Earth, Atmosphere & Environment Sciences
Title : | IoT and Geoinformatics Based Flood Monitoring and Prediction system |
Area of research : | Earth, Atmosphere & Environment Sciences |
Principal Investigator : | Dr. sachin shantaram Panhalkar, shivaji University, Maharashtra |
Timeline Start Year : | 2023 |
Timeline End Year : | 2026 |
Contact info : | panhalkarsachin@gmail.com |
Equipments : | solar Panel
Cloud Virtual Machine
Parts required for IOT system
RADAR TYPE NON CONTACT LEVEL sENsOR
satellite Data (for 312 sq km area)
4G GsM GPRs IoT Modem |
Details
Executive Summary : | Flooding has increased by 4-fold and 2.5-fold in the tropics and northern mid-latitudes between 1985 and 2015, accounting for 44% of all disasters and 31% of all economic losses. Climate change is causing significant changes in river flow, making it crucial to establish a river flood monitoring system. However, there are few studies on real-time forecasting and informing stakeholders in affected areas. This study aims to develop an IoT and Geoinformatics-based flood monitoring and prediction system for Panchganga river. The system includes a real-time hydro-meteorological data monitoring network, data processing center, and telecommunication infrastructure. The IoT-based system architecture monitors precipitation, discharge, and stage details, with gauging stations installed as needed. API data from private weather companies and government websites can also be used to update real-time rainfall/discharge information. The IoT and cloud server provide an all-encompassing tool for collecting data for specific flood disasters. Automatic flood simulation and forecast are calibrated and validated using sWAT/QsWAT/HEC-HMs and HEC-RAs models. The IoT and Geoinformatics platform collects data, filters and searches for relevant data, and applies analytics to provide detailed insight into flood threats and devastating impacts. Long-term mitigation strategies can be implemented by identifying appropriate flood causes. A relationship between rainfall and runoff can be established to assess subbasin-wise discharge and predict floods with a lead time of 5 to 6 hours. stakeholders and district/disaster management authorities can use this system to visualize flood information and transmit flood alerts with appropriate action to reduce casualties and losses. |
Co-PI: | Dr. Ganesh sunil Nhivekar, Yashavantrao Chavan Institute Of science, satara, Maharashtra-415001 |
Total Budget (INR): | 29,77,620 |
Organizations involved