Faculty Publications
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Item Combining agriculture, social and climate indicators to classify vulnerable regions in the Indian semi-arid region(IWA Publishing, 2022) Kalli, R.; Jena, P.R.Climate change vulnerability is highly counter-productive for agriculture among the arid and semi-arid regions. The study constructs the agriculture vulnerability index for Karnataka, a south Indian state. The state has faced frequent climate-related shocks in the last decade. The district-wise vulnerability index is estimated using longitudinal data considering exposure, sensitivity and adaptive capacity as sub-indices. The results show that the districts in the north interior region of Karnataka are highly vulnerable to the climate change followed by the districts in the south interior and coastal regions. There is an urgent need to prioritize the most vulnerable districts while formulating the development policies to minimize the risk of climate change on agriculture. Specific technical knowledge and support need to be made available to the farmers for informative climate resilience action. © 2022 The Authors.Item Subsidized LPG Scheme and the Shift to Cleaner Household Energy Use: Evidence from a Tribal Community of Eastern India(MDPI, 2022) Kalli, R.; Jena, P.R.; Managi, S.Traditional fuels have both environmental and health impacts. The transition from traditional to clean cooking fuel requires significant public policy actions. The Pradhan Mantri Ujjwala Yojana (PMUY) is one of the primary policies launched in India to eradicate energy poverty among households. Past studies have focused on the drivers that motivate rural households to adopt clean energy and identified the bottlenecks for adoption of clean energy in developing countries. PMUY’s success in terms of scale and pace is critical in the national drive to provide access to clean energy fuel to each citizen. The present study focuses on two objectives. First, we investigate the intensity of adoption and refill of LPG under the PMUY scheme. Second, we use household and other demographic characteristics to examine the factors that influence households’ decision on using LPG as a cooking fuel. Empirical results show that rapid growth has been witnessed in the provision of subsidized LPG connections. However, the annual average refill status stands at two LPG cylinders per beneficiary household indicating that the majority of the beneficiaries have failed to refill their LPG cylinders. This imbalance between rapid enrollment of LPG and limited refill among beneficiary households indicate the continued usage of traditional sources of energy for cooking. From the primary survey conducted in the rural tribal communities of Odisha, we observe that household income and education played a significant role in adoption of LPG and continued usage of LPG gas. Additionally, the logit and ordered probit models identify that membership in self-help groups, accessibility and awareness of LPG are the major adoption drivers. In conclusion, policy makers need to address the challenge of refill status among PMUY consumers. Further, educating households on health benefits through SHG and creating accessibility at village level can actively increase the usage of LPG. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.Item Prediction of crop yield using climate variables in the south-western province of India: a functional artificial neural network modeling (FLANN) approach(Springer Science and Business Media B.V., 2023) Jena, P.R.; Majhi, B.; Kalli, R.; Majhi, R.To meet the demand of the growing population, there exists pressure on food production. In this context, appropriate prediction of crop yield helps in agricultural production planning. Given the inability of the traditional linear models to provide satisfactory prediction performance, there is a need to develop a crop yield prediction model that is simple in complexity, accurate in prediction, and less time-consuming during training and validation phases. Keeping these objectives in view, the present paper focuses on building an adaptive, low complexity, and accurate nonlinear model for the prediction of crop yield. A time series dataset for the period 1991–2012 of Karnataka, a southwestern state of India, is used for yield prediction. An empirical nonlinear relation between crop yield and the four independent attributes has been obtained from the proposed ANN model. The independent attributes employed are total rainfall, the cumulative distribution of temperature, the proportion of irrigated land, and the average amount of fertilizer used. It is demonstrated that the developed model exhibits better prediction accuracy, less root mean square error in the range of 0.07–0.14, less mean square error in the range of 0.01–0.04, and mean absolute error in the range of 0.07–0.15 compared to its corresponding linear regression model. It is recommended that the proposed ANN model can also be applied to predict other agricultural products of the same or other geographical regions of the globe. © 2022, The Author(s), under exclusive licence to Springer Nature B.V.Item Effect of irrigation on farm efficiency in tribal villages of Eastern India(Elsevier B.V., 2024) Kalli, R.; Jena, P.R.; Timilsina, R.R.; Rahut, D.B.; Sonobe, T.Irrigation is an important adaptation strategy to cope with climate change which reduces vulnerability to water stress and improves crop productivity to feed millions. There is evidence of crop yield stagnation in many developing countries, and irrigation efficiency is claimed to increase crop productivity. Therefore, this paper uses data envelopment analysis to evaluate the farmer's productivity through technical efficiency (TE), i.e., the relationship between resource inputs and outputs of 513 paddy farmers in Eastern India. The results show that the farms are, on average operating at 14% TE, leaving a considerable scope to improve up to 86% to reach the optimal level. A significant difference is observed between irrigated and rain-fed paddy farmers, such that10% of the irrigated farms achieved efficiency scores over 40% and only 2% of rain-fed farms achieved the same. The tobit and beta fit regression models are estimated to find out the factors that influence the TE. Both surface water and groundwater sources of irrigation are used as predictors, along with other socio-demographic factors. Access to surface water irrigation is identified to be a significant determinant of farm efficiency, however, surface water irrigation, such as canal irrigation, is accessible only to farmers living on plain land. Farmers living on highlands need to explore other sources of irrigation practices, such as drip and sprinkler, that can increase TE and farm productivity. Therefore, this paper calls for government intervention to provide extensive training and facilities for these micro-irrigation practices. © 2023 The Authors