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Early this year, just as India was reeling from its warmest March in over a century with an unusually early onset of heatwaves, scientists at the Indian Agricultural Research Institute (IARI) in Delhi conducted a first-of-its-kind experiment to quantify the impact of the hot weather on crop yield in Punjab and Haryana.
“In the last week of March, we forecasted that wheat farmers in Punjab would experience a yield loss of 6-10 per cent. In Haryana, farmers should be prepared for a 4-5 per cent yield loss,” says S Naresh Kumar, principal scientist at IARI.
The forecast was close to the actual crop loss. Gurvinder Singh, director, Punjab agriculture department, tells Down To Earth that the heatwaves, which continued till April, caused a 14 per cent loss in crop yield to the state.
Currently, the country does not have a system to forecast crop loss due to heatwaves or most other extreme weather conditions. The Mahalanobis National Crop Forecast Centre, under the Union Ministry of Agriculture and Farmers Welfare, provides pre-harvest forecasts for eight major crops at the national, state and district levels.
The agency also puts out forecasts accounting for drought events, but not for other extreme weather conditions. Besides, the agency forecasts with static crop models, which cannot factor in real-time changes.
The IARI scientists, in contrast, used InfoCrop version 2.1, India’s only dynamic crop simulation model developed and released by the institute in 2015 to study the long-term impact of climate change and crop management practices on yield.
The Union Ministry of Environment, Forest and Climate Change included the model’s projections for 1976-2100 in the first two national communications, reports submitted to the UN Framework Convention on Climate Change detailing the level of vulnerability and risks the country faces due to the impacts of climate change. But the March experiment shows that the model can also be used for near-term forecasts.
This is promising as, Kumar says, government and insurance companies should use at least three models for climate impact projections and for pre- or in-season crop yield forecasts to improve accuracy, and InfoCrop could be one of them.
He says the model has an 85 per cent accuracy rate, which is on par with widely used dynamic models such as the Decision Support System for Agrotechnology Transfer model, developed by the US, and Agriculture Production Systems sIMulator, developed by Australia.
InfoCrop is more suited for India as it has the life cycle data for almost all the local varieties of 11 crops: paddy, wheat, maize, sorghum, pearl millet, pigeon pea, chickpea, soybean, groundnut, potato and cotton.
Foreign models can be used to forecast local crop yield, but they would need fine-tuning, making the process cumbersome.
“Indian researchers will have to feed daily temperature, precipitation, along with soil conditions, plant varieties and their characteristics into the foreign models. Next, they will have to check if the model can reproduce the observed performance of that crop variety,” says Kumar.
In InfoCrop, the parameters are already calibrated to Indian crop varieties and they are updated at regular intervals by the institute. The parameters deal with aspects of weather (precipitation, temperature, radiation and others), crop growth (phenology, grain characteristics, leaf growth, temperature and flooding sensitivity and others), soil (texture and organic carbon, water holding characteristics and pH levels) and pests and crop management (organic matter, fertiliser and irrigation).
Besides forecasting, simulation models can be used to assess crop loss in the aftermath of an extreme weather event, which can then be used to provide relief packages, says Anil Kumar Gupta, associate professor, National Institute of Disaster Management, New Delhi.
India currently relies on field trials, which are expensive and resource-intensive. “Simulation models for heatwave-induced crop loss assessments are not as accurate as the models used for droughts. We are working with IARI to improve crop models,” he adds.
Since the model can be used to simulate management scenarios, it can help improve crop yield. “Every crop variety has a maximum yield potential, but it is seldom achieved in real-world conditions. Using this model, we can identify the various inputs required to maximise the yield,” says Kumar.
He explains that some wheat farmers in Haryana and Punjab harvest a maximum of 7-7.5 tonnes per hectare (ha). The model shows this can be increased to 9-11 tonnes through improved soil health and crop management.
InfoCrop is available for free on IARI’s website. Kumar claims that researchers in as many as 46 countries, including Argentina, Brazil and Bangladesh, have downloaded the model.
In March 2018, researchers from Bangladesh demonstrated the potential of using InfoCrop to assess the impact of climatic variability on crops and recommend appropriate options to manage them.
“Creating a model takes a lifetime,” says Kumar. It involves collecting data from studies and also conducting field studies to bridge the data gaps. The process can take decades.
IARI launched its first simulation model, Wheat Growth Simulator, in the 1990s. It could predict the yield of two wheat crop varieties. In 2004, InfoCrop version 1 was launched. The model had to be updated because it did not include crucial parameters such as CO2 levels.
Kumar and his colleagues are now working on the third version of InfoCrop, which has been delayed due to the COVID-19 pandemic.
“There are certain limitations in the existing model. For example, our model does not have information on all the crop management techniques used by farmers. We intend to make the newer version more user-friendly,” he says.
The team is also working on models for other crops such as mint, coriander, onion, tomatoes, cauliflower, kidney beans.
This was first published in the 16-31 October, 2022 edition of Down To Earth