Using GRACE to quantify the depletion of terrestrial water storage in Northeastern Brazil: The Urucuia Aquifer System

Has unsustainable groundwater use induced low flow regimes in the Urucuia Aquifer System? An urgent call for integrated water management

Groundwater depletion in the Urucuia Aquifer System (UAS) has concerned the Brazilian water agencies since it is the principal water source in the arid length of the São Francisco river. In contrast, the irrigation fields increasing and uncertainty regarding climate variability have impaired the management of this important hydrograph region of Brazil. Therefore, the proper management of the UAS relies on the correct definition of the factors that are impacting most of the ground and surface waters, i.e., whether they are from climate or anthropogenic activities. Relying on Artificial Intelligence (AI) modeling and hydrological signatures, this study proposed a methodology to disentangle the role of climatic variability and groundwater pumping on streamflow dynamics by rebuilding natural time series in four watersheds within the UAS's boundaries. By comparing the natural to the observed streamflow time series, the long-term 90th percentile (Q_90) discharge, from which 80% can be granted for multiple uses in the State of Bahia, decreased by up to 50% in the UAS. Yet, the watersheds' productivity, given by the 90% specific yield, ranged from -52.3% (3.8 L/s.km2 to 1.8 L/s.km2) to -74.0% (23.4 L/s.km2 to 6.1 L/s.km2). Low flow duration was ∼1650 days in natural conditions and increased to 10,354 days in the current land use and cover scenario. Changes in the maximum low flow duration length ranged from 191.7% to 1315.7%, and in the low flow, deficits were up to 7150%. These results highlight that groundwater pumping is the principal factor of the UAS's dryness since climate variability could not track streamflow decreases. However, climate variability is secondary because of the intensification of the atmosphere demand. Although it is a Brazilian application, the proposed methodology can be applied in other aquifer systems to guide decision-makers' management strategies worldwide.

The divergence between potential and actual evapotranspiration: An insight from climate, water, and vegetation change

Recently, unprecedented extreme drought has appeared around the world. As the most direct signal of drought, evapotranspiration deserves a more systematic and comprehensive study. Further depicting their divergence of potential (ET_p) and actual evapotranspiration (ET_a) will help to explore the limitation of evapotranspiration. In this paper, the multi-source remote sensing datasets from the Climate Research Unit (CRU), Gravity Recovery and Climate Experiment (GRACE) and its follow-on experiment (GRACE-FO), the Global Land Data Assimilation System (GLDAS), and the Moderate Resolution Imaging Spectroradiometer (MODIS) during 2002 to 2020 were employed to explore the influence of meteorological, hydrological and botanical factors on ET_p, ET_a and their divergence - reduction of evapotranspiration (E_r) which represents regional vegetation and water limitations. According to the Pearson correlation analysis and the Boruta Algorithm based on Random Forest, the temperature is the first decisive promoter of evapotranspiration in the most area while the sparse vegetation is the primary or second determinant limiting the evapotranspiration in 61.84% of the world. In addition, the Coupled Model Intercomparison Project (CMIP6) data from 2030 to 2090 and the support vector machine regression (SVMR) model were applied to predict the future global ET_p, ET_a and E_r on the pixel scale. Predicted results of the model considering the water change not only can highly improve the model performance (with higher R²), but also can simulate the drought in Europe and the more intense ET_a in Africa. Thus, E_r proposed in this study provide a good reference for regional ET_a except for ET_p. The future evapotranspiration value derived by introducing the water storage changes into the machine learning model in this study is also valuable for climate change adaptation and drought warning.

Evaluation of Groundwater Storage Depletion Using GRACE/GRACE Follow-On Data with Land Surface Models and Its Driving Factors in Haihe River Basin, China

Groundwater storage (GWS) in the Haihe River Basin (HRB), which is one of the most densely populated and largest agricultural areas in China, is of great importance for the ecosystem environment and socio-economic development. In recent years, large-scale overexploitation of groundwater in HRB has made it one of the global hotspots of GWS depletion. In this study, monthly GWS variations in HRB from 2003 to 2020 were estimated using the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) data in combination with three land surface models (LSMs) from the Global Land Data Assimilation System (GLDAS). The results show the following: (1) HRB suffered extensive GWS depletion from 2003 to 2020, which has been aggravated since 2014, with a mean rate of 1.88 cm·yr−1, which is equivalent to a volume of 6 billion m3·yr−1. The GWS depletion is more serious in the plain zone (−2.36 cm·yr−1) than in the mountainous zone (−1.63 cm·yr−1). (2) Climate changes are excluded from the reasons for GWS depletion due to annual precipitation and evaporation being close to normal throughout the period. In addition, GWS changes show a low correlation with meteorological factors. (3) The consumption of groundwater for irrigation and land use/cover changes have been confirmed to be the dominant factors for GWS depletion in HRB. (4) The effects of inter-basin water transfer projects cannot be obviously observed using the GRACE and GRACE-FO; more inter-basin water transfers are needed for recovering the GWS in HRB. Therefore, it is imperative to control groundwater exploitation and develop a more economical agricultural irrigation structure for the sustainability of groundwater resources in HRB.

Random Forest-Based Reconstruction and Application of the GRACE Terrestrial Water Storage Estimates for the Lancang-Mekong River Basin

Terrestrial water storage (TWS) is a critical variable in the global hydrological cycle. The TWS estimates derived from the Gravity Recovery and Climate Experiment (GRACE) allow us to better understand water exchanges between the atmosphere, land surface, sea, and glaciers. However, missing historical (pre-2002) GRACE data limit their further application. In this study, we developed a random forest (RF) model to reconstruct the monthly terrestrial water storage anomaly (TWSA) time series using Global Land Data Assimilation System (GLDAS) and Climatic Research Unit (CRU) data for the Lancang-Mekong River basin. The results show that the RF-built TWSA time series agrees well with the GRACE TWSA time series for 2003–2014, showing that correlation coefficients (R) of 0.97 and 0.90 at the basin and grid scales, respectively, which demonstrates the reliability of the RF model. Furthermore, this method is used to reconstruct the historical TWSA time series for 1980–2002. Moreover, the discharge can be obtained by subtracting the evapotranspiration (ET) and RF-built terrestrial water storage change (TWSC) from the precipitation. The comparison between the discharge calculated from the water balance method and the observed discharge showed significant consistency, with a correlation coefficient of 0.89 for 2003–2014 but a slightly lower correlation coefficient (0.86) for 1980–2002. The methods and findings in this study can provide an effective means of reconstructing the TWSA and discharge time series in basins with sparse hydrological data.

Drought Assessment in the São Francisco River Basin Using Satellite-Based and Ground-Based Indices

The São Francisco River Basin (SFRB) plays a key role for the agricultural and hydropower sectors in Northeast Brazil (NEB). Historically, in the low part of the SFRB, people have to cope with strong periods of drought. However, there are incipient signs of increasing drought conditions in the upper and middle parts of the SFRB, where its main reservoirs (i.e., Três Marias, Sobradinho, and Luiz Gonzaga) and croplands are located. Therefore, the assessment of the impacts of extreme drought events in the SFRB is of vital importance to develop appropriate drought mitigation strategies. These events are characterized by widespread and persistent dry conditions with long-term impacts on water resources and rain-fed agriculture. The purpose of this study is to provide a comprehensive evaluation of extreme drought events in terms of occurrence, persistence, spatial extent, severity, and impacts on streamflow and soil moisture over different time windows between 1980 and 2020. The Standardized Precipitation-Evapotranspiration Index (SPEI) and Standardized Streamflow Index (SSI) at 3- and 12-month time scales derived from ground data were used as benchmark drought indices. The self-calibrating Palmer Drought Severity Index (scPDSI) and the Soil Moisture and Ocean Salinity-based Soil Water Deficit Index (SWDIS) were used to assess the agricultural drought. The Water Storage Deficit Index (WSDI) and the Groundwater Drought Index (GGDI) both derived from the Gravity Recovery and Climate Experiment (GRACE) were used to assess the hydrological drought. The SWDISa and WSDI showed the best performance in assessing agricultural and hydrological droughts across the whole SFRB. A drying trend at an annual time scale in the middle and south regions of the SFRB was evidenced. An expansion of the area under drought conditions was observed only during the southern hemisphere winter months (i.e., JJA). A marked depletion of groundwater levels concurrent with an increase in soil moisture content was observed during the most severe drought conditions, indicating an intensification of groundwater abstraction for irrigation. These results could be useful to guide social, economic, and water resource policy decision-making processes.

Mapping terrestrial water storage changes in Canada using GRACE and GRACE-FO

This study focused upon the estimation and analysis of terrestrial water storage (TWS changes) across the Canadian landscape. The estimation was performed using Gravity Recovery and Climate Experiment (GRACE) data from April 2002 to June 2017, and GRACE Follow-On (GRACE-FO) observations from June 2018 to December 2019. Removing the gravity effects of Glacial Isostatic Adjustment (GIA) signals and leakage is required to have realistic estimations of TWS changes in the Canadian landmass. In this study, GIA correction was based on a regional-scale modeling of uplift rate. To evaluate the performance compared to the latest GIA models, a comparison was made to uplift rate derived from 149 GPS stations over the study area. Refined TWS changes showed strong seasonal patterns (between -160 mm and 80 mm). The slope of the trend was positive (6.6 mm/year) for the period combining both GRACE and GRACE-FO. The trend increases to 45 mm/year over the 17-year period across central Canada, especially in regions surrounding Hudson Bay. For GRACE, maximum TWS variations occurred between February and April; for GRACE-FO, it occurred with a 2-month lag earlier during the short period being considered. Uncertainties in TWS variations that were derived by GRACE increased towards the end of the mission. Uncertainty for GRACE-FO is lower than that at the beginning of GRACE. The TWS changes extracted from the used approach were compared to Mascon solutions TWS changes products (GRCTellus JPL MSCNv02 and CSR MSCNv02), by using two steps: 1) the Water Global Assessment Prognosis hydrological model (WGHM), and 2) TWS changes derived from in-situ precipitation and potential evapotranspiration data. In all the cases our approach provided the best correlations and lower root mean square errors, compared to the Mascon products.

Water Appropriation on the Agricultural Frontier in Western Bahia and Its Contribution to Streamflow Reduction: Revisiting the Debate in the Brazilian Cerrado

Over the last three decades, almost half of the Brazilian tropical savanna (Cerrado biome) has been converted into cropland and planted pastures. This study aims to understand the implications of the expansion of the agricultural frontier for water resources in western Bahia state. We use an interdisciplinary approach that combines quantitative and qualitative data (spatial and hydrological analysis, interviews) to tie together land use changes in the Corrente basin, the streamflow and precipitation time series in the Pratudão River sub-basin (part of the Corrente basin), and the perceptions of soybean farmers and smallholder communities about the transformations of the hydrological cycle over the last few years. We observed an almost 10-fold increase in agricultural surface area in the Corrente River basin over the last three decades (1986–2018), going on from 57,090 ha to 565,084 ha, while center-pivot irrigated areas increased from 240 ha to 43,631 ha. Over this period, the streamflow has reduced by 38% in the Pratudão River. Our hydrological analyses, based on the Mann-Kendall test, of seven fluviometric stations and 14 pluviometry stations showed a statistically significant streamflow trend in the Pratudão River sub-basin for both minimum and mean streamflow series (p ≤0.05). Surface runoff coefficient, which relates streamflow and precipitation annual data coefficient, decreased from around 0.4 in the late 1990s to less than 0.2 in 2015. In addition, most precipitation time series analysis (number of annual rainy days) showed no statistically significant trend (p > 0.05). Our results indicate that agricultural changes rather than climate change may be the main driver of downward streamflow trends in the Pratudão River sub-basin that is part of Corrente River basin.

Significant Baseflow Reduction in the Sao Francisco River Basin

Water scarcity is a key challenge to global development. In Brazil, the Sao Francisco River Basin (SFB) has experienced water scarcity problems because of decreasing streamflow and increasing demands from multiple sectors. However, the drivers of decreased streamflow, particularly the potential role of the surface-groundwater interaction, have not yet been investigated. Here, we assess long-term trends in the streamflow and baseflow of the SFB during 1980–2015 and constrain the most likely drivers of observed decreases through a trend analysis of precipitation (P), evapotranspiration (ET), and terrestrial water storage change (TWS). We found that, on average, over 86% of the observed decrease in streamflow can be attributed to a significant decreasing baseflow trend along the SFR, with a spatial agreement between the decreased baseflow, increased ET, and irrigated agricultural land in the Middle SFB. We also noted a decreasing trend in TWS across the SFB exceeding –20 mm year−1. Overall, our findings indicate that decreasing groundwater contributions (i.e., baseflow) are providing the observed reduction in the total SFR flow. A lack of significant P trends and the strong TWS depletion indicate that a P variability only has likely not caused the observed baseflow reduction, in mainly the Middle and Sub-middle SFB. Therefore, groundwater and surface withdrawals may likely be a driver of baseflow reduction in some regions of the SFB.