Farming Systems Design 2007 - International Environmental ...

Farming Systems Design 2007
Field-farm scale design and improvement
INTEGRATED ASSESSMENT OF AGRICULTURAL SYSTEMS:
A CHALLENGE OF SYSTEM AND MODEL COMPLEXITY
J.J Stoorvogel 1 , J. Antle 2
1 Landscape Centre, Wageningen University, The Netherlands, jetse.stoorvogel@wur.nl
2
Dep. of Ag. Econ. and Econ., Montana State University, USA, jantle@montana.edu
Introduction
There is an increasing demand for the integrated assessment of complex agricultural systems.
Integrated modeling approaches are a common tool to deal with this type of analysis. However,
despite the fact that simulation models are simplifications of reality, we see that these models
become increasingly complicated. Additional processes are included to make the models generic
and to describe properly the observed variation in these agricultural systems. The complexity of
these models coincides with an increase in data requirements. As a result of the almost unrealistic
data requirements, many applications are unable to collect the input data. Several approaches are
being used to deal with the data requirements. Many studies use default model values for data that
were not available and/or difficult to measure. In other studies transfer functions are used to
estimate e.g., complex hydrological properties on the basis of soil texture and organic matter
contents. In the case of significant spatial variation, studies use a limited number of representative
locations (e.g. representative weather stations, representative soil profiles, or farm types). The
question that remains is whether we should search for simplifications or whether we should look for
more simple models that are capable to run the key processes using mostly available data?
In this study, we looked at the Tradeoff Analysis Model and its application to the potato-pasturewheat
system in the Peruvian Andes (Antle et al., 2007). Crop growth simulation models,
econometric simulation models, and mechanistic erosion models are integrated through the
Tradeoff Analysis Modeling system (Stoorvogel et al., 2004) to properly describe this complex
system. The advantage of the integrated modeling approach is that we can evaluate a wide range
of alternative scenarios ranging from climate change, terrace adoption, to economic policies. The
key question that remains is whether we need such a complex modeling system if we are
interested in a specific policy or research question. To illustrate this we will look at the specific
issue on the adoption of terraces.
Methodology
The study focuses on the semi-arid La Encañada watershed in the Cajamarca region in northern
Peru. The 10km 2 watershed ranges between 2,950 to 4,000 meters above sea level and is located
between 7°00' and 7°07' southern latitude and betwe en 78°15' and 78°22' western longitude.
Average annual rainfall is low ranging between 430 mm/year in the valleys up to 550 mm/year in
the higher parts of the watershed. The data used in this analysis were collected through farm
surveys conducted in 1997-1999 for a random stratified sample of 40 farm households in five
communities in the watershed. The data show that crop yields are low and parcel size is small, as
is typical of this type of semi-subsistence agriculture. The analysis reported here is based on the
lower-hillside region where cropland is the principal land use. In the last decades a large number of
fields were terraced to reduce soil erosion and maintain soil fertility. The Tradeoff Analysis Model
simulates land allocation and management decisions of a population of farmers in a site-specific
manner. First, the expected productivity for potato and pasture for the various fields is simulated
using calibrated crop growth simulation models from the DSSAT suite of models (Jones et al.,
2003). Subsequently, production functions for input demand and output supply are estimated for
the three main cropping systems: potato, wheat, and pasture. The expected productivity for the
different crops is an important driving factor in these production functions. The production functions
can now be used in an econometric simulation model to simulate management decisions under
various scenarios. Land allocation is determined on the basis of profit maximization. After
simulating land use for the population of agricultural fields, farms can be evaluated in terms of soil
erosion by simulating soil erosion for the various fields with the WEPP model (Flanagan and
Nearing, 1995). Various elements of the modeling approach are evaluated in this study. Firstly, a
simple statistical relationships to assess crop production was assessed rather than crop growth
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