Environmental Engineering Reference
In-Depth Information
Chapter 5
A Generic Farming System Simulator
Kamel Louhichi, Sander Janssen, Argyris Kanellopoulos, Hongtao Li,
Nina Borkowski, Guillermo Flichman, Huib Hengsdijk, Peter Zander,
Maria Blanco Fonseca, Grete Stokstad, Ioannis N. Athanasiadis,
Andrea E. Rizzoli, David Huber, Thomas Heckelei, and Martin van Ittersum
Introduction
The prime decision making unit in agriculture is the farm. It is the unit where agro-
ecological innovations start and where agricultural and agri-environmental policies
trigger changes in land use, production and externalities (e.g. nitrate leaching, soil
erosion and pesticide use). The European Union (27 member states) counts ca. 15
million farms with a wide variation in endowments, specialisation and land use
(Eurostat
2007)
. As a consequence of these differences and the diversity in entre-
preneurship and personal or household aims, responses to a specific policy or
innovation may differ across the farming community. This seriously complicates
the devise and selection of effective and efficient policies, i.e. what may be an
effective (realizing the desired effect with respect to for instance the environment)
and efficient (realizing a desired effect at low cost for a farm or community) for one
type of farms may not be so for another type.
Evaluation of present policies can be done based on empirical data, for instance
using systematic data collected for a sample of farms throughout a region, nation
or continent. The Farm Accountancy Data Network (FADN) provides such a source of
information for the European Union. This is indeed useful to evaluate effectiveness
of policies in terms of some indicators, particularly economic ones. However, such
sources generally lack information on agricultural management and environmental
issues. Moreover, these two data gaps are interrelated: the lack of agricultural
management makes the application of for instance crop simulation models to assess
environmental issues largely impossible. Hence, only FADN data complemented
with detailed surveys and measurements enable the full ex-post evaluation of policy
measures. For
ex-ante
assessment of policies, i.e. assessment of policies before
their introduction, there is little empirical basis. Here, mathematical modelling can
