Three-Day Advisory Flood Forecast System
of the Central Water Commission (CWC), Government of India
Floods are the most common natural disaster in India. In Uttar Pradesh, Bihar, Assam, Gujarat, Rajasthan, Bengal, Andhra Pradesh and Odissa states, floods are a recurrent problem. According to some estimates, on average 7.5 million hectares of land are flooded, 1600 lives are lost, and damage to crops, houses and public utilities is over 18 billion rupees. To cope with that enormous damage caused by floods in the country, the Government of India relies heavily on non-structural measures such as flood forecasting, along with structural measures such as embankments, dams, and flood protection works.
The Central Water Commission (CWC) is a high level Government of India technical organisation mandated to provide the entire country with flood forecasts. CWC has been conducting flood forecasting for 62 years over an extensive network of 325 forecasting stations spread across the country.
Necessity of the project:
CWC conducts conventional flood forecasting by means of the gauge-to-gauge correlation method, which has performed very well over time. However, the statistical nature of that technique has a major in-built drawback: limited and fixed warning time (not more than 24 hrs in India). Moreover, the forecasting is done manually, which is time-consuming. To overcome these limitations, in 2017 CWC introduced a rainfall based hydrological modelling technique for flood forecasting via its three-day advisory flood forecast system. This system, developed totally in-house by CWC officers and involving no funds, complements the conventional system already in place.
The main reason for moving to modelling based flood forecasting technique was strong demand for longer warning time, which is critical for disaster managers and other stakeholders in their efforts to plan and take preventive measures to minimize flood losses.
Project details & impact:
The system uses both hydrologic (rainfall-runoff) and hydrodynamic modelling engines for real-time water level and inflow prediction for river and reservoir forecasts, which are simultaneously updated every three hours for all 325 forecasting stations. The system works in automatic mode without any human involved. The new forecasting technique has increased the warning time to as much as 72 hrs (i.e. three days in advance); it operates nationwide, covering all 19 major river basins of the country. The system generates more than 2000 forecasts per day, all easily accessible on a dedicated GIS platform. The CWC three-day advisory flood forecast system, built around state of the art technology, is on par with all other modern flood forecasting techniques used in the world.
The CWC three-day advisory flood forecasting system is designed to provide timely advance flood warnings which are vital for early evacuation from flood risk zones and for the prevention of flood damage in the region. It is more than a major upgrade from manual gauge-to-gauge to an automated rainfall-based flood forecasting system; it is also an excellent tool for all states and project authorities of the country involved in flood management.
The system is robust, durable, and sustainable. It has been performing very well since 2017, operating successfully for the past five flood seasons. It will serve the country well in the long run since a separate directorate has been entrusted with the responsibility for its maintenance and its continuous improvement in the future.
Mr. Mohd Faiz Syed, deputy director of the project, was assisted by the main development team, which included Mr. Ritesh Khatter, who is currently serving as director of the Government of India’s Ganga Flood Control Commission (GFCC).
The project would not have been possible without the full hearted support and encouragement of the chairman, members of the River Management team, and the Chief Engineer (FMO) of the Central Water Commission.
Figure 1: Web interface of the three day advisory flood forecast of the central water commission of the Government of India
Figure 2: Sketch of the methodology of the forecasting system
Figure 3: Forecast sample on the GIS dissemination portal