From data to decision : Understanding and mitigating uncertainty in watershed water quality models

Abstract

Water quality models are essential tools for understanding, managing, and predicting the impacts of various factors on the quality of water within a watershed (Russo et al., 2023). These models play a crucial role in environmental management, informing policies and decisions related to water resources, pollution control, and ecosystem conservation. However, the accuracy and reliability of these models are often challenged by various sources of uncertainty, which can significantly affect their predictive capabilities and confidence in their outputs (Gorgoglione et al., 2019). The objective of this paper is to identify and analyze the sources of uncertainty in water quality models at the watershed scale. By doing so, we aim to provide a comprehensive understanding of the factors that contribute to uncertainty and offer insights into how these uncertainties can be managed or mitigated. Understanding these uncertainties is critical for improving model performance, enhancing decision-making, and ultimately achieving better outcomes for water resource management.