Examining the Influence of Landscape Patch Shapes on River Water Quality

Abstract

River water quality can be affected by a range of factors, including both point and non-point sources of pollution. Of these factors, changes in land use and land cover are particularly significant, as they can alter the structure of the landscape and consequently impact water quality in rivers. To investigate the relationship between patch shapes, a measure of landscape structure, and river water quality at the catchment scale, this study utilized spatial data from 39 catchments in the southern basin of the Caspian Sea. This study employed stepwise multivariate regression modeling to explore how changes in landscape structure, which can be measured by landscape metrics including the shape index, the contiguity index, the fractal dimension index, the perimeter–area ratio, and the related circumscribing circle, impact water quality variables. Four regression models—linear, exponential, logarithmic, and power models—were evaluated, and the most appropriate model for each water quality variable was determined using the Akaike information criterion. To validate the models, three groups of accuracy metrics were employed, and Monte Carlo simulation was utilized to analyze the models’ behavior. This study found that landscape structure metrics could explain up to 71% and 82% of the variations in the measures of TDS and Mg, respectively, and the shape index, the contiguity index, and fractal metric were particularly significant in predicting water quality. Moreover, this study verified the accuracy of the models and revealed that changes in landscape structure, such as a decline in patch continuity and an increase in patch complexity, can impact river water quality. The findings of this study suggest optimizing landscape structure metrics in land use planning to reduce river pollution and improve water quality.