicit, export
coefficient methodology presented by Mattikalli and Richards (1996)
offers suggestions on how to improve upon mass balance equations to
estimate surface water quality changes in response to land use changes.

Furthermore, these regression models do not account for the influence of
spatial pattern upon the flow of matter and nutrient through a landscape
and the interactions of the stream courses with the upland land surface
(Turner, 1989). In an attempt to test the second hypothesis, we will
investigate the utility of the landscape metrics to find statistically
significant relationships between land use change and alterations in
parameters of water quality. Class and landscape metrics of interest are
percentage of cover type, area, number of patches, mean patch size, and
patch richness. Water quality parameters of interest are stream
discharge, suspended sediment, water temperature, and bioavailable
nitrogen, phosphorous, and iron.

## Analysis of Ecosystem Health

There is little quantitative information concerning historical changes
to the SEZs in the South Lake Tahoe area. Aerial photography is one of
the only available sources for assessing the changes that have affected
SEZs. As we understand changes to SEZs, we better equip ourselves with
the knowledge of how human activities are affecting watersheds within
the Tahoe Basin and the region as a whole (Weller and others, 1997).

Preliminary comparisons between the georectified photographs and
existing DOQs of the South Lake Tahoe area indicate that changes to SEZs
have occurred over the last 60 years. These changes include channel
migrations and avulsions, changes to the structure and composition of
riparian vegetation, channelization projects, impoundments, and
development within the SEZs. Each of these changes has implications for
the water quality of the fluvial systems and for the quantity of
sediment and nutrients delivered to Lake Tahoe from these systems. Once
HDOQs are prepared for additional analysis, changes in the SEZs along
the Upper Truckee River and Trout Creek will be quantified with such
metrics as channel length, area, density, and sinuosity (Binford and
Buchenau, 1993). These metrics will then be correlated with water
quality data prepared by Kilroy and others (1997) and the LTIMP gages
listed in Table 1 to test whether a significant relationship between SEZ
changes and water quality changes exists. Given the aerial extent of
historical riparian zones, area of disturbance and percentage of change
metrics will be compiled to test the third hypothesis of this project.

One of the necessary components of this analysis is to derive metrics
that can be compared across time and the two resolutions of data
sources. Because of their correlation, 55 landscape metrics can been
narrowed down to 6 (Riitters and others, 1995): dominance, contagion,
fractal dimension from perimeter/area, average patch perimeter/area
ratio, average patch/perimeter/area orthogonally adjusted, and number of
classes. Of those, the EPA maintains that changes in landscape patterns
are best characterized by three metrics: contagion, fractal dimension,
and dominance (EPA, 1994). Their application, however, may not be
similar to ours, and those metrics may miss water quality metrics and
ecosystem health indicators. In 1998, Frohn found that contagion and
fractal dimension were not appropriate metrics owing to problems with
perimeter/area relationships, regression estimates, consistency,
diversity, and spatial resolution, and he suggested two alternative
ones: Patch-Per-Unit (PPU) area and Square-Pixel (SqP). He compared the
four metrics in five experiments dealing with spatial resolution,
spatial gradients, vertical gradients, and temporal gradients. For four
of these experiments, he used study sites in the Sierra Nevada,
Washington, DC, Rondonia, Brazil, and Ouro Preto, Brazil. The metrics
discussed here will help elucidate some of the changes in structure over
time (Dunn and others, 1990), and metrics such as contagion, PPU area
and dominance have direct relevance to ecosystem health as they are a
measure of integrity, structure, and function.

It has been suggested that human-influenced systems exhibit simpler
patterns than natural landscapes. For example, smaller patch size and
simpler fractal dimension have been proved to indicate a fragmented
structural pattern between old growth landscapes of eastern hemlock
(*Tsuga canadensis*), sugar maple (*Acer saccharum*), and yellow birch
(*Betula allegheniensis*) (Mladenoff and others, 1993). The assertions
of Mladenoff and others (1993) are in direct contradiction with Frohn
(1998), as well as statements made elsewhere in the literature (Krummel
and others, 1987, O'Neill and others, 1988, Turner and Ruscher, 1988).
With the consistent classification systems and datasets that will be
produced from the HDOQs, the ability to measure landscape disturbance
will be tested by a metric of fractal dimension, as well as its measure
of complexity over time.

Furthermore, metrics such as density of urban lands, urbanized acreage,
and total miles of roads (paved versus unpaved) will be compiled.
FRAGSTATS\*Arc software will be used to derive metrics related to the
basin-wide landscape, land cover types within landscapes, as well as
specific patches of cover type within a landscape (Nautilus,
12/12/2000). In addition, other metrics suggested previously will be
used to test the fourth hypothesis; this testing will reveal the ability
of these metrics to characterize landscape pattern and change over time
and will show how that characterization relates to changes in natural
and anthropogenic cover types.

Given the historical and current structural integrity of the landscape,
key indicator species can be used to assess the function of an
ecosystem. Biologically significant species that have been recognized as
sensitive, threatened, endangered and/or used as a management indicator
species are listed in table 2 (Bish and Kundert, unpublished report for
TRPA).

**Table 2.** Biologically significant species found in the Lake Tahoe
Basin. Compiled for purposes of habitat management and metapopulation
dynamics.

+-----------------+-----------------+-----------------+-----------------+
| **Plants**      | **Amphibians**  | ##              | **Birds**       |
|                 |                 | ####### Mammals |                 |
+-----------------+-----------------+-----------------+-----------------+
| Galena Creek    | Mount Lyell     | Black bear      | American        |
| rockcress       | salamander      | (*Ursus         | peregrine       |
| (*Arabis        | (*Hydromantes   | americanus*)    | falcon (*Falco  |
| rigidissima*)   | platycephalus*) |                 | peregrinus      |
|                 |                 |                 | anatum*)        |
+-----------------+-----------------+-----------------+-----------------+
| Long-petaled    | Mountain        | American marten | Bald eagle      |
| lewisia         | yellow-legged   | (*Martes        | (*Haliaeetus    |
| (*Lewisia       | frog (*Rana     | americana*)     | leucocephalus*) |
| longipetala*)   | muscosa*)       |                 |                 |
+-----------------+-----------------+-----------------+-----------------+
| Soda Springs    |                 | Mule deer       | Blue grouse     |
| silene (*Silene |                 | (*Odocoileus    | (*Dendragapus   |
| invisa*)        |                 | hemionus*)      | obscurus*)      |
+-----------------+-----------------+-----------------+-----------------+
| Star draba      |                 | Sierra Nevada   | California      |
| (Draba          |                 | red fox         | spotted owl     |
| asterophora)    |                 | (*Vulpes vulpes | (*Strix         |
|                 |                 | necator*)       | occidentalis    |
|                 |                 |                 | occidentalis*)  |
+-----------------+-----------------+-----------------+-----------------+
| Tahoe draba     |                 | Fisher (*Martes | Golden eagle    |
| (Draba          |                 | pennanti)*      | (*Aquila        |
| asterophora     |                 |                 | chrysaetos*)    |
| 'Macrocarpa')   |                 |                 |                 |
+-----------------+-----------------+-----------------+-----------------+
| Tahoe           |                 |                 | Northern        |
| yellow-cress    |                 |                 | goshawk         |
| (*Rorippa       |                 |                 | (*Accipiter     |
| subumbellata*)  |                 |                 | gentiles*)      |
+-----------------+-----------------+-----------------+-----------------+
|                 |                 |                 | Osprey          |
|                 |                 |                 | (*Pandion       |
|                 |                 |                 | haliaetus*)     |
+-----------------+-----------------+-----------------+-----------------+
|                 |                 |                 | Pileated        |
|                 |                 |                 | woodpecker      |
|                 |                 |                 | (*Dryocopus     |
|                 |                 |                 | pileatus)*      |
+-----------------+-----------------+-----------------+-----------------+
|                 |                 |                 | Willow          |
|                 |                 |                 | flycatcher      |
|                 |                 |                 | (*Empidonax     |
|                 |                 |                 | traillii*)      |
+-----------------+-----------------+-----------------+-----------------+

The plants and animals of concern are each associated with particular
habitats. Given the extent and quality of remote sensing imagery, the
plants can be mapped and their disturbance documented over time. Remote
sensing imagery cannot identify the occurrence of animals, but each
animal has a preferred habitat that can be identified and assessed
(National Gap Analysis Program). Furthermore, the Watershed Assessment
gathered goshawk and California spotted owl sightings in the Basin that
can complement and field-verify the determinations of preferred habitat.

With an improved understanding of local faunal behavior, the structure
of the landscape pattern (both historical and current) can be assessed
to determine its historical, present, and future ability to support
viable populations and consider metapopulation dynamics (Urban and
Smith, 1989; Stacey and Taper, 1992; McGarigal and Marks, 1994; and
Keitt and others, 1997). Furthermore, the citing locations could be used
linear regression techniques to create a basin-wide probability map of
the likelihood of finding those species in a given location (Bernknopf
and others, 2001). This could then be compared with historical, current,
or planned areas of urban development and used to further test the
fourth hypothesis.

As part of the assessment of ecosystem health, patterns of human
development and environmental disturbance over time will be compared
with existing GIS coverages from the recent past (Table 3). These
coverages will aid in the presentation and synthesis of disparate
information. Furthermore, the data will be investigated for their
potential utility to inform the assessment of ecosystem health. Some
initial suggestions for using these data follow.

**Table 3.** Potentially relevant GIS data for ecosystem health
assessment; from Whitley, 2001; USGS, 2001; Ca Gap, 2001; California
Tahoe Conservancy, 2001; Murphy and Knopp, 2000; and Cartier and others,
1993.

+--------------------------------+----------+-------------------------+
| **GIS Data**                   | **       | **Resolution/Scale**    |
|                                | Format** |                         |
+--------------------------------+----------+-------------------------+
| Digital elevation models       | Raster   | 10 meter                |
+--------------------------------+----------+-------------------------+
| Land cover (NLCD)              | Vector   | 30 meters               |
+--------------------------------+----------+-------------------------+
| Land cover/land use,           | Vector   | MMU= 100 ha upland, 40  |
| vegetation (CA Gap)            |          | ha wetland              |
+--------------------------------+----------+-------------------------+
| Vegetation (Watershed          | Vector   | 30 meters               |
| Assessment)                    |          |                         |
+--------------------------------+----------+-------------------------+
| Streams                        | Line     | 1:24,000                |
+--------------------------------+----------+-------------------------+
| NRCS soils^+^                  | Vector   | 1:24,000                |
+--------------------------------+----------+-------------------------+
| Stream Environment Zones       | Vector   |                         |
| (2001)                         |          |                         |
+--------------------------------+----------+-------------------------+
| Riparian assessment from       | Vector   | 1 meter                 |
| videography                    |          |                         |
+--------------------------------+----------+-------------------------+
| Soil erosion hazard/fire risk  | Raster   | 30 meters               |
+--------------------------------+----------+-------------------------+
| Old growth forests/fire risk   | Raster   | 30 meters               |
+--------------------------------+----------+-------------------------+
| Urban areas/fire risk          | Raster   | 30 meters               |
+--------------------------------+----------+-------------------------+
| Fuel model                     | Raster   | 30 meters               |
+--------------------------------+----------+-------------------------+
| Natural fire ignitions         | Point    |                         |
+--------------------------------+----------+-------------------------+
| Human fire ignitions           | Point    |                         |
+--------------------------------+----------+-------------------------+
| #### Controlled                | Vector   |                         |
| and proposed burn areas (1998) |          |                         |
+--------------------------------+----------+-------------------------+
| Goshawk sightings              | Point    |                         |
+--------------------------------+----------+-------------------------+
| California spotted owl         | Point    |                         |
| sightings                      |          |                         |
+--------------------------------+----------+-------------------------+
| #### Wi                        | Vector   |                         |
| llow-flycatcher habitat (1999) |          |                         |
+--------------------------------+----------+-------------------------+
| Stream crossings and culvert   | Point    |                         |
| locations (1998)               |          |                         |
+--------------------------------+----------+-------------------------+
| Ecological unit inventory      | ###      |                         |
|                                | # Vector |                         |
+--------------------------------+----------+-------------------------+
| Forest mortality over time     | Raste    |                         |
|                                | r/Vector |                         |
+--------------------------------+----------+-------------------------+
| Sierra Nevada old growth       | Raste    |                         |
|                                | r/Vector |                         |
+--------------------------------+----------+-------------------------+
| Bailey Land Capability System  | Vector   | 1:24,000                |
+--------------------------------+----------+-------------------------+

^+^ The NRCS has updated its soil survey with a focus on beach and
alluvial soils.

To understand an ecosystem, we must understand the risks, impacts and
likelihood of historic and current disturbance regimes (Landres and
others, 1999). Given the encroachment of human structures and build out
zones, the data could be compared with the soil erosion and fire hazard
risk map produced for the Lake Tahoe Watershed Assessment. (for
documentation, see Chap. 5 of the Watershed Assessment). Also, the
fuel-loading model, along with GPS locations of historical lightning
strikes and human-triggered ignitions, can be used to create a
likelihood of occurrence. Furthermore, the ignition points can provide
information about the relation of the historical fire-disturbance regime
to the system and can be used to assess the increased disturbance from
anthropogenic sources. Finally, given a model of fire behavior and
linear regression techniques, a probability map of fire occurrence can
be calculated (Bernknopf, unpublished report, 2001). Natural and human
disturbances need to be understood to provide a comprehensive picture of
the stage upon which natural resource management is acted out.

# STUDY RESULTS

The USGS maintains a Website resource for the Basin known as the Lake
Tahoe Data Clearinghouse
([http://tahoe.usgs.gov](http://tahoe.usgs.gov/)). This established
Website will serve as the primary mechanism for the release of data and
results to the public and Tahoe researchers. In addition, journal
articles and Open-File Reports will be published to engage the
scientific community.

# Acknowledgments

We would like to acknowledge the following individuals that have been
and will be integral in the activities and success of this project. Very
special thanks to German Whitley, GIS Specialist with the USDA Forest
Service Lake Tahoe Basin Management Unit for her incredible assistance
with GIS data and project support. We are grateful also to our research
peers at USGS Western Geographic Science Center in Menlo Park, Calif.
Leila Gass, Alexander Evans, and John Vogel, have all made important
contributions to the theory and techniques described in this report.
Their collective assistance has been immensely helpful. We would also
like to thank Sandi Page and Sonya Baird for their help with accounting
arrangements and cooperative agreements.

# REFERENCES CITED

Acevedo, W., Foresman, T.W., and Buchanan, J.T., 1996, Origins and
philosophy of building a temporal database to examine human
transformation processes, in ASPRS/ACSM Annual Convention and
Exhibition, Baltimore, MD, April 22-24, 1996, \[Proceedings\] v. 1, p.
148-161.

Acevedo, W., Richards, L.R., and Buchanan, J.T., 1999, Analysis of land
use change in urban environments: U.S. Geological Survey Fact Sheet FS
188-99, 4 p.

Adams, K.D., and Minor, T.B., 2001, Historic shoreline change at Lake
Tahoe from 1938 to 1998: implications for water clarity: Reno, NV,
Desert Research Institute, Report to the Tahoe Regional Planning Agency.

Anderson, J.R., Hardy, E.E., Roach, J.T., and Witmer, R.E., 1976, A land
use and land cover classification system for use with remote sensor
data: U.S. Geological Survey Professional Paper 964, 28 p.

Arnold, C.L., Jr. and Gibbons, C.J., 1996, Impervious surface coverage:
the emergence of a key environmental indicator: Journal of the American
Planning Association, v. 62, no. 2, p. 243-258.

Bank of America, 1996, Beyond sprawl: new patterns of growth to fit the
new California, <http://www.bofa.com/community/comm_env_urban1.html>
(Mar. 4, 1999).

Bell, C., Acevedo, W., and Buchanan, J.T., 1995, *Dynamic mapping of
urban regions: growth of the San Francisco Sacramento region, in* Urban
and Regional Information Systems Association; San Antonio, TX, July
16-20, 1996 \[Proceedings\] v. 1, p. 723-734.

Berka, C., McCallum, D., and Wernick, B., 1995, Land use impacts on
water quality: case studies in three watersheds, Presented at The Lower
Fraser Basin in Transition: A Symposium and Workshop, May 4, 1995,
<http://www.ire.ubc.ca/ecoresearch/publica3.html> (Jan. 12, 2001).

Bernknopf, R.L., and Forney, W.M., 2000, Progress report for the
assessment of the Tahoe Regional Planning Agency's land use system,
unpublished report: U.S. Geological Survey, Center for Science Policy,
Menlo Park, California.

Bhaduri, B., Grove, M., Lowry, C., and Harbor, J., 1997, Assessing
long-term hydrologic effects of land use change: Journal of the American
Water Works Association, v. 89, no. 11, p. 94-106.

Binford, M.W. and Buchenau, M.J., 1993, Riparian greenways and water
resources, in *Ecology of Greenways*, Smitt, D.S. and Hellmund, P.C.,
eds.: p. 69-103.

Borchardt, D. and Sperling, F., 1997, Urban stormwater discharges:
ecological effects on receiving waters and consequences for technical
measures: Water Science and Technology, v. 36, no. 8-9, p. 173-178,

Botsford, E., Booth, D., and Hill, K., 2000, A rapid landcover
classification method for use in urban watershed analysis: University of
Washington.
<http://www.students.washington.edu/ebots/prism/landsat.html>

Boughton, C.J., Rowe, T.G., Allander, K.K., and Robledo, A.R., 1997,
Stream and ground water monitoring program, Lake Tahoe Basin, Nevada and
California: U.S. Geological Survey Fact Sheet FS-100-97, 6 p.

Bradbury, J.P., and Van Metre, P.C., 1997, A land-use and water-quality
history of White Rock Lake reservoir, Dallas, Texas, based on
paleolimnological analyses: Journal of Paleolimnology, v. 17, p.
227-237.

Brakebill, J.W., 2001, Analyzing effects of land use on ground-water
quality in the Potomac River Basin.
<http://wwwdmdtws.er.usgs.gov/publications/abstract/maha1095_jwb.html>

Brun, S.E., and Band, L.E., 1999, Simulating runoff behaviour in an
urbanizing watershed: University of North Carolina Department of
Geography.
<http://www.unc.edu/depts/geog/them/models/hspf/hspfmodel.html>

Burcar, S., Miller, W.W., Tyler, S.W., and Johnson, D.W., 1994, Seasonal
preferential flow in two Sierra Nevada soils under forested and meadow
cover: Journal of the Soil Science Society of America, v. 58, p.
1555-1561.

Byron, E.R., and Goldman, C.R., 1987, Relationships of stream water
quality to land use characteristics in the Tahoe Basin: A technical
summary of changing water quality in Lake Tahoe: The first five years of
the Lake Tahoe Interagency Monitoring Program: Tahoe Research Group,
University of California at Davis, p. 1 --19.

Byron, E.R., and Goldman, C.R., 1989, Land-use and water quality in
tributary streams of Lake Tahoe, California-Nevada: Journal of
Environmental Quality, v. 18, p. 84-88.

Cablk, M., and Minor, T.B., 2001, Analyses of impervious cover in the
Lake Tahoe Basin using remote sensing and geographic information
systems: International Journal of Remote Sensing, in press.

California Department of Finance (CDOF), 1999, California county and
city profiles. [http://www.dof.ca.gov](http://www.dof.ca.gov/)

California Department of Water Resources (CDWR), 1991, Truckee River
Atlas: Sacramento, DWR Reprographics.

California Gap Analysis Program (Ca GAP), 2001.
<http://www.biogeog.ucsb.edu/projects/gap/>

California Tahoe Conservancy, 2001, Riparian assessment from
videography. <http://www.tahoecons.ca.gov/library/rip_data/>

Cartier, K.D., Peltz, L.A., Smith, J.L, 1993, Development and
documentation of spatial databases for the Lake Tahoe Basin, California
and Nevada: USGS Water Resources Investigations Report 93-4182, 65 p.

Chou, V.T., Maidment, D.R., and Mays, L.W., 1988, Applied hydrology,
McGraw-Hill, Inc.

Chuvieco, E., and Congalton, R.G., 1988, Using cluster analysis to
improve the selection of training statistics in classifying remotely
sensed data: Photogrammetric Engineering and Remote Sensing, v. 54, no.
9, p. 1275-1281.

Civco, D. L., and Hurd, J.D., 1997, Impervious surface mapping for the
state of Connecticut, in ASPRS/ACSM Annual Convention and Exhibition,
Seattle, Wash., \[Proceedings\] v. 3, p. 124-135.

Clark, S., Starr, J., Foresman, T.W., Prince, W., and Acevedo, W., 1996,
Development of the temporal transportation database for the analysis of
urban development in the Baltimore-Washington Region, in ASPRS/ACSM
Annual Convention and Exhibition, Baltimore, Maryland, April 22-24
\[Proceedings\] v. 3, p. 77-88.

Clarke, K.C., and Gaydos, L.J., 1998, Loose-coupling a cellular
automaton model and GIS: long-term urban growth prediction for San
Francisco and Washington/Baltimore: International Journal of
Geographical Information Science, v. 12, no. 7, p. 699-714.

Clarke, K.C., Gaydos, L.J., and Hoppen, S., 1997, A self-modifying
cellular automaton model of historical urbanization in the San Francisco
Bay area: Environment and Planning B, v. 24, p. 247-261.

Coats, R.N. and Goldman, C., 1993, Nitrate transport in subalpine
streams, Lake Tahoe Basin, California-Nevada, USA: Applied Geochemistry,
supplemental issue no. 2, p. 17-21.

Coats, R.N., Leonard, R.L., Goldman, C.R., 1976, Nitrogen uptake and
release in a forested watershed, Lake Tahoe Basin, California: Ecology,
v. 57, p. 995-1004.

Crawford-Tilley, J.S., Acevedo, W., Foresman, T.W., and Prince, W.,
1996, Developing a temporal database of urban development for the
Baltimore/Washington Region, *in* ASPRS/ACSM Annual Convention and
Exhibition, Baltimore, Maryland, April 22-24 \[Proceedings\], v. 3, p.
101-110.

Crnojacki, Z., Law, N.L., Sorensen, E., Szwagiel, S., and Tenenbaum, D.,
1997, Hydrologic land cover classification for the Northeast Humber
Watershed. <http://pingo.geog.toronto.edu/~davidten/wisqqih2/>

Duane, T.P., 1996, Human settlement, 1850-2040, *in* Status of the
Sierra Nevada: the Sierra Nevada Ecosystem Project final report to
Congress, D.C. Erman, ed.: Davis, CA, Centers for Water and Wildlands
Research, v. 2, p. 235-360.

Dunn, C.P., Sharpe, D.M., Guntenspergen, G.R., Streans, F., and Yang,
Z., 1990, Methods for analyzing temporal changes in landscape pattern,
*in* Quantitative Methods in Landscape Ecology, M.G. Turner and R.H.
Gardner, eds. Springer-Verlag, p. 173-198.

Elliot-Fisk, D.L., Cahill, T.C., Davis, O.K., Duan, L., Goldman, C.R.,
Grunell, G.E., Harris, R., Kattleman, R., Lacey, R., Leisz, D.,
Lindstrom, S., Machida, D., Rowntree, R., Rucks, P., Sharley, D.A.,
Stephens, S.L., and Ziegler, D.S., 1996, Lake Tahoe Case Study. Status
of the Sierra Nevada: the Sierra Nevada Ecosystem Project final report
to Congress: D.C. Erman, ed.: Davis, CA, Centers for Water and Wildlands
Research, addendum, p. 217-276.

Environmental Protection Agency (EPA), 1994, Landscape monitoring and
assessment research plan, EPA 620/R-94/009, Washington, DC, Office of
Research and Development.

Environmental Protection Agency (EPA), 1983, Results of a nationwide
urban runoff program: Washington, DC, PB 84-185552, US EPA, Water
Planning Division.

Federal Geographic Data Committee (FGDC), 1996, FGDC vegetation
classification and information standards: FGDC Secretariat, Reston, VA.

Forney, W.M., 1999, The volumetric runoff and erosion model: a landscape
perspective of erosion and land use in the Upper Truckee watershed, Lake
Tahoe, California: Durham, NC, Duke University, Master's project, 42 p.

Frohn, R.C., 1998, Remote sensing for landscape ecology: new metric
indicators for monitoring, modeling, and assessment of ecosystems: Boca
Raton, FL, Lewis Publishers.

Goldman, C.R., 1988, Long-term limnological research at Lake Tahoe, in
International Watershed Symposium \[Proceedings\]: South Lake Tahoe, CA,
Tahoe Resource Conservation District, p. 464-477.

Goldstein, M.A., 1988, Truckee's Chinese community: from coexistence to
disintegration, 1870-1890: Los Angeles, University of California,
Master's thesis.

Hatch, L.K., 1997, The generation, transport, and fate of phosphorus in
the Lake Tahoe Ecosystem: Dissertation in the Department of Ecology, UC
Davis, CA.

Heyvaert, A.C., 1998, The biogeochemistry and paleolimnology of
sediments from Lake Tahoe, California-Nevada: Dissertation, UC Davis,
CA.

Hinkle, G.H., and Hinkle, B.M., 1997, Sierra Nevada Lakes: Reno, NV,
University of Nevada Press, reprint of 1949 edition.

Howard, T.F., 1998, Sierra crossings: first roads to California:
Berkeley and Los Angeles, CA, University of California Press, 226 p.

Irons, C.D., ed., 1885, W.F. Edwards' Tourist guide and Directory of the
Truckee Basin: Truckee, CA, Republican Job Print.

Keitt, T.H., Urban, D.L., and Milne, B.T., 1997, Detecting critical
scales in fragmented landscapes: Conservation Ecology, v. 1(1):4.
http://www.consecol.org/vol1/iss1/art4

Kilroy, K.C., Lawrence, S.J., Lico, M.S., Bevans, H.E., and Watkins,
S.A., 1997, Water-quality assessment of the Las Vegas Valley area and
the Carson and Truckee River basins, Nevada and California: nutrients,
pesticides, and suspended sediment, October 1969 to April 1990: U.S.
Geological Survey Water Resources Investigations Report 97-4106, 144 p.

Kirtland, D., Gaydos, L.J., Clarke, K.C., De Cola, L., Acevedo, W., and
Bell, C., 1994, An analysis of human-induced land transformations in the
San Francisco Bay/Sacramento area: World Resource Review, v. 6, no. 2,
p. 206-217.

Khorram, S., Cheshire, H., Siderelis, K., and Nagy, Z., 1992, Mapping
and GIS development of land use and land cover categories for the
Albemarle-Pamlico Drainage Basin: Albemarle-Pamlico Estuarine Study
Project No. 91-08, 54 p.

Krummel, J.R., Gardner, R.H., Sugihara, G., O'Neill, R.V., and Coleman,
P.R., 1987, Landscape patterns in a disturbed environment: Oikos, v. 48,
p. 321-24.

Landres, P.B., Morgan, P. and Swanson, F.J., 1999, Overview of the Use
of Natural Variability Concepts in Managing Ecological Systems:
Ecological Applications, v. 9, No. 4, p. 1179-1188.

Lantis, D.W., Steiner, R., and Karinen, A.E., 1989, California: the
Pacific connection: Chico, CA, Creekside Press, 593 p.

League to Save Lake Tahoe (LSLT), 1998, Lake Tahoe Information Center.
<http://www.tahoe.org/tahoeblue/LakeTahoeInfo.htm>

Lillesand, T.M., and Kiefer, R.W., 1994, Remote Sensing and Image
Interpretation, 3^rd^ ed: New York, NY, Wiley & Sons, Inc., 750 p.

Loeb, S.L., 1988, Evidence of land use impacts on water quality within
the Lake Tahoe Basin, in Conservation District, p. 25-41.

Loeb, S.L., Goldman, C.R., 1979, Water and nutrient transport via ground
water from Ward Valley into Lake Tahoe: Limnologic Oceanographer, v. 26
(6), p. 1146-1154.International Watershed Symposium \[Proceedings\],
South Lake Tahoe, CA, Tahoe Resource

Lorenz, D.L., and Stoner, J.D., 2001, Sampling design for assessing
water quality of the Red River of the North Basin, Minnesota, North
Dakota, and South Dakota, 1993-1995.
<http://mn.water.usgs.gov/redn/rpts/map_rpt/map_rpt.htm>

Mattikalli, N.M., and Richards, K.S., 1996, Estimation of surface water
quality changes in response to land use change: application of the
export coefficient model using remote sensing and geographical
information system: Journal of Environmental Management, v. 48, p.
263-282.

McCarthy, E., 1997, Lake Tahoe: a watershed management study: Western
Water, July/August, p. 4 --13.

McClintock, K.A., Harbor, J.M., and Wilson, T.P., 1995, Assessing the
hydrological impact of land use change in wetland watersheds: a case
study from Northern Ohio, USA, *in* Geomorphology and Land Management in
a Changing Environment, Wiley and Sons Ltd: McGregor, D.F.M and
Thompson, D.A., eds., p. 107-119.

McGarigal, K., 2001, About landscape change:
<http://www.innovativegis.com/products/fragstatsarc/aboutlc.htm> (March
16, 2001).

McGarigal, K., and Marks, B.J., 1994, FRAGSTATS: spatial pattern
analysis program for quantifying landscape structure, Gen. Tech. Report
PNW-GTR-351, USDA Forest Service, Pacific Northwest Research Station,
Portland, OR.

McGurk, B.J., and Davis, M.L., 1996, Camp and Clear Creeks, El Dorado
County: chronology and hydrologic effects of land use change: in Status
of the Sierra Nevada: Sierra Nevada Ecosystem Project final report to
Congress, D.C. Erman, ed.: Davis, CA, Centers for Water and Wildlands
Research, v. 2, p. 1369-1406.

McMahon, G. and T.F. Cuffney, 2000, Quantifying urban intensity of
drainage basins for assessing stream ecological conditions, revised
paper for the Journal of the American Water Resources Association, 30 p.

Merrill, A.G., 2001, Variation in the structure and nitrogen dynamics of
mountain riparian zones: Dissertation for Wildland Resource Science, UC
Berkeley, California.

Mladenoff, D.J., White, M.A., Pastor, J., and Crow, T.R., 1993,
Comparing spatial pattern in unaltered old-growth and disturbed forest
landscapes: Ecological Applications, v. 3., no. 2, p. 294-306.

Murphy, D.D., and Knopp, C.M., eds., 2000, Lake Tahoe Watershed
Assessment, v. 1 and 2: Albany, CA, Pacific Southwest Research Station,
Forest Service, U.S. Department of Agriculture, 407 p.

Nautilus project at University of Connecticut, 2000, Characterization of
urban sprawl. <http://www.resac.uconn.edu/research/sprawl.html>

National Oceanic and Atmospheric Administration, Coastal Services Center
(NOAA-CSC), 1995, NOAA Coastal Change Analysis Program (C-CAP): guidance
for regional implementation: NOAA Technical Report NMFS 123.

Nevada Division of Water Planning (NDWP), 1997, Truckee River
chronology: a chronological history of Lake Tahoe and the Truckee River
and water issues. <http://www.state.nv.us/cnr/ndwp/truckee/trchrono.htm>

Omarzu, T., 1999, Tahoe National Forest established in 1909: Truckee
Sierra Sun, p. 9A.

O'Neill, R.V, Krummel, J.R., Gardner, R.H., Sugihara, G., Jackson, B.,
Indices of landscape pattern: Landscape Ecology, v. 2, p. 63-69.

Pielou, E.C., 1975, Ecological Diversity: New York, Wiley-Interscience.

Prisloe, S., Lei, Y., and Hurd, J., 2001, Interactive GIS-based
impervious surface model: ASPRS 2001 Annual Convention, St. Louis,
Missouri, April 23-27, 2001 \[Proceeedings\].

PRISM Precipitation Maps: 1961-1990.
<http://www.wrcc.dri.edu/precip.html>

Reuter, J., Heyvaert, A., and Goldman, C.R., 1997, Historical
reconstruction of watershed response to natural and anthropogenic
stress: <http://ice.ucdavis.edu/cehr/c2c7-8.htm>

Richards, L.R., 1999, An historical geographic information system for
Truckee, California: Chico, Calif., Chico State University, Master's
thesis, 135 p.

Riitters, K.H., O'Neill, R.V., Hunsaker, C.T., Wickham, J.D., Yankee,
D.H., Timmins, S.P., Jones, K.B., and Jackson, B.L., 1995, A factor
analysis of landscape pattern and structure metrics: Landscape Ecology,
v. 10, p. 23-39.

Rothman, H.K., 1998, Stumbling toward the millenium: tourism, the
postindustrial world and the transformation of the American West:
California History, v. 77, no. 3, p. 140-155.

Rowe, T.G., 1999, Comparison of water quality for upstream and
downstream sites in the Incline Creek watershed, Lake Tahoe Basin,
Nevada, 1990-98, *in* Western Snow Conference, 67^th^, South Lake Tahoe,
Calif., April 19-22 \[Proceedings\], p. 35-44.

\_\_\_\_\_\_1998, Loads and yields of suspended sediment and nutrients
for selected watersheds in the Lake Tahoe Basin, California and Nevada,
*in* National Water-Quality Monitoring Council's National Monitoring
Conference: Critical Foundations to Protect our Waters, Reno, Nev., July
7-9 \[Proceedings, v. 3\], p 525-535.

Rowe, T.G., and Allander, K.K., 2000, Surface and ground-water
conditions in the Upper Truckee River and Trout Creek watersheds,
July-December 1996, South Lake Tahoe, California: U.S. Geological Survey
Water-Resources Investigations Report 00-4001, 39 p.

Rowe, T.G., and Stone, J.C., 1997, Selected hydrologic features of the
Lake Tahoe Basin, California and Nevada: U.S. Geological Survey
Open-File Report 97-384, 1 p.

Scott, E.B., 1957, Saga of Lake Tahoe, v. 1: Filmer Brothers, San
Francisco.

Sierra Business Council, 2000, Sierra Nevada Wealth Index: 1999-2000
update: Sacramento, Calif., Sierra Business Council, 124 p.

\_\_\_\_\_\_1999, Planning for prosperity: building successful
communities in the Sierra Nevada: Sacramento, Calif., Sierra Business
Council.

\_\_\_\_\_\_1996, Sierra Nevada Wealth Index: Understanding and tacking
our region's wealth: Sacramento, Calif., Sierra Business Council, 48 p.

Sleavin, W.J., Civco, D.L., Prisloe, S., and Giannotti, L., 2000,
Measuring impervious surfaces for non-point source pollution modeling:
University of Connecticut Laboratory for Earth Resources Information
Systems.

Smith, J.L., Stone, J.C., Rowe, T.G., and Gardener, J.V., 1999, Selected
hydrologic features of the Lake Tahoe Basin, California and Nevada,
1998: U.S. Geological Survey Water-Resources Investigations Report
99-4031, 1 p.

Sullivan, M., Warwick, J.J., and Tyler, S.W., 1996, Quantifying and
delineating spatial variations of surface infiltration in a small
watershed: Journal of Hydrology, v. 181, p. 149-168.

Stacey, P.B. and Taper, M., 1992, Environmental variation and the
persistence of small populations: Ecological Applications, v. 2., no. 1,
p. 18-29.

Tahoe Regional Planning Agency (TRPA), 1988, Water quality management
plan for the Lake Tahoe region, v. 5.

\_\_\_\_\_\_1996, Water quality report for the water year 1995.

\_\_\_\_\_\_1999, Regional plan for the Lake Tahoe Basin; Code of
Ordinances, Rules of Procedure.

Tracy, J., Bernknopf, R.L., Forney, W.M., and Hill, K., 2000, A
prototype for understanding the effects of TMDL standards: tying
property values to sediment loads in the Lake Tahoe Basin, *in*
Watershed Management Conference, American Society of Civil Engineers
\[Proceedings\].

Truckee-Donner Historical Society (TDHS), 1994, Fire and Ice, A Portrait
of Truckee: Truckee, CA, Truckee-Donner Historical Society.

Turner, M.G., 1989, Landscape ecology: the effect of pattern on process,
Annual Review of Ecological Systematics, v. 20, p. 171-197.

Turner, M.G., and Ruscher, C.L., 1988, Changes in the spatial patterns
of land use in Georgia: Landscape Ecology, v. 1, p. 24-251.

Twiss, R.H., Elford, C.R., James, J.W., Mueller, P.K., Smith, K.C.,
Warburton, J., and Woo, H.W., 1971, Climate and air quality of the Lake
Tahoe region: South Lake Tahoe, CA, Tahoe Regional Planning Agency and
U.S. Forest Service, 31 p.

U.S. Forest Service (USFS), 2000, Land cover monitoring program.
<http://frap.cdf.ca.gov/projects/change_detection/changedetectfr.html>

U.S. Forest Service (USFS), 2000, Sierra Nevada Conservation Framework.
<http://www.r5.fs.fed.us/sncf.html>

U.S. Geological Survey (USGS), 1999, High-resolution land use and land
cover mapping: U.S. Geological Survey Fact Sheet FS 189-99, 2 p.

\_\_\_\_\_\_1997, USGS to coordinate online scientific database for
Tahoe Basin: press release.
<http://www.usgs.gov/public/press/public_affairs/>press_releases/pr376m.html

U.S. Geological Survey (USGS), 2001, Lake Tahoe Data Clearinghouse
(LTDC). <http://blt.wr.usgs.gov/>

University of California, SNEP Science Team and Special Consultants,
1996, Sierra Nevada Ecosystems: *in* Status of the Sierra Nevada: Sierra
Nevada Ecosystem Project final report to Congress, v. 1, p. 6-16.

Urban, D.L., and Smith, T.M., 1989, Microhabitat pattern and the
structure of forest bird communities: American Nature, v. 133, p.
811-829.

Urban, D.L., 1999, Using model analysis to design monitoring programs
for landscape management and impact assessment: Ecological Applications,
v. 10, no. 6, p. 1820-1832.

Walker, D.A., Webber, P.J., Binnian, E.F., Everett, K.R., Lederer, N.D.,
and others, 1987, Cumulative impacts of oil fields on northern Alaskan
landscapes: Science, v. 238, p. 757-761.

Weller, D.E., Jordan, T.E., and Correll, D.L., 1997, Heuristic models
for material discharge from landscapes with riparian buffers: Ecological
Applications, v. 8, no. 4, p. 1156-1169.

Whitley, M.G., 2001, Digital Lake Tahoe Basin Management Unit GIS
Library, South Lake Tahoe, CA, US Forest Service.

Wilkie, D.S., and Finn, J.T., 1996, Remote sensing imagery for natural
resources monitoring: New York, NY, Columbia University Press, 295 p.

Williams, M.W., Melack, J.M., 1991, Solute chemistry of snowmelt and
runoff in an alpine basin, Sierra Nevada: Water Resources Research, v.
27 (7), p. 1575-1588.

Wilson, D., 1992, Sawdust Trails in the Truckee Basin: A History of
Lumbering Operations 1856-1936: Nevada City, CA, Nevada County
Historical Society.

Wollenberg, C., 1985, Golden Gate Metropolis: Perspectives on Bay Area
History: Berkeley, CA, University of California Institute of
Governmental Studies.

[^1]: For an in-depth discussion of the human history of the Lake Tahoe
    Basin refer to Susan Lindstrom's chapter in the Lake Tahoe Watershed
    Assessment titled "A Contextual Overview of Human Land Use and
    Environmental Conditions." (Chapter 2, Volume 1 published in 2000 by
    U.S. Department of Agriculture Pacific Southwest Research Station)

[^2]: The Lincoln Highway was later called US Highway 40. When
    Interstate 80 was constructed in the 1960s, much of US Highway 40
    was widened and straightened and renamed Interstate 80. A 30-mile
    stretch of the original route of the Lincoln Highway/US 40 still
    exists independently of Interstate 80 between Cisco Grove and
    Truckee, CA, as Donner Pass Road.

[^3]: The year 1982 is an additional consideration for the historical
    mapping as it would contribute to the understanding of change over
    the past 20 years. Due to the high costs of data purchase, 1982 will
    not be mapped as part of the year one pilot study.

[^4]: Road mapping activities will be conducted in a complementary way
    to current U.S. Forest Service mapping of system and nonsystem
    roads; data sharing is a mutual goal. In 1998, GPS and mapping work
    was completed by the U.S. Forest Service Lake Tahoe Basin Management
    Unit to update the USGS 1:24,000-scale digital line graph (DLG)
    files. This update includes GPS-defined locations of Forest Service
    roads and trails. The DLG is a Level 3 (DLG-3) enhanced product,
    which means it contains a full range of attribute codes, has full
    topological structuring, and has passed quality control checks.

[^5]: Structure is the spatial relationships between distinctive
    ecosystems and the distribution of energy, materials, and species
    with the different sizes, shapes, numbers, kinds, and configurations
    of the component parts. Function is the interactions between the
    spatial elements, that is the flow and exchange of energy,
    materials, and organisms among the component parts. Change is the
    alteration in the structure and function of the ecological mosaic
    through time.

[^6]: 5 of the 10 watersheds---Incline, Trout, Edgewood, and Ward
    Creeks, and the Upper Truckee River---have multiple gages along
    their reaches, allowing for subwatershed analyses.