Impacts of Best Management Practices on Sediment and Nutrient Yields
Under Multiple Climate Change Scenarios for the Meramec River Watershed
Abstract
Climate change is a primary factor influencing alterations in watershed
hydrology. Associated changes in temperature and precipitation can
influence the fate and transport of non-point source pollution within a
watershed, which complicates the application of best management
practices (BMPs) for pollution mitigation. Understanding the sensitivity
of BMP implementation as climate change is critical for proper
management of water resources. The objective of this study is to
understand the effects of BMPs on sediment and nutrient yields in the
Meramec River watershed in eastern Missouri, U.S.A due to changes in
climate. The Soil and Water Assessment Tool (SWAT) was used to model the
flow, sediment and nutrient yields across the watershed. Multi-site
calibration (1996-2012) and validation (1981-1995; 2012-2014) gave
varied results, ranging from very good to acceptable, for the monthly
flow, sediment load, total nitrogen (TN) and total phosphorus (TP).
Various BMPs were implemented into the calibrated model in conjunction
with climate data from four Coupled Model Intercomparison Project Phase
5(CMIP5) projections to estimate the effects of climate change on
watershed yields. Implemented BMPs include riparian buffers, vegetated
filter strips, terrace, grassed waterway, and tillage. BMPs were
implemented in subwatersheds with high sediment and nutrient outputs as
well as relatively high ecological value. Results indicate that BMPs
could achieve reductions in a range from 2 to 76% for sediment loss, 1
to 64% for TN loss, and 5 to 54% for TP loss. Among the individual
BMPs assessed, vegetated filter strips were most effective when
considering the reduction in sediment and nutrient loads. This study
highlights the effectiveness of a range of BMPs in reducing the sediment
and nutrient loads and provides quantitative measures for determining
the most effective individual BMP and the optimal combination of BMPs
based on current and future climate scenarios.