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A Data-Analytical Way of Estimating Rice Crop Yield: Economic and Water Related Causative Factors

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Abstract

Data analytical method using both economic and weather parameters is not just an alternative but is supportive and complementary to other commonly used techniques like remote sensing, agro-meteorological modeling, and field surveys to assess crop outlooks. This study, based on a model and official data, finds that economic factors related to markets and policies play an important role in the determination of rice yield in India and the role of rainfall has complex spatio-temporal dimensions and interactions with water management infrastructure and protocols. The yield forecast based on the model and early information of weather can provide a reliable real time outlook for policy use and validation of other forecasts and can be updated over time with the flow of new information.

Keywords

  • River basin
  • Crop yield
  • Climate change
  • Price effect
  • Rice
  • Modeling

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Fig. 1

Notes

  1. 1.

    A barrage is generally built for diverting water. According to the World Commission on Dams, a key difference between a barrage and a dam is that a dam is built for water storage in a reservoir, which raises the level of water significantly.

  2. 2.

    The water stored behind a dam is called its reservoir, and the term “spillway” usually is reserved for structures that release excess inflows, when the reservoir is already full (e.g. floods or heavy snowmelt).

  3. 3.

    Pulses are found major competitors for acreage in the first stage equation not reported but cash crop cotton also emerged as competitor of rice in Punjab and Haryana, jute in West Bengal and sugarcane and vegetables in Assam, Uttar Pradesh and Haryana. Coarse cereals too appeared as competitors for area in two of the states.

  4. 4.

    Sutlej River flows though the states of Himachal Pradesh, Punjab, Jammu and Kashmir and Haryana states. There is a proposed 214 kilometer Sutlej Yamuna link canal out of which 92 km canal has been already completed (MOJS, 2021).

References

  • Agarwal, A., & Narayan, S. (1991). State of India’s environment: Floods. Centre for Science and Environment.

    Google Scholar 

  • Dhawan, B. D. (1995). Magnitude of groundwater exploitation. Economic and Political Weekly, 30(14).

    Google Scholar 

  • Heady, E., & Dillon, J. L. (1961). Agricultural production functions. Iowa State University Press.

    Google Scholar 

  • Indo-Dutch Network Project (IDNP). (2002). Recommendations on waterlogging and salinity control based on pilot area drainage research. CSSRI, Karnal and Alterra-ILRI.

    Google Scholar 

  • James, et al. (2017). Brief history of agricultural systems modeling. Agricultural Systems, 155., Elsevier, 240–254.

    CrossRef  Google Scholar 

  • Justice, C., Gutman, G., & Vadrevu, K. P. (2015). NASA land cover and land use change. (LCLUC): An Interdisciplinary Research Program, 148(15), 4–9.

    Google Scholar 

  • Krishna, R. (1962). A note on the elasticity of the marketable surplus of a subsistence crop. Indian Journal of Agricultural Economics, 17, 79–84.

    Google Scholar 

  • Lasko, K., Vadrevu, K. P., Tran, V. T., Ellicott, E., Nguyen, T. T., Bui, H. Q., & Justice, C. (2017). Satellites may underestimate rice residue and associated burning emissions in Vietnam. Environmental Research Letters, 12(8), 085006.

    CrossRef  Google Scholar 

  • Lasko, K., Vadrevu, K. P., & Nguyen, T. T. N. (2018a). Analysis of air pollution over Hanoi, Vietnam using multi-satellite and MERRA reanalysis datasets. PLoS One, 13(5), e0196629.

    CrossRef  Google Scholar 

  • Lasko, K., Vadrevu, K. P., Tran, V. T., & Justice, C. (2018b). Mapping double and single crop paddy rice with Sentinel-1A at varying spatial scales and polarizations in Hanoi. Vietnam. IEEE journal of selected topics in applied earth observations and remote sensing, 11(2), 498–512.

    CrossRef  Google Scholar 

  • Ministry of Agriculture & Farmers Welfare (MoA&FW) (2019). Agriculture at a Glance 2019. Directorate of Economic and Statistics, Department of Agriculture & Farmers Welfare, GoI.

    Google Scholar 

  • MOJS (Ministry of Jal Shakti (MoJS). (2021). Sutlej-Yamuna Link Canal. http://mowr.gov.in/sutlej-yamuna-link-canal

  • Moran, T., Janny, C., & Carolina, S. (2014). The hidden costs of groundwater overdraft. Understanding california groundwater, water in the west. https://waterinthewest.stanford.edu/groundwater/overdraft/

  • Moorthi, Manthira, S., Oza, M. P., Misra, I., Gambhir, R. K., Darji, N. P., Sharma, S., Jain, D. K., Dhar, D., Padia, K., Ramakrishnan, R., Chowdhury, S., & Parihar, J. S. (2014). FASALSoft – An ISRO software framework for crop production forecast using remote sensing data analysis. Journal of Geomatics, 8(1), 27–33.

    Google Scholar 

  • Nadkarni, M. V., & Deshpande, R. S. (1983). Growth and instability in crop yields: a case study of agriculture in Karnataka, South India. Regional Studies, 17, 29–39.

    CrossRef  Google Scholar 

  • Nandargi, S. S., & Shelar, A. (2018). Rainfall and flood studies of the Ganga River Basin in India. Annals of Geographical Studies, 1(1), 34–50. Sryahwa Publications.

    Google Scholar 

  • National Water Policy (2012). Government of India. http://jalshakti-dowr.gov.in/sites/default/files/NWP2012Eng6495132651_1.pdf

  • Nerlove, M. (1958). The Dynamics of Supply: Estimation of Farm supply Response to Price. Johns Hopkins University Press.

    Google Scholar 

  • NITI AAYOG. (2015). Raising agricultural productivity and making farming remunerative for farmers. An occasional paper, Government of India. https://niti.gov.in/sites/default/files/2019-08/Raising%20Agricultural%20Productivity%20and%20Making%20Farming%20Remunerative%20for%20Farmers.pdf

  • Özyavuz, M., Bilgili, C., & Salıcı, A. (2015). Determination of vegetation changes with NDVI method. Journal of Environmental Protection and Ecology, 16, 264–273.

    Google Scholar 

  • Prasad, V. K., Badarinath, K. V. S., Yonemura, S., & Tsuruta, H. (2004). Regional inventory of soil surface nitrogen balances in Indian agriculture (2000–2001). Journal of Environmental Management, 73(3), 209–218.

    CrossRef  Google Scholar 

  • Ramaswamy R, I. (2015). Living rivers, dying rivers. Oxford University Press.

    Google Scholar 

  • Sarkar, S. (2019). Extreme rainfall and bad infrastructure lead to extreme Indian floods. August 23, the third pole.net Understanding Asia’s water crisis. https://www.thethirdpole.net/2019/08/23/extreme-rainfall-and-bad-infrastructure-lead-to-extreme-indian-floods/

  • Schultz, T. W. (1964). Transforming traditional agriculture. Yale University Press.

    Google Scholar 

  • Shagun, K. (2019). Dams were built to control floods; they are now triggers. Down to Earth, Wednesday 18 September.

    Google Scholar 

  • Sharma, B., Amarasinghe, U., Xueliang, C., de Condappa, D., Shah, T., Mukherji, A., Bharati, L., Ambilia, G., Qureshif, A., Pante, D., Xenariosa, S., Singh, R., & Smakhtin, V. (2010). The Indus and the Ganges: river basins under extreme pressure. Water International, 35(5), 493–521. Routledge Taylor and Francis Group.

    CrossRef  Google Scholar 

  • Sheffrin, S. M. (1983). Rational expectations. Cambridge University Press.

    Google Scholar 

  • Shweta, S., Kholod, N., Chaturvedi, V., Ghosh, P. P., Mathur, R., Clarke, L., Evans, M., Hejazi, M., Kanudia, A., Koti, P. N., Liu, B., Parikh, K. S., Ali, M. S., & Sharma, K., (2017). Water for electricity in India: A multi-model study of future challenges and linkages to climate change mitigation. Applied Energy. https://www.osti.gov/pages/servlets/purl/1364388

  • Singh, A., Chakravarty, S., M. Rajeshwor, Ghosh, N. (2020). Food Production in Indo-Gangetic Plains: To Understand the Role of Water and Hydrology. International Journal of the Science of Food and Agriculture, 4(4), 413–426. https://doi.org/10.26855/ijfsa.2020.12.008

  • Srinivasan, S., Kholod, N., Chaturvedi, V., Ghosh, P.P., Mathur, R., Clarke, L., Evans, M., Hejazi, M., Kanudia, A., Koti, P.N. & Liu, B. (2018). Water for electricity in India: A multi-model study of future challenges and linkages to climate change mitigation. Applied Energy, 210, 673–684.

    Google Scholar 

  • Suhag, R. (2016). Overview of ground water in India. PRS. https://ideas.repec.org/p/ess/wpaper/id9504.html

  • World Commission. (2000). Dams and developments: A new framework for decision making. The report of the World Commission on Dams. https://www.internationalrivers.org/sites/default/files/attached-files/world_commission_on_dams_final_report.pdf

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Acknowledgement

The authors thank Ms. Yashika Rani for data operation and acknowledge the funds provided by the Government of India, Ministry of Agriculture & Farmers Welfare for the FASAL project for which the data is collected and analyzed.

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Correspondence to Nilabja Ghosh .

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Ghosh, N., Rajeshwor, M., Singh, A., Chakravarty, S. (2022). A Data-Analytical Way of Estimating Rice Crop Yield: Economic and Water Related Causative Factors. In: Vadrevu, K.P., Le Toan, T., Ray, S.S., Justice, C. (eds) Remote Sensing of Agriculture and Land Cover/Land Use Changes in South and Southeast Asian Countries. Springer, Cham. https://doi.org/10.1007/978-3-030-92365-5_11

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