Agricultural Reviews
Chief EditorPradeep K. Sharma
Print ISSN 0253-1496
Online ISSN 0976-0741
NAAS Rating 4.84
Chief EditorPradeep K. Sharma
Print ISSN 0253-1496
Online ISSN 0976-0741
NAAS Rating 4.84
Indigenous Technical Knowledge based Rainfall Prediction: A Review
Submitted11-08-2021|
Accepted03-11-2021|
First Online 07-01-2022|
Indigenous technical knowledge (ITK) is the actual knowledge of a given population that reflects the experiences based on tradition and includes more recent experiences with modern technologies. Traditionally, farmers have used traditional knowledge to understand weather and climate patterns in order to make decisions about crop and irrigation cycles. This knowledge has been gained through many decades of experience and has been passed on from previous generations. The present study was undertaken with the objective of collection and documenting the indigenous technical knowledge of farmers regarding rainfall prediction based on abiotic and biotic factors which is being practiced generation after generation. Here in this paper an effort has been made to collect the abiotic and biotic factors predicting rainfall, as a part of ICAR sponsored NASF ad-hoc research project entitled “Developing climate resilient adaptive strategies for empowerment of farmers” which has been implemented in University of Agricultural Sciences, Dharwad from 2019 to 2022. Various indigenous technical knowledge are collected by analyzing the journals and newsletters, deep interaction with the farmers of study area, contacting the local resource persons and documenting oral histories without scientific validation. The study found that traditional methods of rainfall forecasting can be utilized for the purpose of short-term and long-term seasonal rainfall predictions by local communities. All available abiotic and biotic indigenous rainfall forecasting techniques may serve as alternative to modern technologies.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.