Goloka Behari Sahoo

Nutrient and particle load estimates to Lake Tahoe (CA-NV, USA) for Total Maximum Daily Load establishment.

The Lake Tahoe Total Maximum Daily Load (TMDL) requires detailed methodologies to identify sources of flows and pollutants (particles and nutrients) for estimating time-variant loads as input data for the Lake Tahoe clarity model. Based on field data and a modeling study, the major sources of pollutant loads include streams (three subdivisions of this category are urban, nonurban, and stream channel erosion), intervening zones (IZs) (two subdivisions of this category are urban and nonurban), atmosphere (wet and dry), groundwater and shoreline erosion. As Lake Tahoe remains well oxygenated year-round, the contribution of internal loading from the bottom sediments was considered minor. A comprehensive quantitative estimate for fine particle number (< 16 μm diameter) and nutrient (nitrogen and phosphorus) loading is presented. Uncertainties in the estimation of fine particle numbers and nutrients for different sources are discussed. Biologically available phosphorus and nitrogen were also evaluated. Urban runoff accounted for 67% of the total fine particle load for all sources making it the most significant contributor although total urban runoff was only 6%. Non-urban flows accounted for 94% of total upland runoff, but the nitrogen, phosphorus and fine sediment loadings were 18%, 47% and 12%, respectively of the total loadings. Atmospheric nitrogen, phosphorus, and fine particle loadings were approximately 57%, 20%, and 16%, respectively of the total loading. Among streams and IZs, IZ 8000, Upper Truckee River, Trout Creek, Blackwood Creek, and Ward Creek are the top fine particle, nitrogen and phosphorus contributors. The relative percentage contribution of inorganic fine particles from all sources based on annual average for the period 1994-2008 on size classes 0.5-1, 1-2, 2-4, 4-8, and 8-16 μm are 73%, 19%, 5%, 2%, and 1%, respectively. These results suggest clear priorities for resource managers to establish TMDL on sources and incoming pollutants and preserving lake clarity.

Modeling the transport of nutrients and sediment loads into Lake Tahoe under projected climatic changes

The outputs from two General Circulation Models (GCMs) with two emissions scenarios were downscaled and bias-corrected to develop regional climate change projections for the Tahoe Basin. For one model—the Geophysical Fluid Dynamics Laboratory or GFDL model—the daily model results were used to drive a distributed hydrologic model. The watershed model used an energy balance approach for computing evapotranspiration and snowpack dynamics so that the processes remain a function of the climate change projections. For this study, all other aspects of the model (i.e. land use distribution, routing configuration, and parameterization) were held constant to isolate impacts of climate change projections. The results indicate that (1) precipitation falling as rain rather than snow will increase, starting at the current mean snowline, and moving towards higher elevations over time; (2) annual accumulated snowpack will be reduced; (3) snowpack accumulation will start later; and (4) snowmelt will start earlier in the year. Certain changes were masked (or counter-balanced) when summarized as basin-wide averages; however, spatial evaluation added notable resolution. While rainfall runoff increased at higher elevations, a drop in total precipitation volume decreased runoff and fine sediment load from the lower elevation meadow areas and also decreased baseflow and nitrogen loads basin-wide. This finding also highlights the important role that the meadow areas could play as high-flow buffers under climatic change. Because the watershed model accounts for elevation change and variable meteorological patterns, it provided a robust platform for evaluating the impacts of projected climate change on hydrology and water quality.

Snowmelt Timing as a Determinant of Lake Inflow Mixing

Author(s): Roberts, DC; Forrest, AL; Sahoo, GB; Hook, SJ; Schladow, SG | Abstract: