Physical Analysis of Regionalized Flow as an Aid in the Identification of Hydrologically Homogeneous Regions

Abstract

Regionalization is an important technique for estimating the flow of hydrographic sections with a lack of data. First, it is necessary to identify hydrologically homogeneous regions (HHRs), which are commonly validated via statistical analyses. Because this step is understood to be subjective, studies that contribute to a greater reliability in identifying regions are needed. In this context, the objective was to evaluate the inclusion of a physical analysis of the average regionalized flow rates as an aid to identify HHRs. The groupings were defined on the basis of geographical convenience methods and cluster analysis. For the assessment of regionalized flows, six statistical indices were used with a physical analysis that was performed via a comparison of the runoff coefficient to the spatial distribution of precipitation values. It was concluded that the physical analysis reduced the subjectivity in the identification of HHRs.

Minimum streamflow regionalization in a Brazilian watershed under different clustering approaches

“…The drainage area (A, in km 2 ), perimeter (P, in km), centroid X (X, in km), centroid Y (Y, in km), and mean slope (D, in %) of each subwatershed were derived individually from the DEM. Centroids X and Y were used to obtain geographically continuous regions (Rao & Srinivas 2006, Calegario et al 2020. The mean annual total rainfall (p, in mm) was calculated with the aid of the Thiessen Polygon method using datasets from the rain gauges (Cabral et al 2016).…”

Regional Flood Frequency Analysis of Northern Iran

“…Various regionalization techniques have been developed by researchers for the determination of homogeneous regions [7,[13][14][15][16][17][18][19][20][21]. Hierarchical Agglomerative Clustering has become a popular tool for regional distribution identification, and testing of outlier stations [22][23][24][25][26][27]. Tasker and Thomas (1978) applied geographical regionalization method in Arkansas [22].…”

“…The results suggested that the combination of SOM and Ward is much better than the combination of either SOM or fuzzy c-mean and K-mean. Calegario et al (2020) conducted regionalization to identify Hydrologically Homogeneous Regions (HHRs) in the Doce River basin [27]. Grouping was done based on geographical convenience methods and cluster analysis.…”