RESUMEN
Here, we present and release the Global Rainfall Erosivity Database (GloREDa), a multi-source platform containing rainfall erosivity values for almost 4000 stations globally. The database was compiled through a global collaboration between a network of researchers, meteorological services and environmental organisations from 65 countries. GloREDa is the first open access database of rainfall erosivity (R-factor) based on hourly and sub-hourly rainfall records at a global scale. This database is now stored and accessible for download in the long-term European Soil Data Centre (ESDAC) repository of the European Commission's Joint Research Centre. This will ensure the further development of the database with insertions of new records, maintenance of the data and provision of a helpdesk. In addition to the annual erosivity data, this release also includes the mean monthly erosivity data for 94% of the GloREDa stations. Based on these mean monthly R-factor values, we predict the global monthly erosivity datasets at 1 km resolution using the ensemble machine learning approach (ML) as implemented in the mlr package for R. The produced monthly raster data (GeoTIFF format) may be useful for soil erosion prediction modelling, sediment distribution analysis, climate change predictions, flood, and natural disaster assessments and can be valuable inputs for Land and Earth Systems modelling.
RESUMEN
The Water Erosion Prediction Project (WEPP) model has been tested for its ability to predict soil erosion, runoff, and sediment delivery over a wide range of conditions and scales for both hillslopes and watersheds. Since its release in 1995, there has been considerable interest in adding a chemical transport element to it. Total phosphorus (TP) loss at the watershed outlet was simulated as the product of TP in the soil, amount of sediment at the watershed outlet, and an enrichment ratio (ER) factor. WEPP can be coupled with a simple algorithm to simulate phosphorus transport bound to sediment at the watershed outlet. The objective of this work was to incorporate and test the ability of WEPP in estimatingTP loss with sediment at the small watershed scale. Two approaches were examined. One approach (P-EER) estimated ER according to an empirical relationship; the other approach used the ER calculated by WEPP (P-WER).The data used for model performance test were obtained from two side-by-side watersheds monitored between 1976 and 1980. The watershed sizes were 5.05 and 6.37 ha, and each was in a corn (Zea mays L.)-soybean [Glycine max (L.) Merr.] rotation. Measured and simulated results were compared for the period April to October in each year. There was no statistical difference between the mean measured and simulated TP loss. The Nash-Sutcliffe coefficient was 0.80 and 0.78 for the P-EER and P-WER methods, respectively. It was critical for both methods that WEPP adequately represent the biggest sediment yield events because sediment is the main driver for TP loss so that the model can adequately simulate TP losses bound to sediment. The P-WER method is recommended because it does not require use of empirical parameters to estimate TP loss at the watershed outlet.
