Treffer: Error Analysis in Back‐Stripping Procedure for Modeling Natural Subsidence: Application in the Po Delta Area (Northern Italy).

The back‐stripping technique is widely used in geological modeling to quantify basin subsidence history, sedimentation rates, and tectonic subsidence. Recent applications involve reconstructing paleo‐water depths, especially in oceanic and Arctic studies. Despite the availability of open‐source Matlab codes based on this procedure, comprehensive investigations including errors from data acquisition remain lacking. Many studies address the errors related to model parameters, neglecting a systematic approach crucial for result accuracy. To enhance the reliability in subsidence rate calculations via back‐stripping, we propose a method to analyze errors introduced during the pre‐processing of input data. Our approach starts with a qualitative identification of key error sources and proceeds with a quantitative estimation of each of them, using appropriate mathematical techniques such as linear interpolation and combinatorics. The proposed method is applied to the Po Delta in northern Italy, a region historically influenced by anthropogenic and natural subsidence. Analyzing a 2D geological section characterized by thin Holocene sedimentary successions, we identified 12 error sources, grouped into four basic categories: geometry of the model layers, distribution of lithologies, petrophysical properties, and factors related to depositional environments and geodynamics. We then assessed the error ranges and their probability of occurrence. The results show that errors can vary significantly—from the meter to millimeter‐scale—defining the magnitude and distribution of each error source along line, which is essential for accurately interpreting model results and assessing related uncertainties. The study also establishes a replicable workflow for future uncertainty management, contributing to enhance open‐source tools based on the back‐stripping procedure. Plain Language Summary: The numerical back‐stripping procedure is a valuable tool for understanding the formation of sedimentary basins and reconstructing past seafloor in oceanic regions. However, uncertainties associated with this method—arising from data acquisition, processing, and interpretation—can impact on its results. In this study, we identify and quantify the main sources of error affecting the back‐stripping technique, using standard mathematical tools such as linear interpolation and combinatorics. Our analysis reveals that these errors influence various model parameters and shows that some errors occur always, while others happen often. The proposed approach enables the assessment of error magnitude and distribution in both time and space, and it can be adapted to a wide range of geological settings experiencing land subsidence. Furthermore, our method can be easily integrated into open‐source software implementing the back‐stripping technique, thereby improving its overall robustness and applicability. Key Points: A qualitative and quantitative analysis of the main errors affecting the back‐stripping technique in geological modeling is presentedTwelve categories of error are identified, covering geological, stratigraphic, environmental and geodynamic featuresCombinatorics and linear interpolation techniques proven effective for error quantification in numerical back‐stripping codes [ABSTRACT FROM AUTHOR]