Integrating GIS and sensor-based Early Warning Systems for flood management in Manipur


Nongmaithem Anand
Flooding is a recurrent and severe problem in Manipur, exacerbated by heavy monsoon rains, deforestation, inadequate infrastructure, and rapid urbanization. To mitigate the impact of floods, integrating Geographic Information Systems (GIS) and sensor-based Early Warning Systems (EWS) is crucial. These technologies enable real-time data collection, accurate flood forecasting, and timely warnings, thereby reducing the potential for loss of life and property.
The Role of GIS in Flood Management
Geographic Information Systems (GIS) are instrumental in flood manage- ment, offering tools for mapping flood-prone areas, analyzing spatial data, and simulating flood scenarios. GIS integrates various datasets, including topography, land use, and hydro- logical models, to create detailed flood risk maps. These maps help in identifying vulnerable areas and planning mitigation strategies.
For instance, in Parramatta, Australia, the 3Di hydrodynamic model, integrated with GIS, processes real-time precipitation data to predict flood levels within 15 minutes. This system provides local authorities with crucial time to take preventive measures, thus minimizing the impact of floods (Springer, 2020). Similarly, GIS has been effectively used in various regions to visualize and manage flood risks.
In Jordan, advanced GIS applications have been integrated with real-time sensor data to enhance flood prediction and management (MDPI, 2021). GIS also plays a pivotal role in creating comprehensive flood risk maps, which are essential for urban planning and disaster management.
Sensor-Based Early Warning Systems
Sensor-based EWS, including Internet of Things (IoT) devices, play a pivotal role in real-time flood monitoring. These systems deploy various sensors to measure parameters such as rainfall, river levels, and soil moisture. The collected data is transmitted to central databases where it is analyzed to predict flood events and trigger alerts.
In Jordan, a sustainable EWS using rolling forecasts based on Artificial Neural Networks (ANN) and Golden Ratio Optimization has been developed. This system significantly improves flood prediction accuracy, offering a 40% improvement over traditional models (MDPI, 2021).
Similarly, the multi-modal sensor system along the Kikuletwa River in Tanzania collects diverse data to enhance flood prediction accuracy in poorly gauged basins (MDPI, 2023).
Sensor networks are also being used in urban areas for real-time flood monitoring. In Japan, advanced sensor networks monitor rainfall, river levels, and soil moisture to provide timely flood warnings. These systems are integrated with community alert mechanisms to ensure that residents receive timely and actionable information (Sensors, 2019).
Implementing GIS and Sensor-Based EWS in Manipur
Manipur can leverage these technologies to enhance its flood resilience. The State experiences severe flooding due to heavy monsoon rains, steep topography, and inadequate drai- nage systems. Integrating GIS and sensor-based EWS can significantly improve flood management in the region.
1. Early Warning Systems : Deploying sensor networks to monitor real-time data on rainfall, river levels, and soil moisture can provide early warnings. These systems should be integrated with community alert systems to ensure timely dissemination of warnings. For example, a system similar to Parra-matta's 3Di model could be implemented, providing real-time flood predictions based on weather forecasts and river data (Springer, 2020).
2. GIS Mapping and Analysis: Developing detailed flood risk maps using GIS can help identify vulnerable areas. These maps should be regularly updated with real-time data from sensor networks to enhance accuracy. GIS applications can also be used to simulate various flood scenarios, aiding in urban planning and disaster management (Sensors, 2019).
3. Infrastructure Improvements: Upgrading drainage systems and constructing resilient embank- ments using modern materials like self-healing concrete can reduce flood risks. Implementing green infrastructure, such as permeable pavements and rain gardens, can also manage stormwater runoff effectively. For instance, self- healing materials used in embankments can automatically repair cracks, ensuring long-term resilience and reducing main- tenance costs (MDPI, 2021).
Learning from Successful Case Studies
1) Netherlands: The Delta Works Project and Room for the River Program integrate robust embankments and floodplains to manage high water levels. Manipur can adopt similar measures by constructing embankments and restoring natural floodplains. These projects have demonstrated the effectiveness of combining structural and natural flood management techniques to reduce flood risks (Springer, 2020).
2) Japan: Multipurpose dams and advanced warning systems in Japan provide timely alerts and regulate river flow. Implementing multipurpose reservoirs and advanced EWS in Manipur can enhance flood management. Japan's approach to integrating community preparedness with technological advancements offers valuable insights for Manipur (Sensors, 2019).
3) Bangladesh: Community-based approaches, such as flood-resilient housing and multipurpose shelters, engage local communities in flood management. Manipur can promote elevated housing designs and establish community shelters to improve resilience. These strategies ensure that local needs are met and that communities are actively involved in flood preparedness and response (MDPI, 2021).
Recommendations for Manipur
1. Strengthening Infrastructure : Upgrading and maintaining existing flood management infrastructure, such as embankments and drainage systems, is essential. Incorporating advanced materials like self-healing concrete and designing structures to withstand extreme weather events can enhance resilience.
2. Community Engagement : Engaging local communities in flood management planning and decision-making processes is crucial. Public education campaigns, disaster response drills, and community-based monitoring can ensure that residents are prepared and can respond effectively to flood warnings.
3. Policy and Institutional Frameworks : Developing robust policy frameworks that enforce land use regulations, promote sustainable urban planning, and incentivize green infrastructure can reduce flood risks. Esta- blishing public-private partnerships can also mobilize resources and expertise for flood management projects.
4. Technological Integration : Leveraging advanced technologies such as IoT, GIS, and remote sensing for real-time flood monitoring and prediction can enhance early warning systems.
Integrating these technologies into a comprehen- sive flood management strategy can ensure timely and accurate information dissemination. Integrating GIS and sensor-based EWS in Manipur can significantly enhance flood management, providing accurate predictions and timely warnings. By learning from successful case studies and leveraging advanced technologies, Manipur can build a robust flood resilience strategy, safeguarding lives and property from future floods.
The writer is Asst. Professor at Dept. of Civil Engineering, Manipur Technical University