Evaluating the effects of soil data quality on the SWAT runoff prediction Performance; A case study of Saz-Cayirova catchment, Turkey

Oruç H. N., Çelen M., GÜLGEN F., Öncel M. S., Vural S., KILIÇ B.

Urban Water Journal, vol.20, no.10, pp.1592-1607, 2023 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 20 Issue: 10
  • Publication Date: 2023
  • Doi Number: 10.1080/1573062x.2022.2056060
  • Journal Name: Urban Water Journal
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), Communication Abstracts, Geobase, ICONDA Bibliographic, INSPEC, Metadex, Pollution Abstracts, Civil Engineering Abstracts
  • Page Numbers: pp.1592-1607
  • Keywords: Hydrological modeling, SWAT model, FAO, elaborating soil datasets, Saz-cayirova catchment
  • Yıldız Technical University Affiliated: Yes


© 2022 Informa UK Limited, trading as Taylor & Francis Group.This study evaluates the performance of the SWAT model using two different soil databases to reveal the effect of elaborating soil dataset on runoff in a small-scale catchment dominated by dense industrial and residential areas. Soil samples were collected from 29 locations. 7 out of 13 soil parameters required by SWAT were produced by field and laboratory studies to create a specified soil database (SSM). Two simulation designs were constructed using SSM and Food and Agricultural Organization soil database before and after calibration. The main difference between these databases is the soil texture directly affecting runoff. The results show that the SSM is critical for model accuracy in small basins where natural soil cover has decreased due to unnatural activities. In similar basins with these characteristics, significant increases in model accuracy can be achieved by producing specific soil maps with a small number of soil samples or detailing existing maps.