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Intensity-Duration-Frequency Curves in a Data-Rich Era: A Review

期刊

WATER
卷 14, 期 22, 页码 -

出版社

MDPI
DOI: 10.3390/w14223705

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intensity-duration-frequency curves; dataset; rain gauge; satellite; radar; climate change

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This paper provides a comprehensive review of methodologies for constructing intensity-duration-frequency (IDF) curves and discusses the choice of dataset type, uncertainties, and benefits. The use of remotely sensed data as an alternative for rainfall data in ungauged or partially gauged areas is examined. The main aim is to present an overview of the state of the art in using different types of data to build IDF curves, supporting their inclusion in hydrological applications.
Intensity-duration-frequency (IDF) curves are widely used in the hydrological design of hydraulic structures. This paper presents a wide review of methodologies for constructing IDF curves with a specific focus on the choice of the dataset type, highlighting the main characteristics, possible uncertainties, and benefits that can be derived from their application. A number of studies based on updating IDFs in relation to climate change are analyzed. The research was based on a comprehensive analysis of more than 100 scientific papers and reports, of which 80 were found to be suitable for the aim of this study. To classify the articles, the key was mainly intensity-duration-frequency curves in relation to the types of datasets most used for their construction, specific attention was paid to the case study area. The paper aims to answer the following research questions. (i) What is the contribution of a data-rich era? (ii) Are remotely sensed data reliable to build IDFs in ungauged or partially gauged watersheds? (ii) How is uncertainty dealt with when developing IDFs? Remotely sensed data appear to be an alternative to rain-gauge data in scarcely gauged or ungauged areas; however, rain-gauge data are still a preferred dataset in the development of IDFs. The main aim of the present work is to provide an overview of the state of the art on the use of different types of data to build IDFs. The paper is intended to support the inclusion of different data types in hydrological applications.

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