Decision support system for digitally climate informed services to farmers in India

Authors

  • K. K. SINGH India Meteorological Department, Ministry of Earth Sciences, New Delhi
  • KRIPAN GHOSH Agromet Division, India Meteorological Department, Pune
  • S. C. BHAN India Meteorological Department, Ministry of Earth Sciences, New Delhi
  • PRIYANKA SINGH India Meteorological Department, Ministry of Earth Sciences, New Delhi
  • LATA VISHNOI India Meteorological Department, Ministry of Earth Sciences, New Delhi
  • R. BALASUBRAMANIAN Meteorological Centre, Bhopal
  • S. D. ATTRI India Meteorological Department, Ministry of Earth Sciences, New Delhi
  • SHESHAKUMAR GOROSHI India Meteorological Department, Ministry of Earth Sciences, New Delhi
  • R. SINGH India Meteorological Department, Ministry of Earth Sciences, New Delhi

DOI:

https://doi.org/10.54386/jam.v25i2.2094

Keywords:

GKMS, Weather Forecast, Agromet DSS, ICT, Advisory feedback

Abstract

India Meteorological Department (IMD), Ministry of Earth Sciences (MoES) in collaboration with Indian Council of Agriculture Research (ICAR), State Agriculture Universities (SAUs) , Indian Institute of Technology (IITs) and other organizations is rendering weather forecast based District level Agrometeorological Advisory Service (AAS) for benefits of farmers in the country under the centrally sponsored scheme ‘Atmosphere & Climate Research-Modelling Observing Systems & Services (ACROSS) ’ of MOES. AAS, popularly known as Gramin Krishi Mausam Sewa (GKMS) provides advance weather information along, with crop specific agromet advisories to the farming community by using state of the art instruments and technology through efficient delivering mechanism of the information which ultimately enables farmers to take appropriate actions at farm level. The various components of GKMS viz. observing weather, its monitoring and forecast; crop specific advisory bulletin generation and dissemination; outreach and feedback have been/are being digitized to support integrating all the components of information generation and action suggested linked to these information. An Information and Communication Technology (ICT) based Agromet Decision Support System is developed for automation of the services provided under GKMS. This includes a dynamic framework to link the information of weather forecast, real time weather observation, crop-weather calendar etc. to translate weather forecast into actionable farm advisories for efficient farm level decision making in India. Apart from this, effort is being made to develop recent technology driven tools to estimate future yield of crops and prepare an irrigation schedule without a need of multiple parameters.

References

Charvat, K., Junior, K.C., Reznik, T., Lukas, V., Jedlicka, K., Palma, R., Berzins, R. (2018). Advanced visualisation of big data for agriculture as part of databio development. In Proceedings of the IGARSS. In “IEEE International Geoscience and Remote Sensing Symposium”, Valencia. pp. 415–418.

Daron, J. D., Lorenz, S., Wolski, P., Blamey, R. C., and Jack, C. (2015). Interpreting climate data visualisations to inform adaptation decisions. Climate Risk Manag., 10: 17–26.

Jedlička, K. and Charvát, K., (2018). Visualisation of big data in agriculture and rural development. In “Proceedings of the IST-Africa Week Conference (IST-Africa)”, Gaborone, Botswana.

Jones, J.W., (1980). Decision support systems – An organizational perspective. Adm. Sci. Q., 25 (2): 376-382.

Nowak, B. (2021). Precision agriculture: Where do we stand? A review of the adoption of precision agriculture technologies on field crops farms in developed countries. Agric. Res., 10: 515–522

Rao, V.U.M., Rao, A.V.M.S., Sarath Chandran, M.A., Prabhjyot Kaur., Vijaya Kumar, P., BapujiRao, B., Khandgond, I.R. and Srinivasa Rao, Ch. (2015). District level crop weather calendars of major crops in India. Central Research Institute for Dryland Agriculture, Hyderabad – 500 059, 40 pp.

Sheng, Y.K. and Zhang, S. (2009). Analysis of problems and trends of decision support systems development In: International Conference on E-Business and Information System Security. pp. 1216-1218.

Singh, K.K., Baxla, A.K., Singh, P. and Singh, P.K. (2019). Weather Based Information on Risk Management in Agriculture. In book: “Climate Change and Agriculture in India: Impact and Adaptation” DOI: 10.1007/978-3-319-90086-5_16

Taechatanasat, P. and Armstrong, L. (2014). Decision support system data for farmer decision making Proceedings of Asian Federation for Information Technology. Agriculture, pp. 472-486.

Terribile, F., Agrillo,A., Bonfante, A., Buscemi, G., Colandrea, M., D’Antonio, A., De Mascellis, R., DeMichele, C., Langella, G., Manna, P., Marotta, L., Mileti,F.A., Minieri, L. Orefice, N., Valentini, S., Vingiani, S. and Basile, A. (2015). A web-based spatial decision supporting system for land management and soil conservation.

Turban, E .(1995). Decision support and expert system . Prentice Hall , USA

Kumar, V. P., Bal, S.K., Dhakar, R. (2021). Algorithms for weather-based management decisions in major rainfed crops of India: Validation using data from multi-location field experiments. Agronomy J., 113:1−15. https://doi.org/10.1002/agj2.20518.

Wilkinson, E., Budimir, M., Ahmed, A. K., and Ouma, G. (2015). Climate information and services. BRACED countries. (1).

Yazdani, M., Zarate, P., Coulibaly, A. and Zavadskas, E.K. (2017). A group decision making support system in logistics and supply chain management. Expert Syst. Appl., 88: 376-392.

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Published

25-05-2023

How to Cite

K. K. SINGH, KRIPAN GHOSH, S. C. BHAN, PRIYANKA SINGH, LATA VISHNOI, R. BALASUBRAMANIAN, S. D. ATTRI, SHESHAKUMAR GOROSHI, & R. SINGH. (2023). Decision support system for digitally climate informed services to farmers in India. Journal of Agrometeorology, 25(2), 205–214. https://doi.org/10.54386/jam.v25i2.2094

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