Dynamic riparian buffer widths from potential non-point source pollution areas in forested watersheds

摘要

Efforts to manage National Forests in the USA for wood production, while protecting water quality, are currently constrained by models that do not address the temporal dynamics of variable non-point source (NPS) areas. NPS areas are diffuse sources of contaminants contributed mostly by runoff as a result of different land use activities. Riparian vegetative buffers are often used to control contaminants from NPS areas but defining suitable widths require different policy considerations. In this study, the approach for defining suitable buffer widths is to apply a distributed process-based model that predicts potential NPS areas prone to generating runoff in relation to overland flow distances. A case study of the concept was applied to the 72km super(2) Pete King watershed located in the Clearwater National Forest (CNF) in central Idaho, USA. This grid modeling approach is based on a Geographic Information System (GIS) and it integrates the soil moisture routing (SMR) model with probabilistic analysis. The SMR model is a daily water balance model that simulates the hydrology of forested watersheds using real or stochastically generated climate data, a digital elevation model, soil, and land use data. The probabilistic analysis incorporates the variability of soil depth and accounts for uncertainties associated with the prediction of NPS areas using Monte Carlo simulation. A 1-year simulation for the case study location was performed to examine the spatial and temporal changes in NPS areas prone to generating runoff. The results of the simulation indicate that the seasonal variability of saturated areas determines the spatial dynamics of the potential NPS pollution. Use of this model for the design of riparian buffer widths would increase the effectiveness of decision-making in forest management and planning by mapping or delineating NPS areas likely to transport contaminants to perennial surface water bodies.