There is an absence of any quantified use of water in agriculture. Water is treated largely as a free resource with only associated costs of extraction, such as borewells, diesel, and pumps. Overall, water use efficiency is extremely poor across all key crops in India. Farmers lack access to knowledge with respect to measured irrigation. Farmers continue to follow flood irrigation and fear that less water will compromise their crop yield. The existing pricing and subsidies regime for agricultural produce also incentivizes farmers to grow water-intensive crops rather than crops appropriate to the climate, soil, and agroecology of the region. More than 50% of the country’s farmland grows water intensive crops such as rice, wheat, sugarcane, and cotton. Further, there is a lack of involvement of key stakeholders such as farmers in important agriculture-related decision making. All these factors have led to the rapid decline of India’s groundwater tables due to high extraction by farmers for agriculture. Existing water is heavily polluted due to overuse of fertilizer and pesticides. Inappropriate crop choices are predominantly grown in water stressed states, and farmer distress is created from low incomes due to poor returns from small landholdings in water stressed areas. Moreover, poor progress in socio- economic indicators like healthcare, sanitation & education in rural regions are exacerbated due to poor availability and access to water coupled with intensified floods and droughts.
All these issues have further triggered significant out migration from farming to other vocations, and rural to urban movement.
It is an acknowledged fact that climate change is adversely impacting agriculture in India. The UN estimates that during the period 1998-2017, India suffered climate- related losses amounting to $ 80 billion (UNDRR,2017).
Recently, a report by German watch placed India as 7th highest in the Global Climate Risk Index 2021. Changing weather patterns, extreme temperatures (hot and cold) and more extreme events such as droughts, floods, cloud bursts, cyclones, long wet and dry spells are seriously stressing the agricultural sector as well as the land and ecosystem resources agriculture and rural communities depend on. Climate change, apart from the damages and losses it inflicts, is also causing a decline in productivity of many cereal crops especially in wheat and rice, which provide the bulk of diets in south and east Asia. The GOI has recently forecasted that while rainfed rice yields are likely to reduce by up to 2.5%, irrigated rice yields will reduce by 7% in 2050 and 10% in 2080; wheat yield by 6-
25% in 2100 and maize yields by 18-23% (MoA, 2021).
There is thus a need to provide farmers and rural communities with timely and accurate weather forecasts together with customised farm management advisories (crop, livestock, soil, and land management) to enable them to reduce weather-induced risks and mitigate the impacts of climate change. Since farming is a livelihood and farmers must earn a remunerative income from it, these advisories must be accompanied by measures that build adaptive capacities and overall resilience to economic and climatic shocks. Such measures would necessarily include greatly improving resource use efficiency and productivity (such as of water, soil, and biomass), regenerating ecosystems, conserving local biodiversity, and facilitating remunerative monetary returns to farming investments.
To address these issues, we need to employ automation, IoT and good governance at scale to halve water consumption that will lead to rising groundwater levels while ensuring the food supply chain is secure, farmers are prosperous, and land degradation is prevented.
1. Engagement with communities to link the resultant system to supply and demand and effective climate action.
2. Standardized interoperability for data collection, usage, and regulation of agricultural records, market needs, state of crops, soil status, water and nutrient availability and requirements, as well as demographic, socioeconomic and cultural factors (i.e., development indicators) of the communities involved.
3. Utilization of the standardized database with systems linkages for a pilot test agricultural zone through community involvement and the revenue department of the respective region.
4. Development of dynamic resilience models to provide agricultural forecasting and advisory generation for crop production and protection with responsive feedback from communities using human and AI-driven inputs, remote and satellite sensing, and other technologies.
5. Development of a scalable, responsive, localized system for climate-driven agriculture with special emphasis on participation of women groups.
1. Improve crop production and protection for agricultural productivity and farmer livelihoods that maintain ecological sustainability.
2. Diffusion of S&T-based techniques and technologies into agriculture.
3. Highlight costs and benefits of incorporating digital technologies into agricultural communities for climate action.
4. Helping farmers to make informed decisions regarding climate-driven action and provide a sense of ownership over the process of crop production and protection to improve farmer welfare.
5. Provide farmers with direct access to targeted forecasting and advice.
6. Can lead to better crop planning and better usage of data by governments.
7. Better risk protection to prepare and respond to emerging environmental and ecological issues.