PHYSICAL ANALYSIS OF REGIONALIZED FLOW AS AN AID IN THE IDENTIFICATION OF HYDROLOGICALLY HOMOGENEOUS REGIONS

Calegario, Arthur T.; Pruski, Fernando F.; Ribeiro, Rayssa B.; Ramos, Maria C. A.; Rego, Fernando S.

doi:10.1590/1809-4430-Eng.Agric.v40n3p334-343/2020

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Scientific Paper, Soil and Water Engineering • Eng. agríc. (Online) 40 (3) • May-Jun 2020 • https://doi.org/10.1590/1809-4430-Eng.Agric.v40n3p334-343/2020 copy

PHYSICAL ANALYSIS OF REGIONALIZED FLOW AS AN AID IN THE IDENTIFICATION OF HYDROLOGICALLY HOMOGENEOUS REGIONS

Authorship SCIMAGO INSTITUTIONS RANKINGS

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.

KEYWORDS
regionalization; long-term average streamflow; planning and management of water resources; cluster analysis; geographical convenience

	Validation indices	Number of clusters
	Validation indices	2	3	4	5
	Calinski Harabasz	42.7	38.3	49	46.4
Cluster 1	Dunn	0.16	0.16	0.24	0.25
Cluster 1	Sillhouette	0.45	0.415	0.45	0.43
	Xie_Beni	3.6	2.47	1.42	1.52
	Calinski Harabasz	166	193	215	325
Cluster 2	Dunn	0.41	0.16	0.2	0.15
Cluster 2	Sillhouette	0.72	0.63	0.59	0.62
	Xie_Beni	0.44	2.63	2.56	3.03
	Calinski Harabasz	37.2	30.2	28.9	27.4
Cluster 3	Dunn	0.3	0.19	0.22	0.23
Cluster 3	Sillhouette	0.43	0.33	0.37	0.39
	Xie_Beni	1.44	3.31	1.77	1.79
	Calinski Harabasz	58.6	46.5	46.8	55.6
Cluster 4	Dunn	0.37	0.21	0.3	0.29
Cluster 4	Sillhouette	0.52	0.42	0.44	0.43
	Xie_Beni	0.95	2.45	1.03	1.33

Grouping	Hydrologically homogeneous region
Grouping	1	2	3	4	5
Geo 1	$\begin{array}{l} 0.946 P e q_{750}^{1.002} \\ R^{2} = 0.95 \end{array}$	-	-	-	-
Geo 2	$\begin{array}{l} 1.161 P e q_{750} 0.948 \\ R^{2} = 0.97 \end{array}$	$\begin{array}{l} 0.979 P e q_{750} 0.993 \\ R^{2} = 0.97 \end{array}$	$\begin{array}{l} 1.109 P e q_{750} 0.992 \\ R^{2} = 0.91 \end{array}$	$\begin{array}{l} 0.439 P e q_{750} 1.146 \\ R^{2} = 0.96 \end{array}$	-
Geo 3	$\begin{array}{l} 1.161 P e q_{750} 0.948 \\ R^{2} = 0.97 \end{array}$	$\begin{array}{l} 1.109 P e q_{750} 0.992 \\ R^{2} = 0.91 \end{array}$	$\begin{array}{l} 0.439 P e q_{750} 1.146 \\ R^{2} = 0.96 \end{array}$	-	-
Cluster 1	$\begin{array}{l} 1.190 P e q_{750} 0.939 \\ R^{2} = 0.94 \end{array}$	$\begin{array}{l} 0.988 P e q_{750} 0.995 \\ R^{2} = 0.95 \end{array}$	$\begin{array}{l} 0.839 P e q_{750} 1.017 \\ R^{2} = 0.98 \end{array}$	$\begin{array}{l} 0.176 P e q_{750} 1.557 \\ R^{2} = 0.85 \end{array}$	-
Cluster 2	$\begin{array}{l} 1.442 P e q_{750} 0.890 \\ R^{2} = 0.98 \end{array}$	$\begin{array}{l} 1.376 P e q_{750} 0.915 \\ R^{2} = 0.95 \end{array}$	$\begin{array}{l} 0.913 P e q_{750} 0.988 \\ R^{2} = 0.96 \end{array}$	$\begin{array}{l} 0.184 P e q_{750} 1.557 \\ R^{2} = 0.96 \end{array}$	$\begin{array}{l} 0.964 P e q_{750} 0.997 \\ R^{2} = 0.87 \end{array}$
Cluster 3	$\begin{array}{l} 1.057 P e q_{750} 0.972 \\ R^{2} = 0.97 \end{array}$	$\begin{array}{l} 0.592 P e q_{750} 1.136 \\ R^{2} = 0.90 \end{array}$	-	-	-

Grouping	AE (%)	E₁ (-)	E₂ (-)	E₃ (-)	ER_m (%)
Geo 1	-32 a 84	0.52	0.33	0.32	18.43
Geo 2	-31 a 31	0.72	0.68	0.41	14.7
Geo 3	-30 a 33	0.71	0.67	0.41	14.7
Cluster 1	-30 a 48	0.66	0.60	0.39	15.85
Cluster 2	-34 a 86	0.67	0.53	0.44	15.48
Cluster 3	-33 a 58	0.56	0.46	0.34	18.6

		RC amplitude (-)
Grouping	HHR			Average of the estimated RC values (-)	P (mm)
		Observed	Estimated
	1	0.31 a 0.60	0.38 a 0.78	0.62	1317
Geo 2	2	0.31 a 0.60	0.32 a 0.49	0.43	1288
Geo 2	3	0.28 a 0.50	0.26 a 0.52	0.38	1125
	4	0.17 a 0.31	0.03 a 0.29	0.08	1165
	1	0.31 a 0.6	0.37 a 0.63	0.50	1302
Geo 3	2	0.28 a 0.5	0.26 a 0.52	0.38	1125
	3	0.17 a 0.31	0.03 a 0.29	0.08	1165
Cluster 3	1	0.31 a 0.6	0.37 a 0.63	0.50	1302
Cluster 3	2	0.17 a 0.5	0.04 a 0.37	0.12	1145

Associação Brasileira de Engenharia Agrícola SBEA - Associação Brasileira de Engenharia Agrícola, Departamento de Engenharia e Ciências Exatas FCAV/UNESP, Prof. Paulo Donato Castellane, km 5, 14884.900 | Jaboticabal - SP, Tel./Fax: +55 16 3209 7619 - Jaboticabal - SP - Brazil
E-mail: revistasbea@sbea.org.br

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[1] *Corresponding author. Federal University of Viçosa (UFV)/ Viçosa - MG, Brazil. E-mail: tcalegario@hotmail.com