Rainfall Trend Analysis Research Articles

Analysis of Rainfall Trends in India, Incorporating Non-Parametric Tests and Wavelet Synopsis over the Last 117 Years

Rainfall trend analysis is very important in the economic and sociocultural context of the country, like the development of irrigation and water resource management practices. In this paper, Mann-Kendall (M-K), Sen’s slope estimator, and wavelet analysis were used to analyze long-term (1901 ~ 2017) annual and seasonal rainfall trends in India. The sequential Mann-Kendall (SQMK) test is used to estimate the temporal variation of rainfall. The analysis shows monsoon precipitation in “Jammu and Kashmir, Himachal Pradesh, Uttarakhand, Uttar Pradesh, Chhattisgarh, Sikkim, Arunachal Pradesh, Mizoram, Assam, Karnataka, Nagaland, Kerala, Meghalaya, and Goa” have significant trends. The above-mentioned states were subjected to a discrete wavelet transform (DWT) analysis using Daubechies (db5-db10) and Symlet (sym5-sym10) mother wavelet families. The analysis revealed that the trends of subdivisions had a short-term periodicity of less than a decade. Therefore, the present study indicates significant changes over time. By utilizing wavelet techniques, it is possible to gain insight into both short- and long-term tendencies, making it simpler to spot patterns and sudden changes. Therefore, the present study by combining non-parametric tests with wavelet synopsis, offers a thorough comprehension of rainfall trends in India. The collaborative use of these techniques improves the precision of trend identification, offering valuable insights to make well-informed decisions for water resource management and climate adaptation strategies.

Study the seasonal trend analysis and probability distribution functions of rainfall for atmospheric region of Pakistan

It is known that the rainfall is one of the major aspects of the climate change and hydrological processes. Its impact on the resources of water has always been considered very essential. In the countries like Pakistan having severe weather conditions the effect of rainfall can be more crucial. Due to the geographical differences, the impact of sudden rainfall can be more disastrous in Pakistan as in 2011 and 2022 only the few days’ extreme rainfall in summer monsoon disturbed many regions of Pakistan especially southern region of Pakistan and lost hundreds of lives and homes. In addition, there are two methods applied for this study (1) trend analysis and (2) probability distribution functions. Our results revealed that only three cities i.e. Chitral, Skardu and Gilgit having increasing as well as the station Sialkot have increasing trend pattern in only summer rainfall, and other all have shown decreasing trend overall. Furthermore, key extreme weather events over Pakistan have changed in frequency and intensity during the past decades due to significant increase in global warming. The methods and results will be useful to study the historical rainfall data for projecting future rainfall variations impact on hydrological processes due to climate change.•The Data, methods and results of this study can be useful to government officials for protective measures and future developments.•Detecting trend analysis was applied to point out how strong the trend in the rainfall is and whether it is increasing or decreasing.•Additionally, the probability distribution was applied to indicate changed in frequency and intensity during the past decades due to significant variations in rainfall data.

Rainfall probability and trend analysis for strategic crop planning with their impact on the existing cropping system in the new alluvial plains of West Bengal

Rainfall probability and trend analysis for strategic crop planning with their impact on the existing cropping system in the new alluvial plains of West Bengal

Analysis of the climate change impact on the spatiotemporal drought in the Gaza region of the southeastern Mediterranean

Abstract The southeast Mediterranean region of the Gaza Strip is showing traces of evolving drought patterns driven by the impacts of climate change. The analysis of rainfall data at eight meteorological stations for a period extending over 48 years from 1974 to 2021 shows obvious variations in the spatiotemporal distribution of the rainfall over the Gaza Strip. The total monthly rainfall trend analysis for the wet months indicates a decreasing trend during February, March, April, and November with a ratio ranging between −16 and −62% and an increasing trend of about 35 and 141% through October at each of the meteorological stations. However, January shows an increasing trend of about 1–27% at all meteorological stations except Nussirat where a decline of about −7% is recorded while December refers to an increasing trend of about 5–27% in the north area of Gaza and declining trend of −2 to −17% over the southern region of the Gaza Strip. The drought analysis using the SPI indicator refers to a significant development of drought during the years 1990, 1999, 2010, and 2014 in the Gaza Strip with a major incident of occurrence where specifically, the monthly drought in terms of SPI-1 is identified as moderate and mild by about 15–21 and 27–56%, respectively. The agricultural drought of SPI-3 is nominated by severe, moderate, and mild severity with an incident reaching 11%, 8–11%, and 21–52%, respectively. However, the hydrological droughts demonstrated by the 9-month SPI-9 and 12-month SPI-12 potentially occur in extreme, severe, moderate, and mild with a probability of incident defined by up to 4, 13, 15, and 28–40%, respectively, for SPI-9 and by up to 4, 6, 11 and 38% extreme, severe, moderate, and mild, respectively, in case of SPI-12.

Analysis of Rainfall Trend and Pattern in Owerri, Imo State, Nigeria

The study analyzed the rainfall trend and pattern for Owerri municipal, Imo state. The data collected is secondary. A remote sensing daily rainfall data from 1981 to 2020 from CHIRPS data archive given in millimeter (mm) was downloaded. In order to achieve the aim of the research, data analysis was conducted on the rainfall data. Some of the statistical methods used includes mean, variance, standard deviation, coefficient of variation, and standardized anomaly index (S.A.I). The annual rainfall and monthly rainfall for Owerri municipal, Imo state were analyzed and charts were presented which show fluctuation in rainfall trend and pattern. The least annual rainfall happened to be in 1983 of about 1662.9mm, which is followed by that of 2001 of 1828mm. The wettest annual rainfall occurred in the year 1995 of 2962.2mm which happened to be the peak of the study, followed by 1999 of 2837.9mm. It was shown that the month July from 1981 to 2020 experienced more rainfall than that of August. The four decadal rainfall presented for the study shows; near normal condition to very wet condition (1981 – 1990), near normal condition (1991 – 2000), extremely dry conditions to near normal condition (2001 – 2010), and near normal condition to extremely dry condition (2010 - 2020). The hypothesis was tested using chi-square, the results shows there is no significant difference in trend and pattern of rainfall in owerri, thus, the null hypothesis was accepted. The study generally show there is a little or no singnificant change in the rainfall pattern and trend in Owerri from 1998-2020 and hence recommend that there should be more monitoring of rainfall activities in order to curtail it excesses in flooding and agricultural loss.

Impact of Landuse and Landcover Changes on Hydrological Components of the Oti Sub-Basin of Ghana

Landuse and landcover have over the decades been undergoing changes as a result of natural and human activities. These changes for a given area can be attributed to fluctuations in the infiltration ability of the land, leading to changes in the hydrological cycle of a given catchment area. This research assessed some of the impacts that landuse and landcover changes coupled with climate variations have on the hydrological components of the Oti sub-basin of Ghana using the Soil Water Assessment Tool (SWAT) with ArcGIS® interface for the development of models from which conclusions were drawn. The research incorporated into the SWAT system two landuse and landcover data: 1984 and 2013 which were modeled and evaluated alongside soil, slope and climate dataset. The results from running the model indicated a very significant change in landuse and landcover and a loss of forest cover which has negative effect on the hydrological components of the basin. Also, the rainfall trend analysis gave negative significant values of -2.28 and -2.78 for the two stations located at Zabzugu and Bimbila within the basin. Together, these changes have led to an increase in evapotranspiration (ET) and decrease in surface water, lateral flow and groundwater recharge. This is an indication that climate change impact on the basin is a function of the landuse and landcover changes. There is an urgent need for all stakeholders to help protect the basin from anthropogenic activities such as farming too close to the basin in order to prevent future water availability issues in the basin.

Agroclimatic Zone-Based Analysis of Rainfall Variability and Trends in the Wabi Shebele River Basin, Ethiopia

The amount and annual distribution of rainfall caused a major socioeconomic and environmental problem where rainfed agriculture is predominant. This study assessed the long-term variability and trends of rainfall in the Wabi Shebele River Basin (WSRB), Ethiopia. The basin was discretized into 9 local agroclimatic zones (ACZ) based on annual rainfall and elevation. The coefficient of variation (CV) was used to check the variability of rainfall while modified Mann-Kendall (MK) and Innovative Trend Analysis (ITA) methods were used to detect rainfall trends. For each ACZ, stations with long-term records and less than 10% of missing data were selected for further analysis. The mean annual rainfall in the basin ranges from 227.2 mm to 1047.4 mm. The study revealed most of the ACZs showed a very high variation in Belg/Spring rainfall (CV% > 30) than Kiremt/Summer and annual rainfall. Seasonal and annual rainfall trend analysis revealed that no uniform trend was detected in all ACZs. However, most of ACZs in the arid and semi-arid areas showed a non-significant decreasing trend in annual rainfall. From seasonal analysis, Belg and Kiremt rainfall showed relatively decreasing and increasing trends respectively. In comparison, a similar result was observed using MK and ITA methods.

Annual, Seasonal, and Monthly Rainfall Trend Analysis through Non-Parametric Tests in the Sebou River Basin (SRB), Northern Morocco

This paper explores the temporal and spatial patterns of annual, seasonal, and monthly rainfall series during the period of 1961–2018 at 15 stations in the agriculturally important Sebou river basin, northern Morocco. Trends were investigated using the classical non-parametric Mann–Kendall test and the Theil–Sen approach at 90%, 95% and 99% confidence levels. A general decreasing trend was found at the annual scale, significant at the 95% confidence level at 8 stations out of 15 (53%). A particularly large decreasing trend between −30 mm and −50 mm per decade was found in the north and eastern parts of the basin. Autumn rainfall tended to increase, but this was not statistically significant. During the winter months, rainfall tended to decrease sharply (−27 mm and −40 mm per decade) in the northern slopes of the Rif mountains, while in spring, the mountainous area of the basin recorded decreases ranging between −12 mm and −16 mm per decade. During winter and spring, negative trends were significant at ten stations (66%). Summer rainfall tends toward a decrease, but the absolute change is small. These results help to understand the rainfall variability in the Sebou river basin and allow for improved mitigation strategies and water resource plans based on a prospective view of the impact of climate change on the river basin.

Variations of precipitation and runoff in the Bagmati river basin, Bihar, India

AbstractThe trend analysis of precipitation for four rain gauge stations and runoff for Hayaghat station in the Bagmati river basin is carried out in this work by adopting modified Mann–Kendall and Sen's slope methods. Primary and secondary data are used for finding the monthly, seasonal, and annual trends at four stations. Primary data are the observed rainfall from 1981 to 2013 which were collected from IMD Pune, observed runoff data were collected from CWC Patna and secondary data from the National Center for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR) reanalysis rainfall data for the period 1981–2013. The goals of this research are (i) to determine rainfall and runoff trend analysis, as well as the relationship between observed rainfall data and NCEP/NCAR reanalysis secondary data for four stations and (ii) to find the correlation between observed rainfall data and runoff data for all four seasons. The correlation analysis of observed rainfall and NCEP/NCAR reanalysis data shows a very good correlation ranging between 0.6111 and 0.7435. Rainfall is increasing during and after the monsoon at all selected stations, except during the monsoon season in Dhenge. Correlation analysis of rainfall and runoff shows ranges from 0.3724 to 0.4721 for all the four seasons. The correlation of rainfall and runoff is relatively good in monsoon season.HIGHLIGHTSTo determine rainfall and runoff trends, as well as the relationship between observed rainfall data and NCEP/NCAR reanalysis secondary data for four stations. To find the correlation between observed rainfall and runoff data for all four seasons.

Trend Analysis of Rainfall in Telangana State (India) Using Advanced Statistical Approaches

This study was carried out to analyse the trend analysis of the long-term annual and seasonal rainfall pattern in Telangana state, India. For this study monthly rainfall data of Telangana state from January 1982 to December 2021 was collected from the NASA power website (https://power.Iarc.nasa.gov). The linear regression trend line and the non-parametric tests, such as Mann-Kendall test, Modified-Mann Kendall test and Innovative trend analysis tests, were used to understand the trend present in the rainfall data of Telangana. Wallis and Moore test was used to test the randomness of the rainfall data under consideration. Both increasing and decreasing trend was seen in linear regression trend method for Telangana rainfall data. The significant result was found in the month of May which showed an increasing trend, whereas remaining months showed the non-significant trend in the Modified Mann Kendall test as well as in the Innovative trend analysis. The pre-monsoon, monsoon and post-monsoon periods showed a non-significant trend in the rainfall pattern of Telangana state. The annual rainfall of Telangana showed a non-significant trend pattern by Modified Mann-Kendall test. There was a significant increasing trend of rainfall in the month of May and remaining months showed a non-significant trend and no significant trend in the monsoon periods. These accurate identification of rainfall patterns over the area may help to create the appropriate policy measures in advance to plan the future climate uncertainties.

Smallholder farmers' perception of climate change and choice of adaptation strategies in East Hararghe Zone, Eastern Ethiopia

PurposeChange of climate is attributed to human activity that alters the composition of the global atmosphere observed over comparable periods. The purpose of this paper is to explore smallholder farmers' perceptions of climate change and compare it with meteorological data, as well as to identify perceived adaptation barriers and examine the factors that influence the choice of adaptation options in eastern Ethiopia.Design/methodology/approachIn total, 384 sample households were chosen from four districts of the zone. A cross-sectional survey was used to conduct the study. Primary data was acquired through key informant interviews, focus group discussions and semistructured interviews, whereas meteorological data was collected from the National Meteorological Service Agency of Ethiopia. A Mann–Kendall statistical test was used to analyze temperature and rainfall trends over 33 years. A multivariate probit (MVP) model was used to identify the determinants of farmers' choice of climate change adaptation strategies.FindingsThe result indicated that temperature was significantly increased, whereas rainfall was significantly reduced over the time span of 33 years. This change in climate over time was consistently perceived by farmers. Smallholder farmers use improved varieties of crops, crop diversification, adjusting planting dates, soil and water conservation practices, reducing livestock holdings, planting trees and small-scale irrigation adaptation strategies. Moreover, this study indicated that sex of the household head, landholding size, livestock ownership, access to extension, access to credit, social capital, market distance, access to climate change-related training, nonfarm income, agroecological setting and poverty status of the households significantly influence farmers’ choice of adaptation strategies.Research limitations/implicationsFurther research is required to evaluate the economic impact of each adaptation options on the livelihood of smallholder farmers.Practical implicationsInstitutional variables significantly influenced how farmers adapted to climate change, and all of these issues might potentially be addressed by improving institutional service delivery. To improve farm-level adaptation, local authorities are recommended to investigate the institutional service provision system while also taking demographic and agroecological factors in to account.Originality/valueThis study compared farmers' perceptions with temperature and rainfall trend analysis, which has been rarely addressed by other studies. This study adopts an MVP model and indicated the adaptation strategies that complement/substitute strategies each other. Furthermore, this study discovered that the choice of adaptation options differed between poor and nonpoor households, which has been overlooked in previous climate change adaptation research.

Statistical analysis of rainfall trend and its variability (1901–2020) in Kolkata, India

The current study focuses on the altering historical rainfall data analysis and its variability in Kolkata (Kolkata Municipal Corporation), a metropolitan city in India. The research area experiences detrimental urban floods (pluvial floods) at near-annual regularity during the monsoon, and during the pre-monsoon seasons it commonly experiences water shortage problems. Analysing trends and temporal variability of rainfall over 120 years from 1901 to 2020 is the main objective of this study. The original Mann–Kendall (M–K) test has been applied to the rainfall dataset in conjunction with Sen’s Slope Estimator using Python 3.10, after the Durbin-Watson (DW) statistic initially suggested that there is no serial correlation effect. The M–K test, with a Kendall’s tau of 0.17058 (significant at a 5% level), shows an upward trend in annual rainfall between 1901 and 2020. The Sen’s slope, which measures the rate of change annually, has a value of 2.48152. Regression analysis and other dispersion measures are also used in this study to investigate the monthly rainfall trend and its variability. The phase-wise (30-year) analysis of annual rainfall variability reveals a considerable variation over 120 years. While fitting the linear regression line month by month over the entire period, mostly negative trends were found in the pre-monsoon and positive trends in the monsoon and post-monsoon seasons. The findings of this analysis could be useful to urban planners for water supply and management in the study area. The primary concern of planners for effectively managing rainwater and the accompanying issues should be the growing variability of annual precipitation.

Analysis of Temperature and Rainfall Trend in South 24 Parganas District of West Bengal (1988-2017)

Analysis of Temperature and Rainfall Trend in South 24 Parganas District of West Bengal (1988-2017)

Analysis of Rainfall Trends over Assam, North East India

The spatio-temporal variations of long-term rainfall over Assam in the North Eastern part of India were analyzed using data from twenty-six locations during the period 1981-2017. The annual, monthly, and seasonal rainfall trends are assessed by using Mann-Kendall and Sen slope tests over different sub regions. September, December, January, and February months recorded decreasing trends, while May, June, and August exhibited statistically substantial increasing trends. Similarly, annual, pre monsoon season and monsoon seasons exhibited increasing trends, but post monsoon and winter seasons recorded statistically non-significant decreasing rainfall trends. The locations of Demaji, Dibrugarh, Karimganj, and North Lakhimpur were recorded with above 2000 mm annual rainfall. On seasonal time scales, pre monsoon and monsoon rainfall over Assam witnessed increasing trends with statistically notable trends. The post monsoon and winter rainfall recorded decreasing trends, but the trends were statistically non-significant. In the monsoon season, a declining trend was recorded during the first decade (2001-2010). The southern and northeastern portion of the state received the maximum average annual rainfall when compared to the central portion of the Brahmaputra valley of Assam state. The maximum variations in rainfall have been recorded in the Karimganj (36.8%), Hailakandi (31.9%), Silchar (31.9%), and Dhuburi (26.5%) regions. Any slight variations in the rainfall trend could certainly be vulnerable as the state of Assam which comprises valley flood plains and sub-Himalayan boundaries, also supports a large chunk of human as well as ecosystem populations. In the present scenario, extreme and unprecedented rainfall events can affect agricultural activities, stream flow, the availability of food, etc., which may lead to disparities in the socio-economic conditions of the area. The results would be beneficial to policymakers in understanding the impact of changing climates and assessing the climatic vulnerability of natural and human resources.

Analysis of extreme rainfall trend and mapping of the Wadi pluvial flood in the Gaza coastal plain of Palestine

Analysis of extreme rainfall trend and mapping of the Wadi pluvial flood in the Gaza coastal plain of Palestine

Correction to: Spatio-temporal variability and trend analysis of rainfall in Wainganga river basin, Central India, and forecasting using state-space models

Correction to: Spatio-temporal variability and trend analysis of rainfall in Wainganga river basin, Central India, and forecasting using state-space models

Morphometric Analysis of Yamuna River Basin in Delhi Region: Implications to Hydrological Hazards

Abstract Morphometric analysis has been performed for three sub-basins of Yamuna river catchment in Delhi region to gain understanding on differential response of individual sub-basins to rainfall and related hazards viz., surface runoff, soil erosion, flood vulnerability and potential. Sub-basins Delhi central and Delhi east show overall higher soil erodibility and flood potential than Delhi west. Delhi central is more responsive to rainfall induced surface runoff and soil erosion due to its higher relief and complex landscape configuration. The inferences made by morphometric analysis are supported by rainfall trend analysis for past 30 years. Revisiting severe flood events during last one century helped in specifying the areas with higher vulnerability and susceptibility to similar floods in future. The results thus obtained would help in prioritizing the areas for risk assessment and flood management, especially the parts of Delhi east and Delhi central sub-basins that are most vulnerable to floods.

Temporal Variations and Futuristic Projections of Temperature and Precipitation: A study of Vijayawada city

Abstract: Examining the temporal dynamics of meteorological variables in the context of changing climate, particularly in Vijayawada, where agriculture is predominant. Therefore, the study uses trend analysis of rainfall and temperature change in Vijayawada using precipitation data obtained from Precipitation and temperature data. Data have been analysed using the coefficient of variation and standard deviation. Furthermore, the Mann-Kendall test was used to detect the time series trend. The result revealed variability of rainfall and temperature. The month-wise analysis of the temperature and precipitation trends established different unique patterns. This is due to the fact that the sensitivity of the world to climate change varies temporally and spatially. The scope of the study lies in developing the analysis to study different extreme events such as cloudbursts, heat waves, cold waves, etc. Furthermore, the spatial variations of the study can be used to establish the climate sensitivity with temporal factors.

Spatio-temporal variability and trend analysis of rainfall in Wainganga river basin, Central India, and forecasting using state-space models

Spatio-temporal variability and trend analysis of rainfall in Wainganga river basin, Central India, and forecasting using state-space models

Rainfall and Runoff Trend Analysis in the Wadi Mina Basin (Northern Algeria) Using Non-Parametric Tests and the ITA Method

The aim of this paper is to analyze the temporal tendencies of monthly, seasonal, and annual rainfall and runoff in the Wadi Mina basin (north-western side of Africa) using data from five stations in the period from 1973–2012. With this aim, first, a trend analysis was performed using two non-parametric tests: the Theil–Sen estimator and the Mann–Kendall test. Then, to identify trends in the different rainfall and runoff values of the series, the Innovative Trend Analysis technique was further applied. The results of the application of the non-parametric tests on the rainfall data showed a general negative rainfall trend in the Wadi Mina basin for different timescales. Similarly, the results evidenced a general reduction in the runoff values, in particular in the Sidi Abdelkader Djillali and Oued Abtal stations, even though the results obtained for the Oued Abtal station are influenced by a dam. These results were further analyzed through Sen’s method, which enabled the trend identification of the different values (low, medium, and high) of the series.