Analysis Of Rainfall Variability Research Articles

Simulation of climate-adaptation responses to rainfall variability on rainfed yield anomalies

Climate adaptation offers promising approaches to cope with the detrimental impacts of climate change on rainfed agriculture, intending to mitigate yield losses and safeguard food security worldwide. This is especially critical in the semi-arid tropics, characterized by highly variable and often intensified rainfall regimes. The current study explored the potential contribution of climate adaptation measures, specifically sowing windows and supplemental irrigation (SI), to offset the impacts of rainfall variability on rainfed crop yield in the Thondamuthur block, India. Under the proposed adaptation measures, this study analyzed the relationship between historical rainfall variability (1951–2019) and rice, maize, and sorghum yield anomalies. A seamlessly integrated framework was developed to link rainfall variability analysis with yield response simulations using the AquaCrop model. Rainfall classification analysis indicated an increase in rainfall availability during the Kharif season and a decrease during the Rabi season in Period III compared with the baseline. The late-sown Kharif and early-sown Rabi crops demonstrated effective climate adaptation, with the 27th and 38th SMWs identified as optimal climate-adapted sowing weeks, respectively. Significant decreases of 10% and 12% in SI requirements were observed in early-sown Rabi maize and sorghum, respectively. The results showed that substituting Rabi rice and maize with Rabi sorghum led to reductions of 90% and 75% in seasonal SI requirements, respectively. The early-sown Rabi rice and maize contributed to 88% and 12% relative yield increases, respectively, compared with the normal-sown. This study highlights the effectiveness of climate adaptation measures in enabling farmers to withstand climate-induced anomalies.

Comprehensive Analysis of Rainfall Variability in Urban Maiduguri, Nigeria: Implications for Climate Resilience and Sustainable Development

Climate variability, including its effects on precipitation and atmospheric conditions, is a critical aspect of Earth’s dynamic climate system. The increasing frequency of extreme weather events worldwide necessitates a thorough understanding of climatic changes. To address the scarcity of localized climatic studies, this research focuses on Maiduguri, the capital of Borno State in northeastern Nigeria. This study aimed to assess the rainfall variability of urban Maiduguri, with the objectives of investigating rainfall patterns, examining trends, and evaluating variability. The study utilized 31 years of rainfall data from the Nigerian Meteorological Agency, spanning from 1992 to 2023. The data was statistically analyzed using the Coefficient of Variation, Rainfall Anomaly Index (RAI), Sen slope, and the Mann-Kendall trend test. The findings indicate that the minimum annual rainfall in Maiduguri is 292.7 mm, the maximum is 838.2 mm, and the mean annual rainfall is 519.34 mm. These values provide essential insights into the range and central tendency of Maiduguri’s annual rainfall, contributing to a comprehensive understanding of the region’s climatic conditions. Moreover, August stands out as the month with the highest mean value of 196.66 mm, indicating the peak of the rainy season. The Total Annual Rainfall Trend in Maiduguri shows a significant positive Sen’s Slope value obtained from the Mann-Kendall test (z-statistic = 2.773, p-value = 0.005), suggesting an increasing trend in monthly rainfall. The calculated Sen’s Slope of 172.000 highlights the peak rainfall during the core months of the rainy season. This indicates a moderate level of rainfall variability (CV = 28.3%), accompanied by notable fluctuations in the Rainfall Anomaly Index (RAI) during critical months. The Mann-Kendall trend test suggests potential shifts in precipitation patterns. This research serves as a foundation for informed decision-making by local authorities, urban planners, and environmental stakeholders.

Remote sensing-based spatio-temporal rainfall variability analysis: the case of Addis Ababa City, Ethiopia

Remote sensing-based spatio-temporal rainfall variability analysis: the case of Addis Ababa City, Ethiopia

Geo-statistical analysis of climatic variability and trend detection in the Hindu Kush region, North Pakistan.

This paper is an effort of geo-statistical analysis of rainfall variability and trend detection in the eastern Hindu Kush region located in the north-west of Pakistan. The eastern section of the HK region lies in the western part of Pakistan. Exploring rainfall variability and quantifying its trend and magnitude is one of the key indicators among all climatic parameters. In the study area, Pakistan Meteorology Department (PMD) has established seven meteorological stations: Drosh, Chitral, Dir, Timergara, Saidu Sharif, Malam Jabba, and Kalam. Daily, mean monthly, and mean annual rainfall time series data for all the met stations were geo-statistically analyzed in the GIS environment for detecting monthly and annual variability in rainfall, variability, and trend detection. Mann-Kendall (MK) and Theil-Sen's slope (TSS) statistical tests were applied to rainfall data. Initially, the MK test was applied for detection of trends and TSS test was used to quantify the change in magnitude. The results indicate that the rainfall variability in intensity and trend pattern detection. The analysis confirms that an extremely significant rainfall trend in the case of mean annual rainfall was predicted at Dir and Malam Jabba meteorological stations. Opposite to this, at Kalam and Chitral stations, a less significant rainfall trend was noted. In a similar context, no prominent rainfall trend has been found at Drosh, Timergara, and Saidu Sharif meteorological stations. Likewise, using TSS, an extremely negative variation in the magnitude of rainfall was verified at Kalam and Malam Jabba. However, a noteworthy positive change in rainfall magnitude has been noted at Dir and Saidu Sharif meteorological stations. The findings of this research have the potential to assist the decision and policy makers and academicians to think truly and conduct more scientific research studies to mitigate climate change.

Analysis of rainfall variability and trend in a small homogenous region of West Bengal in Malda district

Analysis of rainfall variability and trend in a small homogenous region of West Bengal in Malda district

Spatial and Temporal Analysis of Rainfall Variability and Trends for Improved Climate Risk Management in Kayonza District, Eastern Rwanda

The variability, intensity, and distribution of rainfall have drawn a lot of interest globally and especially in nations where rainfed agriculture is the norm. This article uses rainfall data from the Rwanda Meteorology Agency for the years 1981 to 2021 to delineate and analyze rainfall variability and trends in the Kayonza District. The time series were grouped using the K-means clustering technique based on computed Euclidean distance, the total within-cluster sum of squares, and the elbow plot technique to determine the optimal number of clusters. The coefficient of variation measures was employed to analyze rainfall variability, while Sen’s slope and the Mann–Kendall (MK) test were used, respectively, to find trends and changes in magnitude. The results indicated four near homogeneous zones named region one to four. The dry seasons indicated higher variability compared to rainy seasons and annual rainfall total with a variability of 128–142% over the southeastern part during June to August (JJA) season, while a variability of 16–48% was observed over most of the district during both annual and rainy seasons. It was further noted that the areas in the central part of the Kayonza District indicated a significant increasing trend at a significance level of 95% and above during January to February (JF), September to December (SOND), and on annual basis, while March to May (MAM) and JJA season exhibited no significant trend. The findings of this study are essential for creating adequate mitigation strategies to lessen climate change’s effects on agriculture as well as other socioeconomic sectors.

Analysis of Rainfall Variability and Shifts in Season in Relation to the Rice Cultivation Period in Sleman Regency

The research aimed to determine seasonal rainfall variability in Sleman Regency to determine shifts in season in Sleman Regency, and the relationship between the shift in season and rice cultivation period in Sleman Regency. The method was the coefficient of variation to determine seasonal rainfall variability. The shift in season was analysed in 10-year periods. The relationship between the shift in season and the rice cultivation period was analysed using the Chi-Square test. The result of this research showed that the rainfall variability in the dry season was higher than that in the rainy season in Sleman Regency from 1990-2019. The dry season in 2000-2009 came 10 days earlier in 6 subdistricts. The dry season in 2010-2019 was delayed in a period of 10-50 days. The rainy season in 2000-2009 came 20 days earlier in 7 subdistricts, delayed in a period of 10 days in 3 subdistricts. The rainy season in 2010-2019 was delayed in a period of 10 days in 8 subdistricts. The Chi-Square count was greater than the Chi-Square table, meaning that there was a relationship between shift in season and rice cultivation period in Sleman Regency.

Analysis of rainfall variability in the northern center of the Senegalese groundnut basin: Louga, Thies and Diourbel regions

Analysis of rainfall variability in the northern center of the Senegalese groundnut basin: Louga, Thies and Diourbel regions

Analysis of rainfall variability in the northern center of the Senegalese groundnut basin: Louga, Thies and Diourbel regions

Analysis of rainfall variability in the northern center of the Senegalese groundnut basin: Louga, Thies and Diourbel regions

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.

Trend analysis of historical and future precipitation projections over a diverse topographic region of Khyber Pakhtunkhwa using SDSM

Abstract This study focuses on the spatio-temporal analysis of rainfall variability, trend patterns, and projected changes using GCM CCSM4 for RCP4.5 and RCP8.5 in Khyber Pakhtunkhwa. The historical rainfall variability (1971–2018), trend, and magnitude were assessed using Mann–Kendall and Spearman's Rho. In addition, to downscale GCMs data of precipitation at the regional level of Khyber Pakhtunkhwa, the SDSM conditional sub-model was applied. The monthly Mann–Kendall and Spearman's Rho trend test results revealed that most of the meteorological stations located in the northeastern mountains recorded a decreasing trend while Parachinar observed an increasing trend in almost all months except December. The trend results for seasonal rainfall showed a decreasing trend in winter, spring, and summer in the north and northeastern parts of Khyber Pakhtunkhwa whereas an increasing trend was observed in all seasons at Parachinar. The RCP4.5 projections depicted an increase in precipitation especially in the monsoon-dominating regions in comparison to the western disturbances, while decreasing rainfall projection was observed in RCP8.5. The projections for the summer and winter seasons depicted an increasing trend until the mid-century but in the latter half, a decline is registered. Such seasonal changes may initially cause flooding followed by drought, which calls for effective water management strategies.

Geo-spatial analysis of rainfall variability in Khyber Pakhtunkhwa Province, Pakistan

This paper explores geo-spatial analysis of rainfall variability in Khyber Pakhtunkhwa province, Pakistan. The concern region lies in the north-west of Pakistan and frequently faced the challenges of floods each year. This is an attempt to find out the rainfall trend and fluctuation which is one of the prime indicator of climate change. For this study, the daily rainfall data comprises of almost five decades (1975-2015). For achieving the study objectives, daily, monthly and mean annual rainfall data were analyzed using Mann-Kendall and Standard Deviation combined. Additionally, to further process the rainfall data spatio-statistically, GIS technology has been applied. The analysis specifies that a positive rainfall detected in the meteorological stations of Peshawar, Dir, Chitral, Drosh, Kakul and Saidu, whereas the moderate rainfall trend is detected in Cherat, Bannu, and Balakot. The remaining stations expressed no obvious trend, due to low time period of data.

Rainfall variability analysis and trend assessment in Theni District of Tamil Nadu, India: An implication for crop planning

Rainfall variability analysis and trend assessment in Theni District of Tamil Nadu, India: An implication for crop planning

Analysis of rainfall variability and probability in Theni District, India

Crop planning based probability analysis aids in increasing production. A crop planning research was conducted in the Theni district by examining probability analysis over a 40-year period (1982-2021) using weekly and monthly rainfall data. The mean annual rainfall in the Theni district was 1100.2 mm spread over 90 rainy days. The probability study revealed that obtaining 20mm rainfall per week received for 8 weeks (38 to 45th week), which is beneficial for sowing and planting. On the other side, October had the greatest mean monthly rainfall (191.8 mm), followed by November (147.9 mm). The main crops farmed in this area are rice, sugarcane, and bananas, but they should be replaced with maize, pulses, cowpea, sorghum, ragi, and minor millets since they can grow in a shorter time period and yield higher. Key words: Rainfall, Markov chain analysis, initial and conditional probability and crop planning

Estimation of Fluctuations and Global Tele-connections in the Monsoonal Rainfall and Associated Floods for Barmer District

Abstract: This paper is about the fluctuations and global teleconnections in the monsoonal rainfall and associated floods of Barmer district, Rajasthan, India. For investigation of precipitation and related floods, the precipitation information for period of 1901-2002 is collected from India Meteorological Department (IMD) for Barmer district. Inter-monsoon rainfall variability analysis, percent departure from mean, Normalized Accumulated Departure from Mean (NADM) and conditional probability technique for El Nino and Southern Oscillation (ENSO) have been used for the analyses of monsoonal rainfall data and its effect on floods. The outcomes demonstrate year to year varieties in the precipitation with huge takeoff from mean precipitation. It is seen that greater part of the floods are related with positive takeoff from mean precipitation. The NADM shows epochal conduct of high and low monsoon precipitation of the basin. For analysis of ENSO Sea Surface Temperature (SST) data is obtained from National Oceanic and Atmospheric Administration (NOAA) for years 1950-2019. It is observed that, during La Nina years the rainfall is higher than average annual rainfall. The analysis of ENSO reveals that the probability of the occurrence of the floods is high during cold (La Nina) events and it is very low during warm (El Nino) events. Keywords: Monsoon rainfall, Global Tele-connection, SST, ENSO effect, floods

Analysis of Rainfall Variability in the Province of Quirino

The temporal variability of rainfall in Quirino Province was analyzed through the use of rainfall data of seven (7) rain gauges within the neighboring provinces like Nueva Vizcaya and Aurora. The length of record analyzed from 1997 to 2016. In this study, rainfall frequency analysis and consistency of rainfall data from the different stations through the use of double mass curve analysis was performed and analyzed. The annual series was used to screen each station’s annual rainfall data while the province’s average Thiessen rainfall was screened using maximum period series process. It was found out that all the data of the seven (7) rainfall stations were consistent. To attain allowable error in estimation of 10%, 5% and 1% for the mean annual rainfall the number of rain gauge station needed in the province should be 18, 72 and 1799, respectively.

Analysis of Rainfall Variability in the Province of Quirino

Analysis of Rainfall Variability in the Province of Quirino

BLOCK WISE RAINFALL VARIABILITY ANALYSIS OF DISTRICT SAWAI MADHOPUR, RAJASTHAN, INDIA

An attempt has been made to study the block wise rainfall variability analysis of districts Sawai Madhopur of Rajasthan. Study was performed on data sets of annual rainfall for the period of 1990-2020 (31 years) for district Sawai madhopur of Rajasthan. The coefficient of variation and standard deviation for weekly, monthly and annual rainfall were also computed for district Sawai Madhopur. The normal onset of monsoon in district Sawai Madhopur is between June to September. It was found that the annual rainfall is higher at Sawai madhopur block followed by Gangapur and Khandar block during last second and third decade. The mean annual rainfall is lowest in Bonli block. When the CV for the annual rainfall was examined, it was found be the least in Gangapur block followed by Sawai madhopur, bonli, bamanwas and khandar block, it was the highest.

Spatio‐temporal rainfall variability and trend analysis in the Tekeze‐Atbara river basin, northwestern Ethiopia

AbstractSpatial and temporal rainfall variability analysis at a basin scale is essential to understand water availability for sustainable water resource management. This study investigated the spatial distribution and temporal rainfall trend in the Tekeze river basin using daily rainfall data collected from 43 meteorological stations with records from 1960 to 2019. Coefficient of variation, seasonality index (SI) and trend index were used to evaluate monthly, seasonal and annual rainfall variability in the basin. The non‐parametric Mann‐Kendall's test was used to understand any rainfall trends. Results showed that there is moderate annual rainfall variability in the basin. Rainfall variability is higher in the Tsedey, Bega and Belg than kiremt season. SI results showed that majority of the Tekeze river basin is categorized as seasonal, most of the rain occurring in less than 3 months. Overall, Mann‐Kendall's test result revealed that there is no significant annual rainfall trend in the basin except for four stations. The seasonal rainfall characteristics and short duration of rain in the basin indicate that there is a need to implement water harvesting measures during the wet season for use in the dry periods.

Rainfall Trend and Variability Analysis in Borana Pastoral Lowland Areas: The Case of Yabello and Eel-wayye Station, Southern Ethiopia

Dry lands are traditionally used and managed by a pastoralist, characterized by variable precipitation, climate variability and water scarcity. Change in rainfall trend and variability’s lead to severe production deficit and decline the balance between pasture and livestock on which pastoral livelihood depends on. The study was undertaken to assess the variability and trends of rainfall in Borana pastoral area using monthly rainfall record for the period 1987-2016 of Yabello and Eel-wayye station. Rainfall variability analysis has been done using variability indices like, coefficient of variation, precipitation concentration index and Standard anomaly index. Trend analysis was carried out using Man-Kendall trend test 5% significance level. The coefficient variation of the study area for Yabello was 21.2%, while for Eel-wayye it was 53% which showed high inter-annual variability. The negative anomalies at Yabello station was 53.3% While in Eel-wayye station, revealed 56%. The analysis result indicted that the rainfall concentration index value ranged from 13.2 to 30.23 for the stations which shows moderate to strong irregularly rainfall distribution. The year 2006 was the most drastic and distinct-wide extreme drought episode in both stations, Except short rainy season at Eel-wayye station, the Mann–Kendal test shows not statistically significant (P<0.05). Increasing tendencies of drought during main rainy season and decreasing tendencies of drought during short rainy season and annually were observed in the study area. This threats the livestock production systems, which is the backbone of the pastorals livelihood. The study, suggests policy makers to develop other sustainable water sources for lowlands pastorals.