Influence of Seasonal Changes on the Quality of Water Resources in Southwestern Nigeria: A Review

Ayejoto, Daniel A.; Egbueri, Johnbosco C.; Agbasi, Johnson C.; Omeka, Michael E.; Unigwe, Chinanu O.; Nwazelibe, Vincent E.; Ighalo, Joshua O.; Januraga, Pande Putu

doi:10.1007/978-3-031-21007-5_22

Cited by 9 publications

(5 citation statements)

References 58 publications

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“…All these accessories associated with the use of groundwater facilities such as drawers, ropes, lids and so on, are required to be of good quality, and should be adequately maintained and kept in good hygienic condition so that they do not introduce contaminants into the water- such action will partly enhance the environmental health. Ighalo and Adeniyi 5 and Ayejoto et al 35 had suggested that the government owes it a duty to curtail incessant pollution of water from various sources so that the health of the citizens is not in jeopardy, especially with global climate change scenario and its attendant impact on water resources quality.…”

Section: Resultsmentioning

confidence: 99%

Impact of Human Management of Hand-Dug Well Facility and Its Accessories on Groundwater Quality

Ogunbode,

Oyebamiji,

Aromolaran

et al. 2023

Environ�Health�Insights

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Hand-dug well facility is susceptible to pollution by natural and anthropogenic sources but pollution associated with human handling and management of hand-dug well facility and its accessories has been rarely discussed. A structured questionnaire was administered among 260 respondents cutting across the 5 quarters in Iwo, Osun State, Nigeria. The data collected was subjected to both descriptive and inferential analysis. Descriptive analysis showed that majority of the respondents were of female gender who relied largely on manual mode of fetching water in their respective hand-dug well facilities. Apart from this, different kinds of ropes of varying qualities were attached to their respective water fetchers, 72.69% of which are tyre-tube containers. Data factorability and its adequacy tests showed KMO value of 62.0% and its significance at P < .05, indicating that the data can be processed through Factor Analysis (FA). FA revealed that the pollution of well water attributed to human-handling of hand-dug well facility is associated with 8 variables with a total explanation of 75.55% namely; vicinity of the facility, the side wall quality of the hand-dug well, facility utilisation frequency, facility management authorities, maintenance of the associated facilities, quality of the lid, quality of water drawers and preference for the use of drawer at a time whether single or multiple. The findings suggest that stakeholders should make uptight effort to take the management of hand-dug well facility more conscientiously for sustainable human health. Further research is suggested to extend the frontiers of knowledge on pollutants associated with hand-dug water facility.

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Section: Resultsmentioning

confidence: 99%

Impact of Human Management of Hand-Dug Well Facility and Its Accessories on Groundwater Quality

Ogunbode,

Oyebamiji,

Aromolaran

et al. 2023

Environ�Health�Insights

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“…The Sokoto Plains are located in the country's northwest region, whereas the Borno Plains are located in the country's northeastern corner and extend to the Lake Chad basin. Porous, geologically young sedimentary strata underpin the Lake Chad basin and coastal regions, along with the Niger River delta and western sections of the Sokoto region in the extreme northwest (Encyclopaedia Britannica, 2023;Ayejoto et al 2023). The plateaus' distinctive features are high plains with vast, shallow valleys interspersed with several hills or solitary summits known as inselbergs; the base rocks are crystalline, with sandstones appearing in river basins.…”

Section: Reliefmentioning

confidence: 99%

“…The quality of water supplies has been declining dramatically in recent decades. This re ects both the increase in human activity and the variability of the global climate (Ayejoto et al 2023;Agbasi et al 2023). Natural hydrological, hydrogeologic, and geogenic processes also in uence water quality because they alter the water's chemistry (Xiao et al 2021).…”

Section: Introductionmentioning

confidence: 99%

“…It is feared that with the continuous increase in population and impeding industrial revolution, Nigeria will be put under greater strain in terms of climatic variations. Additionally, the quantity and quality of water resources will experience a further decline and continuous shifts (Ayejoto et al 2023). It becomes imperative therefore for more conscious action plans to be put toward the assessment and prediction of the quality of water resources for informed decision-making and amelioration of contaminated sites through the use of cutting-edge approaches.…”

Section: Introductionmentioning

confidence: 99%

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Exploring the recent trends, progresses, and challenges in the application of Artificial intelligence in water quality assessment and monitoring in Nigeria: A systematic review

Omeka

2024

Preprint

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In recent decades, machine learning (ML) artificial intelligence has found wide application in water quality monitoring and prediction due to the increasing complexity of water quality data. This complexity has been attributed to the global upsurge in anthropogenic activities and climatic variations. It is therefore critical to identify the most accurate and suitable ML model for water quality prediction. In this study, a systematic literature review (SLR) was carried out to explore the trend and progress in the application of ML models in water quality monitoring and prediction in Nigeria from 2003–2024. A comprehensive review of the effectiveness of advanced ML models as well as the gaps in their application in the area of water quality assessment and monitoring was also carried out using the PRISMA-P meta-analysis technique. Forty publications were used to perform bibliographic analysis and visualization using the VOS viewer software. The study found that globally, the use of hybrid ML models in water quality prediction has not been well explored; a majority of the prediction has been based on the use of artificial neural networks (ANN). Among the ANN algorithms, the adaptive neuro-fuzzy inference system (ANFIS), and Wavelet-Adaptive Neural Fuzzy Interference System (W-ANFIS) hybrid models are the most accurate in prediction; with temperature, dissolved oxygen (DO), pH, conductivity (EC), and total dissolved solids (TDS) among the most frequently predicted parameters. Nigeria is grossly lagging in the application of ML in water quality prediction. This limitation is largely attributed to inadequate data on environmental monitoring. It is critical therefore for future water quality monitoring and prediction studies in Nigeria to take advantage of the rapidly evolving field of machine learning; with more emphasis placed on the hybridized machine learning algorithms

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“…According to previous studies, since global warming has begun to impact snowmelt and stream runoff in the Himalayan region, it is critical to track snow cover shifts to forecast the future hydrologic cycle. The snowline altitude is an essential parameter for predicting changes in snow cover [3,40].…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal snowline status and climate variability impact assessment: a case study of Pindari River Basin, Kumaun Himalaya, India

Pandey,

Parashar,

Palni

et al. 2024

Environ Sci Eur

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The snowline exhibits significant seasonal shifts upward and downward, reflecting the ever-changing dynamics of the seasons and being influenced by climate variations, which can vary annually. These fluctuations profoundly impact the cryosphere, biota, and ecosystem processes in high mountain regions. Despite the critical role of snowline variations, comprehensive information on how actual climate variability affects snow cover trends in the central mountain range of the western Himalayas is scarce. In the 'Pindari' region of the Uttarakhand district, India, which is part of the Himalayas, these challenges are exacerbated by the unchecked growth of anthropogenic activities and the broader impacts of climate change. This study analyses snowline variations in the Pindari glacial region from 1972 to 2018. The findings revealed that the snowline elevation significantly shifted upward between 1972 and 2018. Notably, this research revealed a decrease in snow-covered areas of approximately 5.01 km2 over the course of 46 years. This decrease is attributed to a direct response to the increasing number of high-temperature events that occurred during this extended period. This study emphasizes the urgent need for conservation measures in the study region and similar high mountains to combat global warming and safeguard the snowline, which serves as a visible proxy indicator to safeguard high-altitude Himalayan glaciers.

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Influence of Seasonal Changes on the Quality of Water Resources in Southwestern Nigeria: A Review

Cited by 9 publications

References 58 publications

Impact of Human Management of Hand-Dug Well Facility and Its Accessories on Groundwater Quality

Impact of Human Management of Hand-Dug Well Facility and Its Accessories on Groundwater Quality

Exploring the recent trends, progresses, and challenges in the application of Artificial intelligence in water quality assessment and monitoring in Nigeria: A systematic review

Spatiotemporal snowline status and climate variability impact assessment: a case study of Pindari River Basin, Kumaun Himalaya, India

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