Scaling Characteristics of Storm-Centered ARF Using Radar Rainfall

8 pages•Published: September 20, 2018

Abstract

In the hydraulic design practices, it is necessary to apply areal reduction factor to convert the point rainfall into the areal rainfall in the reference area. The fixed-area ARF (ARFf), which is commonly used, can be considered unrealistic because it is estimated through independent frequency analysis of the point rainfall and the areal rainfall. In this study, storm-centred ARF (ARFs) was estimated using radar rainfall data to reflect the spatial distribution characteristics of storm events effectively. ARFs representing the duration and the return period was extracted by 95% non-exceedance probability of the Weibull distribution to derive envelope covering all values from various storm events. ARFs has a correlation with not only the reference area but also the duration and the return period. Their relationships are defined as the scaling factors. A new ARFs equation that reflects the spatio-temporal characteristics of actual rainfall is presented.

Keyphrases: areal reduction factor(arf), radar rainfall, scaling factor, storm centered method

In: Goffredo La Loggia, Gabriele Freni, Valeria Puleo and Mauro De Marchis (editors). HIC 2018. 13th International Conference on Hydroinformatics, vol 3, pages 1070-1077.

Links:	https://easychair.org/publications/paper/gVN6
	https://doi.org/10.29007/hmzf

BibTeX entry

@inproceedings{HIC2018:Scaling_Characteristics_Storm_Centered,
  author    = {Eunji Kim and Boosik Kang},
  title     = {Scaling Characteristics of Storm-Centered ARF Using Radar Rainfall},
  booktitle = {HIC 2018. 13th International Conference on Hydroinformatics},
  editor    = {Goffredo La Loggia and Gabriele Freni and Valeria Puleo and Mauro De Marchis},
  series    = {EPiC Series in Engineering},
  volume    = {3},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2516-2330},
  url       = {/publications/paper/gVN6},
  doi       = {10.29007/hmzf},
  pages     = {1070-1077},
  year      = {2018}}

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