A NOVEL APPROACH TO ANALYSIS DISTRICT LEVEL LONG SCALE SEASONAL FORECASTING OF MONSOON RAINFALL IN ANDHRA PRADESH AND TELANGANA

P. Chandrashaker reddy, Dr. A. Suresh Babu

Abstract


India is a nation which purely relies around agriculture, so rain fall prediction is very important for agriculture to make crop management decisions. Long scale forecast of rainfall during monsoon season (southwest and northeast), at spatial firmness of a district, could serve as an important comment to the agricultural community to take better decisions in yield management. Such forecasts are not producing efficient results which are available now. In this paper rain fall, crops and soil data of Andhra Pradesh (AP) & Telangana (TS) states are gathered to analyze rain fall patterns based on soil for crop management. Variety of crops needs adequate rain fall based on their different categories. In this paper, we are proposing a model which relates the analysis of rain fall patterns, soil types and different crops grown in two states on seasonal wise. We are experimenting with last 12 years of rain fall data, variety of crops grown in different seasons and identifying the average rain fall needed for different crops. DB SCAN clustering algorithm used to identify the rain fall patterns as low and high density. The proposed system serves as a tool to explore the rain fall patterns. The statistical results shows that proposed model could enhance those effectiveness and exactness.

Keywords


Rainfall; DBSCAN ; Crop; Forecast; SWM; NEM; Soil; Clustering ;AP & TS

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DOI: https://doi.org/10.26483/ijarcs.v8i9.4928

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