scholarly journals Trend analyses of regional time series of temperatures and rainfall of the Tapi basin

2021 ◽  
Vol 22 (1) ◽  
pp. 48-51
Author(s):  
GANESH D. KALE
Keyword(s):  
Time Series ◽  
Kendall Test ◽  
Temperature Variations ◽  
Trend Analyses ◽  
Slope Test ◽  
Climate Change Information ◽  
Mann Kendall Test ◽  
Maximum Temperatures ◽  
Planning Development ◽  
Tapi Basin

Climate change information at the scale of basin is vital for planning, development and use of water. The Tapi basin is climatically responsive. Hydrological response of a basin is based mainly on rainfall and temperature. Variations in climate at regional scales impacts fundamental features of our life. Thus, in the present work, trend analyses of regional time series (1971-2004) of minimum, mean, maximum temperatures and rainfallis performed for monthly, annual and seasonal scales for the Tapi basin. Correlogram is utilized for evaluation of dependence of data. Mann-Kendall test and Mann-Kendall test with block bootstrapping are applied for the evaluation of trend significance. Sen’s slope test is applied for the evaluation of trend magnitude. Sequential Mann-Kendall test is applied for assessment of beginning and end of the trend. Statistically significant positive trends are detected in regional annual and winter Tmean time series with their beginning in years 1974 and 1972, respectively.

scholarly journals Re-evaluation of the Power of the Mann-Kendall Test for Detecting Monotonic Trends in Hydrometeorological Time Series

2020 ◽  
Vol 8 ◽  
Author(s):  
Fan Wang ◽  
Wei Shao ◽  
Haijun Yu ◽  
Guangyuan Kan ◽  
Xiaoyan He ◽  
...  
Keyword(s):  
Time Series ◽  
Kendall Test ◽  
Mann Kendall Test

Precipitation Trend Analysis by Mann-Kendall Test: A Case of Tianchang County Anhui Province, China

2013 ◽  
Vol 864-867 ◽  
pp. 2218-2223 ◽  
Author(s):  
Elsie Akwei ◽  
Bao Hong Lu ◽  
Han Wen Zhang
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Trend Analysis ◽  
Null Hypothesis ◽  
Kendall Test ◽  
Anhui Province ◽  
Significant Trend ◽  
Precipitation Data ◽  
Precipitation Time Series ◽  
Mann Kendall Test

The purpose of this research is to study the temporal variability of precipitation time series of Tianchang County in Anhui Province, China to aid in the understanding of the state of the hydrology of the catchment. Trend analysis of one of the main component of the water balance of a catchment and a climate variable, precipitation was conducted with the aim of detecting a possible trend in the precipitation time series of Tianchang County, the non-parametric Mann-Kendall test was applied to precipitation series from 1951-2010 of Tianchang County. It was performed using Trend (version 1.0.2) to identify the significant positive or negative trends in the precipitation data if any. The 59 years period of precipitation data for the different towns in whole area showed, on the whole, some significant trend at an alpha level of 0.01 and 0.05 when grouped into the four seasons present in the area. The trend analysis revealed an overall upward and significant trend in five towns namely Datong, Xinjie, Shiliang, Qinlan and Tongcheng with downward statistically non-significant trend in the other ten areas .Using hypothesis testing, the null hypothesis states that there is no trend and alternative state there is a trend. From the results we reject the null hypothesis within the level of confidence 0.05 and 0.01. The rising rate of precipitation in some months and decreasing in others signifies an overall random pattern in the time series. This result is a part contribution to the effect of Climate change on hydrology and indicates that there is still room for research on the impact of climate change to ensure sustainable development in future.

scholarly journals Influência da Urbanização no Clima da Cidade de Campina Grande-PB (Influence of Urbanization on Climate of the Campina Grande City–PB)

2011 ◽  
Vol 4 (1) ◽  
pp. 134 ◽  
Author(s):  
Francisco de Assis Salviano de Sousa ◽  
Heliene Ferreira de Morais ◽  
Vicente De Paulo Rodrigues da
Keyword(s):  
Time Series ◽  
Relative Humidity ◽  
Air Temperature ◽  
Anthropogenic Activities ◽  
Urban Climate ◽  
Kendall Test ◽  
Annual Rainfall ◽  
Abrupt Changes ◽  
Mann Kendall Test ◽  
Deviation Coefficient

A expansão de cidades produz diversos impactos no ambiente urbano causado por atividades antropogênicas. Este estudo avaliou o efeito da urbanização no clima da cidade de Campina Grande com base em dados mensais de temperatura média do ar, precipitação pluvial, umidade relativa do ar e insolação no período de 1963 a 2004. O método de desvios cumulativos foi utilizado para detectar mudanças abruptas nas séries temporais. Dois períodos de estudo foram estabelecidos: pré-urbano intenso PRÉ-UI (1963-1985) e pós-urbano intenso PÓS-UI (1986-2004). Para cada variável climática foram obtidas estatísticas como: médias, desvio-padrão, coeficiente de variação (CV) e autocorrelação serial. Foram avaliadas as diferenças entre as médias dos períodos PRÉ-UI e PÓS-UI através do teste de t-Student. Também foi usado o teste Mann-Kendall para avaliar as tendências das séries temporais no período total estudado. A temperatura média do ar apresentou tendência crescente, enquanto umidade relativa apresentou tendência decrescente, todas estatisticamente significativas ao nível de 1% através do teste de Mann-Kendall. A série de precipitação pluvial não apresentou tendência estatisticamente significativa. A variabilidade da precipitação pluvial intra-anual, expressa pelo CV, é muito alta e variou de 30 a 89% durante o período analisado. A variabilidade anual da precipitação pluvial é cerca de 30% da variabilidade intra-anual. A temperatura do ar demonstrou persistência natural através dos valores do coeficiente de autocorrelação, para os primeiros lags.Palavras-chave: Clima urbano, Mann-Kendall e variáveis climáticas  Influence of Urbanization on Climate of the Campina Grande City–PB ABSTRACTThe expansion of cities produces different impacts in the urban environment caused by anthropogenic activities. This study evaluated the effect of urbanization on climate of the Campina Grande city based on monthly data of average air temperature, rainfall, relative humidity and sunshine in the period 1963 to 2004. The cumulative deviation method was used to detect abrupt changes in time series. Two study periods were established: intense urban pre-PRE-UI (1963-1985) and after intense urban POST-IU (1986-2004). For each climate variable, statistics were obtained as averages, standard deviation, coefficient of variation (CV) and serial autocorrelation. We evaluated the differences between the mean pre-and post-IU through the IU Student t test. It was also used Mann-Kendall test to assess trends in time series over the entire period studied. The average air temperature showed an ascending trend, while relative humidity showed a declining trend, all statistically significant at 1% through the Mann-Kendall test. The series of rainfall did not show a statistically significant trend. The variability of intra-annual precipitation, expressed as CV, is very high and ranged from 30 to 89% during the period analyzed. The variability of annual rainfall is about 30% of intra-annual variability.The air temperature showed persistence through the natural values the autocorrelation coefficient for the first lags.  Keywords: Urban climate, Mann-Kendall and climatic variables

scholarly journals Tendências e Prognósticos de Chuvas em Seis Microrregiões do Estado da Paraíba (Trends and Forecasts of Rain in Six Regions of Paraíba State)

2011 ◽  
Vol 4 (2) ◽  
pp. 252
Author(s):  
Francisco de Assis Salviano de Sousa ◽  
Heliene Ferreira De Morais ◽  
Vicente de Paulo Rodrigues Da Silva
Keyword(s):  
Time Series ◽  
Prognostic Model ◽  
Kendall Test ◽  
Statistical Test ◽  
The State ◽  
Increasing Trend ◽  
Mann Kendall Test ◽  
Standard Deviations ◽  
The One

Neste trabalho foram utilizadas séries temporais de precipitação pluviométrica de 54 municípios para estimar tendências e prognósticos de chuvas em seis microrregiões do estado da Paraíba, com base no teste estatístico de Mann-Kendall e em modelo prognóstico para cenários com horizontes de 50 e 100 anos. Os maiores valores de desvios-padrão foram registrados na microrregião do Litoral, variando entre 481,4 mm no município de Santa Rita e 601,1 mm em João Pessoa. Os menores ocorreram no Cariri, oscilando entre 189,9 mm em Cabaceiras e 273,3 mm em Monteiro. Observou-se alternância de tendências crescente e decrescente nos vários municípios estudados, com destaque para a microrregião do Brejo que apresentou tendência crescente de chuva em todos os municípios. Quanto aos prognósticos da precipitação, Alhandra, situada na microrregião do Litoral, apresentou os prognósticos mais elevados. Nesse município a estimativa de chuvas para 2050 é de 1791,0 mm e para 2100 é de 1962,6 mm. A microrregião do Cariri foi a que apresentou os menores prognósticos. A estimativa para Picuí em 2050 é de 369,7 mm e para São Sebastião do Umbuzeiro, em 2100 é de 266,5 mm.  Palavras-chave: Teste de Mann-Kendall, modelo prognóstico e precipitação pluvial Trends and Forecasts of Rain in Six Regions of Paraíba State  ABSTRACT In this work we used time series of rainfall of 54 municipalities to estimate trends and forecasts of rain in six regions of the State of Paraíba-based statistical test of Mann-Kendall and prognostic model for scenarios with horizons of 50 and 100 years. The highest values of standard deviations were recorded in the micro region of the Coast, ranging from 481.4 mm in Santa Rita and 601.1 mm in Joao Pessoa. The minors in Cariri, ranging between 189.9 mm and 273.3 mm in Cabaceiras and Monteiro. Observed alternating increasing and decreasing trends in the various districts studied, especially the micro to the Swamp presented increasing trend of rainfall in all municipalities. As for predictions of precipitation, Alhambra, located in the micro region of the Coast had the highest predictions. In this municipality, the estimate for 2050 rainfall is 1791.0 mm and for 2100 is 1962.6 mm. The micro Cariri was the one with the lowest predictions. The estimate for Picuí in 2050 is 369.7 mm and São Sebastião do Umbuzeiro in 2100 is 266.5 mm.  Keywords: Mann-Kendall test, prognostic model and rainfall

scholarly journals Statistical assessment of rainfall variability and trends in northeastern Algeria

2019 ◽  
Vol 40 (1) ◽  
pp. 87-96 ◽  
Author(s):  
Noureddine Merniz ◽  
Ali Tahar ◽  
Amine M. Benmehaia
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Rainfall Variability ◽  
Temporal Trends ◽  
Kendall Test ◽  
Series Data ◽  
Mann Kendall Test ◽  
Slope Estimator ◽  
Northeastern Algeria ◽  
Rainy Days

Abstract In the present study, time series for annual, monthly rainfall and number of rainy days per year were analysed to quantify spatial variability and temporal trends for 22 rainfall stations distributed in northeastern Algeria for the period 1978–2010. The Mann–Kendall test and the Sen’s slope estimator were applied to assess the significance and magnitude of the trend. The results showed that precipitation decreases spatially from North to South and from East to West. The application of the Mann–Kendall test (for 0.05% threshold) to the time series data showed that for annual precipitation, no station showed statistically significant trends, unlike the number of rainy days, where there was a significant negative trend in four stations (Jijel, Constantine, Oum El Bouaghi and Tébessa). For the monthly time series, significant positive trends were observed during the months of September in the coastal stations and July for the plateaus and southern Saharan Atlas stations, while significant negative trends were recorded during the months of February and March for the stations of the extreme East in the study area. These results revealed that for the period analysed, there was no significant climate change in northeastern Algeria but there is a seasonal delay having important agroecological implications.

A simulation study of trend detection methods for integrated ecosystem assessment

2019 ◽  
Vol 76 (7) ◽  
pp. 2060-2069 ◽  
Author(s):  
Sean Hardison ◽  
Charles T Perretti ◽  
Geret S DePiper ◽  
Andrew Beet
Keyword(s):  
Time Series ◽  
Generalized Least Squares ◽  
Kendall Test ◽  
Trend Detection ◽  
Detection Methods ◽  
Times Series ◽  
Model Selection Approach ◽  
Mann Kendall Test ◽  
Ecosystem Level ◽  
Rejection Rates

Abstract The identification of trends in ecosystem indicators has become a core component of ecosystem approaches to resource management, although oftentimes assumptions of statistical models are not properly accounted for in the reporting process. To explore the limitations of trend analysis of short times series, we applied three common methods of trend detection, including a generalized least squares model selection approach, the Mann–Kendall test, and Mann–Kendall test with trend-free pre-whitening to simulated time series of varying trend and autocorrelation strengths. Our results suggest that the ability to detect trends in time series is hampered by the influence of autocorrelated residuals in short series lengths. While it is known that tests designed to account for autocorrelation will approach nominal rejection rates as series lengths increase, the results of this study indicate biased rejection rates in the presence of even weak autocorrelation for series lengths often encountered in indicators developed for ecosystem-level reporting (N = 10, 20, 30). This work has broad implications for ecosystem-level reporting, where indicator time series are often limited in length, maintain a variety of error structures, and are typically assessed using a single statistical method applied uniformly across all time series.

scholarly journals Time Series Modelling of Monthly Temperature and Reference Evapotranspiration for Navsari (Gujarat), India

2019 ◽  
pp. 1-13
Author(s):  
D. K. Dwivedi ◽  
P. K. Shrivastava
Keyword(s):  
Time Series ◽  
Reference Evapotranspiration ◽  
Kendall Test ◽  
Trend Detection ◽  
Positive Trend ◽  
Monthly Temperature ◽  
Mean Temperature ◽  
Time Series Modelling ◽  
Mann Kendall Test ◽  
Past Data

Time series modelling has been proved its usefulness in various fields including meteorology, hydrology and agriculture. It utilizes past data and extracts useful information from them to build up a model which could simulate various processes. The prior knowledge of evapotranspiration could help in estimating the amount of water required by the crops that is useful for optimizing design of irrigation systems. In this study, the time series modelling of monthly temperature and reference evapotranspiration has been carried out utilizing past data of 35 years (1983-2017) to assist decision makers related to agriculture and meteorology. 30 years (1983-2012) of temperature and evapotranspiration data were used for training and remaining 5 years of data (2013-2017) were used for validation. The monthly evapotranspiration was estimated using Penman-Monteith FAO-56 method. Mann-Kendall test was used at 5% significant level for identifying trend component in mean temperature. The time series of temperature and evapotranspiration was made stationary for modelling the stochastic components using ARIMA (Autoregressive Integrated Moving Average) model. In order to check the normality of residuals, the Portmantaeu test was applied. The time series models for temperature and evapotranspiration which were validated for 5 years (2013-2017) and further deployed for forecasting of 5 years (2018-2022). It was found that for modelling temperature and reference evapotranspiration for Navsari, seasonal ARIMA (1,0,0)(0,1,1)12 and seasonal ARIMA (1,0,1)(1,1,2)12 were found to be appropriate models respectively. Mann Kendall test used for trend detection in monthly mean temperature revealed that October and November months had significant positive trend. Negative trend was observed only in the month of June.

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