A geographic information system-based model of the long-term impact of land use change on nonpoint-source pollution at a watershed scale.

摘要

Land use change has significant impacts on watershed hydrology because an increase in impervious/urban areas changes water quantity and quality on a variety of spatial and temporal scales. Urban areas are an important source of runoff and non-point source (NPS) pollution, and NPS pollution is the leading cause of water quality degradation in the US. Traditional hydrologic models focus on event-specific estimation of peak discharges and NPS pollution. Although these are appropriate for short-term, local scale surface water management problems, they are of limited value for attempts to understand the long term hydrologic impacts of land use change. A Long-Term Hydrologic Impact Assessment (L-THIA) model has been developed and expanded, based on the widely used USDA Curve Number (CN) method. Long term climatic records are combined with soils, land use, and pollutant data to assess average annual runoff and NPS pollution at a watershed scale. This model is linked to a Geographic Information System (GIS) which allows easier creation and management of model input and output data, and advanced spatial analyses and visualization. Comparisons of L-THIA predictions with field data and results from two other widely used models (SWMM and WEPP) indicate that L-THIA produces reasonable results for assessing absolute and relative impacts of land use change. Sensitivity analyses show that L-THIA underestimates runoff when variable antecedent moisture conditions are assumed, compared to average antecedent moisture conditions, and that L-THIA results are very sensitive to the climate region. Applications of the technique to two urbanizing watersheds in Indiana demonstrated that increases in urban areas significantly increases annual average runoff and most NPS pollution, while decreases in agricultural areas significantly decreases nutrient pollution. Absolute and relative impacts were highly sensitive to the spatial scale of the analyses. Some sub-watersheds showed greater relative impacts than the entire watershed while other sub-watersheds were less affected by land use change. This technique allows identification of environmentally sensitive areas in terms of runoff and NPS pollution potential, which is critical for evaluating alternative land use management scenarios to improve management of the long-term hydrologic impacts of land use change.