Geography of Udi Cuesta Contribution to Hydro- Meteorological Pattern of the South Eastern Nigeria

The presence of cuesta with escarpment plays an important role in the distribution of rainfall. Its role was studied and was put together in this work. Various parameters were studied and they include: amount of rainfall, elevation, latitude and the distance from the sea. In this research, frequency analysis was performed on the parameters and the log-pearson type III was considered the most suitable distribution method. Also, principal component analysis was used to determine that two components best estimates the variables with close correlation to be rainfall, elevation, latitude and distance from the sea as component 1 and distance to nearest neighbour and longitude as component 2. With regional coefficient of variation of 22%, the area has low variability which is an indication of high rainfall values with good consistency. Annual average rainfall of South Eastern Nigeria is at 1744 mm with bi-modal double peaks in July and September as in most parts of Southern Nigeria. High rain bearing wind speed of the area with escarpment obviously affect the rainfall pattern. From the determination of the difference in mean of rainfall, it is again obvious that areas close to Udi escarpment of the cuesta have difference in mean below or slightly above mean, hence indicating the effect on rainfall

Reliability of stored river water as an alternative for consumption in Ekpoma, Nigeria: a human health risk assessment

With looming global water-related issues, the monitoring of water quality for household and industrial consumption has become more pertinent. Rivers in nearby towns serve as primary water sources for Ekpoma town. 123 samples of stored river water were collected from 41 sampling locations and physical properties - pH, electrical conductivity (EC), salinity, temperature, and total dissolved solids (TDS) - were measured in situ using the Hanna edge® Multiparameter EC/TDS/Salinity Meter-HI2030. Atomic absorption spectrophotometry (AAS) was used to detect and measure the concentration of potentially toxic metals (PTMs): Al, Cr, Cu, Fe, Mn, Ni, Pb, and Zn. The measured concentrations were compared to the WHO, US EPA, and NSDWQ regulatory standards, and a spatiotemporal health risk analysis was performed using HERisk software. Twenty-five percent of the tested samples contained PTM concentrations within the allowable regulatory limits. Spatiotemporal health risk analysis showed that 98.8% of the cumulative carcinogenic risks (CRcum) were entirely from Pb contamination via oral ingestion. PTM concentrations in the samples suggest the degradation of river water quality due to agricultural activities, crude oil exploration activities, and soil composition in the region. Best management practices (BMPs) and treatment processes for the removal of detected contaminants are recommended to improve water quality

Assessment of regional best‐fit probability density function of annual maximum rainfall using CFSR precipitation data

The upper Cross River basin (UCRB) fits a true description of a data scarce watershed in respect of climatic data. This paper seeks to determine the best‐fit probability density function (PDF) of annual maximum rainfall for the UCRB using the Climate Forecast System Reanalysis (CFSR) precipitation data. Also, to evaluate the performance of the Intergovernmental Panel on Climate Change (IPCC) Coupled Model Inter‐comparison Project (CMIP3) Fourth Assessment Report (AR4) Global Circulation Models (GCMs) in simulating the monthly precipitation in the UCRB considering 1979–2014 data. For the determination of the best‐fit PDF, the models under review included the generalized extreme value (GEV), normal, gamma, Weibull and log‐normal (LN) distributions. Twenty‐four weather station datasets were obtained and subjected to frequency distribution analysis on per station basis, and subsequently fitted to the respective PDFs. Also, simulated monthly precipitation data obtained from 16 AR4 GCMs, for weather station p6191, were subjected to frequency distribution analysis. The results showed the percentages of best‐fit to worst‐fit PDFs, considering the total number of stations, as follows: 54.17%, 45.83%, 37.50%, 45.83%, and 50%/50%. These percentages corresponded to GEV, Weibull, gamma, gamma, and LN/normal, respectively. The comparison of the predicted and observed values using the Chi‐square goodness‐of‐fit test revealed that the GEV PDF is the best‐fit model for the UCRB. The correlation coefficient values further corroborated the correctness of the test. The PDF of the observed data (weather station p6191) and the simulations of the 16 GCMs computed using monthly rainfall datasets were compared using a mean square error (MSE) dependent skill score. The result from this study suggested that the CGCM3.1 (T47) and MRI‐CGCM2.3.2 provide the best representations of precipitation, considering about 36 years trend for station p6191. The results have no influence on how well the models perform in other geographical locations

Multi-Dimensional Surface Water Quality Analyses in the Manawatu River Catchment, New Zealand

Land Use and Land Cover (LULC) properties give vital information about pollution signatures in rivers, and they help develop best management practices (BMPs) for effective water resource management. This work employs multivariate statistical methods, receptor modeling, connectivity analysis, and univariate trend analysis to investigate pollution sources across spatiotemporal scales in the Manawatu River, New Zealand. A positive matrix factorization (PMF) method was applied to interpret possible contamination sources. A 25-year dataset (1989–2014) comprising 12 water quality variables from three sites was used. Runoff connectivity analyses identified high-producing grassland (HG) as the most dominant pollution class in all sub-catchments. Univariate analyses revealed that nutrients and sediments were higher than in the initial monitoring years. The PMF analysis found possible pollutants causing impairment, which required attention from waste managers. PMF also showed that point, natural, and agricultural sources significantly contributed to pollution downstream of the river. In the midstream, the erosion, point, and agricultural sources were significant contributing factors. Agricultural pollution and soil erosion were the main contributors to the upstream sub-catchment area. This study suggests that BMPs with a high retention capacity are needed in specific locations in the catchment area to filter high concentrations of pollutants generated

Bacterial Contamination Levels and Brand Perception of Sachet Water: A Case Study in Some Nigerian Urban Neighborhoods

Sachet water (SW) is a major source of drinking in most Nigerian homes, thus making it a possible conveyance medium for health risks due to contamination if persist rather than for replenishment of the body. This study collected SW from three busy neighborhoods in South-West Nigeria and investigated for the presence of indicator bacteria (Escherichia coli (E. coli), Total Coliform (TC), Total Heterophilic Bacteria (THB), Staphylococcus (Staph)) and some physio-chemical parameters (total dissolved solids (TDS), pH, electrical conductivity (EC), and salinity). Multi-variable and exploratory statistical methods were applied to the results to determine correlations between bacterial contamination levels and perceived brand reputation. Bacteriological tests with raw SW samples appeared too numerous to count (TNC) and thus required serial dilutions. After seven-fold serial dilutions, results obtained revealed that SW brands with good reputations had no TC and E. coli and was statistically significant with groupings of other SW brands (χ2 = 12.28; p 2 = 37.96; p 19.7×108 cfu/mL; 14×108 cfu/mL 1.15×108 cfu/mL) and E. coli (18.2×108 cfu/mL; 38.7×108 cfu/mL,32.4×108 cfu/mL) exceeding the threshold value of zero set by the World Health Organization (WHO). Only one sample from a poor reputation brand tested positive for Staphylococcus and was not statistically significant (χ2 = 5.2191; p = 0.074). Principal Component Analysis (PCA)/Factor Analysis (FA) revealed that most of the SW had fecal contamination was the major source. Therefore, this study suggests that periodic cleaning of distribution lines, location-specific treatment, and other quality control (QC) measures should be enforced to reduce water security risk for SW consumption in the region