Comment on essd-2022-87

Abstract

Soil erosion is a major threat to soil resources, causing environmental degradation and contributing to poverty in many parts of the world. Many field experiments have been performed over the past century to study spatio-temporal patterns of soil erosion caused by surface runoff under different environmental conditions. However, these data have never been integrated together in a way that can inform efforts to understand and model soil erosion at different spatial and temporal scales. Here, we designed a database titled AWESOME: Archive for Water Erosion and Sediment Outflow Measurements (Jian et al., 2022). The AWESOME database compiles field measurements of annual soil erosion and sediment yield caused by surface runoff, with data derived from sites around the globe. It includes four soil erosion-related indicators (surface runoff, annual erosion, annual sediment yield, and soil nutrient loss) and more than sixty variables for meta-data that describe the location, climate, soil properties, experimental design (e.g., soil erosion measurement method, field scale, replication), and bibliographic information (e.g., author name and year of publication). Currently, measurements from 1985 geographic sites with unique combinations of longitude and latitude, representing 75 countries, have been compiled into AWESOME. We provide an example of linking AWESOME with an external climate dataset, and identify correlations between soil erosion and several environmental variables. Annual soil erosion rates were most influenced by vegetation type and soil texture group. Annual soil erosion rates exhibited significant negative relationships with plant coverage, soil clay content, soil pH, and soil organic carbon content, and significant positive relationships with annual precipitation and soil bulk density. AWESOME aims to be a freely available, and global framework for compiling field soil erosion and subsequent sediment yield measurements, and to provide data sources to support statistical evaluations, model validation and applications, as well as a better understanding of spatial and temporal patterns of soil erosion.