The aim of this study is to expand the family of LOS indices for the assessment of the intrinsic nitrogen (N) transformation rates of mineralization, nitrification, denitrification, and ammonia volatilization in agricultural lands. The new indices are added to the two existing ones, which concern N losses through percolation and runoff, in order to provide an integrated aspect of the N budget components of each region based on its intrinsic properties by excluding external factors (e.g., agricultural practices, different crops). This provides a common basis for the classification of N processes' dynamics, since they are expressed in units connected to intensity classes, allowing comparisons among different regions. Their calibration is based on non-linear regression analysis using as "observed values" the simulation results of the GLEAMS model from a theoretical reference field crop. Their combination is used for the assessment of the total annual intrinsic rate of N losses and the degree of fertilization failure, which are calculated as secondary indices. The indices can be applied in a GIS environment with easily accessible data and allow the designation of site-specific best management practices (BMPs) to diminish N losses. Finally, a case study in Ferrara Province in Italy is presented in order to highlight the potentiality of these indices to describe the intrinsic N budget components of the agricultural ecosystems and to support BMPs.
Formulation of Indices to Describe Intrinsic Nitrogen Transformation Rates for the Implementation of Best Management Practices in Agricultural Lands
ASCHONITIS, Vasileios;SALEMI, Enzo;COLOMBANI, Nicolo';CASTALDELLI, Giuseppe;MASTROCICCO, Micol
2013
Abstract
The aim of this study is to expand the family of LOS indices for the assessment of the intrinsic nitrogen (N) transformation rates of mineralization, nitrification, denitrification, and ammonia volatilization in agricultural lands. The new indices are added to the two existing ones, which concern N losses through percolation and runoff, in order to provide an integrated aspect of the N budget components of each region based on its intrinsic properties by excluding external factors (e.g., agricultural practices, different crops). This provides a common basis for the classification of N processes' dynamics, since they are expressed in units connected to intensity classes, allowing comparisons among different regions. Their calibration is based on non-linear regression analysis using as "observed values" the simulation results of the GLEAMS model from a theoretical reference field crop. Their combination is used for the assessment of the total annual intrinsic rate of N losses and the degree of fertilization failure, which are calculated as secondary indices. The indices can be applied in a GIS environment with easily accessible data and allow the designation of site-specific best management practices (BMPs) to diminish N losses. Finally, a case study in Ferrara Province in Italy is presented in order to highlight the potentiality of these indices to describe the intrinsic N budget components of the agricultural ecosystems and to support BMPs.I documenti in SFERA sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
