Correlations chart: Tool to analyse the dynamics of water quality parameters

Rocha, Cézar H. B.; Casquin, Antoine P.; Pereira, Renata O.

doi:10.1590/1807-1929/agriambi.v23n5p383-390

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ARTICLES • Rev. bras. eng. agríc. ambient. 23 (5) • May 2019 • https://doi.org/10.1590/1807-1929/agriambi.v23n5p383-390 linkcopy

Correlations chart: Tool to analyse the dynamics of water quality parameters

Gráfico de correlações: Ferramenta para análise da dinâmica de parâmetros de qualidade da água

Authorship SCIMAGO INSTITUTIONS RANKINGS

ABSTRACT

The search for statistical techniques and forms of graphical representation that can explain the most relevant correlations among limnological variables can help interpret phenomena in a body of water. The objective of the article was to propose a graphical representation of the correlations among limnological variables applied in the contributing basin of the Dr. João Penido reservoir, in Juiz de Fora, Minas Gerais state, Brazil. Six sections were monitored monthly from May 2012 to April 2014, analysing 15 water quality parameters and their statistical correlations. The correlations were represented graphically with the program Gephi 0.8.2-beta. The influence of organic matter (of natural and anthropogenic origin resulting from pasture runoff and sewage) on water quality was verified, with an observed increase in water quality parameters especially nitrogen and phosphorous, oxygen consumed, chemical oxygen demand, turbidity and total suspended solids. It is concluded that the correlation chart assists in the understanding of the dynamics of the water quality parameters at the different sites analysed.

Key words:
water resources; limnological variables; hydrographic basin

Classes	Description
Forest	Class referring to plant physiognomy of the Atlantic Forest
Wetland	Area covered principally by Typha sp.
Urban area	Includes the roads and areas with land reclaimed for the provision of buildings and the buildings themselves
Reservoir	Refers to areas subject to the water storage due to the dam
Degraded Pasture	Areas where pasture is degraded by fire, overgrazing or erosion
Pasture	Undergrowth vegetation used by livestock

	pH	TSS	Cond	Tur	DO	OC	COD	BOD	NH₄	NO₂	NO₃	TN	PO₄	TP
P1
TSS	0.36
Cond	0.59**	-0.14
Tur	-0.16	-0.2	-0.13
DO	0.02	-0.03	-0.1	0.26
OC	0.38	-0.13	0.56**	-0.11	-0.03
COD	-0.36	-0.16	-0.19	0	-0.08	-0.06
BOD	-0.36	0.06	-0.25	-0.13	-0.08	-0.18	0.19
NH₄	0.17	0.02	0.22	-0.05	-0.11	0.31	0.05	-0.04
NO₂	-0.23	0.06	-0.22	-0.03	-0.33	-0.1	0.12	0.04	0.38
NO₃	0.3	-0.06	0.27	0.2	0.23	0.22	-0.16	-0.36	0.51**	0.36
TN	0.44*	-0.14	0.66**	0.01	0.12	0.51**	-0.23	-0.34	0.47*	0.09	0.83**
PO₄	0.25	0.08	0.07	-0.19	-0.21	0.48*	-0.23	0.03	-0.17	-0.04	-0.07	0.04
TP	0.05	0.23	0.06	-0.06	0.07	0.1	-0.36	-0.06	0.06	0.2	0.05	0.11	-0.11
E. coli	-0.07	0.08	-0.12	0.2	0.3	0.02	-0.09	-0.34	-0.21	-0.07	0.13	0.01	-0.1	-0.06
P2
TSS	-0.43*
Cond	0.62**	-0.2
Tur	-0.16	0.43*	-0.26
DO	0.27	-0.05	0.12	-0.22
OC	-0.16	0.26	-0.05	0.57**	-0.34
COD	-0.1	0.12	-0.24	0.24	-0.12	0.37
BOD	-0.07	0.04	-0.1	-0.03	-0.15	0.05	0.15
NH₄	-0.01	0.4	-0.04	0.56**	0.34	0.35	0.24	0.19
NO₂	-0.09	0.24	-0.18	0.52**	-0.16	0.52**	0.44*	0.16	0.60**
NO₃	-0.1	0.39	-0.23	0.68**	-0.19	0.65**	0.41	0	0.62**	0.91**
TN	0.17	0.19	0.12	0.36	-0.11	0.34	0.22	0.1	0.49*	0.65**	0.65**
PO₄	0.01	0.25	-0.04	-0.04	0.31	-0.18	-0.21	-0.14	0.03	0.18	0.1	-0.03
TP	-0.08	0.59**	-0.12	0.80**	0.02	0.53**	0.15	-0.04	0.74**	0.49*	0.64**	0.4	0.06
E. coli	-0.24	0.16	-0.13	0.44*	-0.17	0.19	0.17	-0.02	0.11	0	0.13	0.19	0.08	0.24
P3
TSS	-0.08
Cond	-0.16	-0.1
Tur	-0.07	0.3	0.14
DO	0.16	-0.17	-0.27	-0.51**
OC	-0.37*	0.11	0.27	0.37*	-0.3
COD	-0.01	0.16	-0.23	-0.06	0.09	-0.02
BOD	-0.04	0.02	-0.1	0.1	0.39*	-0.01	0.08
NH₄	0.04	0.02	0	-0.18	0.22	0.13	0.19	0.12
NO₂	0.07	0.36*	-0.21	0.33*	-0.03	-0.02	0.66**	0.23	0.40**
NO₃	-0.05	0.24	-0.07	0.61**	-0.42**	0.24	0.3	-0.05	0.12	0.72**
TN	0.11	0.21	0.14	0.66**	-0.33*	0.3	-0.02	0.06	0.24	0.42**	0.56**
PO₄	-0.11	0.35*	0.08	0.24	0.17	0.13	-0.07	0.43**	-0.08	0.04	0.05	0.07
TP	-0.2	0.05	-0.1	0.32	-0.11	0.40*	0.05	0.15	0.40**	0.32	0.22	0.45**	-0.03
E. coli	-0.28	0.04	0.33*	0.45**	-0.53**	0.78*	0	-0.06	-0.08	0.01	0.44**	0.29	0.09	0.16
P4
TSS	-0.12
Cond	0.48*	0.1
Tur	-0.07	0.68**	0.2
DO	0.17	0.09	0.39	-0.07
OC	-0.22	0.43*	-0.12	0.60**	-0.08
COD	-0.05	0.38	0	0.50**	-0.06	0.63**
BOD	0.03	0.27	0.11	0.18	-0.18	0.26	0.04
NH₄	-0.18	0.01	0.16	0.15	0.19	0.19	0.13	-0.05
NO₂	-0.16	0.39	0.27	0.73**	-0.32	0.55**	0.44*	0.26	0.34
NO₃	-0.22	0.04	0.18	0.38	-0.38	0.25	0.28	-0.07	0.17	0.79**
TN	-0.09	0.43**	0.48*	0.21	0.13	0.19	-0.01	0.29	0.3	0.53**	0.44*
PO₄	0.07	0.50**	0.26	0.87**	-0.18	0.47*	0.55**	0.09	0.17	0.73**	0.51**	0.19
TP	-0.08	0.68*	0.17	0.96**	-0.08	0.67**	0.51**	0.2	0.2	0.76**	0.37	0.28	0.80**
E. coli	-0.14	0.56*	-0.02	0.86**	-0.03	0.66**	0.41	0.16	0.02	0.50**	0.19	0.04	0.68**	0.86**
P5
TSS	0.05
Cond	0.23	-0.25
Tur	-0.03	0.54**	-0.03
DO	0.3	-0.29	0.26	-0.19
OC	0.1	0.23	0.17	0.62**	-0.27
COD	0.12	0.3	-0.14	0.26	-0.43*	0.41*
BOD	0.01	0.35	-0.39	-0.03	-0.37	0.04	0.33
NH₄	0.01	0.19	0.07	0.11	0.04	0.05	0.31	0.22
NO₂	0.01	0.24	-0.22	0.07	-0.3	0.14	0.3	0.02	-0.05
NO₃	-0.03	0.33	-0.11	0.46*	-0.4	0.34	0.48*	0.04	0.13	0.52**
TN	0.02	0.37	0.12	0.46*	-0.22	0.27	0.53**	0	0.53**	0.34	0.75**
PO₄	0.34	0.36	0.1	0.05	-0.35	0.17	0.33	0.48*	-0.03	0.18	0.22	0.2
TP	-0.05	0.44*	-0.12	0.77**	-0.04	0.4	0.42*	0.1	0.41*	0.05	0.43*	0.54**	-0.02
E. coli	-0.05	0.53**	-0.01	0.93**	-0.06	0.56**	0.15	-0.06	0.14	0.02	0.25	0.41	-0.03	0.72**
P6
pH	-0.05
TSS	-0.16	-0.21
Cond	0.13	-0.05	-0.05
Tur	0.14	0.32	0.32	0.28
DO	0.06	-0.46*	0.50*	0.04	-0.03
OC	-0.28	0	-0.03	0.09	0.04	-0.15
COD	-0.34	0.16	-0.12	0.31	-0.24	0.06	0.33
NH₄	-0.03	0.24	0.27	-0.06	0.04	0.24	0.27	0.2
NO₂	-0.27	0.53**	-0.08	-0.04	-0.3	0.25	0.42*	0.18	0.60**
NO₃	-0.31	0.48*	0.03	-0.08	-0.32	0.48*	0.22	0.04	0.34	0.72**
TN	-0.06	0.2	0.48*	0.03	0.25	0.53**	0.05	-0.15	0.49*	0.33	0.64**
PO₄	0.08	-0.14	-0.11	0.26	0.03	-0.07	-0.04	-0.09	-0.09	0.43*	-0.1	-0.25
TP	-0.02	0.06	-0.14	0.05	-0.22	-0.01	0.02	-0.14	0.31	0.3	0.06	-0.11	0.70**
E. coli	-0.06	0.01	0.01	0.06	0.35	0.27	-0.16	-0.24	-0.08	-0.07	0.19	0.3	-0.05	-0.14

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Unidade Acadêmica de Engenharia Agrícola Unidade Acadêmica de Engenharia Agrícola, UFCG, Av. Aprígio Veloso 882, Bodocongó, Bloco CM, 1º andar, CEP 58429-140, Tel. +55 83 2101 1056 - Campina Grande - PB - Brazil
E-mail: revistagriambi@gmail.com

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[TFN02] ** significant at p < 0.01; * significant at p < 0.05

[TFN03] P1 – Spring in the Atlantic Forest; P2 - Culvert in the mean course of the principal tributary under the road adjacent to the rural area; P3 - Culvert under State Highway AMG-3085 in the grazing area of the Burros stream in the reservoir; P4 – Culvert under Highway AMG-3085 in pasture area of the Grama stream; P5 - Outlet of the Vista Alegre stream in the rural area and P6 – Catchment to the Water Treatment Station (see Figure 2)