Stochastic modelling of water deficit

Authors

  • B. S. DEORA S.D. Agril. University, S.K. Nagar, Gujarat -385 506
  • R. V. SINGH College of Tech. and Engineering, MPUAT, Udaipur-313 001

DOI:

https://doi.org/10.54386/jam.v11i1.1217

Keywords:

Stochastic, water deficit, time series, periodic

Abstract

A stochastic model for weekly water deficit series, using 28 years climatological data, under climatic condition of S.K. Nagar has been developed. The turning point test and Kendall’s rank correlation test are applied for detecting the trend. Correlogram technique is used to detect the periodicity, which is then analyzed by Fourier series method. Significant harmonics were also identified. The statistical properties of the generated water deficit series were compared with observed series. The developed model was validated by predicting two years ahead and compared with the observed water deficit series, The test results indicated the high degree of model fitness. The developed model may be used for representing the time-based structure of the water deficit time series. 

Downloads

Published

01-06-2009

How to Cite

B. S. DEORA, & R. V. SINGH. (2009). Stochastic modelling of water deficit. Journal of Agrometeorology, 11(1), 19–28. https://doi.org/10.54386/jam.v11i1.1217

Issue

Vol. 11 No. 1 (2009): June

Section

Research Paper

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

This is a human-readable summary of (and not a substitute for) the license. Disclaimer.

You are free to:

Share — copy and redistribute the material in any medium or format

Adapt — remix, transform, and build upon the material

The licensor cannot revoke these freedoms as long as you follow the license terms.

    Under the following terms:

    Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.

    NonCommercial — You may not use the material for commercial purposes.

    ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.

    No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

    Notices:

    You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation.

    No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.