IMHE OpenIR  > 山地学报
Application of different clustering approaches to hydro-climatological catchment regionalization in mountainous regions, a case study in Utah State
Elnaz SHARGHI; Vahid NOURANI; Saeed SOLEIMANI; Fahreddin SADIKOGLU
Corresponding AuthorElnaz SHARGHI
2018-03
Source PublicationJournal of Mountain Science
ISSN1672-6316
EISSN1672-6316
Volume15Issue:3Pages:461-484
Subtype期刊论文
AbstractWith respect to the different hydrological responses of catchments, even the adjacent ones, in mountainous regions, there are a great number of motivations for classifying them into homogeneous clusters. These motivations include prediction in ungauged basins (PUB), model parameterization, understanding the potential impact of environmental changes, transferring information from gauged catchments to the ungauged ones. The present study investigated the similarity of catchments through the hydro-climatological pure time-series of a 14-year period from 2001 to 2015. Data sets encompass more than 13,000 month-station streamflow, rainfall, and temperature data obtained from 27 catchments in Utah State as one of the eight mountainous states of the USA. The identification, analysis, and interpretation of homogeneous catchments were investigated by applying the four approaches of clustering, K-means, Ward, and SOM (Self-Organized Map) and a newly proposed Wavelet-Entropy-based (WE-SOM) clustering method. By using two clustering evaluation criteria, 3, 5, and 6 clusters were determined as the best numbers of clusters, depending on the method employed, where each cluster represents different hydro-climatological behaviors. Despite the absence of geographic characteristics in input data matrix, the results indicated a regionalization in agreement with topographic characteristics. Considering the dependency of the hydrological behavior of catchments on the physiographic field aspects and characteristics, WE-SOM method demonstrated a more acceptable performance, compared to the other three conventional clustering methods, by providing more clusters. WE-SOM appears to be a promising approach in catchment clustering. It preserves the topological structure of data which can, as a result, be proofed in a greater number of clusters by dividing data into higher numbers of distinct clusters with similar altitudes of catchments in each cluster. The results showed the aptitude of wavelets to quantify the time-based variability of temperature, rainfall and streamflow, in the way contributing to the regionalization of diverse catchments.
KeywordCatchment clustering K-means Ward Self-Organized Map Wavelet – Entropy Utah
DOI10.1007/s11629-017-4454-4
Indexed BySCIE
Language英语
Quartile4区
TOP
Citation statistics
Cited Times:6[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.imde.ac.cn/handle/131551/23174
Collection山地学报
Affiliation1 Department of Water Resources Engineering, Faculty of Civil Engineering, University of Tabriz, P.O. Box: 51666, Tabriz, Iran; 2 Department of Civil Engineering, Near East University, P.O. Box: 99138, Nicosia, North Cyprus, Mersin 10, Turkey; 3 Department of Electrical and Electronic Engineering, Near East University, P.O. Box: 99138, Nicosia, North Cyprus, Mersin 10, Turkey
Recommended Citation
GB/T 7714
Elnaz SHARGHI,Vahid NOURANI,Saeed SOLEIMANI,et al. Application of different clustering approaches to hydro-climatological catchment regionalization in mountainous regions, a case study in Utah State[J]. Journal of Mountain Science,2018,15(3):461-484.
APA Elnaz SHARGHI,Vahid NOURANI,Saeed SOLEIMANI,&Fahreddin SADIKOGLU.(2018).Application of different clustering approaches to hydro-climatological catchment regionalization in mountainous regions, a case study in Utah State.Journal of Mountain Science,15(3),461-484.
MLA Elnaz SHARGHI,et al."Application of different clustering approaches to hydro-climatological catchment regionalization in mountainous regions, a case study in Utah State".Journal of Mountain Science 15.3(2018):461-484.
Files in This Item:
File Name/Size DocType Version Access License
2.pdf(3022KB)期刊论文出版稿开放获取CC BY-NC-SAView Application Full Text
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Elnaz SHARGHI]'s Articles
[Vahid NOURANI]'s Articles
[Saeed SOLEIMANI]'s Articles
Baidu academic
Similar articles in Baidu academic
[Elnaz SHARGHI]'s Articles
[Vahid NOURANI]'s Articles
[Saeed SOLEIMANI]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Elnaz SHARGHI]'s Articles
[Vahid NOURANI]'s Articles
[Saeed SOLEIMANI]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: 2.pdf
Format: Adobe PDF
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.