A Modified Region of Influence Approach for Flood Regionalization

Eslamian, Seyed Saeid; Hosseinipour, E. Zia

doi:10.1061/41114(371)247

Cited by 4 publications

(7 citation statements)

References 22 publications

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“…Closer stations to the reference station were mostly assigned higher weights, but some stations at greater distance from the reference station also had high weights. These results of the RoI approach are in agreement with previous findings (Eslamian 2010a(Eslamian , 2010b. Estimation of hydrological parameters in ungauged stations or station with incomplete data requires more accurate and reliable methods, such as the RoI approach.…”

Section: Regionalization With the Roi Approachsupporting

confidence: 92%

“…In the metric space, this similarity is defined by the distance criterion. Researchers have employed different distance criteria, but the Euclidean distance metric has been used in most studies (Burn 1990a(Burn , 1990bHolmes et al 2002;Eslamian 2010aEslamian , 2010bDehghan et al 2018aDehghan et al , 2018b. By applying appropriate weights for available attributes in regions without data, acceptable and reliable results can be obtained for ungauged stations (Dehghan et al 2018a).…”

Section: Introductionmentioning

confidence: 99%

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Regionalization of potential evapotranspiration using a modified region of influence

Saray

Eslamian

Kløve

et al. 2019

Theor Appl Climatol

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This study examined the effect of different attributes on regionalization of potential evapotranspiration (ETp) in Urmia Lake Basin (ULB), Iran, using the region of influence (RoI) framework. Data for the period 1997-2016 from 30 weather stations were selected for the analysis. To achieve similarity between stations, climate, geographical, and statistical attributes were selected. To determine the effect of each attribute, the Shannon entropy weighting method was used. The results showed that attribute weighting had a significant impact on ETp clustering. Among the groups studied, the most significant effect of weighting was observed in the statistical attributes category. Among all attributes, skewness coefficient (C S) was the most useful in determining similarity between stations. Based on the results, ULB can be divided into three homogeneous regions. Proximity of weather stations did not always indicate similarity between them, but by weighting the stations in addition to weighting the attributes, more accurate estimates of ETp in the basin were obtained. Overall, the results demonstrate potential for application of the RoI approach in regionalization of ETp, by assigning a weight to weather stations and to influencing attributes.

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Section: Regionalization With the Roi Approachsupporting

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Regionalization of potential evapotranspiration using a modified region of influence

Saray

Eslamian

Kløve

et al. 2019

Theor Appl Climatol

View full text Add to dashboard Cite

show abstract

“…In recent decades, various studies have been carried out for regionalizing a basin by different tools. It can be cited to identify and select the characteristics of the study basin or stations using the principal component analysis (PCA) technique as well as regionalization of rainfall using hierarchical clustering (Dinpashoh et al, 2004;Eslamian, 2010;Garcia-Marın et al, 2011;Darand and Mansouri Daneshvar, 2014). In a number of studies, rainfall regionalization has been used for regional frequency analysis of flood or rainfall extreme data (Gaal et al, 2008b;Goyal and Gupta, 2014).…”

Section: Introductionmentioning

confidence: 99%

“…Generally, regionalization is performed based on similarity theory among the study stations and is measured by distance criterion. From the different distance criteria, metric distance which is used for determining the proximity of the study stations in a space characteristic has been widely applied and describes similarity between a series of attributes (Burn, 1990;Zrinji and Burn, 1994;Castellarin et al, 2001;Ramachandra Rao and Srinivas, 2006a;Gaal et al, 2008a;Eslamian, 2010).…”

Section: Introductionmentioning

confidence: 99%

Spatial clustering of maximum 24‐h rainfall over Urmia Lake Basin by new weighting approaches

Dehghan

Eslamian

Modarres

2017

Intl Journal of Climatology

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The lack of data in rainfall stations of Iran is one of the main problems in design and management of hydrologic systems. Moreover, the density of these stations network is not sufficient for estimation of rainfall at ungauged regions. Therefore, regionalization can be an essential tool to be applied for clustering the rainfall and spatial pattern analysis of homogeneous regions to quantify regional rainfall patterns. Homogeneous regions are usually defined based on different methods and with consideration of a category of attributes. Selection of attributes as representatives of the study region is an important aspect in clustering of a region, as is the importance degree (or determined weight) that each of these attributes can allocate to themselves. Consequently, the aim of this study is to select a broad category of climatic, geographical, and statistical attributes of the maximum 24‐h rainfall of the Urmia Lake Basin for 63 selected stations for the period 1979–2008 and next to determine an appropriate weight for each of the attributes in each defined category. To investigate the weighting effect in regionalizing and to determine the appropriate weight for each defined attribute, respectively, Ward's clustering technique, principal component analysis, and correlation coefficients matrix methods were used. The homogeneity measure test showed that all identified clusters are homogeneous. The clustering results showed that based on the different attributes categories, different results can be presented in terms of the number of clusters, distribution of stations, and spatial pattern of clusters. Moreover, the performances of the proposed weighting approaches for spatial clustering analysis are better than no‐weight scenario in most modes according to the spatial patterns and homogeneity measurements.

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“…However, it doesn't mean that each phenomenon is perfectly divisible on every given band, and thus for this purpose the supervised classification method was chosen. Maximum likelihood algorithm is widely used classification method in most of studies [130][131][132][133][134][135][136][137][138][139][140][141][142][143].…”

Section: Primary Detection Of Land-use Changesmentioning

confidence: 99%

Change Detection of Urban Land Use and Urban Expansion Using GIS and RS, Case Study: Zanjan Province, Iran

2018

International Journal of Constructive Research in Civil Enginee

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A Modified Region of Influence Approach for Flood Regionalization

Cited by 4 publications

References 22 publications

Regionalization of potential evapotranspiration using a modified region of influence

Regionalization of potential evapotranspiration using a modified region of influence

Spatial clustering of maximum 24‐h rainfall over Urmia Lake Basin by new weighting approaches

Change Detection of Urban Land Use and Urban Expansion Using GIS and RS, Case Study: Zanjan Province, Iran

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