## 1 Introduction  
The demand for water, both in quantitative and qualitative terms, is increasingly significant, taking into consideration population growth and economic development. Therefore, it is essential to manage water resources and other natural resources to guarantee access to water under suitable usage conditions [1]. Given this importance, the United Nations (UN) within the framework of Agenda 2030 prioritizes drinking water and sanitation as one of the 17 Sustainable Development Goals (SDGs) for a global sustainable development agenda by 2030. SDG 6 aims to ensure the availability and sustainable management of water and sanitation for all. Its main objectives involve improving water quality, integrated water resource management, universal access to basic sanitation, water use efficiency, and the protection and restoration of aquatic ecosystems such as forests, rivers, lakes, aquifers, and wetlands [2]. The assessment of water quality and mitigation of major sources of pollution are two of the pillars adopted by Brazil to fulfill SDG 6. This assessment is one of the steps in water resources management and is carried out through monitoring physical, chemical, and microbiological parameters via measurements of dissolved substance concentrations, physical properties, and analysis of pathogenic microorganisms [3]. The spatial distribution of land use is a key factor that affects water quality, where industrial, urban, and agricultural land uses generally pose relatively high pollution risks compared to other types of land use such as forests and wetlands [4]. In addition to land use, water quality can also be influenced by quantity, as it directly depends on the amount of water available to dissolve, dilute, and transport substances, whether beneficial or harmful to living organisms [5]. Hence, water quality may be perceived as the outcome of both natural processes and human activities within the watershed, with land use and cover therein acting as determining factors. Understanding its relationship with land use and cover can be useful for identifying potential risks to water quality and coordinating water resource management with other uses of environmental resources [3]. The conceptual model for analyzing the relationship between land use and water quality involves selecting a study area, selecting monitoring points, obtaining land use and water quality data, organizing a database, defining the scale of analysis, selecting appropriate mathematical models, running models, and analyzing results and reference parameters [6; 7]. Understanding the relationship between land use and water quality is most easily achieved through statistical techniques [8; 9]. The most common statistical techniques used are Correlation Coefficients, Least Squares Method, Weighted Geographic Regression, Bayesian Hierarchical Linear Regression, Multiple Linear Regression, Stepwise Multiple Regression, Mixed Effect Linear Model, Partial Least Squares Regression, Principal Component Analysis, and Redundancy Analysis [8; 9; 10]. The impacts of land use and land cover on water quality are mainly assessed at three different spatial scales: sub-basin (catchment areas), riparian zone or parallel marginal zone (buffers), and point (concentric circles). According to [PERSON] et al. [10], most studies adopt only one of these scales, but recently studies have been conducted using a multiscale approach, adopting more than one scale at the same time, showing that human activities at different scales lead to different impacts on water quality [6; 10]. The optimal spatial scale, from a statistical perspective of correlation between land use and water quality, still varies from case to case, due to the peculiar characteristics of each river basin, the intensity of human interference, and the accuracy of the data. Thus, more research is needed to quantify the effect of different scales of land use on water quality to improve water resource management [4; 6; 9; 10].