Wavelet Entropy and Complexity Analysis for Drinkers' EEG

This paper investigates the influence of alcohol on brain complexity. Considering electroencephalogram (EEG) has the nonlinear dynamics characteristic of time-varying and non-stationary, the wavelet entropy (WE) analysis is introduced. The EEG data of drinkers' and normal people's is analyzed using the wavelet entropy. The results show that the EEG wavelet entropy of drinkers' is markedly greater than the EEG wavelet entropy of normal people's, The EEG complexity of drinkers' is higher and the brain of drinkers' is in a more chaotic state

Desertification and Its Control along the Qinghai-Tibet Railway

The Qinghai-Tibet Railway is a magnificent project in the twenty first century. However, the problem of land desertification has arisen during the operation of the railway. Many sections of the railway roadbed are buried by sand. The ecological safety along the railway and the safe operation of the railway have attracted worldwide attention. This chapter will focus on the current situation of desertification along the Qinghai-Tibet Railway, such as key desertification sections and the temporal and spatial characteristics of the occurrence of desertification. At the same time, it introduces the characteristics of the dynamic conditions of railway desertification and the source of sand material. It is divided into two parts: biological measures and engineering measures to introduce desertification control along the railway. The biological measures focus on the selection of Lolium perenne, Festuca sinensi, Elymus breviaristatus, Elymus nutans and Poa crymophila, and other alpine native sand-fixing plant materials. The engineering measures will introduce the railway desertification comprehensive prevention and control technology system that combines solidification, resistance, and transportation

A Hybrid Wavelet de-noising and Rank-Set Pair Analysis approach for forecasting hydro-meteorological time series

Accurate, fast forecasting of hydro-meteorological time series is presently a major challenge in drought and flood mitigation. This paper proposes a hybrid approach, wavelet de-noising (WD) and Rank-Set Pair Analysis (RSPA), that takes full advantage of a combination of the two approaches to improve forecasts of hydro-meteorological time series. WD allows decomposition and reconstruction of a time series by the wavelet transform, and hence separation of the noise from the original series. RSPA, a more reliable and efficient version of Set Pair Analysis, is integrated with WD to form the hybrid WD-RSPA approach. Two types of hydro-meteorological data sets with different characteristics and different levels of human influences at some representative stations are used to illustrate the WD-RSPA approach. The approach is also compared to three other generic methods: the conventional Auto Regressive Integrated Moving Average (ARIMA) method, Artificial Neural Networks (ANNs) (BP-error Back Propagation, MLP-Multilayer Perceptron and RBF-Radial Basis Function), and RSPA alone. Nine error metrics are used to evaluate the model performance. Compared to three other generic methods, the results generated by WD-REPA model presented invariably smaller error measures which means the forecasting capability of the WD-REPA model is better than other models. The results show that WD-RSPA is accurate, feasible, and effective. In particular, WD-RSPA is found to be the best among the various generic methods compared in this paper, even when the extreme events are included within a time series

An SEM-REM-Based Study on the Driving and Restraining Mechanisms and Potential of Reclaimed Water Utilization in China

In order to promote the efficient use of reclaimed water in China and make water resources allocation better structured, this paper analyzed the factors that drive and restrain the current utilization of reclaimed water and unveiled their correlation and hierarchy in a way to develop a non-recursive structural framework of what drives and restrain reclaimed water use. By structural equation modeling (SEM), the transmission path of affecting factors was identified, the contribution of the factors quantified, and key indicators for potential prediction selected. On that basis, a random-effects model (REM) was built to predict the potential availability of the country’s reclaimed water. Meanwhile, parametric confidence intervals at 10–90% quantile levels were described, given the uncertainty of REM parameters. The results showed that four indicators for potential prediction, namely the total amount of wastewater treated, the density of water pipelines in built-up areas, investment in facilities for reclaimed water treatment, and the processing of applications for water treatment patents, are intertwined with the utilization of reclaimed water. Overall, the REM for potential prediction produced more precise fitting results, with the most significant fitting error standing at 5.9%. Going ahead, China is set to maintain the rapid growth in reclaimed water use, and up to 13.7 billion cubic meters of reclaimed water is expected to be available by 2025. This will help better structure the urban water supply and render regional water recycling more efficient

A Data Assimilation Approach to the Modeling of 3D Hydrodynamic Flow Velocity in River Reaches

The measurement of river discharge is essential for sustainable water resource management. The velocity–area approach is the most common method for calculating river discharge. Although several velocity measurement methods exist, they often have varying degrees of technical issues attributed to their operational complexity, time effectiveness, accuracy, and environmental impact. To address these issues, we propose a three-dimensional (3D) hydrodynamic model coupled with data assimilation (DA) for velocity measurement with improved accuracy and efficiency. We then apply this model to the Lanxi River reach in Zhejiang Province, China. The experimental results confirm that the obtained assimilated velocities using our proposed algorithm are much closer to the observed velocities than the simulated velocities. Our results show that when using the proposed method, the RMSE is decreased by 78%, and the SKILL and DASS values are 0.96 and 0.92, respectively. These confirm that the DA scheme of the flow velocity measurement is effective and capable of significantly improving the accuracy of the velocity with lower computational complexity

A Data Assimilation Approach to the Modeling of 3D Hydrodynamic Flow Velocity in River Reaches

The measurement of river discharge is essential for sustainable water resource management. The velocity–area approach is the most common method for calculating river discharge. Although several velocity measurement methods exist, they often have varying degrees of technical issues attributed to their operational complexity, time effectiveness, accuracy, and environmental impact. To address these issues, we propose a three-dimensional (3D) hydrodynamic model coupled with data assimilation (DA) for velocity measurement with improved accuracy and efficiency. We then apply this model to the Lanxi River reach in Zhejiang Province, China. The experimental results confirm that the obtained assimilated velocities using our proposed algorithm are much closer to the observed velocities than the simulated velocities. Our results show that when using the proposed method, the RMSE is decreased by 78%, and the SKILL and DASS values are 0.96 and 0.92, respectively. These confirm that the DA scheme of the flow velocity measurement is effective and capable of significantly improving the accuracy of the velocity with lower computational complexity

Concentration–Discharge Relationships in Runoff Components during Rainfall Events at the Hydrohill Experimental Catchment in Chuzhou, China

Concentration–discharge (C-Q) relationships are a convenient and increasingly popular tool for interpreting the episodic hydrochemical response to the varying discharge in small basins, providing insights into solute transport and streamflow generation. While most studies are focused on total runoff, this study quantified C-Q relationships in four runoff components during precipitation events at the Hydrohill experimental catchment in Chuzhou, China. This unique artificial catchment is carefully engineered, allowing observations of the interacting runoff components that collectively determine total flow issuing from the catchment. The four runoff components, or flow paths, include surface runoff (SR), shallow interflow at 0–30 cm depth (SSR30), deeper interflow at 30–60 cm depth (SSR60), and groundwater flow at 60–100 cm depth (SSR100). Water samples were collected during three consecutive precipitation events to study how the concentrations of primary solutes vary with flow. Analysis of C-Q relationships reveals that concentrations of Na+, Ca2+, Mg2+, SO42−, and HCO3− in the four runoff components had a negative relationship with discharge, while the concentration of K+ and Cl− were negatively correlated with discharge in SR and SSR30 but positively correlated in SSR60 and SSR100. Further insights were gained from principal component analysis. Three eigenvectors explained 92% of the variability in hydrochemistry in surface runoff, while two eigenvectors explained most of the variability in the hydrochemistry of subsurface flows observed at various depths in the soil profile (73% for SSR30, 79% for SSR60, and 76% for SSR100). PC1 (the first Principal Component) can be interpreted as a salinity factor, deriving from carbonate minerals such as dolomites and limestone minerals. Results indicated that leaching and dilution processes, water–soil interaction, and macropore flows in soils are the primary factors controlling the C-Q relationships. Our work sheds light on the coupled processes and streamflow generation mechanisms that control water quality at the catchment scale