scholarly journals ANALYSIS OF RAINFALL RECORDS IN INDIA: SELF-ORGANIZED CRITICALITY AND SCALING

Fractals ◽  
2006 ◽  
Vol 14 (04) ◽  
pp. 289-293 ◽  
Author(s):  
A. SARKAR ◽  
P. BARAT
Keyword(s):  
Time Series ◽  
Power Law ◽  
Rainfall Intensity ◽  
Time Series Data ◽  
Series Data ◽  
Scaling Analysis ◽  
Rainfall Time Series ◽  
Self Organized ◽  
Time Period ◽  
Self Organized Criticality

The time series data of the monthly rainfall records (for the time period 1871–2002) in All India and different regions of India are analyzed. It is found that the distributions of the rainfall intensity exhibit perfect power law behavior. The scaling analysis revealed two distinct scaling regions in the rainfall time series.

Congo Basin's Shrinking Watersheds

2020 ◽  
pp. 1452-1468
Author(s):  
Bila-Isia Inogwabini
Keyword(s):  
Time Series ◽  
Regression Analysis ◽  
Time Series Data ◽  
Democratic Republic Of Congo ◽  
Congo Basin ◽  
Series Data ◽  
Water Volume ◽  
Rainfall Time Series ◽  
Aquatic Resources ◽  
Basin Water

Rainfall time series data from three sites (Kinshasa, Luki, and Mabali) in the western Democratic Republic of Congo were analyzed using regression analysis; rainfall intensities decreased in all three sites. The Congo Basin waters will follow the equation y = -20894x + 5483.16; R2 = 0.7945. The model suggests 18%-loss of the Congo Basin water volume and 7%-decrease for fish biomasses by 2025. Financial incomes generated by fishing will decrease by 11% by 2040 compared with 1998 levels. About 51% of women (N= 408,173) from the Lake Tumba Landscape fish; their revenues decreased by 11% between 2005 and 2010. If this trend continues, women's revenues will decrease by 59% by 2040. Decreased waters will severely impact women (e.g. increasing walking distances to clean waters). Increasing populations and decreasing waters will lead to immigrations to this region because water resources will remain available and highly likely ignite social conflicts over aquatic resources.

scholarly journals The Presidential Political Business Cycle of 1972

1984 ◽  
Vol 44 (2) ◽  
pp. 265-271 ◽  
Author(s):  
Robert R. Keller ◽  
Ann Mari May
Keyword(s):  
Time Series ◽  
Business Cycle ◽  
Time Series Data ◽  
Political Business Cycle ◽  
Series Data ◽  
The Political ◽  
Operating Environment ◽  
Macroeconomic Conditions ◽  
Price Controls ◽  
Time Period

Previous studies of the political business cycle have examined time series data to determine whether a pattern of pre-election boom and post-election slump exists. The studies do not investigate the behavior and mechanisms by which a politician may effectuate a political business cycle. We focus on one time period, 1969 to 1972, and conclude that President Nixon's personality and operating environment explain why he manipulated the economy for political gain. The mechanisms he utilized to improve macroeconomic conditions before the 1972 election include monetary policy, fiscal policy, and wage-price controls.

scholarly journals Modified singular spectrum analysis in identifying rainfall trend over peninsular Malaysia

2019 ◽  
Vol 15 (1) ◽  
pp. 283
Author(s):  
S.M. Shaharudin ◽  
N. Ahmad ◽  
N.H. Zainuddin
Keyword(s):  
Time Series ◽  
Spectrum Analysis ◽  
Time Series Data ◽  
Singular Spectrum Analysis ◽  
Singular Values ◽  
Peninsular Malaysia ◽  
Series Data ◽  
Rainfall Time Series ◽  
Singular Spectrum ◽  
Torrential Rainfall

<p>Identifying the local time scale of the torrential rainfall pattern through Singular Spectrum Analysis (SSA) is useful to separate the trend and noise components. However, SSA poses two main issues which are torrential rainfall time series data have coinciding singular values and the leading components from eigenvector obtained from the decomposing time series matrix are usually assesed by graphical inference lacking in a specific statistical measure. In consequences to both issues, the extracted trend from SSA tended to flatten out and did not show any distinct pattern.  This problem was approached in two ways. First, an Iterative Oblique SSA (Iterative O-SSA) was presented to make adjustment to the singular values data. Second, a measure was introduced to group the decomposed eigenvector based on Robust Sparse K-means (RSK-Means). As the results, the extracted trend using modification of SSA appeared to fit the original time series and looked more flexible compared to SSA.</p>

scholarly journals Trend Analysis of Rainfall Time Series in Shanxi Province, Northern China (1957–2019)

Water ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2335
Author(s):  
Feng Gao ◽  
Yunpeng Wang ◽  
Xiaoling Chen ◽  
Wenfu Yang
Keyword(s):  
Time Series ◽  
Water Supply ◽  
Trend Analysis ◽  
Agricultural Production ◽  
Time Series Data ◽  
Shanxi Province ◽  
Series Data ◽  
Rainfall Time Series ◽  
Mk Test ◽  
Wutai Shan

Changes in rainfall play an important role in agricultural production, water supply and management, and social and economic development in arid and semi-arid regions. The objective of this study was to examine the trend of rainfall series from 18 meteorological stations for monthly, seasonal, and annual scales in Shanxi province over the period 1957–2019. The Mann–Kendall (MK) test, Spearman’s Rho (SR) test, and the Revised Mann–Kendall (RMK) test were used to identify the trends. Sen’s slope estimator (SSE) was used to estimate the magnitude of the rainfall trend. An autocorrelation function (ACF) plot was used to examine the autocorrelation coefficients at various lags in order to improve the trend analysis by the application of the RMK test. The results indicate remarkable differences with positive and negative trends (significant or non-significant) depending on stations. The largest number of stations showing decreasing trends occurred in March, with 10 out of 18 stations at the 10%, 5%, and 1% levels. Wutai Shan station has strong negative trends in January, March, April, November, and December at the level of 1%. In addition, Wutai Shan station also experienced a significant decreasing trend over four seasons at a significance level of 1% and 10%. On the annual scale, there was no significant trend detected by the three identification methods for most stations. MK and SR tests have similar power for detecting monotonic trends in rainfall time series data. Although similar results were obtained by the MK/SR and RMK tests in this study, in some cases, unreasonable trends may be provided by the RMK test. The findings of this study could benefit agricultural production activities, water supply and management, drought monitoring, and socioeconomic development in Shanxi province in the future.

Congo Basin's Shrinking Watersheds

2017 ◽  
pp. 211-226
Author(s):  
Bila-Isia Inogwabini
Keyword(s):  
Time Series ◽  
Regression Analysis ◽  
Time Series Data ◽  
Democratic Republic Of Congo ◽  
Congo Basin ◽  
Series Data ◽  
Water Volume ◽  
Rainfall Time Series ◽  
Aquatic Resources ◽  
Basin Water

Rainfall time series data from three sites (Kinshasa, Luki, and Mabali) in the western Democratic Republic of Congo were analyzed using regression analysis; rainfall intensities decreased in all three sites. The Congo Basin waters will follow the equation y = -20894x + 5483.16; R2 = 0.7945. The model suggests 18%-loss of the Congo Basin water volume and 7%-decrease for fish biomasses by 2025. Financial incomes generated by fishing will decrease by 11% by 2040 compared with 1998 levels. About 51% of women (N= 408,173) from the Lake Tumba Landscape fish; their revenues decreased by 11% between 2005 and 2010. If this trend continues, women's revenues will decrease by 59% by 2040. Decreased waters will severely impact women (e.g. increasing walking distances to clean waters). Increasing populations and decreasing waters will lead to immigrations to this region because water resources will remain available and highly likely ignite social conflicts over aquatic resources.

scholarly journals Enhanced accuracy of rainfall–runoff modeling with wavelet transform

2012 ◽  
Vol 15 (2) ◽  
pp. 392-404 ◽  
Author(s):  
Chien-ming Chou
Keyword(s):  
Time Series ◽  
Wavelet Transform ◽  
Response Function ◽  
Time Series Data ◽  
Series Data ◽  
Rainfall Time Series ◽  
Calibration Data ◽  
Validation Data ◽  
Original Scale ◽  
Using Data

Wavelet transform (WT) is typically used to decompose time series data for only one hydrological feature at a time. This study applied WT for simultaneous decomposition of rainfall and runoff time series data. For the calibration data, the decomposed rainfall and runoff time series calibrate the subsystem response function using the least squares (LS) method at each scale. For the validation data, the decomposed rainfall time series are convoluted with the estimated subsystem response function to obtain the estimated runoff at each scale. The estimated runoff at the original scale can be obtained by wavelet reconstruction. The efficacy of the proposed method is evaluated in two case studies of the Feng-Hua Bridge and Wu-Tu watershed. The analytic results confirm that the proposed wavelet-based method slightly outperforms the conventional method of using data only at the original scale. The results also show that the runoff hydrograph estimated by using the proposed method is smoother than that obtained using a single scale.

Trend Analysis on Precipitation Time Series Data in Munda Catchment, Pakistan

2014 ◽  
Vol 692 ◽  
pp. 97-102 ◽  
Author(s):  
Ijaz Ahmad ◽  
De Shan Tang ◽  
Mei Wang ◽  
Sarfraz Hashim
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Series Data ◽  
Positive Trend ◽  
Precipitation Time Series ◽  
Significance Level ◽  
Annual Basis ◽  
Time Period ◽  
Seasonal Basis ◽  
Correlation Trend

This paper investigates the trends in precipitation time series of 10 stations for the time period of 51 years (1961-2011) in the Munda catchment, Pakistan. The Mann-Kendall (MK) and Spearman’s rho (SR) tests were employed for detection of the trend on the seasonal and annual basis at 5% significance level. For the removal of the serial correlation Trend Free Pre-Whitening approach was applied. The results show, a mixture of positive (increasing) and negative (decreasing) trends. A shift in precipitation time series is observed on seasonal scale from summer to autumn season. The Charbagh station exhibits the most number of significant cases on the seasonal basis while, no significant trends are found at Thalozom, Kalam and Dir stations. On the annual basis, only Charbagh station shows a significant positive trend, while on other stations, no significant trends are found annually. The performance of MK and SR tests was consistent in detecting the trend at different stations.

Subtle nonlinearity in popular album charts

1999 ◽  
Vol 02 (03) ◽  
pp. 197-208 ◽  
Author(s):  
R. Alexander Bentley ◽  
Herbert D. G. Maschner
Keyword(s):  
Time Series ◽  
Popular Music ◽  
Power Law ◽  
Large Scale ◽  
Selective Sampling ◽  
Self Organized ◽  
Self Organized Criticality ◽  
Critical Model ◽  
Power Law Distributions ◽  
Multiplicative Processes

Large-scale patterns of culture change may be explained by models of self organized criticality, or alternatively, by multiplicative processes. We speculate that popular album activity may be similar to critical models of extinction in that interconnected agents compete to survive within a limited space. Here we investigate whether popular music albums as listed on popular album charts display evidence of self-organized criticality, including a self-affine time series of activity and power-law distributions of lifetimes and exit activity in the chart. We find it difficult to distinguish between multiplicative growth and critical model hypotheses for these data. However, aspects of criticality may be masked by the selective sampling that a "Top 200" listing necessarily implies.

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