Application of different clustering approaches to hydro-climatological catchment regionalization in mountainous regions, a case study in Utah State

doi:10.1007/s11629-017-4454-4

CORC > 成都山地灾害与环境研究所 > 中国科学院水利部成都山地灾害与环境研究所 > Journal of Mountain Science > Journal of Mountain Science-2018 > Vol15 No.3

	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
刊名	Journal of Mountain Science
	2018-03
卷号	15 期号:3 页码:461-484
关键词	Catchment clustering K-means Ward Self-Organized Map Wavelet – Entropy Utah
ISSN号	1672-6316
DOI	10.1007/s11629-017-4454-4
通讯作者	Elnaz SHARGHI
英文摘要	With 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.
电子版国际标准刊号	1672-6316
语种	英语
内容类型	期刊论文
源URL	[http://ir.imde.ac.cn/handle/131551/23165]
专题	Journal of Mountain Science _Journal of Mountain Science-2018_Vol15 No.3
作者单位	1 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
推荐引用方式 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.