Citation

Deo RC, Byun HR, Kim GB, Adamowski JF. Environ. Monit. Assess. 2018; 190(8): 450.

Affiliation

Department of Bioresource Engineering, Faculty of Agricultural & Environmental Sciences, McGill University, Montreal, Québec, H9X 3V9, Canada.

Copyright

(Copyright © 2018, Holtzbrinck Springer Nature Publishing Group)

DOI

10.1007/s10661-018-6806-0

PMID

29974256

Abstract

A water resources index based on weight-accumulated precipitation over the passage of time in heavy rainfall events is used in this study for monitoring flood risk and peak danger, as well as to develop flood warnings. In this research, an hourly water resources index (WRI_hr) based on rainfall accumulations over the passage of time is proposed. WRI_hr is able to monitor flood risk by taking into account the hourly effective precipitation that accumulates the precipitation (P_hr) of both current and antecedent hours, while the contributions from the preceding hours is subjected to a time-dependent reduction function that addresses the depletion of water volume by various hydrological processes (e.g., discharge, runoff, evapotranspiration). By converting rainfall into a water resources index (WRI), the hourly precipitation over a 24-h period is redistributed to formulate a long-term water resources index (WRI_hr-L) that monitors flood status based on long-term (more than 1 year) fluctuations in P_hr and a short-term water resources index (WRI_D-hr-S) that considers shorter (D = 24-148 hourly) accumulations of the P_hr data. WRI was assessed for its potential in flood monitoring at two hydrologically diverse sites: Dobong (South Korea; August 1998) and Brisbane (Australia; December 2010-January 2011), and its applicability was verified using river water level (H) measurements at hydrological stations. The power spectrum density and spectral coherence of hourly rainfall, river water level, and the corresponding WRI showed good agreements, as did the low and high frequency wavelet components using the discrete wavelet transform algorithm. Importantly, WRI_24-hr-S computed over 24 hourly accumulation periods was able to mimic the risk of short-term (flash-style) floods caused by concentrated rainfall, whereas WRI_hr-L was more useful for flood risk assessment caused by an event over a long-term period. Dynamical changes in H were closely in-phase with the patterns of change noted in the WRI_hr over the respective temporal scale. We conclude that the proposed WRI was able to replicate the flood evolution over the passage of time and, therefore, could possibly aid in the early warning of water-related disasters, demonstrating its practicality for continuous monitoring of the flood risk when a sustained period of rainfall event is observed.

Language: en

Keywords

Antecedent rainfall; Australia; Flood monitoring system; Hourly water resources index; Korea; Short- and long-term flood monitoring