Assessing drought conditions in Northeast Brazil: A comparative analysis of soil moisture, groundwater, and total water storage
Mayara Silva de Oliveira, Alfredo Ribeiro Neto, Luiz Antônio Cândido, Peyman Saemian
Abstract
Northeast Brazil (NEB). Over the past few decades, there has been a noticeable surge in the applications of drought indices centered around Total Water Storage (TWS) and its components. This study aims to evaluate the dynamics of continental water storage and its components in Northeast Brazil (NEB), utilizing drought indices based on soil moisture (SMI), groundwater (GWI) and TWS (WSDI) for the period 2003–2022. Four types of data were employed: remote sensing (ESA CCI SM and GRACE), in-situ data (SM and GW storage), land surface model simulations, and global Standardized Precipitation Evapotranspiration Index (SPEI). The first two served as the reference for comparison with the SM, GW, and TWS simulated by the Catchment Land Surface Model (CLSM). New hydrological insights for the region: Drought indices based on CLSM data from the Global Land Data Assimilation System (GLDAS) can be considered reliable after comparison with SPEI and analysis of their patterns using continuous wavelet transformation (CWT). The SMI is more correlated with the SPEI-3 (3-month time scale), and the GWI presented better correlations with the time scales between 12 and 36 months of the SPEI. Changes in the trend of the indices were detected in the hydrographic regions localized in the south of the study area, indicating an increase in drought occurrence. The calculation of the TWS (doing the sum of SM and GW from the CLSM) fitted well with the GRACE data. • The soil moisture from the CLSM model was satisfactorily validated with ESA CCI SM. • The CLSM version with GRACE data assimilation provides better estimates of TWS. • Indices based on CLSM data can be considered reliable after comparison with SPEI. • Spatio-temporal patterns were captured by the application of wavelet in the indices. • Changes in the trend of the indices were detected in the south of the study area.