A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
A predictive management tool for blackfly outbreaks on the Orange River, South Africa
Downstream flow alteration resulting from river impoundment or interbasin transfer schemes, while improving water supply assurance levels, has been shown to have negative ecological consequences, including outbreaks of pest blackfly. In South Africa's Orange River, large impoundments constructed in the 1970s have created an ongoing blackfly outbreak problem. Although the severity of the outbreaks has been successfully managed using aerial applications of larvicides, periodic outbreaks continue to occur. Understanding the interactions of the multiple variables driving the outbreaks is complex. We integrated variables useful in predicting outbreak conditions (discharge, water temperature, seston concentration, benthic algae) using a Bayesian network approach. Data to define probabilities were collected at 11 sites over four sampling seasons, and system states were derived using flow and water temperature thresholds. The late summer months (February, March, and April) were most favourable for pest blackly outbreaks, and the probability of an outbreak is six times higher for postimpoundment versus preimpoundment flow conditions. The model was successful in integrating multiple environmental variables that act as triggers for pest blackfly outbreaks. The efficacy of the model as a management tool will increase if ongoing monitoring data are incorporated into the model as case files.
A predictive management tool for blackfly outbreaks on the Orange River, South Africa
Downstream flow alteration resulting from river impoundment or interbasin transfer schemes, while improving water supply assurance levels, has been shown to have negative ecological consequences, including outbreaks of pest blackfly. In South Africa's Orange River, large impoundments constructed in the 1970s have created an ongoing blackfly outbreak problem. Although the severity of the outbreaks has been successfully managed using aerial applications of larvicides, periodic outbreaks continue to occur. Understanding the interactions of the multiple variables driving the outbreaks is complex. We integrated variables useful in predicting outbreak conditions (discharge, water temperature, seston concentration, benthic algae) using a Bayesian network approach. Data to define probabilities were collected at 11 sites over four sampling seasons, and system states were derived using flow and water temperature thresholds. The late summer months (February, March, and April) were most favourable for pest blackly outbreaks, and the probability of an outbreak is six times higher for postimpoundment versus preimpoundment flow conditions. The model was successful in integrating multiple environmental variables that act as triggers for pest blackfly outbreaks. The efficacy of the model as a management tool will increase if ongoing monitoring data are incorporated into the model as case files.
A predictive management tool for blackfly outbreaks on the Orange River, South Africa
Rivers‐Moore, Nicholas A. (author) / Hill, Trevor R. (author)
River Research and Applications ; 34 ; 1197-1207
2018-11-01
11 pages
Article (Journal)
Electronic Resource
English
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