Effect of DEM Resolution, Source, Resampling Technique and Area Threshold on SWAT Outputs

Application of an inappropriate Digital Elevation Model (DEM) might lead to uncertainty in modelling of the hydrological cycle. The novelty of this work is the development of a comprehensive framework to evaluate the effect of DEM resolution (12 to 500 m), source (TanDEM-X, SRTM, AW3D30 and ASTER GDEM2), resampling technique (nearest neighbour, bilinear interpolation, cubic convolution and majority) and area threshold (1000 to 50,000 ha) on Soil and Water Assessment Tool (SWAT) outputs based on five criteria: (1) river network extraction, (2) streamflow simulation, (3) topography, slope and basin characteristics, (4) hydrological and (5) water quality simulations. Kelantan River Basin, a tropical basin in Peninsular Malaysia was selected as study area. The major findings are summarized as follows: (1) TanDEM-X had better river network extraction capability than ASTER GDEM2, (2) better monthly streamflow simulations were obtained between 20 m and 60 m DEM resolutions, with the smallest area threshold (1000 ha), (3) TanDEM-X and SRTM DEMs outperformed ASTER GDEM2 on monthly streamflow simulation, (4) DEM resolution, source and resampling technique were insensitive to most of the hydrological components, except the lateral flow, (5) area threshold was sensitive to SWAT-simulated surface runoff, soil water content and evapotranspiration, (6) DEM scenarios had a larger impact on sediment yield simulations compared to the total nitrogen and total phosphorus simulations. We recommend a preliminary assessment of DEM uncertainties on SWAT outputs to obtain more reliable modelling outputs.

[1]  T. A. Costello,et al.  Effect of DEM data resolution on SWAT output uncertainty , 2005 .

[2]  Fei Xu,et al.  Impacts of DEM uncertainties on critical source areas identification for non-point source pollution control based on SWAT model , 2016 .

[3]  Jeffrey G. Arnold,et al.  Soil and Water Assessment Tool Theoretical Documentation Version 2009 , 2011 .

[4]  Naresh Pai,et al.  Hydrologic and Water Quality Models: Performance Measures and Evaluation Criteria , 2015 .

[5]  Jiaping Wu,et al.  Evaluating DEM source and resolution uncertainties in the Soil and Water Assessment Tool , 2012, Stochastic Environmental Research and Risk Assessment.

[6]  Barnali M. Dixon,et al.  Impacts of DEM resolution, source, and resampling technique on SWAT-simulated streamflow. , 2015 .

[7]  Takeo Tadono,et al.  GENERATION OF THE 30 M-MESH GLOBAL DIGITAL SURFACE MODEL , 2016 .

[8]  Sung-Min Cho,et al.  SENSITIVITY CONSIDERATIONS WHEN MODELING HYDROLOGIC PROCESSES WITH DIGITAL ELEVATION MODEL 1 , 2001 .

[9]  Huiliang Wang,et al.  A Comprehensive Study of the Effect of Input Data on Hydrology and non-point Source Pollution Modeling , 2015, Water Resources Management.

[10]  W. Featherstone,et al.  Comparison and validation of the recent freely available ASTER-GDEM ver1, SRTM ver4.1 and GEODATA DEM-9S ver3 digital elevation models over Australia , 2010 .

[11]  V. Chaplot.  Impact of spatial input data resolution on hydrological and erosion modeling: Recommendations from a global assessment , 2014 .

[12]  Vincent Chaplot,et al.  Impact of DEM mesh size and soil map scale on SWAT runoff, sediment, and NO3-N loads predictions , 2005 .

[13]  Theresa Mannschatz,et al.  Nexus Tools Platform: Web-based comparison of modelling tools for analysis of water-soil-waste nexus , 2016, Environ. Model. Softw..

[14]  Raghavan Srinivasan,et al.  Threshold Effects in HRU Definition ofthe Soil and Water Assessment Tool , 2015 .

[15]  Jeffrey G. Arnold,et al.  The Soil and Water Assessment Tool: Historical Development, Applications, and Future Research Directions , 2007 .

[16]  Zulkifli Yusop,et al.  Climate change impacts under CMIP5 RCP scenarios on water resources of the Kelantan River Basin, Malaysia , 2017 .

[17]  Raghavan Srinivasan,et al.  Using the Soil and Water Assessment Tool (SWAT) to model ecosystem services: A systematic review , 2016 .

[18]  Zhenyao Shen,et al.  Uncertainty of SWAT model at different DEM resolutions in a large mountainous watershed. , 2014, Water research.

[19]  M. Goyal,et al.  Comparative Assessment of SWAT Model Performance in two Distinct Catchments under Various DEM Scenarios of Varying Resolution, Sources and Resampling Methods , 2017, Water Resources Management.

[20]  Jeffrey G. Arnold,et al.  Advances in ecohydrological modelling with SWAT—a review , 2008 .

[21]  Gerhard Krieger,et al.  Generation and performance assessment of the global TanDEM-X digital elevation model , 2017 .

[22]  Takeo Tadono,et al.  Generation of the 30 M-MESH global digital surface model by alos prism , 2016 .

[23]  R. Srinivasan,et al.  ARCGIS‐SWAT: A GEODATA MODEL AND GIS INTERFACE FOR SWAT 1 , 2006 .

[24]  Hannes Isaak Reuter,et al.  An evaluation of void‐filling interpolation methods for SRTM data , 2007, Int. J. Geogr. Inf. Sci..

[25]  K. C. Patra,et al.  Evaluating the Uncertainties in the SWAT Model Outputs due to DEM Grid Size and Resampling Techniques in a Large Himalayan River Basin , 2017 .

[26]  Ian D. Moore,et al.  Modeling subsurface stormflow on steeply sloping forested watersheds , 1984 .

[27]  Michael J. Oimoen,et al.  ASTER Global Digital Elevation Model Version 2 - summary of validation results , 2011 .

[28]  John R. Williams,et al.  LARGE AREA HYDROLOGIC MODELING AND ASSESSMENT PART I: MODEL DEVELOPMENT 1 , 1998 .

[29]  Ngai Weng Chan,et al.  Hydro-Meteorological Assessment of Three GPM Satellite Precipitation Products in the Kelantan River Basin, Malaysia , 2018, Remote. Sens..