Improving efficiency of block-level agrometeorological advisory system by exploiting reuse: A study in Telangana

Authors

  • MAMATHA ALUGUBELLY IT for Agricultural Research Center, IIIT, Hyderabad, Telangana, India
  • KRISHNA REDDY POLEPALLI IT for Agricultural Research Center, IIIT, Hyderabad, Telangana, India
  • BALAJINAIK BANOTH Agro Climate Research Center, PJTSAU, Hyderabad, Telangana, India
  • SREENIVAS GADE Agro Climate Research Center, PJTSAU, Hyderabad, Telangana, India
  • ANIRBAN MONDAL Department of Computer Science, Ashoka University, Delhi, India
  • SEISHI NINOMIYA Institute for Sustainable Agro-ecosystem Services, University of Tokyo, Japan

DOI:

https://doi.org/10.54386/jam.v23i3.38

Keywords:

Agromet advisory, Weather condition, Reuse, Similarity, Categorical Weather Condition, Weather forecast

Abstract

India Meteorological Department (IMD) has started block-level level agromet advisory (AA) service from the year 2015 and is currently operating in a few blocks of each state across India. In a block-level AA service, on every Tuesday and Friday, AA is being prepared for each block based on the block-level Medium Range weather Forecast (MRF). In this paper, we propose a framework to improve the preparation of blocklevel AA by modeling a weather situation as “Category-based Weather Condition (CWC)” and exploiting both “temporal reuse” and “spatial reuse” of AA based on the similarity among CWCs. The weather data analysis for 12 blocks of Telangana by considering the phenophase-specific CWCs of Rice crop showed that there is a scope to improve the efficiency of block-level AA bulletin preparation process by exploiting reuse.

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Published

01-09-2021

How to Cite

MAMATHA ALUGUBELLY, KRISHNA REDDY POLEPALLI, BALAJINAIK BANOTH, SREENIVAS GADE, ANIRBAN MONDAL, & SEISHI NINOMIYA. (2021). Improving efficiency of block-level agrometeorological advisory system by exploiting reuse: A study in Telangana. Journal of Agrometeorology, 23(3), 330–339. https://doi.org/10.54386/jam.v23i3.38

Issue

Vol. 23 No. 3 (2021): September

Section

Research Paper

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