Source: The Hindu
Gs3: Disaster Management
Context: India needs to shift to ensemble weather and flood forecast model to achieve better accuracy in flood forecasting.
What is the significance of using Ensemble forecast?
|Deterministic forecast model||Ensemble forecast|
|· Deterministic forecast model merely indicates “Rising” or “Falling” above a water level at a river point.
· In this model,there is no idea of the area of inundation, its depth, and when the accuracy of the forecast decreases at 24 hours and beyond
|· It gives probability-based estimation as to different scenarios of water levels and regions of inundation.
· For example, it can indicate the probability like, the chances of the water level exceeding the danger level is 80%, with likely inundation of a village nearby at 20%.
|· It provides a lead time of just 24 hours||· It provides a lead time of 7-10 days ahead.
|· Since the end users (district administration, municipalities and disaster management authorities) receive such forecasts with very less “Lead time” and have to act quickly, flood forecast becomes less accurate.||· It helps local administrations with better decision-making and helps them to get prepared better in advance.
|· India has recently shifted towards -Deterministic forecast model||· The United States, the European Union and Japan have shifted towards Ensemble flood forecasting along with “Inundation modelling”.|
What are the shortcomings with India’s flood forecasting?
- The India Meteorological Department (IMD) issues meteorological or weather forecasts while the Central Water Commission (CWC) issues flood forecasts at various river points.
- Therefore, the advancement of flood forecasting depends on how quickly rainfall is estimated and forecast by the IMD and how quickly the CWC integrates the rainfall forecast with flood forecast.
- It also is linked to how fast the CWC disseminates this data to end user agencies.
- This complicated arrangement reduces the “Lead time”.
- Most flood forecasts at several river points across India are based on outdated statistical methods that enable a lead time of less than 24 hours.
- It renders the India’s flood forecast driven by Google’s most advanced Artificial Intelligence (AI) techniques ineffective.
Not uniform across India:
- A recent study shows that, India has only recently moved to use hydrological or simply rainfall-runoff models not all, but in specific river basins.
- Therefore, outdated technologies and a lack of technological parity between multiple agencies and their poor water governance decrease crucial lead time.
- Forecasting errors increase and the burden of interpretation shifts to incompetent end user agencies. The outcome is an increase in flood risk and disaster.
What is the way forward?
- The IMD has already started testing and using ensemble models for weather forecast through its supercomputers (“Pratyush” and “Mihir”).
- Yet, the forecasting agency has to adapt with advanced technology and need to achieve technological parity with the IMD in order to couple ensemble forecasts to its hydrological models.
- The IMD has to modernise the telemetry infrastructure along with raising technological compatibility with river basin-specific hydrological, hydrodynamic and inundation modelling.
- It also needs to trains its technical workforce to get well versed with ensemble models and capable of coupling the same with flood forecast models.
- It is only then that India can look forward to probabilistic-based flood forecasts with a lead time of more than seven to 10 days that will place India on par with the developed world.