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Mountainous areas are of special hydrological concern because topography and atmospheric conditions can result in large and sudden floods, posing serious risks to water-related safety in neighbouring countries. The Yarlung Zangbo (YZ) River basin is the largest river basin on the Tibetan Plateau (TP), but how floods will discharge in this basin and how the role of glacier melt in floods will change throughout the 21st-century under shared socioeconomic pathways scenarios (SSP2-4.5 and SSP5-8.5) remain unclear. Here, we comprehensively address this scientific question based on a well-validated large-scale glacier-hydrology model. The results indicate that extreme floods was projected to increase in the YZ basin, and was mainly reflected in increased duration (4–10 d per decade) and intensity (153–985 m3 s−1 per decade). Glacier runoff was projected to increase (2–30 mm per decade) throughout the 21st-century, but there was also a noticeable decrease or deceleration in glacier runoff growth in the late first half of the century under the SSP2-4.5, and in the latter half of the century under the SSP5-8.5. Glacier melt was projected to enhance the duration (12%–23%) and intensity (15%–21%) of extreme floods under both SSPs, which would aggravate the impact of future floods on the socioeconomics of the YZ basin. This effect was gradually overwhelmed by precipitation-induced floods from glacier areas to YZ outlet. This study takes the YZ basin as a projection framework example to help enrich the understanding of future flood hazards in basins affected by rainfall- or meltwater across the TP, and to help policy-makers and water managers develop future plans.

ERA5 (European Centre for Medium-Range Weather Forecasts Reanalysis Fifth Generation) is a significant dataset in climate reanalysis. Conducting a global-scale accuracy assessment and spatiotemporal distribution characteristic study of its temperature and precipitation data is crucial for gaining in-depth understanding of extreme climate changes. This study, based on CRU TS v4.04 (Climatic Research Unit Time-Series version 4.04) gridded data, employs multiple statistical indicators and detection metrics to assess the accuracy of the ERA5 temperature and precipitation dataset at a monthly scale over the past 70 years. Additionally, it utilizes Empirical Orthogonal Functions (EOF) to explore its spatiotemporal distribution characteristics. The results indicate that: (1) ERA5 demonstrates good consistency in most regions globally; however, the influence of uneven station density distribution results in weaker correlation in areas with sparse station density. (2) The accuracy of ERA5 data exhibits certain differences between the two periods (1950–1979, 1979–2019); with the overall performance of ERA5 temperature data near the Earth’s surface being better than that of precipitation data. (3) ERA5 precipitation data in the mid and low latitudes of the Southern and Northern Hemispheres exhibit characteristics of positive–negative distribution, while temperature data show an opposite distribution in the Northern and Southern Hemispheres (with a predominant pattern of warmer temperatures in the north and colder temperatures in the south). Additionally, the typical patterns for both variables occur in January and July each year. The above study will provide reference and insights for future climate change prediction and adaptation efforts.

ObjectivesTo investigate the near-wall rotating cylindrical wake and hydrodynamic characteristics, flow around cylinder at typical gap ratios is investigated. MethodsA numerical simulation of flow around a near-wall rotating cylinder with different gap ratios (G/D = 0.2，0.8，1.4) and rotation rates at Reynolds number\begin{document}$Re = 200$\end{document} was carried out to compare the cylindrical wake and hydrodynamic characteristics at different gap ratios and rotation rates. ResultsThe results show that: For \begin{document}$G/D = 0.2$\end{document}, the cylindrical vortex shedding is significantly suppressed and the lift and drag force on the cylindrical surface remain steady. For \begin{document}$G/D = 0.8$\end{document} and \begin{document}$G/D = 1.4$\end{document}, at low rotation rates, the "wake vortex" is shed and is similar to the 2S pattern, with sinusoidal periodic fluctuations in the lift and drag coefficients and small amplitude; at higher positive rotation rates, the cylindrical wake pattern is the stable D pattern with no vortex shedding (changing from D+ to D− pattern as the rotation rate increases), the "wake vortex layer" is separated from the "wall vortex layer", the "wall vortex" is shed multi-periodically, the lift and drag coefficients are fluctuating multi-periodically and the amplitude is increasing significantly; at higher reverse rotation rates, the cylindrical surface is wrapped by a positive boundary layer, with no vortex shedding and no fluctuations in lift and drag. ConclusionsThe results can provide a reference for the development of high efficient flow control technology.

In the context of the current rapid development of the financial market, how to establish an effective stock price index model to avoid investment risks and enhance investment returns for investors has become a subject of great concern. On this basis, a new method of stock price index prediction employing deep neural networks is investigated. This paper employs the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) technique to break down the time series of the stock index into its constituent Intrinsic Modal Functions (IMFs). According to the similarity of the values of Fuzzy Entropy (FE), the subsequence is reorganized to become a new sequence, which highlights the fluctuation state of the stock index at different frequencies and improves the forecasting efficiency. In terms of a forecasting method, the combination of Temporal Convolutional Network (TCN), Gated Recurrent Unit (GRU), and Convolutional Block Attention Module (CBAM) is used to forecast the reorganized subsequence, and the final forecast results are reconstructed to obtain the final prediction value. To further evaluate the performance of the proposed CEEMDAN-TCN-GRU-CBAM model, this paper selects four representative stock indices in emerging and developed markets while comparing them with the benchmark model. It uses four evaluation metrics to measure the model performance. The study shows that the proposed model outperforms other benchmark models has better robustness and universality, and has higher forecasting accuracy.

Submerged floating tunnel (SFT) may be subjected to sudden impact loads such as submarine and shipwreck. Besides the local damage caused by impact, the overall transient dynamic response may also affect its driving safety. Based on the dynamic impact finite element software, the full-length model and the locally truncated accurate model with solid element of the SFT are established respectively. By applying different spring stiffness constraints on the boundary of the truncated model, its first three modes are consistent with the full-length model, thus their dynamic characteristics are basically the same. The truncated model is further used to simulate the impact of a massive object on the SFT under different impact velocities, impact mass, impact angles and impact positions. The velocity and mass of the impact object have positive influences on the peak contact force, the displacement amplitude of the tube and the length of the damaged area. When the impact angle is perpendicular to the SFT tube, the contact force, displacement amplitude and the damaged area are the largest. The change of the impact position has little effect on the contact force and the damage area, but it will affect the distribution of displacement amplitude.

Objective:The mortality rate of primary brainstem hemorrhage (PBH) is high, and the optimal treatment of PBH is controversial. We used mixed reality navigation technology (MRNT) to perform brainstem hematoma puncture and drainage surgery in seven patients with PBH. We shared practical experience to verify the feasibility and safety of the technology.Method:We introduced the surgical procedure of brainstem hematoma puncture and drainage surgery with MRNT. From January 2021 to October 2022, we applied the technology to seven patients. We collected their clinical and radiographic indicators, including demographic indicators, preoperative and postoperative hematoma volume, hematoma evacuation rate, operation time, blood loss, deviation of the drainage tube target, depth of implantable drainage tube, postoperative complications, preoperative and 1-month postoperative GCS, etc.Result:Among seven patients, with an average age of 56.71 ± 12.63 years, all had underlying diseases of hypertension and exhibited disturbances of consciousness. The average evacuation rate of hematoma was 50.39% ± 7.71%. The average operation time was 82.14 ± 15.74 min, the average deviation of the drainage tube target was 4.58 ± 0.72 mm, and the average depth of the implantable drainage tube was 62.73 ± 0.94 mm. Among all seven patients, four patients underwent external ventricular drainage first. There were no intraoperative deaths, and there was no complication after surgery in seven patients. The 1-month postoperative GCS was improved compared to the preoperative GCS.Conclusion:It was feasible and safe to perform brainstem hematoma puncture and drainage surgery by MRNT. The technology could evacuate about half of the hematoma and prevent hematoma injury. The advantages included high precision in dual-plane navigation technology, low cost, an immersive operation experience, etc. Furthermore, improving the matching registration method and performing high-quality prospective clinical research was necessary.

Hydrologic models are a powerful tool to predict water-related natural hazards. Of all hydrologic models, CREST (Coupled Routing and Excess STorage) was developed to facilitate hydrologic sciences and applications across various spatial and temporal scales. The CREST model was the earliest implementation of a quasi-global flood model integrating remote-sensing data and is the first operational deployment of a real-time model in the National Weather Service functioning at flash flood scales across a continent. Since being published in 2011, the CREST model has been evolving to empower flood predictions and to inform water resources management practices. Moreover, the CREST model is convenient to couple with other models/schemes (e.g., weather forecast model, snowmelt model, land surface model, hydrodynamic model, groundwater model, landslide model, vector-based routing) for border practices of investigating water-related natural hazards. To date its 10th anniversary, more than 80 peer-reviewed journal articles that have used the CREST model are curated and reviewed from the aspects of model development, worldwide applications, and outreach to emerging regions. Finally, the future directions for the CREST model family are outlined in the hope of stimulating new research endeavors. A digital collection of CREST model family is archived online at https://crest-family.readthedocs.io/en/latest/.

Satellite and reanalysis precipitation estimates of high quality are widely used for hydrological modeling, especially in ungauged or data-scarce regions. To improve flood simulations by merging different precipitation inputs or directly merging streamflow outputs, this study comprehensively evaluates the accuracy and hydrological utility of nine corrected and uncorrected precipitation products (TMPA-3B42V7, TMPA-3B42RT, IMERG-cal, IMERG-uncal, ERA5, ERA-Interim, GSMaP, GSMaP-RNL, and PERSIANN-CCS) from 2006 to 2018 on a daily timescale using the Coupled Routing and Excess Storage (CREST) hydrological model in two flood-prone tributaries, the Beijiang and Dongjiang Rivers, of the Pearl River Basin, China. The results indicate that (1) all the corrected precipitation products had better performance (higher CC, CSI, KGE’, and NSCE values) than the uncorrected ones, particularly in the Beijiang River, which has a larger drainage area; (2) after re-calibration under Scenario II, the two daily merged precipitation products (NSCE values: 0.73–0.87 and 0.69–0.82 over the Beijiang and Dongjiang Rivers, respectively) outperformed their original members for hydrological modeling in terms of BIAS and RMSE values; (3) in Scenario III, four evaluation metrics illustrated that merging multi-source streamflow simulations achieved better performance in streamflow simulation than merging multi-source precipitation products; and (4) under increasing flood levels, almost all the performances of streamflow simulations were reduced, and the two merging schemes had a similar performance. These findings will provide valuable information for improving flood simulations and will also be useful for further hydrometeorological applications of remote sensing data.

Shocked phosphates can record the collisional history of asteroid parent bodies, according to texture-age relationships from microstructural observations and geochronological measurements of apatite and merrillite grains in the Chelyabinsk meteorite

In the data-driven era, the mining of financial asset information and the selection of appropriate assets are crucial for stable returns and risk control. Multifactor quantitative models are a common method for stock selection in financial assets, so it is important to select the optimal set of factors. Elastic Net, which combines the benefits of the L1 and L2 penalty terms, performs better at filtering features due to the complexity of the features in high-dimensional datasets than Lasso and Ridge regression. At the same time, the false discovery rate (FDR), which is important for making reliable investment decisions, is not taken into account by the current factor-selection methodologies. Therefore, this paper constructs the Knockoff Logistic regression Elastic Net (KF-LR-Elastic Net): combining Logistic regression with Elastic Net and using Knockoff to control the FDR of variable selection to achieve factor selection. Based on the selected factors, stock returns are predicted under Logistic regression. The overall model is denoted as Knockoff Logistic regression Elastic Net-Logistic regression (KL-LREN-LR). The empirical study is conducted with data on the CSI 300 index constituents in the Chinese market from 2016–2022. KF-LREN-LR is used for factor selection and stock-return forecasting to select the top 10 stocks and establish an investment strategy for daily position changing. According to empirical evidence, KF-LR-Elastic Net can select useful factors and control the FDR, which is helpful for increasing the accuracy of factor selection. The KF-LREN-LR forecast portfolio has the advantages of high return and controlled risk, so it is informative for optimizing asset allocation.

In sea surface salinity (SSS) retrieval using L-band passive radiometry, radiometer-independent ocean wind speed is needed as auxiliary data. Wind speed data from scatterometer and weather models are commonly used as auxiliary data in satellite SSS missions. This article's overarching goal is to explore the feasibility of incorporating the cyclone global navigation satellite system (CyGNSS) data into the SSS retrieval algorithm of the soil moisture active and passive (SMAP) mission over tropical and subtropical oceans. As a proof-of-concept study, empirical geophysical model functions in the retrieval algorithm are developed using the statistics of collocated SMAP, CyGNSS, and referenced buoys measurements. The SSS accuracy of CyGNSS-incorporated salinity retrieval is investigated against the SMAP SSS data product. Comparisons show that the proposed CyGNSS-incorporated retrieval algorithm improves the SSS accuracy by 0.1∼0.2 psu at low wind speed (

Small watersheds are ideal objects for studying the evolution of hydrological and water resources at small scales. Whether precipitation products can meet the runoff simulation of small watersheds is the main purpose of this study. With NOAA-CPC-US precipitation as a reference, in nine small watersheds of the United States, accuracy of the precipitation products such as PERSIANN, PERSIANN-CDR, TRMM-3B42V7, GPM-IMERG, StageIV, and ERA5 is analyzed. By driving the CREST hydrological model using these datasets, the runoff simulation effects were evaluated. Result shows the precipitation products match the NOAA-CPC-US from high to low in the order of StageIV, PERSIANN-CDR, GPM-IMERG, PERSIANN, ERA5, and finally TRMM-3B42 V7. These datasets have relatively low accuracy in the northern high latitude area and the western mountains, while accuracy is better in the central, southern, and eastern parts of the United States. In the runoff simulation effectiveness evaluation, the daily runoff of watersheds is simulated during the same verification period. The results show that: NOAA-CPC-US and StageIV have good simulation effect in small watersheds. In the northern and western United States, the PERSIANN, PERSIANN-CDR, GPM-IMERG, and ERA5 for runoff simulation should be used with caution. TRMM-3B42V7 is not suitable for runoff simulation in small watershed.

The investment, construction and operation management of gas storage have been highly valued by all levels of government departments and related enterprises in China since the 12 th Five-Year Plan.Recently, the investment and construction of gas storage have been rapidly developed.As the system and mechanism reform of natural gas industry steps into a critical period, it is necessary to sort out and summarize the relevant policies and regulations on gas storage issued by China in recent years and the research results of Chinese scholars.The time series logic of policy items was clarified according to the investment, construction and operation management policies and evolution of China's underground gas storage since 12 th Five-Year Plan.The research progress and main achievements of Chinese scholars on the working gas capacity, operation mode, unit investment and operation cost, gas storage pricing, economic assessment methods and parameters of underground gas storage at home and abroad were comprehensively summarized.In such special development period when the "three period superimposed" occurs in China's natural gas industry, in order to further improve the investment decision-making level, stimulate the motivation to invest and construct the underground gas storage, and improve the operation and management capability of gas storage, the main directions for subsequent policy setting, research and consultation works were put forward.

Objective: This systematic review aimed to assess the efficacy of adjuvant corticosteroids in managing patients with chronic subdural hematoma (CSDH) undergoing surgical intervention.Methods: We searched for eligible studies electronically on the databases of PubMed, Embase, and Google Scholar. The last date of the search was 15th Jun 2021. Outcomes were pooled to calculate risk ratios (RR) with 95% confidence intervals (CI).Results: Eleven studies were included. Four of them were randomized controlled trials (RCTs). Six studies reported data on good neurological outcomes but with variable definitions. Combining all studies, we noted no statistically significant difference in good neurological outcome with the use of adjuvant corticosteroids (RR: 0.91 95% CI: 0.74, 1.12 I2 = 92% p = 0.39). Similar results were obtained on subgroup analysis based on definition and study type. However, the use of adjuvant corticosteroids was associated with a significantly reduced risk of recurrence (RR: 0.51 95% CI: 0.40, 0.64 I2 = 0% p < 0.0001). The meta-analysis also demonstrated no statistically significant difference in mortality rates with the use of adjuvant corticosteroids (RR: 1.01 95% CI: 0.47, 2.21 I2 = 76% p = 0.97). The results did not differ between RCTs and non-RCTs. Limited studies reported data on complications, and pooled analysis indicated no significant increase in infectious, gastrointestinal, and neurological complications with the use of adjuvant corticosteroids.Conclusion: The use of corticosteroids with surgery for CSDH might be associated with a reduction in recurrence rate. However, corticosteroids do not improve functional outcomes or mortality rates. Future studies should assess the impact of different corticosteroid regimens on patient outcomes, and should use standardized reporting of neurological outcomes with uniform follow-up duration.

Abstract Flash floods, characterized by rapid, short‐duration, and high‐velocity flows, are the major causes of property damage and casualties worldwide. Flash flood warning is one of the key measures to prevent flash floods. Relying upon rain gage data and official statistics of flash flood events with casualties, this study proposes a new rainfall triggering index, β, defined as the ratio of accumulated rainfall to intraday rainfall, which effectively divides floods into events triggered by heavy intraday rainfall (0 < β ≤ 5) and those triggered by high cumulative rainfall (β > 5). Then, historical disaster events were used to evaluate the performance of the proposed index. Results reveal that: (1) when 0 < β ≤ 5, the intensity–duration (I–D) curve method is more desirable, and the simulation result has a high correlation coefficient (r = 0.95) with the measured result; (2) when β > 5, the rainfall triggering index (RTI) method is more suitable (r = 0.8); (3) the cumulative critical rainfall using the RTI method ranges from 50 to 400 mm. This paper stretches the thought of flash flood warning method and provides the reference for flood‐prone regions.

Soil moisture (SM) measurements from ground stations are often after quality control (QC) in the operational system, but the QC flags may not be reliable in some cases when precipitation events or manual watering happen. This study applies the triple collocation (TC) method to conduct a cross-evaluation of SM data from ERA5 reanalysis estimates, ESA-CCI estimates, and ~2000 ground stations across the China domain. The results show that all datasets can capture the spatial pattern of SM in China. TC-based correlation coefficient (CC) and root mean square error (RMSE) show that the station data have worse performance in western and central China. For most stations, TC-based CC is between 0.6~0.9, and TC-based RMSE is between 0.01~0.06 m3/m3. In addition, TC-based metrics show good agreement with the CC between precipitation and SM, indicating that these metrics can reflect the quality of station data. We further selected typical stations (e.g., CC ≤ 0.2, RMSE ≥ 0.06 m3/m3) to check the quality of the QC procedure. The comparison shows that TC-based metrics can better represent the actual quality for these stations compared to raw QC flags. This study indicates that TC has the potential to detect problematic stations and could be a supplement to traditional QC of station observations.

The precipitation phase (i.e., rain and snow) is important for the global hydrologic cycle and climate system. The objective of this study is to evaluate the precipitation-phase partitioning capabilities of remote sensing and reanalysis modeling methods on the global scale. Specifically, observation data from the National Centers for Environmental Prediction (NCEP) Automated Data Processing (ADP), from 2000 to 2007, are used to evaluate the rain–snow discrimination accuracy of the Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG) and the fifth-generation reanalysis product of the European Centre for Medium Range Weather Forecasts (ERA5). The results show that: (1) the ERA5 performs better than the IMERG at distinguishing rainfall and snowfall events, overall. (2) The ERA5 has high accuracy in all continents except for South America, while the IMERG performs well only in Antarctica and North America. (3) Compared with the IMERG, the ERA5 can more effectively capture snowfall events at high latitudes but shows worse performance at mid-low latitude regions. Both the IMERG and ERA5 have lower accuracy for rain–snow partitioning under heavy precipitation. Overall, the results of this study provide references for the application and improvement of global rain–snow partitioning products.

Due to its ubiquity in rock types and ability to accommodate a wide range of trace elements, apatite is widely used to interpret magmatic evolution and track volatile elements in hydrothermal systems. Volatile elements and Cl–O isotopes make apatite an ideal mineral with which to record the chemical and textural signatures of geological processes. This study describes a new analytical procedure to obtain the F, Cl, and S contents and Cl and O isotopes simultaneously using secondary ion mass spectrometry (SIMS) within ~10 min of analysis time for each spot. The analytical precision of δ18O (2 SD (standard deviation) ~0.30‰) and δ37Cl (2 SD ~0.20‰) has no obvious trade-off compared with ordinary SIMS analysis. The new protocol is time-efficient and, more importantly, ensures the consistency of data sources. A set of apatite standards with different uses were determined using this new method to provide a complete set of recommended values.

High-quality and high-resolution precipitation products are critically important to many hydrological applications. Advances in satellite remote sensing instruments and data retrieval algorithms continue to improve the quality of the operational precipitation products. However, most satellite products existing today are still too coarse to be ingested for local water management and planning purposes. Recent advances in deep learning algorithms enable the fusion of multi-source, high-dimensional data for statistical learning. In this study, we investigated the efficacy of an attention-based, deep convolutional neural network (AU-Net) for learning spatial and temporal mappings from coarse-resolution to fine-resolution precipitation products. The skills of AU-Net models, developed using combinations of static and dynamic predictors, were evaluated over a 3 × 3° study area in Central Texas, U.S., a region known for its complex precipitation patterns and low predictability. Three coarse-resolution satellite/reanalysis precipitation products, ERA5-Land (0.1°), TRMM (0.25°), and IMERG (0.1°), are used as part of the inputs, while the predictand is the 1-km PRISM data. Auxiliary predictors include elevation, vegetation index, and air temperature. The study period includes 18 years of data (2001–2018) at the monthly scale for training, validation, and testing. Results show that the trained AU-Net models achieve different degrees of success in downscaling the baseline coarse-resolution products, depending on the total precipitation, the accuracy of large-scale patterns captured by the baseline products, and the amount of information transferable from predictors. Higher precipitation rate tends to affect AU-Net model performance negatively. Use of the attention mechanism in the AU-Net models allows for infilling of multiscale features and generation of sharper images. Correction using gauge data, if there is any, can further improve the results significantly.

Abstract The relative effect of climate change and El Niño–Southern Oscillation (ENSO) is essential not only for understanding the hydrological mechanism over Jiangxi province in China but also for local water resources management as well as flood control. This study quantitatively researched in‐depth information on climate change in Jiangxi using the up‐to‐date “ground truth” precipitation and temperature data, the Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE, 1961–2015, 0.25°) data; analyzed the connections between ENSO and climate factors (including precipitation and temperature); and discussed the relationships between the ENSO and climate change. The main findings of this study were (1) during the period of 1961–2015, annual precipitation and temperature generally increased at a rate of 2.68 mm/year and 0.16 °C/10a, respectively; (2) the precipitation temporal trends have significant spatial differences. For example, the high precipitation increasing rates occurred in northern Jiangxi province in summer, while the large decreasing rates happened in most regions of Jiangxi province in spring; (3) an abrupt temperature change was detected around 1984, with general decreasing trends and increasing trends in 1961–1984 and 1984–2015, respectively; (4) ENSO had significant impacts on precipitation changes over Jiangxi province, for example; the El Niño events, beginning in April and May, were likely to enlarge the amounts of precipitation in the following summer, and the El Niño events beginning in October were likely to enlarge the precipitation amounts in the following spring and summer; and (5) the El Niño events, starting in the second half of the year, were likely to raise the temperature in the winter and the following spring. These findings would provide valuable information for better understanding the climate change issues over Jiangxi province.

Extreme precipitation events (EPE) often cause catastrophic floods accompanied by serious economic losses and casualties. The latest version (V06) of the Integrated Multi-satellite Retrievals for Global Precipitation Measurement (GPM IMERG) provides global satellite precipitation data from 2000 at a higher spatiotemporal resolution with improved quality. It is scientifically and practically important to assess the accuracy of the IMERG V06 in capturing extreme precipitation. This study evaluates the two widely used products of IMERG during 2000–2018, i.e., IMERG late run (IMERG-L) and IMERG final run (IMERG-F), in the densely populated and flood-prone North China Plain. The accuracy of the IMERG V06 is evaluated with ground measurements from rain gauge stations at multiple scales (hourly, daily, and seasonally). A novel target tracking method is introduced to extract three-dimensional (3D) extreme precipitation events, and the near-real-time uncalibrated PERSIANN-CCS (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks Cloud Classification System) and GSMAP (Global Satellite Mapping of Precipitation) satellite data are added to further evaluate IMERG’s performance during extreme precipitation. Finally, for flash flood events induced by extreme rainfall in the Hebei Province from 15 to 23 July 2016, the accuracy of capturing the event with IMERG-F and IMERG-L was verified. Results reveal that IMERG-F is better than IMERG-L at all investigated scales (hourly, daily, and seasonally), but the difference between the two products is less at higher time resolutions. Both products manifest decreased performance when capturing 3D extreme precipitation events, and comparatively, IMERG-F performs better than IMERG-L. IMERG-F exhibits a distinct discontinuity in extreme precipitation thresholds between land and ocean, which is a limitation of IMERG-F not documented in previous studies. Moreover, IMERG-L and IMERG-F are comparable at an hourly scale for some metrics, which is beyond the expectation that IMERG-F is notably better than IMERG-L. This study provides a scientific basis for the performance of satellite precipitation products and contributes to guiding users when applying global precipitation products.

The Earth’s water cycle involves energy exchange and mass movement in the hydrosphere and thus sustains the dynamic balance of global hydrologic cycle. All water cycle variables on the Earth are closely interconnected with each other through the process of energy and water circulation. Observing, understanding and predicting the storage, movement, and quality of water remains a grand challenge for contemporary water science and technology, especially for researches across different spatio-temporal scales. The remote sensing observing platform has a unique advantage in acquiring complex water information and has already greatly improved observing, understanding, and predicting ability of the water cycle. Methods of obtaining comprehensive water cycle data are also expanded by new remote sensing techniques, and the vast amount of data has become increasingly available and thus accelerated a new Era: the Remote Sensing Big Data Study of Global Water Cycle. The element inversion, time and space reconstruction, and scale conversion are three key scientific issues for remote sensing water cycle in such Era. Moreover, it also presents a huge opportunity of capitalizing the combinations of Remote Sensing and Big Data to advance and improve the global hydrology and water security research and development, and uncork the new bottlenecks.

The mineral beryl (Be3Al2(SiO3)6) has the most abundant phase with industrial value for extracting a critical metal—beryllium. Due to multi-stage, fluid-induced growth, individual beryl grains may yield complex geochemical records, revealing variations in the oxygen isotopes of the fluids from which they crystallize. Secondary ion mass spectrometry (SIMS) with high sensitivity and high spatial resolution represents a good tool for in situ isotopic analysis. SIMS oxygen analyses require matrix-matched reference materials to calibrate instrumental mass fractionations during measurement. In this work, the oxygen isotope homogeneities of six beryl samples with different compositions (BS1, BS2, BS3, BS4, BS5, and BS6) were documented by SIMS. These samples’ recommended oxygen isotope compositions were characterized by laser fluorination isotope ratio mass spectrometry (IRMS). This study suggests that there is no matrix effect related to composition variation in beryl SIMS oxygen isotope analysis. The recommended δ18O values of the four reference materials, BS1, BS2, BS4, and BS5, were 15.01 ± 0.34‰ (2 standard deviations, 2 SD), 7.53 ± 0.16‰ (2 SD), 2.38 ± 0.14‰ (2 SD), and 10.72 ± 0.44‰ (2 SD), respectively. Therefore, BS1, BS2, BS4, and BS5 are recommended as suitable reference materials for in situ mineral beryl oxygen isotope microanalysis.

A two-dimensional numerical model for solving the Navier–Stokes equations was developed to investigate the local scour around a submarine pipeline with a spoiler. Both the suspended load and the bed load were considered in the present numerical model. The focus of the present study is to investigate the effects of the spoiler length on the hydrodynamic forces on the pipeline and the spoiler as well as the local scour around the submarine pipeline. The corresponding numerical results show that the mean drag coefficients of the pipeline and the spoiler increase with the increase of the spoiler length. As for the mean lift coefficient, a general decreasing trend with the increasing spoiler length is observed for the pipeline. However, the mean lift coefficient of the spoiler first increases and then decreases with the increasing spoiler length. In addition, it is found that a larger spoiler length leads to a deeper scour depth, and an empirical equation was proposed for predicting the non-dimensional scour depth of submarine pipelines with non-dimensional spoiler length based on the numerical results.

NASA’s Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG) is a major source of precipitation data, having a larger coverage, higher precision, and a higher spatiotemporal resolution than previous products, such as the Tropical Rainfall Measuring Mission (TRMM). However, there rarely has been an application of IMERG products in flash flood warnings. Taking Yunnan Province as the typical study area, this study first evaluated the accuracy of the near-real-time IMERG Early run product (IMERG-E) and the post-real-time IMERG Final run product (IMERG-F) with a 6-hourly temporal resolution. Then the performance of the two products was analyzed with the improved Rainfall Triggering Index (RTI) in the flash flood warning. Results show that (1) IMERG-F presents acceptable accuracy over the study area, with a relatively high hourly correlation coefficient of 0.46 and relative bias of 23.33% on the grid, which performs better than IMERG-E; and (2) when the RTI model is calibrated with the gauge data, the IMERG-F results matched well with the gauge data, indicating that it is viable to use MERG-F in flash flood warnings. However, as the flash flood occurrence increases, both gauge and IMERG-F data capture fewer flash flood events, and IMERG-F overestimates actual precipitation. Nevertheless, IMERG-F can capture more flood events than IMERG-E and can contribute to improving the accuracy of the flash flood warnings in Yunnan Province and other flood-prone areas.

Quantifying uncertainties of precipitation estimation, especially in extreme events, could benefit early warning of water-related hazards like flash floods and landslides. Rain gauges, weather radars, and satellites are three mainstream data sources used in measuring precipitation but have their own inherent advantages and deficiencies. With a focus on extremes, the overarching goal of this study is to cross-examine the similarities and differences of three state-of-the-art independent products (Muti-Radar Muti-Sensor Quantitative Precipitation Estimates, MRMS; National Center for Environmental Prediction gridded gauge-only hourly precipitation product, NCEP; Integrated Multi-satellitE Retrievals for GPM, IMERG), with both traditional metrics and the Multiplicative Triple Collection (MTC) method during Hurricane Harvey and multiple Tropical Cyclones. The results reveal that: (a) the consistency of cross-examination results against traditional metrics approves the applicability of MTC in extreme events; (b) the consistency of cross-events of MTC evaluation results also suggests its robustness across individual storms; (c) all products demonstrate their capacity of capturing the spatial and temporal variability of the storm structures while also magnifying respective inherent deficiencies; (d) NCEP and IMERG likely underestimate while MRMS overestimates the storm total accumulation, especially for the 500-year return Hurricane Harvey; (e) both NCEP and IMERG underestimate extreme rainrates (>= 90 mm/h) likely due to device insensitivity or saturation while MRMS maintains robust across the rainrate range; (g) all three show inherent deficiencies in capturing the storm core of Harvey possibly due to device malfunctions with the NCEP gauges, relative low spatiotemporal resolution of IMERG, and the unusual “hot” MRMS radar signals. Given the unknown ground reference assumption of MTC, this study suggests that MRMS has the best overall performance. The similarities, differences, advantages, and deficiencies revealed in this study could guide the users for emergency response and motivate the community not only to improve the respective sensor/algorithm but also innovate multidata merging methods for one best possible product, specifically suitable for extreme storm events.

Low accuracy and coarse spatial resolution are the two main drawbacks of satellite precipitation products. Therefore, calibration and downscaling are necessary before these products are applied. This study proposes a two-step framework to improve the accuracy of satellite precipitation estimates. The first step is data merging based on optimum interpolation (OI), and the second step is downscaling based on geographically weighted regression (GWR); therefore, the framework is called OI-GWR. An Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) (IMERG) product is used to demonstrate the effectiveness of OI-GWR in the Tianshan Mountains, China. First, the original IMERG precipitation data (OIMERG) are merged with rain gauge data using the OI method to produce corrected IMERG precipitation data (CIMERG). Then, using CIMERG as the first guess and the normalized difference vegetation index (NDVI) as the auxiliary variable, GWR is utilized for spatial downscaling. The two-step OI-GWR method is compared with several traditional methods, including GWR downscaling (Ori_GWR) and spline interpolation. The cross-validation results show that (1) the OI method noticeably improves the accuracy of OIMERG, and (2) the 1-km downscaled data obtained using OI-GWR are much better than those obtained from Ori_GWR, spline interpolation, and OIMERG. The proposed OI-GWR method can contribute to the development of high-resolution and high-accuracy regional precipitation datasets. However, it should be noted that the method proposed in this study cannot be applied in regions without any meteorological stations. In addition, further efforts will be needed to achieve daily- or hourly-scale downscaling of precipitation.

The performance of the latest released Integrated Multi-satellitE Retrievals for GPM mission (IMERG) version 5 (IMERG v5) and the TRMM Multisatellite Precipitation Analysis 3B42 version 7 (3B42 v7) are evaluated and compared at multiple temporal scales over a semi-humid to humid climate transition area (Huaihe River basin) from 2015 to 2017. The impacts of rainfall rate, latitude and elevation on precipitation detection skills are also investigated. Results indicate that both satellite estimates showed a high Pearson correlation coefficient (r, above 0.89) with gauge observations, and an overestimation of precipitation at monthly and annual scales. Mean daily precipitation of IMERG v5 and 3B42 v7 display a consistent spatial pattern, and both characterize the observed precipitation distribution well, but 3B42 v7 tends to markedly overestimate precipitation over water bodies. Both satellite precipitation products overestimate rainfalls with intensity ranging from 0.5 to 25 mm/day, but tend to underestimate light (0–0.5 mm/day) and heavy (>25 mm/day) rainfalls, especially for torrential rains (above 100 mm/day). Regarding each gauge station, the IMERG v5 has larger mean r (0.36 for GPM, 0.33 for TRMM) and lower mean relative root mean square error (RRMSE, 1.73 for GPM, 1.88 for TRMM) than those of 3B42 v7. The higher probability of detection (POD), critical success index (CSI) and lower false alarm ratio (FAR) of IMERG v5 than those of 3B42 v7 at different rainfall rates indicates that IMERG v5 in general performs better in detecting the observed precipitations. This study provides a better understanding of the spatiotemporal distribution of accuracy of IMERG v5 and 3B42 v7 precipitation and the influencing factors, which is of great significance to hydrological applications.

Probable Maximum Precipitation (PMP) is an essential prerequisite in designing dams, spillways, and reservoirs in order to minimize the risk of overtopping infrastructure collapse, especially under today’s changing climate. This study investigates conventional PMP estimation approach by using both scarce in-situ observations and mainstream satellite precipitation products in the Dadu River basin, where plenty of reservoirs and dams are being built. The satellite data include Climate Prediction Center (CPC) MORPHing algorithm (CMORPH), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), and Tropic Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42V7. The evaluation of satellite products shows that CMORPH and 3B42V7 agree well with gauge-based dataset for the period of 1998–2013 at both the grid and basin scales, also capturing the extreme precipitation events, with high Correlation Coefficients (CC) in terms of 0.68 and 0.71, respectively. Also, CMORPH and 3B42V7 show better performance for the magnitude and spatial distribution of 24-h PMP in such complex terrains. PERSIANN-CDR shows an overestimation in the upstream and an underestimation in the downstream. As among the first studies of satellite precipitation-based PMP estimation, this work sheds lights on the suitability of satellite precipitation in PMP estimation and could provide a reference for future extended spatially-distributed PMP estimation in vast ungauged regions.

Spaceborne precipitation radars are powerful tools used to acquire adequate and high-quality precipitation estimates with high spatial resolution for a variety of applications in hydrological research. The Global Precipitation Measurement (GPM) mission, which deployed the first spaceborne Ka- and Ku-dual frequency radar (DPR), was launched in February 2014 as the upgraded successor of the Tropical Rainfall Measuring Mission (TRMM). This study matches the swath data of TRMM PR and GPM DPR Level 2 products during their overlapping periods at the global scale to investigate their similarities and DPR’s improvements concerning precipitation amount estimation and type classification of GPM DPR over TRMM PR. Results show that PR and DPR agree very well with each other in the global distribution of precipitation, while DPR improves the detectability of precipitation events significantly, particularly for light precipitation. The occurrences of total precipitation and the light precipitation (rain rates < 1 mm/h) detected by GPM DPR are ~1.7 and ~2.53 times more than that of PR. With regard to type classification, the dual-frequency (Ka/Ku) and single frequency (Ku) methods performed similarly. In both inner (the central 25 beams) and outer swaths (1–12 beams and 38–49 beams) of DPR, the results are consistent. GPM DPR improves precipitation type classification remarkably, reducing the misclassification of clouds and noise signals as precipitation type “other” from 10.14% of TRMM PR to 0.5%. Generally, GPM DPR exhibits the same type division for around 82.89% (71.02%) of stratiform (convective) precipitation events recognized by TRMM PR. With regard to the freezing level height and bright band (BB) height, both radars correspond with each other very well, contributing to the consistency in stratiform precipitation classification. Both heights show clear latitudinal dependence. Results in this study shall contribute to future development of spaceborne radar precipitation retrievals and benefit hydrological and meteorological research.

The coupled routing and excess storage (CREST) distributed hydrological model has been applied regionally and globally for years. With the development of remote sensing, requirements for data assimilation and integration have become new challenges for the CREST model. In this paper, an improved CREST model version 3.0 (Tsinghua University and China Institute of Water Resources and Hydropower Research, Beijing, China) is proposed to enable the use of remotely-sensed data and to further improve model performance. Version 3.0 model’s runoff generation, soil moisture, and evapotranspiration based on three soil layers to make the CREST model friendly to remote sensing products such as soil moisture. A free water reservoir-based module which separates three runoff components and a four mechanism-based cell-to-cell routing module are also developed. Traditional CREST and CREST 3.0 are applied in the Ganjiang River basin, China to compare their simulation capability and applicability. Research results indicate that CREST 3.0 outperforms the traditional model and has good application prospects in data assimilation, flood forecasting, and water resources planning and management applications.

Satellite-based precipitation estimates products, CMORPH and PERSIANN-CCS, were evaluated with a dense rain gauge network over Beijing and adjacent regions for an extremely heavy precipitation event on July 21 2012. CMORPH and PEERSIANN-CSS misplaced the region of greatest rainfall accumulation, and failed to capture the spatial pattern of precipitation, evidenced by a low spatial correlation coefficient (CC). CMORPH overestimated the daily accumulated rainfall by 22.84% while PERSIANN-CCS underestimated by 72.75%. In the rainfall center, both CMORPH and PERSIANN-CCS failed to capture the temporal variation of the rainfall, and underestimated rainfall amounts by 43.43% and 87.26%, respectively. Based on our results, caution should be exercised when using CMORPH and PERSIANN-CCS as input for monitoring and forecasting floods in Beijing urban areas, and the potential for landslides in the mountainous zones west and north of Beijing.

Biogeography-based optimization (BBO) is a new effective population optimization algorithm based on the biogeography theory with inherently insufficient exploration capability. To address this limitation, we proposed a modified BBO with local search mechanism (denoted as MLBBO). In MLBBO, a modified migration operator is integrated into BBO, which can adopt more information from other habitats, to enhance the exploration ability. Then, a local search mechanism is used in BBO to supplement with modified migration operator. Extensive experimental tests are conducted on 27 benchmark functions to show the effectiveness of the proposed algorithm. The simulation results have been compared with original BBO, DE, improved BBO algorithms, and other evolutionary algorithms. Finally, the performance of the modified migration operator and local search mechanism are also discussed.

Numerical simulations were performed in this paper to investigate an elastically mounted circular cylinder subjected to vortex-induced vibration (VIV). A three-step finite element method (FEM) is introduced for solving the incompressible fluid flow equations in two dimensions. The computational procedure is coupled with a mesh movement scheme by use of the arbitrary Lagrangian-Eulerian (ALE) formulation on account of the body motion in the flow field. On running the numerical simulations, the Reynolds number was kept constant of Re = 100 and the reduced velocity U r = U /( f n D ) was varied from 3.0 to 10.2 by changing the natural frequency f n of the cylinder. The mass ratio m * = 4m/ρπD 2 and damping ratio ξ are set to be 10.0 and 0.01, respectively, where U is free-stream velocity, D the diameter of the circular cylinder, m the mass of the cylinder per unit length, and ρ the density of the fluid. Numerical results are examined for the response amplitude of transverse direction as well as the phase angle, φ, between the lift force and the transverse displacement of the cylinder. The numerical results reveal that the transverse amplitudes present only two branches, namely, initial branch and lower branch, rather than three branches as the results obtained from high-Re experiments with low m ∗ ξ. On the other hand, the phase angles present almost linear increase with the reduced velocity in the synchronization region. However, experiments concerned with high Re exhibit a sudden jump in phase angle of approximate 180 ∘ . The difference between the present study and the high-Re experiment is attributed to no substantial vortex shedding mode transition at the present numerical results of laminar flow.

The performance of Day-1 Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM) mission (IMERG) and its predecessor, the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis 3B42 Version 7 (3B42V7), was cross-evaluated using data from the best-available hourly gauge network over the Tibetan Plateau (TP). Analyses of three-hourly rainfall estimates in the warm season of 2014 reveal that IMERG shows appreciably better correlations and lower errors than 3B42V7, though with very similar spatial patterns for all assessment indicators. IMERG also appears to detect light rainfall better than 3B42V7. However, IMERG shows slightly lower POD than 3B42V7 for elevations above 4200 m. Both IMERG and 3B42V7 successfully capture the northward dynamic life cycle of the Indian monsoon reasonably well over the TP. In particular, the relatively light rain from early and end Indian monsoon moisture surge events often fails to be captured by the sparsely-distributed gauges. In spite of limited snowfall field observations, IMERG shows the potential of detecting solid precipitation, which cannot be retrieved from the 3B42V7 products.

A predator-prey model with disease in prey, Ivlev-type functional response, and impulsive effects is proposed. By using Floquet theory and small amplitude perturbation skill, sufficient conditions of the existence and global stability of susceptible pest-eradication periodic solution are obtained. By impulsive comparison theorem, conditions ensuring the permanence of the system are established. Examples and simulation are given to show the complex dynamics for the key parameters.

The flow-induced vibrations (FIVs) of two identical tandem square cylinders with mass ratio m*=3.5 at Reynolds number Re=150 are investigated through two-dimensional direct numerical simulation (DNS) and linear stability analysis over a parameter range of spacing ratio 1.5=L*=5 and reduced velocity 3=Ur =34. Three kinds of FIV responses, namely vortex-induced vibration (VIV), biased oscillation (BO) and galloping (GA), are identified. The FIVs are then further classified into the branches of initial VIV (IV), resonant VIV (RV and RV'), flutter-induced VIV (FV), desynchronized VIV (DV), VIV developing from GA (GV), transitional state between VIV and GA (TR), BO and GA based on the characteristics of the vibration responses. The transitions among different FIV branches are examined by combining the DNS with linear stability analysis, where the transition boundaries among the VIV, BO and GA branches over the concerned parameters are identified on the branch maps. The transition from IV to RV or RV' is found to be related to the unstable wake mode, while the FV, transiting from RV or RV', is induced by the unstable structural factor in the wake-structure mode. The structural instability is considered as the physical origin of GA, whereas the mode competition between unstable wake and structure leads to DV, GV and TR, and thus delays the appearance of GA. The transition fromDV to BO with biased equilibrium position, accompanied by the even-order harmonic frequencies, is essentially induced by the symmetry breaking bifurcation. [ABSTRACT FROM AUTHOR]