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      SWAT Ungauged: Water Quality Modeling in the Upper Mississippi River Basin

      , , , , , , ,
      Journal of Hydrology
      Elsevier BV

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          Abstract

          Improving model performance in ungauged basins has been a chronic challenge in watershed model application to understand and assess water quality impacts of agricultural conservation practices, land use change, and climate adaptation measures in large river basins. Here, we evaluate a modified version of SWAT2012 (referred to as SWAT-EC hereafter), which integrates an energy balanced soil temperature module (STM) and the CENTRUY-based soil organic matter algorithm, for simulating water quality parameters in the Upper Mississippi River Basin (UMRB), and compare it against the original SWAT2012. Model evaluation was performed for simulating streamflow, sediment, and nitrate-N (NO 3 -N) and total nitrogen (TN) loadings at three stations near the outlets of UMRB. The model comparison was conducted without parameter calibration in order to assess their performance under ungauged conditions. The results indicate that SWAT-EC outperformed SWAT2012 for stream flow and NO 3 -N and TN loading simulation on both monthly and annual scales. For sediment, SWAT-EC performed better than SWAT2012 on a monthly time step basis, but no noticeable improvement was found at the annual scale. In addition, the performance of the uncalibrated SWAT-EC was comparable to other calibrated SWAT models reported in previous publications with respect to sediment and NO 3 -N loadings. These findings highlight the importance of advancing process representation in physically-based models to improve model credibility, particularly in ungauged basins.

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          Author and article information

          Journal
          Journal of Hydrology
          Journal of Hydrology
          Elsevier BV
          00221694
          February 2020
          February 2020
          : 124601
          Article
          10.1016/j.jhydrol.2020.124601
          7900929
          33627888
          6c1475e6-7ad4-413c-892c-50f1ca99069a
          © 2020

          https://www.elsevier.com/tdm/userlicense/1.0/

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