Grace periods and exposure misclassification in self-controlled case-series studies of drug-drug interactions.

The self-controlled case-series (SCCS) research design is increasingly used in pharmacoepidemiologic studies of drug-drug interactions (DDIs), with the target of inference being the incidence rate ratio (IRR) associated with concomitant exposure to the object plus precipitant drug versus the object drug alone. While day-level drug exposure can be inferred from dispensing claims, these inferences may be inaccurate, leading to biased IRRs. Grace periods (periods assuming continued treatment impact after days' supply exhaustion) are frequently used by researchers, but the impact of grace period decisions on bias from exposure misclassification remains unclear. Motivated by an SCCS study examining the potential DDI between clopidogrel (object) and warfarin (precipitant), we investigated bias due to precipitant or object exposure misclassification using simulations. We show that misclassified precipitant treatment always biases the estimated IRR toward the null, whereas misclassified object treatment may lead to bias in either direction or no bias, depending on the scenario. Further, including a grace period for each object dispensing may unintentionally increase the risk of misclassification bias. To minimize such bias, we recommend 1) avoiding the use of grace periods when specifying object drug exposure episodes; and 2) including a washout period following each precipitant exposed period.

Serum BAFF level is associated with the presence and severity of coronary artery disease and acute myocardial infarction.

OBJECTIVE: The aim of this study was to investigate the relationship between circulating levels of B cell activating factor (BAFF) and the presence and severity of coronary artery disease (CAD) and acute myocardial infarction (AMI) in humans, as its biological functions in this context remain unclear. METHODS: Serum BAFF levels were measured in a cohort of 723 patients undergoing angiography, including 204 patients without CAD (control group), 220 patients with stable CAD (CAD group), and 299 patients with AMI (AMI group). Logistic regression analyses were used to assess the association between BAFF and CAD or AMI. RESULTS: Significantly elevated levels of BAFF were observed in patients with CAD and AMI compared to the control group. Furthermore, BAFF levels exhibited a positive correlation with the SYNTAX score (r = 0.3002, P < 0.0001) and the GRACE score (r = 0.5684, P < 0.0001). Logistic regression analysis demonstrated that increased BAFF levels were an independent risk factor for CAD (adjusted OR 1.305, 95% CI 1.078-1.580) and AMI (adjusted OR 2.874, 95% CI 1.708-4.838) after adjusting for confounding variables. Additionally, elevated BAFF levels were significantly associated with a high GRACE score (GRACE score 155 to 319, adjusted OR 4.297, 95% CI 1.841-10.030). BAFF exhibited a sensitivity of 75.0% and specificity of 71.4% in differentiating CAD patients with a high SYNTAX score, and a sensitivity of 75.5% and specificity of 72.8% in identifying AMI patients with a high GRACE score. CONCLUSION: Circulating BAFF levels serve as a valuable diagnostic marker for CAD and AMI. Elevated BAFF levels are associated with the presence and severity of these conditions, suggesting its potential as a clinically relevant biomarker in cardiovascular disease.

The association between GRACE score at admission for myocardial infarction and the incidence of sudden cardiac arrests in long-term follow-up - the MADDEC study.

Background. Sudden cardiac arrest (SCA), often also leading to sudden cardiac death (SCD), is a common complication in coronary artery disease. Despite the effort there is a lack of applicable prediction tools to identify those at high risk. We tested the association between the validated GRACE score and the incidence of SCA after myocardial infarction. Material and methods. A retrospective analysis of 1,985 patients treated for myocardial infarction (MI) between January 1st 2015 and December 31st 2018 and followed until the 31st of December of 2021. The main exposure variable was patients' GRACE score at the point of admission and main outcome variable was incident SCA after hospitalization. Their association was analyzed by subdistribution hazard (SDH) model analysis. The secondary endpoints included SCA in patients with no indication to implantable cardioverter-defibrillator (ICD) device and incident SCD. Results. A total of 1985 patients were treated for MI. Mean GRACE score at baseline was 118.7 (SD 32.0). During a median follow-up time of 5.3 years (IQR 3.8-6.1 years) 78 SCA events and 52 SCDs occurred. In unadjusted analyses one SD increase in GRACE score associated with over 50% higher risk of SCA (SDH 1.55, 95% CI 1.29-1.85, p < 0.0001) and over 40% higher risk for SCD (1.42, 1.12-1.79, p = 0.0033). The associations between SCA and GRACE remained statistically significant even with patients without indication for ICD device (1.57, 1.30-1.90, p < 0.0001) as well as when adjusting with patients LVEF and omitting the age from the GRACE score to better represent the severity of the cardiac event. The association of GRACE and SCD turned statistically insignificant when adjusting with LVEF. Conclusions. GRACE score measured at admission for MI associates with long-term risk for SCA.

What is already known about this subject?Nearly 50% of cardiac mortality is caused by sudden cardiac death, often due to sudden cardiac arrest.Despite the effort, there is a lack of applicable prediction tools to identify those at high risk.What does this study add?This study shows that GRACE score measured at the point of admission for myocardial infarction can be used to evaluate patients' risk for sudden cardiac arrest in a long-term follow-up.How might this impact on clinical practice?Based on our findings, the GRACE score at the point of admission could significantly affect the patients' need for an ICD device after hospitalization for MI and should be considered as a contributing factor when evaluating the patients' follow-up care.

Diagnostic and prognostic role of serum interleukin-6 and carotid ultrasonography to detect subclinical atherosclerosis in patients with RA and ANCA-associated vasculitis.

ANCA-associated vasculitis (AAV) can affect multiple organs with severe life-threatening manifestations. Disease monitoring is difficult due to a lack of defined biomarkers. We aimed to assess the diagnostic role of serum interleukin-6 and vascular ultrasonography in AAV and subclinical atherosclerosis. The study included 20 AAV patients and two control groups of 34 patients with rheumatoid arthritis (RA) and 35 healthy controls. The levels of Il-6, carotid intima-media thickness test (CIMT), atherosclerotic plaque, and degree of stenosis were investigated. A GRACE-risk score was calculated for AAV and RA patients. The AAV patients had elevated levels of IL-6 (115 ± 23.96) compared to the RA patients (91.25 ± 42.63) and the healthy controls (15.65 ± 3.30), p < 0.001. IL-6 showed a diagnostic accuracy of 73% in distinguishing AAV from RA patients (AUC = 0.730; 95% CI 0.591 to 0834). In the AAV group, CIMT was 1.09, above the upper reference value of 0.90, p < 0.001. The AAV patients had a higher median GRACE risk score, and 60% of them had a high risk of cardiovascular events as compared to 35% of the RA patients. Sonography of extracranial vessels and serum levels of IL-6 can be used in daily clinical practice to diagnose and monitor patients with AAV.

The possible utility of global longitudinal strain in the risk-stratifying process of non-ST elevation-acute coronary syndrome.

BACKGROUND: There are various ways that coronary artery disease (CAD) might present itself. Individual risk stratification for non ST-elevation-acute coronary syndrome (NSTE-ACS) patients should determine whether invasive coronary angiography and revascularization should be scheduled. AIM OF WORK: To assess the possible utility of left ventricular global longitudinal strain in the risk-stratifying process of NSTE-ACS. SUBJECTS AND METHODS: The cardiology department of Zagazig University in Egypt organized and oversaw this cross-sectional study. The practical portion was carried out on 90 patients with NSTE-ACS based on European society of cardiology (ESC) guidelines (and they agreed for invasive strategy) between May 2019 and December 2020 at Salalah Heart Center in Sultanate of Oman. All patients underwent a full clinical examination, 12-lead ECG, and serial high-sensitivity troponin T (hs-TnT) in addition to a thorough history taking process. On patient's admission, the GRACE risk score was assessed. All patients who were suspected of having NSTE-ACS upon admission underwent transthoracic echocardiography, including two-dimensional speckle tracking (2D-ST). Left ventricular global longitudinal strain (LV-GLS %) was measured and analyzed using 2D speckle tracking. SYNTAX Score was determined for all patients. RESULTS: By analysis of the performance of LV-GLS% in prediction of high risk by GRACE score, we found that with cutoff (≥-13.8), the AUC was (0.944) with sensitivity, specificity, PPV, NPV, and accuracy (0.944, 93.3%, 84%, 53.8%, 98.4%, 85.6%), respectively. CONCLUSION: Global longitudinal strain can predict accurately high-risk NSTE-ACS patients by GRACE score.

GRACE Follow-On revealed Bangladesh was flooded early in the 2020 monsoon season due to premature soil saturation.

The overall size and timing of monsoon floods in Bangladesh are challenging to measure. The inundated area is extensive in low-lying Bangladesh, and observations of water storage are key to understanding floods. Laser-ranging instruments on Gravity Recovery and Climate Experiment (GRACE) Follow-On spacecraft detected the peak water storage anomaly of 75 gigatons across Bangladesh in late July 2020. This is in addition to, and three times larger than, the maximum storage anomaly in soil layers during the same period. A flood propagation model suggested that the water mass, as shown in satellite observations, is largely influenced by slow floodplain and groundwater flow processes. Independent global positioning system measurements confirmed the timing and total volume of the flood water estimates. According to land surface models, the soils were saturated a month earlier than the timing of the peak floodplain storage observed by GRACE Follow-On. The cyclone Amphan replenished soils with rainfall just before the monsoon rains started, and consequently, excessive runoff was produced and led to the early onset of the 2020 flooding. This study demonstrated how antecedent soil moisture conditions can influence the magnitude and duration of flooding. Continuous monitoring of storage change from GRACE Follow-On gravity measurements provides important information complementary to river gauges and well levels for enhancing hydrologic flood forecasting models and assisting surface water management.

Assessing terrestrial water storage dynamics and multiple factors driving forces in China from 2005 to 2020.

In the context of global warming, comprehending the dynamics of terrestrial water storage (TWS) and its responses to natural and anthropogenic factors is paramount for hydrological research and the management of water resources in China. This study utilized GRACE (Gravity Recovery and Climate Experiment)/GRACE-Follow On (GRACE-FO) satellite data to analyze terrestrial water storage across nine basins in China from 2005 to 2020 at multiple temporal and spatial scales. Subsequently, employing a Geographic detector model, potential influencing factors were identified, and an enhanced Geographically Weighted Regression (GWR) method was proposed for attributing changes in TWS in China. The findings reveal a consistent declining trend in TWS based on GRACE/GRACE-FO data across different temporal scales, with the most pronounced decreases observed in August and September. Geographic Detector analysis unveils significant interactions among various environmental factors, with climate variables playing a pivotal role in modulating hydrological characteristics of major river basins, where rising temperatures can exacerbate the severity of precipitation events, thus increasing the risk of floods and droughts. Moreover, analysis of the primary influencing factors indicates significant impacts of population density and topography on water resources in the southeastern and southwestern regions, particularly amidst increasing human activities and urbanization expansion. The results of this study are crucial for comprehending the dynamic changes and mechanisms of TWS in China, as well as for formulating water resource management strategies.

Long-term trends in human-induced water storage changes for China detected from GRACE data.

Terrestrial Water Storage (TWS) plays a pivotal role in water resource management by providing a comprehensive measure of both surface water and groundwater availability. This study investigates changes in TWS driven by human activities from 2003 to 2023, and forecasts future TWS trends under various climate change and development scenarios. Our findings reveal a continuous decline in China's TWS since 2003, with an average annual decrease of approximately 1.36 mm. This reduction is primarily attributed to the combined effects of climate change and human activities, including irrigation, industrial water use, and domestic water consumption. Notably, TWS exhibits significant seasonal and annual fluctuations, with variations ranging ±10 mm. For the future period (2024-2030), we project greater disparities between water resource supply and demand in specific years for the Songliao, Southwest, and Yangtze basins. Consequently, future water resource management must prioritize water conservation during wet seasons, particularly in years when supply-demand conflicts for limited water resources intensify. This study is valuable for effective planning and sustainable utilization of water resources.

Application of GRACE-based satellite estimates in the assessment of flood potential: A case study of Gangetic-Brahmaputra basin, India.

The high frequency of flood occurrences and the uneven distribution of hydrological stations make it difficult to monitor large-scale floods. Emergence of the Gravity Recovery and Climate Experiment (GRACE) satellite system sets up a new era of large-scale flood monitoring without much reliance on in situ hydrological observations. The GRACE-derived flood potential index (FPI) exhibits its ability to monitor major events of 2003, 2004, 2007, and 2008 over the Indo-Gangetic-Brahmaputra Basin (IGBB). Precipitation and soil moisture are the major influencing factors of flood. However, the response of potential flooding to such parameters is little known. Pearson's lag correlation analysis is used to examine the response of the GRACE-based FPI to precipitation and soil moisture over the study region comparing seasonal time series of the variables. Results exhibited a 2-month lagged response of FPI to precipitation in the Upper Gangetic Yamuna Chambal Basin (UGYCB) and the Lower Gangetic Basin (LGB) and 1-month lagged response in the Lower Brahmaputra Basin (LBB). With context to soil moisture, a 1-month lag is observed in the Gangetic basins, and no lag is observed in the LBB. Event wise analysis of the lags portrays slightly varying lags for different events; however, it provides a picture on the interaction between these variables. This study also assesses the agreement between FPI and satellite-based river discharge, i.e. Dartmouth Flood Observatory (DFO) discharge. A good correlation (> 0.60) between the two is observed. Threshold values of FPI are determined for the LBB due to its annual flood frequency. The nearly similar accuracy of threshold FPI, determined using DFO discharge, in monitoring floods and the predictive skill measure of FPI for LBB to the previous studies demonstrates the utility of satellite-based discharge in the quantification of threshold FPI values for different percentile floods.

Evaluating groundwater resources trends through multiple conceptual models and GRACE satellite data.

In this research, three numerical groundwater flow models, developed and calibrated from three equally plausible conceptual models over the Nasia Basin, have been used to assess groundwater resources variations over a transient period. The use of multiple numerical models reduces the effect of uncertainties in conceptual model formulation. All the three calibrated numerical models indicate an increasing trend of groundwater recharge and storage over the period of the groundwater level monitoring. This suggests that the prevailing erratic climatic conditions in the area are conducive for increasing groundwater recharge and storage in the terrain. The high-intensity, short duration rainfall patterns, attending climate change in the basin, enhance high levels of infiltration and percolation, leading to steadily increasing groundwater recharge. Groundwater recharge estimates from each of the models over the transient period appear to reflect the pattern of seasonal variations in rainfall in the region. Data from the models indicates a significant role of baseflow in sustaining perennial streamflow in the area. This presents a significant development in terms of groundwater-based adaptation projects, especially in agriculture. The trend of groundwater recharge in the Nasia Basin is in sync with regional groundwater storage variations estimated from the Gravity Recovery and Climate Experiment (GRACE) satellite data collected and processed over the Volta Basin. At the Volta Basin level, groundwater storage variations indicate a strong positive trend of increasing groundwater recharge from 2002 (beginning of the GRACE mission) to 2022 (end point of the data used for this research). Analysis of the GRACE data suggests that there is a cumulative increase in groundwater storage by 30 cm, representing approximately 120 km3 of groundwater over the period in the basin. This translates into approximately 15 mm/year of groundwater storage increase. Thus, at both the regional and local levels, groundwater appears to be responding positively to the impacts of erratic rainfall patterns observed in the area recently. The high-intensity, short duration rainfall patterns appear to favor significant groundwater recharge, resulting in a strong positive groundwater storage signal. The high positive groundwater storage signal suggests increasing groundwater resources potential in the area, indicating promising opportunities for groundwater-based climate change adaptation interventions.

A State of Grace: Community, Self-Consciousness, and Faith in W.H. Auden's "The Age of Anxiety".

In this essay, the author examines a highly influential poem, The Age of Anxiety by W.H. Auden, for its engagement with anxiety and religious faith in the modern world. Published in 1947, the book-length poem reveals Auden's deep understanding of western psychology, Judaism, and Christianity. The author argues for the relevance of The Age of Anxiety in this modern moment, but demonstrates that this relevance does not derive from any direct diagnostic or therapeutic implications of the poem. Rather, Auden's work provides readers with an image of a state of grace in the middle of an age of anxiety.

Grace, too: the sense of agency and Jeremy Safran's relational vision.

The sense of agency, our felt sense of authorship for our actions, is a difficult concept to define, yet its faltering stands at the heart of psychopathology. Historically undertheorized by psychoanalysis and typically positioned opposite relatedness by clinical psychology, Jeremy Safran conceived of agency and relatedness as paradoxically related. This paper pays tribute to Safran's ideas by taking his writings on agency as a starting point to elaborate how agency forms, and goes awry, in the relational crucible of early life. In doing so, the paper draws on the developmental theory of Winnicott, empirical research on embodied agency from adjacent fields of study, and Safran's clinical phenomenology.

Performance of the Risk Scores for Predicting In-Hospital Mortality in Patients with Acute Coronary Syndrome in a Chinese Cohort.

Background: The prognosis of patients with acute coronary syndrome (ACS) varies greatly, and risk assessment models can help clinicians to identify and manage high-risk patients. While the Global Registry of Acute Coronary Events (GRACE) model is widely used, the clinical pathways for acute coronary syndromes (CPACS), which was constructed based on the Chinese population, and acute coronary treatment and intervention outcomes network (ACTION) have not yet been validated in the Chinese population. Methods: Patients with ACS who underwent coronary angiography or percutaneous coronary intervention from 2011 to 2020, were retrospectively recruited and the appropriate corresponding clinical indicators was obtained. The primary endpoint was in-hospital mortality. The performance of the GRACE, GRACE 2.0, ACTION, thrombolysis in myocardial infarction (TIMI) and CPACS risk models was evaluated and compared. Results: A total of 19,237 patients with ACS were included. Overall, in-hospital mortality was 2.2%. ACTION showed the highest accuracy in predicting discriminated risk (c-index 0.945, 95% confidence interval [CI] 0.922-0.955), but the calibration was not satisfactory. GRACE and GRACE 2.0 did not significantly differ in discrimination (p = 0.1480). GRACE showed the most accurate calibration in all patients and in the subgroup analysis of all models. CPACS (c-index 0.841, 95% CI 0.821-0.861) and TIMI (c-index 0.811, 95% CI 0.787-0.835) did not outperform (c-index 0.926, 95% CI 0.911-0.940). Conclusions: In contemporary Chinese ACS patients, the ACTION risk model's calibration is not satisfactory, although outperformed the gold standard GRACE model in predicting hospital mortality. The CPACS model developed for Chinese patients did not show better predictive performance than the GRACE model.

Predictive Value of the Modified GRACE Scoring System for All-Cause Mortality in Patients with Acute Myocardial Infarction.

Background: To establish a modified Global Registry of Acute Coronary Events (GRACE) scoring system with an improved predictive performance compared with the traditional GRACE scoring system. Methods: We identified 5512 patients who were hospitalized with a definite diagnosis of acute myocardial infarction (AMI) from January 1, 2015, to December 31, 2020, at the Heart Center of the First Affiliated Hospital of Xinjiang Medical University through the hospital's electronic medical record system. A total of 4561 patients were enrolled after the inclusion and exclusion criteria were applied. The mean follow-up was 51.8 ± 23.4 months. The patients were divided into dead and alive groups by endpoint events. The differences between the two groups were compared using the two-sample t test and chi-square test. Adjusted traditional risk factors as well as LogBNP (B-type natriuretic peptide precursor, BNP) and the modified GRACE scoring system were included in a multifactorial COX regression model. The predictive performance of the traditional and modified GRACE scoring systems was compared by (Receiver Operating Characteristic) ROC curves. Results: Significant differences in age, heart rate, creatinine, uric acid, LogBNP, traditional GRACE score, and modified GRACE score were found between the dead and alive groups by the two-sample t test. Comparison of the two groups by the chi-square test revealed that the dead group had a higher incidence of males; higher cardiac function class; a previous history of hypertension, diabetes, coronary artery disease (CAD), or cerebrovascular disease; a history of smoking; the need for intra-aortic balloon pump (IABP) support; and more patients taking aspirin, clopidogrel, ticagrelor, and ß -blockers. The results were analyzed by a multifactorial COX regression model, and after adjusting for confounders, age, cardiac function class, history of CAD, use of aspirin and ß -blockers, and the modified GRACE scoring system were found to be associated with all-cause mortality (ACM) in patients with AMI. The ROC curve was used to compare the predictive performance of the conventional GRACE scoring system with that of the modified GRACE scoring system, and it was found that the modified GRACE scoring system (Area Under Curve (AUC) = 0.809, p < 0.001, 95% (Confidence Interval) CI (0.789-0.829)) was significantly better than the traditional GRACE scoring system (AUC = 0.786, p < 0.001, 95% CI (0.764-0.808)), the comparison between the two scores was statistically significant (p < 0.001). The change in the C statistic after 10-fold crossover internal validation of the modified GRACE score was not significant, and the integrated discrimination improvement (IDI) between the old and new models was calculated with IDI = 0.019 > 0, suggesting that the modified GRACE score has a positive improvement on the traditional GRACE score. Conclusions: The modified GRACE scoring system, established by combining B-type natriuretic peptide precursor (BNP) and the traditional GRACE scoring system, was independently associated with ACM in patients with AMI, with a larger AUC and higher predictive value than the traditional GRACE scoring system. Clinical Trial Registration: NCT02737956.

Ethnicity-dependent performance of the Global Registry of Acute Coronary Events risk score for prediction of non-ST-segment elevation myocardial infarction in-hospital mortality: nationwide cohort study.

AIMS: The Global Registry of Acute Coronary Events (GRACE) score was developed to evaluate risk in patients with the acute coronary syndrome with or without ST-segment elevation. Little is known about its performance at predicting in-hospital mortality for ethnic minority patients. METHODS AND RESULTS: We identified 326 160 admissions with non-ST-segment elevation myocardial infarction (NSTEMI) in the Myocardial Infarction National Audit Project (MINAP), 2010-17, including White (n = 299 184) and ethnic minorities (excluding White minorities) (n = 26 976). We calculated the GRACE score for in-hospital mortality and assessed ethnic group baseline characteristics by low, intermediate and high risk. The performance of the GRACE risk score was estimated by discrimination [area under the receiver operating characteristic curve (AUC)] and calibration (calibration plots). Ethnic minorities presented younger and had increased prevalence of cardiometabolic risk factors in all GRACE risk groups. The GRACE risk score for White [AUC 0.87, 95% confidence interval (CI) 0.86-0.87] and ethnic minority (AUC 0.87, 95% CI 0.86-0.88) patients had good discrimination. However, whilst the GRACE risk model was well calibrated in White patients (expected to observed (E : O) in-hospital death rate ratio 0.99; slope 1.00), it overestimated risk in ethnic minority patients (E : O ratio 1.29; slope: 0.94). CONCLUSION: The GRACE risk score provided good discrimination overall for in-hospital mortality, but was not well calibrated and overestimated risk for ethnic minorities with NSTEMI.

Using Downscaled GRACE Mascon Data to Assess Total Water Storage in Mississippi Alluvial Plain Aquifer.

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.

Evaluating the Hydrological Components Contributions to Terrestrial Water Storage Changes in Inner Mongolia with Multiple Datasets.

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.

Global analysis of the correlation and propagation among meteorological, agricultural, surface water, and groundwater droughts.

Groundwater drought monitoring relies on ground observation data, which cannot be used to reflect large-scale droughts in groundwater resources. The Gravity Recovery and Climate Experiment Satellite (GRACE) improved the situation and provided a new solution for groundwater drought research. However, the propagation relationship among global different drought types has not been fully explored. We employed CRU precipitation data, MERR2 reanalysis soil moisture data, GLDAS and GRACE data to calculate SPI (Standardized precipitation index), SSI (Standardized soil moisture index), SRI (Standardized runoff index), and GDI (Groundwater drought index), characterizing meteorological, agricultural, surface water and groundwater droughts, respectively. The Pearson correlation coefficient was adopted to study the propagation time of these four types of droughts. The results showed that the average propagation times for the different drought types are meteorological drought to surface water drought (3.5 months), meteorological drought to agricultural drought (5.7 months), agricultural drought to groundwater drought (12.97 months), surface water drought to groundwater drought (13.78 months), and meteorological drought to groundwater drought (14.47 months) from longest to shortest. (2) Climate conditions had a significant impact on the propagation time of different drought types. Low temperatures in cold climates resulted in the longest drought propagation time, while dry summer climates in temperate climates reduced drought propagation time. There were weaker propagation relationships in arid climates. In tropical climates, precipitation may not be the main driving factor for drought propagation. (3) Different land cover types show significant differences in the propagation of groundwater droughts, with forests having a longer propagation time from meteorological drought to agricultural drought or surface water drought than grassland and cropland, and forests having the shortest propagation time when meteorological drought, agricultural drought, and surface water drought is propagated to groundwater drought. Woody plants have deeper root systems than herbaceous plants and can draw up deeper groundwater. Forests have greater water storage capacity and weaker groundwater recharge than grasslands and croplands, resulting in forests being more resistant to agricultural and surface water droughts and less resistant to groundwater droughts during meteorological droughts. This study can help to clarify the propagation laws among different drought types and understand the internal mechanisms that affect the development of drought during the water cycle.

Enhancing spatial resolution of GRACE-derived groundwater storage anomalies in Urmia catchment using machine learning downscaling methods.

The Urmia lake in north-west Iran has dried up to perilously low levels in the past two decades. In this study, we investigate the drivers behind the decline in lake water level with the help of in-situ and remote sensing data. We use total water storage (TWS) changes from the gravity recovery and climate experiment (GRACE) satellite mission. TWS from GRACE includes all the water storage compartments in a column and is the only remote sensing product that can help in estimating groundwater storage (GWS) changes. The coarse spatial (approx. 300 km) resolution of GRACE does not allow us to identify local changes that may have led to the Urmia lake disaster. In this study, we tackle the poor resolution of the GRACE data by employing three machine learning (ML) methods including random forest (RF), support vector regression (SVR) and multi-layer perceptron (MLP). The methods predict the groundwater storage anomaly (GWSA), derived from GRACE, as a function of hydro-climatic variables such as precipitation, evapotranspiration, land surface temperature (LST) and normalized difference vegetation index (NDVI) on a finer scale of 0.25° × 0.25°. We found that i) The RF model exhibited highest R (0.98), highest NSE (0.96) and lowest RMSE (18.36 mm) values. ii) The RF downscaled data indicated that the exploitation of groundwater resources in the aquifers is the main driver of groundwater storage and changes in the regional ecosystem, which has been corroborated by few other studies as well. The impact of precipitation and evapotranspiration on the GWSA was found to be rather weak, indicating that the anthropogenic derivers had the most significant impact on the GWSA changes. iii) We generally observed a significant negative trend in GWSA, having also significant positive correlations with the well data. However, over regions with dam construction significant negative correlations were found.

Spatiotemporal variability and controlling factors of groundwater depletion in endorheic basins of Northwest China.

Recent global groundwater overpumping is threatening ecosystem stability and food security, particularly in arid basins. A solid investigation regarding the drivers of groundwater depletion is vital for groundwater restoration, hitherto, yet it remains largely unquantified. Here, a framework to quantify the contribution of natural forcing (NF) and anthropogenic perturbations (AP) to groundwater storage anomalies (GWSA) variability by separating the GWSA estimated by the Gravity Recovery and Climate Experiment (GRACE) satellite into natural- and human-induced GWSA was proposed in the northwest endorheic basin (NWEB) of China. Further, a multiple linear regression model was established for GWSA change prediction. Our results showed that, during the period 2003-2020, the GWSA depleted at a rate of 0.25 cm yr-1 in the entire NWEB. In addition, GWSA was found to decrease significantly (exceeding 1 cm yr-1) in the west of NWEB where there are heavily irrigated areas, and has become one of the regions with the most serious groundwater depletion in China. Whereas a significantly increasing trend (greater than 0.5 cm yr-1) was observed in the Qaidam basin and south part of the Tarim River basin, becoming a groundwater enrichment reservoir in NWEB. The negative contribution of AP to groundwater depletion has increased from 3% to 95% in the last decade, as determined by separating the effects of NF and AP on GWSA. The rapid expansion of the cropland area and the increase in water use due to population growth are investigated to be the main reasons for GWSA depletion, particularly in the North Tianshan Rivers, Turpan-Hami, and Tarim River basins. Therefore, we conclude that AP are dominating and accelerating groundwater depletion in the NWEB. The increase of GWSA in the Qaidam basin has been attributed to the increase in solid water melt and regional precipitation. The western route project of China's south-north water diversion and water-saving irrigation are important ways to solve the problem of groundwater depletion in NWEB. Our results emphasize that a more feasible framework capable of reliably identifying the driving factors of groundwater storage change is a necessary tool for promoting the sustainable management of groundwater resources under both NF and AP in arid endorheic basins.