Results Of Sen Research Articles

Trend analysis on CO2 emissions and their implications: a comparative study between India and China.

This research paper aims to provide a comparative trend analysis of CO2 emissions from the two largest emitters, India and China. The analysis focuses on the main sources of CO2 emissions-coal, oil, cement, and gas and their annual data and global share percentages from 1960 to 2019. The study uses non-parametric trend analysis methods, which do not rely on assumptions of normality, outliers, or data length. Pettitt's test, a well-established non-parametric method, was used to detect sudden shifts in the data. The Mann-Kendall (MK) test and Sen's slope estimator were then applied to identify the presence or absence of monotonic linear trends and assess the magnitude of the slopes. In addition, the innovative trend analysis (ITA) method was used, which is particularly effective in detecting and visualizing monotonic, non-monotonic, and sub-trends. The ITA method has the advantage of presenting these trends in a graphical format. According to the results of Pettitt's test, an abrupt change was detected in India in 1989 for all sources of CO2 emissions. In China, however, an abrupt change was detected in 1989 for coal and gas-related sources, while other sources showed a change point in 1990. The results of the MK test and the ITA method showed that all sources show only monotonic increasing trends. Based on the results of Sen's slope estimator, the average rate of change of CO2 emissions is significantly higher in China than in India in all categories after the detection of the abrupt change point. Policymakers should promote the adoption of renewable energy sources, such as solar, wind, hydro, and geothermal, and also implement strategies to control deforestation to counteract the abnormal increase in CO2 emissions. Finally, this research lays a solid foundation for future studies on CO2 emissions.

Investigating river water quality assessment through non‐parametric analysis: A case study of the Godavari River in India

AbstractThis study examines temporal variations in water quality parameters of Godavari River. The present study examines the concentrations of seven water quality parameters, namely total alkalinity (Alk), calcium (Ca), chlorine (Cl), total hardness (Hard), magnesium (Mg), sodium (Na), and sulfate (SO4), using data from 1981 to 2005 at seven gauging stations, that is, Mancherial, Pathagudem, Nowrangpur, Jagdalpur, Perur, Konta, and Polavaram. A seasonal analysis (pre‐monsoon, monsoon, and post‐monsoon) is conducted to detect trends in water quality parameters. The study also uses normality tests Kolmogorov–Smirnov (K–S) and Shapiro–Wilk (S–W) which reveals nonnormal distribution in the majority of datasets, necessitating non‐parametric analysis. The concentration of Alk, Ca, and Hard is found to be significantly increasing trend at some stations during all three seasons, along with significantly decreasing trend found in the concentrations of Cl, Na, and SO4 using non‐parametric Mann–Kendall's (M–K) and Sen's Slope test. The concentration of Mg depicts mixed trends at different stations which may be due the variation in agricultural practices or industrial activities surrounding the stations. It is evident that none of the parameter exhibits statistically significant trends across all seasons at any station. The results of Sen's Slope test are found to be in good agreement with Mann–Kendall's test statistics. A second order auto‐regressive model (AR (2)) is successfully employed to predict and forecast the water quality parameters in present and future time steps. The authenticity of AR (2) model is assessed using Nash‐Sutcliffe (NSE) efficiency and coefficient of determination (R2). The values of NSE and R2 are found to be more than 0.85 for all parameters during all the three seasons, along with, the values of mean square error (MSE), root mean square error (RMSE), and mean absolute error (MAE). The results of coefficient of variation (CV) and persistence‐criterion (PC) also depicts that AR (2) can successfully be utilized in forecasting the water quality parameters. The research contributes insights for effective water resource management in Godavari River basin.

Trend Analysis of Annual Runoff in Yong’an Creek Basin of Zhejiang

Yong’an Creek is the source of the Lingjiang River, one of the eight major river systems in Zhejiang, and is of great significance to support the economic and social development of the Zhejiang region. Based on the runoff data of Baizhi’ao Hydrological Station from 1985 to 2020, this paper uses linear regression, Mann-Kendall method and Sen’s slope estimator to analyze the change trend of the annual runoff of Yong’an Creek, and diagnoses abrupt changes. The results show: The runoff in the Yong’an Creek basin has large interannual variability, and the linear regression and M-K trend test results show that the runoff in the Yongan River Basin has a downward trend. There is no real mutation point in the precipitation in the Yong’an Creek basin from 1985 to 2020. The results of Sen’s slope show that the rate of change of runoff is small. The results of the study will provide necessary guidance for sustainable water resources management and disaster risk reduction of the Yong’an Creek basin.

Applicability of SPI and RDI for forthcoming drought events: a non-parametric trend and one way ANOVA approach

Abstract Monthly, seasonal and annual trends of rainfall and temperature (both minimum and maximum) have been analyzed using the Mann–Kendall trend test (a non-parametric test) and Sen's slope estimator for Sagar division, India from 1988 to 2018. Sagar division is a drought-prone zone of Madhya Pradesh, India. The same analysis has been performed for two drought indices, the Standardized Precipitation Index (SPI) and Reconnaissance Drought Index (RDI). Both indices were calculated to see the trend in the drought for 35 rain-gauge stations belonging to the study area. The study revealed that the minimum temperature had increased more than the maximum temperature in the last 31 years. The strong similarity in the results of Sen's slope of SPI and RDI were seen for both significant and non-significant trends. Analysis of variance (ANOVA) testing validates the substantial similarity between SPI and RDI based on Sen's slope. It also indicated the suitability of RDI for future projection of drought using the general circulation models (GCMs) or regional climate models (RCMs) in meteorological drought as well as the agricultural drought category. In contrast, the SPI indicated the meteorological drought only. The distribution of trends of temperature and drought indices were presented using the kriging interpolation.

Spatial and temporal variability of precipitation concentration in Iran

Precipitation concentration is an important factor to assess climate hazards such as flood and availability of water resources at a regional scale. This paper investigates the spatial and temporal changes of precipitation concentration using the precipitation concentration index (PCI) in 113 stations in Iran for a duration of 30 years (1988-2017). The results show that the mean average of the annual rainfall in Iran varies from 55 mm in the Eastern and central regions (Zabol and Yazd) to 1838 mm in the southwest coast of the Caspian Sea (Bandar Anzali). The highest coefficient of variation (CV) of precipitation is related to the southeastern and southern parts of the country, whereas the lowest CV is observed in the Caspian Sea coast and northwest region. Therefore, its value is mostly a function of latitude. Precipitation concentration and its CV are also influenced by topography and reveal more homogeneity in the northern regions. The Mann-Kendall (MK) test on precipitation concentration data indicates that except for 6 stations (ascending in 2 stations and descending in 4stations), there was no significant trend in others. The stations with non-significant ascending values are located mostly in the Eastern, central and western parts of the country while the non-significant descending ones can be seen in the central and northeastern regions. The results of Sen's slope estimator are also similar to the values of the MK test.

Wavelet-based trend analysis of hydrological processes at different timescales

This study analyzes involved trends in stream flow and precipitation data at monthly, seasonal and annual timescales observed at six precipitation and four stream flow stations of Tampa Bay using non-parametric Mann–Kendall (MK) and discrete wavelet transform (DWT) methods. The MK test and sequential MK analysis were applied to different combinations of DWT after removing the effect of significant lag-1 serial correlation to calculate components responsible for trend of the time series. Also, the sequential MK test was used to find the starting point of changes in annual time series. The results showed that negative trend is prevalent in the case study; generally, short-term periods were important in the involved trend at original time series. Thus, the precipitation data at three scales showed short-term periods of 2 months, 6 months and 2 years in monthly, seasonal and annual scales, respectively. In the greatest stream-flow time series at three timescales, wavelet-based detail at level 2 plus the approximations time series was conceded as the dominant periodic component. Finally, the results of Sen's trend analysis, applied to the original annual time series, also confirmed the results of the proposed wavelet-based MK test in most cases.

Calibration of three-parameter Weibull stress model for 15Kh2NMFA RPV steel

Weibull stress model represents a basic local approach model used in the ductile-to-brittle transition region for description and prediction of cleavage fracture for materials of both PWR and WWER reactor pressure vessels. In the Weibull stress model used most frequently until now [1], the parameters are determined by a calibration procedure using the fracture toughness values of high and low constraint specimens. In the present paper, the results of SEN(B) pre-cracked specimens of 10 × 20 × 120 mm size, with deep and shallow cracks, are utilized. Specimens were made of material of WWER-1000 reactor pressure vessel, and were tested at Nuclear Research Institute Rez. Determination of Weibull stress was performed for both the case of including plastic strain correction into the Weibull stress formula and without it.

Chalcogen-Nitrogen Compounds of the Heavier Group 16 Elements

Abstract Recent results of Se-N and Te-N chemistry at Gottingen University are summarized. This includes the preparation and structural characterisation of compounds with short Se-N and Te-N bonds, the first stable Te nitride, the first Te(III) radical and the first compound containing a nitrene group.

On some sequential simultaneous confidence intervals procedures

The purpose of this paper is two-fold: (i) to extend the simultaneous confidence intervals procedures (SCIP) of Healy [7] along the lines of Chow and Robbins [3] and (ii) to develop certain robust non-parametric SCIP based on the results of Sen [10] and Sen and Ghosh [11]; the allied efficiency results are also presented.

On a class of asymptotically optimal nonparametric tests for grouped data I

Generalizing the results of Sen [8], a class of nonparametric tests for the hypothesis of no regression in the multiple linear regression model is obtained here. The asymptotic power properties of the proposed class of tests are studied, and the asymptotic optimality of the tests is established under the conditions of Wald [10]. Applications of the results are also considered.