scholarly journals Secular change of annual rainfall time series and nonstationary hydrologic frequency analysis.

1992 ◽  
Vol 20 ◽  
pp. 25-32
Author(s):  
Noriaki SOGAWA ◽  
Satoru NAKAMURA ◽  
Hiroki YAMADA
Keyword(s):  
Time Series ◽  
Frequency Analysis ◽  
Secular Change ◽  
Annual Rainfall ◽  
Rainfall Time Series ◽  
Hydrologic Frequency Analysis

scholarly journals Variability and Trend Analysis of Rainfall Data of Shillong and Agartala Stations of North East India

2020 ◽  
pp. 134-142
Author(s):  
Mirbana Lusick K. Sangma ◽  
Hamtoiti Reang ◽  
G. T. Patle ◽  
P. P. Dabral
Keyword(s):  
Time Series ◽  
Trend Analysis ◽  
Winter Season ◽  
Summer Season ◽  
Annual Rainfall ◽  
Rainfall Time Series ◽  
North East ◽  
South West ◽  
Total Annual Rainfall ◽  
Sw Monsoon

This paper discusses the variability in rainfall and trend analysis of annual and seasonal rainfall time series of Shillong and Agartala stations located in the north-east region of India. Commonly used non-parametric statistical methods namely Mann-Kendall and Sen’s slope estimator was used to analyse the seasonal and annual rainfall time series. Statistical analysis showed less variation in annual and south-west monsoon rainfall for both Shillong and Agartala stations. In the total annual rainfall, the share of south-west (SW) monsoon, north-east (NE) monsoon, winter season and summer season rainfall was observed 64.60%, 13.22%, 1.40% and 20.80%, respectively for Shillong station of Meghalaya state. However, the contribution of SW monsoon, NE monsoon, winter season and summer season rainfall in the total annual rainfall was 59.59%, 9.55%, 1.14% and 29.72%, respectively for Agartala station of Tripura state. Non-significant increasing trends of rainfall was observed by 4.54 mm/year, 2.80 mm/year and 2.54 mm/year for annual, SW monsoon, and summer season, whereas, non-significant decreasing trends in rainfall for NE monsoon and winter season was observed with a magnitude of 1.83 mm/year and 1.63 mm/year for Shillong, Meghalaya during 1992 to 2017. Results also revealed that rainfall increased by 1.07 mm/year and 0.18 mm/year in SW monsoon and winter season whereas, rainfall decreased by 7.64 mm/year, 2.58 mm/year and 1.29 mm/year during annual, NE monsoon and summer season non-significantly during 1995 to 2019 in case of Agartala. The findings of present study will be useful for water management and crop planning in hill agriculture of Meghalaya and Tripura state of India.

scholarly journals Analyzing Trend and Variability of Rainfall in The Tafna Basin (Northwestern Algeria)

Atmosphere ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 347 ◽  
Author(s):  
Hanane Bougara ◽  
Kamila Baba Hamed ◽  
Christian Borgemeister ◽  
Bernhard Tischbein ◽  
Navneet Kumar
Keyword(s):  
Time Series ◽  
Water Resource Management ◽  
Statistical Tests ◽  
Trend Detection ◽  
Detection Methods ◽  
Annual Rainfall ◽  
Rainfall Time Series ◽  
Friedman Test ◽  
Upward Trend ◽  
Increasing Trend

Northwest Algeria has experienced fluctuations in rainfall between the two decades 1940s and 1990s from positive to negative anomalies, which reflected a significant decline in rainfall during the mid-1970s. Therefore, further analyzing rainfall in this region is required for improving the strategies on water resource management. In this study, we complement previous studies by dealing with sub basins that were not previously addressed in Tafna basin (our study area located in Northwest Algeria), and by including additional statistical methods (Kruskal–Wallis test, Jonckheere-Terpstra test, and the Friedman test) that were not earlier reported on the large scale (Northwest Algeria). In order to analyse the homogeneity, trends, and stationarity in rainfall time series for nine rainfall stations over the period 1979–2011, we have used several statistical tests. The results showed an increasing trend for annual rainfall after the break detected in 2007 for Djbel Chouachi, Ouled Mimoun, Sidi Benkhala stations using Hubert, Pettitt, and Buishand tests. The Lee and Heghinian test has detected a break at the same year in 2007 for all stations except Sebdou, Beni Bahdel, and Hennaya stations, which have a break date in 1980. We have confirmed this increasing trend for rainfall with other trend detection methods such as Mann Kendall and Sen’s method that highlighted an upward trend for all the stations in the autumn season, which is mainly due to an increase in rainfall in September and October. On a monthly scale, the date of rupture is different from one station to another because the time series are not homogeneous. In addition, we have applied three tests enabling further results: (i) the Jonckheere-Terpstra test has detected an upward trend for two stations (Khemis and Hennaya), (ii) Friedman test has indicated the difference between the mean rank again with Khemis and Hennaya stations and the Merbeh station, (iii) according to the Kruskal-Wallis test, there have been no variance detected between all the rainfall stations. The increasing trend in rainfall may lead to a rise in stream flow and enhance potential floods risks in low-lying regions of the study area.

scholarly journals A Nonparametric Procedure to Assess the Accuracy of the Normality Assumption for Annual Rainfall Totals, Based on the Marginal Statistics of Daily Rainfall: An Application to the NOAA/NCDC Rainfall Database

2021 ◽  
Vol 60 (4) ◽  
pp. 595-605
Author(s):  
Dario Ruggiu ◽  
Francesco Viola ◽  
Andreas Langousis
Keyword(s):  
Time Series ◽  
Goodness Of Fit ◽  
Random Search ◽  
Daily Rainfall ◽  
Annual Rainfall ◽  
Rainfall Time Series ◽  
Normality Assumption ◽  
Normal Shape ◽  
Nonparametric Procedure ◽  
Rain Rates

AbstractWe develop a nonparametric procedure to assess the accuracy of the normality assumption for annual rainfall totals (ART), based on the marginal statistics of daily rainfall. The procedure is addressed to practitioners and hydrologists that operate in data-poor regions. To do so we use 1) goodness-of-fit metrics to conclude on the approximate convergence of the empirical distribution of annual rainfall totals to a normal shape and classify 3007 daily rainfall time series from the NOAA/NCDC Global Historical Climatology Network database, with at least 30 years of recordings, into Gaussian (G) and non-Gaussian (NG) groups; 2) logistic regression analysis to identify the statistics of daily rainfall that are most descriptive of the G/NG classification; and 3) a random-search algorithm to conclude on a set of constraints that allows classification of ART samples on the basis of the marginal statistics of daily rain rates. The analysis shows that the Anderson–Darling (AD) test statistic is the most conservative one in determining approximate Gaussianity of ART samples (followed by Cramer–Von Mises and Lilliefors’s version of Kolmogorov–Smirnov) and that daily rainfall time series with fraction of wet days fwd < 0.1 and daily skewness coefficient of positive rain rates skwd > 5.92 deviate significantly from the normal shape. In addition, we find that continental climate (type D) exhibits the highest fraction of Gaussian distributed ART samples (i.e., 74.45%; AD test at α = 5% significance level), followed by warm temperate (type C; 72.80%), equatorial (type A; 68.83%), polar (type E; 62.96%), and arid (type B; 60.29%) climates.

scholarly journals Investigating changes over time of annual rainfall in Zimbabwe

2010 ◽  
Vol 14 (12) ◽  
pp. 2671-2679 ◽  
Author(s):  
D. Mazvimavi
Keyword(s):  
Time Series ◽  
Regression Analysis ◽  
Quantile Regression ◽  
Rainy Season ◽  
Annual Rainfall ◽  
Rainfall Time Series ◽  
Average Rainfall ◽  
Quantile Regression Analysis ◽  
Changes Over Time ◽  
Over Time

Abstract. There is increasing concern in southern Africa about the possible decline of rainfall as a result of global warming. Some studies concluded that average rainfall in Zimbabwe had declined by 10% or 100 mm during the last 100 years. This paper investigates the validity of the assumption that rainfall is declining in Zimbabwe. Time series of annual rainfall, and total rainfall for (a) the early part of the rainy season, October-November-December (OND), and (b) the mid to end of the rainy season, January-February-March (JFM) are analysed for the presence of trends using the Mann-Kendall test, and for the decline or increase during years with either high or low rainfall using quantile regression analysis. The Pettitt test has also been utilized to examine the possible existence of change or break-points in the rainfall time series. The analysis has been done for 40 rainfall stations with records starting during the 1892–1940 period and ending in 2000, and representative of all the rainfall regions. The Mann-Kendal test did not identify a significant trend at all the 40 stations, and therefore there is no proof that the average rainfall at each of these stations has changed. Quantile regression analysis revealed a decline in annual rainfall less than the tenth percentile at only one station, and increasing of rainfall greater than the ninetieth percentile at another station. All the other stations had no changes over time in both the low and high rainfall at the annual interval. Climate change effects are therefore not yet statistically significant within time series of total seasonal and annual rainfall in Zimbabwe. The general perception about declining rainfall is likely due to the presence of multidecadal variability characterized by bunching of years with above (e.g. 1951–1958, 1973–1980) and below (e.g. 1959–1972, 1982–1994 ) average rainfall.

Spatiotemporal variability of annual and seasonal rainfall time series in Ho Chi Minh city, Vietnam

2018 ◽  
Vol 10 (3) ◽  
pp. 658-670 ◽  
Author(s):  
Dang Nguyen Dong Phuong ◽  
Vu Thuy Linh ◽  
Tran Thong Nhat ◽  
Ho Minh Dung ◽  
Nguyen Kim Loi
Keyword(s):  
Time Series ◽  
Rainy Season ◽  
Kendall Test ◽  
Dry Season ◽  
Seasonal Rainfall ◽  
Spatiotemporal Variability ◽  
Ho Chi Minh City ◽  
Annual Rainfall ◽  
Rainfall Time Series ◽  
Spatial And Temporal Patterns

Abstract This study analyzed spatial and temporal patterns of rainfall time series from 14 proportionally distributed stations in Ho Chi Minh City for the period 1980–2016. Both parametric and nonparametric approaches, specifically, linear regression, the Mann–Kendall test and Sen's slope estimator, were applied to detect and estimate the annual and seasonal trends after using original and notched boxplots for the preliminary interpretation. The outcomes showed high domination of positive trends in the annual and seasonal rainfall time series over the 37-year period, but most statistically significant trends were observed in the dry season. The results of trend estimation also indicated higher increasing rates of rainfall in the dry season compared to the rainy season at most stations. Even though the total amount of annual rainfall is mainly contributed by rainfall during the rainy season, the pronounced increment in the dry season can be a determining factor of possible changes in annual rainfall. Additionally, the interpolated results revealed a consistently increasing trend in the southeastern parts of the study area (i.e., Can Gio district), where annual rainfall was by far the lowest intensity compared to other regions.

Precipitation trends in Victoria, Australia

2014 ◽  
Vol 6 (2) ◽  
pp. 278-287 ◽  
Author(s):  
Siti Nazahiyah Rahmat ◽  
Niranjali Jayasuriya ◽  
Muhammed A. Bhuiyan
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Annual Rainfall ◽  
Series Data ◽  
Rainfall Time Series ◽  
Full Data ◽  
Data Set ◽  
Rainfall Analysis ◽  
Mk Test ◽  
Abrupt Changes

Annual rainfall series trends were investigated for more than 100 years of data using two non-parametric trend tests Mann–Kendall (MK) and Sen's slope (Q) for five selected meteorological stations in Victoria, Australia. The annual rainfall time series showed no significant trends for any of the five stations. To assess the sensitivity of trends to the length of the time periods considered, the annual rainfall analysis was repeated using recent data from approximately half the data set between 1949 and 2011. Contrasting results from the original full data set analysis were revealed. All five stations showed decreasing trends with two stations showing significant trends suggesting that this recent time period has added more low precipitation data to the time series. The year of abrupt changes for all the five stations identified using the sequential MK test varied. Conclusions drawn from this paper, point to the importance of selecting the time series data length in identifying trends and abrupt changes. Due to the climate variability, trend testing results might be biased and strongly dependent on the data period selected. Therefore, use of the full data set available would be required in order to improve understanding of change or to undertake any further studies.

Spatial Variability of the Hurst Exponent for the Daily Scale Rainfall Series in the State of Zacatecas, Mexico

2013 ◽  
Vol 52 (12) ◽  
pp. 2771-2780 ◽  
Author(s):  
M. A. Velásquez Valle ◽  
G. Medina García ◽  
Ignacio Sánchez Cohen ◽  
L. Klaudia Oleschko ◽  
J. A. Ruiz Corral ◽  
...  
Keyword(s):  
Time Series ◽  
Hurst Exponent ◽  
Fractal Theory ◽  
Daily Rainfall ◽  
The State ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Rainfall Time Series ◽  
Wavelet Techniques ◽  
Hurst Exponents

AbstractThe structural pattern of rainfall data exhibits random fluctuations over time and space. Utilizing concepts of fractal theory, it has been possible to identify characteristics of rainfall data beyond simple statistical indicators of their randomness. The objective of this research was to identify the spatial variation of the Hurst exponent, extracted through standard wavelet techniques from time series of daily rainfall data in the state of Zacatecas, Mexico. The Hurst exponent was extracted for 26 locations using the reference techniques for auto-affine traces—in particular, the wavelets method. Results have shown that the Hurst exponents of rainfall time series are negatively influenced by altitude; thus, stations located at higher altitudes were characterized by Hurst exponents indicating more nonpersistent behavior. The trends among geographical variables (west longitude and latitude) and climatic parameters (annual rainfall and number of rainy days) and their relationship with the Hurst exponent were also analyzed.

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