Water Quality Modeling in Headwater Catchments: Comprehensive Data Assessment, Model Development and Simulation of Scenarios

Abstract

Water quality is a major concern globally and in headwater catchments of developing countries it is often poorly managed. In these catchments, having scarce and heterogeneous information hinders the development of water quality assessments and predictive models to support management. To address this issue, the authors propose a framework of three stages that allows for: (i) conducting a comprehensive assessment of water quality; (ii) the development of a mountain stream water quality model based on said assessment; and (iii) the simulation of scenarios with the model to resolve conflicts between uses and quality of water. The framework involves multivariate analyses of principal components and clusters and follows a novel modeling protocol mainly designed for mountainous streams in developing countries. Applied to an Andean catchment in Colombia, the first stage of the framework revealed the catchment’s most significant water quality constituents and the most polluted season. The problematic constituents in this catchment include pathogens, nutrients, organic matter, and metals such as the highly toxic Cr and Pb, while water pollution is the highest during the driest months of the year (i.e., January to March). In the second stage, the model was calibrated reproducing the concentrations of pathogens, organic matter, and most nutrients, and showed a predictive capacity. This capacity was measured with an objective function to be minimized based on a normalized root mean square error. It increased only 14% when verified with a different dataset. In addition, during the third stage of the proposed framework, the simulation of alternative scenarios showed that centralized treatment is not sufficient to make water safe for potabilization and agriculture in the catchment. For this reason, improving water quality in the sub-basins at the highest altitudes is required. The proposed framework can be applied in other headwater catchments where information is limited, and where an improved management of water quality is needed.