GDGT-based lake-level reconstruction and proxy dataset from Jili Lake (northwest China) over the past 5200 years: Implications for Silk Road dynamics and water availability in arid Central Asia

This repository contains the complete proxy dataset and analytical code for the palaeohydrological study of Jili Lake, focusing on its water-level history and catchment dynamics over the past 5.2 kyr. The data enable the replication of the quantitative lake-level reconstruction and support the environmental interpretations presented in the associated research article.<br><b>Data Contents</b>The repository comprises two core files.<b>1. </b><b>Source_Data_JiliLake.xlsx</b>This file consolidates all primary and calibration data. It includes six key datasets:GDGT-based lake-level reconstruction for the down-core sequence.Fractional abundances of GDGTs in down-core sediments, surface sediments, and catchment soils, providing the core proxy data and modern calibration.X-ray fluorescence (XRF) elemental scanning data for down-core sediments, used as a detrital input proxy.Fractional abundances of n-alkanes in down-core sediments, used for organic matter source analysis.<b>2. </b><b>Supplementary_Code_MonteCarlo_Simulation.py</b>This script provides the Monte Carlo simulation code used to calculate palaeo-water depth from the down-core GDGT indices. The simulated depths are subsequently converted to absolute lake-level elevations using core-top elevation and stratigraphic depth, as detailed in the associated manuscript.<br><b>Methodology &amp; Usage Notes</b>The lake-level reconstruction is derived from three independent GDGT indices (%Cren, %GDGT-0, RI), each of which exhibits a robust logarithmic relationship with water depth in Jili Lake, as established by our modern calibration study. The Monte Carlo simulation framework integrates these three proxy relationships and propagates their individual calibration uncertainties, thereby generating a probabilistic reconstruction of past water depth with quantified confidence intervals. The complementary XRF and n-alkane data offer insights into catchment processes and organic matter sources. This dataset is suited for palaeoclimate studies, method validation, and regional synthesis work.<br><b>Related Publication:</b>Chen, R. et al. Lake expansion underpinned the Silk Road prosperity during a drought period. Commun. Earth Environ. (under review).