Estimates of groundwater depletion under extreme drought in the Brazilian semi-arid region using GRACE satellite data: application for a small-scale aquifer | Estimation de l’épuisement des eaux souterraines sous des conditions de sècheresse extrême dans une région semi-aride du Brésil à l’aide des données satellite de GRACE: application pour un aquifère de faible extension Estimaciones del agotamiento del agua subterránea durante una sequía Extrema en la región semiárida brasileña utilizando datos del satélite GRACE: aplicación para un acuífero a pequeña escala 利用GRACE卫星数据估算巴西半干旱地区极端干旱下的地下水枯竭:小尺度含水层的应用 Estimativas de depleção de água subterrânea sob seca severa no semiárido brasileiro usando dados do satélite GRACE: aplicação para um aquífero de pequena escala
2019
Melati, Maurício D. | Fleischmann, Ayan S. | Fan, Fernando M. | Paiva, Rodrigo C. D. | Athayde, Gustavo B.
The temporal and spatial monitoring of groundwater levels is among the most widely used techniques for understanding groundwater reserves, which is essential for the management of regions with drought-related issues. Between 2010 and 2017, the Brazilian semi-arid region suffered a severe drought, presenting intensity and societal impacts undetected in decades. This research aimed to understand how Gravity Recovery and Climate Experiment (GRACE) data can be used as a tool for monitoring groundwater reserves in one of the most important aquifers in the Araripe Sedimentary Basin (Middle Aquifer System), located in a developing region with scarce amounts of data, and where 84,000,000 m³ of groundwater is abstracted annually through pumping. Groundwater storage (GWS) in-situ data were related to GWS estimates based on a combination of GRACE-based terrestrial water storage (TWS with both mascon and spherical harmonic solutions) and Global Land Data Assimilation System (GLDAS) soil moisture (CLM, MOS, NOAH and VIC models were evaluated). Results were analyzed with Nash-Sutcliffe (NS) and Pearson correlation coefficient metrics, and showed that the GWS GRACE-based estimate using the Community Land Model (CLM) land-surface model was more suitable for representing aquifer storage variations. Seven wells (58%) demonstrated a NS > 0.50 for both GWS GRACE-based solutions. In conclusion, GWS GRACE-based methodology has potential for monitoring the 1,394-km² outcrop area of the Middle Aquifer System.
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