Precipitation Concentration Index Research Articles

Towards sustainable precipitation management in Madurai Town Planning Area (India)

This study aimed to look for efficient development strategies towards achieving sustainable precipitation management in the Madurai Town Planning Area (MTPA) in India. In the MTPA, precipitation is the predominant source of freshwater for agricultural and domestic uses in addition to water received through conventional systems. The average annual precipitation in the region is ~ 816 mm with standard deviation of 233 mm. The regression analysis showed that annual precipitation is following a decreasing trend and will be about 716 mm by 2030. The Precipitation Concentration Index (PCI) values ranging from 18 to 20 represented strong irregularities and seasonality in annual precipitation over the study area. March, July, September, and November months contributed 2.5, 6.19, 14, and 16% to annual precipitation, respectively, and all showed decreasing trends over time. Only 20% of Northeast monsoon was active over the past 44 years (1976–2019), resulting in a 15% probability of flood and drought occurrences throughout the MTPA. The long-term (1976–2019) average value of annual precipitation days was about 42. The Concentration Index (CI) showed that 60–70% of precipitation was received within 25% of precipitable days. Daily precipitation class of moderate (7.5–34 mm) and rather heavy (34–64 mm) ranges were the dominant types of precipitation, contributing 46% and 26% to total annual precipitation, respectively. Except for October, the monthly precipitation received was deficit to meet the irrigation water demand in the MTPA. However, development of precipitation harvesting systems can annually preserve about 27 Mm3 freshwater in the urban space of the MTPA.

Irregularity and time series trend analysis of rainfall in Johor, Malaysia

Due to its effect on weather and its propensity to cause catastrophic incidents, climate change has garnered considerable global attention. Depending on the area, the effects of climate change may vary. Rainfall is among the most significant meteorological factors associated with climate change. In Malaysia, changes in rainfall distribution pattern have led to many floods and droughts events which lead to La Nina and El Nino where Johor is one of the states in southern part that usually affected. Thus, rainfall trend analysis is important to identify changes in rainfall pattern as it gives an initial overview for future analysis. This research aims to evaluate historical rainfall data of Johor between 1991 to 2020. Normality and homogeneity tests were used to ensure the quality of data followed by Mann-Kendall and Sen’s slope analysis to determine rainfall trend as the rainfall data is not normally distributed (p > 0.05). Standardized precipitation anomaly, coefficient of variation, precipitation concentration index and rainfall anomaly index were used to identify rainfall variability and intensity while standard precipitation index was used to evaluate drought severity. The lowest annual rainfall recorded was 1725.07 mm in 2016 and the highest was 2993.19 mm in 2007. Annual rainfall and seasonal rainfall showed a declining trend although it is not statistically significant (p> 0.05). Results reveal that Johor experienced extreme wet and dry years, leading to drought and flood incidents. Major floods arose in 2006, 2007, 2008, 2010 and 2011 while driest years occurred in 1997, 1998 and 2016 which led to El Nino phenomenon. March and April were identified as the driest months among all. Thus, the findings from this study would assist researchers and decision-makers in the development of applicable adaptation and mitigation strategies to reduce climate change impact. It is recommended that more data analysis from more stations should be done in the future research study to obtain a clearer view and more comprehensive results.

Temporal Dynamics and Trend Analysis of Areal Rainfall in Muger Subwatershed, Upper Blue Nile, Ethiopia

This study was employed to investigate the temporal variability and trend analysis of areal rainfall in the Muger subwatershed, Upper Blue Nile, Ethiopia. The study was run over the following procedures to handle the main objective: (1) determining the areal rainfall from gauged point rainfall using the Thiessen polygon method, (2) grouping the months in the season according to the study area, (3) evaluating the temporal dynamics of annual and seasonal areal rainfall using the coefficient of variation (CV), standard anomaly index (SAI), and precipitation concentration index (PCI), and (4) analyzing the trend of annual and seasonal areal rainfall using modified Mann–Kendall’s (modifiedmk) test in RStudio. Based on the temporal variability analysis, CV results depict that annual and summer areal rainfall had low variability with values of 13.43% and 13.7%, respectively. Winter and spring areal rainfall shows high variation with a CV value of 50.5% and 36%, respectively. According to the SAI output, around 70% of the considered year was in the normal condition of wetness. On the other hand, the seasonal (winter, spring, and summer) rainfall distribution of the study area shows strong irregularity distribution throughout the considered years as a result of PCI with a value of 57.5%. The trend of the areal rainfall was shown to be both increasing and decreasing. However, the trend was insignificant with a 10% confidence level.

Rainfall Repercussions: Assessing Climate Change Influence on Iraq Precipitation Patterns

The unequal spatial and temporal distribution of precipitation, exacerbated by climate change, has received significant attention. Rainfall is pivotal for crop growth and environmental health, crucial in the water cycle, and essential to replenishing surface water sources vital for drinking water supplies. Consequently, understanding this phenomenon is critical for future planning. Evaluating spatial and temporal variations in rainfall is essential for the effective management of water resources. This study employs a statistical analysis of rainfall data from 16 rain gauge stations to identify annual rainfall trends, Linear Regression Equations, Coefficients of Determination (R²), Precipitation Concentration Index (PCI), and Rainfall Variability Index (RVI). The findings of the study come to show as the PCI has indicated strongly irregular rainfall concentration in Iraq. RVI identifies 2017 and 1983 as notably dry years, while 2018 stands out as a particularly wet year within the 40-year period from 1980 to 2019. RVI also highlights that normal rainfall years predominate, with very dry years ranging from 2 to 13, dry years from 3 to 11, wet years from 1 to 7, and very wet years from 6 to 10 within the study period.

Assessment of rainfall erosivity for Bundelkhand region of central India using long-term rainfall data

Prevention of soil erosion requires long term assessment of rainfall erosivity and other related variables of the region. In the present study, four variables related to rainfall erosivity i.e. modified Fournier index (MFI), rainfall erosivity (R) factor, erosivity density (ED) and precipitation concentration index (PCI) were calculated. Long-term (1901-2021) daily rainfall data of Bundelkhand region (Central India) were used in the analysis. The above variables were assessed for spatial and temporal variability on annual and seasonal scale. The R-factor values range from 3010.61 MJ.mm ha-1 h-1 to 5346.53 MJ.mm ha-1 h-1, showing the region belongs to moderate to severe erosivity class. The mean annual R-factor, MFI, ED and PCI values for the Bundelkhand region were calculated as 4072.86 MJ.mm ha-1 h-1, 270.55 mm, 19.13 MJ ha-1 h-1 and 28.88, respectively. This study provides the insights of soil erosion problems of Bundelkhand region and would help in adopting the preventive measures and watershed development activities.

Spatiotemporal trends and variability of rainfall across agro-ecologies in East Guji Zone, Southeast Ethiopia

Distribution and trends of rainfall reveal spatial and temporal variability that have a paramount effect on the life and livelihood of small-holder farmers. This study aimed to analyze spatial variability and temporal trends of rainfall distribution across the three Agro-Ecological Zones (AEZs) of East Guji. Time series gridded daily rainfall data (1990–2020) were collected from the Ethiopian Meteorological Institution. Different descriptive statistics, trend tests: Man Kendal and Sen’s slope estimator, Inverse Distance Weighted Index and Precipitation Concentration Index (PCI) was used in the study. The finding demonstrated that altitude and rainfall decrease as one advances from the western (highland) to the eastern (lowland) direction in the study area where the highest rainfall was recorded in Solemo (highland) and the least in Negele (lowland).The study showed that as altitude increases annual rainfall also increases and rainfall variability decreases. Similarly the mean length of the growing season declines as one advance from the highlands to the lowlands. The PCI of the lowlands, midlands, and highlands AEZs was 19%, 17%, and 12% respectively. The PCI showed that those highlands had moderately concentrated rainfall but both lowlands, and midlands, had an irregular distribution of rainfall. The Coefficient of Variation (CV) indicated that highland areas had moderate variability in rainfall in all seasons except winter. In contrast, the low and midlands had shown high variability of rainfall (>30%) in all seasons. From a seasonal perspective, both CV and PCI revealed that the winter season showed more variability than others. Moreover, a significant increasing trend of annual rainfall was observed in the highlands AEZs (Bore 15.3mm/year and Solemo14.6mm/year), lowland AEZs (Chembe 10.9mm/year, Dawa 8mm/year and Bitata 7.8mm/year) as well as midland AEZs (Kercha 14.5mm/year) at a significant level of 5%. Therefore, strategies should be designed to use additional water resources for irrigation; and provide short-cycle grown and drought-resistant crops in the rest of the midlands and lowlands AEZs.

Annual and Seasonal Characteristics of Rainfall Erosivity in the Eastern Rhodopes (Bulgaria)

Rainfall, with its intensity, duration, and seasonal distribution, is among the main factors causing soil erosion, which is a widespread environmental problem in Bulgaria. Rainfall erosivity shows the potential of precipitation to generate erosion processes and is an essential indicator of the climate vulnerability of a region. This paper aims to evaluate rainfall erosivity in a part of the Eastern Rhodopes Mountains, an area that is characterised by high-intensity erosion processes and high erosion risk. Local peculiarities of rainfall erosivity were revealed by the calculation of some precipitation indices based on the monthly precipitation for the period 2000–2021, such as the precipitation concentration index (PCI), Angot precipitation index, Fournier index (FI), and modified Fournier index (MFI). The analysis of the extremely wet and extremely dry months at the annual and seasonal (October–March and April–September) levels was performed to evaluate the susceptibility to erosion. The results from the study show that rainfall erosivity in the studied area varies from low to moderate in the northern part of the study area and from high to very high in the south. According to the MFI, high and very high erosivities have been observed mainly since 2012. The erosivity increases from north to south, to the area with a complex relief, where the combination of orography and atmospheric circulation make favourable conditions for the occurrence of extreme precipitation. The analyses of the calculated indices show that the precipitations in most of the studied area generally have from a low to a moderate erosivity, but this does not exclude the occurrence of cases with high and very high erosivities, which are characteristic of recent years and are related to the increase in annual precipitations and extreme precipitation months. The results of this study can contribute to the development and implementation of measures and preventive activities for the reduction and possible elimination of the negative impacts of extreme precipitation.

Power Data Access Viewer-Based Meteorological Drought Analysis and Rainfall Variability in the Nile River Basin

Meteorological drought poses a frequent challenge in the Nile River basin, yet its comprehensive evaluation across the basin has been hindered by insufficient recorded rainfall data. Common indices like the standard precipitation index, coefficients of variation, and precipitation concentration index serve as pivotal tools in gauging drought severity. This research aimed to assess the meteorological drought status in the Nile River basin by using the Power Data Access Viewer product rainfall data. Bias correction procedures were implemented to refine the monthly rainfall data for Bahirdar, Markos, Nekemt, and Muger stations, resulting in notable improvements in the coefficient of determination (R2) that were increased from 0.74 to 0.93, 0.72 to 0.89, 0.71 to 0.96, and 0.69 to 0.84, respectively. The average spatial distribution of drought in the Nile basin was classified as extremely wet (3.81%), severely wet (9.01%), moderately wet (7.36%), near normal (9.97%), moderately drought (21.20%), severely drought (17.11%), and extremely drought (31.54%). Approximately 10.33% of the Nile River basin was situated in regions characterized by high rainfall variability, while around 21.17% was located in areas with a notably irregular precipitation concentration index. Overall, this study sheds light on the prevailing meteorological drought patterns in the Nile River basin, emphasizing the significance of understanding and managing these phenomena for the sustainable development of the region.

Less concentrated precipitation and more extreme events over the Three River Headwaters region of the Tibetan Plateau in a warming climate

Widely known as the “China Water Tower”, changes in precipitation concentration and insufficient rainfall days over the Three River Headwaters region (TRH) may threaten food and water security in TRH and downstream areas. However, current research on rainfall occurrences in TRH lacks a comprehensive understanding of the spatiotemporal variations in precipitation concentration, the seasonal distribution of rainy days across different rainfall categories, and their correlations with global warming. In this study, we utilize the CN05.1 gridded daily rainfall dataset to address these gaps. Our analysis reveals a decreasing trend in both the precipitation concentration index (PCI) and precipitation concentration degree (PCD), accompanied by an earlier onset of the precipitation concentration period (PCP) in TRH over the past six decades. The distribution of monthly rainfall becomes more uniform throughout the year, with precipitation spreading across a greater number of days annually. Notably, the reduction in both the number of rainy days and the proportion of rainfall during the summer, along with the decrease in the frequency of light and moderate rainfall days and the increase in the frequency of moderately heavy and heavier rainfall days, will lead to a more extreme distribution of summer precipitation in TRH. The increase in the number of rainy days across all intensity categories and the proportion of precipitation during winter, has favorable implications for the sustainable development and water security in TRH. Additionally, the relative increase in the occurrence of heavy and extremely heavy rainfall days in spring demonstrates the most pronounced change, with a notable rise of 12.74% to 28.24% per decade. This provides a certain degree of alleviation for spring drought in TRH. Furthermore, we find that for every 1-degree Celsius increase in global temperature, both PCI and PCD decrease by 9.82% and 8.5%, and PCP advances by 6.41 days. With the 50th percentile of precipitation serving as a dividing line, stronger precipitation events beyond this threshold exhibit a higher positive response to global warming. Conversely, weaker precipitation events falling below the 50th percentile show a higher negative response to global warming. Light rainy days decrease by 16.2% per degree Celsius of warming, while very heavy and extremely heavy rainy days increase by 26.4% and 27.5%, respectively. These findings have important implications for mitigating droughts and floods, as well as for developing a comprehensive framework for the management of water resources and agricultural irrigation in TRH.

CHIRPS rainfall product application for analyzing rainfall concentration and seasonality in Johor river basin, Malaysia

It is crucial to carry out a spatiotemporal evaluation of rainfall concentration in the Johor river basin (JRB) given that erratic rainfall can lead to floods. The study utilized the CHIRPS rainfall dataset from 1983 to 2018 to determine rainfall concentration using the Concentration Index (CI). To further define the rainfall regime, the Seasonality Index (SI) and Precipitation Concentration Index (PCI) were examined. The Mann-Kendall (MK) test was utilized to examine the trend at a 95% level of significance. The results showed the better accuracy of SI than PCI in classifying the rainfall regime in the JRB, defined as “equable but with a definite wetter season” type. The CI values ranged from 0.61 to 0.72 and were typically high all over the basin, with the northwestern and western regions having the highest values. At 27 grid points on the eastern border of the upper and middle parts of the basin, CI has significantly increased as a result of an upsurge in rainfall concentration brought on by climate change. More than 67% and up to 83% of the yearly rainfall for all grid locations was accounted for by the North East monsoon (NEM), with the 25% wettest days caused by high-intensity rainfall events.

Effects of precipitation changes on fractional vegetation cover in the Jinghe River basin from 1998 to 2019

Studying the spatiotemporal evolutionary characteristics of vegetation and the effect of precipitation changes is necessary for understanding the regional ecological environment. We used trend analysis, partial correlation analysis, significance tests, and residual trend analysis to analyze the spatiotemporal evolution characteristics and driving factors of fractional vegetation cover (FVC) in the Jinghe River Basin (JRB) from 1998 to 2019. The results showed that vegetation coverage in the JRB significantly improved from 1998 to 2019. FVC showed an increasing trend in 90.64% of the areas in the JRB, and the overall annual change in FVC was extremely significant (p ≤ 0.01). However, precipitation in the JRB showed an insignificant increasing trend; the annual distribution of precipitation developed in a uniform direction and the precipitation centroid tended to move backward. The area with a significant correlation between the FVC change and the precipitation concentration index accounted for the largest proportion (18.47%). Precipitation changes in the JRB generally favored vegetation recovery; however, the effect was limited and non-precipitation factors dominated the changes in FVC. Our study contributes to a more comprehensive understanding of the effects of changes in precipitation patterns on vegetation cover to facilitate regional ecological protection.

Temporal rainfall variability and drought characterization in Cheleka Watershed, Awash River Basin, Ethiopia

Study regionCheleka Watershed, lower Awash River Basin, Ethiopia. Study focusThe lower part of Awash River (Cheleka Watershed) with an area of 1744.48 km2 has limited rainfall temporal variability and drought incidence data. So, the study analyzed the temporal rainfall variability and drought incidence from five meteorological station starting from1988 up to 2017. Coefficient of variation, precipitation concentration index, mean and standard deviation were computed to analysis the temporal variations of rainfall; frequency and severity of droughts were characterized through rainfall anomalies indexes (RAI) and standardized precipitation indexes (SPI). New hydrological insights for the regionThe study found that, mean annual rainfall with a range value of 908.90 mm - 1181.48 mm in Batie and Majetie station respectively. Kiremt rainfall total with the highest coefficient of variation (22.93–29.12%) next to Belg rainfall total (39.31–52.43%) and the lowest variations of annual rainfall total (15–22.59%). Frequency of drought in 12 month’s interval indicates severely dry droughts, most frequently next to moderately dry drought. The maximum frequency for severely dry (8.61%) and moderately dry (11.39%) drought were occurred in Kemisse station. The longest duration and the highest magnitude drought were occurred in Kombolcha station next to Kemisse. As recommendation, since, this study was focused only temporal rainfall variability and drought characteristic, it is better that, future research will be conducted to evaluate the spatial rainfall variability and hydrological drought severity nature and its impact on socio-economic and human well-beings in the area.

Erratic Rainfall and its Upshot on Rice Production in Kerala

In recent years, rainfall irregularities have affected crop production in Kerala. Rice, a water-reliant crop, is the staple food of people in Kerala. It is challenging to revive paddy if the soil loses even 10 to 20 per cent of its moisture. Due to erratic rains and frequent dry spells, rain-dependent paddy cultivation is nearly impossible in Kerala. Among the three seasons of paddy cultivation in Kerala, the autumn season entirely depends on rainfall. According to 2020-21 Kerala agriculture statistics, the majority of the rice is cultivated under irrigated conditions in the state. This loss in rain-fed paddy cultivation was due to the decline in autumn rice cultivation after the mid-1990s. The study analysed the annual and seasonal rainfall variability and their relationships with autumn rice production in Kerala. The variability and concentration in the annual and seasonal rainfall were analysed using the coefficient of variation and the precipitation concentration index, respectively. The results revealed that the overall rainfall distribution pattern in Kerala was moderate to irregular. The seasonal index was estimated for the monthly rainfall data, and it was found that in June and July, the rainfall was the maximum. Production and productivity of autumn rice showed a high correlation with rains in June and July. The variability in rice production was positively influenced by rainfall and negatively influenced by the standard deviation of precipitation.

Spatiotemporal Evolution of Precipitation Heterogeneity Characteristics in the Heilongjiang Province from 1961 to 2020

Precipitation unevenness significantly influences the rational allocation of water resources and the management of agricultural irrigation. Based on precipitation data from 29 meteorological stations in Heilongjiang Province, China, from 1961 to 2020, this study calculated the precipitation concentration index (PCI), precipitation concentration degree (PCD), and precipitation concentration period (PCP) to analyze the spatial distribution characteristics of precipitation heterogeneity at three distinct timescales: year, maize growth period, and the four stages of the maize growth period. The findings reveal that the rainy season in Heilongjiang Province commences earlier in the southwest compared with the northeast and northwest, with a primary concentration in July. At the annual scale, PCI in southwestern Heilongjiang Province surpasses that in the southeastern region, displaying an approximate east–west gradient in PCD and PCP values ranging from 0.544 to 0.746 and 196 to 203, respectively. During the growth period scale, precipitation concentrates in the southwest and central regions, occurring earlier than in the northeast and northwest. In contrast to the annual scale, the PCI value is smaller, and precipitation predominantly concentrates in mid and late July. Examining the four stages of the maize growth period, PCD generally exhibits a decreasing gradient from west to east. The highest values of PCI and PCD manifest in the southwestern part of Heilongjiang Province, with precipitation concentrated in the middle of each growth stage. The research results serve as a valuable reference for policymakers and stakeholders involved in water resource allocation and agricultural water management in Heilongjiang Province.

Evaluation of an Alternative Functional Form to Fit the Lorenz Curve for the Concentration Index Calculation

Precipitation concentration indices have become a popular tool for analyzing the structure of daily precipitation amounts. Among the existing indices, the concentration index (CI) is widely used. In calculating the CI, an important aspect is adjusting the Lorenz curve based on the observed precipitation data. Usually, the fit has been carried out with equations of the type y = axebx. However, in some research work, it has been observed that sometimes, the fit obtained only partially describes the behavior of the data. Thus, this work evaluated an alternative functional form to fit the Lorenz curve. For this, daily precipitation data from 44 climatological stations in Mexico were used to assess two equations for adjusting the Lorenz curve. Once the fit was made, the goodness of fit was evaluated to determine which of the functional forms best described the behavior of the data. Results showed that the two functional forms produced similar results for low precipitation concentrations. However, when the concentration increased, the alternative functional form generated results following the behavior of the observations. Thus, it is recommended to use the alternative functional form to avoid overestimations of the concentration of daily precipitation in areas where it is known that a high concentration occurs.

Analysis of Changes in Rainfall Concentration over East Africa

Understanding the spatial and temporal distribution of precipitation is important in agriculture, water management resources, and flood disaster management. The present study analyzed the changes in rainfall concentration over East Africa (EA). Three matrices—the precipitation concentration index (PCI), the precipitation concentration degree (PCD), and the precipitation concentration period (PCP)—were used to examine the changes in rainfall during 1981–2021. The changes in spatial variance annually and during two seasons, namely, “long rains” (March to May [MAM]) and “short rain” (October to December [OND]), were estimated using an empirical orthogonal function (EOF). The study employed the robust statistical metrics of the Theil–Sen estimator to detect the magnitude of change and modified Mann–Kendall (MMK) to examine possible changes in rainfall concentration. The localized variation of the power series within the series for PCI, PCD, and PCP variability was performed using the continuous wavelet transform. The findings showed that the concentration of rainfall patterns of EA occurred in four months of the total months in a year over most parts, with the western sides experiencing uniform rainfall events throughout the year. The EOF analysis revealed a homogeneous negative pattern during the MAM season over the whole region for PCD, PCI, and PCP for the first mode, which signified reduced rainfall events. Moreover, the MMK analysis showed evidence of declining trends in the PCD annually and during the MAM season, while the opposite tendency was noted for the OND season where an upward trend in the PCD was observed. Interestingly, areas adjacent to Lake Victoria in Uganda and Lake Tanganyika in Tanzania showed increasing trends in the PCD for annual and seasonal time scales. The analysis to characterize the rainfall cycle and possible return period, considering the indices of PCD, PCI, and PCP, showed higher variability during the year 2000, while much variability was presented in the PCP for the annual period. During the MAM and OND seasons, a 1-year band as a dominant period of variability was observed in all the indices. Overall, the findings of the present study are crucial in detecting the observed changes in rainfall concentration for avoiding the loss of life and property, as well as for coping with potential changes in water resources.

Spatiotemporal variability of precipitation concentration in Pakistan

AbstractPrecipitation is a meteorological variable that plays a vital role in determining water resources and managing water risks. The intensity and frequency of precipitation extremes have increased in recent years; however, the changes in precipitation regimes across Pakistan remain unclear. This study analysed spatial and temporal changes in the precipitation concentration index (PCI) and concentration index (CI) from 100 meteorological stations across Pakistan from 1981 to 2017. Using innovative trend analysis (ITA) and Pettitt's test, we detected trends and change points in the annual and wet season PCI and CI. Additionally, we examined the relationship between PCI/CI values and latitude and altitude. The results revealed that the CI and PCI ranged between 0.48–0.78 and 10–55, respectively, with higher values being more prevalent in the dry and hot zones of the country. The study established a linear relationship between PCI/CI values, latitude and altitude, with higher values at lower altitudes and a decrease in values from south to north. Most stations presented a significant positive ITA trend for PCI and CI from 1981 to 2017, with a change between 1985 and 1995, indicating an overall increase in heavy precipitation events in the area. These findings are crucial for disaster preparedness, water resource planning, the mitigation of drought and flood risks, and conservation efforts.

Analysis the characterization of climate change and its impacts on smallholder farmers in Eastern Ethiopia

The impact of climate change on agriculture and food production is manifested through alterations in agro-ecological factors. The region of sub-Saharan Africa is particularly susceptible to the effects of climate change and variability, given its reliance on rainfall-dependent agriculture and inadequate adaptive capabilities. The objective of this study was to analysis of the characterization of climate change and its impacts on smallholder farmers in eastern Ethiopia. Historical daily rainfall, maximum and minimum temperature in 1991–2021 years of 12 weather station were collected from National Meteorological Institute of Ethiopia and NASA/POWER. Data quality control, trend test and outlier detection test were used. Climate characterization (onset, cessation, LGS and Dry/wet spell length) and precipitation concentration index were examined. The earliest, and latest start of rainy season in Kombolcha and Haramaya were 81DOY (March 21) and 225DOY (August 13) within mean 130DOY and 125DOY, respectively. In study area the minimum and maximum length of growing period of was recorded in Chinakesen and Haramaya by the values of 32DOY and 253DOY (Days of the year) respectively. In this arid and semi-arid areas, growing period was recorded under the short season crop maturity while long cropping season maturity does no satisfy crop water requirement due to moisture stress. The coefficient of variation of length of growing season from Mieso and Chinakesen were 36.2% and 47.9% which implies that the areas were highly vulnerable to climate extreme events of drought. Length of growing season (LGS) of Gemechis district was decreasing by a factor −2.533 shows highly significant at alpha value of 0.05 confidence level. Dry spell length probability occurrence of 5 days during the main cropping rainy season is significantly very high. The 30 years of data record suggests that a 29–48% precipitation concentration index of kiremt (JJAS) and belg (FMAM) seasonal rainfall which are demonstrating irregular precipitation. kiremt (JJAS) rainfall trend tests of Babile, Kurfa chale and Mieso districts were increasing by a factor of 2.016, 2.043 and 2.117, respectively and statistically significant at 95% confidence level, in the time period of 1991–2021 years. If furtherstudy will be examined climate extreme indices and adaptation strategies designed to simulate the impacts and variability of climate change in the study area.

Spatiotemporal Variability of Rainfall as an Evidence of Changing Climate over the Nigerian Niger Delta

This study assesses the spatial and temporal variability of rainfall over the Niger Delta area (Benin, Calabar, Port Harcourt and Uyo) in Nigeria between 1990 and 2020. The daily rainfall data used for this study were obtained through secondary source from NASA’s POWER (Prediction of Worldwide Energy Resources). Coefficient of variation, standardized anomaly index (SAI), precipitation concentration index (PCI) and seasonality index (SI) were used to evaluate rainfall variability and seasonality. The results of temporal analysis of annual rainfall indicated that Benin had the highest annual rainfall amount in 2000 and lowest in 1999 while Calabar and Port Harcourt had their highest rainfall amount in 2007 with the lowest occurring in 1991 and 2014 respectively. Uyo had the highest in 2000 and lowest in 2014. SAI also witnessed the presence of interannual variability of rainfall with negative and positive anomalies in 59.46% and 40.54% of the analyzed years, respectively. PCI and SI results implied that the Niger Delta area had strong irregular rainfall distribution. The results confirm the meteorological sensitivity to locations and provide support for the implementation of station and regional meteorological hazards prevention and to support the mitigation of hazards and improve the management practices of environment system in Niger Delta area.

Analysis of Historical Monthly and Annual Rainfall and Temperature Variability (1980–2020) in Baringo Couny County, Kenya

Climate variability entails the mean fluctuations in climatic elements and other observable characteristics on temporal or spatial scales. Assessing climate variability is a frequent practice in climatology based on its impact on social - economic aspects. Climate is subject to variations in many parts of world, exhibited mainly by rainfall and temperature fluctuations. The variability in Africa has resulted in the spread of desert conditions in the Sahel. Kenya experiences great variations of climate annually and considerable uncertainty when rains are expected, impacting negatively on farming activities. The study objective was to establish the historical trends of variability patterns in rainfall and temperature in Baringo County between 1980 – 2020. The study adopted a longitudinal study design as it involved a time series analysis of the trends and variability patterns of rainfall and temperature. Secondary data on rainfall and temperature was collected from Kenya Meteorological Services headquarters in Nairobi. Rainfall variability was determined and measured using the following techniques; Mean ( ), Standard deviation (SD), Precipitation concentration index (PCI), Relative variability (RV), Drought Intensity (DI) and Coefficient of variability (CV). Temperature variability was determined and measured by analyzing the County temperature distribution tables. Results indicated Baringo South to have a higher variability than Baringo North, marked with its higher CV, DI, RV and PCI. Pre-drought planning to cope up or overcome the droughts were highly recommended and measures provided. The study findings are expected to help farmers, the government and economic planners to focus on effective mitigation areas, formulate alternative policies on mitigating the effect of rainfall and temperature variability on activities of farming in Baringo County.