An Approach for Determination of the Drainage Network Effect on GIUH Using Hesitant Probabilistic Fuzzy Linguistic Sets

Hüseyin Akay () and Müsteyde Baduna Koçyiğit ()
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Hüseyin Akay: Gazi University
Müsteyde Baduna Koçyiğit: Gazi University

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2021, vol. 35, issue 11, No 23, 3873-3902

Abstract: Abstract Digital elevation models (DEMs) enable extraction of stream networks, delineation of watersheds and determination of geomorphological characteristics. A widely used method for stream network extraction is to specify a threshold area required to initiate a channel. This is achieved by applying a threshold area value (As) in GIS software which displays the accumulated flow to each cell. In this study, the effect of the assigned As on the direct runoff hydrographs was analyzed. Of using different threshold values varying in a wide range, stream network extraction and watershed delineation were performed, and then stream orders, main channel lengths and related morphometric parameters were computed. The geomorphological instantaneous unit hydrograph (GIUH) theory was adopted to obtain the hydrological response of the watershed and three direct runoff hydrographs were considered for validation. Statistical parameters and cumulative density functions of both observed and simulated hydrographs were computed and uncertainty analysis was performed. The best performing value of As with respect to the stream order and main channel length was determined using hesitant probabilistic fuzzy linguistic sets for different runoff hydrographs and criteria considered. It was found that the As value affected the stream order as expected and a stream order of maximum 3 was adequate for estimation of the runoff hydrograph with acceptable accuracy without unreasonably increasing the computational effort.

Keywords: Geomorphological instantaneous unit hydrograph; Drainage network; Hesitant probabilistic fuzzy linguistic sets; Uncertainty (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s11269-021-02935-y

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