Annual Rainfall Amount Research Articles

Long-term effects of climatic and hydrological variation on natural vegetation production and characteristics in a semiarid watershed: The northern Negev, Israel

Climate models for semiarid and arid regions predict increasing average temperatures and reduced amounts of total annual rainfall. This warming and drying trend could have critical, adverse effects on natural vegetation activity and survival in arid and semiarid zones. We investigated the long-term effects of climate change and surface-runoff variations on the production of natural vegetation in a dry, undisturbed, first-order watershed in the northern Negev, Israel. Vegetation dynamics were estimated by normalized difference vegetation index. Yearly annual vegetation cover varied greatly during the monitoring period (2000−2013), but a significant positive regression was found with annual rainfall and runoff amounts, suggesting a strong relationship between annual vegetation dynamics and rainfall amount in a given year. A significant positive linear regression was found between annual ET0 values and year of measurement (1994–2013), with no corresponding decrease in vegetation condition. Surface runoff in the watershed affected the vegetation's water source. Large variation in annual runoff amounts was observed for 1994–2011, averaging 22.3 and 9 mm for the first (2000–2006) and second (2007–2013) vegetation-monitoring subperiods, respectively. Perennial vegetation was less sensitive to drought years than annual vegetation, likely due to differences in water-source availability. Perennials also benefited from the arrival of nutrients, organic matter, and fertile soil flowing with the surface runoff and eroded soil into their growing area.

Impact of rainfall structure and climate change on soil and groundwater salinization

Irrigated areas, mainly in arid regions, are threatened by salinization processes. Climate change inducing temperature rise and rainfall depletion are expected to enhance these processes. Numerical models are often used to predict salinization in the root zone as well as water and solute fluxes reaching groundwater. Climatic data, mainly rainfall, have an important influence on the estimation of those fluxes. The present paper studies the impact of rainfall structure and climate change on soil and groundwater salinization. Soil samples were collected in three drip-irrigated plots in Korba semi-arid coastal plain in Tunisia during dry and wet seasons. Collected field data (water contents and soil salinities) are used to define the initial solute and flow conditions and to estimate the soil hydraulic parameters for numerical modeling. Daily rainfall structure and annual rainfall transition under both Markov Chain and climate change (RCP4.5 and RCP8.5) are assessed. Different climatic scenarios are then introduced as boundary conditions in HYDRUS-1D, to test the influence of rainfall on the salinity evolution in the soil profile and groundwater. Results show that both annual rainfall amounts and daily structure have an impact on soil concentrations and solute fluxes quantities reaching groundwater. The influence of rainfall paths is more important for larger unsaturated zone thickness when considering the dry and median rainfall conditions. Climate change scenarios show significant accumulation of salts in the root zone implying the imperative use of adequate irrigation practices.

Spatial and Temporal Variation of Rainfall and Streamflow in the Kikuletwa Catchment of Upper Pangani Basin, Tanzania

Streamflow and rainfall records from 1980 to 2015 as a (common period for the analyzed stations) were used to analyze the variations of rainfall and streamflow in the Kikuletwa catchment. Also, the analysis of the longest time series available at each station up to 2015 (referred to as the whole series in this study) was conducted to relate past rainfall and streamflow changes, at the tributaries of Kikuletwa River located above the Rundugai natural springs as recommended from previous studies. Various methods such as simple statistics of the mean, standard deviation, coefficient of variance, and graphs were used to analyze intra-annual variations. Multi-year variability was analyzed by trends and change point tests using MannKendall and Pettitt tests respectively. The results of the study revealed the spatial variation of rainfall which was related to elevation differences. The streamflow amounts were found to vary from upstream to downstream. The whole time series analysis of annual rainfall and streamflow amounts revealed a decrease in rainfall and streamflow amounts for almost all stations though a significant decrease was only observed at two stations located on the upstream (for rainfall) and two stations located above the Rundugai natural springs (for streamflow). During 1980 – 2015, trends analysis indicated significant decreasing trends only in annual rainfall amounts at the two stations located on the upstream of the catchment with Z values of -3.20 and -2.68. In contrast, average annual flow trends analysis indicated significant decreasing trends at four stations out of five with Z values of -2.52, -2.28, -1.99 and -3.4 and, at one station insignificant decreasing trend was observed. The findings revealed the existence of other catchment influences to the streamflow changes other than rainfall during 1980-2015. The study provides very useful information that decides the necessity for separating the climate and human influences to the streamflow changes to find the most influencing factor.

Characteristics of sediment dynamics following large-scale sediment supply events in mountain watersheds in Japan

Large-scale sediment supply events (LSEs) cause not only a sudden increase in sediment discharge immediately after their occurrence, but also a long-term condition of elevated sediment yield. In Japan, many LSEs, triggered by heavy rainfall or earthquakes have created high risks for sediment-related disaster. However, the difference between sediment dynamics following a LSE triggered by rainfall and one triggered by an earthquake is unclear, as the sediment dynamics due to rainfall and those due to earthquakes have not been compared using consistent methodology. In this study, we estimated the volume of sediment supply VL (m3), time series of the volume of sediment yield VY (m3year−1) and the non-dimensional parameter NVY as estimated by dividing VL by the catchment area and annual maximum 3-day rainfall amount using the same methodology for 16 events in eight study basins in Japan. We used annual maximum 3-day rainfall amounts as a surrogate for discharge. Using these parameters, we estimated the period over which the effect of a LSE continues (PLS); sediment retention time (residence time, Tr1), and time for active sediment yield to recover to the background level (recovery time, Tr2a). In addition, we estimated the recovery time (Tr2b) based on when the maximum of NVY immediately after the LSE decreased to a certain extent. This calculation allowed us to estimate the recovery time even when background level was unknown. Both residence and recovery times ranged from <1 year to 19 years, with recovery time tending to be shorter than residence time. We found that Tr2b can be used as a substitute for Tr2a. No differences in PLS between rainfall-induced and earthquake-induced events were apparent, although VL differed markedly between event types. This discrepancy may be due to the difference in sediment connectivity between hillslopes and river channels. VY during the first and second year after a LSE associated with an earthquake is likely to be greater than that after a rainfall-associated event.

Multi-method groundwater recharge estimation at Eshito micro-watershed, Rift Valley Basin in Ethiopia

ABSTRACT Understanding recharge processes is fundamental to improve sustainable groundwater resource management. Shallow groundwater (SGW) is being developed for multiple purposes in Ethiopia without consideration of monitoring. We established a citizen science-based hydro-meteorological monitoring network, with a focus on SGW recharge estimation, in Eshito micro-watershed, Ethiopia. Citizen scientists collected rainfall, groundwater-level and stream water-level data. We characterized the shallow aquifer using pumping tests. The data were used to estimate SGW recharge using three methods: chloride mass balance, water-level fluctuation (WLF) and baseflow separation. Approximately 20% and 35% of annual rainfall amount contributes to recharge based on the chloride mass balance and WLF results, respectively. Baseflow separation showed recharge values for the watershed vary from 38% to 28% of annual rainfall at the upstream and downstream gauging stations, respectively. This study shows that the recharge in previously unmonitored micro-watersheds can be studied if citizens are involved in data generation.

Assessment of rainfall erosivity (R-factor) during 1986-2015 across Nepal: a step towards soil loss estimation.

Rainfall is a main cause of soil erosion which varies spatially and temporarily. R-factor is an erosive power of the rainfall that is responsible for soil detachment and subsequent displacement. Mathematically, it is expressed as a sum of the product of kinetic energy and maximum 30-min rain intensity. A precise assessment of R-factor needs higher temporal resolution rainfall data (sub-hourly) for a period of several years, which is rarely available. Many empirical approaches are used to predict R-factor as a function of mean monthly and annual rainfall amount. In this study, we used Loureiro and Countinho (Journal of Hydrology 250:12-18, 2001) approximation approach to estimate R-factor and explore its intra-annual variability using 30years (1986-2015) of daily rainfall data from 280 stations distributed across Nepal. This study employs different intra-annual variability indices and calculates erosivity density (ED) and weighted erosivity density (WED). The country average mean annual R-factor (MAR), annual ED, and WED are found to be 9434.8MJmmha-1h-1year-1, 4.39MJha-1h-1,and 1.61MJha-1h-1, respectively. On a monthly scale, July is the highest erosive month followed by August (> 2000MJmmha-1h-1month-1). Likewise, November is the lowest erosive month followed by December (~ 50MJmmha-1h-1month-1). Spatial distributions of these indices show clear delineations of areas with different erosivity patterns at different time of the year. In addition, this study explores inter-annual variation, temporal evolution, and trend estimation of R-factors over the country (for the first time). Significant rising trends are observed in the western region of the country. We found that the mean soil erosion for Nepal is estimated at 21.01 tonha-1year-1. The smallest R-factors are observed in the north-western region of the country and the maximum values are observed at mid hills and southern plains of the country. Our study could be an initial but important step for effective soil conservation, land use planning, and agricultural production.

The role of soil fertility in the management of agricultural bioproductivity

Relevance and methods. The optimal selection of precursors and methods of biologization can increase the return of organic matter to the soil, increase the yield and productivity of crops. Corn was studied on irrigation, and crops (sorghum, oats, winter wheat) in crop rotation were studied on the bogar. To elucidate the general patterns of plant development in the system of forest strips and in experimental fields (bogar), statistical processing of the research results was used in the Exel and Statistica software packages, which is based on the generalization and synthesis of the results, which makes it possible to reach forecasts of plant development during the growing season. The soil is light chestnut, heavy loamy, with a humus content in the arable layer of 1.74%, the pH of the soil solution is 8.1. The content of easily hydro-lyzable nitrogen is low — 3.2–3.9 mg/100 g of soil, average phosphorus mobile — 2.1–3 mg and exchange potassium increased — 30–40 mg/100 g of soil. The amount of average annual rainfall is 339.7 mm.Results. A study of the data showed that regardless of crop rotation the maximum content of nutrients (nitrogen, phosphorus, potassium) was observed in the tillering phase, then decreased. The correlation coefficient on irrigation shows the tightness of communication over the entire array and gives grounds to use the approximation of the multiple regression equation as predictive in the system of forest stripes on irrigation: Y = a + b1 Х1 + b2X2 and on the dry land: Y = a + b1X1 + b2X2 + b3X3. In dry years the yield of grain crops (corn, sorghum, oats, winter wheat) ranges from 0.59 to 1.73 t/ha. In wet years the yield of grain crops increases to 4.95 t/ha. With the help of programs you can calculate the amount of fertilizer for a given yield and manage the bioproductivity of crops in the system of forest belts and on the dry land. The importance of soil fertility in managing bioproductivity is based on the optimal selection of precursors and methods of biologization, which can increase the yield of grain crops. The scope of the recommendations is the Lower Volga soil zone.

SUPPLY OF NPK ELEMENTS THROUGH PRECIPITATION AND THROUGHFALL IN A COPPICE OF GREEN OAK IN THE EAST OF ALGERIA

Nutrient provisions through precipitation and throughfall represent major factor of the sustainability of the forest ecosystem. Nevertheless, data related to this aspect are non-existent in Algeria. Precipitation and throughfall volumes and their contributions in NPK elements were evaluated between 2012 and 2013, in a green oak coppice at Marconna in Aurès (eastern Algeria). Precipitation volumes were evaluated by the placement of 10 containers in a bare soil. To quantify the throughfall, four containers were installed under the canopy of each tree among 25 selected trees. Water samples taken from previously rinsed plastic bottles with distilled water were kept away from light and transported to the laboratory for volume estimation and chemical analysis, as quickly as possible. After rapid filtration, samples became ready for NPK analysis. Various devices and chemicals were used for the measurements of NPK elements in the laboratory. Kjeldahl's method, colorimetry and flame photometry were used for quantifying total nitrogen, phosphorus and potassium respectively. The results showed that annual rainfall amounts varied between 223,9 and 289,6 mm, whereas the annual throughfall was 127,1 mm for 2012 and 189,8 mm for 2013.Besides, the annual quantities of N, P and K returned to the soil by the rainfall ranged from 5,05 to 7,62 kg/ ha/year. However, the throughfall results showed that the coppice accumulated amounts of N, P and K elements varying between 4,08 and 5,47 kg / ha / year. On average, nitrogen was the most provided element. It represented 47,07%.

Potential impact of rainfall variability on groundwater resources: a case study in Uttar Pradesh, India

Groundwater systems are largely influenced by rainfall variability which is considered the principal source of recharge. The present study explores the relation between the long-term rainfall (1992–2014) and the corresponding water table variation over the Varanasi district. The temporal trends of both the water table and long-term rainfall were analyzed using non-parametric Mann-Kendall time-series trend test. The district experienced an annual rainfall average of 876 mm during the study period. In the recent decade (2003–2014), the amount of annual rainfall and rainy days declined by 42 mm and 8 days, respectively, were compared with previous decade (1992–2002). The water table fluctuation had also shown decreasing trend in the recent decade and were compared with the previous decade. The frequent fluctuations in rainfall anomaly and water table fluctuation had been related to El Nino and La Nina events to study the impact of these events at regional scale. The intense cultivation of water intensive crops as well as rainfall variation was found to be one of the major causes behind the water table fluctuation in the study area. Therefore, artificial water recharge and change in cropping pattern through cultivating less water consuming crops with efficient irrigation technologies of water management may help to overcome the upcoming adverse situations.

Study on the Effects of Extreme Precipitation for Seven Growth Stages of Winter Wheat in Northern Weihe Loess Plateau, China

The research on the characteristic frequency of precipitation is a great significance for guiding regional agricultural planning, water conservancy project designs, and drought and flood control. Droughts and floods occurred in northern Weihe Loess Plateau, affecting growing and yield of winter wheat in the area. Based on the daily precipitation data of 29 meteorological stations from 1981 to 2012, this study is to address the analysis of three different frequencies of annual precipitation at 5%, 50%, and 95%, and to determine the amount of rainfall excess and water shortage during seven growth stages of winter wheat at 5%, 10%, and 20% frequencies, respectively. Pearson type III curve was selected for this study to analyze the distribution frequency of annual rainfall and rainfall amount following seven growth stages of winter wheat crop in 29 stations of Northern Weihe loess plateau. As a result of our study, annual precipitation is gradually increasing from southwest to northeast of Northern Weihe loess plateau. The highest amount of annual precipitation occurred in the Baoji area and the lowest precipitation covered by the northwest area of Northern Weihe loess plateau. Moreover, the amount of rainfall of seven growth stages indicates that excessive rainfall occurs not only in the first stage (sowing to tillering) and seventh stage (flowering to ripening) but also in second stage (tillering to wintering). In the seventh stage, a large amount of excessive rainfall occurred in Changwu, Bin, Qianyang, Fengxiang, Baojiqu, and Baojixian. Moreover, water shortage is distributed in the third stage (from wintering to greening), the fourth stage (from greening to jointing), the fifth stage (from jointing to heading), and the sixth stage (from heading to flowering). Furthermore, the worst water shortages occurred in Hancheng, Heyang, Chengcheng, Pucheng, Dali, Tongchuan, and Fuping in the fourth stage (greening to jointing stage). Even though we study the crop water requirement under extreme rainfall conditions, the amount of rainwater still supply inadequate in some parts of the winter wheat growth stage. Therefore, this study provides main clues for the next step to study the irrigation water needs of winter wheat crops and to reduce agricultural risks in 29 counties in the northern loess plateau and other regions.

Long-term Variability of Summer Heavy Rainfall in the Seoul Metropolitan Area

The long-term variability of summer heavy rainfall in the Seoul metropolitan area was investigated in this study for the period of 1970-2018. The study period was divided into two phases; first phase from 1970 to 1994 and the second phase was 1995 to 2018. Long-term variability of summer heavy rainfall was examined using the change-point analysis method. Annual mean heavy rainfall amounts showed increasing trends in Seoul and Incheon during summer monsoon season (June to August). Results revealed that the changes in frequency and amount of heavy rainfall were observed larger in the months of July and August as compare to June during the second phase. The upper-level trough was prominently developed at the west of the Seoul metropolitan area and the core region of the upper-level jet was shifted to the east of the area during second phase. The western North Pacific subtropical high was expanded westward and moisture flux flowed along the southwesterly wind, resultant increasing moisture supply. The temperature and humidity tended to increase recently at the lower and mid-levels.

Selecting “the best” nonstationary Generalized Extreme Value (GEV) distribution: on the influence of different numbers of GEV-models

ABSTRACT The selection of an appropriate nonstationary Generalized Extreme Value (GEV) distribution is frequently based on methods, such as Akaike information criterion (AIC), second-order Akaike information criterion (AICc), Bayesian information criterion (BIC) and likelihood ratio test (LRT). Since these methods compare all GEV-models considered within a selection process, the hypothesis that the number of candidate GEV-models considered in such process affects its own outcomehas been proposed. Thus, this study evaluated the performance of these four selection criteria as function of sample sizes, GEV-shape parameters and different numbers candidate GEV-models. Synthetic series generated from Monte Carlo experiments and annual maximum daily rainfall amounts generated by the climate model MIROC5 (2006-2099; State of Sao Paulo-Brazil) were subjected to three distinct fitting processes, which considered different numbers of increasingly complex GEV-models. The AIC, AICc, BIC and LRT were used to select “the most appropriate” model for each series within each fitting process.BIC outperformed all other criteria when the synthetic series were generated from stationary GEV-models or from GEV-models allowing changes only in the location parameter (linear or quadratic). However, this latter method performed poorly when the variance of the series varied over time. In such cases, AIC and AICc should be preferred over BIC and LRT. The performance of all selection criteria varied with the different number of GEV-models considered in each fitting processes. In general, the higher the number of GEV-models considered within aselection process, the worse the performance of the selection criteria. In conclusion, the number of GEV-models to be used within a selection process should be set with parsimony.

The link between smallholders’ perception of climatic changes and adaptation in Tanzania

Farmers’ subjective perceptions of climatic changes are not always in line with historic climate observations. Adaptation decisions based on these perceptions thus remain controversial. The paper therefore relates to the following questions: First, what are farmers’ perceptions of climatic changes? Second, do they correlate with observations from climatic data? Third, how do farmers respond and what are the factors determining adaptation? The analysis is based on household survey data from a sample of 900 farmers in rural Tanzania and secondary data from local meteorological stations. We find that farmers’ perception of a rising average temperature over time is generally confirmed. This is not the case for rainfall: farmers perceive that annual rainfall amount decreased, while climate data rather shows no change in the amount, but indicates a change in the rainfall pattern. However, we do find only a weak link between farmers’ perception and their behavior. Although farmers perceive climatic changes to happen and to affect them, some choose to not adapt at all and many only react in an evasive way, i.e., by coping measures that will not protect their household from future damage. Only a small share of farmers chose investment-intensive long-term strategies such as irrigation systems. Results confirm that a limited adaptive capacity plays a role, but also reveal the intention to adapt as a relevant factor. This is represented by the farmers’ loss experience due to climatic shocks and personality traits. This approach gives a more complete picture of the farmers’ adaptation decision.

Environmental Study of Water Reservoirs for the Watershed Management in Pakistan

Water reservoirs in most parts of the world face the problem of sedimentation. Environmental impacts and land-use changes/landslide have enormous potential to generate more sediment load in water reservoirs. Hence, the capacity of water reservoirs in Pakistan has been constantly reducing due to sedimentation. In this study, we have computed the environmental impacts on sedimentation load in Tarbela and Mangla water reservoirs using multi-satellite and ground-based data. The total drainage area of watershed is calculated using Shuttle Radar Topographic Mission data. Satellite data from NOAA-AVHRR are used to monitor urban development and changes in vegetation area, while MODIS data are used to estimate the snow area in the watershed region. Normalized Difference Vegetation Index is used to estimate the temporal changes in vegetation cover, whilst principle component analysis is applied to monitor urban changes in watershed region. Similarly, snow cover area in the study region is estimated using Normalized Difference Snow Index algorithm. Rainfall data obtained from Pakistan Meteorological Department are used to evaluate the relationship between sedimentation deposited in water reservoirs and annual rainfall amount. Results of the current study reveal that increase in urban development and high amount of precipitation has direct relationship with the load of sedimentation, while amount of vegetation has inverse relationship with the load of sedimentation in water reservoirs of the country.

The Effect of Landscape Interventions on Groundwater Flow and Surface Runoff in a Watershed in the Upper Reaches of the Blue Nile

Anthropogenic landscape conversion from forest to agricultural land affects baseflow. Baseflow is a source of potable water and can be used for the irrigation of high value crops. Finding ways to increase base and inter flow (i.e., groundwater flow) is, therefore, essential for the improvement of the livelihood of rural inhabitants. Therefore, the objective is to investigate the effect of landscape interventions on stream discharge and, in particular, on groundwater flow. The Tikur-Wuha experimental watershed in the upper reaches of the Blue Nile was selected because discharge data were available before and after implementation of a suite of land management practices that, among others, enhanced the percolation of water to below the rootzone. The parameter efficient distributed (PED) model was used to separate overland flow from total flow. The groundwater flow index (GWFI), defined as the quotient of the annual groundwater flow to the total stream discharge at the outlet of the watershed, was calculated. Our analysis with the PED model showed that at similar annual rainfall amounts, more baseflow and less surface runoff was generated after the landscape intervention, which promoted deep infiltration of the rainwater. The decrease in surface runoff shortly after the implementation of the land management practices is similar to observations in other watersheds in the Ethiopian highlands.

Liana abundance and diversity increase with rainfall seasonality along a precipitation gradient in Panama

In tropical regions, rainfall gradients often explain the abundance and distribution of plant species. For example, many tree and liana species adapted to seasonal drought are more abundant and diverse in seasonally‐dry forests, characterized by long periods of seasonal water deficit. Mean annual precipitation (MAP) is commonly used to explain plant distributions across climate gradients. However, the relationship between MAP and plant distribution is often weak, raising the question of whether other seasonal precipitation patterns better explain plant distributions in seasonally‐dry forests. In this study, we examine the relationship between liana abundance and multiple metrics of seasonal and annual rainfall distribution to test the hypothesis that liana density and diversity increase with increasing seasonal drought along a rainfall gradient across the isthmus of Panama. We found that a normalized seasonality index, which combines MAP and the variability of monthly rainfall throughout the year, was a significant predictor of both liana density and species richness, whereas MAP, rainfall seasonality and the mean dry season precipitation (MDP) were far weaker predictors. The strong response of lianas to the normalized seasonality index indicates that, in addition to the total annual amount of rainfall, how rainfall is distributed throughout the year is an important determinant of the hydrological conditions that favor liana proliferation. Our findings imply that changes in annual rainfall and rainfall seasonality will determine the future distribution and abundance of lianas. Models that aim to predict future plant diversity, distribution, and abundance may need to move beyond MAP to a more detailed understanding of rainfall variability at sub‐annual timescales.

Accounting for Tropical Cyclones in Extreme Rainfall Distributions in Florida

This study investigates the contribution of tropical cyclones to the statistics of extreme rainfall events in Florida for durations ranging between 15 min and 7 days. It is shown that, at most rain-gauge locations, the probability distribution of annual maximum rainfall amounts associated with tropical cyclones is significantly different from the probability distribution of annual maximum rainfall amounts not associated with tropical cyclones. Typically, the probability distribution of the annual maximum rainfall can be better described by a mixed probability distribution rather than by the conventional lumped distribution, leading to differences in the estimated rainfall amounts associated with given return periods. The results presented in this paper indicate that more accurate intensity-duration-frequency functions could be obtained by separately accounting for rainfall associated with tropical cyclones.

Groundwater recharge estimation using HYDRUS 1D model in Alaşehir sub-basin of Gediz Basin in Turkey.

Gediz Basin, located in the western part of Turkey constituting 2% land of the country, has an important groundwater potential in the area. Alasehir sub-basin, located in the southeast of the Gediz Basin and subject to the extensive withdrawal for the irrigation, constitutes the study area. Natural recharge to the sub-basin due to precipitation is numerically investigated in this study. For this purpose, 25 research wells, whose depths range from 20 to 50 m, were drilled to observe the recharge and collect the necessary field data for the numerical model. Meteorological data were collected from 3 weather stations installed in the study area. The numerical model HYDRUS was calibrated using the field water content data. Soil characterization was done on the core samples; the aquifer characterization was performed, and the alluvial aquifer recharge due to precipitation was calculated. As a result, the computed recharge value ranges from 21.78 to 68.52 mm, with an average value of 43.09 mm. According to the numerical model, this amount of recharge corresponds to 10% of the amount of annual rainfall.

Development of Models for Rainfall Intensity- duration-frequency for Akure, South-west, Nigeria

The rainfall Intensity-Duration-Frequency (IDF) relationship is widely used for adequate estimation of rainfall intensity over a particular catchment. A 25 year daily rainfall data were collected from Nigerian Meteorological Agency (NIMET) Abuja for Akure station. Twenty five year annual maximum rainfall amounts with durations of 5, 10, 15, 20, 30, 45, 60, 90, 120, 180, 240, 300 and 420 minutes were extracted and subjected to frequency analysis using the excel solver software wizard. A total of six (6) return period specific and one (1) general IDF models were developed for return periods of 2, 5, 10, 25, 50 and 100 years using Gumbel Extreme Value Type-1 and Log Pearson Type -3 distributions. Anderson Darling goodness of fit test was used to ascertain the best fit probability distribution. The R2 values range from 0.982 to 0.985 for GEVT -1 and 0.978 to 0.989 for Log Pearson type -3 while the Mean Squared Error from 33.56 to 156.50 for GEVT -1 and 43.01 to 150.63 Log Pearson Type III distributions respectively. The probability distribution models are recommended for the prediction of rainfall intensities for Akure metropolis.

Modelling Rainfall Intensity by Optimization Technique in Abeokuta, South-West, Nigeria

The design of water resources engineering control structures is best achieved with adequate estimation of rainfall intensity over a particular catchment. To develop the rainfall intensity, duration and frequency (IDF) models, 25 year daily rainfall data were collected from Nigerian Meteorological Agency (NIMET) Abuja for Abeokuta. The annual maximum rainfall amounts with durations of 5, 10, 15, 20, 30, 45, 60, 90, 120, 180, 240, 300 and 420 minutes were extracted and subjected to frequency analysis using the Excel Optimization Solver wizard. Specific and general IDF models were developed for return periods of 2, 5, 10, 25, 50 and 100 years using the Gumbel Extreme Value Type -1 and Log Pearson Type -3 distributions. The Anderson-Darling goodness of fit test was used to ascertain the best fit probability distribution. The R2 values range from 0.973 – 0.993 and the Mean Squared Error, MSE from 84.49 – 134.56 for the Gumbel and 0.964 – 0.997 with MSE of 42.88 – 118.68 for Log Pearson Type -3 distribution, respectively. The probability distribution models are recommended for the prediction of rainfall intensities for Abeokuta metropolis.