Description: CAMELS-CL relies on multiple data sources (including ground data, remote-sensed products and reanalyses) to characterise the hydroclimatic conditions and landscape of a region where in situ measurements are scarce. The dataset includes 516 catchments and provides boundaries, daily streamflow records and basin-averaged daily time series of precipitation (from one national and three global datasets), maximum, minimum and mean temperatures, potential evapotranspiration (PET; from two datasets), and snow water equivalent. We calculated hydro-climatological indices using these time series, and leveraged diverse data sources to extract topographic, geological and land cover features. Relying on publicly available reservoirs and water rights data for the country, we estimated the degree of anthropic intervention within the catchments. To facilitate the use of this dataset and promote common standards in large-sample studies, we computed most catchment attributes introduced by Addor et al. (2017) in their Catchment Attributes and MEteorology for Large-sample Studies (CAMELS) dataset (doi:10.5065/D6G73C3Q), and added several others. --- CAMELS-CL can be visualised from http://camels.cr2.cl --- This research emerged from the collaboration with many colleagues at the Center for Climate and Resilience Research (CR2, CONICYT/FONDAP/15110009). Camila Alvarez-Garreton was funded by FONDECYT postdoctoral grant no. 3170428. Pablo Mendoza received additional support from FONDECYT postdoctoral grant no. 3170079. Mauricio Zambrano-Bigiarini thanks FONDECYT 11150861 for financial support. The development of CR2MET was supported by the Chilean Water Directorate (DGA), through National Water Balance Updating Project DGA-2319, and by FONDECYT grant no. 3150492. This study is a contribution to the Large-sample Hydrology working group of the Panta Rhei Research Initiative of the International Association of Hydrological Sciences (IAHS).

Description: The Landscape Fire Scars Database for Chile makes publicly available for the first time a historical high-resolution (~30 m) burned area and fire severity product for the country. The georeferenced database is a multi-institutional effort containing information on more than 8,000 fires events between July 1984 and June 2018. Using Google Earth Engine (GEE), we reconstructed the fire scar area, perimeter, and severity for each fire. We also provide the Landsat mosaic image of pre- and post-fire events, including the NDVI and NBR indexes. In the related paper, we release the GEE code to reproduce our database or enable the international community to reconstruct another individual burned areas and fire severity data, with minimum input requirements. In the summary file is the list of reconstructed fire events. The identification number (ID) relates the initial information of the wildfires with fire scar and severity data.