Characterising droughts in Central America with uncertain hydro-meteorological data

Abstract:

Droughts studies are scarce in Central America, a region frequently affected by droughts that cause significant socio-economic and environmental problems. Drought characterisation is important for water management and planning and can be done with the help of drought indices. Many indices have been developed in the last decades but their ability to suitably characterise droughts depends on the region of application. In Central America, comprehensive and high-quality observational networks of meteorological and hydrological data are not available. This limits the choice of drought indices and denotes the need to evaluate the quality of the data used in their calculation. This paper aimed to find which combination(s) of drought index and meteorological database are most suitable for characterising droughts in Central America. The drought indices evaluated were the standardised precipitation index (SPI), deciles (DI), the standardised precipitation evapotranspiration index (SPEI) and the effective drought index (EDI). These were calculated using precipitation data from the Climate Hazards Group Infra-Red Precipitation with station (CHIRPS), CRN073, the Climate Research Unit (CRU), ERA-Interim and station databases, and temperature data from the CRU database. All the indices were calculated at 1-, 3-, 6-, 9- and 12-month accumulation times. As a first step, the large-scale meteorological precipitation datasets were compared to have an overview of the level of agreement between them and find possible quality problems. Then, the performance of all the combinations of drought indices and meteorological datasets were evaluated against independent river discharge data, in form of the standardised streamflow index (SSI). Results revealed the large disagreement between the precipitation datasets; we found the selection of database to be more important than the selection of drought index. We found that the best combinations of meteorological drought index and database were obtained using the SPI and DI, calculated with CHIRPS and station data.