Indian Journal of Soil Conservation
  • Year: 2016
  • Volume: 44
  • Issue: 3

Statistical modelling of weekly rainfall data for crop planning in Bundelkhand region of central India

  • Author:
  • N.M. Alam1,, Rajeev Ranjan2, Partha Pratim Adhikary3, Ambirsh Kumar1, C. Jana1, Sanjeev Panwar4, P.K. Mishra1, N.K. Sharma1
  • Total Page Count: 7
  • Page Number: 336 to 342

1ICAR-Indian Institute of Soil and Water Conservation, Dehradun-248195, Uttarakhand

2ICAR-Indian Institute of Soil and Water Conservation, Research Centre, Datia-475661, Madhya Pradesh

3ICAR-Indian Institute of Soil and Water Conservation, Research Centre, Koraput-7 63002, Odhisa

4Indian Council of Agricultural Research, New Delhi-110001

*E-mail: alam.nurnabi@gmail.com

Online published on 23 December, 2016.

Abstract

The historical rainfall data for the period of 46 years (1968–2013) of Datia district in Bundelkhand were analysed for selection of most appropriate probability distribution of rainfall. The best distribution among different data sets has been identified using probability plot and Anderson-Darling (AD) test for goodness-of-fit, along with the appropriateness of estimated percentiles. From the analysis, it was found that one single probability distribution has not been found appropriate to represent all the datasets though Weibull and Gamma distributions were found promising for most of the datasets. The best-fit distribution has been employed for obtaining the assured quantum of rainfall pertaining to Standard Meteorological Weeks (SMWs) (24–42) at various probability levels. Minimum assured rainfall at 40–50% probability level was found to be in close agreement with the long-term average weekly rainfall data. The minimum assured rainfall of 20 mm and more are expected from SMW27 onwards at 70% probability. This indicated that the sowing of kharif crops has to be done during the SMW 27 for maximum utilization of rain water.

Keywords

Anderson Darling test, Bundelkhand, Crop planning, Maximum likelihood estimation, Probability distribution