Comparative Analysis of Intensity–Duration–Frequency Curves in Arid Regions of Central Iran (Case Study: Rain Gauge and Synoptic Stations of the Sanij Watershed – Bidakhvid Station- Yazd)

Document Type : Research Paper

Author

Ph.D, Rangeland and Watershed Management Department, Faculty of Natural Resources and Desertification, Yazd University, Yazd, Iran.

10.29252/aridbiom.2026.4056

Abstract

Intensity–Duration–Frequency (IDF) curves are among the most important tools for analyzing rainfall occurrence frequency and estimating return periods of precipitation events in hydrological studies. The objective of this research is to derive and compare IDF curves based on data from rain gauge and synoptic stations in the Sanij watershed (Bidakhvid station), located in the arid regions of central Iran. For this purpose, 24-hour rainfall data and instantaneous rainfall records from the selected station were utilized. IDF curves based on 24-hour rainfall were developed using the Ghahreman method. In addition, IDF curves derived from instantaneous rainfall data were extracted using the EasyFit software and selected probability distribution functions. The IDF curves were generated for various rainfall durations up to 24 hours and return periods ranging from 2 to 250 years. The results indicate that rainfall intensity during the second half of the year (autumn and winter) is, on average, approximately 60% higher than that of the first half of the year (spring and summer). This difference becomes more pronounced for longer return periods and extended rainfall durations. Furthermore, the mean annual rainfall intensity during the second half of the year was estimated to be about 35% higher than that of the first half. Considering that a significant portion of precipitation in the second half of the year occurs as snowfall and has a limited contribution to runoff and flood generation, a more detailed seasonal and temporal analysis of precipitation is essential for accurate runoff assessment. The findings demonstrate that neglecting temporal–seasonal differentiation of rainfall can result in errors exceeding 30% in estimating effective rainfall intensity. Therefore, the application of integrated approaches, including satellite-based analyses, local observational data, and indigenous knowledge from local residents, is recommended to distinguish between effective and ineffective precipitation in flood generation. These approaches can significantly enhance the accuracy of hydrological modeling, water resources management, and flood control strategies in the study area.

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