A New Empirical Formulation of the Areal Reduction Factor for Design Rainfalls Applied to the Umbria Region in Central Italy
Publication: Journal of Hydrologic Engineering
Volume 29, Issue 2
Abstract
A reliable estimate of the areal reduction factor (ARF), useful for implementing the upscaling procedure of point rainfall information, is of crucial relevance in many hydrological applications aimed at hydraulic structures design. Despite the availability of different methodologies in the literature, the choice of the best formulation to be applied for ARF assessment in a specific region remains an open problem. In fact, the transposition of ARF formulations to areas different from those where they were developed, even with similar geographical features, could lead to incorrect ARF estimates and relevant errors in design rainfalls, especially for short durations. In this paper, a new deterministic fixed-area approach is proposed; it relies upon an averaging procedure of the ratios between areal and local annual maximum rainfalls. The proposed approach was applied to the study area of Umbria region in central Italy, where a parametric relation expressing ARF in a wide range of rainfall duration (5–2,880 min) and areas (up to about 6,100) was derived. A comparison of the proposed approach with the most widely used empirical methodologies was also performed. The methodology can be adopted in any other region where a network characterized by a minimum length of rainfall time series of 7 years and a proper spatial density of stations is available.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The authors would like to acknowledge Marco Stelluti and the Umbrian Regional Authority for providing the data.
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© 2024 American Society of Civil Engineers.
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Received: May 8, 2023
Accepted: Nov 20, 2023
Published online: Feb 7, 2024
Published in print: Apr 1, 2024
Discussion open until: Jul 7, 2024
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