GIS-based spatial prediction of poor-drainage areas using frequency ratio: a case study of Tekirdag Province, Turkey

Abstract

The present study aims to identify the distribution and the sensibility ratios of the poorly drained areas of Tekirdag Province. GIS-based frequency ratio (FR) was used to detect areas that are likely to limit agricultural production due to poor drainage. Sensitive areas were identified and classified using susceptibility analysis. Spatial features were calculated and mapped using FR by combining the factors that could cause the drainage problem in the study area. The results indicated that the drainage conditions in the majority of the study area fall in well-drained (20.14%) and somewhat excessively drained (18.22%) classes. Furthermore, the study area was found to be 50.99% well suited, 11.66% suited, 13.35% moderately suited, and 24.00% unsuited, respectively, for agricultural production. About one-third of the unsuited area was found to be under agro-production. Furthermore, agriculturally suited areas were located mostly in plateaus and sloping lands. On the other hand, unsuited areas were located in the lowland areas where the groundwater level is high, the slope is low, and alluvial lithology and heavily textured soil features are present, while most of the scrublands, forest lands, and vineyard land use classes are located in well-drained areas in both provincial boundaries and the hotspot areas. On the other hand, agriculture, paddy fields, barren lands, pasture, and settlements are mostly located in poorly drained areas. To minimize the effect of the drainage problems, it is crucial to detect poorly drained areas using susceptibility analysis on agricultural areas. As a result, the spatial distribution of poor drainage areas can be mapped precisely and so contribute to agricultural productivity. Thus, sustainable agricultural policies can be developed by contributing to the agricultural economy and food security.