Abstract：
:The theory of critical slowing down (CSD) suggests an increasing pattern in the time series of CSD indicators near catastrophic events. This theory has been successfully used as a generic indicator of early warning signals in various fields, including climate research. In this paper, we present an application of CSD on water level data with the aim of producing an early warning signal for floods. To achieve this, we inspect the trend of CSD indicators using quantile estimation instead of using the standard method of Kendall's tau rank correlation, which we found is inconsistent for our data set. For our flood early warning system (FLEWS), quantile estimation is used to provide thresholds to extract the dates associated with significant increases on the time series of the CSD indicators. We apply CSD theory on water level data of Kelantan River and found that it is a reliable technique to produce a FLEWS as it demonstrates an increasing pattern near the flood events. We then apply quantile estimation on the time series of CSD indicators and we manage to establish an early warning signal for ten of the twelve flood events. The other two events are detected on the first day of the flood.
journal_name
Int J Environ Res Public Healthauthors
Syed Musa SMS,Md Noorani MS,Abdul Razak F,Ismail M,Alias MA,Hussain SIdoi
10.3390/ijerph17176131subject
Has Abstractpub_date
2020-08-24 00:00:00issue
17eissn
1661-7827issn
1660-4601pii
ijerph17176131journal_volume
17pub_type
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