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GOVERNMENT OF INDIA
MINISTRY OF EARTH SCIENCES
LOK SABHA
UNSTARRED QUESTION NO. 4072
TO BE ANSWERED ON WEDNESDAY, 12TH AUGUST, 2026
FLOOD FORECASTING AND EARLY WARNING SYSTEM IN NORTHEAST
INDIA
4072. SHRI GAURAV GOGOI:
Will the Minister of EARTH SCIENCES be pleased to state:
(a) whether the India Meteorological Department (IMD) issued advance rainfall alerts
before the July 2026 floods in upper Assam and if so, the details thereof including
the classification of rainfall and the associated weather system;
(b) whether the IMD has assessed the accuracy and lead time of its rainfall forecasts and
warnings issued for flood-affected districts of Assam during the 2026 monsoon
season and if so, the details thereof;
(c) whether El Niño and Indian Ocean Dipole conditions are factored into seasonal
rainfall and flood-risk assessments for Northeast India and if so, the details thereof;
and
(d) whether steps are being taken to improve the spatial resolution and accuracy of
rainfall forecasts and extreme-weather warnings at the sub-district level in Northeast
India and if so, the details thereof?
ANSWER
THE MINISTER OF STATE (INDEPENDENT CHARGE) FOR
MINISTRY OF SCIENCE AND TECHNOLOGY
AND EARTH SCIENCES
(DR. JITENDRA SINGH)
(a) Yes. The India Meteorological Department (IMD) issued advance district-level
rainfall forecasts and colour-coded impact-based warnings for all districts of Upper
Assam, including Jorhat, Golaghat, Sivasagar, and Charaideo, prior to and during the
heavy to very heavy rainfall activity from 18th to 20th July 2026. The forecasts
issued by IMD for the State captured the occurrence of the heavy and very heavy
rainfall events with a lead time of 7 days, accompanied by daily colour-coded
warnings valid for the subsequent 7 days. Standard rainfall classifications per IMD
guidelines were followed, categorizing rainfall intensity levels across light,
moderate, heavy, and very heavy precipitation alongside spatial distribution scales
ranging from scattered to widespread coverage.
The high rainfall event was driven by key synoptic weather systems and atmospheric
components during 17th to 20th July 2026. On 17th July 2026, the mean sea level
monsoon trough extended towards the Northeast Bay of Bengal, accompanied by a
low-pressure area over Gangetic West Bengal and adjoining regions, along with an
upper air cyclonic circulation over Northeast Assam and its neighborhood extending
up to 1.5 km above mean sea level. Between 18th and 20th July 2026, the upper aircyclonic circulation over Northeast Assam shifted towards Central Assam and
adjoining Nagaland between 1.5 km and 3.1 km above mean sea level and persisted
through 20th July. Additionally, an upper air cyclonic circulation over North
Jharkhand and adjoining Bihar, along with a connected atmospheric trough
extending across Gangetic West Bengal and Bangladesh to Tripura, further sustained
the strong monsoonal activity across Upper Assam. Daily weather bulletins detailing
the episode remain archived and available with the Regional Meteorological Centre,
Guwahati.
(b) Yes. IMD regularly assesses the performance, accuracy, and lead time of its extreme
heavy rainfall forecasts and warnings across all regions of Assam, divided into sub-
regions including West Assam, South Assam, Central Assam, and Northeast Assam.
The evaluation parameters primarily measure overall accuracy, detection probability,
threat handling, and false alarm frequencies for lead times spanning from Day 1 to
Day 5. In West Assam, the overall forecast accuracy expressed as Percentage of
Correct forecasts (PC) ranges from 72.14% on Day 1 to 80.94% on Day 5. The
Probability of Detection (POD) stands at 0.6345 for Day 1 and gradually decreases
to 0.1209 on Day 5. Correspondingly, the False Alarm Ratio (FAR) ranges from
0.738 on Day 1 to 0.9613 on Day 5, while the Critical Success Index (CSI) moves
between 0.1936 on Day 1 and 0.0264 on Day 5.
In South Assam, the Percentage of Correct forecasts remains consistently high,
ranging from 60.48% on Day 1 up to 84.68% on Day 5. The Probability of Detection
records a value of 0.525 for Day 1 and decreases to 0.0425 for Day 5. The False
Alarm Ratio varies from 0.855 on Day 1 to 0.75 on Day 5, whereas the Critical
Success Index records values ranging between 0.12 on Day 1 and 0.0425 on Day 5.
In Central Assam, the forecasting system demonstrates high overall accuracy, with
the Percentage of Correct forecasts improving from 66.36% on Day 1 to 80.18% on
Day 5. The Probability of Detection starts at 0.6929 on Day 1 and shifts to 0.0757 by
Day 5. The False Alarm Ratio ranges from 0.8114 on Day 1 to 0.8883 on Day 5,
while the Critical Success Index records a performance ranging between 0.1671 on
Day 1 and 0.0429 on Day 5.
In Northeast Assam, the Probability of Detection is notable at 0.7229 on Day 1 and
0.1857 on Day 5, supported by a lower False Alarm Ratio ranging between 0.3913
on Day 1 and 0.5538 on Day 5. The Critical Success Index shows strong
performance ranging from 0.4275 on Day 1 to 0.19 on Day 5. The overall forecast
accuracy in terms of Percentage of Correct forecasts for Northeast Assam remains
stable across the lead times, measuring 58.47% on Day 1 and 51.61% on Day 5.
(c) India Meteorological Department considers large-scale climate drivers, including the
El Niño–Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD), while
preparing seasonal rainfall forecasts over India, including Northeast India. IMD's
seasonal forecasting system utilizes a combination of dynamical coupled climate
models and statistical techniques that incorporate various oceanic and atmospheric
parameters such as sea surface temperatures, atmospheric circulation, ENSO, IOD,
and other climate indicators. These factors are assessed collectively to generate
probabilistic forecasts of seasonal rainfall.For Northeast India, ENSO and IOD influence rainfall variability. While El Niño is
generally associated with below-normal southwest monsoon rainfall over most parts
of India, Northeast India receives normal to above-normal rainfall during some El
Niño years. The relationship between El Niño and rainfall over Northeast India is
relatively weak and complex compared to the rest of the country, as rainfall over the
region is strongly influenced by factors such as Bay of Bengal moisture transport,
monsoon circulation, and orographic effects. Consequently, the impact of El Niño on
Northeast India's seasonal rainfall is not uniform and varies from one event to
another. Currently, moderate El Niño conditions are prevailing, while IOD remains
neutral, and these conditions have been incorporated into IMD's seasonal rainfall
outlooks. However, flood risk over Northeast India also depends on short-duration
extreme rainfall events, river basin conditions, and catchment characteristics;
therefore, flood-risk assessments are based on both seasonal climate outlooks and
operational weather forecasts.
With regard to flood-risk assessment, IMD's rainfall forecasts and weather warnings
form important meteorological inputs for flood forecasting. Operational flood
forecasting in the country is carried out by the Central Water Commission (CWC),
which integrates IMD's weather forecasts with hydrological observations, river
gauge data, and hydrological models for issuing flood forecasts and warnings. Thus,
ENSO and IOD contribute to seasonal assessment of rainfall variability and flood
potential, while actual flood forecasts are based primarily on observed and forecast
rainfall, river conditions, and hydrological modelling.
(d) Yes. To improve spatial resolution and accuracy at the sub-district level in the
Northeast India, the advanced Numerical Weather Prediction model development
has been operationalized, featuring the high-resolution New Bharat Forecasting
System (BharatFS) at 6 km to cater to block and panchayat levels, supported by the
enhanced computing power of the "Arunika" and "Arka" systems. Under Mission
Mausam, the advanced Multi-Hazard Early Warning-Decision Support System
(MHEW-DSS) has been introduced for real-time monitoring and forecasting.
Furthermore, the observational network over Northeast India is being enhanced
through the installation of state-of-the-art observing systems.
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