scholarly journals Trend analysis of time series rainfall data using robust statistics

2017 ◽  
Vol 8 (4) ◽  
pp. 691-700 ◽  
Author(s):  
Arati Paul ◽  
Riddhidipa Bhowmik ◽  
V. M. Chowdary ◽  
Dibyendu Dutta ◽  
U. Sreedhar ◽  
...  
Keyword(s):  
Robust Regression ◽  
Robust Statistics ◽  
Monsoon Season ◽  
Kendall Test ◽  
Negative Trend ◽  
Positive Trend ◽  
Rainfall Analysis ◽  
Mann Kendall Test ◽  
Rainy Days ◽  
Non Parametric

Abstract A temporal rainfall analysis was carried out for the study area, Rajahmundry city located in lower Godavari basin, India, during the period 1960–2013. Both the parametric and non-parametric approaches were envisaged for identifying the trends at different temporal scales. Linear and robust regression analysis revealed a negative trend at weekly scale during monsoon months, but failed to signify the slope at 95% confidence level. The magnitude of Sen's slope was observed to be negative during the months of April–September. Results of the Mann–Kendall test ascertained the negative rainfall trends during the monsoon months of June and July with a significant trend at 95% confidence interval. Application of robust statistics for long-term rainfall analysis helped to address the outlier's problem in the dataset. The Mann–Kendall test rejected the null hypothesis for all months except February–May and August after exclusion of outliers. Overall, a negative trend during monsoon season and a positive trend during post-monsoon season were observed using a robust non-parametric approach. Further, good correlation was found between the total rainfall and rainy days during the study period. On average, 21.25% days of a year is considered as rainy, while heavy and extreme rainfall in this region together occupies nearly 15% of the rainy days.

scholarly journals Temporal Analysis of Temperature and Precipitation Trends in Shaheed Benazir Abad Sindh, Pakistan

2017 ◽  
Vol 7 (6) ◽  
pp. 2171-2176 ◽  
Author(s):  
S. R. Samo ◽  
N. Bhatti ◽  
A. Saand ◽  
M. A. Keerio ◽  
D. K. Bangwar
Keyword(s):  
Diurnal Temperature Range ◽  
Kendall Test ◽  
Maximum Temperature ◽  
Linear Regression Method ◽  
Positive Trend ◽  
Diurnal Temperature ◽  
Temperature Range ◽  
Temperature And Precipitation ◽  
Mann Kendall Test ◽  
Rainy Days

Temperature and precipitation variations have a huge environmental, social and economic impact. This study aims to analyze the temporal variation of temperature and precipitation in Shaheed Benazir Abad district by using the linear regression method, the trend magnitude, the Mann-Kendall test and the Sen’s estimator of slope. The annual precipitation and monthly temperature data of Shaheed Benazir Abad for the period of 1996-2014 are considered. The result shows that the Diurnal temperature range of all months is decreasing due to the increasing of monthly minimum temperature at a faster rate than the monthly maximum temperature. However, the Diurnal temperature range of extreme events is increasing. The results obtained by using Mann-Kendall test revealed that rainfall exhibits significant positive trend. The trends of rainfall and rainy days show that the amount of rainfall is increasing much more rapidly than that of rainy days which indicates the occurrence of heavy events.

scholarly journals Trend Detection in Rainfall and Temperature Data [1960-2014] of Anand, Gujrat, India

2021 ◽  
pp. 125-133
Author(s):  
S. S. Chinchorkar ◽  
G. J. Kamani
Keyword(s):  
Linear Trend ◽  
Monsoon Season ◽  
Meteorological Data ◽  
Weather Conditions ◽  
Kendall Test ◽  
Trend Detection ◽  
Growth Stages ◽  
Climate Risks ◽  
Mann Kendall Test ◽  
Rainy Days

The temperature and rainfall trends are analyzed for meteorological data of Anand in Gujarat, India over approximately last three decades stretching between years 1960 to 2014. The long–term change in temperature and rainfall has been assessed by linear trend analysis. Due to their biophysical characteristics, dry lands ecosystems are most Vulnerable the Climate risks. Climate variability has serious implications on major livelihoods of the region i.e. Agriculture and livestock. In this paper, attempts have been made to study variations in temperature and rainfall in Anand of Gujarat, India. Data at annual, seasonal and monthly time scales for the period of 1960-2014 (Temperature) and 1960-2014 (Rainfall) were examined. Study of monthly variations revealed rise in the temperatures in the month of September. Rainfall and Rainy days have also increased in past 4 decades. Annual and Monsoon rainfall have been observed to increase, where the month of August shows a statistically significant increasing trend. Any variability in monsoon season will have implications on agricultural activities as the season overlaps with Kharif, a major cropping season for the country. The variations of temperature and rainfall during monsoons may have impacts on the various growth stages of the crops. Changing weather conditions may lead to increase in pest infestations. Macro level studies may or may not be relevant at village level and therefore the advisories generated may not benefit the locals. Trends in temperature, rainfall and rainy days have been assessed by Non-parametric tests (Mann-Kendall or Pre Whitened Mann-Kendall test for trend detection and Theil and Sen's Slope for magnitude of trend). Temperature and Rainfall variations, Climate Change, Mann-Kendall Test.

scholarly journals Innovative Trend Analysis of Precipitation in the Lake Issyk-Kul Basin, Kyrgyzstan

Atmosphere ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 332 ◽  
Author(s):  
Yilinuer Alifujiang ◽  
Jilili Abuduwaili ◽  
Balati Maihemuti ◽  
Bilal Emin ◽  
Michael Groll
Keyword(s):  
Trend Analysis ◽  
Resource Planning ◽  
Kendall Test ◽  
Trend Test ◽  
Lake Basin ◽  
Positive Trend ◽  
Monthly Precipitation ◽  
Innovative Trend Analysis ◽  
Mann Kendall Test ◽  
Increasing Trends

The analysis of various characteristics and trends of precipitation is an essential task to improve the utilization of water resources. Lake Issyk-Kul basin is an upper alpine catchment, which is more susceptible to the effects of climate variability, and identifying rainfall variations has vital importance for water resource planning and management in the lake basin. The well-known approaches linear regression, Şen’s slope, Spearman’s rho, and Mann-Kendall trend tests are applied frequently to try to identify trend variations, especially in rainfall, in most literature around the world. Recently, a newly developed method of Şen-innovative trend analysis (ITA) provides some advantages of visual-graphical illustrations and the identification of trends, which is one of the main focuses in this article. This study obtained the monthly precipitation data (between 1951 and 2012) from three meteorological stations (Balykchy, Cholpon-Ata, and Kyzyl-Suu) surrounding the Lake Issyk-Kul, and investigated the trends of precipitation variability by applying the ITA method. For comparison purposes, the traditional Mann–Kendall trend test also used the same time series. The main results of this study include the following. (1) According to the Mann-Kendall trend test, the precipitation of all months at the Balykchy station showed a positive trend (except in January (Zc = −0.784) and July (Zc = 0.079)). At the Cholpon-Ata and Kyzyl-Suu stations, monthly precipitation (with the same month of multiple years averaged) indicated a decreasing trend in January, June, August, and November. At the monthly scale, significant increasing trends (Zc > Z0.10 = 1.645) were detected in February and October for three stations. (2) The ITA method indicated that the rising trends were seen in 16 out of 36 months at the three stations, while six months showed decreasing patterns for “high” monthly precipitation. According to the “low” monthly precipitations, 14 months had an increasing trend, and four months showed a decreasing trend. Through the application of the ITA method (January, March, and August at Balykchy; December at Cholpon-Ata; and July and December at Kyzyl-Suu), there were some significant increasing trends, but the Mann-Kendall test found no significant trends. The significant trend occupies 19.4% in the Mann-Kendall test and 36.1% in the ITA method, which indicates that the ITA method displays more positive significant trends than Mann–Kendall Zc. (3) Compared with the classical Mann-Kendall trend results, the ITA method has some advantages. This approach allows more detailed interpretations about trend detection, which has benefits for identifying hidden variation trends of precipitation and the graphical illustration of the trend variability of extreme events, such as “high” and “low” values of monthly precipitation. In contrast, these cannot be discovered by applying traditional methods.

scholarly journals Temporal Trend Analysis of Historical Climatic Data at Northeastern Hilly Region of Bangladesh Using Mann-Kendall Test

2020 ◽  
Vol 11 (2) ◽  
pp. 19-25
Author(s):  
KK Mondal ◽  
Md AE Akhter ◽  
MAK Mallik
Keyword(s):  
Temporal Trend ◽  
Monsoon Season ◽  
Kendall Test ◽  
Climatic Data ◽  
Total Rainfall ◽  
The North ◽  
Positive Tendency ◽  
Hilly Region ◽  
North Eastern ◽  
Mann Kendall Test

An attempt has been implemented to find out the temporal trend of climatic data of average temperature and total rainfall for the study period 1980-2016 at North-Eastern Hilly Region in Bangladesh. The non-parametric Mann-Kendall test is used to analyze the trend of climatic data. The objective of the study is to investigate the trend variation in the North-Eastern hilly region. Results show that in monsoon season, both Sylhet and Srimangal meteorological stations experience a positive tendency with a rate of 0.037 and 0.0170C/year, respectively which are statistically significant at 99.9% level of significance. Monthly significant positive changes are found in all months except November, December and January for Sylhet while Srimangal indicates significant positive changes except July, September, October and November. The total rainfall at both the stations reveals decreasing trend during maximum seasons and months but the trend is not significant. Journal of Engineering Science 11(2), 2020, 19-25

scholarly journals Analysis of rainfall trends over Tripura

MAUSAM ◽  
2022 ◽  
Vol 73 (1) ◽  
pp. 27-36
Author(s):  
RANJAN PHUKAN ◽  
D. SAHA
Keyword(s):  
Heavy Rainfall ◽  
Monsoon Season ◽  
Rainfall Variability ◽  
Kendall Test ◽  
Annual Rainfall ◽  
The North ◽  
Rainfall Trends ◽  
Annual Scale ◽  
Increasing Trends ◽  
Rainy Days

Rainfall in India has very high temporal and spatial variability. The rainfall variability affects the livelihood and food habits of people from different regions. In this study, the rainfall trends in two stations in the north-eastern state of Tripura, namely Agartala and Kailashahar have been studied for the period 1955-2017. The state experiences an annual mean of more than 2000 mm of rainfall, out of which, about 60% occurs during the monsoon season and about 30% in pre-monsoon. An attempt has been made to analyze the trends in seasonal and annual rainfall, rainy days and heavy rainfall in the two stations, during the same period.Non-parametric Mann-Kendall test has been used to find out the significance of these trends. Both increasing and decreasing trends are observed over the two stations. Increasing trends in rainfall, rainy days and heavy rainfall are found at Agartala during pre-monsoon season and decreasing trends in all other seasons and at annual scale. At Kailashahar, rainfall amount (rainy days & heavy rainfall) is found to be increasing during pre-monsoon and monsoon seasons (pre-monsoon season). At annual scale also, rainfall and rainy days show increasing trends at Kailashahar. The parameters are showing decreasing trends during all other seasons at the station. Rainy days over Agartala show a significantly decreasing trend in monsoon, whereas no other trend is found to be significant over both the stations.  

scholarly journals Rainfall trend analysis

2021 ◽  
Vol 17 (1) ◽  
pp. 121-125
Author(s):  
Virendra N. Barai ◽  
Rohini M. Kalunge
Keyword(s):  
Trend Analysis ◽  
Kendall Test ◽  
River Basins ◽  
Annual Rainfall ◽  
Positive Trend ◽  
Rainfall Trend ◽  
Trend Magnitude ◽  
Increasing Trends ◽  
Multiple Units ◽  
Rainy Days

This article aims to review studies pertaining to trends in rainfall, rainy days over India. Non-parametric tests such as Sen’s Slope were used as estimator of trend magnitude which was supported by Mann-Kendall test. The findings of various studies indicate variance with respect to the rainfall rate, which contributes to an uncertain picture of the rainfall trend. In the study of monsoon of different locations in India some places showed increasing trends however, there is signifying decrease in trend all over India. It was also mentioned that analysis can vary from for a location if done using different source or types of collection of data. Spatial units range from station results and sub-division to sub-basin/river basins for trend analysis. The outcomes of the different experiments vary and a simple and reliable picture of the trend of rainfall has not appeared. While there can be a non-zero slope value for the multiple units (sub-basins or sub-divisions), few values are statistically important. In a basin-wise trend analysis report, some basins had a declining annual rainfall trend; at a 95 per cent confidence stage, only one basin showed a strong decreasing trend. Out of the six basins exhibiting a rising trend saw a major positive trend in one basin. Many of the basins have the same pattern direction on the annual and seasonal scale for rainfall and rainy days.

scholarly journals Trend analysis of weather parameters over Indian Sundarbans

2021 ◽  
Vol 21 (3) ◽  
pp. 307-615
Author(s):  
UTTAM KUMAR MANDAL ◽  
DIBYENDU BIKAS NAYAK ◽  
SOURAV MULLICK ◽  
ARPAN SAMUI ◽  
AMIT KUMAR JANA ◽  
...  
Keyword(s):  
Monsoon Season ◽  
Temporal Trends ◽  
Kendall Test ◽  
Eastern Coast ◽  
Annual Rainfall ◽  
Crop Evapotranspiration ◽  
Indian Sundarbans ◽  
Sunshine Hours ◽  
Weather Parameters ◽  
Rainy Days

Sundarbans in West Bengal of India by virtue of its strategic location in the Eastern coast on the Bay of Bengal falls in one of the most vulnerable zones of abrupt climate change. Temporal trends of weather parameters of Canning Town (22o18'10.8'' N Latitude, 88o39'58.4'' E Longitude, elevation 3.52 m msl) representing Indian Sundarbans were analysed by non-parametric Mann-Kendall test and Sen's slope approaches. Analysis of long term rainfall data (1966-2015) indicated that Canning receives a mean annual rainfall of 1821 mm (±341.8 mm) with a considerable variation (CV = 18.8%). The results revealed that total annual rainfall trend decreased non-signicantly at the rate of 0.94 mm yr-1. On an average 84.4 rainy days in a year was recorded in the region, whereas during last ten years (2006-2015), the number of rainy days was reduced to 79.7 days yr-1. There was no signicant change in maximum, minimum and mean temperature of the region. Bright sunshine hours declined signicantly at an annual rate of 0.055 hr yr-1. Reference crop evapotranspiration (ET ) calculated using FAO Penman-Monteith method revealed that annual ET signicantly decreased at the rate of 5.98 mm yr-1. There was 2.7 times surplus rainfall than  crop evapotranspiration during monsoon months indicating very high scope of water harvesting to tackle water logging during the monsoon season and unavailability of fresh water for irrigation during lean season.

scholarly journals Fitting and testing the significance of linear trends in Gumbel-distributed data

2002 ◽  
Vol 6 (1) ◽  
pp. 17-24 ◽  
Author(s):  
R. T. Clarke
Keyword(s):  
Maximum Likelihood ◽  
Linear Regression ◽  
Gumbel Distribution ◽  
Kendall Test ◽  
Mean Value ◽  
Return Periods ◽  
Testing Procedures ◽  
Mann Kendall Test ◽  
Linear Trends ◽  
Non Parametric

Abstract. The widely-used hydrological procedures for calculating events with T-year return periods from data that follow a Gumbel distribution assume that the data sequence from which the Gumbel distribution is fitted remains stationary in time. If non-stationarity is suspected, whether as a consequence of changes in land-use practices or climate, it is common practice to test the significance of trend by either of two methods: linear regression, which assumes that data in the record have a Normal distribution with mean value that possibly varies with time; or a non-parametric test such as that of Mann-Kendall, which makes no assumption about the distribution of the data. Thus, the hypothesis that the data are Gumbel-distributed is temporarily abandoned while testing for trend, but is re-adopted if the trend proves to be not significant, when events with T-year return periods are then calculated. This is illogical. The paper describes an alternative model in which the Gumbel distribution has a (possibly) time-variant mean, the time-trend in mean value being determined, for the present purpose, by a single parameter β estimated by Maximum Likelihood (ML). The large-sample variance of the ML estimate ˆβMR is compared with the variance of the trend βLR calculated by linear regression; the latter is found to be 64% greater. Simulated samples from a standard Gumbel distribution were given superimposed linear trends of different magnitudes, and the power of each of three trend-testing procedures (Maximum Likelihood, Linear Regression, and the non-parametric Mann-Kendall test) were compared. The ML test was always more powerful than either the Linear Regression or Mann-Kendall test, whatever the (positive) value of the trend β; the power of the MK test was always least, for all values of β. Keywords: Extreme value probability distribution, Gumbel distribution, statistical stationarity, trend-testing procedures

scholarly journals Non-Parametric and Parametric Analysis of Runoff in Satluj River Basin, Himachal Pradesh, India

2015 ◽  
Vol 54 ◽  
pp. 15-36
Author(s):  
Sandeep Kumar ◽  
Santosh
Keyword(s):  
River Basin ◽  
Missing Values ◽  
Monsoon Season ◽  
Linear Regression Analysis ◽  
Kendall Test ◽  
Data Series ◽  
Annual Series ◽  
Daily Data ◽  
Satluj River ◽  
Non Parametric

Testing the significance of observed trends in hydrological time series has received a great attention recently, especially in connection with climate change. The changing pattern of runoff deserves urgent and systematic attention over a basin for planning, development, utilisation and management of water resources. Therefore, one large catchment i.e. Indian part of Satluj River Basin is selected for the present study. The daily data of runoff were converted to monthly and then computed to seasonal and annual series. The missing values in the data were computed by using average method. For better understanding of the observed trends, data were computed into standardised runoff indices (SDI). These standardised data series were plotted against time and the linear trends observed were represented graphically. The records of runoff were subjected to trend analysis by using both non-parametric (Mann-Kendall test) and parametric (linear regression analysis) procedures.Trend analysis results of runoff show that out of 8 annual trends 2 (25%) are statistically insignificant increasing and 6 (75%) are decreasing in nature where 2 (25%) are statistically significant at 95% confidence level. Apart from annual, the changes were investigated for the four seasons: winter (December-March), pre-monsoon (April-June), monsoon (July-September) and post-monsoon (October-November). The analysis of annual as well as seasonal runoff for the Satluj River Basin indicates significant changes from 1984 to 2010. There is a clear contrast in the runoff pattern of river between the high altitude mountainous region and the lower reaches where it changes as a result of contribution from rainfall, especially during monsoon season. Although the runoff at majority of stations showed decreasing trend, but very few are statistically significant. Such studies help us to resolve potential issues associated with availability of water for agriculture, industry, hydropower, domestic use etc.

Analysis of Meteorological Elements Variations of Chongqing over the Past 60 Years

2014 ◽  
Vol 501-504 ◽  
pp. 2016-2019
Author(s):  
Xun Jian Long ◽  
Chun Min Zhang ◽  
Tao Hong Yang ◽  
Yu Lin Huang
Keyword(s):  
Wind Speed ◽  
Sunshine Duration ◽  
Kendall Test ◽  
Trend Detection ◽  
Annual Data ◽  
Annual Variations ◽  
Mann Kendall Test ◽  
Mean Wind Speed ◽  
Meteorological Elements ◽  
Non Parametric

The power of a test is the probability that it cannot reject a null hypothesis when it is true. With interchangeably of non-parametric Mann-Kendall test, practical application is used in meteorological elements analysis. In this study, trend detection of meteorological elements data of Shapingba district in Chongqing, during 1951 to 2011, was estimated by non-parametric Mann-Kendall test. The analyzed elements are composed by mean precipitation, annual sunshine hours, annual humidity, annual mean temperature and annual mean wind speed. And the results show that inter-annual variations of precipitation and mean annual relative humidity are not significant. However, inter-annual variation of sunshine duration is significantly reduced, while inter-annual temperature and wind speed are significantly increased. At the same time, the non-parametric Mann-Kendall test also detects the trend on seasonal data. It is different from the annual data, and trends in different seasons show markedly different.

Sign in / Sign up

Export Citation Format

Share Document