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In statistical modeling, it is crucial to have consistent variables that are the most relevant to the outcome variable(s) of interest in the model. With the increasing richness of data from multiple sources, the size of the pool of potential variables is escalating. Some variables, however, could provide redundant information, add noise to the estimation, or waste the degrees of freedom in the model. Therefore, variable selection is needed as a parsimonious process that aims to identify a minimal set of covariates for maximum predictive power. This study illustrated the variable selection methods considered and used in the small area estimation (SAE) modeling of measures related to the proficiency of adult competency that were constructed using survey data collected in the first cycle of the PIAAC. The developed variable selection process consisted of two phases: phase 1 identified a small set of variables that were consistently highly correlated with the outcomes through methods such as correlation matrix and multivariate LASSO analysis; phase 2 utilized a k-fold cross-validation process to select a final set of variables to be used in the final SAE models.

Rainfall data, as an important input data, its temporal and spatial resolution directly affects the accuracy of watershed hydrological simulations. Weather radar has been used in business in China, but the uncertainty of radar rainfall data is large, so the two-source rainfall data fusion based on radar and rainfall stations has become an important method to obtain rainfall data with high resolution. In this paper, taking Duanzhuang watershed in the eastern foot of Taihang Mountain for example, based on the data of 18 rainfall stations in the basin and Shijiazhuang’s S-band radar data, the radar data are preprocessed, initially optimized (overall optimization and subsection optimization) and evaluated. Then 11 rainfalls in this basin are selected by three fusion methods for fusion and quality evaluation. The results show that the pre-processed radar rainfall data and the preliminarily optimized radar rainfall data have poor effects in rainfall spatial estimation This indicates that single-source radar data cannot be directly used to describe rainfall events. Among the three fusion algorithms, the rainfall proportional coefficient fusion method (q_k method) is the best, the optimal interpolation method is the second, and the mixed geographically weighted regression-gaussian function (MGWR-GAU) fusion algorithm is the worst under the conditions of spatial and temporal variation of rainfall and different station densities. In the case of q_k method, the correlation coefficients of the three inspection stations are increased to 0.51, 0.78 and 0.82 on the point scale, and to 0.98 on the basin area scale, and the rainfall changes smoothly in time and space.It shows this method can effectively improve the data accuracy of weather radar, and it is an important fusion method to obtain high temporal and spatial resolution rainfall data in the watershed.

Zn powder (Zn-P)-based anodes are always regarded as ideal anode candidates for zinc ion battery owing to low-cost and ease of processing. However, the intrinsic negative properties of Zn-P-based anodes such as easy corrosion and uncontrolled dendrite growth have limited their further applications. Herein, a novel 3D cold-trap environment printing (3DCEP) technology is proposed to achieve the MXene and Zn-P (3DCEP-MXene/Zn-P) anode with highly ordered arrangement. Benefitting from the unique inhibition mechanism of high lattice matching and physical confinement effects within 3DCEP-MXene/Zn-P anode, it can effectively homogenize the Zn

In this work, we demonstrate the performance of a silicon-compatible, high-performance, and self-powered photodetector. A wide detection range from visible (405 nm) to near-infrared (1550 nm) light was enabled by the vertical p-n heterojunction between the p-type antimony telluride (Sb

The Wuqing urban section of the North Canal Basin, Tianjin, is a significant gathering place for multisource pollution, showing the characteristics of a stagnant water body supplied by unconventional water sources. With the development of the economy and society, the water quality of the Wuqing urban section of the North Canal Basin, Tianjin, has been seriously polluted due to the discharge of sewage outlets and the influx of nonpoint source pollution from farmland. In this study, based on the results of special water experiments, a two-dimensional hydrodynamic water quality model was constructed. The concentrations of ammonia nitrogen (NH3-N), total phosphorus (TP), and chemical oxygen demand (COD) in the study area were simulated, and the model parameters were calibrated and verified with the measured values. Based on the model verification, the water quality improvement scheme of the ecological floating bed with different plant ratios was set up to simulate the water quality. The research results showed that the average concentrations of NH3-N, TP, and COD decreased by 10.4%, 15.7%, and of d 26.3%, respectively, after the ecological floating bed was arranged. During model parameter calibration and validation, the RMSE ranges of NH3-N, TP, and COD were 0.09~0.22 mg/L, 0.00~0.02 mg/L, and 0.37~2.42 mg/L, respectively. Other statistical indicators are also within a reasonable range, and the model accuracy and reliability are high. The simulation results of different scenarios showed that the optimal ratio of ecological floating bed plants was 700 m2 of Scirpus validus Vahl and 700 m2 of Canna in zone 1 of the floating bed combination, 430 m2 of Scirpus validus Vahl, and 170 m2 of Iris in zone 2 of the floating bed combination, and 200 m2 of Iris and 200 m2 of Lythrum salicaria in zone 3 of the floating bed combination. This study can provide a theoretical basis for the sustainable development of water purification in the North Canal. It can also provide a model approach for the implementation of river water purification schemes, exemplified by the North Canal.

Hydrological models are a conceptual representation of a simplified hydrological cycle. The hydrological cycle is the water cycle that circulates water from the land surface to the atmosphere and back again to the land. With the use of Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS), an event-based model and a continous hydrological model were established in Zijinguan watershed of Daqinghe River basin. To study the loss methods provided by HEC-HMS and its appropriateness for model fitting, is the main objective of this paper. The watershed was delineated with HEC-GeoHMS in ArcGIS, and its properties were extracted from a Digital Elevation Model (DEM) of 30 m × 30 m. The HEC-HMS includes a soil conservation service curve number (SCS-CN) method and a soil moisture calculation (SMA) loss method, simulating the event and continuous runoff, respectively. SCS Unit hydrograph and Muskingum were used for flow routing. Specifically, eight rainfall events were selected for calibrating (6 events) and verifying (2 events) the event-based model. Similarly, for the continuous model the wet seasons of eight different years were used for calibration and verification. The calibrated parameters of the events model were used in the continuous model. The soil moisture and evapotranspiration data were decoded from the satellite data to set in the continuous model. The performance of SCS-CN and SMA models was compared. During the calibration period, the values of NSE, PEV and PEPF range from 0.605 to 0.744, 3.1 to 13.58%, and 11.104 to 27.72%, and during validation they are 0.527 to 0.634, 4.35% to 5.01%, and 13.66% to 27.88%, for SCS-CN model. For the SMA model, the values of NSE, PEV and PEPF during calibration range from 0.434 to 0.604, 2.879 to 34.326%, −4.831 to 57.48%, and during validation they are 0.094 to 0.624, −19.52% to −12.55%, and 40.213% to 50.15%. Overall, the performance of SCS-CN model is found more satisfactory than that of SMA model.

Flood scaling theory is important for flood predictions in data-scarce regions but is often applied to quantile-based floods that have no physical mechanisms. In this study, we propose a framework for flood prediction in data-scarce regions by event-based flood scaling. After analyzing the factors controlling the flood scaling, flood events are first simulated by a hydrological model with different areally averaged rainfall events and curve number (CN) values as inputs, and the peak discharge of each subcatchment is obtained. Then, the flood scaling is analyzed according to the simulated peak discharge and subcatchment area. Accordingly, the relationship curves between the scaling exponent and the two explanatory factors (rainfall intensity and CN) can be drawn. Assuming that the flood and the corresponding rainfall event have the same frequency, the scaling exponent with a specific flood frequency can be interpolated from these curves. HIGHLIGHTS Hydrological modeling was used to conduct flood scaling analysis.; Rainfall intensity and curve number were identified to be the two main factors affecting flood scaling.; A framework of flood prediction by event-based flood scaling in data-scarce regions was proposed.

Drought is an important factor that limits economic and social development due to its frequent occurrence and profound influence. Therefore, it is of great significance to make accurate predictions of drought for early warning and disaster alleviation. In this paper, SPEI-1 was confirmed to classify drought grades in the Guanzhong Area, and the autoregressive integrated moving average (ARIMA), random forest (RF) and support vector machine (SVM) model were established. Meteorological data and remote sensing data were used to derive the prediction models. The results showed the following. (1) The SVM model performed the best when the models were developed using meteorological data, remote sensing data and a combination of meteorological and remote sensing data, but the model's corresponding kernel functions are different and include linear, polynomial and Gaussian radial basis kernel functions, respectively. (2) The RF model driven by the remote sensing data and the SVM model driven by the combined meteorological and remote sensing data were found to perform better than the model driven by the corresponding other data in the Guanzhong Area. It is difficult to accurately measure drought with the single meteorological data. Only by considering the combined factors can we more accurately monitor and predict drought. This study can provide an important scientific basis for regional drought warnings and predictions. HIGHLIGHTS SPEI-1 was used to analyze the temporal distribution characteristics of drought and the main driving factors in Guanzhong Area, China.; Drought grades were selected as the dependent variable, and the meteorological, geographical and vegetative factors were selected as the independent variables to establish an autoregressive integrated moving average (ARIMA) model, random forest (RF) model and support vector machine model.; Meteorological data and remote sensing data were used as independent variables to derive prediction models, respectively.; Comparing the models driven by remote sensing data only and the combination of meteorological and remote sensing data, the RF model driven by the remote sensing data and the SVM model driven by the combined meteorological and remote sensing data were found to perform better than the model driven by the corresponding other data in Guanzhong Area.; This study can provide an important scientific basis for regional drought warning and prediction.

CaTiO3 microwave dielectric ceramic was fabricated utilizing traditional two-step sintering process. XRD pattern analysis after Rietveld refinement indicated a pure phase CaTiO3 sample. SEM image illustrated well-crystallized sample with uniform grain sizes and clear grain boundaries. The lattice vibrational characteristics were analyzed by Raman and IR spectroscopy, and the intrinsic properties were calculated in conjunction with the semi-quantum four-parameter (FPSQ) model, which turned out that the low-frequency vibrational modes contribute the most to the dielectric properties. Besides, the real and imaginary parts of the dielectric function were drawn from the FPSQ model. The intrinsic property results fitted from the FPSQ model agree well with the measured values.

Threshold level method is well-known for drought identification with the advantage of its simplicity. However, there is no criterion for classification of drought classes in this method. Therefore, a K index based on threshold level method was proposed and verified to perform well in drought assessment in the Luanhe River basin, China. Meteorological data and remote sensing data were used to calculate the net primary productivity (NPP) of the basin by the CASA model. Results showed that the model had a good performance in comparison with the downloaded yearly remote sensing NPP and monthly PsnNet. The NPP in the basin tended to increase slowly during the year of 2000–2010, and the NPP in the downstream was generally larger than upstream. In three selected representative drought years, drought reduced NPP by about 15–25%, and during the growth season, drought may reduce NPP by about 4.6%, 2.7%, and 1.9% in July, August, and September, respectively, due to reduced precipitation. NPP on grasslands and agricultural land were more susceptible to drought than forests. The result of gray incidence analysis showed that the effects of drought on NPP had a certain delay with about 5 months.

Initial abstraction (Ia) is a sensitive parameter in hydrological models, and its value directly determines the amount of runoff. Ia, which is influenced by many factors related to antecedent watershed condition (AWC), is difficult to estimate due to lack of observed data. In the Soil Conservation Service curve number (SCS-CN) method, it is often assumed that Ia is 0.2 times the potential maximum retention S. Yet this assumption has frequently been questioned. In this paper, Ia/S and factors potentially influencing Ia were collected from rainfall–runoff events. Soil moisture and evaporation data were extracted from GLDAS-Noah datasets to represent AWC. Based on the driving factors of Ia, identified using the Pearson correlation coefficient and maximal information coefficient, artificial neural network (ANN)-estimated Ia was applied to simulate the selected flood events in the Hydrologic Engineering Center Hydrologic Modeling System (HEC-HMS) model. The results indicated that Ia/S varies over different events and different watersheds. Over 75% of the Ia/S values are less than 0.2 in the two study areas. The driving factors affecting Ia vary over different watersheds, and the antecedent precipitation index appears to be the most influential factor. Flood simulation by the HEC-HMS model using statistical Ia gives the best fitness, whereas applying ANN-estimated Ia outperforms the simulation with median Ia/S. For over 60% of the flood events, ANN-estimated Ia provided better fitness in flood peak and depth, with an average Nash–Sutcliffe efficiency coefficient of 0.76 compared to 0.71 for median Ia/S. The proposed ANN-estimated Ia is physically based and can be applied without calibration, saving time in constructing hydrological models.

The characteristics of urban pluvial flooding are altering all over the world due to environmental change. In this paper, generalized additive models for location, scale and shape (GAMLSS) was employed to analyze nonstationary frequency of extreme precipitation at subdaily scale. Nonstationary precipitation return periods were estimated using the expected waiting time (EWT) interpretation. A model coupling SWMM and MIKE21 was established, and calibrated and verified by three historical urban floods. Then, it was utilized to simulate urban floods under stationary and nonstationary rainfall conditions with different return periods. The simulated results illustrated that rainfall depth under nonstationarity was greater than that of stationarity when return period was less than 10 years, but the results reversed when the return period was over 20 years. The main variation of rainfall depth occurred within 6 h. The deviation of the maximum water depth was less than 10% for five return levels, and the difference in the longest inundation lengths was 1.2 h for 50-year return period under two assumptions. It may indicate that slight differences of urban flooding were detected between stationary and nonstationary conditions in the study region, which suggested a further study about urban flood under nonstationarity.

The study of flood scaling is an important means to solve the problem of flood prediction in ungauged and poorly gauged basins. With the impact of climate change and human activities, the mechanism and process of floods are constantly changing. However, in many areas, there are only simple scaling results that can be used to guide daily work. Taking the Daqinghe River basin as an example, a fixed flood scaling exponent determined in 1974 (before the change point of 1979) is still used all over the basin, which is apparently no longer appropriate. Therefore, in this paper, we aim to explore: (1) the scale relationship between the peak flows and the basin area under changing environments; (2) the validation of the scale invariance theory; (3) the physical relationship between the event-based scaling theory and the annual flood quantile-based scaling theory in the mesoscale non-nested and partly nested basins; and (4) the modification of the existing uniform flood scaling exponent in the study area. To achieve these objectives, eight simultaneous observed flood events in seven non-nested and partly nested mesoscale sub-basins of the Daqinghe River basin were selected to analyze the flood scaling theory. The results showed that there was a scaling relationship between the flood peaks and watershed area for the flood events, and the scale invariance theory was also supported herein. To analyze the effect of the environmental conditions on flood scaling in the Daqinghe River basin, the flood events were reconstructed after the change point (the year 1979). It was found that the flood scaling exponents of the reconstructed flood events are larger than those of the observed events after the change point. The flood scaling exponent changed with flood events, varying from 0.65 to 1.26 when considering the basin area as the independent variable, and decreasing with a minimum of 0.36 when taking the rainfall characteristics into consideration. It was also found that the mean of the event-based scaling exponents is larger than the annual flood quantile-based scaling exponents.

Global climate change and rapid urbanization have caused increases in urban floods. Urban flood risk assessment is a vital method for preventing and controlling such disasters. This paper takes the central region of Cangzhou city in Hebei Province as an example. Detailed topographical information, such as the buildings and roads in the study area, was extracted from GF-2 data. By coupling the two models, the SWMM and MIKE21, the spatial distribution of the inundation region, and the water depth in the study area under different return periods, were simulated in detail. The results showed that, for the different return periods, the inundation region was generally consistent. However, there was a large increase in the mean inundation depth within a 10-to-30-year return period, and the increase in the maximum inundation depth and inundation area remained steady. The comprehensive runoff coefficient in all of the scenarios exceeded 0.8, indicating that the drainage system in the study area is insufficient and has a higher flood risk. The flood risk of the study area was evaluated based on the damage curve, which was obtained from field investigations. The results demonstrate that the loss per unit area was less than CNY 250/m2 in each return period in the majority of the damaged areas. Additionally, the total loss was mainly influenced by the damaged area, but, in commercial areas, the total loss was highly sensitive to the inundation depth.

Many drought forecasting methods have been proposed, but only a few have considered the changing environment. The main purpose of this study is to improve the accuracy of drought forecasting models under changing environments by considering the influence of large-scale climate patterns and human activities on hydrological drought. To select the most significant large-scale climatic index that influences drought events in the Luanhe River basin, Spearman’s rho correlation test was applied to detect the relationship between large-scale oceanic–atmospheric circulation patterns and the standardized runoff index (SRI). We also proposed a human activity index (HI) to represent the effect of human activities on hydrological drought. Based on a multivariate normal distribution, we included the above indices in a probabilistic forecasting model, which forecasted the probabilities of transition from the current to a future SRI value. Using the Liying hydrological station as an example, the impacts of a controlled large-scale climatic index (Niño-3.4) and the HI on the transition probabilities were illustrated, and the results showed that the turning point of the Niño-3.4 effect on the transition probabilities occurred within the range from 25.91 to 26.90. Finally, a scoring method was applied to compare the forecasting model performances. The results showed that the inclusion of the large-scale climatic index and HI improved the forecasting accuracy.

Flood scaling issue is usually studied under stationary conditions. However, in recent decades, climate change and anthropogenic activities have changed hydrological processes, and stationary assumption has been questioned. To test the flood scaling invariance (simple scaling or multiscaling) and analyze the influence of environmental change on flood scaling parameter, in this study, eight mesoscale sub-watersheds in Daqinghe River basin were selected as the study area, and the trend and change point of annual maximum flood peak (AMFP) series were detected, respectively. All the AMFP series had downward trend, and the change point was around 1979. Therefore, the AMFP series are nonstationary. To analyze the flood scaling issue in the Daqinghe River basin, the AMFP series were reconstructed under the environmental conditions before and after the change point, respectively. Then, flood quantiles were calculated using the reconstructed stationary series. We also used GAMLSS (Generalized Additive Model in Location, Scale and Shape) to calculate flood quantiles based on the observed nonstationary AMFP series. According to the flood quantiles calculated by the above methods, the relationship of the drainage areas of the sub-watersheds and the flood quantiles was fitted with power function. Flood quantiles of the reconstructed stationary and observed nonstationary series showed obvious flood multiscaling. The increase in rainfall depth causes the increase in flood scaling exponents with the increase in return period, and different change ratios of land use before and after change point resulted in the flood scaling exponents of reconstructed series before 1979 were smaller than those after the change point at same return period.

Black phosphorus (BP) with a layered structure is the most stable allotrope of phosphorus, which was first prepared under high pressure in 1914. Since the development of a field-effect transistor with BP in 2014, BP has drawn interest, exhibiting numerous superior properties, such as distinct pleated structures in layers, an adjustable direct band gap, high carrier mobility, and many interesting in-layer anisotropies. This review summarizes the latest preparation techniques, properties, and applications of low-dimensional BP. Methods for the fabrication of two-dimensional BP include mechanical exfoliation, electrochemical assistance, and liquid exfoliation. The last method can also produce BPQDs by changing the process. In numerous excellent physical properties of BP, this review emphasizes its distinct anisotropy, including mechanical, thermally conductive, optical anisotropy, and so on. The potential uses of low-dimensional BP, involving field-effect transistors, photodetectors, catalysts, as well as photothermal therapeutic agents, are introduced in detail. The last application listed is closely associated with the health of human beings. To improve the stability of BP, its degradation mechanism with several fruitful protection methods is elaborated. Finally, the shortcomings in current research are discussed, and suggestions and prospects are proposed for the future research on low-dimensional BP.

Recently, the land surface in the Haihe River basin has changed, influencing the flood processes in the basin. To quantify this impact, seven typical sub-catchments were selected from different hyd...

Drought propagation is very significant for short-term drought forecast and water resources management. However, the law of drought propagation is still unclear, especially with human activities. In this study, we calibrated and validated the SWAT model in the Luanhe River basin controlled by the Luanxian hydrological station, where there are three large reservoirs upstream and water diversion to Tianjin city. The variable threshold level (VTL) method was employed to identify meteorological and hydrological events both under natural and reservoir-influenced conditions. Drought occurred more frequently, drought duration became longer, and drought deficit became larger with the influence of reservoir regulation and water diversion to Tianjin city. The lag time of hydrological drought onset was shorter and termination longer, i.e., the drought period was more persistent. Multiple regression was used to establish the relations between hydrological drought and the driving factors both under natural and reservoir-influenced conditions. The coefficient of determination is high enough to explain drought propagation. The driving factors were different under the two conditions. The results could provide valuable information for water resource managers.

La(Mg1/2Sn1/2)O3 (LMS) ceramic was synthesized via the conventional solid-state reaction method. The main phase of the sample is LMS with a double perovskite structure (monoclinic P121/n1 symmetry), which is confirmed by X-ray diffraction. Scanning electron microscopy shows the sample is well-crystallized with dense and uniform grains as well as clear grain boundaries. The Raman scattering and Fourier transform far-infrared reflection spectroscopies were employed to analyze the lattice vibrational modes of the sample. The Raman active modes were fitted by the Lorentz function, and the lattice vibrational modes were assigned and illustrated accurately. The four-parameter semiquantum model was applied to simulate the intrinsic dielectric properties, which agree well with the data calculated from the microscopic polarizability & damping angles. The A1g(La) Raman mode in A-site has a great impact on the dielectric loss, and F3u(2) mode makes the largest contribution to the dielectric constant and the dielectric loss. Keywords: Microwave dielectric ceramic, Double perovskite, Crystal structures, Intrinsic dielectric properties, Vibration characteristics

It is critical to assess drought risk probability based on a really spatio-temporal continuum identification and characterization method, which is of great importance for drought resistance, planning, and management of water resource as well as agricultural production. Therefore, the major motivation of this study is to identify and characterize hydrological drought events in a three-dimensional framework and further assess the potential drought risk probability in a multivariate framework in the Luanhe River basin during 1961–2011. The study adopts a really spatio-temporal continuum identification method to characterize drought, and copula functions for multivariate risk probability assessment of hydrological drought. First, the Soil and Water Assessment Tool (SWAT) model is used to simulate the watershed runoff and the cubic spline interpolation method is used to obtain the gridded data sets. Second, the Standardized Runoff Index (SRI) and the three-dimensional identification method are employed to identify hydrological drought. Third, according to three drought parameters of drought severity (S), duration (D), and affect area (A), the marginal distribution, bivariate, and trivariate joint distribution are constructed, and the optimal ones are selected based on different evaluation methods of goodness-of-fit. Fourth, based on the derived marginal and joint distributions, drought risk probability is fully assessed. Results indicate that: (1) SWAT model is a reliable tool to simulate the watershed hydrologic processes; (2) the three-dimensional identification method used in this study is robust and efficient; (3) the optimal marginal distributions for S, D, and A are GEV, GEV, and lognormal distribution; the optimal bivariate copula function for S-D, S-A, and D-A are Joe, Gumbel, and Joe copula; and the optimal trivariate copula function for S-D-A is Nested Gumbel copula; (4) return periods of the first five most serious drought events are 80, 75, 46, 45, and 40 years, respectively; (5) to completely characterize the spatio-temporal variability of hydrological drought, it is necessary to completely consider the three characteristic variables of S, D, and A.

This study investigates the impacts of drought on water supply risk of Panjiakou reservoir in Luanhe River basin of China under environmental change by using a copula-based streamflow series generation approach. To understand how nonstationarity of runoff sequence influences water supply risk, reservoir performance metrics including reliability (time-based and volume-based), resilience, vulnerability, drought risk index (DRI), and sustainability index (SUI) are evaluated with 1956–1979 and 1980–2016 inflows of Panjiakou reservoir, respectively. The results indicated that the prolonged and severe drought may seriously affect the safety of water supply. From two results of generated streamflow time series, the reliability reduction rate reached 58.3% (0.773 to 0.322) when water supply assurance rate was 75% and ecological water level was minimum. Perturbing the copula parameter will make it possible to increase the drought durations and deficits for Panjiakou reservoir to analyze drought impacts on water supply. Based on the reservoir performance metrics, the analysis for Panjiakou reservoir showed that the trend of drought in the future made water supply reliability (time-based and volume-based), resilience, and SUI decrease, but vulnerability and DRI increase, which means the water supply system security became more vulnerable in the future. These results make it easy for decision makers to understand how drought influences future planning and management of Panjiakou reservoir.

BaMoO4 ceramic was prepared using a conventional solid-sintering method. It was observed that the sample is a pure BaMoO4 with a tetragonal scheelite structure by analyzing X-ray diffraction data. Scanning electron microscopy characterized the dense sample with uniform grains. The phonon modes were analyzed by Raman and Far-infrared reflection spectra, and the phonon characteristics were studied. The intrinsic properties of the sample were calculated by the four-parameter semi-quantum model as well as the Clausius-Mosotti & damping equations, and the results were of εr = 9.388 and tanδ = 4.760 × 10−4, εr = 9.798 and tanδ = 6.445 × 10−4, respectively, which agrees well with the experimental values (εr = 9.84, tanδ = 5.0 × 10−4). The contributions to dielectric properties of each mode were investigated, and the results indicate that the external mode (Eu) yield greatest contribution to intrinsic permittivity and loss. Keywords: Microwave dielectric ceramic, BaMoO4, Crystal structure, Dielectric properties, Phonon characteristics

Since the bias and uncertainties of the current design flood estimation methods for ungauged catchments are inevitable, estimation of the design flood in ungauged catchments still remains an unsolved problem. The derived distribution approach appears to be the one of the promising design flood estimation methods, as this method can improve the understanding on which processes contribute most to flood in ungauged catchments. Generally, the distribution of rainfall characteristics and lumped rainfall-runoff modelling was incorporated to estimate the flood magnitude in this method. However, we should note that rainfall is not the only driving factor of flood events. Soil moisture conditions are also an important driving factor affecting the rainfall-runoff transformation, and may even control rainfall-runoff coefficients to a higher degree than does rainfall. Hence, here we perform soil moisture analysis at national scale by employing GLDAS-Noah datasets, and link this to observed event runoff coefficients from a large sample of UK catchments. The relationship between soil moisture conditions and rainfall-runoff coefficient was explored to analyse the spatio-temporal variability of runoff coefficient. This study laid the foundation for further development of a practical derived distribution method, by considering the statistical distribution of rainfall-runoff coefficients and the influence of soil moisture conditions.

Runoff simulations are of great significance to the planning management of water resources. Here, we discussed the influence of the model component, model parameters and model input on runoff modeling, taking Hanjiang River Basin as the research area. Convolution kernel and attention mechanism were introduced into an LSTM network, and a new data-driven model Conv-TALSTM was developed. The model parameters were analyzed based on the Conv-TALSTM, and the results suggested that the optimal parameters were greatly affected by the correlation between the input data and output data. We compared the performance of Conv-TALSTM and variant models (TALSTM, Conv-LSTM, LSTM), and found that Conv-TALSTM can reproduce high flow more accurately. Moreover, the results were comparable when the model was trained with meteorological or hydrological variables, whereas the peak values with hydrological data were closer to the observations. When the two datasets were combined, the performance of the model was better. Additionally, Conv-TALSTM was also compared with an ANN (artificial neural network) and Wetspa (a distributed model for Water and Energy Transfer between Soil, Plants and Atmosphere), which verified the advantages of Conv-TALSTM in peak simulations. This study provides a direction for improving the accuracy, simplifying model structure and shortening calculation time in runoff simulations.

Evaluation of satellite-based quantitative precipitation estimates (QPEs) with reliable and independent ground-based measurements is important for both product developers and users. Here, we present a comprehensive evaluation on 3 high-resolution QPEs, namely, the Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS), the latest non-real-time post-processing version of Tropical Rainfall Measuring Mission (TRMM 3B42 V7), and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), in 3 basins with different climates in China. The accuracy of 3 QPEs in reproducing the spatial extent of daily and monthly precipitation (PR) as well as extreme PR indices was evaluated. Two simulation scenarios were utilized to evaluate the efficiency of hydrologic events forecasting of these 3 QPEs quantitatively. The results indicated that the 3 QPEs generally show high accuracy in estimating monthly PR in 3 basins, among which TRMM 3B42 V7 performs best (coefficient of determination R2

Flood frequency analysis for practical application is traditionally based on the assumption of stationarity, but this assumption has been open to doubt in recent years. A number of studies have focused on the nonstationary flood frequency analysis, and the associated causes of nonstationarity. In this study, the annual maximum flood peak and flood volume of Wangkuai reservoir watershed were used, and several univariate and bivariate models were established to investigate the nonstationary flood frequency, with the distribution parameters changing over the climate indices (NPO, Nino3) and the check dam indices (CDIp, CDIv). In the univariate models, the Weibull distribution performed best and exhibited an undulate behavior for both flood peak and volume, which tended to describe the nonstationarity reasonably well. The bivariate models were constructed using copulas, of which the optimal Weibull distribution in the univariate flood frequency analysis was considered as marginal distributions within the joint distribution. The results showed that the Gumbel-Hougaard copula offered the best joint distribution, and most of the probability isolines crossed each other, which demonstrated the possibility that the occurrence of combinations of the flood peak and volume may be the same under multiple effects of phase changes in the climate patterns and certain human activities (i.e. soil and water conservation). The most likely events were elaborated in diagrams, and the associated combinations of the flood peak and volume were smaller than that estimated by the fixed parameters (i.e. stationary condition) during most of the study period, while it was the opposite in 1956, 1959 and 1963. The results highlight the necessity of nonstationary flood frequency analysis under various conditions in both univariate and multivariate domains.

(1 −x) Ba(Mg1/3Ta2/3)O3–x Ba(Co1/3Nb2/3)O3 (BMT–BCN, x = 0.0, 0.20, 0.25, 0.30, 0.40) ceramics were prepared using the traditional solid-state reaction method. X-ray diffraction patterns have shown that the intensities of (001) and (100) super-lattices decrease with the increase in the BCN content. Seven main Raman vibrational modes are observed, assigned, and illustrated, in particular. Raman shifts of Eg(O) modes and the FWHM values of F2g(O)/A1g(O) modes have close relationship with the dielectric properties. The calculated values by the four-parameter semiquantum model based on IR reflectivity match well with the measured data (@3.8 GHz), which means that most of dielectric contribution to the system may be ascribed to the absorption of structural phononic oscillations at the infrared region, and the contribution from the scattering of the defective phonons is small. The contributions of each vibrational mode on the dielectric responses were investigated in detail, indicating that the low-frequency modes (A2u(1) and Eu(1)) have a decisive role to the dielectric properties.

Ba1+ xMoO4 (-0.03 ≤ x ≤ 0.03) ceramics were fabricated by a conventional two-step sintering technique. X-ray diffraction patterns show that there appeared new diffraction peaks when x > 0, which were identified as Ba2MoO5. The Rietveld refinement results indicate that the unit cell volume is the largest at x = -0.02, because it has the lowest packing fraction and covalency. The far-infrared reflectivity (IR) spectra were fitted and analyzed for calculating the intrinsic properties, which comply well with the data obtained from microscopic polarizabilities and damping coefficient angle. The proportion of each mode in the dielectric response demonstrates that the Ba-O8 polyhedra have a decisive role on the dielectric properties. And based on the Raman modes, the internal relations of the structural-properties were revealed with the changes of Ba2+ content.

Pr(Mg1/2Sn1/2)O3 (PMS) ceramic was prepared through a conventional solid-state reaction method. Crystal structure was investigated through X-ray diffraction (XRD), which certificates that the main phase is PMS with monoclinic P21/n1 symmetry. Lattice vibrational modes were obtained through Raman scattering spectroscopy and Fourier transform far-infrared reflection spectroscopy. The Raman spectrum active modes were assigned and illustrated, respectively, and then fitted with Lorentzian function. The four modes within the range of 110–200 cm−1 are derived from the F 2g vibrations (A-site cations), and the other three modes (300–430 cm−1) are derived from the F 2g vibrations (B-site cations).The mode with highest frequency above 650 cm−1 is attributed to A 1g -like mode that corresponds to the symmetric breathing of oxygen octahedral. The far-infrared spectrum with seven infrared active modes was fitted using four-parameter semi-quantum models to calculate intrinsic properties (permittivity and loss). F 2u (2) yielded the greatest contribution to dielectric constant and loss, which is mainly performed as the inverted translational vibration of Pr-MgO6 octahedron.

Sm(Mg1/2Sn1/2)O3(SMS) microwave dielectric ceramic was prepared by the traditional solid state synthesis method. The samples were tested by X-ray diffraction (XRD), vibrational spectra (Raman scattering and far-infrared reflectance spectroscopy). The Sm(Mg1/2Sn1/2)O3 perovskite is monoclinic with the space group P21/n proved by XRD. Raman vibrational modes were fitted and assigned by Lorentz function. To calculate the intrinsic properties, far-infrared spectra with seven active modes were fitted using a four-parameter semi-quantitative (FPSQ) model. The dielectric constant calculated according to FPSQ is similar to that obtained from the molecular polarization and the Clausius equation. The intrinsic loss has been determined by the relationship between the damping factor and the spectral center frequency, which is slightly larger than the value obtained in the four-parameter fitting, and indicates that A1g(Sm) Raman mode has a enormous effect on the dielectric loss. F3u (3) and F4u (4) have the greatest contribution to the dielectric constant and loss. Finally, the real and imaginary parts of permittivity were analyzed with Kramers-Kronig transformation.

The frequency of drought occurring in the Luanhe River basin in China has increased since 1965. The severe droughts are mainly influenced by the negative phase of Arctic Oscillation (AO) and the 12-month time-lag La Nina events. In this study, we investigate the mechanism of the severe droughts occurring in the Luanhe River basin due to the 12-month time-lag Pacific sea-surface temperature anomaly (SSTA) and AO in the Luanhe River basin for the period of 1965–2012. According to the 3-month time scale of the low-level circulations and SSTA in the Pacific Ocean, when AO is in a continuous negative phase, the geopotential height at the 500-hPa level over high-latitude regions, such as Siberia, Lake Baikal and the Ural Mountains, decreases. The Europe–Asia wave train is located southward, which results in meridional anomalous circulation prevailing over East Asia. Due to air–sea interactions, the 12-month time-lag Pacific SSTA weakens the northwestern Pacific subtropical high and blocks the warm air from the Pacific. When the negative phase of AO and La Nina happened simultaneously during 1971/1972, the first stage of 2000/2002 and 2008/2009, a severe drought occurred in the Luanhe River basin. A severe drought happened in this region during 1980/1981 and the third stage of 2000/2002 when AO was in the negative phase.