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Calibration using R-programming and parallel processing at the HUC12 subbasin scale in the Mid-Atlantic region: Development of national SWAT hydrologic calibration.

Authors :
Bawa, Arun
Mendoza, Katie
Srinivasan, Raghavan
Parmar, Rajbir
Smith, Deron
Wolfe, Kurt
Johnston, John M.
Corona, Joel
Source :
Environmental Modelling & Software. May2024, Vol. 176, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

The first phase of a national scale Soil and Water Assessment Tool (SWAT) model calibration effort at the HUC12 (Hydrologic Unit Code 12) watershed scale was demonstrated over the Mid-Atlantic Region (R02), consisting of 3036 HUC12 subbasins. An R-programming based tool was developed for streamflow calibration including parallel processing for SWAT-CUP (SWAT- Calibration and Uncertainty Programs) to streamline the computational burden of calibration. Successful calibration of streamflow for 415 gages (KGE ≥0.5, Kling-Gupta efficiency; PBIAS ≤15%, Percent Bias) out of 553 selected monitoring gages was achieved in this study, yielding calibration parameter values for 2106 HUC12 subbasins. Additionally, 67 more gages were calibrated with relaxed PBIAS criteria of 25%, yielding calibration parameter values for an additional 150 HUC12 subbasins. This first phase of calibration across R02 increases the reliability, uniformity, and replicability of SWAT-related hydrological studies. Moreover, the study presents a comprehensive approach for efficiently optimizing large-scale multi-site calibration. [Display omitted] • HUC2- region 02 SWAT hydrological calibration was performed for 553 USGS gages. • A successful calibration of 415 gages was achieved at KGE ≥0.5 and PBIAS ≤15. • A detailed methodology to optimize large-scale multi-site calibration was provided. • A R-programming based parallel processing calibration approach was developed. • Input uncertainty analysis for 19 SWAT parameters was generated. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13648152
Volume :
176
Database :
Academic Search Index
Journal :
Environmental Modelling & Software
Publication Type :
Academic Journal
Accession number :
176631634
Full Text :
https://doi.org/10.1016/j.envsoft.2024.106019