Y. Parvizi and M. Gorji and M.H. Mahdian and M. Omid
Sensitivity Analysis for Determining Priority of Factors Controlling SOC Content in Semiarid Condition of West of Iran
604 - 608
2010
4
11
International Journal of Environmental and Ecological Engineering
https://publications.waset.org/pdf/2273
https://publications.waset.org/vol/47
World Academy of Science, Engineering and Technology
Soil organic carbon (SOC) plays a key role in soil
fertility, hydrology, contaminants control and acts as a sink or source
of terrestrial carbon content that can affect the concentration of
atmospheric CO2. SOC supports the sustainability and quality of
ecosystems, especially in semiarid region. This study was
conducted to determine relative importance of 13 different
exploratory climatic, soil and geometric factors on the SOC contents
in one of the semiarid watershed zones in Iran. Two methods
canonical discriminate analysis (CDA) and feedforward back
propagation neural networks were used to predict SOC. Stepwise
regression and sensitivity analysis were performed to identify
relative importance of exploratory variables. Results from sensitivity
analysis showed that 721 neural networks and 5 inputs in CDA
models output have highest predictive ability that explains 70 and
65 of SOC variability. Since neural network models outperformed
CDA model, it should be preferred for estimating SOC.
Open Science Index 47, 2010