Climate Change Impacts on Soil Processes and Land Degradation Risks in Tea-Growing Regions of the Central Highlands, Vietnam

**Description** This dataset provides a high-resolution, multi-dimensional representation of climate–soil interactions in tea-growing regions of the Central Highlands of Vietnam, with a focus on Bao Loc City, Lam Dong Province. It supports the study: *“Climate Change Impacts on Soil Processes and Land Degradation Risks in Tea-Growing Regions of the Central Highlands, Vietnam”* . The dataset integrates climate variability, soil properties, and land degradation indicators over the period 2005–2023. It includes both observationally derived and model-supported variables, structured to enable reproducible analysis of climate impacts on soil processes in tropical highland agroecosystems. **Key components of the dataset include:** * **Climate data:** Daily temperature (mean, maximum, minimum) and precipitation, along with derived rainfall intensity and extreme climate indicators (heavy rainfall days and drought days).* **Soil data:** Multi-depth soil profiles (0–20 cm and 20–40 cm) with replicated measurements of pH, soil organic matter, cation exchange capacity (CEC), soil moisture, and bulk density.* **Soil physical properties:** Soil texture fractions (sand, silt, clay), consistent with basalt-derived Ferralsols typical of the region.* **Soil carbon data:** Soil organic carbon (SOC) and estimated carbon stocks (t ha⁻¹), supporting analysis of carbon dynamics under climate variability.* **Erosion modeling:** Soil loss estimates based on a simplified RUSLE framework, integrating rainfall, slope, soil erodibility, and management factors.* **Spatial data:** Geographic coordinates of sampling locations in GeoJSON format, enabling integration with GIS and remote sensing datasets.* **Uncertainty and reproducibility:** Measurement uncertainty estimates and analysis scripts are included to ensure transparency and reproducibility. The dataset reveals consistent increases in temperature and rainfall over the study period, alongside strong statistical relationships between rainfall and soil moisture, and negative relationships between temperature and soil organic matter. These patterns highlight the role of climate variability in driving soil degradation processes, particularly in sloping tea plantations. This dataset follows FAIR data principles (Findable, Accessible, Interoperable, Reusable) and is intended to support a wide range of applications, including: * Climate–soil interaction studies* Soil degradation and erosion modeling* Carbon cycle and soil fertility research* Climate change adaptation in perennial cropping systems* Machine learning applications in environmental and agricultural sciences **Geographic coverage:** Central Highlands of Vietnam (Bao Loc, Lam Dong Province)**Temporal coverage:** 2005–2023**Data format:** CSV, GeoJSON, JSON**License:** CC-BY-4.0 This dataset provides a reproducible and scalable framework for understanding climate-driven soil processes in tropical agricultural landscapes and supports the development of sustainable land management strategies under changing climatic conditions.