2001–2020年中国东北区域土壤水蚀数据集

Abstract

The black soil area in Northeast China plays an important role in food production and ecological security in China. However, over-cultivation practices have led to severe soil erosion, which seriously threatens food security and ecological environment in Northeast China. Accurate simulations of water erosion with high spatio-temporal resolution are important for advancing sustainable development goals, such as promoting sustainable agriculture and monitoring land degradation in Northeast China. This dataset is based on Google Earth Engine (GEE) cloud platform, integrating multi-source remote sensing data, deconstructing RUSLE model, and optimizing algorithm combinations for each factor of the model. We compared and verified the annual sand transport volume and sand transport modulus data from the main hydrological monitoring stations in Northeast China with the soil erosion modulus estimated by the RUSLE model. Then, we selected the optimal factor algorithm combination based on three accuracy metrics (time series correlation, root mean square error and mean absolute error), and obtained the estimation results of soil water erosion modulus with the resolution of 250 m. This dataset can better depict the spatial distribution and temporal changes of soil erosion modulus in Northeast China from 2001 to 2020. It can serve as an effective reference for soil erosion control and assessments in Northeast China.