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

Abstract

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.

Risk of Natural Hazards Caused by Extreme Precipitation in Poland in 1951–2020

“…Various indices are used to assess extreme precipitation in the context of natural hazards, e.g., a daily sum exceeding the 95th or 99th percentile of a given time series, calculated separately for each station with a daily sum of ≥1 mm [14,[34][35][36], or various amounts of precipitation; ≥30 mm/day, ≥50 mm/day, ≥70 mm/day, and ≥100 mm/day [13,16,22,28,32,33], i.e., with thresholds similar to these of the present study. As pointed out by some scientists [43][44][45], EDPr events could be characterized much better if researchers had at their disposal not only the amount of precipitation, but also its duration. However, acquisition of such data covering long multi-year periods of at least 70 years from several dozen stations in the whole country is almost impossible.…”

Flood Risk Assessment for an Irrigation Project in Odissa, India

“…IMD compiles these maps using daily rainfall data from Ordinary Rain Gauges (ORG) at 746 stations located within the states and their surroundings. Some of these stations have rainfall data spanning more than 30 years, and in some cases, over a century (10) .…”

“…Site-specific IDF curves, developed using local rainfall data, provide precise rainfall estimates for hydrological modeling. These curves enable the estimation of rainfall intensity for the 2-, 5-, 10-, 50-, and 100-year return periods (10) .…”

Modelling the future climate impacts on hydraulic infrastructure development in tropical (peri-)urban region: Case of Kigali, Rwanda

“…Among them, some emphasised the necessity of regularly updating the standard codes of practice to evaluate, attribute, and cope with the updates within the changing climate conditions, such as adjusting the flood design factors and rainfall estimations [ 12 , 17 , 20 ]. Meanwhile, multiple studies have tried to incorporate the changes through the IDF Curves [ 3 , 4 , 21 , 22 ].…”