Toward Improved Parameterizations of Reservoir Operation in Ungauged Basins: A Synergistic Framework Coupling Satellite Remote Sensing, Hydrologic Modeling, and Conceptual Operation Schemes

Assessments of water and energy security over historical and future periods require hydrologic models that can accurately simulate reservoir operations. However, scare reservoir operation data limits the accuracy of current reservoir representations in simulating reservoir behaviors. Furthermore, the reliability of these representations under changing inflow regimes remains unclear, which makes their application for long future planning horizons questionable. To this end, we propose a synergistic framework to predict the release, storage, and hydropower production of ungauged reservoirs (i.e., reservoirs without in-situ inflow, release, storage, and operating rules) by combining remotely sensed reservoir operating patterns and model-simulated reservoir inflow with conceptual reservoir operation schemes within a land surface-hydrologic model. A previously developed reservoir operation scheme is extended with a storage anomaly based calibration approach to accommodate the relatively short time series and large time intervals of remotely sensed data. By setting up controlled experiments in the Yalong River Basin in China, we show that remote sensing can improve the parameter estimation and simulations of ungauged reservoirs for all selected reservoir operation schemes, thereby improving the downstream flood and streamflow simulations. However, most of these schemes show degraded accuracies of reservoir operation simulations under a changing inflow regime, which could lead to unreliable assessments of future water resources and hydropower production. In comparison, our newly extended reservoir operation scheme can be more adaptable to flow regime variations. Our study provides a practical framework for reservoir impact assessments and predictions with the ongoing satellite altimetry projects such as Surface Water and Ocean Topography

Toward improved parameterizations of reservoir operation in ungauged basins: a synergistic framework coupling satellite remote sensing, hydrologic modeling, and conceptual operation schemes

Assessments of water and energy security over historical and future periods require hydrologic models that can accurately simulate reservoir operations. However, scare reservoir operation data limits the accuracy of current reservoir representations in simulating reservoir behaviors. Furthermore, the reliability of these representations under changing inflow regimes remains unclear, which makes their application for long future planning horizons questionable. To this end, we propose a synergistic framework to predict the release, storage, and hydropower production of ungauged reservoirs (i.e., reservoirs without in-situ inflow, release, storage, and operating rules) by combining remotely sensed reservoir operating patterns and model-simulated reservoir inflow with conceptual reservoir operation schemes within a land surface-hydrologic model. A previously developed reservoir operation scheme is extended with a storage anomaly based calibration approach to accommodate the relatively short time series and large time intervals of remotely sensed data. By setting up controlled experiments in the Yalong River Basin in China, we show that remote sensing can improve the parameter estimation and simulations of ungauged reservoirs for all selected reservoir operation schemes, thereby improving the downstream flood and streamflow simulations. However, most of these schemes show degraded accuracies of reservoir operation simulations under a changing inflow regime, which could lead to unreliable assessments of future water resources and hydropower production. In comparison, our newly extended reservoir operation scheme can be more adaptable to flow regime variations. Our study provides a practical framework for reservoir impact assessments and predictions with the ongoing satellite altimetry projects such as Surface Water and Ocean Topography

Effect of Sodium-Glucose Co-transporter 2 Inhibitors on Bone Metabolism and Fracture Risk

The effect of anti-diabetic medications on bone metabolism has received increasing attention, considering that type 2 diabetes mellitus is a common metabolic disorder with adverse effects on bone metabolism. Sodium-glucose co-transporter 2 (SGLT2) inhibitors are novel anti-diabetic medications that prevent glucose resorption at the proximal convoluted tubules in the kidney, increasing urinary glucose excretion, and decreasing the blood glucose level. The superiority of SGLT2 inhibitors shows in reducing the glucose level independent of insulin secretion, lowering the risk of hypoglycemia, and improving cardiovascular outcomes. SGLT2 inhibitors have been associated with genital mycotic infections, increased risk of acute kidney injury, dehydration, orthostatic hypotension, and ketoacidosis. Moreover, the effect of SGLT2 inhibitors on bone metabolism and fracture risk has been widely taken into consideration. Our review summarizes the results of current studies investigating the effects of SGLT2 inhibitors on bone metabolism (possibly including increased bone turnover, disrupted bone microarchitecture, and reduced bone mineral density). Several mechanisms are probably involved, such as bone mineral losses due to the disturbed calcium and phosphate homeostasis, as confirmed by an increase in fibroblast growth factor 23 and parathyroid hormone levels and a decrease in 1,25-dihydroxyvitamin D levels. SGLT2 inhibitors might indirectly increase bone turnover by weight loss. Lowering the blood glucose level might ameliorate bone metabolism impairment in diabetes. The effect of SGLT2 inhibitors on bone fractures remains unclear. Evidence indicating the direct effect of SGLT2 inhibitors on fracture risk is lacking and increased falls probably contribute to fractures

Model estimates of China's terrestrial water storage variation due to reservoir operation

Understanding the role of reservoirs in the terrestrial water cycle is critical to support the sustainable management of water resources especially for China where reservoirs have been extensively built nationwide. However, this has been a scientific challenge due to the limited availability of continuous, long-term reservoir operation records at large scales, and a process-based modeling tool to accurately depict reservoirs as part of the terrestrial water cycle is still lacking. Here, we develop a continental-scale land surface-hydrologic model over the mainland China by explicitly representing 3,547 reservoirs in the model with a calibration-free conceptual operation scheme for ungauged reservoirs and a hydrodynamically based two-way coupled scheme. The model is spatially calibrated and then extensively validated against streamflow observations, reservoir storage observations and GRACE-based terrestrial water storage anomalies. A 30-year simulation is then performed to quantify the seasonal dynamics of China’s reservoir water storage (RWS) and its role in China\u27s terrestrial water storage (TWS) over recent decades. We estimate that, over a seasonal cycle, China\u27s RWS variation is 15%, 16%, and 25% of TWS variation during 1981–1990, 1991–2000, and 2001–2010, respectively, and one-fifth of China’s reservoir capacity are effectively used annually. In most regions, reservoirs play a growing role in modulating the water cycle over time. Despite that, an estimated 80 million people have faced increasing water resources challenges in the past decades due to the significantly weakened reservoir regulation of the water cycle. Our approaches and findings could help the government better address the water security challenges under environmental changes

Association Between Bone Mineral Density, Bone Turnover Markers, and Serum Cholesterol Levels in Type 2 Diabetes

Purpose: The association between bone mineral density (BMD), bone turnover markers, and serum cholesterol in healthy population has already been proved. However, in patients with type 2 diabetes mellitus (T2D), it has not been adequately analyzed. In this study, we investigated the correlation between BMD, bone turnover markers, and serum cholesterol levels in people with T2D.Methods: We enrolled 1,040 men and 735 women with T2D from Zhongshan Hospital between October 2009 and January 2013. Their general condition, history of diseases and medication, serum markers, and BMD data were collected. We used logistic regression analysis to identify the association between serum cholesterol levels and BMD as well as bone turnover markers.Results: In multivariate regression analysis, we observed that in men with T2D, high high-density lipoprotein-cholesterol and total cholesterol levels were significantly associated with low total lumbar, femur neck, and total hip BMD, while low-density lipoprotein-cholesterol level was only inversely associated with total lumbar and femur neck BMD. Total cholesterol and low-density lipoprotein-cholesterol levels were also negatively associated with osteocalcin, procollagen type I N-terminal propeptide, and β-crosslaps. In women with T2D, high-density lipoprotein-cholesterol level was observed to be negatively correlated with total lumbar, femur neck, and total hip BMD, while total cholesterol and low-density lipoprotein-cholesterol levels were only associated with BMD at the total lumbar. Furthermore, total cholesterol was also negatively associated with osteocalcin, procollagen type I N-terminal propeptide, and β-crosslaps; high-density lipoprotein-cholesterol was only related to osteocalcin and parathyroid hormone, while low-density lipoprotein-cholesterol was only related to β-crosslaps in women.Conclusion: Our study suggests a significantly negative correlation between serum cholesterol levels and BMD in both men and women with T2D. The associations between serum cholesterol levels and bone turnover markers were also observed in T2D patients

A Multi-step Prediction Method of Urban Air Quality Index Based on Meteorological Factors Analysis

With the development of science and technology, Industry, transportation and other industries used to discharge a large number of pollutants into the atmosphere, which results in air pollution. When air pollution become serious, it will do great harm to human health. High-precision Air Quality Index(AQI) prediction is as important as weather prediction. People could arrange traveling and their life according to the highly precise prediction results, so as to better protect their own health. Considering a lot of complex factors, we choose several potential meteorological factors and historical data to precisely forecast AQI. The principal component analysis (PCA) is introduced in our method to conduct dimension reduction on nine meteorological factors, in order to reduce noise of data and the complexity of the model calculation, which improves the accuracy of AQI prediction as a result. Then the data of meteorological factors after PCA and historical AQI are input into the multi-step prediction model based on LSSVM to train and refine it. Finally, we set up the experiment with data of meteorological factors and AQI. Experimental results show that the method proposed in this paper has better prediction accuracy over classical ARIMA method and has better generalization than ARIMA method as well

A Critical Review on Regional Ecological Environment Assessment

With the continuous advancement of industrialization and urbanization, the relationship between mankind and the ecological environment has become increasingly tense, and the ecological environment assessment has become a research hotspot in recent years. The article summarizes the research content and development process of ecological environment assessment, lists various mainstream assessment methods and introduces their application characteristics, and then divides the weight determination methods into subjective weighting, objective weighting and subjective and objective combination, and analyses their advantages and disadvantages; Meanwhile, the application of remote sensing technology in ecological environment assessment research is analyzed. Finally, the main problems of ecological environment assessment work are summarized and its future development direction is pointed out

Relation of Mid-High-Latitude Eurasian ISO to Ural Blocking Frequency and Their Co-Effect on Extreme Hot Events during Boreal Summer

Based on NCEP reanalysis daily data during 1979–2018, the spatiotemporal evolution of the 10–30-day atmospheric intraseasonal oscillations (ISO) at mid-high-latitude Eurasia and its effect on the Ural blocking frequency are investigated. The co-effect of the blocking and ISO on extreme hot event frequency is also investigated. The ISO exhibits two modes of eastward and westward propagation. During the eastward (westward) propagating mode, the northwest–southeast tilted quadrupole (east–west dipole) quasi-barotropic geopotential height anomaly coupled with the air temperature anomaly at the troposphere propagates southeastward (westward). The phase composite shows that, during both modes, the mid-high-latitude low-frequency Rossby wave trains significantly affect the frequency of the European blocking during the propagating journey. The most frequent European blocking appears in phase 2 during both the eastward- and westward- propagating mode. Compared with the situation without the Ural blocking, the blocking activity results in the positive geopotential height anomalies throughout Europe and north of 60° N in the Ural Mountains and the negative geopotential height anomalies in the south of 60° N in the Ural Mountains and north of the Japan Sea. The occurrence of Ural blocking is conducive to the occurrence of extreme high-temperature events in Europe and the high latitudes of the Ural Mountains, and a reduced frequency of extreme high-temperature events in the mid-latitudes of the Ural Mountains and north of the Japan Sea. Therefore, the Ural blocking activities significantly regulate the effect of the two propagating ISO modes on the extreme hot events over the middle and high latitudes of Eurasia