Location: Water Quality and Ecology ResearchTitle: Climate change impacts on runoff, sediment, and nutrient loads in an agricultural watershed in the Lower Mississippi River Basin Author
|Bingner, Ronald - Ron|
Submitted to: Applied Engineering in Agriculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/13/2017
Publication Date: N/A
Citation: N/A Interpretive Summary: Climate change is projected to impact nutrient and sediment loads from agricultural fields of the Lower Mississippi River Alluvial Plain (i.e. the Delta). Increased loads of agricultural pollutants can produce problems for water resources and ecosystems. In this study projected climate data were used to evaluate potential impacts on pollutant loads in Beasley Lake watershed using the USDA Annualized Agricultural Non-Point Source (AnnAGNPS) pollution model. Overall, average temperature is estimated to rise 2 – 3°C with no change in average precipitation by 2070. Simulation results indicated reduced expected runoff, but increases in sediment and nutrient loads due to more intense storms. Conservation practices showed potential for reducing sediment and nutrient loads by 20 – 75% below historical levels, thus mitigating the impact of climate change. The implication for NRCS or state agency resource managers is that an investment in wider application of conservation practices may pay additional future dividends for improving water quality and ecosystems.
Technical Abstract: Projected climate change can impact various aspects of agricultural systems, including the nutrient and sediment loads exported from agricultural fields. This study evaluated the potential changes in runoff, sediment, nitrogen, and phosphorus loads using projected climate estimates from 2041 – 2070 in the Beasley Lake watershed in Mississippi, USA using the Annualized Agricultural Non-Point Source (AnnAGNPS) pollution watershed model. Fifteen global climate models (GCMs) for the climate change scenario RCP8.5 in Western Mississippi were used. Daily precipitation and air temperature were generated with the weather generator SYNTOR. Daily climate data derived from all 15 GCMS were used in AnnAGNPS simulations to generate ensemble projected loads, and climate data from four GCMs were used in simulations to assess the effectiveness of five different conservation practices for reducing projected loads. Predicted median annual-average pollutant loads increased by 9 to 12% with ensemble projected climate change. However, no-tillage and cover crop conservation practices were predicted to reduce pollutant loads from 20 to 75% below historical levels despite the impacts of climate change. This study suggests that greater implementation of conservation practices can be effective at mitigating water quality degradation associated with projected climate change.