Crop Climate Simulation Modelling

M. Sayedur Rahman

ISBN 10: 3848496224 / ISBN 13: 9783848496228

Published by LAP LAMBERT Academic Publishing Mär 2012, 2012

About this Item

This item is printed on demand - Print on Demand Titel. Neuware -A stochastic model based on first-order Markov chain was developed to simulate daily rainfall. The model is capable of simulating daily rainfall data of any length, based on the estimated transitional probabilities, mean, standard deviation and skew coefficients of rainfall amounts. A study of rainfall probability is an approach to sound planning for any variation of rainfall either small or large. The simulation model has been used successfully to estimate daily rainfall. The Multivariate logistic regression is used to estimate the probability that it is raining. The logistic regression technique is used to compare between the actual and simulation results for a rainfall from January to December in Bangladesh. The probability of occurrence of rainfall is of vital importance in efficient planning and execution of water use program. This study describes a crop-climate simulation model under rainfed conditions in Bangladesh to be used as a tool for analyzing growth and yield to help planning and management of rice production.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 220 pp. Englisch.

Seller Inventory # 9783848496228

Bibliographic Details

• Title: Crop Climate Simulation Modelling
• Publisher: LAP LAMBERT Academic Publishing Mär 2012
• Publication Date: 2012
• Language: English
• ISBN 10: 3848496224
• ISBN 13: 9783848496228
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 14D millimeters 220 millimeters width by 150 millimeters height by 14 millimeters depth
• Weight: 346 grams

About this title

Synopsis

A stochastic model based on first-order Markov chain was developed to simulate daily rainfall. The model is capable of simulating daily rainfall data of any length, based on the estimated transitional probabilities, mean, standard deviation and skew coefficients of rainfall amounts. A study of rainfall probability is an approach to sound planning for any variation of rainfall either small or large. The simulation model has been used successfully to estimate daily rainfall. The Multivariate logistic regression is used to estimate the probability that it is raining. The logistic regression technique is used to compare between the actual and simulation results for a rainfall from January to December in Bangladesh. The probability of occurrence of rainfall is of vital importance in efficient planning and execution of water use program. This study describes a crop-climate simulation model under rainfed conditions in Bangladesh to be used as a tool for analyzing growth and yield to help planning and management of rice production.

About the Author

M. Sayedur Rahman received M.Sc., M. Phil and Ph.D. degree in Statistics. He was joined as a lecturer in 1988, University of Rajshahi, and subsequently he promoted as Professor in 2003. He is involved in many national and international scientific projects & research groups. He has also authored and co-authored more than 50 scientific papers.