Dr. P Kabbilawsh

About

Dr P. Kabbilawsh is highly adept in developing statistical models such in field of water resource research mainly focusing on hydrological modelling, stochastic time-series analysis, and climate-driven streamflow forecasting. Developed hybrid variants of SARIMA, Hyndmna-Khandakar SARIMA models and first to apply Thomas-Fiering stochastic streamflow generation model to precipitation data for forecasting long-term precipitation. Dr P Kabbilawsh line of work brings wavelet techniques, Machine Learning Techniques and applied four most conventional used statistical homogeneity techniques for hydrological predictions under non-stationary and climate-impacted conditions, thereby supporting robust water management and flood forecasting strategies.

Employment

• National Institute of Technology Calicut Research Scholar (Completed in 2025)
  2016 - Present

Education

• National Institute of Technology Calicut PhD

Projects & Funding

Projects & funding information is unavailable.

Publications (5)

• Assessment of temporal homogeneity of long-term rainfall time-series datasets by applying classical homogeneity tests
  Environment, Development and Sustainability 2023 DOI: 10.1007/s10668-023-03310-0
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• Performance evaluation of univariate time-series techniques for forecasting monthly rainfall data
  Journal of Water and Climate Change 2022 DOI: 10.2166/wcc.2022.107
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• Forecasting long-term monthly precipitation using SARIMA models
  Journal of Earth System Science 2022 DOI: 10.1007/s12040-022-01927-9
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• Infilling Missing Monthly Maximum and Minimum Temperature Dataset by EM Algorithm Followed by Distribution Based Statistical Assessment Using Eight Absolute Homogeneity Tests
  Water Science and Technology Library 2021 DOI: 10.1007/978-3-030-64202-0_43
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• Trend analysis and SARIMA forecasting of mean maximum and mean minimum monthly temperature for the state of Kerala, India
  Acta Geophysica 2020 DOI: 10.1007/s11600-020-00462-9
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