AgHive announced the publication of a new Hydrologic Curve Number (CN) App in the Google Earth Engine. The application, based on a recent paper in Nature's Scientific Data by Dr. Hadi Jaafar and his team, presents the first global data set of rainfall-runoff relationships. In the framework of the Climate Change Initiative of the European Space Agency (ESA), the Land Cover project lead to the development of a global land cover map in raster format for 2015 at 300m resolution and a time series of these maps dating back to 1992.
The production of the two data sets (HYSOG250m and ESA LC map of 2015) inspired GCN250, the first global curve number dataset at the 250m resolution. An early challenge was to map the ESA land cover classification into the land cover types described by USDA: while some types existed in both classification systems, many did not. The plant functional types were mapped into the USDA classes to enable the assignment of curve numbers according to their underlying hydrologic soil group. A weighting function was developed to determine the curve numbers for ESA land covers that map into several plant functional types. The second challenge was the computation effort needed to calculate the curve numbers for 2.4 billion pixels that cover the world: to speed the process and lessen the computational time, parallel programming and tiling was used. Finally, validation, including validating the curve number method itself, was accomplished. Using Google Earth Engine to access three years of daily runoff data from the Global Land Data Assimilation System (GLDAS), runoff from the world's major watersheds were compared to runoff from data set in response to daily precipitation from GLDAS. Because runoff response to rainfall is dynamic in nature, three curve number data sets (dry, average, and wet antecedent runoff conditions) were generated. The App allows the user to judge which data set (or combination thereof) to choose for the modeling/engineering scenario studied.
The GCN250m app presents global coverage of runoff potential. Its value to the scientific community lies in allowing users to visualize the gridded hydrologic curve number dataset at 250m resolution globally. Users have the option to choose run-off condition (wet, dry, or average) and a specific country of interest. Once the user clicks the map on their area of interest, the CN value is calculated. Hydrologic curve number is a crucial parameter in hydrology that indicates the runoff potential based on land cover, soils, and antecedent runoff conditions. Scientists, engineers, and practitioners working in hydrology and floodplain analysis will find this data helpful for hydrologic design and modeling. GCN250 can be accessed through this link.