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Erosion modelling for land management in the Tahoe basin, USA: scaling from plots to forest catchments

Grismer, M.E.
Hydrological sciences journal 2012 v.57 no.5 pp. 878-900
equations, erodibility, highlands, lakes, land management, models, pollution load, prediction, rainfall simulation, runoff, sediment yield, sediments, soil amendments, water quality, watersheds, United States
Land management and its effects on water quality are a concern where regulatory agencies work to establish sediment and/or nutrient loadings. Runoff and erosion measurement in the field and modelling at the catchment scale are often the only means of generating realistic data and results for subsequent analyses. As such, it is critical to link local-scale field measurements associated with the range of land uses or soil restoration efforts with the catchment-scale sediment loading. A distributed hydrological model with locally-derived, slope-dependent sediment yield (erodibility) equations developed from rainfall simulation (RS) studies at the 1-m² scale across the Tahoe basin, USA, is employed to determine the runoff-dependent scaling factors (SFs) necessary to predict daily stream sediment loading from the forested uplands. Data from three “paired”, adjacent, west-shore Lake Tahoe tributary catchments are considered for the period 1994–2004 at time scales ranging from daily to annual. At all time scales, the SF was dependent on runoff (R), particularly at smaller values, but was readily simplified as an approximately inverse square-root function. Optimized SF–runoff regressions for each watershed were equivalent when modified by ratios of watershed area. As a result, a single daily SF–runoff equation was determined (through minimization of sediment load prediction errors) that could be successfully applied to all three watersheds with an accuracy consistent with the predictive error associated with any one of the watersheds alone. Sensitivity analyses indicated that sediment loading predictions were more sensitive to the SF–runoff equation coefficient rather than the exponent. Annual sediment load prediction errors of ˜30% might be expected for low or high runoff years.