A High-Resolution (30m) Daily Soil Moisture Dataset via Causal Deep Learning (2016–2023)

This dataset provides an ultra-high-resolution daily soil moisture record specifically covering Hubei Province, China, spanning from 2016 to 2023. Generated utilizing advanced causal deep learning methodologies, it features an unprecedented spatial resolution of 30 meters and a daily temporal resolution, encompassing both Surface Soil Moisture (SSM) and Root Zone Soil Moisture (RZSM). This level of granular detail makes it highly valuable for regional precision agriculture, eco-hydrological modeling, and local-scale water resource management across the province. By employing a causal deep learning framework rather than relying solely on traditional statistical correlations, this dataset explicitly models the underlying cause-and-effect relationships between meteorological drivers and land surface conditions. This innovative approach ensures a physically robust, accurate, and reliable representation of complex, high-resolution soil moisture dynamics tailored to the specific environmental and geographical context of Hubei Province. The development of this dataset was financially supported by the Wuhan Natural Science Foundation Exploration Project (Chenguang Project) under grant number 2024040801020279. Researchers and practitioners utilizing this soil moisture data for academic or applied studies are kindly requested to properly cite the dataset and acknowledge this funding source in their related publications and research outputs. (Data Availability Note: Due to its large file size, the complete 2000–2023 soil moisture dataset is being uploaded in separate parts. This upload represents Part 3, covering the 2016–2023 period.)本数据集提供覆盖中国湖北省的超高分辨率逐日土壤湿度记录，时间跨度为2016年至2023年。本数据集采用先进的因果深度学习方法生成，具备前所未有的30米空间分辨率与逐日时间分辨率，涵盖表层土壤湿度（Surface Soil Moisture, SSM）与根区土壤湿度（Root Zone Soil Moisture, RZSM）两类数据。这种高粒度细节特征使其在湖北省的区域精准农业、生态水文模拟以及局域水资源管理等领域具有极高应用价值。 与仅依赖传统统计相关性的方法不同，本数据集采用因果深度学习框架，显式建模了气象驱动因子与地表状态间的内在因果关联。这一创新方法确保了针对湖北省特定环境与地理背景的复杂高分辨率土壤湿度动态过程具备物理鲁棒性、准确性与可靠性的表征。 本数据集的研发得到了武汉市自然科学基金探索项目（晨光计划）（项目编号：2024040801020279）的经费支持。恳请使用该土壤湿度数据开展学术研究或应用实践的研究者与从业者，在相关出版物及研究成果中正确引用本数据集，并对本资助来源予以致谢。 （数据可用性说明：由于文件体量较大，完整的2000–2023年土壤湿度数据集将分批次上传。本次上传为第3部分，涵盖2016–2023年时段。）