The aim of this study is the establishment of the existence of trend and variability on a typical 24-hourly sorted thirty years (1986-2015) annual maximum series (AMS) and maximum monthly series (MMS) rainfall data for Uyo metropolis in Nigeria. Data were downscaled into shorter durations of 0.25, 0.5, …,12 hours. The statistical tool applied for the study was the Mann-Kendall (MK) test and Sen Slope estimator. The results showed that there exists increasing trend for all durations analyzed with consistency in the test statistic results. The MK statistic lZl  for the AMS varied between 3.1701 and 3.2827 while that of MMS was 4.756, were greater than critical Z = 1.96. Also, the computed p-value for the AMS varied between 0.0012 and 0.0015, and were lower than the significant level of alpha,  = 0.05. Thus, the null hypothesis of no trend was rejected. Similarly, the Sen Slope estimator gave an average rate of change in rainfall as 2.1288 and 2.16 mm/year for AMS and MMS time series data, respectively. The result from the Sen Slope estimator indicated that the magnitude of the trend decreased as the duration of rainfall increased such that shorter duration exhibited more trend than higher duration. The results of the MK trend and Sen Slope analysis proved that both test exhibited high degree of consistency with statistically significant positive trend and variability. These results have provided further evidence of an accelerated alarming rate in climate change increasing trend in Uyo metropolis and perhaps the environs. Therefore, planning for effective and accurate rainfall prediction for annual maximum time series data with established variability in trend will require adoption of non-stationary concept to account for the influence of changing climatic parameters in intensity-duration-frequency (IDF) modeling.

This paper mainly investigated the basic information about non-stationary trend change point patterns. After performing the investigation, the corresponding results show the existence of a trend, its magnitude, and change points in 24-hourly annual maximum series (AMS) extracted from monthly maximum series (MMS) data for thirty years rainfall data for Uyo metropolis. Trend analysis was performed using Mann-Kendall (MK) test and Sen's slope estimator (SSE) used to obtain the trend magnitude, while the trend change point analysis was conducted using the distribution-free cumulative sum test (CUSUM) and the sequential Mann-Kendall test (SQMK). A free CUSUM plot date of change point of rainfall trend as 2002 at 90% confidence interval was obtained from where the increasing trend started and became more pronounced in the year 2011, another change point year from the SQMK plot with the trend intensifying. The SSE gave an average rate of change in rainfall as 2.1288 and 2.16 mm/year for AMS and MMS time series data respectively. Invariably, the condition for Non-stationary concept application is met for intensity-duration-frequency modeling.

The development of Intensity-Duration-Frequency (IDF) models for storm drain design and related flood mitigation structures requires rainfall amount and corresponding duration records. To achieve this purpose, three short duration downscaling methods from 24-hourly rainfall amount data were selected for improvement, namely: IMD, AIMD and MCIMD, with the CAMS method used as the experiment control. Three types of general PDF-IDF models (GEVT-1, LPT-3 and ND) were developed based on the downscaling methods yielding goodness of fit (R2) with very high correlation of 0.995–0.999 and model accuracy with mean square error (MSE) of 4.123–7.85. The PDF-IDF models predicted intensities plotted against durations for different return periods of 2, 5, 10, 25, 50 and 100 years, showed visual differences in the predictive performance of the intensities derived from the downscaling methods. Kruskal-Wallis non-parametric test of significance at 5% level carried out showed that no-significant difference exist for 15-60 minutes duration, while the difference was significant for durations between 90–300 minutes. The LPT-3 based on MCIMD yielded higher improved performance in prediction of intensities relative to the IMD. The level of improvement ranges from 35.17 to 52.26% and 25.0 to 39.89%; while that of AIMD ranges from 10.97 to 20.87% and 3.33 to 12.53% for 10 and 100 year return periods, respectively. The use of the IMD downscaling method with the LPT-3 PDF-IDF model for design purposes will be justified if modified with some percentage improvement or adjustment factor.

The aim of this study is to assess the water quality of the Nigerian Port Authority Water way. A cross-sectional study was carried out using a composite sampling method, where three water samples were collected randomly from each station to ensure that the samples were representative of the entire station. Water samples were taken from four different locations along the waterway with new unused bottles, chosen based on the level of port activity in the area. The samples were thereafter analysed for physiochemical parameters, and heavy metal, and compared to the World Health Organization's Permissible Limits. Data analyses covered descriptive statistics, Pearson correlation coefficient analysis, Agglomerative hierarchy clustering, parallel coordinate plot and Water Quality Index computation. The results showed that most parameters were above the standards, indicating a potential risk of bioaccumulation. The water quality index for the station was found to range from 3192.635 to 5061.35 for the four stations, indicating that the waterway is of poor water quality and unsuitable for consumption, and irrigation purposes. The parallel coordinate plot identified Lead and Salinity as the main contaminant in the waterway.

This study aims at establishing if climate change exists in the Niger Delta environment using non-stationary rainfall Intensity-Duration-Frequency (IDF) modelling incorporating time-variant parameters. To compute the intensity levels, the open-access R-studio software was used based on the General Extreme Value (GEV) distribution function. Among the four linear parameter models adopted for integrating time as a covariate, the fourth linear model incorporating scale and location with the shape function constant produced the least corrected Akaike Information Criteria (AICc), varying between 306.191 to 101.497 for 15 and 1440 minutes, respectively, selected for calibration of the GEV distribution equation. The non-stationary intensities yielded higher values above those of stationary models, proving that the assumption of stationary IDF models underestimated extreme events. The difference of 13.71 mm/hr (22.71%) to 14.26 mm/hr (17.0%) intensities implies an underestimation of the peak flood from a stationary IDF curve. The statistical difference at a 95% confidence level between stationary and non-stationary models was significant, confirming evidence of climatic change influenced by time-variant parameters. Consequently, emphasis should be on applying shorter-duration storms for design purposes occurring with higher intensities to help reduce the flood risk and resultant infrastructural failures.