Lake Tahoe is one of the most pristine lakes in the world. In recent decades, once pristine portions of the Tahoe Basin are becoming urbanized. Studies during the past forty years have shown that many factors have interacted to degrade the Lake Tahoe Basin's air quality, terrestrial
landscape, and water quality. These factors include land disturbance, increasing resident and tourist population, habitat destruction, air pollution, soil erosion, roads and road maintenance, and loss of natural landscapes capable of detaining and infiltrating rainfall runoff. Since 1968,
there has been a decline of the lake's Secchi depth clarity at an alarming rate of nearly one foot per year. A TMDL for Lake Tahoe is currently under development with an endpoint target for lake clarity defined as the mean annual Secchi depth during the period 1967–71. In support
of this effort, a detailed watershed model is being developed to help associate natural and anthropogenic sources within the watershed to lake clarity, and provide a basis for performing allocation analysis and future TMDL implementation planning. The development effort integrates research
results from numerous ongoing studies being conducted in support of the Lake Tahoe TMDL along with extensive available historical data currently available. This paper highlights a few of the customized data and methods developed specifically for this TMDL, including meteorological data compilation
and quality control, integration of high-resolution/high-frequency 3-by-3 kilometer synthetic meteorological data coverage, and customized land use GIS data sources and data analysis and processing techniques that were applied. The Lake Tahoe drainage area was divided into 184 subwatersheds,
with 16 land use and disturbance classifications. The watershed was modeled using the United States Environmental Protection Agency (USEPA) approved Loading Simulation Program in C++ (LSPC). LSPC is a watershed modeling system that includes streamlined Hydrologic Simulation Program FORTRAN
(HSPF) algorithms for simulating hydrology, sediment, and general water quality on land as well as simplified stream transport. Since the quality of detailed watershed modeling directly depends on data quality and representation, the efforts described in this paper have proven beneficial for
the modeling process.
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