Search Results (36)

The Iberian region relies heavily on groundwater and is highly vulnerable to climate variability, making it crucial to understand factors influencing water availability. The aim of this research was to assess how large-scale climate patterns affect total water storage anomalies (TWSAs) in Iberia, particularly in relation to persistent droughts and floods. To address this, I analyzed TWSAs derived from a reconstructed dataset (GRACE-REC) spanning from 1980 to 2019, first at the scale of the entire Iberian Peninsula and then across its main river basins. The links between the North Atlantic Oscillation (NAO), East Atlantic (EA) and Scandinavian (SCAND) patterns, TWSAs, and hydrological extremes were quantified using wavelet and principal component analysis. The results reveal that the NAO exerts the strongest multiyear influence on TWSAs, with periodicities of approximately 10 and 6.5 years, particularly in the southern river basins (Tagus, Guadiana, and Guadalquivir). EA and SCAND have stronger influences in the northern basins (Douro, Minho, and Ebro), driving 2- to 3.5-year cycles. Coupled phases of climate patterns, such as NAO+ and EA− (or SCAND−), correspond to extreme droughts, whereas NAO− and EA+ (or SCAND+) correspond to wet conditions. Full article

The growing and unprecedented water crisis leads to the need to find alternative water resources, and the reuse of treated urban wastewater is an excellent approach. Accordingly, in this work, the disinfection of a secondary effluent (W) discharged from a wastewater treatment plant (WWTP) by hydrogen peroxide combined with radiation (H₂O₂+UV/visible) was studied with the aim of obtaining treated water that can be reused. Firstly, the effect of hydrogen peroxide alone, radiation per se and the combined H₂O₂+UV/Visible process in the inactivation of enterobacteria were assessed. It was found that the oxidant alone is not efficient; the maximum inactivation is achieved when the oxidant and radiation are used simultaneously. For the first time, the effect of some operational parameters, namely the hydrogen peroxide concentration (between 50 and 125 mg/L), initial pH (from 5.0 to 7.0), temperature (between 15 and 25 °C), and radiation intensity (100 to 500 W/m²), on the efficiency of the disinfection process was assessed. When the process was carried out under the best operating conditions found ([H₂O₂] = 75 mg/L, pH = 5.0, T = 25 °C, and UV/visible light with I = 500 W/m²), total enterobacteria and total heterotrophs were inactivated and the abundance of the 16S rRNA, bla_TEM, qnrS, and intl1 genes was reduced. The cultivable microorganisms grew again after 3 days of storing the treated wastewater (TW), making it impossible to reuse such effluent after storage. Therefore, the potential capacity of a diverse bacterial community present in river water to inhibit the regrowth of potentially harmful bacteria present in the urban secondary wastewater after the application of the treatment process was also evaluated. To the authors’ knowledge, this has never been studied before. For this purpose, the TW was diluted with river water (R) at a volumetric percentage of 50/50—sample R+TW. It was found that, after storage, only the total heterotrophs grew, while the abundance of the targeted genes remained practically constant. The R+TW sample after storage met the legal limits for reuse in urban and agricultural applications. The results of this study suggest that the combination of the H₂O₂+UV/visible radiation treatment with dilution of the final treated effluent with natural surface water can contribute to reducing the burden of water scarcity. Full article

Drought is a natural phenomenon that has adverse effects on agriculture, the economy, and human well-being. The primary objective of this research was to comprehensively understand the drought conditions in Sistan and Balouchestan Province from 2002 to 2017 from two perspectives: vegetation cover and hydrology. To achieve this goal, the study utilized MODIS satellite data in the first part to monitor vegetation cover as an indicator of agricultural drought. In the second part, GRACE satellite data were employed to analyze changes in groundwater resources as an indicator of hydrological drought. To assess vegetation drought, four indices were used: Vegetation Health Index (VHI), Vegetation Drought Index (VDI), Visible Infrared Drought Index (VSDI), and Temperature Vegetation Drought Index (TVDI). To validate vegetation drought indices, they were compared with Global Land Data Assimilation System (GLDAS) precipitation data. The vegetation indices showed a strong, statistically significant correlation with GLDAS precipitation data in most regions of the province. Among all indices, the VHI showed the highest correlation with precipitation (moderate (0.3–0.7) in 51.7% and strong (≥0.7) in 45.82% of lands). The output of vegetation indices revealed that the study province has experienced widespread drought in recent years. The results showed that the southern and central regions of the province have faced more severe drought classes. In the second part of this research, hydrological drought monitoring was conducted in fifty third-order sub-basins located within the study province using the Total Water Storage (TWS) deficit, Drought Severity, and Total Storage Deficit Index (TSDI Index). Annual average calculations of the TWS deficit over the period from April 2012 to 2016 indicated a substantial depletion of groundwater reserves in the province, amounting to a cumulative loss of 12.2 km³ Analysis results indicate that drought severity continuously increased in all study basins until the end of the study period. Studies have shown that all the studied basins are facing severe and prolonged water scarcity. Among the 50 studied basins, the Rahmatabad basin, located in the semi-arid northern regions of the province, has experienced the most severe drought. This basin has experienced five drought events, particularly one lasting 89 consecutive months and causing a reduction of more than 665.99 km³. of water in month 1, placing it in a critical condition. On the other hand, the Niskoofan Chabahar basin, located in the tropical southern part of the province near the Sea of Oman, has experienced the lowest reduction in water volume with 10 drought events and a decrease of approximately 111.214 km³. in month 1. However, even this basin has not been spared from prolonged droughts. Analysis of drought index graphs across different severity classes confirmed that all watersheds experienced drought conditions, particularly in the later years of this period. Data analysis revealed a severe water crisis in the province. Urgent and coordinated actions are needed to address this challenge. Transitioning to drought-resistant crops, enhancing irrigation efficiency, and securing water rights are essential steps towards a sustainable future. Full article

Over the past two decades, the Gravity Recovery and Climate Experiment (GRACE) satellite mission and its successor, GRACE-follow on (GRACE-FO), have played a vital role in climate research. However, the absence of certain observations during and between these missions has presented a persistent challenge. Despite numerous studies attempting to address this issue with mathematical and statistical methods, no definitive optimal approach has been established. This study introduces a practical solution using Linear Regression Analysis (LRA) to overcome data gaps in both GRACE data types—mascon and spherical harmonic coefficients (SHCs). The proposed methodology is tailored to monsoon patterns and demonstrates efficacy in filling data gaps. To validate the approach, a global analysis was conducted across eight basins, monitoring changes in total water storage (TWS) using the technique. The results were compared with various geodetic products, including data from the Swarm mission, Institute of Geodesy and Geoinformation (IGG), Quantum Frontiers (QF), and Singular Spectrum Analysis (SSA) coefficients. Artificial data gaps were introduced within GRACE observations for further validation. This research highlights the effectiveness of the monsoon method in comparison to other gap-filling approaches, showing a strong similarity between gap-filling results and GRACE’s SHCs, with an absolute relative error approaching zero. In the mascon approach, the coefficient of determination (R²) exceeded 91% for all months. This study offers a readily usable gap-filling product—SHCs and smoothed gridded observations—with accurate error estimates. These resources are now accessible for a wide range of applications, providing a valuable tool for the scientific community. Full article

The Yellow River Basin (YRB) plays a very important role in China’s economic and social development and ecological security, so studying the spatiotemporal variation characteristics of net primary productivity (NPP) and its influencing factors is of great significance for protecting the stable development of its ecological environment. This article takes the YRB as the research area, based on Moderate Resolution Imaging Spectroradiometer (MODIS) data, climate data, terrain data, land data, social data, and the gravity recovery and climate experiment (GRACE) data. The spatiotemporal evolution characteristics of vegetation NPP in the YRB from 2000 to 2022 were explored using methods such as trend analysis, correlation analysis, and geographic detectors, and the correlation characteristics of NPP with meteorological factors, social factors, and total water storage (TWS) were evaluated. The results indicate that the NPP of vegetation in the YRB showed an increasing trend (4.989 gC·m⁻²·a⁻¹) from 2000 to 2022, with the most significant changes occurring in the middle reaches of the YRB. The correlation coefficient indicates that temperature and accumulated temperature have a significant positive impact on the change of NPP, while TWS has a significant negative impact. In the study of the factors affecting vegetation NPP in the YRB, the most influential factors are soil type (0.48), precipitation (0.46), and temperature (0.32). The strong correlation between TWS and vegetation NPP in the YRB is about 39%, with a contribution rate of about 0.12, which is a factor that cannot be ignored in studying vegetation NPP changes in the YRB. Full article

The Gravity Recovery and Climate Experiment (GRACE) provided valuable insights into variations in Groundwater Storage (GWS). However, the sensitivity of utilizing Global Positioning System (GPS) time series displacement data for detecting changes in GWS remains a subject of ongoing discussion. In order to estimate the spatiotemporal GWS, we selected a vertical displacement from 65 GPS stations located in the Main Karoo Aquifer (MKA). We performed total water storage (TWS) inversion on GPS vertical displacement components; after that, we deducted surface water components based on the Global Land Data Assimilation System (GLDAS) from January 2013 to December 2021. Additionally, for validation, we compared our GWS estimates with the GRACE-derived GWS and observed GWS values derived from the WaterGAP Global Hydrology Model (WGHM) compartments. We discovered that the TWS and GWS trends derived from GPS and GRACE exhibited similar behaviors with trend values overestimated by GRACE and WGHM. Our findings demonstrate relatively typical behavior between GPS and GRACE in the first and second principal component behaviors (PCs) and empirical orthogonal function (EOF) loadings (or spatial patterns). With a contribution of 71.83% to GPS-derived GWS variability and 68.92% to GRACE-derived GWS variability, EOF-1 is a relatively potent factor. For Principal Components PC1 and PC2, the GRACE and GPS PCs have correlation coefficients of 0.75 and 0.84, respectively. Finally, with higher temporal resolution, GPS can perform the same task as GRACE in hydrological applications. In addition, GPS can add important and valuable information to assess regional GWS change. Full article

In this study, multiple remote sensing data were used to quantitatively evaluate the contributions of surface water, soil moisture and groundwater to terrestrial water storage (TWS) changes in five groundwater resources zones of Inner Mongolia (GW_I, GW_II, GW_III, GW_IV and GW_V), China. The results showed that TWS increased at the rate of 2.14 mm/a for GW_I, while it decreased at the rate of 4.62 mm/a, 5.89 mm/a, 2.79 mm/a and 2.62 mm/a for GW_II, GW_III, GW_IV and GW_V during 2003–2021. Inner Mongolia experienced a widespread soil moisture increase with the rate of 4.17 mm/a, 2.13 mm/a, 1.20 mm/a, 0.25 mm/a and 1.36 mm/a for the five regions, respectively. Significant decreases were detected for regional groundwater storage (GWS) with the rate of 2.21 mm/a, 6.76 mm/a, 6.87 mm/a, 3.01 mm/a, and 4.14 mm/a, respectively. Soil moisture was the major contributor to TWS changes in GW_I, which accounted 58% of the total TWS changes. Groundwater was the greatest contributor to TWS changes in other four regions, especially GWS changes, which accounted for 76% TWS changes in GW_IV. In addition, this study found that the role of surface water was notable for calculating regional GWS changes. Full article

The importance of high-resolution and continuous hydrologic data for monitoring and predicting water levels is crucial for sustainable water management. Monitoring Total Water Storage (TWS) over large areas by using satellite images such as Gravity Recovery and Climate Experiment (GRACE) data with coarse resolution (1°) is acceptable. However, using coarse satellite images for monitoring TWS and changes over a small area is challenging. In this study, we used the Random Forest model (RFM) to spatially downscale the GRACE mascon image of April 2020 from 0.5° to ~5 km. We initially used eight different physical and hydrological parameters in the model and finally used the four most significant of them for the final output. We executed the RFM for Mississippi Alluvial Plain. The validating data R² for each model was 0.88. Large R² and small RMSE and MAE are indicative of a good fit and accurate predictions by RFM. The result of this research aligns with the reported water depletion in the central Mississippi Delta area. Therefore, by using the Random Forest model and appropriate parameters as input of the model, we can downscale the GRACE mascon image to provide a more beneficial result that can be used for activities such as groundwater management at a sub-county-level scale in the Mississippi Delta. Full article

Changes in the terrestrial total water storage (TWS) have been estimated at both global and river basin scales from the Gravity Recovery and Climate Experiment (GRACE) mission and are still being detected from its GRACE Follow-On (GRACE-FO) mission. In this contribution, the sixth release of GRACE-FO (RL06) level-2 products applying DDK5 (decorrelation filter) were used to detect water mass variations for the Nile River Basin (NRB) in Africa and the Mega Aquifer System (MAS) in Asia. The following approach was implemented to detect the mass variation over the NRB and MAS: (1) TWS mass (June 2018–June 2021) was estimated by converting the spherical harmonic coefficients from the decorrelation filter DDK 5 of the GRACE-FO Level-2 RL06 products into equivalent water heights, where the TWS had been re-produced after removing the mean temporal signal (2) Precipitation data from Global Precipitation Climatology Project was used to investigate the pattern of change over the study area. Our findings include: (1) during the GRACE-FO period, the mass variations extracted from the RL06-DDK5 solutions from the three official centers—CSR, JPL, and GFZ—were found to be consistent with each other, (2) The NRB showed substantial temporal TWS variations, given a basin average of about 6 cm in 2019 and about 12 cm in 2020 between September and November and a lower basin average of about −9 cm in 2019 and −6 cm in 2020 in the wet seasons between March and May, while mass variations for the MAS had a relatively weaker temporal TWS magnitude, (3) the observed seasonal signal over the NRB was attributed to the high intensity of the precipitation events over the NRB (AAP: 1000–1800 mm yr⁻¹), whereas the lack of the seasonal TWS signal over the MAS was due to the low intensity of the precipitation events over the MAS (AAP:180–500 mm yr⁻¹). Full article

The Canadian Prairies region is considered a climate change hot spot due to the extreme drought events and their impacts on water resources. The overall goal of this research is to understand the linkage between meteorological droughts and Total Water Storage (TWS) variations in the Canadian Prairies. To achieve this goal, a diversified database is collected and analyzed by geostatistical tools and cross-wavelet transform approach. It concerns a multitude of climatic data (four CMIP6 multi-model datasets) and satellite observations (GRACE data). The results indicate that: (1) the models overestimate the precipitation rate over the Canadian Prairies, and the Norwegian Earth System Model version 2 (NorESM2–LM) is the most suitable model for the context of the Canadian Prairies; (2) Sen’s slope estimator of annual rainfall can reach −2.5 mm/year/year, with a decreasing magnitude of trends in the NE to SW direction; (3) the Standardized Precipitation Index (SPI) and the Modified China-Z Index (MCZI) demonstrate that, in the past, most of the climatological years were near normal with some extremely dry years (1952, 2000, 2003, and 2015) and one extremely wet year (1960); (4) the projections in the far future indicate an increase in the number of extremely dry years (2037, 2047, 2080, 2089, and 2095); (5) the combined analysis of GRACE-derived TWS and drought indices show the direct impact of the meteorological drought periods on the water resources. The TWS values decreased from 23 cm in 2002 to −54 cm in 2020, indicating a significant water reserve decline in the region. The results of this study are expected to provide a valuable perspective to understand the dynamic of hydrosystems in a climate change context in the Canadian Prairies. Full article

Gravity Recovery and Climate Experiment (GRACE) satellite data are widely used in drought studies. In this study, we quantified drought severity based on land terrestrial water storage (TWS) changes in GRACE data. We used the water storage deficit (WSD) and water storage deficit index (WSDI) to identify the drought events and evaluate the drought severity. The WSDI calculated by GRACE provides an effective assessment method when assessing the extent of drought over large areas under a lack of site data. The results show a total of 22 drought events in the central Asian dry zone during the study period. During spring and autumn, the droughts among these incidents occurred more frequently and severely. The longest and most severe drought occurred near the Caspian Sea. In the arid area of central Asia, the north of the region tended to be moist (the WSDI value was 0.04 year⁻¹), and the south, east, and Caspian Sea area tended to be drier (the WSDI values were −0.07 year⁻¹ in the south, −0.11 year⁻¹ in the east, and −0.19 year⁻¹ in the Caspian Sea). These study results can provide a key scientific basis for agricultural development, food security, and climate change response in the Asian arid zone. Full article

For 15 years, the Gravity Recovery and Climate Experiment (GRACE) mission have monitored total water storage (TWS) changes. The GRACE mission ended in October 2017, and 11 months later, the GRACE Follow-On (GRACE-FO) mission was launched in May 2018. Bridging the gap between both missions is essential to obtain continuous mass changes. To fill the gap, we propose a new approach based on a remove–restore technique combined with an autoregressive (AR) prediction. We first make use of the Global Land Data Assimilation System (GLDAS) hydrological model to remove climatology from GRACE/GRACE-FO data. Since the GLDAS mis-models real TWS changes for many regions around the world, we further use least-squares estimation (LSE) to remove remaining residual trends and annual and semi-annual oscillations. The missing 11 months of TWS values are then predicted forward and backward with an AR model. For the forward approach, we use the GRACE TWS values before the gap; for the backward approach, we use the GRACE-FO TWS values after the gap. The efficiency of forward–backward AR prediction is examined for the artificial gap of 11 months that we create in the GRACE TWS changes for the July 2008 to May 2009 period. We obtain average differences between predicted and observed GRACE values of at maximum 5 cm for 80% of areas, with the extreme values observed for the Amazon, Alaska, and South and Northern Asia. We demonstrate that forward–backward AR prediction is better than the standalone GLDAS hydrological model for more than 75% of continental areas. For the natural gap (July 2017–May 2018), the misclosures in backward–forward prediction estimated between forward- and backward-predicted values are equal to 10 cm. This represents an amount of 10–20% of the total TWS signal for 60% of areas. The regional analysis shows that the presented method is able to capture the occurrence of droughts or floods, but does not reflect their magnitudes. Results indicate that the presented remove–restore technique combined with AR prediction can be utilized to reliably predict TWS changes for regional analysis, but the removed climatology must be properly matched to the selected region. Full article

A downscaling framework for coarse resolution Gravity Recovery and Climate Experiment (GRACE) Total Water Storage Anomaly (TWSA) data is described, exploiting the observations of precipitation from the Global Precipitation Measurement (GPM) mission, using the Integrated Multi-satellite Retrievals for GPM (IMERG). Considering that the major driving force for changes in TWS is precipitation, we tested our hypothesis that coarse resolution, i.e., 1°, GRACE TWSA can be effectively downscaled to 0.1° using GPM IMERG data. The algorithm for the downscaling process comprises the development of a regression equation at the coarse resolution between the GRACE and GPM IMERG data, which is then applied at the finer resolution with a subsequent residual correction procedure. An ensemble of GRACE data from three processing centers, i.e., GFZ, JPL and CSR, was used for the time period from June 2018 until March 2021. To verify our downscaling methodology, we applied it with GRACE data from 2005 to 2015, and we compared it against modeled TWSA from two independent datasets in the Thrace and Thessaly regions in Greece for the same period and found a high performance in all examined metrics. Our research indicates that the downscaled GRACE observations are comparable to the TWSA estimated with hydrological modeling, thus highlighting the potential of GRACE data to contribute to the improvement of hydrological model performance, especially in ungauged basins. Full article

The dynamic nature and unsustainable exploitation of groundwater aquifers pose a range of management challenges. The accurate basin-wide hydrological assessment is very critical for the quantification of abstraction rates, spatial patterns of groundwater usage, recharge and discharge processes, and identification of critical areas having groundwater mining. This study provides the appraisal of remote sensing technology in comparison with traditionally prevailing tools and methodologies and introduces the practical use of remote sensing technology to bridge the data gaps. It demonstrates the example of Gravity Recovery and Climate Experiment (GRACE) satellite inferred Total Water Storage (TWS) information to quantify the behavior of the Upper Indus Plain Aquifer. The spatio-temporal changes in aquifer usage are investigated particularly for irrigation and anthropogenic purposes in general. The GRACE satellite is effective in capturing the water balance components. The basin-wide monthly scale groundwater storage monitoring is a big opportunity for groundwater managers and policymakers. The remote sensing integrated algorithms are useful tools to provide timely and valuable information on aquifer behavior. Such tools are potentially helpful to support the implementation of groundwater management strategies, especially in the developing world where data scarcity is a major challenge. Groundwater resources have not grown to meet the growing demands of the population, consequently, overexploitation of groundwater resources has occurred in these decades, leading to groundwater decline. However, future developments in the field of space technology are envisioned to overcome the currently faced spatio-temporal challenges. Full article

Assessing the impacts of human activities on the variations in terrestrial water storage (TWS) is essential for water resource management, particularly in regions like the Aral Sea Basin which suffers from severe water scarcity. In this study, the variations in TWS anomalies (TWSA) of the Aral Sea Basin during the period of April 2002 to June 2017 were analyzed using Gravity Recovery and Climate Experiment (GRACE) data and the Global Land Data Assimilation System (GLDAS) Noah model outputs. The impacts of human activities on TWS variations were further quantified through the variations in TWS components and the comparison of TWS obtained from GRACE and GLDAS. The results indicate that TWSA of the entire Aral Sea Basin derived from GRACE experienced a significant decreasing trend of 4.12 ± 1.79 mm/year (7.07 ± 3.07 km³/year) from 2002 to 2017. Trends in individual TWS components indicate that the reduction in TWS of the Aral Sea Basin was primarily attributed to surface water loss, followed by groundwater depletion, which account for ~53.16% and 11.65 ± 45.39 to 42.48 ± 54.61% of the total loss of TWS, respectively. Precipitation (P) and evapotranspiration (ET) both exhibited increasing trends, indicating that ET played a dominant role in TWS depletion from the perspective of water balance. The variations in ET and TWS induced by human activities contributed ~45.54% and ~75.24% to those in total ET and TWS of the Aral Sea Basin, respectively. Full article