Literature DB >> 24509347

Uncertainty of SWAT model at different DEM resolutions in a large mountainous watershed.

Peipei Zhang1, Ruimin Liu2, Yimeng Bao1, Jiawei Wang1, Wenwen Yu1, Zhenyao Shen1.   

Abstract

The objective of this study was to enhance understanding of the sensitivity of the SWAT model to the resolutions of Digital Elevation Models (DEMs) based on the analysis of multiple evaluation indicators. The Xiangxi River, a large tributary of Three Gorges Reservoir in China, was selected as the study area. A range of 17 DEM spatial resolutions, from 30 to 1000 m, was examined, and the annual and monthly model outputs based on each resolution were compared. The following results were obtained: (i) sediment yield was greatly affected by DEM resolution; (ii) the prediction of dissolved oxygen load was significantly affected by DEM resolutions coarser than 500 m; (iii) Total Nitrogen (TN) load was not greatly affected by the DEM resolution; (iv) Nitrate Nitrogen (NO₃-N) and Total Phosphorus (TP) loads were slightly affected by the DEM resolution; and (v) flow and Ammonia Nitrogen (NH₄-N) load were essentially unaffected by the DEM resolution. The flow and dissolved oxygen load decreased more significantly in the dry season than in the wet and normal seasons. Excluding flow and dissolved oxygen, the uncertainties of the other Hydrology/Non-point Source (H/NPS) pollution indicators were greater in the wet season than in the dry and normal seasons. Considering the temporal distribution uncertainties, the optimal DEM resolutions for flow was 30-200 m, for sediment and TP was 30-100 m, for dissolved oxygen and NO₃-N was 30-300 m, for NH₄-N was 30 to 70 m and for TN was 30-150 m.
Copyright © 2014 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  DEM resolution; Mountainous watershed; Non-point Source pollution; SWAT model; Uncertainty analysis

Mesh:

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Year:  2014        PMID: 24509347     DOI: 10.1016/j.watres.2014.01.018

Source DB:  PubMed          Journal:  Water Res        ISSN: 0043-1354            Impact factor:   11.236


  5 in total

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  5 in total

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