FORECASTING OF RAINFALL IN METEOROLOGICAL SUBDIVISIONS OF KARNATAKA USING NON-LINEAR STATISTICAL MODELS

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dc.contributor.advisorMOHAN KUMAR, T. L.
dc.contributor.advisorMOHAN KUMAR, T. L.
dc.contributor.authorKODANDARAMA, S. R.
dc.contributor.authorKODANDARAMA, S. R.
dc.date.accessioned2022-09-22T06:13:50Z
dc.date.available2022-09-22T06:13:50Z
dc.date.issued2020-12-01
dc.date.issued2020-12-01
dc.description.abstractIndian agriculture is mainly dependent on the timely arrival of rainfall and its distribution pattern. The analysis of rainfall distribution pattern and its forecast were essential for planning and management of water resources for agriculture and allied activities. Therefore, the present study was undertaken to analyze the trend, shifting pattern and forecasting of rainfall in four meteorological subdivisions of Karnataka namely North Interior Karnataka (NIK), South Interior Karnataka (SIK), Malnad and Coastal subdivisions using sixty years of monthly rainfall data (1960- 2019) collected from AICRP (Agro-Meteorology), GKVK and KSNDMC, Bengaluru. To analyze the trend in rainfall, Mann-Kendal and Modified Mann-Kendall tests were employed. For annual rainfall data, results of Mann-Kendal test revealed that no significant trend in all the subdivisions. However, Modified Mann-Kendall test showed monotonic increasing trend in SIK (1.47) and Coastal (5.10) subdivisions, monotonic decreasing trend in NIK (-1.40) subdivision, and no monotonic trend in Malnad subdivision. Likelihood Ratio test was used to assess the shifting pattern. Results revealed that NIK subdivision had decreased rainfall distribution after shifting year 2010 whereas, in SIK, Malnad and Coastal subdivisions increased rainfall distribution was observed after shifting years 1968, 2016 and 1966 respectively. To forecast monthly rainfall, H-WES, SARIMA, ARCH, GARCH and ANN time-series models were employed. For all the subdivisions, the ANN model was performed better than other models on both training and testing data on the basis of lowest RMSE value. Hence, ANN model can be used for forecasting monthly rainfall data in all the meteorological subdivisions of Karnataka.en_US
dc.description.abstractIndian agriculture is mainly dependent on the timely arrival of rainfall and its distribution pattern. The analysis of rainfall distribution pattern and its forecast were essential for planning and management of water resources for agriculture and allied activities. Therefore, the present study was undertaken to analyze the trend, shifting pattern and forecasting of rainfall in four meteorological subdivisions of Karnataka namely North Interior Karnataka (NIK), South Interior Karnataka (SIK), Malnad and Coastal subdivisions using sixty years of monthly rainfall data (1960- 2019) collected from AICRP (Agro-Meteorology), GKVK and KSNDMC, Bengaluru. To analyze the trend in rainfall, Mann-Kendal and Modified Mann-Kendall tests were employed. For annual rainfall data, results of Mann-Kendal test revealed that no significant trend in all the subdivisions. However, Modified Mann-Kendall test showed monotonic increasing trend in SIK (1.47) and Coastal (5.10) subdivisions, monotonic decreasing trend in NIK (-1.40) subdivision, and no monotonic trend in Malnad subdivision. Likelihood Ratio test was used to assess the shifting pattern. Results revealed that NIK subdivision had decreased rainfall distribution after shifting year 2010 whereas, in SIK, Malnad and Coastal subdivisions increased rainfall distribution was observed after shifting years 1968, 2016 and 1966 respectively. To forecast monthly rainfall, H-WES, SARIMA, ARCH, GARCH and ANN time-series models were employed. For all the subdivisions, the ANN model was performed better than other models on both training and testing data on the basis of lowest RMSE value. Hence, ANN model can be used for forecasting monthly rainfall data in all the meteorological subdivisions of Karnataka.en_US
dc.identifier.otherTh-12752
dc.identifier.otherTh-12752
dc.identifier.urihttps://krishikosh.egranth.ac.in/handle/1/5810188014
dc.keywordsRainfall, Tropical Monsoon Climateen_US
dc.keywordsRainfall, Tropical Monsoon Climateen_US
dc.language.isoEnglishen_US
dc.language.isoEnglishen_US
dc.pages115en_US
dc.pages115en_US
dc.publisherUniversity of Agricultural Sciences GKVK, Bangaloreen_US
dc.publisherUniversity of Agricultural Sciences GKVK, Bangaloreen_US
dc.subAgricultural Statistics and Informaticsen_US
dc.subAgricultural Statistics and Informaticsen_US
dc.themeRAINFALL IN METEOROLOGICAL SUBDIVISIONSen_US
dc.themeRAINFALL IN METEOROLOGICAL SUBDIVISIONSen_US
dc.these.typeM.Scen_US
dc.these.typeM.Scen_US
dc.titleFORECASTING OF RAINFALL IN METEOROLOGICAL SUBDIVISIONS OF KARNATAKA USING NON-LINEAR STATISTICAL MODELSen_US
dc.titleFORECASTING OF RAINFALL IN METEOROLOGICAL SUBDIVISIONS OF KARNATAKA USING NON-LINEAR STATISTICAL MODELSen_US
dc.typeThesisen_US
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