Long-Term Homogeneity, Trend, and Change-Point Analysis of Rainfall in the Arid District of Ananthapuramu, Andhra Pradesh State, India

Patakamuri, Sandeep Kumar; Muthiah, Krishnaveni; Sridhar, Venkataramana

doi:10.3390/w12010211

Cited by 95 publications

(70 citation statements)

References 69 publications

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“…Since the results of the MK test are likely to be affected by the presence of autocorrelation in a time series data, a serial correlation test was carried out before the MK. This was done by computing the lag-1 serial correlation coefficient r 1 for a two-tailed test at a 5% significance level [27,33]:…”

Section: Mann-kendall Test and Sen's Slope Methodsmentioning

confidence: 99%

“…Thus, the Trend-Free Pre-Whitening (TFPW) [34] approach which is a modified MK test was used. The R package "modifiedmk" [27] was used to perform the above mentioned non-parametric tests.…”

Section: Mann-kendall Test and Sen's Slope Methodsmentioning

confidence: 99%

“…When a p-value is lower than the significance level 5%, one should reject H0 and accept Ha. To evaluate the results of these four tests, we made a classification based on the number of tests rejecting H0 [26][27][28]. They are (i) Class [24] and Von Neumann's Ratio Test (VNRT) [25] at a 5% significance level were used to assess the homogeneity of the monthly and annual time series of R, T max and T min .…”

Section: Study Area and Data Collectionmentioning

confidence: 99%

“…When a p-value is lower than the significance level 5%, one should reject H 0 and accept Ha. To evaluate the results of these four tests, we made a classification based on the number of tests rejecting H 0 [26][27][28] . They are (i) Class A which stands for "Useful"-when none or only one of the above four tests rejects H 0 ; (ii) Class B which represents "Doubtful"-when two of the four tests reject H 0 ; and (iii) Class C which is "Suspect"-when three or all the tests reject H 0 .…”

Section: Study Area and Data Collectionmentioning

confidence: 99%

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Rainfall and Temperature Trend Analysis by Mann–Kendall Test and Significance for Rainfed Cereal Yields in Northern Togo

Gadédjisso-Tossou¹,

Adjegan²,

Kablan³

2020

Sci

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This study investigates the trend in monthly and annual rainfall, minimum and maximum temperature (Tmin and Tmax) using the Mann–Kendall (MK) test and Sen’s slope (SS) method and evaluates the significance of their variability for maize, sorghum and millet yields in northern Togo employing multiple regression analysis. The historical data of Kara, Niamtougou, Mango and Dapaong weather stations from 1977 to 2012 were used. Four non-parametric methods—Alexandersson’s Standard Normal Homogeneity Test (SNHT), Buishand’s Range Test (BRT), Pettitt’s Test (PT) and Von Neumann’s Ratio Test (VNRT)—were applied to detect homogeneity in the data. For the data which were serially correlated, a modified version of the MK test (pre-whitening) was utilised. Results showed an increasing trend in the annual rainfall in all four locations. However, this trend was only significant at Dapaong (p < 0.1). There was an increasing trend in Tmax at Kara, Mango and Niamtougou, unlike Dapaong where Tmax revealed a significant decreasing trend (p < 0.01). Similarly, there was an increasing trend in Tmin at Kara, Mango and Dapaong, unlike Niamtougou where Tmin showed a non-significant decreasing trend (p > 0.05). Rainfall in Dapaong was found to have increased (7.79 mm/year) more than the other locations such as Kara (2.20 mm/year), Niamtougou (4.57 mm/year) and Mango (0.67 mm). Tmax increased by 0.13, 0.13 and 0.32 °C per decade at Kara, Niamtougou and Mango, respectively, and decreased by 0.20 per decade in Dapaong. Likewise, Tmin increased by 0.07, 0.20 and 0.02 °C per decade at Kara, Mango and Dapaong, respectively, and decreased by 0.01 °C per decade at Niamtougou. Results of multiple regression analysis revealed nonlinear yield responses to changes in rainfall and temperature. Rainfall and temperature variability affects rainfed cereal crops production, but the effects vary across crops. The temperature has a positive effect on maize yield in Kara, Niamtougou and Mango but a negative effect on sorghum in Niamtougou and millet in Dapaong, while rainfall has a negative effect on maize yield in Niamtougou and Dapaong and millet yield in Mango. In all locations, rainfall and temperature variability has a significant effect on the cereal crop yields. There is, therefore, a need to adopt some adaptation strategies for sustainable agricultural production in northern Togo.

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Section: Mann-kendall Test and Sen's Slope Methodsmentioning

confidence: 99%

“…Thus, the Trend-Free Pre-Whitening (TFPW) [34] approach which is a modified MK test was used. The R package "modifiedmk" [27] was used to perform the above mentioned non-parametric tests.…”

Section: Mann-kendall Test and Sen's Slope Methodsmentioning

confidence: 99%

Section: Study Area and Data Collectionmentioning

confidence: 99%

“…When a p-value is lower than the significance level 5%, one should reject H 0 and accept Ha. To evaluate the results of these four tests, we made a classification based on the number of tests rejecting H 0 [26][27][28] . They are (i) Class A which stands for "Useful"-when none or only one of the above four tests rejects H 0 ; (ii) Class B which represents "Doubtful"-when two of the four tests reject H 0 ; and (iii) Class C which is "Suspect"-when three or all the tests reject H 0 .…”

Section: Study Area and Data Collectionmentioning

confidence: 99%

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Rainfall and Temperature Trend Analysis by Mann–Kendall Test and Significance for Rainfed Cereal Yields in Northern Togo

Gadédjisso-Tossou¹,

Adjegan²,

Kablan³

2020

Sci

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show abstract

“…Information about long-term homogeneity in trends of precipitation can help in making informed management decisions [1]. Almost 90% of the storm rainfall in the urban watersheds is lost to surface runoff causing floods [2].…”

Section: Introductionmentioning

confidence: 99%

Homogeneity in Patterns of Climate Extremes Between Two Cities—A Potential for Flood Planning in Relation to Climate Change

Abbas¹,

Farooque²,

Afzaal³

2020

Water

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Information about potential scenarios and causes of floods is important for future planning. Historical weather data of Fredericton (New Brunswick) and Charlottetown (Prince Edward Island), the two coastal cities of Atlantic Canada, were analyzed using RClimDex, Mann–Kendall test, and Sen’s slope estimates for potential scenarios and causes of floods. Flood hazard analyses were conducted using GIS (Geographical Information System) and ArcSWAT software. The watersheds of Fredericton and Charlottetown were delineated from 25 × 25 m resolution DEMs (Digital Elevation Models) of the two cities followed by percent watershed area calculations for different elevation classes for flood generation. Over the past 100 years, there was a significant decreasing trend in the high intensity precipitation in Charlottetown supported by a significant decrease in the number of heavy precipitation days. However, maximum one-day precipitation and maximum five-day precipitation significantly increased in Charlottetown and Fredericton, respectively. Charlottetown received more annual precipitation than Fredericton. In the last 30 years, there was an event exceeding 50 mm precipitation (considered as a threshold for the return period of urban floods) in Charlottetown; Fredericton experienced such events for more than 1.5 times. For twelve times, these events occurred more than once in a year in Charlottetown as compared to fourteen times in Fredericton. Despite statistically proven similarities in the occurrence of extreme events in the two cities, the visualized flood hazards, and the mapping of watershed characteristics, no devastating floods were reported for Charlottetown. This does not necessarily mean that there had never been risks of flooding in Charlottetown. These findings may help policymakers for future developments.

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Extreme Rainfall Analysis in Pernambuco, Northeast Brazil, Using a High‐Resolution Gridded Dataset

Gomes,

da Silva,

Araújo

et al. 2024

Intl Journal of Climatology

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This paper presents a detailed spatio‐temporal analysis of the rainfall in the state of Pernambuco, Northeast Brazil. It is based on climate indices for extreme precipitation recommended by the Expert Team on Climate Change Detection, Monitoring and Indices. To accomplish this, daily rainfall 1data (1961–2019) were extracted from 809 high‐resolution grid points (0.1° × 0.1°) using the Brazilian Daily Weather Gridded Data (BR‐DWGD). The significance and magnitude of index trends were assessed using the modified Mann–Kendall and Sen's slope tests. This study also examined whether there existed a significant difference in climate indices among the three regions (Sertão, Agreste and Zona da Mata) within the state. The findings revealed notable significant negative trends in the PRCPTOT, R10mm, R20mm, Rx1day, Rx5day and CWD indices across all regions of Pernambuco, exhibiting a gradient from the coast to the state's interior. Reduction values of up to 15 mm year−1 for PRCPTOT, 0.7 day year−1 for R10mm, 0.2 day year−1 for R20mm, 0.01 mm year−1 for Rx1day, 0.03 mm year−1 for Rx5day, 0.4 day year−1 for CWD were observed. Furthermore, an alarming pattern was also noted for CDD, displaying a higher concentration of significant positive trends in all regions of the state, with estimated increases of up to 1.4 day year−1. Conversely, a balance of trends—both positive and negative—was observed across the entire state for R95p and R99p, with a majority of trends proving non‐significant. SDII exhibited a higher frequency of grid points showing a significant positive trend, particularly notable in the Sertão and Zona da Mata regions, where significant differences in the index values were absent. However, the remaining indices showcased notable regional differences, with values decreasing from the east to the west of the state, except for CDD. This study will assist decision makers, providing detailed long‐term information essential for preventing natural disasters and supporting socioeconomic and environmental policies in the state.

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Long-Term Homogeneity, Trend, and Change-Point Analysis of Rainfall in the Arid District of Ananthapuramu, Andhra Pradesh State, India

Cited by 95 publications

References 69 publications

Rainfall and Temperature Trend Analysis by Mann–Kendall Test and Significance for Rainfed Cereal Yields in Northern Togo

Rainfall and Temperature Trend Analysis by Mann–Kendall Test and Significance for Rainfed Cereal Yields in Northern Togo

Homogeneity in Patterns of Climate Extremes Between Two Cities—A Potential for Flood Planning in Relation to Climate Change

Extreme Rainfall Analysis in Pernambuco, Northeast Brazil, Using a High‐Resolution Gridded Dataset

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