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Title: On the impact of gaps on trend detection in extreme streamflow time series
Authors: Slater, Louise
Villarini, Gabriele
Keywords: Gaps
Trend detection
Annual maximum
Times series analysis
Issue Date: 2017
Publisher: © Royal Meteorological Society. Published by Wiley
Citation: SLATER, L. and VILLARINI, G., 2017. On the impact of gaps on trend detection in extreme streamflow time series. International Journal of Climatology, 37(10), pp. 3976-3983.
Abstract: Streamflow time series often contain gaps of varying length and location. However, the influence of these gaps on trend detection is poorly understood and cannot be estimated a priori in trend-detection studies. We simulated the effects of varying gap size (1, 2, 5, and 10 years) and location (one quarter, one third, and half of the way) on the detection rate of significant monotonic trends in annual maxima and peaks-over-threshold, based on the most commonly-used trend tests in time series of varying length (from 15 to 150 years) and trend magnitude (β1). Results show that, in comparison with the complete time series, the loss in trend detection rate tends to grow with (i) increasing gap size, (ii) increasing gap distance from the middle of the time series, (iii) decreasing β1 slope, and (iv) decreasing time series length. Based on these findings, we provide objective recommendations and cautionary remarks for maximal gap allowance in trend detection in extreme streamflow time series.
Description: This paper is in closed access until 19th December 2017.
Sponsor: This study was supported by the Broad Agency Announcement (BAA) Program and the Engineer Research and Development Center (ERDC)–Cold Regions Research and Engineering Laboratory CRREL) under Contract No. W913E5-16-C-0002.
Version: Accepted for publication
DOI: 10.1002/joc.4954
URI: https://dspace.lboro.ac.uk/2134/23978
Publisher Link: http://dx.doi.org/10.1002/joc.4954
ISSN: 1097-0088
Appears in Collections:Closed Access (Geography)

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