Analyzing Effects of Two Different Land Use Datasets on Hydrological Simulations by Using SWAT Model

Abstract

Land use/cover (LULC) dataset can be addressed as one of the significant factors governing watershed hydrology. Thus, there is a necessity for using appropriate LULC data especially while working on the hydrology of sensitive watersheds from which drinking water is provided. The aim of this study is to analyze the effect of using two different LULC datasets on the hydrological components of a basin in Turkey. Omerli Basin that covers one of the important drinking water reservoirs of Istanbul with a drainage area of 621 km2 is selected as the study area. The Soil and Water Assessment Tool (SWAT), a physically-based hydrological and public domain model, is used as the hydrological model to evaluate the water budget of the basin. SWAT model is calibrated with an automatic calibration and uncertainty analysis program (SWAT-CUP) by using SUFI-2 algorithm. Model setup is conducted for two different LULC datasets which are CORINE obtained for year 2006, and LULC data produced from 2006 dated Landsat satellite image. This pioneer study evaluates and compares the impact of CORINE and Landsat LULC datasets used in hydrological modeling by using SWAT model at sub-basin level. It revealed that different LULC datasets yielded quite similar results in terms of surface water runoff and actual evapotranspiration in the Omerli Basin; however, different spatial distribution was observed especially in urbanized sub-basins. Despite the coarser land-use classification in Landsat data, it enabled the detection of different LULC classification with higher spatial resolution, and thus, different model outputs were achieved especially in the urbanized sub-basins.

Effects of Various Land Use Land Cover (LULC) Data on Hydrological Model Performances

“…While the monthly and annual average values of the simulations allowed us to interpret the overall results for the entire basin, visualizations were made to examine the changes in the subbasin-scale. Similar to [23], spatial differences in surface runoff values were more striking compared to water yield values. For this purpose, in Fig.…”

Land cover change analysis between 1990 and 2021 using Landsat images and object-based classification: A case study in Bodrum peninsula, Aegean Region, Turkey

“…There are many studies that determine LULC with opensource Landsat images effect on forest cover (Yavaşlı, Masek, & Franks, 2013), water resources (Cüceloğlu, Şeker, & Tanık, 2021), vegetation (İkiel & Koç, 2015), geomorphology (Ölgen, 2004) and soil salinity (Aksoy, Yıldırım, & Gorji, 2022). In recent years, there are a lot of studies in which Object-based classification is used in determining the LULC (Sertel & Akay, 2015;Alganci, Sertel, & Kaya 2018;Esetlili, Bektas Balcik, & Balik Sanli, 2018;Karabulut, Ceylan, & Bahar, 2021).…”

GIS and Hydrological Model Based Hydropower Potential Assessments of Temcha Watershed

“…The application of the SWAT hydrological model to assess the temporal and spatial variability of hydropower potential in the Temcha watershed in the upper Blue Nile basin. The assessment of the head, site selection, and simulation of flow at each selected site was carried out using the SWAT model (Zahou, et al, 2013;Strauch, et al, 2012;Cüceloğlu et al, 2021). The SWAT model generates stream network characteristics, the length of the river, and elevation difference for each stream within the watershed boundary.…”