Uncertainty Quantification in Geochemical Mapping: A Review and Recommendations

Geochemical mapping is a crucial tool that can provide valuable insights for a wide range of applications, including mineral resources prospecting, environmental impact assessment, geological process understanding, and climate change research. Despite its significance, geochemical mapping requires spatial modeling based on sparse, heterogeneous, and potentially inaccurate data sets. Moreover, the underlying geological processes are often imperfectly understood. Therefore, uncertainty quantification (UQ) is vital in geochemical mapping to ensure accurate and reliable results, ultimately facilitating well-informed decision-making. In this contribution, we distinguish two primary types of uncertainties: systemic and stochastic. We identify the key sources of uncertainties in geochemical mapping and review the techniques that have been employed or hold potential for uncertainty quantification, communication, visualization, and sensitivity analysis. This contribution also illustrates the general procedure of UQ in geochemical mapping by a case study of mapping geochemical anomalies associated with gold mineralization in northwestern Sichuan Province, China. We also explore potential strategies for mitigating the critical uncertainties, such as gathering more geochemical data, developing more effective models, enhancing our understanding of the geochemical dispersion process, or leveraging other thematic information or knowledge. Future research should prioritize addressing underexplored uncertainties and implementing more practical applications to validate the UQ procedure in geochemical mapping. Geochemical mapping is a vital tool for various applications such as finding minerals, assessing environmental impact, understanding geological processes, and researching climate change. However, the challenges lie in dealing with limited, varied, and potentially inaccurate data coupled with an imperfect understanding of geological processes. To ensure accurate and reliable results, we emphasize the importance of uncertainty quantification in geochemical mapping. Our review distinguishes between two main uncertainties, systemic and stochastic, and identifies their key sources in geochemical mapping. We also explore techniques for uncertainty quantification, communication, visualization, and sensitivity analysis. Using a case study in northwestern Sichuan Province, China, we illustrate the general procedure of uncertainty quantification by mapping geochemical anomalies related to gold mineralization. To address critical uncertainties, we suggest strategies such as gathering more data, improving models, and enhancing our understanding of geochemical dispersion. Future research should focus on exploring underexplored uncertainties and implementing more practical applications to validate the procedure of uncertainty quantification in geochemical mapping. Geochemical mapping is intricate due to its scale-dependent and heterogeneous nature Uncertainty quantification is an essential part of geochemical mapping The Monte-Carlo framework is effective to account for multiple crucial sources of uncertainty manifested in geochemical mapping