Spatial data analysis for mapping managed aquifer recharge potential under uncertainty in the Murray-Darling Basin: Python 3 code and input data

Managed aquifer recharge (MAR) potential was assessed under unconfined and confined aquifer conditions using a spatial analysis method that incorporates uncertainty. Long-term groundwater level trends identified areas of decline, while sensitivity analysis showed that key variable impacts are location-dependent. This integrated approach highlights opportunities to reduce groundwater stress and support agricultural productivity. This collection underpins a journal article published in January 2026 in Groundwater for Sustainable Development: https://doi.org/10.1016/j.gsd.2026.101579

本研究采用考虑不确定性的空间分析方法，针对无压含水层与承压含水层两种水文地质条件，评估了含水层人工补给（Managed Aquifer Recharge, MAR）的潜力。通过长期地下水位动态趋势分析识别出水位下降区域，敏感性分析结果显示，关键变量的影响效应具有区位依赖性。该综合研究方法可为缓解地下水压力、保障农业生产力提供可行途径。本数据集支撑了2026年1月发表于《地下水与可持续发展（Groundwater for Sustainable Development）》期刊的一篇学术论文，其DOI链接为：https://doi.org/10.1016/j.gsd.2026.101579