Experiment code 20.7.3.15
Experiment Title Trends and Geostatistical Interpolation of Spatio- Temporal Variability of Precipitation in Gujarat
Research Type Departmental Research
Experiment Background Examining the variability of rainfall across spatial and temporal dimensions holds significance for the sustainable management of water resources and future development in the context of climate change (Dassou et al.2016). Understanding and quantifying long-term rainfall variability at regional scale is important for a country like India where economic growth is very much dependent on agricultural production which in turn is closely linked to rainfall distribution. (Mohapatra et al.2021). Spatial interpolation techniques are widely utilized to enhance the spatial resolution of data through the estimation of values in areas without sampling, applied in geosciences, water resources, environmental sciences, and agriculture. The study will help to understand the spatial and temporal variability of rainfall in the Gujarat.
Experiment Group Social Science
Unit Type (02)EDUCATION UNIT
Unit (12)NAVINCHANDRA MAFATLAL COLLEGE OF AGRICULTURE (NAVSARI)
Department (247)Statistics Department, NMCA, Navsari
BudgetHead (303/12712/03)303/03/REG/01784
Objective
  1. To study trends of precipitation over the Gujarat.
  2. To study Spatio-Temporal variability of precipitation
PI Name (NAU-EMP-2014-000353)YOGESH ASHOK GARDE
PI Email y.garde@nau.in
PI Mobile 8469764778
Year of Approval 2024
Commencement Year 2024
Completion Year 2026
Research Methodology
  • Location of Study: This study will be explained rainfall variations spanning 39 years, from 1985 to 2023, in Gujarat, India.
  • Data will be collected from i) www.imdpune.gov.in

                                          ii) https://power.larc.nasa.gov/data-access-viewer/

  • Research Design: This study will be used Kriging and Inverse Distance Weighting methods associated with Mann-Kendall and Sen’s slope estimator to overview the spatio-temporal variability of rainfall.
  • Kriging methods: Kriging is a geostatistical method of interpolation (prediction) for spatial data

 

  • Inverse Distance Weighting (IDW) methods: It is a local interpolation method which was defined as distance reverse function of each point from neighboring points. This method estimates values at un-sampled points by the weighted average of observed data at  surrounding points

  • Mann-Kendall: The Mann-Kendall  test  is  a  test developed by Mann  in 1945  and  completed by Kendall  in 1975.

  • Sen’s slope estimator: The Sen’s slope method is a non-parametric procedure developed by Sen in 1968
(NAU-EMP-2014-000353)
YOGESH ASHOK GARDE 		y.garde@nau.in 8469764778 06-02-2025
Active
(NAU-EMP-2019-000537)
NITIN VARSHNEY 		nitin.caw@nau.in 9157548912 12/06/2024
Active
(NAU-EMP-2013-000562)
VIPUL TANAJI SHINDE 		vipulshinde@nau.in 8128984318 12/06/2024
Active
(NAU-EMP-2015-000063)
ALOK SHRIVASTAVA 		igkvalok@nau.in 9424242849 12/06/2024
Active
(NAU-EMP-2019-000955)
ARVINDKUMAR PURABHAI CHAUDHARY 		apchaudhary@nau.in 9662838469 12/06/2024
Active
(NAU-EMP-2013-000974)
VISHAL SHANKAR THORAT 		vishalthorat@nau.in 8469552697 12/06/2024
Active
(NAU-EMP-2015-000926)
PRAVINSINH KANUBHAI PARMAR 		aspeeagmet@nau.in 9998715092 12/06/2025
Active
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