Assessment of urban river water pollution with urbanization in East Africa

Chen, Sophia Shuang; Kimirei, Ismael A.; Cheng, Yu; Shen, Qiushi; Gao, Qun

doi:10.1007/s11356-021-18082-1

Cited by 64 publications

(30 citation statements)

References 41 publications

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“…Increases in the use of artificial fertilizers are likely to increase nutrient transport to the lake basin easily. Rapid increase in population and economic activities has driven increases in nitrogen in other large lakes (Chen et al, 2022 ; Gao et al, 2015 ).…”

Section: Discussionmentioning

confidence: 99%

Citizen scientist monitoring accurately reveals nutrient pollution dynamics in Lake Tanganyika coastal waters

Moshi

Kimirei

Shilla

et al. 2022

Environ Monit Assess

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Several studies in Lake Tanganyika have effectively employed traditional methods to explore changes in water quality in open waters; however, coastal monitoring has been restricted and sporadic, relying on costly sample and analytical methods that require skilled technical staff. This study aims in validating citizen science water quality collected data (nitrate, phosphate and turbidity) with those collected and measured by professional scientists in the laboratory. A second objective of the study is to use citizen scientist data to identify the patterns of seasonal and spatial variations in nutrient conditions and forecast potential changes based on expected changes in population and climate (to 2050). The results showed that the concentrations of nitrate and phosphate measured by citizen scientists nearly matched those established by professional scientists, with overall accuracy of 91% and 74%, respectively. For total suspended solids measured by professional and turbidity measured by citizen scientists, results show that, using 14 NTU as a cut-off, citizen scientist measurements of Secchi tube depth to identify lake TSS below 7.0 mg/L showed an accuracy of 88%. In both laboratory and citizen scientist-based studies, all measured water quality variables were significantly higher during the wet season compared to the dry season. Climate factors were discovered to have a major impact on the likelihood of exceeding water quality restrictions in the next decades (2050), which could deteriorate lake conditions. Upscaling citizen science to more communities on the lake and other African Great Lakes would raise environmental awareness, inform management and mitigation activities, and aid long-term decision-making.

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Section: Discussionmentioning

confidence: 99%

Citizen scientist monitoring accurately reveals nutrient pollution dynamics in Lake Tanganyika coastal waters

Moshi

Kimirei

Shilla

et al. 2022

Environ Monit Assess

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show abstract

“…In addition, because rivers and waters are generally very wide, it is common for the same river to travel between different regions. In this case, it is often difficult to clearly define the scope of responsibility for cross-provincial rivers, which affects the timeliness and effectiveness of WP prevention [15].…”

Section: Risk Elements In Wp Prevention and Control Environmentmentioning

confidence: 99%

Exploration on Risk Assessment of Water Pollution Prevention and Control Based on Fuzzy Bayesian Network

2020

WPPCP

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With the acceleration of industrialization, modernization of agriculture and animal husbandry and urbanization, the pressure of water environment and water pollution are also increasingly prominent. However, agriculture, industry, service industry and the whole society have an increasing demand for water resources, and the contradiction of water resources shortage is also increasingly obvious. In this case, although some water pollution (WP) prevention measures have been put forward, there are still some risks in WP prevention. In this regard, this paper studied the risk factors and evaluation of WP prevention and control based on the fuzzy Bayesian network. It put forward the prevention and control risk factors such as the risk of pollution prevention and control laws and regulations, the risk of prevention and control management mechanism, and evaluated and studied the risk levels of WP prevention and control in the three urban areas of Z City. The results showed that the risk index of WP prevention and control in D, X and Q districts was 45.9, 51.5 and 49.3 respectively from the perspective of average value, and the risk level of the three urban areas was acceptable; from the perspective of fuzzy Bayesian network, the risk level of WP prevention and control in D, X and Q areas also belonged to the acceptable risk level.

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“…He Xiaodong studied the surface water pollution of the loess plateau in central China [13]. Chen Sophia Shuang analyzed the water pollution assessment of urban rivers under the urbanization of East Africa [14]. However, there is no research on integrating the improved BP algorithm of genetic algorithm for application.…”

Section: Introductionmentioning

confidence: 99%

Improved BP Algorithm Incorporating Genetic Algorithm for Water Pollution Prevention and Warning Application

2020

WPPCP

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In recent years, with the accelerated urbanization and industrial development, a large number of water pollution events have occurred in many regions, which have had a significant impact not only on the environment and socio-economics, but also on water quality. In this paper, the improved BP (back propagation) algorithm of genetic algorithm was used to improve the early warning system for water pollution prevention and control. This paper first introduced the current status of water resources monitoring and early warning mechanisms and the causes of sewage generation, followed by the transmission algorithm and the improved BP algorithm. Then the water pollution prevention and early warning system was designed by combining the two and the application effect was analyzed. It was found that the timeliness of water pollution early warning could be greatly improved after using the fused genetic algorithm and the improved BP algorithm. The water pollution prevention efficiency of water intake 1 was the highest, and its water pollution prevention efficiency was improved by 29% after adopting the water pollution prevention early warning system with fused genetic algorithm and improved BP algorithm. At present, the water pollution prevention and early warning system is more widely used, so the improved BP algorithm of genetic algorithm can be combined to improve the water pollution prevention and early warning effect.

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Assessment of urban river water pollution with urbanization in East Africa

Cited by 64 publications

References 41 publications

Citizen scientist monitoring accurately reveals nutrient pollution dynamics in Lake Tanganyika coastal waters

Citizen scientist monitoring accurately reveals nutrient pollution dynamics in Lake Tanganyika coastal waters

Exploration on Risk Assessment of Water Pollution Prevention and Control Based on Fuzzy Bayesian Network

Improved BP Algorithm Incorporating Genetic Algorithm for Water Pollution Prevention and Warning Application

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