VivianGrom/SensitivityLEMandDZ: v1.0 - Initial Release

This repository contains the code and data used to investigate how surface processes influence sediment provenance and the interpretation of detrital zircon (DZ) U-Pb age distributions. By integrating landscape evolution models (LEMs) with statistical provenance models, this study explores how variations in erosion, lithologic contributions, and zircon concentrations affect the representation of source populations in sedimentary records and contribute to uncertainty in provenance interpretations. The workflow combines numerical landscape evolution simulations with statistical mixing experiments to compare three approaches to sediment mixing: a null model based on source proportions, a mass-based model, and a grain-number-based model. Synthetic and published detrital zircon age distributions are used to evaluate differences among these approaches through repeated sampling experiments, with Kolmogorov–Smirnov (K-S) statistics and R^2 metrics used to quantify differences between modeled age distributions. The repository includes code and data for: 1. Landscape evolution simulations: Modeling uplift, erosion, and soil diffusion in layered and spatially distinct geological source configurations using Landlab. 2. Tracking sediment and zircon properties: Quantifying time-dependent erosion rates, lithologic proportions, and source-specific zircon concentrations. 3. Synthetic provenance experiments: Simulating sediment mixtures from synthetic detrital zircon source populations to evaluate the effects of alternative mixing assumptions. 4. Empirical provenance experiments: Applying the statistical mixing framework to detrital zircon age distributions from published datasets. 5. Statistical evaluation and data visualization: Comparing mixing approaches using K-S statistics and R^2 metrics, with model outputs and experiment results saved in NetCDF and Excel formats. These resources support the investigation of how landscape evolution and sediment-mixing assumptions influence detrital zircon provenance interpretations. The repository provides the code and data needed to reproduce the described experiments and explore the uncertainty associated with reconstructing sediment source contributions from detrital zircon records. Associated manuscript: “Exploring Surface Process Imprints in Sediment Provenance: Integrating Landscape Evolution and Statistical Models to Assess Uncertainty in Detrital Zircon Provenance.” Basin Research (2026; under review).