EconPapers    
Economics at your fingertips  
 

Identification of important factors for water vapor flux and CO2 exchange in a cropland

Zhong Qin, Gao-li Su, Jia-en Zhang, Ying Ouyang, Qiang Yu and Jun Li

Ecological Modelling, 2010, vol. 221, issue 4, 575-581

Abstract: Water vapor flux and carbon dioxide (CO2) exchange in croplands are crucial to water and carbon cycle research as well as to global warming evaluation. In this study, a standard three-layer feed-forward back propagation neural network technique associated with the Bayesian technique of automatic relevance determination (ARD) was employed to investigate water vapor and CO2 exchange between the canopy of summer maize and atmosphere in responses to variations of environmental and physiological factors. These factors, namely the photosynthetically active radiation (PAR), air temperature (T), vapor pressure deficient (VPD), leaf-area index (LAI), soil water content in root zone (W), and friction velocity (U*), were used as inputs in neural network analysis. Results showed that PAR, VPD, T and LAI were the primary factors regulating both water vapor and CO2 fluxes with VPD and W more critical to water vapor flux and PAR and T more crucial to CO2 exchange. Furthermore, two time variables “day of the year (DOY)” and “time of the day (TOD)” could also improve the simulation results of neural network analysis. The important factors identified by the neural network technique used in this study were in the order of PAR>T>VPD>LAI>U*>TOD for water vapor flux and in the order of VPD>W>LAI>T>PAR>DOY for CO2 exchange. This study suggests that neural network technique associated with ARD could be a useful tool for identifying important factors regulating water vapor and CO2 fluxes in terrestrial ecosystem.

Keywords: Artificial neural network; Water vapor and CO2 flux; Cropland; Automatic relevance determination (search for similar items in EconPapers)
Date: 2010
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304380009007534
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:221:y:2010:i:4:p:575-581

DOI: 10.1016/j.ecolmodel.2009.11.007

Access Statistics for this article

Ecological Modelling is currently edited by Brian D. Fath

More articles in Ecological Modelling from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:ecomod:v:221:y:2010:i:4:p:575-581