Modelling of the water quality index of the São Francisco River Integrating Project using Minimum Spanning Tree and SKATER algorithm

Érika Alves Tavares Marques; Anthony Epifanio Alves; Rogério Moreira Chagas; Arisvaldo Vieira Méllo Júnior; Maria do Carmo Sobral

doi:10.5327/Z2176-94782799

Authors

Érika Alves Tavares Marques Universidade Federal de Pernambuco (UFPE) - Brazil https://orcid.org/0000-0002-6615-3347
Anthony Epifanio Alves Universidade Federal de Pernambuco (UFPE) - Brazil https://orcid.org/0000-0002-4966-4364
Rogério Moreira Chagas Universidade de São Paulo (USP) - Brazil https://orcid.org/0000-0001-5696-5694
Arisvaldo Vieira Méllo Júnior Universidade de São Paulo (USP) - Brazil https://orcid.org/0000-0001-7110-3128
Maria do Carmo Sobral Universidade Federal de Pernambuco (UFPE) - Brazil https://orcid.org/0000-0001-8945-1606

DOI:

https://doi.org/10.5327/Z2176-94782799

Keywords:

transposition of the São Francisco River; environmental quality; spatial modeling; water quality index.

Abstract

This study modeled the water quality index in the East and North Axis of the São Francisco River Integration Project (PISF) using the statistical tools Minimum Spanning Tree and SKATER algorithm. This study is justified by presenting, for the first time, a historical series over 13 years, considering water quality data from the hydrographic basins included in the two axes of the transposition, between 2009 and 2022, showing the spatial-temporal evolution of water quality indices during this period. The spatial variation identified in each axis is useful for establishing sustainable management and planning programs for the water bodies under study. In both the North and East Axes, the WQI of the basins ranged from Excellent to Poor during the study period. It is noteworthy that the best WQI corresponded to the São Francisco River Basin, as it is the water-donating basin. It is noteworthy that no sampling points classified as Very Poor were recorded in either the North or East Axis during the study period. The findings highlighted that the use of WQI, associated with statistics and spatial modeling techniques was efficient to define that the waters of the studied sampling points were suitable for multiple uses, however, considering that they are located in the semi-arid region, it is necessary to intensify management actions in these basins, as climate change related issues could affect water quality in the future.

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