HYDERABAD: Thirteen districts in Telangana are facing an exceptional agricultural drought, with soil moisture levels significantly below normal, according to an agricultural website developed by researchers at IIT Bombay.
With the Rabi season approaching, the findings raise fresh concerns over water availability for farmers.
The situation is worrying in Jogulamba Gadwal, Narayanpet, Nagarkurnool, Wanaparthy and Mahbubnagar, which are among the worst-affected districts.
Their soil moisture anomaly values ranged from -1.65 to -2.88 during the week of November 2 to 8. Jogulamba Gadwal recorded the highest deficit at -2.883, followed by Narayanpet (-2.820), Nagarkurnool (-2.532), Wanaparthy (-2.527) and Mahabubnagar (-2.501).
Vikarabad recorded an anomaly of -2.446 and Sangareddy -2.256. The figures for Kamareddy, Adilabad, Nizamabad, Nirmal, Rangareddy and Medak stood at -2.096, -2.029, -1.972, -1.896, -1.777 and -1.650, respectively.
Across several other affected regions, values ranged from -2 to -2.9, indicating significantly drier-than-normal conditions.
Across several other affected regions, soil moisture anomalies ranged from -2 to -2.9 across other affected regions, indicating significantly drier-than-normal conditions compared with the average for the same period over the previous 10 years.
Several other states also face drought
However, Telangana is not alone in facing these conditions. Parts of Rajasthan, western Gujarat, western Madhya Pradesh, Maharashtra, northern Karnataka, southern Andhra Pradesh and the northeastern states are also among the worst-affected regions in the country, according to krishidrought. in, a public portal launched by IIT Bombay on October 28.
Despite the recent cyclonic systems, western and northern Telangana continue to face severe agricultural drought, said Karthikeyan Lanka, associate professor at IIT Bombay’s Centre of Studies in Resources Engineering (CSRE) and associate faculty member of its Interdisciplinary Programme in Climate Studies.
The rainfall may provide some relief, but is unlikely to make up for the accumulated soil moisture deficit, he told TNIE. With moisture levels falling and pressure on available water resources mounting, Rabi cultivation could face further stress.
Farmers dependent on groundwater and irrigation are particularly vulnerable. Much of the available water may already have been used to sustain Kharif crops, leaving limited resources for the next season. While central Telangana is showing some improvement, the recent rainfall may not be enough to reverse the deficit, Lanka said.
The associate professor attributed the widespread drought partly to El Nino, but said the current situation was more severe than the drought in 2015, another El Nino year. The Indian Ocean Dipole (IOD) and Madden-Julian Oscillation (MJO) could also be influencing rainfall patterns, and the team is examining their role in the ongoing drought. Several affected regions, he added, did not experience favourable atmospheric conditions for rainfall during the monsoon.
Early forecasts, Lanka said, could help governments identify drought conditions and intervene before farmers suffer further losses.
Had authorities used such assessments sooner, they could have recognised the severity of the situation and declared drought conditions earlier.
The team has begun sharing its forecasts with the Union Ministry of Agriculture and Farmers Welfare and farmers’ welfare associations, and plans to approach state agriculture departments to promote their use in agricultural planning and drought mitigation.
The forecasts are generated through KrishiDrought.in, developed by the institute’s Ecohydrology research group, led by Lanka, in collaboration with CSRE and the Centre for Climate Studies; the platform provides weekly agricultural drought forecasts for the country, up to four weeks ahead.
Updated every Monday, it predicts root-zone soil moisture at depths of zero to 100 cm, at a spatial resolution of approximately 9 km, using satellite observations, hydroclimatic data, weather forecasts and a deep learning model that factors in earlier land-atmosphere conditions and large-scale climate patterns.