Non-availability of historic data hampers flood management in India: IIT study
Unlock Exclusive Insights with The Tribune Premium
Take your experience further with Premium access. Thought-provoking Opinions, Expert Analysis, In-depth Insights and other Member Only BenefitsAs many parts of north-west India grappled with heavy floods during August-September this year, a study by the Indian Institute of Technology (IIT) Delhi has revealed that historic flood data, which is vital for flood management, is not available in India.
This includes data for the Indus Basin that affects Ladakh, Jammu and Kashmir, Himachal Pradesh, Punjab and Haryana. Heavy rainfall and severe floods were witnessed during the monsoon season in parts of Punjab, Himachal Pradesh and Jammu, with some dams recording unprecedented inflow.
“Though India has some of the world’s most densely populated flood-prone catchments and characterizes diverse geographical settings, including various climates, landforms, and topography, a detailed assessment of flood characteristics at a national scale to understand flood climatology and the influencing hydro-geomorphic characteristics has been missing,” the study undertaken by IIT’s Department of Civil Engineering states.
“Effective flood management requires a robust understanding of past floods. In India, such understanding is largely limited to case studies due to the absence of a standardised observed flood dataset,” the study adds.
The data for the Indus and Brahmaputra basins is classified and not openly accessible as these are “trans-boundary rivers”, according to the researchers. The Indus basin is spread across four countries, with most of it falling in India, Pakistan and some part of it in China and Afghanistan.
The floods in north India were caused by the Ravi and Beas rivers. Other rivers in the basin include the Indus, Jhelum, Chenab and Sutlej and their tributaries, as well as the Kabul River flowing into the Indus from Afghanistan.
“Available flood event datasets in India, such as the India Flood Inventory (IFI), do not include any information on flood discharges and associated catchment variables, which limits their usefulness in computational research,” the study states.
Titled ‘Large-sample Characterization of Flooding Events in India’, the study has been published in the current issue of Hydrological Sciences Journal, released by the International Association of Hydrological Sciences.
The southwest monsoon from June to September accounts for 80 percent of the annual rainfall in India and it drives the flood seasonality observed in most river basins. Over 86 percent of flood events take place during this period.
Floods are an intricate phenomenon resulting from the complex interaction of multiple physiographic and atmospheric features, and there is a wide variability in these relationships from catchment to catchment.
Pointing out that large-scale and large-sample studies are rare in developing countries, the researchers said that the major impediment for such studies in India is the nonexistence of a comprehensive catalog of past flood events in the country, along with their physical characteristics such as flood level, discharge, duration, etc.
Observing that hydrological models often struggle with capturing peak flows and extreme events as they are inherently subject to many limitations due to uncertainties in input data, coarse spatial resolution and oversimplified parameterisations, the researchers said that these biases are particularly pronounced in regions with complex hydro-geomorphological conditions or limited observational data for calibration.
“As a result, modeled runoff datasets may fail to accurately represent localised flood dynamics or provide reliable estimates of key flood parameters such as discharge and timing. This underscores the critical need for observed flood event data to ensure accuracy and robustness in hydrological analyses,” they said.
The researchers have addressed this gap by developing the first ever national dataset of 7,500 flooding events by merging observed streamflow records with official flooding thresholds and augmenting it with multiple catchment-scale variables.
This is said to offer robust insights into the dominant characteristics and factors influencing flood hydro-climatology in many areas, but does not include the critical Indus and Brahmaputra basins.