Water Availability of São Francisco River Basin Based on a Space-Borne Geodetic Sensor

Hatchery tanks induce intense reduction in microbiota diversity associated with gills and guts of two endemic species of the São Francisco River

The São Francisco River (SFR), one of the main Brazilian rivers, has suffered cumulative anthropogenic impacts, leading to ever-decreasing fish stocks and environmental, economic, and social consequences. Rhinelepis aspera and Prochilodus argenteus are medium-sized, bottom-feeding, and rheophilic fishes from the SFR that suffer from these actions. Both species are targeted for spawning and restocking operations due to their relevance in artisanal fisheries, commercial activities, and conservation concerns. Using high-throughput sequencing of the 16S rRNA gene, we characterized the microbiome present in the gills and guts of these species recruited from an impacted SFR region and hatchery tanks (HT). Our results showed that bacterial diversity from the gill and gut at the genera level in both fish species from HT is 87% smaller than in species from the SFR. Furthermore, only 15 and 29% of bacterial genera are shared between gills and guts in R. aspera and P. argenteus from SFR, respectively, showing an intimate relationship between functional differences in organs. In both species from SFR, pathogenic, xenobiont-degrading, and cyanotoxin-producer bacterial genera were found, indicating the critical pollution scenario in which the river finds itself. This study allowed us to conclude that the conditions imposed on fish in the HT act as important modulators of microbial diversity in the analyzed tissues. It also raises questions regarding the effects of these conditions on hatchery spawn fish and their suitability for restocking activities, aggravated by the narrow genetic diversity associated with such freshwater systems.

Trends and Climate Elasticity of Streamflow in South-Eastern Brazil Basins

Trends in streamflow, rainfall and potential evapotranspiration (PET) time series, from 1970 to 2017, were assessed for five important hydrological basins in Southeastern Brazil. The concept of elasticity was also used to assess the streamflow sensitivity to changes in climate variables, for annual data and 5-, 10- and 20-year moving averages. Significant negative trends in streamflow and rainfall and significant increasing trend in PET were detected. For annual analysis, elasticity revealed that 1% decrease in rainfall resulted in 1.21–2.19% decrease in streamflow, while 1% increase in PET induced different reductions percentages in streamflow, ranging from 2.45% to 9.67%. When both PET and rainfall were computed to calculate the elasticity, results were positive for some basins. Elasticity analysis considering 20-year moving averages revealed that impacts on the streamflow were cumulative: 1% decrease in rainfall resulted in 1.83–4.75% decrease in streamflow, while 1% increase in PET induced 3.47–28.3% decrease in streamflow. This different temporal response may be associated with the hydrological memory of the basins. Streamflow appears to be more sensitive in less rainy basins. This study provides useful information to support strategic government decisions, especially when the security of water resources and drought mitigation are considered in face of climate change.

The Drought Events over the Amazon River Basin from 2003 to 2020 Detected by GRACE/GRACE-FO and Swarm Satellites

The climate anomaly in the Amazon River basin (ARB) has a very important influence on global climate change and has always been the focus of scientists from all over the world. To fill the 11-month data gap between Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) missions, we fused the TWSC results from six GRACE solutions by using the generalized three-cornered hat and the least square method to improve the reliability of TWSC results, and then combined Swarm data to construct an uninterrupted long time series of a TWSC-based drought index (GRACE/Swarm-DSI). The drought index was used to detect and characterize the drought events in the ARB between 2003 and 2020. The results show that GRACE/Swarm-DSI has a strong correlation with Self-Calibrating Palmer Drought Severity Index (SCPDSI) (0.6345), Standardized Precipitation Evapotranspiration Index-3 (SPEI-3) (0.5411), SPEI-6 (0.6377) and SPEI-12 (0.6820), and the Nash–Sutcliffe efficiency between GRACE/Swarm-DSI and the above four drought indices are 0.3348, 0.2786, 0.4044 and 0.4627, respectively. Eleven drought events were identified in the ARB during the study period, and the 2005, 2010 and 2016 droughts are the most severe and the longest. The correlation between GRACE/Swarm-DSI and precipitation (PPT) (the correlation coefficient is 0.55 with a 2-month delay) is higher than that of evapotranspiration (ET) (the correlation coefficient is −0.18 with a 12-month delay). It explains that less PPT is the main cause of drought events in the ARB. The influence of PPT is greater in the plains than the one in the mountains and the response time of GRACE/Swarm-DSI to PPT is 1~2 months in most regions. Our results provide a certain reference for the hydrological application of the Swarm model in filling the gap between GRACE and GRACE-FO missions.

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.

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

Covering a plateau area of approximately 125,000 km², the Urucuia Aquifer System (UAS) represents a national strategic water resource in the drought-stricken Northeastern part of Brazil. Variations in terrestrial water storage (TWS) extracted using a three-model-ensemble from the Gravity Recovery and Climate Experiment (GRACE) mission showed a negative balance equal to water stress. Monthly GRACE-derived water storage changes from 2002 to 2014 were compared with those derived from an independent hydrologic water balance of the region using in situ measurements and estimated evapotranspiration rates. Trend analyses revealed a TWS depletion rate of 6.5 ± 2.6 mm yr^-1, but no significant decline in precipitation as observed from available data records. Water storage depletion was found to be driven by anthropogenic impacts rather than by natural climatic variability. The obtained results demonstrate that GRACE is able to adequately capture water storage changes at the subregional scale, particularly during dry seasons.

Performance of Remotely Sensed Soil Moisture for Temporal and Spatial Analysis of Rainfall over São Francisco River Basin, Brazil

Variability in precipitation patterns in the northeast and southeast regions of Brazil are complex, and the combined effects of the Tropical Atlantic, Pacific Niños, and local characteristics influence the precipitation rates. This study assesses the performance of multi-satellite precipitation product SM2RAIN-Climate Change Initiative (SM2RAIN-CCI) for the period of 1998–2015 at monthly scale. To accomplish this aim, various statistical analyses and comparison of multi-satellite precipitation analysis products with rain gauge stations are carried out. In addition, we used three values corresponding to extreme events: The total daily precipitation (PRCPTOT) and the number of consecutive dry/wet days (CDD/CWD). Results reveal that monthly rainfall data from SM2RAIN-CCI are compatible with surface observations, showing a seasonal pattern typical of the region. Data correlate well with observations for the selected stations (r ≥ 0.85) but tend to overestimate high rainfall values (>80 mm/month) in the rainy area. There is a significant decrease in rainfall to the indices, especially in PRCPTOT during the occurrence of tropical ocean–atmosphere interactions, reflecting CWD and CDD values. Moreover, our findings also indicate a relationship, at interannual timescales, between the state of El Niño Southern-Oscillation (ENSO) and Tropical Atlantic (TA) annual precipitation variability from 1998 to 2015. The SM2RAIN-CCI could be a useful alternative for rain-gauge precipitation data in the São Francisco River basin.

Prospects for Imaging Terrestrial Water Storage in South America Using Daily GPS Observations

Few studies have used crustal displacements sensed by the Global Positioning System (GPS) to assess the terrestrial water storage (TWS), which causes loadings. Furthermore, no study has investigated the feasibility of using GPS to image TWS over South America (SA), which contains the world’s driest (Atacama Desert) and wettest (Amazon Basin) regions. This work presents a resolution analysis of an inversion of GPS data over SA. Firstly, synthetic experiments were used to verify the spatial resolutions of GPS-imaged TWS and examine the resolving accuracies of the inversion based on checkerboard tests and closed-loop simulations using “TWS” from the Noah-driven Global Land Data Assimilation System (GLDAS-Noah). Secondly, observed radial displacements were used to image daily TWS. The inverted results of TWS at a resolution of 300 km present negligible errors, as shown by synthetic experiments involving 397 GPS stations across SA. However, as a result of missing daily observations, the actual daily number of available stations varied from 60–353, and only 6% of the daily GPS-imaged TWS agree with GLDAS-Noah TWS, which indicates a root-mean-squared error (RMSE) of less than 100 kg/m 2 . Nevertheless, the inversion shows agreement that is better than 0.50 and 61.58 kg/m 2 in terms of the correlation coefficient (Pearson) and RMSE, respectively, albeit at each GPS site.

The application of multi-mission satellite data assimilation for studying water storage changes over South America

Constant monitoring of total water storage (TWS; surface, groundwater, and soil moisture) is essential for water management and policy decisions, especially due to the impacts of climate change and anthropogenic factors. Moreover, for most countries in Africa, Asia, and South America that depend on soil moisture and groundwater for agricultural productivity, monitoring of climate change and anthropogenic impacts on TWS becomes crucial. Hydrological models are widely being used to monitor water storage changes in various regions around the world. Such models, however, comes with uncertainties mainly due to data limitations that warrant enhancement from remotely sensed satellite products. In this study over South America, remotely sensed TWS from the Gravity Recovery And Climate Experiment (GRACE) satellite mission is used to constrain the World-Wide Water Resources Assessment (W3RA) model estimates in order to improve their reliabilities. To this end, GRACE-derived TWS and soil moisture observations from the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) and Soil Moisture and Ocean Salinity (SMOS) are assimilated into W3RA using the Ensemble Square-Root Filter (EnSRF) in order to separately analyze groundwater and soil moisture changes for the period 2002-2013. Following the assimilation analysis, Tropical Rainfall Measuring Mission (TRMM)'s rainfall data over 15 major basins of South America and El Niño/Southern Oscillation (ENSO) data are employed to demonstrate the advantages gained by the model from the assimilation of GRACE TWS and satellite soil moisture products in studying climatically induced TWS changes. From the results, it can be seen that assimilating these observations improves the performance of W3RA hydrological model. Significant improvements are also achieved as seen from increased correlations between TWS products and both precipitation and ENSO over a majority of basins. The improved knowledge of sub-surface water storages, especially groundwater and soil moisture variations, can be largely helpful for agricultural productivity over South America.

Space-based observations of crustal deflections for drought characterization in Brazil

Widespread environmental impacts of frequent drought episodes in Brazil have resulted in several drought-related diagnostics studies. However, the potential of many "opportunistic sensors", such as the Global Positioning System (GPS), has not yet been considered in hydrological hazard monitoring in Brazil. In this study, the response of the Earth's crust to Brazil's 2012-2015 drought event in different structural provinces is analyzed by comparing GPS-observed vertical crustal deformations (VCDs) with the terrestrial water storage (TWS) derived from the Gravity Recovery and Climate Experiment (GRACE). The results indicate that there is no spatial correlation between annual amplitudes of the TWS and VCDs in different structural provinces apart from the purely elastic response of the crust to TWS dynamics, at almost all the 39 GPS stations that were analyzed. However, approximately 15% of the monitoring stations show that VCD leads TWS with a phase lag of 2-4 months. Errors associated with VCD and TWS are within the accepted range for space geodetic techniques (i.e., GPS and GRACE) and despite the need for further investigation, the phase lead seems to be associated with rainfall, which impacts the TWS through the hydrographs. Overall, the GPS-based drought index (DI_VCD) reflects the water depletion in many regions of Brazil, which agrees with the GRACE-based DI_TWS in terms of the Spearman correlation coefficient (ranging from 0.4 to 0.9) in the Amazon, Tocantins, La Plata, and São Francisco river basins. This agreement confirms the drought persistence during the study period and that DI_VCD can be used to monitor hydrological droughts. In regions in which DI_TWS sufficiently agrees with DI_VCD (48% of the sites), near real-time drought monitoring is feasible. This could be useful in the optimization of models for the forward prediction of drought events in other regions worldwide, where GPS vertical displacements strongly correlate with hydrological GRACE signals.

Evaluating the Impaction of Coal Mining on Ordovician Karst Water through Statistical Methods

This study aims to reveal karst water trend change and the variation of affecting factors in the Heilongdong spring area due to long-term coal mining. In this study, five yearly recoded data over more than 40 years were collected, including underground water level dynamics, water flow, groundwater withdrawal for industrial and agricultural production and domestic production (groundwater withdrawal), mine drainage and rainfall. On that basis, we conducted linear regression, innovative trend analysis (ITA) and the Mann–Kendall method to quantitative analyze the trend and mutation sequence of the time series of environmental hydrological parameters in the study area. To determine the correlation of different affecting parameters under coal mining, as well as the trend of the correlation, we conducted multivariate linear regression analysis and exploited wavelet coherence. The results suggest: (1) under human influence, the annual value of underground water level in the Heilongdong spring area shows an insignificant decrease of 0.42 m/a; precipitation shows a significant downward trend of 2.34 mm/a, primarily the decrease of rainstorm; the spring flow shows a significant decrease of 9.41 × 106 m3/a, and springs with different flow show a significant decrease. (2) The abrupt changes of various factors affecting spring flow in the study area were successively delayed by rainfall, mine drainage rate, industrial and agricultural water consumption and underground water level. (3) Since the year of the start of dramatic changes, under the impact of increased manual mining and mine drainage, the amount of spring overflow has decreased, the groundwater level has decreased, and the groundwater dynamics have varied from meteorological type to meteorology-artificial type. Moreover, the factors affecting the dynamic changes of groundwater have been changed to rainfall and artificial mining and drainage. (4) As the results of Wavelet coherence analysis suggest, the spring flow resonates significantly with rainfall from the period of 3a to 15a. The correlation between the original spring flow and groundwater level is more obvious than that between the original spring flow and rainfall. The correlation between residual flow and groundwater level is less obvious than that between residual flow and rainfall. The above results provide a basis for comprehensively exploiting water resources in coal mining areas and regional groundwater resources protection measures.