MANN-KENDALL TEST: TREND ANALYSIS OF TEMPERATURE, RAINFALL AND DISCHARGE OF GHOTKI FEEDER CANAL IN DISTRICT GHOTKI, SINDH, PAKISTAN

2021 ◽  
Vol 5 (2) ◽  
pp. 137-142
Author(s):  
Shoukat Ali Shah ◽  
Madeeha Kiran
Keyword(s):  
Continuous Flow ◽  
Heavy Rainfall ◽  
Monsoon Season ◽  
Kendall Test ◽  
Annual Rainfall ◽  
Rainfall Trend ◽  
Rabi Season ◽  
Significance Level ◽  
Average Temperature ◽  
Temperature And Precipitation

Temperature and precipitation variations have huge environmental, socio-economic impacts. This study aims to detect the trend of temperature, precipitation, and discharge from 2000-2020 in the district Ghotki. Mann Kendal test and Sen’s slope were applied by using XLSTAT in MS Excel to investigate the significance of all trends. The results showed that the annual rainfall trend was increased with the highest intensity noted in 2003; 275mm and 2010; 271 mm. The trend in the monsoon season was increased with the highest slope 0.863 by comparing with non-monsoon which showed the slope was 0.642. The annual temperature was increased an average temperature recorded in 2016; 28.5 & 2018; 28 °C. Further, the summer-autumn season’s trend has sharply increased. While the trend of Ghotki feeder discharge was slightly increased in January due to the continuous flow of water and less demand for water during the Rabi season. But in July, the highest discharge was recorded in 2010 due to heavy rainfall and flood situations over the study area. The trend in Kharif was continuously declined due to farmers started sowing sugarcane crops instead of rice and cotton which need less irrigation water. It is concluded that the performance of MK and SS tests was consistent at the verified significance level.

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 Kecenderungan dan Perubahan Hujan Ekstrem Harian di Pulau Madura

2020 ◽  
Vol 18 (1) ◽  
pp. 89-96
Author(s):  
Ahmad Nur Akma Juangga Fura ◽  
Retno Utami Agung Wiyono ◽  
Indarto Indarto
Keyword(s):  
Flood Hazard ◽  
Parametric Method ◽  
Extreme Rainfall ◽  
Kendall Test ◽  
Random Processes ◽  
Rain Gauge ◽  
Rainfall Trend ◽  
Significance Level ◽  
High Level ◽  
Crossing Test

Madura subject to a high level of flood hazard. One of the main causes of flood is extreme rainfall. Global warming generates changes in the amount of extreme rainfall. This research is conducted to identify and to analyze the trends, changes, and randomness of 24-hour extreme rainfall data on Madura Island. The method used is a non-parametric method which includes the Median Crossing test, the Mann-Kendall test, and the Rank-Sum test at the significance level of α =0.05. The analysis was carried out on 31 rain gauge stations. The recording period observed is between 1991-2015. The results of the analysis show that based on the Median Crossing test, most rainfall stations have data originating from random processes. The result shows also that the maximum 24-hour extreme rainfall trend is significantly decreased in a few locations, while for the majority of other stations have no experience a significant trend.

scholarly journals Study of rainfall features over Goa state during southwest monsoon season

MAUSAM ◽  
2021 ◽  
Vol 61 (2) ◽  
pp. 155-162
Author(s):  
S. M. METRI ◽  
KHUSHVIR SINGH
Keyword(s):  
Heavy Rainfall ◽  
Monsoon Season ◽  
Southwest Monsoon ◽  
Annual Rainfall ◽  
Statistical Parameters ◽  
Maximum Rainfall ◽  
Rainfall Events ◽  
Average Rainfall ◽  
Southwest Monsoon Season ◽  
Heavy Rainfall Events

In this paper the rainfall features at different raingauge stations of Goa state have been studied for the period of 30 years. The statistical parameters such as mean monthly rainfall, Standard Deviation and Coefficient of Variation have been computed for each raingauge station of Goa. Some heavy rainfall events during the period have also been studied. The study shows the significant rising trend of rainfall towards the eastern parts of Goa. Goa experiences an average rainfall of about 330 cm annually and around 90% of annual rainfall occurs during southwest monsoon season i.e. (June to September). Studies revealed that most of heavy rainfall events caused due to active off-shore trough and low pressure systems formed over southeast Arabian Sea. It has also come out from the study that the orography of Goa plays an important role in rainfall distribution. Valpoi receives maximum rainfall due to its orographic effect.

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 Modeling and Trend Analysis of Climatic Variables of Ranchi District, Jharkhand

2021 ◽  
Vol 8 (2) ◽  
pp. 120-128
Author(s):  
PAWAN JEET ◽  
KN SINGH ◽  
RAJEEV RANJAN KUMAR ◽  
BISHAL GURANG ◽  
AK SINGH ◽  
...  
Keyword(s):  
Minimum Temperature ◽  
Monsoon Season ◽  
Arima Model ◽  
Climatic Variables ◽  
Annual Rainfall ◽  
Annual Maximum ◽  
Rainfall Trend ◽  
Average Rainfall ◽  
Increasing Trend

In this paper, an attempt has been made to study the temporal variation in monthly, seasonal and annual rainfall, and average annual maximum and minimum temperature for the period 1901-2015 over Ranchi district of Jharkhand, India. Long-term changes in rainfall, temperature was determined by Man-Kendall rank statistics and Sen’s slope, and forecasting of time series was determined by ARIMA model. The results revealed that there was significant decrease of average rainfall in the month of February and August while increase in month May and Pre-monsoon season. Average rainfall in the month of February, May, August and Pre-monsoon season showing insignificant increasing as well as decreasing rainfall trend. The average annual maximum and minimum temperature showing decreasing and increasing trend over Ranchi district during the period 1901 to 2015. This paper also describes five-year prediction of rainfall and temperature climatic variables.

scholarly journals Rainfall trend analysis and weather forecast accuracy in selected parts of Khyber Pakhtunkhwa, Pakistan

2021 ◽  
Vol 3 (5) ◽  
Author(s):  
Fakhri Alam ◽  
Muhammad Salam ◽  
Nasir Ahmad Khalil ◽  
Owais khan ◽  
Masaud Khan
Keyword(s):  
Climate Change ◽  
Trend Analysis ◽  
Forecast Accuracy ◽  
Weather Forecast ◽  
Kendall Test ◽  
Annual Rainfall ◽  
Rainfall Trend ◽  
Khyber Pakhtunkhwa ◽  
Temperature Records ◽  
Nonparametric Techniques

AbstractClimate change is a multidimensional phenomenon, which has various effects on people's environmental and socioeconomic conditions. In the agricultural economy that is susceptible to natural changes, its impact is more profound. Therefore, climate change directly affects society in different ways, and society must pay a price. Climate change, especially the changes in annual temperature and rainfall, has attracted widespread attention worldwide. The variability of these factors or the magnitude of fluctuations varies according to location. Therefore, in the context of climate change, especially in countries dominated by rainfed agriculture, studying the trend of meteorological variables is essential to assess climate-induced variations and propose feasible adaptation approaches. Focusing on this fact is the main goal of this research study was to determine the rainfall trend and the accuracy of predicted temperature at three particular stations of Khyber Pakhtunkhwa (Kp) Province, Pakistan. For this purpose, rainfall and temperature data were provided by Pakistan Meteorological Department (PMD), Islamabad, for the period 1960–2020. Two types of nonparametric techniques, Sen’s slope estimate and the Mann–Kendall test, were applied to determine a trend in the average monthly and annual rainfall. The results of the annual rainfall trend analysis showed that Peshawar and Dera Ismail Khan stations showed a positive increasing trend, while the monthly rainfall trend showed a negative decreasing trend for all stations. The trend was statistically significant for Peshawar and Saidu Sharif stations. The accuracy of predicted and actual temperature and rainfall indicated that mostly over-forecast occurred at Saidu Sharif and Peshawar. Most of the precipitation and temperature records showed under forecast for Dera Ismail Khan, but some over-prediction has also occurred. Graphical abstract

scholarly journals Trend Analysis of Precipitation and Temperature over Different Districts of Karnataka: An Aid to Climate Change Detection and Cropping System Option

2020 ◽  
pp. 15-25
Author(s):  
S. Sridhara ◽  
Pradeep Gopakkali ◽  
R. Nandini
Keyword(s):  
Minimum Temperature ◽  
Monsoon Season ◽  
Cropping System ◽  
Weather Conditions ◽  
Kendall Test ◽  
Annual Rainfall ◽  
Maximum Temperature ◽  
Land Preparation ◽  
Mk Test ◽  
Increasing Trend

Aims: To know the rainfall and temperature trend for all the districts of Karnataka state to develop suitable coping mechanisms for changing weather conditions during the cropping season. Study Design: The available daily data of rainfall (1971-2011) and minimum and maximum temperature (1971-2007) for each district was collected from NICRA-ICAR website. A non-parametric model such as the Mann-Kendall (MK) test complemented with Sen’s slope estimator was used to determine the magnitude of the trend. Place and Duration of Study: The rainfall data of 41 years (1971-2011) and temperature data of 37 years (1971-2007) was collected for all 27 districts of Karnataka. Methodology: Basic statistics related to rainfall like mean, standard deviation (SD), the coefficient of variation (CV) and the percentage contribution to annual rainfall were computed for monthly and season-wise. Mann-Kendall test was used to detect trend for rainfall as well as temperature. Results: An increasing trend in rainfall during winter, monsoon and annual basis for all most all the districts of Karnataka and decreasing trend of rainfall during pre and post-monsoon season was noticed. An early cessation of rainfall during September month in all most all the districts of Karnataka was observed. Similarly, monthly mean, maximum and the minimum temperature had shown an increasing trend over the past 37 years for all the districts of Karnataka. Conclusion: The more variation in rainfall during the pre-monsoon season was observed, which is more important for land preparation and other operations. The increasing trend of maximum and minimum temperature throughout the year may often cause a reduction in crop yield. It is necessary to change crops with its short duration varieties in order to avoid late season drought.

scholarly journals Spatial Characteristics of Flooded Areas in the Mun and Chi River Basins in Northeastern Thailand

2019 ◽  
Vol 14 (9) ◽  
pp. 1337-1345 ◽  
Author(s):  
Shingo Zenkoji ◽  
Shigehiko Oda ◽  
Taichi Tebakari ◽  
Boonlert Archevarahuprok ◽  
◽  
...  
Keyword(s):  
Extreme Value Distribution ◽  
Kendall Test ◽  
Generalized Extreme Value Distribution ◽  
Annual Rainfall ◽  
Spatial Characteristics ◽  
Significance Level ◽  
Inundation Area ◽  
Inundation Depth ◽  
Rainfall Change

The objectives of this study are to conduct an analysis on rainfall change tendencies, calculate the inundation in the basins of Mun and Chi Rivers in the northeastern region of Thailand, and clarify the flood risk in the long term, taking the spatial characteristics of flooding into consideration. To grasp the rainfall change tendencies, two statistical analyses are conducted using the Mann-Kendall test and the generalized extreme value distribution. The inundation analysis is conducted using the Rainfall-Runoff-Inundation (RRI) model. As a result of the statistical analysis on the rainfall characteristics, it can be observed that the annual rainfall has significant increasing tendencies at the significance level of 5% in a wide area of the upper reaches. In addition, inundation calculation indicates that the maximum inundation depth and inundation area have increased in recent years.

scholarly journals Análise da Variação Sazonal e de Tendências na Precipitação Pluviométrica no Município de Juazeiro-BA

2020 ◽  
Vol 13 (6) ◽  
pp. 2641
Author(s):  
Henrique Santos Junqueira ◽  
Luan Moreira Fernandes de Almeida ◽  
Tailan Santos de Souza ◽  
Patricia Dos Santos Nascimento
Keyword(s):  
Agricultural Development ◽  
Kendall Test ◽  
Annual Rainfall ◽  
Rainfall Trend ◽  
Rainy Period ◽  
Precipitation Concentration Index ◽  
A Value ◽  
Daily Series ◽  
Climate Series ◽  
Kendall Method

A cidade de Juazeiro-BA destaca-se por ser um importante polo de desenvolvimento agrícola em bases irrigadas no Nordeste, no qual a distribuição sazonal da precipitação pluviométrica tem influência decisiva no contexto da relação saúde e saneamento em áreas urbanizadas, na agricultura familiar, no abastecimento de água de famílias isoladas e na economia dessa região. Assim, essa pesquisa tem como objetivo avaliar a distribuição das chuvas no município de Juazeiro-BA, analisando uma série diária de 32 anos de dados pluviométricos, calculando os valores anuais e sazonais do Índice de Concentração da Precipitação (ICP) e realizando um estudo de tendência da precipitação pluviométrica, a partir do método de Mann-Kendall. Os resultados revelaram que, em Juazeiro, o período chuvoso é bem definido, com os maiores índices de precipitação entre os meses de dezembro e março. O ICP anual tem o valor de 28,48 %, indicando alta irregularidade na distribuição das chuvas anuais, possibilitando a ocorrência de eventos extremos, tanto de inundações quanto de escassez hídrica. O teste de Mann-Kendall, para o período em estudo, apresentou tendência de diminuição da média pluviométrica anual em 7,51 mm, o que pode aumentar o déficit hídrico na região.Palavras-chave: Chuvas; Séries Climáticas; Concentração Pluviométrica; Mann-Kendall. Seasonal Variation and Trend in Rainfall in the Municipality of Juazeiro-BA A B S T R A C TThe city of Juazeiro-BA stands out for being an important agricultural development hub on irrigated bases in the Northeast, in which the seasonal distribution of pluviometric precipitation has a decisive influence in the context of the health and sanitation relationship in urbanized areas, in family agriculture, in water supplying of isolated families and the economy of that region. Thus, this research aims to assess the distribution of rainfall in the municipality of Juazeiro-BA, analyzing a daily series of 32 years of rainfall data, calculating the annual and seasonal values of the Precipitation Concentration Index (PCI) and conducting a rainfall trend study, using the Mann-Kendall method. The results revealed that, in Juazeiro, the rainy period is well defined, with the highest levels of precipitation between the months of December and March. The annual PCI has a value of 28.48 %, indicating a high irregularity in the distribution of annual rainfall, enabling the occurrence of extreme events, both floods and water scarcity. The Mann-Kendall test, for the period under study, presented tendency decrease of the annual rainfall average by 7.51 mm, which may increase the water deficit in the region.Keywords: Rainfall; Climate Series; Rain Concentration; Mann-Kendall.

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