Development of Rainfall Intensity-Duration-Frequency Curves Based on Dynamically Downscaled Climate Data: Arizona Case Study

Amin Mohebbi, Simin Akbariyeh, Montasir Maruf, Ziyan Wu, Juan Carlos Acuna, Katlynn Rose Adams

Research output: Contribution to journalArticlepeer-review

Abstract

The ideal framework for water infrastructure design in any region relies on rainfall characteristics of that region, which is defined through rainfall intensity-duration-frequency (IDF) curves. The current IDF curves are based on historical observations of precipitation. However, with the help of numerical models, more up-to-date IDF curves can be developed to reflect the current precipitation regime. Here, a weather research and forecasting (WRF) model was applied to produce the precipitation data for Arizona from 1950 to 2017. A total of 20 weather forecasting scenarios were simulated by changing the microphysics schemes to improve precipitation forecasting accuracy. The National Severe Storm Laboratory (NSSL) scheme with cloud condensation nuclei (CCN) improved the coefficient of determination by 10% and was selected as the optimum forecasting scenario. The IDF curves were then constructed based on the modeled data and annual maximum series analysis for each climate division in Arizona. The comparison between updated IDF curves and historical IDF curves showed that incorporating up-to-date precipitation data resulted in lower rainfall intensities for short durations.

Original languageEnglish (US)
Article number05021005
JournalJournal of Hydrologic Engineering - ASCE
Volume26
Issue number5
DOIs
StatePublished - May 1 2021

Keywords

  • Climate division
  • Intensity-duration-frequency (IDF) curves
  • Microphysics
  • Spatiotemporal precipitation
  • Weather research forecasting (WRF) model

ASJC Scopus subject areas

  • Environmental Chemistry
  • Civil and Structural Engineering
  • Water Science and Technology
  • Environmental Science(all)

Fingerprint

Dive into the research topics of 'Development of Rainfall Intensity-Duration-Frequency Curves Based on Dynamically Downscaled Climate Data: Arizona Case Study'. Together they form a unique fingerprint.

Cite this