| Title |
A Decision Support System Based On Rainfall Nowcasting And Artificial Neural Networks To Mitigate Wastewater Treatment Plant Downstream Floods |
| ID_Doc |
1295 |
| Authors |
Termite L.F.; Bonamente E.; Garinei A.; Bolpagni D.; Menculini L.; Marconi M.; Biondi L.; Chini A.; Crespi M. |
| Year |
2022 |
| Published |
Communications in Computer and Information Science, 1612 CCIS |
| DOI |
http://dx.doi.org/10.1007/978-3-031-17098-0_7 |
| Abstract |
This contribution presents a Decision Support System for operators working in a wastewater treatment plant, aimed at helping them in taking appropriate mitigation strategies in case of extreme rainfall events. The Decision Support System is based on the real-time monitoring of several variables within the area of interest and on the forecasting of specific variables in key points. The forecasting relies on Artificial Neural Networks, predicting water levels and flows from rainfall inputs. The use of very-short-term Quantitative Precipitation Estimates – nowcasting – allows for an extension of the forecasting horizon with respect of using measured rainfall only. Different Artificial Neural Networks architectures are tested. The Decision Support System was developed and tested on a real setting, specifically a wastewater treatment plant collecting the sewage from the city of Brescia, Italy. The quickness of the computation is compliant with the real-time needs and makes the developed platform an efficient tool to be used in a Smart City. © 2022, Springer Nature Switzerland AG. |
| Author Keywords |
Artificial neural networks; Decision support systems; Flood mitigation |
