Remote Sensing (Dec 2022)

Evaluation of Numerous Kinetic Energy-Rainfall Intensity Equations Using Disdrometer Data

  • Linh Nguyen Van,
  • Xuan-Hien Le,
  • Giang V. Nguyen,
  • Minho Yeon,
  • May-Thi Tuyet Do,
  • Giha Lee

DOI
https://doi.org/10.3390/rs15010156
Journal volume & issue
Vol. 15, no. 1
p. 156

Abstract

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Calculating rainfall erosivity, which is the capacity of rainfall to dislodge soil particles and cause erosion, requires the measurement of the rainfall kinetic energy (KE). Direct measurement of KE has its own challenges, owing to the high cost and complexity of the measuring instruments involved. Consequently, the KE is often approximated using empirical equations derived from rainfall intensity (Ir) inputs in the absence of such instruments. However, the KE–Ir equations strongly depend on local climate patterns and measurement methods. Therefore, this study aims to compare and evaluate the efficacy of 27 KE–Ir equations with observed data. Based on a re-analysis, we also propose an exponential KE–Ir equation for the entire Korean site, and the spatial distribution of its parameter in the equation is also discussed. In this investigation, we used an optical disdrometer (OTT Parsivel2) to gather data in Sangju City (Korea) between June 2020 and December 2021. The outputs of this study are shown as follows: (1) The statistically most accurate estimates of KE expenditure and KE content in Sangju City are obtained using power-law equations given by Sanchez-Moreno et al. and exponential equations published by Lee and Won, respectively. (2) The suggested KE–Ir equation applied to the entire Korean site exhibits a comparable general correlation with the observed data. The parameter maps indicate a high variance in geography.

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