Integrated GIS-Based Rainfall Forecasting and Urban Flood Susceptibility Assessment in Ordu, Türkiye

Abstract

Flooding has become one of the most significant hydrometeorological hazards affecting rapidly urbanizing coastal cities in the Black Sea Region of Türkiye. Ordu revi, particularly the Altınordu district and the lower Melet River basin, has experienced increasing flood susceptibility due to the combined effects of intense precipitation, complex topography, and expanding impervious urban surfaces. This study investigates rainfall variability and spatial flood susceptibility in Ordu  by integrating long-term precipitation records with Geographic Information System (GIS)-based spatial modelling. Monthly rainfall data covering the period from 2015 to 2024 were analyzed together with satellite-derived precipitation products from the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) dataset and digital elevation information obtained from SRTM data. Temporal analysis revealed that Ordu exhibits a persistently humid precipitation regime, with mean monthly rainfall ranging from  86 to 201 mm. The highest precipitation amounts occur during late autumn and winter, particularly in November, December, February, and March, whereas relatively lower rainfall conditions are observed during July and August. Frequency analysis using the Gumbel distribution and rainfall intensity estimation based on the Mononobe equation indicated that extreme precipitation increases considerably with longer return periods. Estimated rainfall depths for the 2-, 5-, 10-, and 15-year return periods were calculated as 330.35 mm, 467.82 mm, 558.83 mm, and 610.17 mm, respectively. The GIS-based overlay analysis demonstrated that  63% of the study area is characterized by moderate to high flood susceptibility. High-risk zones are predominantly concentrated in low-elevation coastal sectors and in areas adjacent to the Melet River corridor where dense urban development and reduced infiltration capacity intensify surface runoff generation. The produced flood susceptibility map successfully identifies priority areas requiring mitigation measures and climate adaptation strategies. The integration of statistical rainfall modelling, remote sensing datasets, and GIS-based spatial analysis provides a robust framework for understanding hydrometeorological risks in Ordu . The proposed methodology offers valuable scientific support for developing early warning systems, improving urban flood management policies, and promoting resilient spatial planning practices in coastal cities of the Black Sea Region.