Parthsarthi Pandya

About

Worked/Working on Drip Irrigation, Agricultural and Meteorological Drought characterization and development of operation agricultural drought monitoring applications using remote sensing and machine learning, Hydrology, Watershed Management, Soil and Water Conservation. Teaching to UG (B.Tech, Agril. Engineering) and PG (M.Tech, Soil and Water Conservation/Irrigation and Drainage Engineering) at Junagadh Agricultural University, Junagadh, Gujarat, India. The subjects include Dryland Water management Technologies, Advanced soil and water conservation engineering, Watershed planning and management, Fluid Mechanics and Open Channel Hydraulics, Water harvesting and Soil & Water Conservation Structures. Holding the responsibility as Technical Officer to Hon'ble Vice Chancellor, Junagadh Agricultural University.

Employment

• Junagadh Agricultural University Assistant Professor
  2015 - Present

Education

Education history is unavailable.

Projects & Funding

Projects & funding information is unavailable.

Publications (11)

• From raw to reliable: machine learning bias correction of reanalysis data for improved drought severity classification
  Journal of Hydrology 2026 DOI: 10.1016/j.jhydrol.2025.134892
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• Correlation vs. Kappa statistic: a new perspective on comparing meteorological drought indices
  Theoretical and Applied Climatology 2025 DOI: 10.1007/s00704-024-05291-0
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• Analysis of Meteorological Drought for Selected Districts of Saurashtra Region of Gujarat
  International Journal of Environment and Climate Change 2024 DOI: 10.9734/ijecc/2024/v14i84364
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• Exploring Temperature Trends and Evapotranspiration Modelling for Effective Water Management: A Comprehensive Analysis Using Mann-Kendall Test and Seasonal ARIMA Model
  Research Square 2024 DOI: 10.21203/rs.3.rs-4146952/v1
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• Improving remote sensing based agricultural drought characterization in Saurashtra, Gujarat: A region-specific threshold approach
  Mausam 2024 DOI: 10.54302/mausam.v75i2.6077
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• Development of drought severity–duration–frequency curves for identifying drought proneness in semi-arid regions
  Journal of Water and Climate Change 2023 DOI: 10.2166/wcc.2023.438
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• Early crop yield prediction for agricultural drought monitoring using drought indices, remote sensing, and machine learning techniques
  Journal of Water and Climate Change 2023 DOI: 10.2166/wcc.2023.386
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• Development of PCA-based composite drought index for agricultural drought assessment using remote sensing
  Journal of Agrometeorology 2022 DOI: 10.54386/jam.v24i4.1738
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• Meteorological Drought Analysis Using Standardized Precipitation Index
  Current World Environment 2020 DOI: 10.12944/CWE.15.3.12
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• HYPSOMETRIC ANALYSIS OF OZAT RIVER BASIN (GUJARAT) USING REMOTE SENSING AND GIS TECHNIQUES
  AGRES – An International e. Journal 2018 DOI: 10.12944
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