Different Infiltration Methods for Swat Model Seasonal Calibration of Flow and Sediment Production

Priscila Pacheco Mariani (), Nilza Maria Reis Castro, Vanessa Sari, Taís Carine Schmitt and Olavo Correa Pedrollo
Additional contact information
Priscila Pacheco Mariani: Federal University of Rio Grande do Sul
Nilza Maria Reis Castro: Federal University of Rio Grande do Sul
Vanessa Sari: Federal University of Santa Maria
Taís Carine Schmitt: Federal University of Santa Maria
Olavo Correa Pedrollo: Federal University of Rio Grande do Sul

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2024, vol. 38, issue 1, No 16, 303-322

Abstract: Abstract Hydrosedimentological models make it possible to better understand the dynamics of water and sediment production in watersheds when properly calibrated. The objective of this study was to analyze the effects of the curve number (CN) and Green and Ampt (GA) methods and of seasonal calibration of the Soil and Water Assessment Tool (SWAT) model for estimating flow and sediment production in an agricultural basin. In this research, we presented an original application with the hourly suspended sediment concentration (SSC) generated by artificial neural networks (ANNs) for use in SWAT model calibration. This method was applied in the Taboão basin (77.5 km2), with data from 2008 to 2018. The best Nash–Sutcliffe (NS) coefficient values were obtained using the combination of wet years for calibration and the GA method for both daily flow (NScalibration: 0.74; and NSvalidation: 0.68) and daily sediment production (NScalibration: 0.83; and NSvalidation: 0.77). The CN method did not result in satisfactory values during daily flow calibration (NScalibration 0.39). The results showed that it is possible to employ the SWAT model for hydrosedimentological prediction in the Taboão basin, with a favorable efficiency, using the GA method and calibration with data for wet periods.

Keywords: Artificial neural networks; Green–Ampt method; Curve number method (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s11269-023-03671-1 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:waterr:v:38:y:2024:i:1:d:10.1007_s11269-023-03671-1

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11269

DOI: 10.1007/s11269-023-03671-1

Access Statistics for this article

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA) is currently edited by G. Tsakiris

More articles in Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA) from Springer, European Water Resources Association (EWRA)
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().