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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #311915
Title: Climate change impact on critical source area identification in a Maryland watershed

Author
item RENKENBERGER, JASON - University Of Maryland
item MONTAS, H.J. - University Of Maryland
item LEISNHAM, PAUL - University Of Maryland
item CHANSE, VICTORIA - University Of Maryland
item SHIRMOHAMMADI, A. - University Of Maryland
item Sadeghi, Ali
item BRUBAKER, KAYE - University Of Maryland
item ROCKLER, AMANDA - University Of Maryland
item HUTSON, THOMAS - University Of Maryland
item LANSING, DAVID - University Of Maryland

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 5/3/2015
Publication Date: 5/3/2015
Citation: Renkenberger, J., Montas, H., Leisnham, P., Chanse, V., Shirmohammadi, A., Sadeghi, A.M., Brubaker, K., Rockler, A., Hutson, T., Lansing, D. 2015. Climate change impact on critical source area identification in a Maryland watershed Proceedings of the American Society of Agricultural and Biological Engineers Climate Change Symposium, May 3-5, 2015, Chicago, Illinois.

Interpretive Summary:

Technical Abstract: Large scale hydrologic modeling can be a useful tool to explore the effects of climate change on watersheds. In the Chesapeake Bay region agriculture has been identified as one of many contributing sources to water quality degradation. Accurate identification of the environmental factors and processes that contribute excessive nitrogen, phosphorus and sediment (or pollution “hotspots”) is critical to help ensure watershed sustainability. This study investigates the relationship between climate change scenarios and hotspot delineation. To overcome the problems inherent to the analysis of large geographic areas, the Soil Water and Assessment Tool (SWAT), in combination with ArcGIS, were used to build and then analyze a watershed model. After calibrating and validating the model for the Choptank watershed, an agricultural watershed in eastern Maryland, SWAT outputs were spatially mapped to identify hotspots. Considering changes in precipitation (distribution and quantity) as the primary driver of watershed response, these hotspots were mapped under several possible future climate scenarios. Under scenarios with increased rainfall intensity, preliminary results show increases in total hotspot area. Conversely, scenarios with lower rainfall intensity show a similar reduction in total hotspot area. Ultimately, we can show managers and policy makers that a variable climate translates to a variable distribution of hotspots. With a more complete understanding of how different areas will change in their export of non-point source (NPS) pollution, public officials can write and implement NPS reduction strategies more effectively.