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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 #328364
Title: Improving SWAT model prediction using an upgraded denitrification scheme and constrained auto calibration

Author
item SHARIFI, AMIR - University Of Maryland
item Sadeghi, Ali
item LANG, M.W. - University Of Maryland
item McCarty, Gregory
item LEE, S. - University Of Maryland
item YEN, H. - Texas A&M University
item JEONG, J. - Texas A&M University

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 7/5/2016
Publication Date: 7/27/2016
Citation: Sharifi, A., Sadeghi, A.M., Lang, M., Mccarty, G.W., Lee, S., Yen, H., Jeong, J. 2016. Improving SWAT model prediction using an upgraded denitrification scheme and constrained auto calibration. Meeting Abstract. p. 79.

Interpretive Summary:

Technical Abstract: The reliability of common calibration practices for process based water quality models has recently been questioned. A so-called “adequately calibrated model” may contain input errors not readily identifiable by model users, or may not realistically represent intra-watershed responses. These shortcomings are partly due to the use of evaluation criteria that are exclusively established using global in-stream model responses without considering intra-watershed responses. In this study, we introduced a modification to the SWAT model’s nitrogen (N) cycling relationships and a new calibration tool that collectively decrease the chance of misrepresenting intra-watershed responses. The N cycling relationships in the SWAT model were modified to better represent NO3 cycling in soils with various degrees of water holding capacity, an approach that demonstrates the capacity to spatially distinguish areas of high denitrification potential. The new calibration tool has the capacity to calibrate paired watersheds simultaneously within a single framework. Results showed that when both proposed methodologies were applied jointly to a system of paired watersheds on the Delmarva Peninsula adjacent to the Chesapeake Bay (i.e., the Greensboro and Tuckahoe watersheds), the performance of the models suffered; however, the intra-watershed responses (mass of nitrate lost to denitrification) in the Greensboro and Tuckahoe models automatically converged on realistic sums. The modified SWAT model demonstrates the capacity to spatially distinguish areas of high denitrification potential (hot spots), an ability that has implications for identifying prominent areas for wetland restoration to minimize nitrogen loss into stream networks.