Asia is the region most vulnerable to climate change and India is ranked as one of the most climate vulnerable countries in the world, frequently affected by natural disasters. In this study, we investigated the impact of drought on crop productivity, farmer’s employment and income. The difference-in-difference model (DID) and stepwise multiple linear regression (MLR) were employed to quantify the impact of adopting climate resilient technologies (CRTs) on farm household income during a drought. The factors influencing farm incomes were analyzed using MLR. The study used survey data collected from the drought prone district of Telangana, India. Sixty farmers each from a village adopted under the National Innovations in Climate Resilient Agriculture (NICRA) program and a control village were interviewed. Primary data on the socio-economic characteristic of farmers, cropping pattern, income composition, productivity of major crops, employment and climate resilient interventions adopted by farmers were collected using a well-structured schedule. The results reveal that income crop cultivation was the major contributor to household income (60%) followed by livestock rearing. Farmers reported that droughts decreased the income from crops by 54 per cent and income from livestock rearing by 40 per cent. The farmers belonging to the climate resilient village had 35 per cent higher incomes compared to those in the control village and it was estimated to be Rs. 31,877/farm household/year during droughts using the DID estimate. Farm size, livestock possession, adoption of CRTs and investment in agriculture were the determining factors influencing farm income. Thus, farmers especially in drought prone regions need to be encouraged and supported to adopt cost effective, location specific climate resilient technologies.

The variability in climate affects the agricultural production especially in drylands. It is necessary to understand and quantify the impacts of resilient technologies as well as effects of extreme events. Keeping these in view, the primary data on household characteristics and the farm income was collected from a sample of 60 farmers each from National Innovations in Climate Resilient Agriculture (NICRA) program adopted village and a comparable control village in the district. The sample was also post classified into small, medium and large farmer to bring out the economic impact across land classes. The impact was estimated following the difference-in-differences (DiD) model as the data allows us to use effectively the data across time and regions. The results show us that the average income of a farm household in the NICRA village is more than 40 percent than non-adopted village and during a drought situation the farmers under NICRA intervention where better off by 19.5 percent. The income from crops and livestock production in adopted village was significantly higher than the control village. The DiD model output showed the farm income of adopted village was 40 percent higher showing that better climate smart interventions improved the farm incomes. The estimate showed that the treated farm household had higher income of Rs. 54,717 than the control during a drought year. Better knowledge and quantification of impact of technology adoption on farm income specially during drought will help to effectively design technological and policy interventions for better drought management in drylands.

Climate change is considered as a potential threat to sustainability of agriculture in India. Considering the importance of agriculture in the pursuit of the India’s development objectives, including the Sustainable Development Goals of the United Nations, understanding possible impacts of climate change on productivity of major food crops in the country assumes importance in developing appropriate policies and programmes for agricultural technology development and transfer in general and for climate change adaptation in particular. Such an understanding at a scale where most of the development planning is done will be more useful in policy planning. This paper analysed climate change impacts at district level for major food crops using the district level climate projections for two time periods viz., mid-century (2021–2050) and end-century (2071–2098). Yields of most crops are projected to decrease in a majority of districts during mid-century period. The yield impacts are deeper and wider during end-century period. The yield impacts are relatively smaller and even positive in case of rapeseed & mustard and soybean. Some of the policy implications emerging from this study are: (i) Efforts are to be targeted and prioritized in the districts where the yields are likely to suffer more (ii) Concerns related to abiotic stress, especially those related to heat/temperature stress, need more attention in crop improvement and natural resource management programmes and (iii) Considering the dimension of climate change along with other bottlenecks to sustainable agriculture in the research and development process is a desirable way of mainstreaming climate change in to economic development programmes.

Agricultural Research & Technology: Open Access Journal is a dynamic journal for publishing research reports, short communications, Critical Reviews in Agricultural Economics and Farm Management, Agronomy, Forestry, Animal Science, Food Technology, etc. The goal of the open access journalsis to publish articles on new and emerging fields and concepts for providing future directions to promote agricultural research globally. It is a unique open access journal covering all the disciplines of crop sciences, animal sciences, fishery sciences, forestry sciences and natural resources management sciences, to stimulate interest in inter-disciplinary research. This open access journal will catalyze policy development on issues impacting rational agricultural growth and development globally. It also publishes open access books.

To make rainfed agriculture an economically viable enterprise for improving the livelihood and welfare of the farming communities contributing around 40 percent of the total food production in India, it is vital to implement best management practices to keep soils healthy, conserve agronomic inputs, minimize environmental impacts, and produce adequate yields. Increases in the sudden downpour of rain invites a high amount of soil loss from agricultural fields, eroding the uppermost soil layer. Permanent fodder grass strips effectively trap sediments and check nutrient removal from soil on one hand and on other meet the green fodder demands of small ruminants. However, nutrients removed by erosion create a limitation on land productivity. It has been observed that grass systems are useful for the improvement of other soil properties (soil physical and biological properties, for example) related to soil erosion control, slope stabilization, and food production. Hence, this study brought out the impact of grass-strip-based cropping systems on the sustainability of rainfed farming. Fields with grass strips improved their soil quality from 0.39 to 0.52 over a four-year period. This concept of growing grasses on both sides of a field (in a one-meter strip) in areas of loamy fine sand to sandy loam textured soils improves soil health and significantly reduces runoff from cropped fields. A permanent belt of Brachiaria ruziziensis and Stylosanthes hamata in two meter widths was established at every fifteen meters across the direction of the slope and reduced soil loss by 65–70 percent. This mechanization of friendly technology provides sufficient green fodder for small ruminants. A castor–redgram rotation with fodder grass strips (especially Brachiaria ruziziensis) on the upper and lower sides of the slopes fetched better crop productivity, and thus the total returns increased from 137,022 rupees/ha to 178,689 rupees/ha. The use of grass strips is a low-cost measure for soil conservation, especially for slowing down the run-off from sudden downpours of high intensity. This study may aid researchers and managers in helping farmers with this low-cost and viable technology.