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Published in: Water Resources Management 4/2024

01-02-2024

Multiple Risk Trend Identification with Seesaw Methodology in Hydrometeorology Time Series

Author: Zekâi Şen

Published in: Water Resources Management | Issue 4/2024

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Abstract

In this paper, trends are determined by population characteristics through a set of the risk levels (exceedence probabilities) from CDFs. This is a new method in which unique trend identification is possible at any risk level, not just the average. The entire approach is based on the cumulative distribution functions (CDF) risk levels for time series records and their two equal halves. At a given risk level the corresponding data amounts represent weights at two ends of a seesaw and the whole data amount the support. In this way, also extreme values such as low (dry, drought) and high (wet, flood) trend possibilities can be defined without any restrictive assumptions. The application of the methodology is given for annual discharge measurements of Danube River, in addition to the annual precipitation records from Istanbul meteorology station.

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Metadata
Title
Multiple Risk Trend Identification with Seesaw Methodology in Hydrometeorology Time Series
Author
Zekâi Şen
Publication date
01-02-2024
Publisher
Springer Netherlands
Published in
Water Resources Management / Issue 4/2024
Print ISSN: 0920-4741
Electronic ISSN: 1573-1650
DOI
https://doi.org/10.1007/s11269-024-03737-8

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