Trend Assessment by the Innovative-Şen Method

İsmail Dabanlı (), Zekai Şen, Mehmet Öner Yeleğen, Eyüp Şişman, Bülent Selek and Yavuz Selim Güçlü
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İsmail Dabanlı: Istanbul Technical University
Zekai Şen: Istanbul Technical University
Mehmet Öner Yeleğen: Fatih Sultan Mehmet Vakif University
Eyüp Şişman: Yildiz Technical University
Bülent Selek: State Hydraulic Works (DSI)
Yavuz Selim Güçlü: Istanbul Technical University

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2016, vol. 30, issue 14, No 14, 5193-5203

Abstract: Abstract Hydro-meteorological time series may include trend components mostly due to climate change since about three to four decades. Trend detection and identification in a better and refined manner are among the major current research topics in water resources domain. Even though different methodologies can be found for trend detection in literature, two well-known procedures are the Mann-Kendall (MK) trend test and recently innovative-Şen trend method, which provides different aspects of the trend. The theoretical basis and application of these two methods are completely different. The MK test gives a holistic monotonic trend without any categorization of the time series into a set of clusters, but the innovative-Şen method is based on cluster and provides categorical trend behavior in a given time series. The main purpose of this paper is to provide important differences between these two approaches and their possible similarities. The applications of the two approaches are given for hydro-meteorological records including relative humidity, temperature, precipitation and runoff from Ergene drainage basin in the north-western part of Turkey. It is observed that although MK trend test does not show significant trend almost in all the cases, the innovative-Şen approach yields trend categorizations as “very low”, “low”, “medium” “high” and “very high”, which should be taken into consideration in future flood (“very high”) and drought (“very low”) studies.

Keywords: Clustered trend; Climate change; Mann-Kendall; Innovative-Şen; Ergene basin (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/s11269-016-1478-4

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