Stochastic Modeling of Water Deficit for Crop Planning » książka
Stochastic Modeling of Water Deficit for Crop Planning
ISBN-13: 9783659507656 / Angielski / Miękka / 2014 / 112 str.
The main objective of the study is to develop Stochastic model of water deficit for crop planning of Jabalpur. The weekly climatic data of rainfall, air temperature, relative humidity, wind speed and bright sunshine hours were collected for the period of 30 years (1981-2010) and soil data were also obtained.With the help of meteorological data, weekly water deficit and surplus were calculated. The Turning point test and Kendall's rank correlation test were applied for detecting the trend and Correlogram technique was used to detect the periodicity in water deficit, which was then analyzed by Fourier series method. Significant harmonics were also identified in series of water deficit. After knowing that weekly water deficit series are trend free, a mathematical model was describing the periodic- stochastic behavior of the series Statistical properties of generated water deficit series for model were compared with the observed series for tecting the accuracy of model. The developed model is validated by predicting the next two year and compared with the observed water deficit series. The results indicated high degree of model fitness, which may be used for representing time based st
The main objective of the study is to develop Stochastic model of water deficit for crop planning of Jabalpur. The weekly climatic data of rainfall, air temperature, relative humidity, wind speed and bright sunshine hours were collected for the period of 30 years (1981-2010) and soil data were also obtained.With the help of meteorological data, weekly water deficit and surplus were calculated. The Turning point test and Kendalls rank correlation test were applied for detecting the trend and Correlogram technique was used to detect the periodicity in water deficit, which was then analyzed by Fourier series method. Significant harmonics were also identified in series of water deficit. After knowing that weekly water deficit series are trend free, a mathematical model was describing the periodic- stochastic behavior of the series Statistical properties of generated water deficit series for model were compared with the observed series for tecting the accuracy of model. The developed model is validated by predicting the next two year and compared with the observed water deficit series. The results indicated high degree of model fitness, which may be used for representing time based st
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