CONICET | Buscador de Institutos y Recursos Humanos

Soil moisture is a key variable of the earth-atmosphere system, that not only reflects the soil conditions of a given region, but it also can modulate the atmosphere from seasonal to synoptic time scales. This study aims to compare the agreement between simulated soil moisture anomalies derived from the Global Land Data Assimilation System (GLDAS version 1 and 2) with the Standardized Precipitation Index (SPI). In this study, a verification of the soil conditions simulated by GLDAS is carried out, which is of high relevance due to the lack of observational soil moisture datasets over South America. A special interest of this analysis is set on the southeastern part of South America (SESA,35-25°S latitude and 63-50°W longitude), which is part of the La Plata Basin (LPB), one of the largest basins of the world and reservoir of high biological wealth, where the agriculture is the main source of incomes. The results obtained from GLDAS-1 and from GLDAS-2 indicate that the precipitation dataset used to force the Land Surface Models (LSM), is of major relevance for representing the soil conditions in an adequate manner. Nevertheless, it was shown that CLM2 and NOAH LSM from GLDAS-1 had a very good agreement, although the forcing dataset used to generate GLDAS-1 is climatologically inconsistent. Over the region of SESA, the closer relationship between soil moisture and precipitation at 3-months time scales, points out that precipitation is one of the main controlling factor upon the simulated soil moisture, and therefore, upon agricultural droughts. Finally, and in agreement with other studies and monitoring applications using simulated soil moisture (e.g. the CPC Drought Monitoring), the potential usefulness of GLDAS outputs for the analysis of droughts and their main features (i.e. spatial, frequency and intensity) is documented and the development of new droughts indices based on GLDAS over the South America is recommended for future works.