Satellite agromet products and their adaptation for advisory services to Indian farming community
DOI:
https://doi.org/10.54386/jam.v25i1.2084Keywords:
Agromet Advisory, Satellite, Agromet Products, GKMSAbstract
Anomalous and erratic behaviour of weather pose various challenges for agricultural community from crop sowing to post harvest. The balance between turn-around-time for farm operations and resource optimization can limit the expected losses due to unfavourable weather. In the past, thrust was given to issue agromet advisories to farmers for a group of districts and blocks primarily using medium-range weather forecast with coarser grid resolution, crop records and point observation for crop condition. The current advisory framework under Gramin Krishi Mausam Seva (GKMS) of India Meteorological Department (IMD) lacks in, near real time assessment of crop and soil conditions to improve the quality and coverage of advisories. The spectral observations from polar and geostationary satellites provide agromet products for synoptic, real-time and continuous monitoring of crops. In order to strengthen the existing advisories under GKMS, the usage of satellite derived daily agromet products in six AFMUs (Agro-Met Field Units) (382 blocks of 60 districts) was initiated by Space Applications Centre, ISRO and IMD. Several agromet products such as Normalized Difference Vegetation Index (NDVI), Potential Evapotranspiration (PET), Surface Dryness Index (SDI), Minimum and Maximum Land Surface Temperature (LST) and Surface Soil Moisture (SSM) aggregated for block and district agricultural regions are provided to all six AFMUs in user friendly format since October 2019 through a dedicated web link
from VEDAS (https://vedas.sac.gov.in) geoportal. Time series and near real-time agromet products during agricultural seasons are being used to interpret crop sowing prospect, crop condition, irrigation requirement, crop stress etc. at block and district scales. Regular evaluation of these products over respective AFMUs with measured ground data showed 9% and 10% difference for PET and SSM respectively, whereas, LST showed RMSE of 2.0 K. In future, crop specific agromet parameters and their short-term forecasting are primary focus to provide value-added quality advisories at Gram Panchayat level to all AFMUs.
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Copyright (c) 2023 RAHUL NIGAM, BIMAL BHATTACHARYA, MEHUL R PANDYA
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