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PixelSWAT: A user-friendly ArcGIS tool for preparing inputs to run SWAT in a distributed discretization scheme

This paper documents the development of PixelSWAT, a Graphical User interface (GUI) python toolbox developed with the motive of creating gridded watershed and stream features to run the Soil and Water Assessment Tool (SWAT) in a distributed discretization scheme thus allowing optimum utilization of gridded weather datasets. Additionally, the tool also aims to automate the preparation of SWAT weather input files from Network Common Data (NetCDF) files for any SWAT user along with the option to interpolate the weather files for each grid. A case study was conducted in the Mago basin of Tawang, Arunachal Pradesh, using gridded weather datasets for hydrological simulation. Three SWAT models were prepared – a conventional SWAT model; a 500 m and a 1000 m gridded watershed PixelSWAT models. Statistical indices Nash Sutcliffe (NSE), Coefficient of Determination (R2) and Percent Bias (PBIAS) showed that the PixelSWAT projects performed marginally better than the conventional model and also incorporated the weather data more meaningfully.

Availability
202551.136Perpustakaan BIG (Eksternal Harddisk)Available
Detail Information
Series Title
Applied Computing and Geoscience - Open Access
Call Number
551.136
Publisher
Amsterdam : Elsevier.,
Collation
17 hlm PDF, 20.155 KB
Language
Inggris
ISBN/ISSN
2590-1974
Classification
551.136
Content Type
text
Media Type
-
Carrier Type
-
Edition
Vol.23, September 2024
Subject(s)
Interpolation
ArcSWAT
Gridded dataset
Python toolbox
Distributed-discretization scheme
Hydrological modelling
Specific Detail Info
-
Statement of Responsibility
Other version/related

No other version available

File Attachment
  • PixelSWAT: A user-friendly ArcGIS tool for preparing inputs to run SWAT in a distributed discretization scheme
    This paper documents the development of PixelSWAT, a Graphical User interface (GUI) python toolbox developed with the motive of creating gridded watershed and stream features to run the Soil and Water Assessment Tool (SWAT) in a distributed discretization scheme thus allowing optimum utilization of gridded weather datasets. Additionally, the tool also aims to automate the preparation of SWAT weather input files from Network Common Data (NetCDF) files for any SWAT user along with the option to interpolate the weather files for each grid. A case study was conducted in the Mago basin of Tawang, Arunachal Pradesh, using gridded weather datasets for hydrological simulation. Three SWAT models were prepared – a conventional SWAT model; a 500 m and a 1000 m gridded watershed PixelSWAT models. Statistical indices Nash Sutcliffe (NSE), Coefficient of Determination (R2) and Percent Bias (PBIAS) showed that the PixelSWAT projects performed marginally better than the conventional model and also incorporated the weather data more meaningfully.
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