| Ref.No: | 61212800 |
| Start date: | 01.01.2023 |
| End date: | 31.12.2025 |
| Approval date: | 16.12.2022 |
| Department: | CIVIL ENGINEERING |
| Sector: | WATER RESOURCES AND ENVIRONMENTAL ENGINEERING |
| Financier: | PRASINO TAMEIO |
| Budget: | 200.000,00 € |
| Public key: | Ψ85246ΨΖΣ4-ΡΘ2 |
| Scientific Responsible: | Prof. TSOUKALA |
| Email: | tsoukala@mail.ntua.gr |
| Description: | WITH CLIMATE CHANGE UNFOLDING AND SEA LEVELS RISING, FLOODS ARE REGARDED AS ONE OF THE MOST DANGEROUS NATURAL DISASTERS. THE COMBINED FORCES OF HEAVY RAINFALL, OCEAN WATER LEVEL ELEVATION DUE TO STORM SURGES AND WAVE ACTION, ALBEIT THE LOW CONCURRENCE PROBABILITY, CAN LEAD TO CATASTROPHIC COMPOUND COASTAL FLOOD EVENTS WITH SEVERE IMPACTS ON COASTAL COMMUNITIES. HENCE, EMERGENCY MANAGEMENT AGENCIES AND STRATEGY PLANNERS ARE IN URGENT NEED OF A DECISION-SUPPORT TOOL THAT CAN ACCURATELY PREDICT INUNDATION FROM SUCH COMPOUND EVENTS. THE ULTIMATE GOAL OF EWS_COCOFLOOD IS TO DEVELOP A RELIABLE EARLY WARNING SYSTEM FOR COMPOUND COASTAL FLOOD EVENTS AND CONSEQUENTLY IMPROVE SOCIETAL PREPAREDNESS FOR COASTAL FLOOD RISKS. THE SYSTEM WILL RELY UPON A CHAIN OF NUMERICAL MODELS AND BIG DATA FROM OPEN DATABASES. IN ORDER TO OVERCOME THE COMPUTATIONALLY DEMANDING SIMULATIONS FOR A REAL COASTAL AREA AN ARTIFICIAL NEURAL NETWORK (ANN) WILL BE DEVELOPED AND TRAINED WITH THE SIMULATION RESULTS FOR A PLETHORA OF WISELY CHOSEN DISTINCT EVENTS. THE ANN WILL SERVE AS AN EARLY WARNING SYSTEM, BASED ON FORECASTS OF OPEN SEA STATE AND PRECIPITATION DATABASES, DRASTICALLY IMPROVING THE SOCIETAL PREPAREDNESS AGAINST SUCH EVENTS IN THE SHORT TERM. THE PROPOSED INTEGRATED SYSTEM WILL BE APPLIED IN THE FLOOD-PRONE COASTAL AREA OF ALFIOS RIVER ESTUARY IN THE COASTAL ZONE OF MUNICIPALITY OF PYRGOS, GREECE. |
