Temporal Variability Of Rainfall Research Articles

Rainfall variation over Sinai Peninsula and its teleconnection to El Niño sea surface temperature

This study aims at investigating the spatial and temporal variability of the seasonal rainfall over Sinai Peninsula, Egypt, relying on rainfall data taken from gridded data of four gauge stations for 35 years. Moreover, this study determines the teleconnection between the seasonal rainfall and equatorial Pacific sea surface temperature (El Niño SST) over El Arish and Wadi Watir. Due to non-stationary characteristics of Sinai rainfall, this study employs the Wavelet Principal Component Analysis (WPCA) technique. According to the spatial characteristics of January, February and March (JFM), and October, November and December (OND) rainfall seasons, Sinai Peninsula can be divided into two zones: northern zone along the coastal area of the Mediterranean, and central-southern zone. The WPC signals showed that the dominant frequency period of Sinai rainfall ranged 2–8 years. Using Wavelet Coherence (WC), the study found a strong teleconnection between the seasonal rainfall over El Arish and Wadi Watir as well and El Niño SST at a 3-month lead time. The study results will improve the forecasting skills of flash water events over Sinai Peninsula, particularly, the northern zone in order to take suitable precautions to eliminate their impacts.

Spatio-temporal change in rainfall over five different climatic regions of India

AbstractThe present study deals with the estimation of dependences, spatio-temporal trends, change points, and stationarity in rainfall and rainy day series (1901–2013) for five (out of six) different climatic regions of India. Only one-fourth of the station rainfall and rainy day datasets exhibits long-term dependence on an annual and seasonal basis. The presence of lag-one serial correlation is prominent for almost all the climatic regions of India. The significant decreasing trend is found mainly for the stations of semi-arid and humid sub-tropical regions. The magnitude of rainfall is decreasing for most parts of the study area by 10% for annual and monsoon seasons. The change point is presented in a smaller number of stations. Non-stationary behaviour is observed for the rainy day series of semi-arid and humid sub-tropical regions, which may increase the temporal variability of rainfall over the same regions. The findings of this study could be very useful for the planning and management of water resources of different climatic regions of India.

Understanding the Temporal Variability of Rainfall for Estimating Agro-Climatic Onset of Cropping Season over South Interior Karnataka, India

Annual, seasonal and intra-seasonal variations in rainfall affect crop production from land preparation to the realization of potential crop yield in a region. Particularly, the onset of the rainy season is most crucial for determining the sowing period. Statistical analysis (Modified Mann-Kendall aka MMK-test for trend and likelihood ratio test for shifting pattern) of 60 years rainfall of south interior Karnataka (SIK) inferred the presence of temporal variability in rainfall. There was a monotonic increase in rainfall of February, March, April, June and August months (a positive sign of MM-K (tau) value), with a negligible rate of change (Sen’s slope towards zero). Upon seasonal analysis, there was a significant increase in winter, pre-monsoon and monsoonal rainfall as compared to post-monsoonal rainfall (higher Sen’s slope for pre-monsoon), indicating a need for agronomic interventions for estimating an effective date of sowing for reducing risks of crop production. Further, the agro-climatic onset of cropping season was estimated by considering soil–crop–water relations. Earlier onset of cropping season was estimated based on thresholds of soil–crop–water relations, which highlights sowing of crops in advance (May 1st fortnight) instead of late (June 1st fortnight) to avoid crop losses due to early-season drought.

Assessment of Meteorological Drought with Application of Standardized Precipitation Evapotranspiration Index (SPEI) for Tripura, Northeast India

Drought is one of the major water-related natural hazards. Understanding the spatial and temporal variation of rainfall is of great importance in water resources planning and management as it is related with food security and management of scarce water resource, which becomes critical in case of drought events. The advent of GIS to produce spatially interpolated drought map helps the water managers to undertake appropriate measures in drought relief and prioritization of drought mitigation works. Limitation of literature on Tripura suggests that study of drought over Tripura could help in strengthening of mitigation planes and rationalization of disaster management policies. Hence, the present study is focused to investigate the drought persistence and severity in the Tripura state of India during the period 1980-2013, using Standardized Precipitation Evapotranspiration Index (SPEI). Three time scale i.e., 3, 6 and 12 month time scales were opted for the study. Gridded monthly precipitation data distributed over the four districts of Tripura was used for drought analysis. Significant drought events were detected over the study area during the selected period. Annual analysis of SPI time series showed that the study area received the intense drought during the year 1985. Geospatial technique was used to generate the SPEI drought map for the year 1985.

Tree growth responses to temporal variation in rainfall differ across a continental-scale climatic gradient.

Globally, many biomes are being impacted by significant shifts in total annual rainfall as well as increasing variability of rainfall within and among years. Such changes can have potentially large impacts on plant productivity and growth, but remain largely unknown, particularly for much of the Southern Hemisphere. We investigate how growth of the widespread conifer, Callitris columellaris varied with inter-annual variation in the amount, intensity and frequency of rainfall events over the last century and between semi-arid (<500 mm mean annual rainfall) and tropical (>800 mm mean annual rainfall) biomes in Australia. We used linear and polynomial regression models to investigate the strength and shape of the relationships between growth (ring width) and rainfall. At semi-arid sites, growth was strongly and linearly related to rainfall amount, regardless of differences in the seasonality and intensity of rainfall. The linear shape of the relationship indicates that predicted future declines in mean rainfall will have proportional negative impacts on long-term tree growth in semi-arid biomes. In contrast, growth in the tropics showed a weak and asymmetrical (‘concave-down’) response to rainfall amount, where growth was less responsive to changes in rainfall amount at the higher end of the rainfall range (>1250 mm annual rainfall) than at the lower end (<1000 mm annual rainfall). The asymmetric relationship indicates that long-term growth rates of Callitris in the tropics are more sensitive to increased inter-annual variability of rainfall than to changes in the mean amount of rainfall. Our findings are consistent with observations that the responses of vegetation to changes in the mean or variability of rainfall differ between mesic and semi-arid biomes. These results highlight how contrasting growth responses of a widespread species across a hydroclimatic gradient can inform understanding of potential sensitivity of different biomes to climatic variability and change.

Evaluation of the Performance of CMIP6 Models in Reproducing Rainfall Patterns over North Africa

This study assesses the performance of historical rainfall data from the Coupled Model Intercomparison Project phase 6 (CMIP6) in reproducing the spatial and temporal rainfall variability over North Africa. Datasets from Climatic Research Unit (CRU) and Global Precipitation Climatology Centre (GPCC) are used as proxy to observational datasets to examine the capability of 15 CMIP6 models’ and their ensemble in simulating rainfall during 1951–2014. In addition, robust statistical metrics, empirical cumulative distribution function (ECDF), Taylor diagram (TD), and Taylor skill score (TSS) are utilized to assess models’ performance in reproducing annual and seasonal and monthly rainfall over the study domain. Results show that CMIP6 models satisfactorily reproduce mean annual climatology of dry/wet months. However, some models show a slight over/under estimation across dry/wet months. The models’ overall top ranking from all the performance analyses ranging from mean cycle simulation, trend analysis, inter-annual variability, ECDFs, and statistical metrics are as follows: EC-Earth3-Veg, UKESM1-0-LL, GFDL-CM4, NorESM2-LM, IPSL-CM6A-LR, and GFDL-ESM4. The mean model ensemble outperformed the individual CMIP6 models resulting in a TSS ratio (0.79). For future impact studies over the study domain, it is advisable to employ the multi-model ensemble of the best performing models.

Temporal and Agricultural Factors Influence Escherichia coli Survival in Soil and Transfer to Cucumbers.

Biological soil amendments of animal origin (BSAAO) increase nutrient levels in soils to support the production of fruits and vegetables. BSAAOs may introduce or extend the survival of bacterial pathogens which can be transferred to fruits and vegetables to cause foodborne illness. Escherichia coli survival over 120 days in soil plots (3 m2) covered with (mulched) or without plastic mulch (not mulched), amended with either poultry litter, composted poultry litter, heat-treated poultry pellets, or chemical fertilizer, and transfer to cucumbers in 2 years (2018 and 2019) were evaluated. Plots were inoculated with E. coli (8.5 log CFU/m2) and planted with cucumber seedlings (Supremo). The number of days needed to reduce E. coli levels by 4 log CFU (dpi4log) was determined using a sigmoidal decline model. Random forest regression and one-way analysis of variance (ANOVA; P < 0.05) identified predictors (soil properties, nutrients, and weather factors) of dpi4log of E. coli and transfer to cucumbers. The combination of year, amendment, and mulch (25.0% increase in the mean square error [IncMSE]) and year (9.75% IncMSE) were the most prominent predictors of dpi4log and transfer to cucumbers, respectively. Nitrate levels at 30 days and soil moisture at 40 days were also impactful predictors of dpi4log. Differing rainfall amounts in 2018 (24.9 in.) and 2019 (12.6 in.) affected E. coli survival in soils and transfer to cucumbers. Salmonella spp. were recovered sporadically from various plots but were not recovered from cucumbers in either year. Greater transfer of E. coli to cucumbers was also shown to be partially dependent on dpi4log of E. coli in plots containing BSAAO.IMPORTANCE Poultry litter and other biological soil amendments are commonly used fertilizers in fruit and vegetable production and can introduce enteric pathogens such as Escherichia coli O157:H7 or Salmonella previously associated with outbreaks of illness linked to contaminated produce. E. coli survival duration in soils covered with plastic mulch or uncovered and containing poultry litter or heat-treated poultry litter pellets were evaluated. Nitrate levels on day 30 and moisture content in soils on day 40 on specific days were good predictors of E. coli survival in soils; however, the combination of year, amendment, and mulch type was a better predictor. Different cumulative rainfall totals from year to year most likely affected the transfer of E. coli from soils to cucumbers and survival durations in soil. E. coli survival in soils can be extended by the addition of several poultry litter-based soil amendments commonly used in organic production of fruits and vegetables and is highly dependent on temporal variation in rainfall.

Spatio-temporal rainfall variability of equatorial small island: case study Bintan Island, Indonesia

The water resources of Bintan Island depend much on rainfall since the impervious granitic basement that bears a low water storage capacity dominates the geology of Bintan Island. Water demand in Bintan is increasing due to both population and economic growth. This paper aims to determine the spatial and temporal rainfall variability over Bintan Island using the daily corrected-CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data) version two (v2.0) dataset to a ground-based observation dataset (Kijang station) using quantile-base bias correction for period 1 January 1981–31 August 2018. For the analysis process, we used monthly corrected-CHIRPS, NINO 3.4 anomaly index, the DMI (dipole mode index), zonal and meridional wind, and specific humidity from January 1981 to December 2017. Semi-annual, annual, and interannual variations influence monthly rainfall amounts over the island. Two peaks representing equatorial and monsoonal patterns characterize the temporal variability of rainfall. Spatially, the southern part of the island receives more rainfall than the northern part especially in MAM and SON related to the more convergence of moisture. The effects of interannual variation, ENSO (El Nino-Southern Oscillation) and IOD (Indian Ocean dipole), vary with season. ENSO contributes more to rainfall variability than IOD during the period of study.

Variation in physical characteristics of rainfall in Iran, determined using daily rainfall concentration index and monthly rainfall percentage index

Variations in rainfall characteristics play a key role in available water resources for a country. In this study, spatial and temporal variations in rainfall in Iran were determined using the daily rainfall concentration index (DRCI) and monthly rainfall percentage index (MRPI), based on 30-year (1987–2016) daily precipitation records from 80 meteorological stations throughout Iran. The results showed that MRPI differed between locations within Iran, with increasing or decreasing trends observed in different areas. The highest significant decreasing trend in MRPI (3–7% per decade) was found for March rainfall in western Iran, and the highest increasing trend in MRPI (3–7% per decade) for November rainfall in eastern and southern Iran. The DRCI values obtained varied from 0.57 to 0.71, indicating moderate and high rainfall concentrations, with the highest DRCI values in coastal zones of Iran near the Caspian Sea and the Persian Gulf. Trend analysis showed increasing trends in DRCI values at 80% of meteorological stations, and these trends were significant at 37% of those stations.

Spatio-temporal analysis of rainfall, meteorological drought and response from a water supply reservoir in the megacity of Chennai, India

Assessment of rainfall variability and drought is essential to address the existing water crisis and water resources management. This study was carried out to assess the rainfall variability, meteorological drought and relative response of a water supply reservoir located in Chennai Metropolitan, India. Spatial and temporal variation of rainfall and drought across the river basin was assessed using historical rainfall records from 1978 to 2016. A significant number of rainfall stations show increasing trends in post-monsoon and northeast monsoon. The annual rainfall is concentrated for less than six months and shows an irregular to strongly irregular distribution. The degree of variability in monthly rainfall reveals markedly seasonal with long dry periods. Three different drought indices such as rainfall deviation method, Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI) were used and compared to identify the meteorological droughts. The duration of meteorological drought events in this region ranged from 3 to 9 months. Identified drought events reveal that the rainfall deficiency in the northeast monsoon causes most of the meteorological drought. The reservoir system has higher response and coherence with SPI at a higher time scale. So, SPI can be used to represent the hydrological drought in higher time scales. Hence, SPI is recommended as more appropriate for drought assessments for this region. The large scale atmospheric circulations have moderate impacts on drought events in this region. The outcomes of this study could be useful for better drought and water resources management.

Agricultural community-based impact assessment and farmers\u2019 perception of climate change in selected Ecological Zones in Nigeria

BackgroundThe impacts of climate change are affecting sustenance and livelihood of many rural farmers in Africa. The majority of these farmers have low adaptive capacity. This study investigates climate change impacts, farmers’ perception, adaptation options and barriers to adaptation in three selected ecological zones in Nigeria using three staple crops. Rainfall and temperature data of over 35 years were analysed using ANOVA, Mann Kendall and Sen’s Slope Analysis. Farmers’ perception of climate change and cropping experiences were assessed with the aid of a well-structured questionnaire, semi-structured interview and focus group discussion.ResultsThe results of the study revealed high variability in the annual and monthly rainfall and temperature during the study period. The highest annual maximum temperature was recorded in Kwara with Tmax > 32 ℃. Though, there appeared to be spatial and temporal variations in rainfall in the study area, the highest was in Ogun with mean annual rainfall = 1586.9 mm and lowest in Kwara with mean annual rainfall = 1222.6 mm. Generally the Mann Kendall and Sen's slope analysis revealed general increase in the minimum and maximum temperature, while rainfall revealed generally downward trend. The study revealed a difference in farmers’ perception but nearly 74% of farmers perceived that climate is changing, which is affecting their farming activities. Nearly 70% claimed that lack of financial capital is the major barrier to climate change adaptation.ConclusionsThe study concludes that rainfall and temperature variability have significantly impacted cropping and that farmers are aware of long-term changes in temperature and rainfall, but some are unable to identify those changes as climate change. There is a need for affordable and available improved seedlings and variety of crops that can adapt to climate change conditions.

Spatiotemporal variability and trends of rainfall and its association with Pacific Ocean Sea surface temperature in West\xa0Harerge Zone, Eastern Ethiopia

BackgroundRainfall variability exceedingly affects agriculture in Ethiopia, particularly in the eastern region where rainfall is relatively scarce. Hence, understanding the spatiotemporal variability of rainfall is indispensable for planning mitigation measures during high and low rainfall seasons. This study examined the spatiotemporal variability and trends of rainfall in the West Harerge Zone, eastern Ethiopia.MethodThe coefficient of variation (CV) and standardized anomaly index (SAI) were used to analyze rainfall variability while Mann-Kendall (MK) trend test and Sen’s slop estimator were employed to examine the trend and magnitude of the rainfall changes, respectively. The association between rainfall and Pacific Ocean Sea Surface Temperature (SST) was also evaluated by Pearson correlation coefficient (r).ResultsThe annual rainfall CV during 1983–2019 periods is between 12 and 19.36% while the seasonal rainfall CV extends from 15–28.49%, 24–35.58%, and 38–75.9% for average Kiremt (June–September), Belg (February–May), and Bega (October–January) seasons, respectively (1983–2019). On the monthly basis, the trends of rainfall decreased in all months except in July, October, and November. However, the trends were not statistically significant (α = 0.05), unlike in November. On a seasonal basis, the trends of mean Kiremt and Belg seasons rainfall decreased while it increased in Bega season although it is not statistically significant. Moreover, the annual rainfall showed a non-significant decreasing trend. The findings also revealed that the correlation between rainfall and Pacific Ocean SST was negative for Kiremt while positive for Belg and Bega seasons. Besides, annual rainfall and Pacific Ocean SST was negatively correlated.ConclusionsHigh spatial and temporal rainfall variability was observed at the monthly, seasonal, and annual time scales. Seasonal rainfall has high inter-annual variability in the dry season (Bega) than other seasons. The trends in rainfall were decreased in most of the months. Besides, the trend of rainfall decreased in the annual, Belg and Kiremt season while increased in the Bega season. The study also indicated that the occurrence of droughts in the study area was associated with ENSO events like most other parts of Ethiopia and East Africa.

The effect of hillslope geometry on Hortonian rainfall-infiltration-runoff processes

Topography is one of the main factors in hillslope rainfall-runoff processes. The effect of hillslope geometry, representing an important aspect of topography, on Hortonian rainfall-runoff has not been fully understood. In order to investigate this effect, hillslope geometry was abstracted as the combination of longitudinal profile curvature and plan shape, and a set of representative hillslope surfaces were generated using a variety of values of the profile curvature and plan shape factor. The infiltration and Hortonian runoff processes, mainly characterized by ponding time, infiltration rate, and runoff rate and depth, were computed using Richards’ equation for variably-saturated flow with given initial soil moisture, rainfall, and soil texture. The results show that different profile curvature and plan shape can cause more than 10% difference in cumulative runoff and runoff rate and more than 20% difference in ponding time. The curvature of hillslope longitudinal profile affects infiltration and runoff nonmonotonically and plays a more important role than the plan shape, whose effect is monotonic. The profile curvature and plan shape can complicate each other’s effect, but the effect of profile curvature also varies with rainfall duration. For a fixed plan shape, the longest time to ponding occurs on the straight profile hillslope. Hillslopes with opposite values of the plan shape factor and curvature have similar infiltration and runoff processes because of the similar slope gradient distributions. The widely used time compression approximation (TCA) for rainfall infiltration prediction after ponding can lead to an error of more than 37% when applied to hillslopes with a curved profile and variable width. This is because of the inaccurate estimation of the ponding time, especially for low intensity rainfalls, suggesting the presence of partial area runoff on these hillslopes. In addition, the results show that the effect of subsurface lateral flow near surface is generally negligible, and the run-on effect causes more infiltration on convex hillslope topography. The soil property and rainfall temporal variability do not change the trends but can alter the magnitudes of the hillslope geometry effect. The study provides insights into the rainfall runoff processes on natural hillslopes that could benefit studies related to hillslope hydrology and geomorphology.

Geo-statistical assessment of meteorological drought in the context of climate change: case of the Macta basin (Northwest of Algeria)

Northwestern Algeria experiences a high number of spatial and temporal variations in precipitation. This phenomenon predominantly alters the duration as well as the frequency of drought in this region. The objective of this study is to detail the geographical variations in terms of drought intensity, duration, magnitude and frequency in the Macta basin using time series of rainfall data for 42 years (1970–2011) from 42 rainfall stations. The methodology employed lies in analyzing the spatial and temporal variations of rainfall along with the computation of the standardized precipitation index (SPI) to assess the spatial–temporal variations of meteorological drought over different time scales. The Sen’s slope test estimator, Mann–Kendall (MK) test, and the recently developed Innovative Trend Analysis (ITA) method were used for the purpose of evaluating the precipitation trend. The application of the above-mentioned methods has shown a very notable increasing trend during autumn and a decreasing trend during spring precipitation. In this scenario, the annual, winter, and summer precipitation time series experienced a mixed (increasing as well as decreasing) trend. The magnitude of the highest increasing (decreasing) precipitation trend was found at 2.20 mm/season (− 2.55 mm/season) during autumn (spring) season. The annual precipitation trend was in the range of − 4.93 mm/year and 5.29 mm/year. A decreasing trend was observed from both MK and ITA tests in the northern part of the Mediterranean Sea, near the coastal region in Macta basin, whereas the increasing trend was observed in the south. In drought analysis, the long-term frequency drought showed that both northern and western regions faced drought conditions most of the time in comparison with southern and eastern parts of the study area. This infers that the northern and western parts lack long-term water resources. Further, the northern part of the basin usually experiences severe drought conditions when compared to other parts. Drought duration varies from 9 to 37 months with an average of 20 months. Thus, this area is cited to be highly sensitive and prone to droughts compared to other parts of the basin. These findings would be very useful in applying drought adaptation policies by water resource managers in the Macta basin.

Spatial and temporal variability of rainfall over the Republic of Djibouti from 1946 to 2017

AbstractFor the first time, the spatial and temporal variability of rainfall in the Republic of Djibouti is investigated using data from 14 weather stations over the period 1946–2017. Due to limited data availability, high‐resolution long‐term satellite rainfall products (CHIRPS, PERSIANN‐CDR, TAMSATv3, ARC2) and ERA5 reanalysis also contribute to document time–space rainfall variability at monthly, seasonal and annual scales. Principal component analysis identifies two spatially coherent regions of rainfall variability in the east (coastal zone) and the west (inland zone) of the country. Annual rainfall amounts are everywhere very low (60–300 mm), but with contrasted regimes. At seasonal scale, the highest rainfall amounts in the eastern part of the country are found between October–December (OND) and March–May (MAM), while July–September is the wettest season in the western part. The monthly rainfall regimes are relatively well reproduced by most products. ERA5 displays the highest monthly correlations with observations, followed by PERSIANN‐CDR and CHIRPS. Trend analysis since 1983 shows a significant decrease of rainfall during MAM which is in agreement with other parts of East Africa. On the other hand, nonsignificant decreasing trends are observed in January–February (JF) and OND. Only June–September (JJAS) revealed a nonsignificant increasing trend, but it follows a prior drying trend since the 1950s. The impact of large‐scale background climate on rainfall variability is assessed with focus given on El Niño Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD). Rainfall variability during OND shows a significant correlation with IOD, while in JJAS it is significantly negatively correlated with ENSO. In general, ERA5, CHIRPS and PERSIANN datasets are best able to reproduce rainfall patterns in Djibouti and suitable for further analysis. The fact that the interannual and decadal‐scale rainfall variations in Djibouti show large‐scale teleconnections with global sea‐surface temperature fields, as demonstrated in this study, provides good prospects for the prediction of rainfall variations at a range of different temporal scales.

Climate Change Impact on Vegetation Dynamics in Tensift Region, Morocco

Tensift region is known by an arid and semi-arid climate. The city of Marrakech, experience an important temporal variability in rainfall and an increasing trend of temperature during the last five decades. However, the evolution of rainfall is more contrasted by a downward trend in Marrakech, it is also distinguished by alarming clues of global warming, like the number of hot days and heat waves. This paper evaluates the effect of climate change on Vegetation cover (evaluated by NDVI) in the Tensift region, Morocco. Temperature, rainfall data, and vegetation cover were used in this analysis. The effect of climate change on vegetation was studied using a linear regression analysis method, to explore the relationship between vegetation dynamics and climate factors (the trend of vegetation dynamics for the years between 1973 -2019). Analysis of annual data, for the temperature and vegetation cover shows a low regression coefficient value of 0.3057 and, rainfall and vegetation cover analysis show regression coefficient value of 0.7024. Monthly periods analysis showed that the most important period is the one between December and May where the regression coefficient value is 0.6568. In more details the period between March and May shows regression coefficient value of 0.4685, the period between December and February shows regression coefficient value of 0.434, the period between September and November shows regression coefficient value of 0.0734. The study reveals that, rainfall is significantly related with vegetation cover, especially the period between December and May, more than the temperature does in Tensift region.

Temporal Variations in Rainfall and Temperature and their Effects on the River Discharge in the Mara River Basin

The Mara River basin is one of the important transboundary resources in Eastern Africa that not only serve Kenya and Tanzania where it is located as one of the waterheads but also serve the lower countries of Sudan and Egypt. Variations in weather conditions, especially rainfall and temperature in the basin have impacts beyond the basin. The environmental processes that relate to variation in weather conditions include river flow regimes, vegetation cover, agro-calendar and wildlife. This paper looked at how variations in rainfall and temperature affect the river discharge in the Mara basin in order to determine the nature of rainfall and temperature variations in relation to river discharge in the basin. Observed long-term daily rainfall, temperature and river discharge covering 1983 – 2014 period, are used in time series analyses to measure periodicity and trend in rainfall, temperature and river discharge. The relationship between river discharge and the weather elements is determined using linear correlation analysis and multiple regression procedures at ? = 0.05. The results of the data analysis reveal that, the long-term variations in temperature, rainfall and river discharge are such that temperatures are tending toward increase while rainfall and river discharge are tending towards decline. Further, variations in rainfall and temperature conditions indicate un-seasonality in the timing and duration of monthly variations. The variations in rainfall, temperature and discharge series are statistically not significant (Mann Kendall trend test). The relationship between variations in rainfall and temperature with river discharge is that rainfall has stronger linear correlation with river discharge than temperature and therefore declining trends in rainfall are causing reduction in river discharge in the Mara basin. Measures should, therefore, be taken to reduce activities in the basin that are likely to impact on rainfall and temperature such as deforestation and encroachment on the water towers.

Rainfall trend and variability over Opak River basin, Yogyakarta, Indonesia

Rainfall intensity seems to be increasing nowadays due to climate change as presented in many studies of both global and regional scale. Consequently, cities worldwide are now more vulnerable to flooding. In Indonesia, increasing frequency of floods was reported for the past decades by The National Agency for Disaster Countermeasure (BNPB). To understand the rainfall changes, long-term trend evaluation over a specific area is then crucial due to the large variability of spatial and temporal rainfall distribution. This study investigates the homogeneity and trend of rainfall data from 20 stations over the Opak River basin, Yogyakarta, Indonesia. A long-term ground observation rainfall data whose period varies from 1979 to 2019 were analyzed. Non-parametric Mann – Kendall test was applied to assess the trend, while the magnitude was calculated using the Sen’s slope estimator. An increasing annual maximum of daily rainfall intensity was observed at four stations on a 0.95 confidence level based on the Mann – Kendall test, while the Sen’s slope estimator shows a positive trend at almost all stations. The trend of heavy rainfall frequency was also found to be significantly increased, with only one station showed a decreasing trend. Furthermore, this paper also described the spatial and temporal rainfall variability. Positive trend was mostly found during the rainy season, while the negative trend occurred during the dry season. This could pose a challenge for water resource management engineering and design, such as water supply systems or reservoir management. Understanding this phenomena will benefit hydrologists in preparing future water resource engineering and management.

The Innovative Trend Analysis Applied to Annual and Seasonal Rainfall in the Tafna Watershed (Algeria)

Abstract This study analyzes the temporal variability of seasonal and annual rainfall in the Tafna watershed (Northwest Algeria), using a homogeneous monthly rainfall database from 17 stations of 46 years of observation (1970-2015). Possible trends in seasonal and annual variations in rainfall were detected using the innovative trend analysis (ITA), which identifies trends in the low, medium and high values of a series. The results obtained indicate that seasonal rainfall showed a decreasing trend in winter and spring, while increasing trend is detected in summer and autumn. Low and high values categories are the most affected by the decrease in winter, while for spring it is the medium and high values, which are affected. In addition, spring showed the greatest decrease in arithmetic average and standard deviation. On the other hand, summer and autumn, present a growing trend affecting the low and high values, while in autumn, these are the medium and high values. Summer recorded the maximum increase in arithmetic average and standard deviation, and may present a flooding risk in future. Annually, a decreasing trend dominate. Most stations are marked by a decrease in their annual arithmetic means and standard deviation.

Assessment of the effect of extreme rainfall events on temporal rainfall variability in Kuwait

In recent decades, Kuwait is witnessing an increase in the number of flash floods, which puts a serious risk on human lives and properties. During November 2018, the highest extreme rainfall event was recorded in Kuwait. This paper aims at investigating the frequency of occurrence of extreme rainfall events and their effect on the temporal variability of rainfall in Kuwait. Statistical methods were implemented, such as frequency analysis of annual maximum hourly and daily rainfalls, in addition to the cumulative departure from the mean (CDM) to analyze the effect of extreme rainfall events on the temporal pattern of rainfall in Kuwait. The results show that the total annual rainfall is very wide from 31 mm in 1964 to 344 mm in 2018, while the general trend of rainfall in Kuwait is increasing with time. The statistical analysis based on developing suitable cumulative density functions for rainfall events in Kuwait shows that the return periods of the annual maximum hourly (41.5 mm/h) and the annual maximum daily (103.1 mm/day) rainfall events were 50 and 155 years, respectively. The analysis show that without the rainfall data of 2018, 49% of the CDM curve remains above the average limit of 112 mm/year. However, when the extreme rainfall events of 2018 are included in the analysis, only 11% of the CDM curve remains above the mean line of the new average limit of 116 mm. The study concluded that the rainfall pattern of Kuwait is affected considerably by extreme rainfall events and the amount of rainfall increases against reduction in number of days in the recent decades, which accordingly increases the rainfall intensities to produce more flash floods.