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In everyday life, one encounters many experiences of affliction that, for whatever reason, nature (ours or others') cannot resolve. Yet, when nature's finite resources are exhausted and hope seems in vain, humans often experience extra-ordinary moments of renewal and resolution—breakthroughs, remissions, insights, and conversions. We experience these moments in our natural existence; yet, we feel they cannot originate, cannot be attributed to nature alone. Rather, these experiences, called "graces" in Christianity, are attributed to a divine power acting in us. How do we come to describe these experiences in this way? Is it possible to formulate a general theory of these experiences as "graces"? Is there an "experience" of grace in general, a "state of grace", which serves as ground and unifying experience for the "graces" we receive? Working from the Catholic theological point of view, this paper examines such experiences of affliction and renewal, as well as the basic Catholic framework schematizing them as found in the Bible and Catholic religious writings. In doing so, this paper highlights the theme of impossibility (absolutely or in context) underlying each experience, and broadly categorizes them as happening within three regions of human life: the external, ethical sphere, the interior self-relationship, and the vertical relationship to the Divine. In dialogue with theologians and phenomenological thinkers, general formulations of the experiences are placed within their respective spheres, and certain problems in the identification or interpretation of these experiences are identified. The paper then explores how the experience of a "New Creation" can serve not only as a label for the totality of these experiences, but also as a totalizing and overarching ground-experience of "grace" and an interpretive hermeneutic for graces in general. As a result, a graced moment of total personal "rebirth" or "recreation", prevenient with respect to any personal co-operation or experiences of grace as grace, is identified as a potential ground for all other graces considered. Finally, this paper considers some potential implications of this account of grace for both Catholic thought and Phenomenology more generally. [ABSTRACT FROM AUTHOR]

Due to the influences of climate change and human activities, the resources and environments of the "One Belt and One Road" initiative are facing severe challenges. Using drought indicators, this study aimed to analyze the spatiotemporal characteristics of the drought environment and the response of vegetation cover in the area to drought conditions. The Gravity Recovery and Climate Experiment (GRACE) drought severity index (GRACE-DSI), GRACE water storage deficit index (GRACE-WSDI) and standardized precipitation index (SPI) were calculated to measure hydrological drought. Additionally, based on GRACE and Global Land Data Assimilation System (GLDAS) data, groundwater data in Central Asia was retrieved to calculate the groundwater drought index using the GRACE Standardized Groundwater Level Index (GRACE-SGI). The findings indicate that, from 2000, Central Asia's annual precipitation decreased at a rate of 1.80 mm/year (p < 0.1), and its annual temperature increased slightly, at a rate of 0.008 °C/year (p = 0.62). Water storage decreased significantly at a rate of −3.53 mm/year (p < 0.001) and showed an increase-decrease-increase-decrease pattern. During the study period, the aridity in Central Asia deteriorated, especially on the eastern coast of the Caspian Sea and the Aral Sea basin. After 2020, most of Central Asia experienced droughts at both the hydrological and groundwater droughts levels and of varying lengths and severity. During the growing season, there was a substantial positive association between the Normalized Difference Vegetation Index (NDVI) and drought indicators such as GRACE-DSI and GRACE-WSDI. Nonetheless, the NDVI of cultivated land and grassland distribution areas in Central Asia displayed a strong negative correlation with GRACE-SGI. This study concludes that the arid environment in Central Asia affected the growth of vegetation. The ecological system in Central Asia may be put under additional stress if drought conditions continue to worsen. This paper explores the drought characteristics in Central Asia, especially those of groundwater drought, and analyzes the response of vegetation, which is very important for the ecological and environmental protection of the region. [ABSTRACT FROM AUTHOR]

Is it possible for Aquinas's moral theology to engage constructively with contemporary moral naturalism? The proposed question has already been a subject of scholarly interest, eliciting various responses. Some authors emphasize the difficulties and contradictions, while others identify potential affinities. This paper explores the extent to which Aquinas's concept of Natural Law might align, albeit partially, with a form of moral non-reductive, non-non-cognitivist ethical naturalism. Specifically, it aims to assess how his view of Natural Law, rooted in practical reason and natural inclinations, incorporates a teleological understanding of nature, which provides a foundational basis for this consonance. Within this framework, moral virtue emerges as central in bridging bio-psychological facts with ethical principles. Aquinas's assertion that gratia non tollit naturam, sed perficit "grace does not destroy nature but perfects it" (ST I. q1. a8) further underscores the continuity between nature and normativity, suggesting that while grace and revelation introduce true novelty, they enhance rather than supplant the natural moral order. [ABSTRACT FROM AUTHOR]

This paper aims to address the limitations of the distribution number and uniformity of Continuously Operating Reference Stations (CORS) and their impact on the reliability of inverting regional groundwater storage (GWS) based on Green's function method and using global navigation satellite system (GNSS) data. A fusion method on the inversion of regional GWS changes from GNSS and the Gravity Recovery and Climate Experiment (GRACE) was proposed in this paper. Taking the Shaanxi–Gansu–Ningxia (SGN) region as an example, the in situ groundwater level data from ten CORS stations and eight wells were used for test analyses. In this paper, an atmospheric pressure model from the European Centre for Medium-Range Weather Forecasts (ECMWF), a global land data assimilation system (GLDAS), a WaterGAP global hydrology model (WGHM), and mean sea level anomaly (MSLA) data were used to quantitatively monitor the influence of vertical deformation caused by non-tidal environmental load. After deducing these loading deformations from the filtered time series of non-linear monthly geodetic height from the GNSS, the GWS changes in the SGN region from 2011 to 2014 were inverted. Meanwhile, the change in surface water storage from the GLDAS and WGHM models were removed from the terrestrial water storage (TWS) changes derived from GRACE. On this basis, the remove–restore theory in the Earth's gravity field was introduced to both fuse the inversion results and obtain the regional GWS changes based on the fusion method. The results showed the following: (1) The local characteristics from the fusion results were more prominent than those of GRACE on the spatial scale, such as in the southwest and northeast in the study area. In addition, the fusion results were more uniform than those from GNSS, especially for the sparse and missing areas in which CORS stations were located, and the local effect was weakened. (2) On the time scale, compared with GRACE, the trends in GWS changes obtained from the fusion method and from GNSS inversion were roughly the same as the in situ groundwater level changes. (3) For the in situ groundwater wells "6105010031" and "6101260010", the correlation coefficients of the fusion result were 0.53 and 0.56, respectively. The accuracy of the fusion method was slightly higher than that from GNSS, which indicates that the fusion method may be more effective for areas where CORS stations are missing or sparsely distributed. The methods in this paper can provide significant reference material for hydrodynamic research, sustainable management of water resources, and the dynamic maintenance of height data. [ABSTRACT FROM AUTHOR]

The conventional average acceleration approach relies on K-band range observation, containing an unknown bias, which leads to possible degradation of the precision of Earth's gravity field modelling. It also suffers from correlated errors caused by three-point numerical differentiation. In this study, an improved approach is proposed that makes use of K-band range-rate observations instead and overcoming the influence of correlated errors by introducing a whitening filter. GRACE-Follow On data spanning the period from January 2019 to December 2022 were processed by the proposed approach and a series of time-varying gravity field models was derived, referred to as SSM-AAA-GFO in this paper. This model series is compared comprehensively with three official model series. Results demonstrate that all model series are highly coincident below degree 30 and reflect similar time-varying gravity field signals in both large and small basins. After filtering, SSM-AAA-GFO shows uncertainty, in the form of equivalent water height below 2.5 cm, which is comparable with three official model series. The comparison results confirm the effectiveness of the proposed approach for precisely modelling a time-varying gravity field based on K-band range-rate observations. [ABSTRACT FROM AUTHOR]

The aim of this paper is to assess the correlation of groundwater level changes (or groundwater level anomalies (GWLA)) obtained from direct measurements in wells with groundwater storage anomalies (GWSA) calculated using Gravity Recovery and Climate Experiment (GRACE) products and Global Land Data Assimilation Systems (GLDAS) models across different climate zones, from temperate Poland to Arctic Sweden. We recognize that such validation studies are needed to increase the understanding of the spatio-temporal limits of remote sensing model applicability, not least in data-scarce sub-Arctic and Arctic environments where processes are complex due to the impacts of snow and (perma) frost. Results for temperate climates in Poland and southern Sweden show that, whereas one of the models (JPL_NOAH_GWSA) failed due to water balance term overestimation, the other model (CSR_CLM_GWSA) produced excellent results of monthly groundwater dynamics when compared with the observations in 387 groundwater wells in the region during 2003–2022 (cross-correlation coefficient of 0.8). However, for the sub-Arctic and Arctic northern Sweden, the model suitable for other regions failed to reproduce typical northern groundwater regimes (of the region's 85 wells), where winter levels decrease due to the blocking effect of ground frost on groundwater recharge. This suggests, more generally, that conventional methods for deriving GWSA and its seasonality ceases to be reliable in the presence of considerably infiltration-blocking ground frost and permafrost (whereas snow storage modules perform well), which hence need further attention in future research. Regarding long-term groundwater level trends, remote sensing results for southern Sweden show increasing levels, in contrast with observed unchanged to decreasing (~10 mm/a) levels, which may not necessarily be due to errors in the remote sensing model but may rather emphasize impacts of anthropogenic pressures, which are higher near the observation wells that are often located in eskers used for water supply. For sub-Arctic and Arctic Sweden, the (relatively uncertain) trend of the remote sensing results nevertheless agrees reasonably well with the groundwater well observations that show increasing groundwater levels of up to ~14 mm/a, which, e.g., is consistent with reported trends of large Siberian river basins. [ABSTRACT FROM AUTHOR]

One of the key constraints for the accelerometer of GRACE-type gravity satellites to accurately measure the non-gravitational accelerations acting on the satellite is that the center of mass of the satellite and the proof mass of the accelerometer should maintain a coincidence. In addition, the accuracy requirement is that the center of mass offset (CM-offset) in the three directions is less than 100 microns. Since the center of mass (CoM) of the satellite will change with the consumption of cold-gas fuel in the tanks, it is necessary to regularly carry out the CoM calibration maneuver. Firstly, the observation equations consisting of the accelerometer linear acceleration, angular acceleration, and the CM-offset vector are established in order to estimate the amount of CM-offset. Then, according to the estimated CM-offset, the satellite mass trim mechanisms are used to change the satellite's CoM, so that the satellite's CoM always approaches the proof mass of the accelerometer, with an accuracy of 100 μm per axis. The CM-offset of the satellite of GRACE-FO is estimated by using the accelerometer, star camera, magnetic torquer, magnetometer, and the precision orbit data during the GRACE-C CM-offset calibration period on 1 February 2020. Four kinds of CM-offset results are obtained by four different angular accelerations as follows: the angular acceleration based on the attitude dynamics ("MTQ angular acceleration"), the accelerometer angular acceleration calibrated by MTQ, the accelerometer angular acceleration, and the angular acceleration calculated by the star camera. By comparing the four kinds of CM-offset results that are estimated by the four different methods, all four of the results are shown to have the same level of accuracy. Based on the accelerometer (calibrated) angular acceleration, the difference with the JPL result is 0.5 μm, while the difference between the conventional method and the JPL result is 6.0 μm. All four of the methods can achieve the requirement of 50 μm accuracy and using four CM-offset estimation methods simultaneously can improve the integrity of the calibration results. Subsequently, the CM-offset results of GRACE-C since its launch are estimated here. The calibration algorithm that is proposed in this paper can be used as a reference in the calibration of gravity satellites carrying an accelerometer payload. [ABSTRACT FROM AUTHOR]

The terrestrial water resources in Shaanxi–Gansu–Ningxia (SGN) region are relatively scarce, and its climate change is unstable. Research on the deformation driven by terrestrial water load is of great significance to the dynamic maintenance of reference station networks. In this paper, data derived from Gravity Recovery and Climate Experiment (GRACE) and Global Navigation Satellite System (GNSS) from 2010 to 2014 were combined to monitor the spatiotemporal characteristics of surface vertical deformation caused by terrestrial water load change. The single scale factor was calculated by comparing CPC, WGHM, and GLDAS hydrological model to restore filtering leakage signal. The singular spectrum analysis (SSA) method was used to extract the principal component of temporal vertical deformation, and its spatial distribution was analyzed. At the same time, in order to study the relationship between the terrestrial water load deformation from GRACE and that from GNSS, the first-order term correction, the Atmosphere and Ocean De-aliasing Level-1B product (GAC) correction, and the first-order load LOVE number correction for GRACE were adopted in this paper. In addition, a quantitative comparative analysis of both the monitoring results was carried out. The results show that the time-variable characteristics of surface vertical deformation characterized by the filtered three hydrological models were consistent with those of GRACE. The correlation coefficient and Nash–Sutcliffe efficiency coefficient (NSE) values were the highest in the GLDAS model and the GRACE model, respectively; the former index is 0.93, while the latter is 0.85. The crustal vertical deformation from terrestrial water load showed a declining rate from 2010 to 2014. Its spatial change rate showed an obvious ladder distribution, with the surface subsidence rate gradually decreasing from south to north. In addition, weighted root mean square (WRMS) contribution rate of the crustal vertical deformation resulting from GRACE with GAC correction between the different GNSS stations ranged from 18.52% to 54.82%. The correlation coefficient between them was close to 0.70. After deducting the mass load impact of GRACE only, the WRMS contribution rate of the corresponding stations decreased from −8.42% to 21.18%. The correlation coefficient between them reduced noticeably. Adding GAC back can increase the comparability with GRACE and GNSS in terms of monitoring the crustal vertical deformation. The annual amplitude and phase of surface vertical deformation resulting from GRACE with GAC correction were close to those of GNSS. The research results can help to explore the motion mechanism between water migration and surface deformation, which is of benefit in the protection of the water ecological environment in the region. [ABSTRACT FROM AUTHOR]

Flood events have caused huge disasters with regard to human life and economic development, especially short-term flood events that have occurred in recent years. Gravity Recovery and Climate Experiment (GRACE) satellites can directly detect the spatiotemporal characteristics of terrestrial water storage anomalies (TWSA), which play an important role in capturing flood signals. However, the monthly resolution of GRACE-derived TWSA limits its application in monitoring sub-monthly flood events. Therefore, this paper first reconstructs the daily TWSA based on a statistical model with near real-time precipitation and temperature as input variables, and then three daily flood monitoring indexes are developed based on the reconstructed TWSA. Furthermore, these indexes are employed to evaluate the temporal and spatial characteristics of the 2016 short-term flood event in the Haihe River basin (HRB), including the flood potential index (FPI), water storage deficit index (WSDI), and combined climate deviation index (CCDI). In contrast to previous studies, the temporal resolution of TWSA-based indexes is improved from the monthly scale to the daily scale, which largely improves the temporal characterization of flood monitoring. Results demonstrate that (1) among ten kinds of "Temperature-Precipitation" combinations, the reconstructed TWSA based on CN05.1-CN05.1 match well with the GRACE TWSA, as well as publicly available daily TWSA datasets with a Nash-Sutcliffe efficiency coefficient (NSE) of 0.96 and 0.52 ~ 0.81 respectively. (2) The short-term flood characteristics can be better characterized by the reconstructed daily TWSA based on CN05.1-CN05.1, reaching the peak of 216.19 mm on July 20 in the flood center. Additionally, the spatial characteristics of the equivalent water height (EWH) are detected to evolve from southwest to northeast during the short-term flood. (3) FPI, WSDI, and CCDI are proven to be effective in monitoring flood events in the HRB, which validates the reliability of the reconstructed daily TWSA. Moreover, compared to the 56% and 66% coverage of damage quantified by FPI and CCDI, the 45% damage coverage of the flood mapped by WSDI is more consistent with the governmental reports within the HRB. This paper is expected to provide a valuable reference for the assessment of short-term events caused by extreme climate change. [ABSTRACT FROM AUTHOR]

As a major grain-producing region in China, the North China Plain (NCP) faces serious challenges such as water shortage and land subsidence. In late 2014, the Central Route of the South-to-North Water Diversion Project (SNWD-C) began to provide NCP with water resources. However, the effectiveness of this supply in mitigating land subsidence remains a pivotal and yet unassessed aspect. In this paper, we utilized various geodetic datasets, including the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow On (GRACE-FO), Global Navigation Satellite System (GNSS) and leveling data, to conduct a spatial-temporal analysis of the equivalent water height (EWH) and vertical ground movement in the NCP. The results reveal a noteworthy decline in EWH from 2011 to 2015, followed by a slight increase with minor fluctuations from 2015 to 2020, demonstrating a strong correlation with the water resources supplied by the SNWD-C. The GRACE-derived surface deformation rate induced by hydrological loading is estimated to be <1 mm/yr. In comparison, GNSS-derived vertical ground movements exhibit considerable regional differences during the 2011–2020 period. Substantial surface subsidence is evident in the central and eastern NCP, contrasting with a gradual uplift in the front plain of the Taihang Mountains. Three-stage leveling results indicate that the rate of subsidence in the central and eastern plains is gradually increasing with the depression area expanding from 1960 to 2010. Based on these geodetic results, it can be inferred that the SNWD-C's operation since 2014 has effectively mitigated the reduction in terrestrial water storage in the NCP. However, land subsidence in the NCP persists, as the subsidence rate does not turn around in sync with the change in EWH following the operation of SNWD-C. Consequently, it's necessary to maintain and enforce existing policies, including controlling groundwater exploitation and water resources supply (e.g., SNWD-C) to curtail the exacerbation of land subsidence in the NCP. Additionally, continuous monitoring of land subsidence by GRACE, GNSS, leveling and other geodetic techniques is crucial to enable timely policy adjustments based on monitoring results. [ABSTRACT FROM AUTHOR]

This paper compares Augustine's view on the value of learning to classical Chinese philosophy (Laozi, Confucius, Mengzi, Xunzi, Zhu Xi). While Laozi has a quite negative notion of learning as leading humans away from true nature, most Confucians esteem learning highly as the only way to human perfection. Similar to the Confucians, the early Augustine sees knowledge and learning as a way for humans to ascend to divine truth. In his mature works, however, Augustine points out more clearly the dangers of learning: it can make humans proud instead of humble, causing them to rely on their own power instead of confessing their weakness and their need for divine grace. His hesitations on the value of learning bear some similarity to Laozi's view. [ABSTRACT FROM AUTHOR]

The coordinates of the KBR (K-band ranging system) antenna phase center of GRACE-type gravity satellites in the satellite Science Reference Frame should be precisely known, and the determination accuracy should reach 0.3 mrad in the Y (pitch) and Z (yaw) directions. Due to the precision limitation of ground measurement and the change of space environment during orbit, the KBR antenna phase center changes. In order to obtain more accurate KBR antenna phase center coordinates, it is necessary to maneuver the satellite to achieve the on-orbit calibration of the KBR antenna phase center. Based on the in-orbit calibration data of KBR of GRACE-FO satellites, a new method is proposed to estimate the antenna phase center of KBR using the inter-satellite range acceleration as the observation value. The antenna phase center of KBR is solved by the robust estimation method, and the obtained calibration results are better than 72 μm in the Y and Z directions and better than 1.3 mm in the X direction, which is 50% better than the least squares estimation algorithm. The accuracy of KBR calibration results obtained by using the data of positive maneuvers or mirror (negative) maneuvers, respectively, does not meet 0.3 mrad. It is shown that mirror maneuvers are required for KBR calibration of a GRACE-type gravity satellite to obtain antenna phase center estimation results that meet the accuracy requirements. The calibration algorithm proposed in this paper can provide reference for KBR antenna phase center calibration of Chinese GRACE-type gravity satellites. [ABSTRACT FROM AUTHOR]

During gravity field modeling, the conventional acceleration approach rarely incorporates KBR inter-satellite range rate data from the GRACE mission. To propose an improved acceleration method, this study introduces initial orbital position and velocity vectors to be estimated along with a combination of Cowell, KSG, and Adams integrators. In addition to achieving a full-rank design matrix regarding orbit corrections when constructing observation equations, the proposed method is capable of utilizing range rate observations for gravity field estimation. To verify the reliability of this approach, GRACE data from April 2002 to December 2016 was used to calculate a time series of monthly gravity solutions up to a degree and order of 96, referred to as Tongji-Acc RL06 in this paper. The computed time series are compared with the official models (i.e., CSR RL06, GFZ RL06, and JPL RL06) in terms of geoid degree variances, signal contents over distinct areas, and noise levels in desert regions. The investigations lead to the following conclusions: (a) the geoid degree variances indicate that Tongji-Acc RL06 exhibits comparable signal levels (approximately below 20 degrees) to the other three models while demonstrating lower noise at higher degrees (above 40 degrees); (b) the analysis over the globe, typical river basins, and land–ice regions illustrates that the solutions derived using the proposed acceleration method agree well with the official models based on the dynamic approach; (c) especially over the two large-scale river basins (i.e., Amazon and Zambezi) and another two small-scale river basins (i.e., Tennessee and Irrawaddy), Tongji-Acc RL06 significantly improves the SNR values; and (d) in the cases of the Sahara and Karakum deserts, Tongji-Acc RL06 achieves noise reductions of over 55.8% and 61.5% relative to CSR RL06, respectively. In general, the signal and noise analyses demonstrate that the proposed acceleration-based approach can effectively extract gravity field signals from KBR inter-satellite range rate observations with improved SNR, while significantly reducing the high-frequency noise. [ABSTRACT FROM AUTHOR]

Meteorological hazards, such as floods, can develop rapidly and are usually a local phenomenon. On the other hand, drought is a phenomenon arising over longer periods. Moreover, it occurs in areas that are remarkably diverse in terms of surface area. Drought has a massive impact on agriculture, socio-economic activities, and the natural environment. However, determining the losses associated with the phenomenon of drought and its identification is complicated. The aim of this paper is to identify and quantify droughts using climatic indices, which include the combined climatologic deviation index, groundwater drought index, water storage deficit index and multivariate standardized drought index. Based on the research, it was concluded that the CCDI, GGDI, WSDI, and MSDI indicators can be a useful tool, on the basis of which it was possible to analyze drought periods. These periods were not related to changes and loss of groundwater, but resulted from low rainfall and snowfall. [ABSTRACT FROM AUTHOR]

This paper investigates the relationship between rainfall, groundwater and Gravity Recovery and Climate Experiment (GRACE) data to generate regional-scale estimates of terrestrial water storage variations in the Andalucía region of southern Spain. These estimates can provide information on groundwater depletion (caused by periods of low rainfall or droughts) and groundwater recovery. The spatial distribution of groundwater bodies in southern Spain is complex and current in situ groundwater monitoring methods are deficient, particularly in terms of obtaining representative samples and in implementing and maintaining groundwater monitoring networks. The alternative approach proposed here is to investigate the relationship between precipitation time series and changes in the terrestrial water storage estimated from GRACE observations. The results were validated against the estimated fluctuation in regional groundwater. The maximum correlation between the mean groundwater level and the GRACE observations is 0.69 and this occurs at a lag of one month because the variation in gravity is immediate, but rainfall water requires around one month to travel across the vadose zone before it reaches the groundwater table. Using graphical methods of accumulated deviations from the mean, we show that, in general, groundwater storage follows the smooth, multi-year trends of terrestrial water storage but with less short-term trends; the same is true of rainfall, for which the local trends are more pronounced. There is hysteresis-like behaviour in the variations in terrestrial water storage and in the variations of groundwater. In practical terms, this study shows that, despite the abnormal dryness of the Iberian Peninsula during the 2004–2010 drought, the depleted groundwater storage in Andalucía recovered almost to its pre-drought level by 2016. In addition, groundwater storage and terrestrial water storage show very similar trends but with a delay in the groundwater trend. [ABSTRACT FROM AUTHOR]

Groundwater has been extensively exploited in the North China Plain (NCP) since the 1970s, leading to various environmental issues. Numerous studies have utilized Gravity Recovery and Climate Experiment (GRACE) satellite data to analyze changes in groundwater storage in the NCP and provide valuable insights. However, the low spatial resolution of GRACE data has posed challenges for its widespread application, and there have been limited studies focusing on refining groundwater storage changes in the NCP. In addition, the lack of data on the gap period between GRACE and GRACE-FO hinders in-depth research on regional groundwater storage anomalies (GWSA). This paper applied a groundwater storage model called NGFLOW-GRACE to construct a groundwater storage change model in the NCP at spatial resolutions of both 1° and 0.05°. The groundwater storage change model was calibrated and driven using gratis data, with hydrogeological parameter values estimated using the shuffled complex evolution algorithm (SCE-UA). The model exhibited favorable performance, with correlation coefficients greater than 0.85 during the calibration period and 55% of coefficients greater than 0.50 during the validation period. Interestingly, the results indicate that different combinations of remote sensing data do not significantly impact the outcomes, while the hydraulic gradient coefficient demonstrates the highest sensitivity. Appropriate reconstructed data were selected within the empty window period, and by downscaling the model to a resolution of 0.05°, a complete cycle (January 2003 to December 2020) of GWSA was derived. Through comprehensive comparisons with previous research findings on both temporal and spatial scales, it can be concluded that the downscaled groundwater storage changes obtained from the established model demonstrated high reliability. [ABSTRACT FROM AUTHOR]

Using the Gravity Recovery and Climate Experiment (GRACE) satellite to monitor groundwater storage (GWS) anomalies (GWSAs) at the local scale is difficult due to the low spatial resolution of GRACE. Many attempts have been made to downscale GRACE-based GWSAs to a finer resolution using statistical downscaling approaches. However, the time-lag effect of GWSAs relative to environmental variables and optimal model parameters is always ignored, making it challenging to achieve good spatial downscaling, especially for arid regions with longer groundwater infiltration paths. In this paper, we present a novel spatial downscaling method for constructing GRACE-based 1 km-resolution GWSAs by using the back propagation neural network (BPNN) and considering the time-lag effect and the number of hidden neurons in the model. The method was validated in Alxa League, China. The results show that a good simulation performance was achieved by adopting varying lag times (from 0 to 4 months) for the environmental variables and 14 hidden neurons for all the networks, with a mean correlation coefficient (CC) of 0.81 and a mean root-mean-square error (RMSE) of 0.70 cm for each month from April 2002 to December 2020. The downscaled GWSAs were highly consistent with the original data in terms of long-term temporal variations (the decline rate of the GWSAs was about −0.40 ± 0.01 cm/year) and spatial distribution. This study provides a feasible approach for downscaling GRACE data to 1 km resolution in arid regions, thereby assisting with the sustainable management and conservation of groundwater resources at different scales. [ABSTRACT FROM AUTHOR]

GRACE observations and land subsidence data derived from InSAR both assess groundwater storage changes. However, GRACE data at local scales are restricted by the coarser spatial resolution of satellite systems, and inversion of Groundwater Storage Anomalies (GWSA) by InSAR requires extensive and unavailable lithological data. Here, we propose a New Subsidence Feature Weighted Combination (NSFWC) scheme to enhance the spatial resolution of GRACE-derived GWSA from 0.5° to 0.05°. This method can not only retain the spatial distribution of groundwater changes but also reflect local details related to surface subsidence. A case study was executed to evaluate the performance of the NSFWC scheme in the Beijing Plain, which has seriously overexploited groundwater. Results showed that the simulated GWSA were consistent with in situ measurements in most regions, with a correlation coefficient of 0.85 and an RMSE of 4.41 mm/year. Additionally, there were 22 overexploited wells in the Beijing Plain, although groundwater levels generally recovered after the South to North Water Diversion Project. Simultaneously, four cones of depression were detected by the InSAR technology, where the maximum cumulative subsidence and subsidence rate achieved −198.52 mm and −53.09 mm/year, respectively. This paper provides data support and technical guarantees for small-scale groundwater resources management. [ABSTRACT FROM AUTHOR]

Groundwater is a primary freshwater resource for human consumption and an essential source for industry and agriculture. Therefore, understanding its spatial and temporal trends and drivers is crucial for governments to take appropriate measures to manage water resources. This paper uses Gravity Recovery and Climate Experiment (GRACE) satellite data and the Global Land Data Assimilation System (GLDAS) to derive groundwater storage anomalies (GWSAs) and to analyze the spatial and temporal trends of GWSA in different regions of China (Xinjiang, Tibet, Inner Mongolia, North China Plain, South China, and Northeast China). It used groundwater-level observation data to verify the accuracy of GWSA estimates and analyzed the drivers of regional GWSA changes. The results showed that: (1) GWSA in South China increased at a rate of 4.79 mm/a from 2003 to 2016, and GWSA in other regions in China showed a decreasing trend. Among them, the decline rates of GWSA in Xinjiang, Tibet, Inner Mongolia, North China Plain, and Northeast China were −6.24 mm/a, −3.33 mm/a, −3.17 mm/a, −7.35 mm/a, and −0.75 mm/a, respectively. (2) The accuracy of the annual-scale GWSA estimates was improved after deducting gravity losses due to raw coal quality, and the correlation coefficient between GWSA and groundwater levels monitored by observation wells increased. (3) In Xinjiang, the annual water consumed by raw coal mining, industrial, and agricultural activities had a greater impact on GWSA than rainfall and temperature, so these human activities might be the main drivers of the continued GWSA decline in Xinjiang. Water consumption by raw coal mining and industry might be the main drivers of the continued decline in GWSA in Inner Mongolia and the North China Plain. The increase in groundwater storage in South China was mainly due to the recharge of rainfall. [ABSTRACT FROM AUTHOR]

The Gravity Recovery and Climate Experiment (GRACE) satellite mission has provided global long-term observations of mass transport in the Earth system with applications in numerous geophysical fields. In this paper, we targeted the in-orbit performance of the GRACE key instruments, the ACCelerometers (ACC) and the MicroWave ranging Instrument (MWI). For the ACC data, we followed a transplant approach analyzing the residual accelerations from transplanted accelerations of one of the two satellites to the other. For the MWI data, we analyzed the post-fit residuals of the monthly GFZ GRACE RL06 solutions with a focus on stationarity. Based on the analyses for the two test years 2007 and 2014, we derived stochastic models for the two instruments and a combined ACC+MWI stochastic model. While all three ACC axes showed worse performance than their preflight specifications, in 2007, a better ACC performance than in 2014 was observed by a factor of 3.6 due to switched-off satellite thermal control. The GRACE MWI noise showed white noise behavior for frequencies above 10 mHz around the level of 1.5 × 10 − 6   m / Hz . In the combined ACC+MWI noise model, the ACC part dominated the frequencies below 10 mHz, while the MWI part dominated above 10 mHz. We applied the combined ACC+MWI stochastic models for 2007 and 2014 to the monthly GFZ GRACE RL06 processing. This improved the formal errors and resulted in a comparable noise level of the estimated gravity field parameters. Furthermore, the need for co-estimating empirical parameters was reduced. [ABSTRACT FROM AUTHOR]

The geophysical effects are the main factor that causes the nonlinear motion of the station, and a comprehensive analysis of the relationship between the GRACE seasonal load deformation and the GPS station coordinates is helpful to study the physical mechanism that causes the nonlinear motion of the station. Aiming at the continuous GPS coordinate time series in Greenland, this paper comprehensively analyzes the correlation between GRACE seasonal load deformation and GPS station coordinates. First, in order to improve the accuracy of GPS station coordinates, the principle component analysis (PCA) method was used to eliminate the common mode error (CME) of the station coordinates. The results show that this method effectively reduces the uncertainty of the station coordinates time series. Secondly, when extracting seasonal signals, it is found that the singular spectrum (SSA) method can effectively obtain the time-varying part of seasonal signals, and its extraction effect is better than that of the least square fitting (LSF) method. Finally, the seasonal relationship between GRACE load deformation and GPS station coordinates is analyzed from the aspects of time series change, correlation, and WRMS reduction. It is found that there are differences in the amplitude and phase parts of the time series. The mean value of correlation is 0.73, the maximum reduction of WRMS is 55.20% (QAQ1 station), and the minimum is −22.69% (KMJP station), indicating that most stations mainly exhibit seasonal load deformation, while individual stations cannot effectively reflect. In addition, the influence of GRACE seasonal load deformation on the station coordinate parameters is quantitatively analyzed. The results show that the best noise model of the station is mainly WN + FN, which effectively reduces the velocity uncertainty of the station coordinate, and weakens the seasonal term oscillation. [ABSTRACT FROM AUTHOR]

Approximately 3.5 million people in Nicaragua have experienced food insecurity due to the El Niño-Southern Oscillation (ENSO)-induced drought from 2014 to 2016. It is essential to study terrestrial water storage component (TWSC) changes and their responses to ENSO to prevent the water crisis in Nicaragua influenced by ENSO. In this paper, we investigate the TWSC changes in Nicaragua and its sub-basins derived from the Gravity Recovery and Climate Experiment (GRACE)'s temporal gravity field, hydrological model, and water level data, and then determine the connection between the TWSC and ENSO from April 2002 to April 2021 by time series analysis. The research results show that: (1) The estimated TWSC changes in Nicaragua are in good agreement with the variation of precipitation and evaporation, and precipitation is the main cause of TWSC variation. (2) According to the cross-correlation analysis, there is a significant negative peak correlation between the interannual TWSC and ENSO in western Nicaragua, especially for interannual soil moisture (−0.80). The difference in peak correlation between the western and eastern sub-basins may be due to the topographic hindrance of the ENSO-inspired precipitation process. (3) The cross-wavelet analysis indicates that the resonance periods between TWSC and ENSO are primarily 2 and 4 years. These resonance periods are related to the two ENSO modes (the central Pacific (CP) mode with a quasi-2-year period and the eastern Pacific (EP) mode with a quasi-4-year period). Furthermore, their resonance phase variation may be due to the transition to ENSO mode. This study revealed the relationship between ENSO and TWSC in Nicaragua, which can provide a certain reference for water resources regulation. [ABSTRACT FROM AUTHOR]

The special geographical environment of the Tibetan Plateau makes ground observation of Ground Water Storage (GWS) changes difficult, and the data obtained from the GRACE gravity satellites can effectively solve this problem. However, it is difficult to investigate the detailed GWS changes because of the coarser spatial resolution of GRACE data. In this paper, we constructed a 0.1° resolution groundwater storage anomalies (GWSA) dataset on the Tibetan Plateau from 2002 to 2020 based on a phased statistical downscaling model and analyzed the spatiotemporal variation and driving factors of the GWSA in order to better study the changes of GWS on the Qinghai Tibet Plateau. The results show that: (1) In the Tibetan Plateau and 12 sub-basins, the GWSA before and after downscaling show a very high correlation in time series and relatively good performance in spatial consistency, and the downscaled GWSA indicate a consistent trend with the measured groundwater level. (2) The GWSA on the Tibetan Plateau shows a downward trend (−0.45 mm/yr) from 2002 to 2020, and the variation trend of the GWSA in the Tibetan Plateau shows significant spatial heterogeneity. (3) The GWSA changes in the Tibetan Plateau are mainly dominated by natural factors, but the influence of human activities in individual sub-basins can not be ignored. Among the teleconnection factors, El Nino-Southern Oscillation Index (ENSO) has the greatest influence on the GWSA on the Tibetan Plateau. [ABSTRACT FROM AUTHOR]

Groundwater is a crucial source of the world's drinking and irrigation water. Nonetheless, it is being rapidly depleted in many parts of the world. To enact policy decisions to preserve this precious resource, policymakers need real-time data on the groundwater levels in their local area. However, groundwater monitoring wells are costly and scarce in supply. The use of satellite imagery is a promising alternative with its ability to provide continuous information over a large area. Machine learning has also emerged as an alternative to computationally intensive physics-based models. However, advancements in machine learning such as unsupervised learning methods have never been translated to groundwater modeling. Thus, in this paper, learned representations were generated for the GRACE satellite for the first time. When used as an input to groundwater prediction models, the learned representations reduce the root mean square error (RMSE) by up to 19% and improve the Nash–Sutcliffe efficiency (NSE) by up to 8x compared to traditional satellite data inputs at three different spatial scales: national, state, and county. The learned representations are able to discern fine-grained patterns from the coarse satellite data, globally downscaling the GRACE satellite. Crucially, the globally trained representations have the potential to improve the performance of virtually every machine learning-based groundwater prediction model. With accurate measurements, local officials are empowered to make proactive decisions to ensure the stability of their region's water. [ABSTRACT FROM AUTHOR]

The precise tracking of distance variations between two satellites in low Earth orbit can provide key data for the understanding of the Earth's system, specifically on seasonal and sub-seasonal water cycles and their impact on water levels. Measured distance variations, caused by local variations in gravitational field, serve as inputs to complex gravity models with which the movement of water on the globe can be identified. Satellite missions GOCE (2009–2013) and GRACE (2002–2017) delivered a significant improvement to our understanding of spatial and temporal gravity variations. Since 2018, GRACE Follow-On has been providing data continuity and features for the first time through the use of a laser interferometer as the technology demonstrator, in addition to a microwave ranging system as the main instrument. The laser interferometer provides an orders-of-magnitude lower measurement noise, and thereby could enable a significant improvement in the measurement of geoids if combined with suitable improvements in auxiliary instrumentation and Earth system modelling. In order to exploit the improved ranging performance, the ESA is investigating the design of a 'Next Generation Gravity Mission', consisting of two pairs of satellites with laser interferometers, improved accelerometers and improved platform performance. In this paper, we present the current design of the laser interferometer developed by us, the development status of the individual instrument units and the options available. [ABSTRACT FROM AUTHOR]

Groundwater-induced land movement can cause damage to property and resources, thus its monitoring is very important for the safety and economics of a city. London is a heavily built-up urban area and relies largely on its groundwater resource and thus poses the threat of land subsidence. Interferometric Synthetic Aperture Radar (InSAR) can facilitate monitoring of land movement and Gravity Recovery and Climate Experiment (GRACE) gravity anomalies can facilitate groundwater monitoring. For London, no previous study has investigated groundwater variations and related land movement using InSAR and GRACE together. In this paper, we used ENVISAT ASAR C-band SAR images to obtain land movement using Persistent Scatterer InSAR (PSInSAR) technique and GRACE gravity anomalies to obtain groundwater variations between December 2002 and December 2010 for central London. Both experiments showed long-term, decreasing, complex, non-linear patterns in the spatial and temporal domain. The land movement values varied from −6 to +6 mm/year, and their reliability was validated with observed Global Navigation Satellite System (GNSS) data, by conducting a two-sample t-test. The average groundwater loss estimated from GRACE was found to be 9.003 MCM/year. The ground movement was compared to observed groundwater values obtained from various boreholes around central London. It was observed that when large volumes of groundwater is extracted then it leads to land subsidence, and when groundwater is recharged then surface uplift is witnessed. The results demonstrate that InSAR and GRACE complement each other and can be an excellent source of monitoring groundwater for hydrologists. [ABSTRACT FROM AUTHOR]

The aim of this study was to investigate the relationship between surface subsidence and groundwater changes. To investigate this relationship, we first analyzed surface subsidence. This paper presents the results of a case study of surface subsidence in Beijing from 1 August 2007 to 29 September 2010. The Multi-temporal Interferometric Synthetic Aperture Radar (multi-temporal InSAR) technique, which can simultaneously detect point-like stable reflectors (PSs) and distributed scatterers (DSs), was used to retrieve the subsidence magnitude and distribution in Beijing using 18 ENVISAT ASAR images. The multi-temporal InSAR-derived subsidence was verified by leveling at an accuracy better than 5 mm/year. Based on the verified multi-temporal InSAR results, a prominent uneven subsidence was identified in Beijing. Specifically, most of the subsidence velocities in the downtown area were within 10 mm/year, and the largest subsidence was detected in Tongzhou, with velocities exceeding 140 mm/year. Furthermore, Gravity Recovery and Climate Experiment (GRACE) data were used to derive the groundwater change series and trend. By comparison with the multi-temporal InSAR-derived subsidence results, the long-term decreasing trend between groundwater changes and surface subsidence showed a relatively high consistency, and a significant impact of groundwater changes on the surface subsidence was identified. Additionally, the spatial distribution of the subsidence funnel was partially consistent with that of groundwater depression, i.e., the former possessed a wider range than the latter. Finally, the relationship between surface subsidence and groundwater changes was determined. [ABSTRACT FROM AUTHOR]

The Gravity Recovery and Climate Experiment (GRACE) enables large-scale monitoring of terrestrial water storage changes, significantly contributing to hydrology and related fields. However, the coarse resolution of groundwater storage anomaly (GWSA) data limits local-scale research utilizing GRACE and GRACE-FO missions. In this study, we develop a regional downscaling model based on the linear regression relationship between GWSA and environmental variables, reducing the grid resolution of GWSA obtained from GRACE from approximately 25 km to 1 km. First, we estimate the missing values of monthly continuous terrestrial water storage anomaly (TWSA) for the period from 2003 to 2020 using interpolated multi-channel singular spectrum analysis (IMSSA). Next, we apply the water balance equation to separate GWSA from TWSA, which is provided jointly by the Global Land Data Assimilation System (GLDAS) and the distributed ecohydrological model ESSI-3. We then employ a partial least squares regression (PLSR) model to identify the most significant environmental variables related to GWSA. Precipitation (Prec), normalized difference vegetation index (NDVI), and actual evapotranspiration (AET), with variable importance in projection (VIP) values greater than 1.0, are recognized as effective variables for reconstructing long-term, high-resolution groundwater storage changes. Finally, we downscale and reconstruct the long-term (2003–2020), high-resolution (1 km × 1 km) monthly GWSA in the Songhua River Basin using fused and supplemented GRACE/GRACE-FO data, employing either geographically weighted regression (GWR) or random forest (RF) models. The results demonstrate superior performance of the GWR model (CC = 0.995, NSE = 0.989, RMSE = 2.505 mm) compared to the RF model in downscaling. The downscaled GWSA in the Songhua River Basin not only achieves high spatial resolution but also exhibits improved accuracy when compared to in situ groundwater observation records. This research enhances understanding of spatiotemporal variations in regional groundwater due to local agricultural and industrial water use, providing a scientific basis for regional water resource management. [ABSTRACT FROM AUTHOR]

In recent decades, the Loess Plateau has undergone rapid urbanization alongside extensive afforestation efforts aimed at controlling soil erosion. These large-scale land use changes have inevitably affected the region's hydrological cycle. Despite these changes, the impact on groundwater has not been thoroughly investigated. This study aims to examine the spatial and temporal evolution of groundwater storage (GWS) in the Loess Plateau from 2003 to 2022, identify the driving factors behind these changes, and evaluate the sustainability of groundwater levels through the Reliability–Resilience–Vulnerability framework. GWS changes were estimated using GRACE gravity satellite data and the Global Land Assimilation Dataset (GLDAS). Our study also analyzed the drivers of GWS evolution by integrating land use change data, ERA5-Land reanalysis data, and various statistical data. Our findings indicate a decline in GWS at a rate of −6.9 ± 3.84 mm/yr. Seasonal variations show that the GWS is relatively higher in spring and autumn, but lower in summer and winter. The eastern part of the Loess Plateau in particular is experiencing a rate of decline that is 150% of that of the overall regional average. Groundwater storage in the Loess Plateau is currently at a critically unsustainable level, with conditions in the west being more favorable compared to the central and eastern regions. Climate factors such as precipitation, evaporation, and runoff did not show a significant correlation with GWS changes. Increases in forest areas and water consumption together explained 95.8% of the changes in GWS, with forest area growth being the dominant factor. Human activities are identified as the main cause of GWS decline. This study's findings improve our understanding of GWS dynamics in the Loess Plateau and offer a scientific basis for formulating groundwater resource management and ecological restoration policies in the region. [ABSTRACT FROM AUTHOR]

The Gravity Recovery and Climate Experiment (GRACE) satellite provides time-varying gravity field models that can detect total water storage change (TWSC) from April 2002 to June 2017, and its second-generation satellite, GRACE Follow-On (GRACE-FO), provides models from June 2018, so there is a one year gap. Swarm satellites are equipped with Global Positioning System (GPS) receivers, which can be used to recover the Earth's time-varying gravitational field. Swarm's time-varying gravitational field models (from December 2013 to June 2018) were solved by the International Combination Service for Time-variable Gravity Field Solutions (COST-G) and the Astronomical Institute of the Czech Academy of Sciences (ASI). On a timely scale, Swarm has the potential to fill the gap between the two generations of GRACE satellites. In this paper, using 26 global watersheds as the study area, first, we explored the optimal data processing strategy for Swarm and then obtained the Swarm-TWSC of each watershed based on the optimal results. Second, we evaluated Swarm's accuracy in detecting regional water storage variations, analyzed the reasons for its superior and inferior performance in different regions, and systematically explored its potential in detecting terrestrial water storage changes in land areas. Finally, we constructed the time series of terrestrial water storage changes from 2002 to 2019 by combining GRACE, Swarm, and GRACE-FO for the Amazon, Volga, and Zambezi Basins. The results show that the optimal data processing strategy of Swarm is different from that of GRACE. The optimal results of Swarm-TWSC were explored in 26 watersheds worldwide; its accuracy is related to the area size, runoff volume, total annual mass change, and instantaneous mass change of the watershed itself, among which the latter is the main factor affecting Swarm-TWSC. Knowledge of the Swarm-TWSC of 26 basins constructed in this paper is important to study long-term water storage changes in basins. [ABSTRACT FROM AUTHOR]

This paper introduces GRACETOOLS, the first open source gravity field recovery tool using GRACE type satellite observations. Our aim is to initiate an open source GRACE data analysis platform, where the existing algorithms and codes for working with GRACE data are shared and improved. We describe the first release of GRACETOOLS that includes solving variational equations for gravity field recovery using GRACE range rate observations. All mathematical models are presented in a matrix format, with emphasis on state transition matrix, followed by details of the batch least squares algorithm. At the end, we demonstrate how GRACETOOLS works with simulated GRACE type observations. The first release of GRACETOOLS consist of all MATLAB M-files and is publicly available at Supplementary Materials. [ABSTRACT FROM AUTHOR]

This study evaluates the use of remote sensing data to improve the understanding of groundwater resources in climate-sensitive regions with limited data availability and increasing agricultural water demands. The research focuses on estimating groundwater reserve dynamics in two major river basins in Morocco, characterized by significant local variability. The study employs data from Gravity Recovery and Climate Experiment satellite (GRACE) and ERA5-Land reanalysis. Two GRACE terrestrial water storage (TWS) products, CSR Mascon and JPL Mascon (RL06), were analyzed, along with auxiliary datasets generated from ERA5-Land, including precipitation, evapotranspiration, and surface runoff. The results show that both GRACE TWS products exhibit strong correlations with groundwater reserves, with correlation coefficients reaching up to 0.96 in the Oum Er-rbia River Basin and 0.95 in the Tensift River Basin (TRB). The root mean square errors (RMSE) were 0.99 cm and 0.88 cm, respectively. GRACE-derived groundwater storage (GWS) demonstrated a moderate correlation with observed groundwater levels in OERRB (R = 0.59, RMSE = 0.82), but a weaker correlation in TRB (R = 0.30, RMSE = 1.01). On the other hand, ERA5-Land-derived GWS showed a stronger correlation with groundwater levels in OERRB (R = 0.72, RMSE = 0.51) and a moderate correlation in TRB (R = 0.63, RMSE = 0.59). The findings suggest that ERA5-Land may provide more accurate assessments of groundwater storage anomalies, particularly in regions with significant local-scale variability in land and water use. High-resolution datasets like ERA5-land are, therefore, more recommended for addressing local-scale heterogeneity in regions with contrasted complexities in groundwater storage characteristics. [ABSTRACT FROM AUTHOR]

Regarding the terrestrial water storage anomaly (TWSA) gap between the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-on (-FO) gravity satellite missions, a BEAST (Bayesian estimator of abrupt change, seasonal change and trend)+GMDH (group method of data handling) gap-filling scheme driven by hydrological and meteorological data is proposed. Considering these driving data usually cannot fully capture the trend changes of the TWSA time series, we propose first to use the BEAST algorithm to perform piecewise linear detrending for the TWSA series and then fill the gap of the detrended series using the GMDH algorithm. The complete gap-filling TWSAs can be readily obtained after adding back the previously removed piecewise trend. By comparing the simulated gap filled by BEAST + GMDH using Multiple Linear Regression and Singular Spectrum Analysis with reference values, the results show that the BEAST + GMDH scheme is superior to the latter two in terms of the correlation coefficient, Nash-efficiency coefficient, and root-mean-square error. The real GRACE/GFO gap filled by BEAST + GMDH is consistent with those from hydrological models, Swarm TWSAs, and other literature regarding spatial distribution patterns. The correlation coefficients there between are, respectively, above 0.90, 0.80, and 0.90 in most of the global river basins. [ABSTRACT FROM AUTHOR]

The accessibility and deployment of complex hydrological models remain significant challenges in water resource management and research. This study presents a comprehensive workflow for converting Python-based hydrological models into web APIs, addressing the need for more accessible and interoperable modeling tools. The workflow leverages modern web technologies and containerization to streamline the deployment process. The workflow was applied to three distinct models: a GRACE downscaling model, a synthetic time series generator, and a MODFLOW groundwater model. The implementation process for each model was completed in approximately 15 min with a reliable internet connection, demonstrating the efficiency of the approach. The resulting APIs provide standardized interfaces for model execution, progress tracking, and result retrieval, facilitating integration with various applications. This workflow significantly reduces barriers to model deployment and usage, potentially broadening the user base for sophisticated hydrological tools. The approach aligns hydrological modeling with contemporary software development practices, opening new avenues for collaboration and innovation. While challenges such as performance scaling and security considerations remain, this work provides a blueprint for making complex hydrological models more accessible and operational, paving the way for enhanced research and practical applications in hydrology. [ABSTRACT FROM AUTHOR]

Persistent droughts pose a threat to agricultural production, and the changing environment worsens the risk of drought exposure. Understanding the propagation of drought in changing environments and assessing possible impact factors can help in the early detection of drought, guiding agricultural production practices. The current study cannot reflect the propagation status of drought to the total terrestrial hydrological drought, so this work creatively investigated the atmospheric to hydrological drought propagation time in the Yangtze River Basin under the dynamic and static perspectives based on the Standardized Precipitation Evapotranspiration Index and the Terrestrial Water Storage Anomalous Drought Index, fine-tuned the time scale to the seasonal scale, and explored the contributing capacity of the variable interactions. The results show that: (1) under the dynamic perspective, while the propagation time is decreasing in the annual scale, the spring season shows the opposite trend; and (2) large variability exists in the timing of drought propagation at spatial scales, with elevation playing the most important influential role, and bivariate interactions contributing stronger explanations compared to single variables. This study highlights the importance of considering the impact of variable interactions and contributes to our understanding of the response of secondary droughts to upper-level droughts, providing valuable insights into the propagation of droughts to total terrestrial hydrologic drought. [ABSTRACT FROM AUTHOR]

Elderly people make up an increasingly large part of society and the Church. The theme of old age is also increasingly present in papal teaching. This is evidenced, for example, by the series of Wednesday Catecheses on old age delivered by Pope Francis in 2022, or by the establishment of the World Day for Grandparents and the Elderly. Given the importance of the presence of the elderly, this article aims to present old age in the perspective of faith, and the importance of the presence of the elderly in the life of the Church. The author will therefore focus, first and foremost, on the view of old age as a time of thanksgiving and gratitude to God for the gift of life, for the goods received, the experiences lived, and the people encountered. Viewed from the perspective of faith, old age is also a time of preparation for death and for meeting the Risen Christ. It is therefore a time to adopt a new outlook on faith and the call to holiness. Old age is, at the same time, a period of life in which individuals can still contribute a lot to the life of the family, society, and the Church through their commitment, service, bearing witness to the faith, bearing witness to the Gospel and the values that flow from living the Gospel, through works of charity and, above all, through sharing the awareness that life is a beautiful gift from God that is worth using well and wisely. And, through the wisdom gained over the many years of their lives, elderly people become authentic witnesses of God's love. The experience of long life and gratitude for this gift is not only relevant to Catholics and Christians, but has a universal appeal, since in any society, regardless of faith, human life should also be valued in old age. [ABSTRACT FROM AUTHOR]

The accuracy of estimating changes in terrestrial water storage (TWS) using Gravity Recovery and Climate Experiment (GRACE) level-2 products is limited by the leakage effect resulting from post-processing and the weak signal magnitude in adjacent areas. The TWS anomaly from 2003 to 2016 in the Dnieper River basin, with characteristics of medium scale and an adjacent weak TWS anomaly area, are estimated in this work. Two categories of leakage error repair approaches (including forward modeling, data-driven, single, and multiple scaling factor approaches) are employed. Root mean square error (RMSE) and Nash–Sutcliffe Efficiency (NSE) are used to evaluate the efficiency of approaches. The TWS anomaly inverted by the forward modeling approach (FM) is more accurate in terms of RMSE 3.04 and NSE 0.796. We compared single and multiple scaling approaches for the TWS anomaly and found that leakage signals mostly come from semi-annual terms. From the recovered results demonstrated in the spatial domain, the South of Dnieper River basin is more sensitive to the leakage effect because of it is adjacent to a weak hydrological signal region near the Black Sea. Further, comprehensive climate insights and physical mechanisms behind the TWS anomaly were confirmed. The temperate continental climate of this river basin is shown according to the variation in TWS anomaly in the spatial domain. Snowmelt plays a significant role in the TWS anomaly of the Dnieper River basin, following the precipitation record and the 14-year temperature spatial distribution for February. We compared single and multiple scaling approaches for the TWS anomaly and found that leakage signals mostly come from semi-annual terms. [ABSTRACT FROM AUTHOR]

The Yangtze River Basin experienced a once-in-a-century extreme drought in 2022 due to extreme weather, which had a serious impact on the local agricultural production and ecological environment. In order to investigate the spatial distribution and occurrence of the extreme drought events, this study used multi-source remote sensing data to monitor the extreme drought events in the Yangtze River Basin in 2022. In this study, the gravity satellite data product CSR_Mascon was used to calculate the GRACE Drought Intensity Index (GRACE-DSI), which was analyzed and compared with the commonly used meteorological drought indices, relative soil humidity, and soil water content data. The results show that (1) terrestrial water storage change data can well reflect the change in water storage in the Yangtze River Basin. Throughout the year, the average change in terrestrial water storage in the Yangtze River Basin from January to June is higher than the average value of 33.47 mm, and the average from July to December is lower than the average value of 48.17 mm; (2) the GRACE-DSI responded well to the intensity and spatial distribution of drought events in the Yangtze River Basin region in 2022. From the point of view of drought area, the Yangtze River Basin showed a trend of extreme drought increasing first, and then decreasing in the area of different levels of drought, and the range of drought reached a maximum in September with a drought area of 175.87 km2, which accounted for 97.71 per cent of the total area; at the same time, the area of extreme drought was the largest, with an area of 85.69 km2; (3) the spatial and temporal variations of the GRACE-DSI and commonly used meteorological drought indices were well correlated, with correlation coefficients above 0.750, among which the correlation coefficient of the SPEI-3 was higher at 0.937; (4) the soil moisture and soil relative humidity products from the CLDAS, combined with soil moisture products from the GLDAS, reflect the starting and ending times of extreme drought events in the Yangtze River Basin in 2022 well, using the information from the actual stations. In conclusion, gravity satellite data, analyzed in synergy with data from multiple sources, help decision makers to better understand and respond to drought. [ABSTRACT FROM AUTHOR]

In areas where groundwater overexploitation occurs, land subsidence triggered by aquifer compaction is observed, resulting in high socio-economic impacts for the affected communities. In this paper, we focus on the Konya region, one of the leading economic centers in the agricultural and industrial sectors in Turkey. We present a multi-source data approach aimed at investigating the complex and fragile environment of this area which is heavily affected by groundwater drawdown and ground subsidence. In particular, in order to analyze the spatial and temporal pattern of the subsidence process we use the Small BAseline Subset DInSAR technique to process two datasets of ENVISAT SAR images spanning the 2002-2010 period. The produced ground deformation maps and associated time-series allow us to detect a wide land subsidence extending for about 1200 km² and measure vertical displacements reaching up to 10 cm in the observed time interval. DInSAR results, complemented with climatic, stratigraphic and piezometric data as well as with land-cover changes information, allow us to give more insights on the impact of climate changes and human activities on groundwater resources depletion and land subsidence. [ABSTRACT FROM AUTHOR]

In the era of global climate change, the monitoring of water resources, including groundwater, is of fundamental importance for nature, agriculture, economy and society. The purpose of this paper is to check compliance of changes in groundwater level obtained from direct measurements in wells with groundwater storage (GWS) anomalies calculated using gravity recovery and climate experiment (GRACE) observations in Poland. Data from the global land data assimilation (GLDAS), in the form of soil moisture (SM) and snow water equivalence (SWE), were used to convert GRACE observations into a series of GWS changes. It was found that very high consistency occurs between GRACE observations and changes in water level in wells, while the GWS series obtained from GRACE and GLDAS do not provide adequate compatibility. Further research presented in the paper was devoted to attempts to explain this phenomenon. In addition, time series of GRACE, GLDAS and groundwater head series were analyzed. [ABSTRACT FROM AUTHOR]

This study addresses the imperative to comprehend gravity shifts resulting from groundwater storage (GWS) variations in the Arabian Peninsula. Despite the critical importance of water resource sustainability and its relationship with gravity, limited research emphasizes the need for expanded exploration. The investigation explores the impact of GWS extraction on the gravity field, utilizing Gravity Recovery and Climate Experiment (GRACE) and Global Land Data Assimilation System (GLDAS) data in addition to validation using the WaterGAP Global Hydrology Model (WGHM). Spanning April 2002 to June 2023, this study predicts GWS trends over the next decade using the Seasonal Autoregressive Integrated Moving Average (SARIMA) model. The comprehensive time-series analysis reveals a significant GRACE-derived groundwater storage (GWS) trend of approximately −4.90 ± 0.32 mm/year during the study period. This trend has a notable impact on the gravity anomaly (GA) values, as observed through the decomposition analysis. The projected GWS indicates a depletion rate of 14.51 km3/year over the next decade. The correlation between GWS and GA is substantial at 0.80, while the GA and rainfall correlation is negligible due to low precipitation rates. Employing multiple linear regression explains 80.61% of the variance in gravity anomaly due to GWS, precipitation, and evapotranspiration. This study investigates climate change factors—precipitation, temperature, and evapotranspiration—providing a holistic understanding of the forces shaping GWS variations. Precipitation and evapotranspiration exhibit nearly equal values, limiting GWS replenishment opportunities. This research holds significance in studying extensive GWS withdrawal in the Arabian Peninsula, particularly concerning crust mass stability. [ABSTRACT FROM AUTHOR]

This study addresses Roger Scruton's understanding of what he called "moments of revelation". In two short essays, both entitled "Effing the ineffable", Scruton framed his discussion of moments of revelation with reference to the medieval Christian mystical discourse. Introducing the medieval discussion of this topic, this study provides an analysis of Scruton's approach to the theme. In tune with the traditional discourse on revelation, his general aim was to demonstrate that there are ways of revealing important truths about the supernatural, of the world "beyond the window", that do not require words to be pronounced. He calls our experiences of such phenomena moments of revelation and identifies four different transitory sources of revelation. This study deals with them one by one, after considering whether it is right to label such a revelation transcendental. The four sources of Scruton's moments of revelation are natural beauty, the beauty of painting, the beauty of music, and personal encounters. The first three examples are connected to his thoughts on art and beauty as a substitute of divine revelation. Perhaps the most surprising of these is the last ones, moments of intersubjective human relationships, "our knowledge of each other". Relying on both Buber and Levinas, Scruton makes the strong claim that it is in the other that we can experience that world "beyond the window". His phenomenological exploration of human encounters sheds light on concepts like grace, shekhinah, or real presence and gift. He explains the Christian understanding of the human–divine relationship as well along the lines of the nature of interpersonal human relationship, both of them being in a certain sense, he claims, transcendental. From grace, his account moves forward to self-sacrifice and finally arrives at his idiosyncratic understanding of gratefulness for life. His moments of revelation in art and interpersonal exchange turn out to be, indeed, late and secular versions of the Christian understanding of revelation. In its summary, this study claims that revelation, understood by Scruton as a form of general human experience, allows to catch a glimpse of that which is beyond the window, by the direct, sensually based experience of either the existence of another person or of the beauty of nature and art. [ABSTRACT FROM AUTHOR]

Situated in China's arid and semi-arid zones, the Xinjiang region heavily relies on groundwater for its freshwater supply. This study utilizes data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission, covering the years 2003 to 2021, to quantitatively evaluate the temporal and spatial changes in groundwater storage anomalies (GWSA) in the Xinjiang region. Furthermore, we incorporate the HydroSHEDS dataset to examine the spatial variations in groundwater storage anomalies across watersheds of varying scales. Based on our findings, the GWSA decreased during the study period at a mean rate of −0.381 mm/month, marked by a consistent trend and notable interannual variability. In addition, significant regional disparities are observed; while groundwater storage in the southeastern watersheds is on an upward trend, a general decline is noted in the northern and central regions. The most pronounced depletion is detected in the northwest, especially in the Ili River basin and along the western slopes of the Tianshan Mountains. These changes are intricately linked to anthropogenic factors, including population growth and escalating water demands. In response, the study advocates for the development and enforcement of more rigorous and scientifically informed groundwater management strategies to promote sustainable water use in Xinjiang. [ABSTRACT FROM AUTHOR]

China has implemented a series of ecological protection and restoration projects in Tianshan Mountain and Yili Valley in Xinjiang, which have significantly improved regional vegetation coverage. Vegetation improves soil structure through roots, especially increasing non-capillary porosity, which enhances the precipitation infiltration performance, thus reducing surface runoff, increasing the interception and infiltration of groundwater resources, and enhancing regional water retention capacity of soil. In order to quantitatively study the impact of ecological conservation and restoration (represented by fraction of natural vegetation coverage, FVC) on groundwater storage (GWS), we investigated GWS changes in this region, identified the main factors, and quantified their relative impacts. Here, we combined data from the Gravity Recovery and Climate Experiment (GRACE) satellite, GRACE Follow-On (GRACE-FO), and Global Land Data Assimilation System (GLDAS) hydrological model from January 2003 to December 2020 and evaluated GWS changes. We used the variable importance in projection and partial least squares regression methods to determine the main influencing factors. We found that (1) before and after 2012, GWS decreased at a rate of 0.80 cm/yr and 0.75 cm/yr (with statistical significance p < 0.01), respectively. (2) Before 2012, the main factors affecting the decrease in GWS were agricultural planting areas, and after 2012, they were temperature, evaporation, and FVC, with relative contributions of 54.72%, 34.59%, and 10.69%, respectively. FVC has a positive regulating effect on the increase in regional GWS. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to estimate the water balance in a semi-arid environment with limited in situ data using a remote sensing approach. We focus on the Lake Manyara catchment, located within the East African Rift of northern Tanzania. We use a distributed conceptual hydrological model driven by remote sensing data to study the spatial and temporal variability of water balance parameters within the catchment. Satellite gravimetry GRACE data is used to verify the trends of the inferred lake level changes. The results show that the lake undergoes high spatial and temporal variations, characteristic of a semi-arid climate with high evaporation and low rainfall. We observe that the Lake Manyara water balance and GRACE equivalent water depth show comparable trends; a decrease after 2002 followed by a sharp increase in 2006-2007. Our modeling confirms the importance of the 2006-2007 Indian Ocean Dipole fluctuation in replenishing the groundwater reservoirs of East Africa. We thus demonstrate that water balance modeling can be performed successfully using remote sensing data even in complex climatic settings. Despite the small size of Lake Manyara, GRACE data showed great potential for hydrological research on smaller un-gauged lakes and catchments in similar semi-arid environments worldwide. The water balance information can be used for further analysis of lake variations in relation to soil erosion, climate and land cover/land use change as well as different lake management and conservation scenarios. [ABSTRACT FROM AUTHOR]

The terrestrial water storage anomaly (TWSA) gap between the Gravity Recovery and Climate Experiment (GRACE) and its follow-on mission (GRACE-FO) is now a significant issue for scientific research in high-resolution time-variable gravity fields. This paper proposes the use of singular spectrum analysis (SSA) to predict the TWSA derived from GRACE. We designed a case study in six regions in China (North China Plain (NCP), Southwest China (SWC), Three-River Headwaters Region (TRHR), Tianshan Mountains Region (TSMR), Heihe River Basin (HRB), and Lishui and Wenzhou area (LSWZ)) using GRACE RL06 data from January 2003 to August 2016 for inversion, which were compared with Center for Space Research (CSR), Helmholtz-Centre Potsdam-German Research Centre for Geosciences (GFZ), Jet Propulsion Laboratory (JPL)'s Mascon (Mass Concentration) RL05, and JPL's Mascon RL06. We evaluated the accuracy of SSA prediction on different temporal scales based on the correlation coefficient (R), Nash–Sutcliffe efficiency (NSE), and root mean square error (RMSE), which were compared with that of an auto-regressive and moving average (ARMA) model. The TWSA from September 2016 to May 2019 were predicted using SSA, which was verified using Mascon RL06, the Global Land Data Assimilation System model, and GRACE-FO results. The results show that: (1) TWSA derived from GRACE agreed well with Mascon in most regions, with the highest consistency with Mascon RL06 and (2) prediction accuracy of GRACE in TRHR and SWC was higher. SSA reconstruction improved R, NSE, and RMSE compared with those of ARMA. The R values for predicting TWS in the six regions using the SSA method were 0.34–0.98, which was better than those for ARMA (0.26–0.97), and the RMSE values were 0.03–5.55 cm, which were better than the 2.29–5.11 cm RMSE for ARMA as a whole. (3) The SSA method produced better predictions for obvious periodic and trending characteristics in the TWSA in most regions, whereas the detailed signal could not be effectively predicted. (4) The predicted TWSA from September 2016 to May 2019 were basically consistent with Global Land Data Assimilation System (GLDAS) results, and the predicted TWSA during June 2018 to May 2019 agreed well with GRACE-FO results. The research method in this paper provides a reference for bridging the gap in the TWSA between GRACE and GRACE-FO. [ABSTRACT FROM AUTHOR]

The laser ranging interferometer onboard the Gravity Recovery and Climate Experiment Follow-On mission proved the feasibility of an interferometric sensor for inter-satellite length tracking with sub-nanometer precision, establishing an important milestone for space laser interferometry and the general expectation that future gravity missions will employ heterodyne laser interferometry for satellite-to-satellite ranging. In this paper, we present the design of an on-axis optical bench for next-generation laser ranging which enhances the received optical power and the transmit beam divergence, enabling longer interferometer arms and relaxing the optical power requirement of the laser assembly. All design functionalities and requirements are verified by means of computer simulations. A thermal analysis is carried out to investigate the robustness of the proposed optical bench to the temperature fluctuations found in orbit. [ABSTRACT FROM AUTHOR]

The availability of water is crucial for the growth and sustainability of human development. The effective management of water resources is essential due to their renewable nature and their critical role in ensuring food security and water safety. In this study, the multi-step-ahead modeling approach of the Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage (TWS) was utilized to gain insights into and forecast the fluctuations in water resources within Saudi Arabia. This study was conducted using mascon solutions obtained from the University of Texas Center for Space Research (UT-CSR) over the period of 2007 to 2017. The data were used in the development of artificial intelligence models, namely, an Elman neural network (ENN), a backpropagation neural network (BPNN), and kernel support vector regression (k-SVR). These models were constructed using various input variables, such as t-12, t-24, t-36, t-48, and TWS, with the output variable being the focus. A simple and weighted average ensemble was introduced to improve the accuracy of marginal and weak predictive results. The performance of the models was assessed with the use of several evaluation metrics, including mean absolute error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE), correlation coefficient (CC), and Nash–Sutcliffe efficiency (NSE). The results of the estimate indicate that k-SVR-M1 (NSE = 0.993, MAE = 0.0346) produced favorable outcomes, whereas ENN-M3 (NSE = 0.6586, MAE = 0.6895) emerged as the second most effective model. The combinations of all other models exhibited accuracies ranging from excellent to marginal, rendering them unreliable for decision-making purposes. Error ensemble methods improved the standalone model and proved merit. The results also serve as an important tool for monitoring changes in global water resources, aiding in drought management, and understanding the Earth's water cycle. [ABSTRACT FROM AUTHOR]

Revealing the mechanism of hydrological and agricultural drought has been challenging and vital in the environment under extreme weather and water resource shortages. To explore the evolution process from meteorological to hydrological and agricultural drought further, multi-source remote sensing data, including the Gravity Recovery and Climate Experiment (GRACE) product, were collected in the Huaihe River basin of China during 2002–2020. Three machine learning methods, including long short-term memory neural network (LSTM), convolutional neural network (CNN), and categorical boosting (CatBoost), were constructed for hydrological and agricultural drought forecasting. The propagation time from meteorological drought to surface water storage and terrestrial water storage drought, evaluated by the standardized precipitation evapotranspiration index, was 8 and 11 months with Pearson correlation coefficients (R) of 0.68 and 0.48, respectively. Groundwater storage drought was correlated with evapotranspiration and vegetation growth with a 12-month lag time, respectively. In addition, vegetation growth was affected by the drought of soil moisture at depths ranging from 100 to 200 cm with an 8-month lag time with an R of −0.39. Although the forecasting performances of terrestrial water storage drought were better than those of groundwater storage drought and agricultural drought, CNN always performed better than LSTM and CatBoost models, with Nash–Sutclife efficiency values during testing ranging from 0.28 to 0.70, 0.26 to 0.33, and −0.10 to −0.40 for terrestrial water storage drought, groundwater storage drought, and agricultural drought at lead times of 0–3 months, respectively. Furthermore, splitting training and testing data at random significantly improved the performances of CNN and CatBoost methods for drought forecasting rather than in chronological order splitting for non-stationary data. [ABSTRACT FROM AUTHOR]