10.6 Case Study 5: The Adoption of Soil Conservation Practices
in Northern Vietnam and Policy Recommendations
10.6.1 Introduction
Previous research has shown that farmers in north-western Vietnam know about
soil erosion and soil conservation, but still do not apply preventive practices (SaintMacary et al. 2010), and without soil conservation measures in place, large amounts
of soil are eroded from sloping land (Schmitter et al. 2010; Valentin et al. 2008;
Wezel et al. 2002).
7 The objective of this study was to simulate the adoption of soil
conservation practices, and to assess the impact of a payment policy for the
application of such practices in the north-west of Vietnam.
10.6.2 Methods
10.6.2.1 Models
This study applied Mathematical Programming-based Multi-Agent Systems (MPMAS), an integrated modeling approach used in order to evaluate the adoption of
soil conservation practices in north-western Vietnam, and to suggest policy options
that would promote sustainable agriculture. Scientists are the target users of the
model, one that integrates farm decisions on investment and production with the
biophysical processes that occur, from soil nutrients to crop yields, as presented in
Fig. 10.16, in which the available nutrient levels are calculated from rainfall, soil
nutrient stock through the decomposition process, and mineral fertilizers, then the
crop yields estimated through yield response functions, as follows:
Agent decisions were simulated using an optimization across two phases of
investment and production, and were based on the availability of land, labor and
capital, as agents’ detailed plans showed the areas of land to be used for specific
crops such as maize, cassava or rice, plus how many animals should be raised and
the quantity of outputs that should be sold or consumed for subsistence. Information
related to cropping decisions, as well as production outputs, was used to estimate
the biophysical data, including crop residuals, nutrient uptake, nutrient balance,
nutrients remaining in the soil and the productivity of crops for the next optimization, and these were applied directly into the Tropical Soil Productivity Calculator
(TSPC) (Fig. 10.16), which was used to calculate available nutrients in the soil, the
rate of soil erosion, crop yields and the biomass residuals for all agents in the next
period. The update cycle for soil nutrient content is also shown in Fig. 10.16.
Initially, the yields, stover, soil erosion and nutrient balance of all the cropping
7 This section was written by Dang Viet Quang, Pepijn Schreinemachers and Thomas Berger.
10 Integrated Modeling of Agricultural Systems in Mountainous Areas
405
in Northern Vietnam and Policy Recommendations
10.6.1 Introduction
Previous research has shown that farmers in north-western Vietnam know about
soil erosion and soil conservation, but still do not apply preventive practices (SaintMacary et al. 2010), and without soil conservation measures in place, large amounts
of soil are eroded from sloping land (Schmitter et al. 2010; Valentin et al. 2008;
Wezel et al. 2002).
7 The objective of this study was to simulate the adoption of soil
conservation practices, and to assess the impact of a payment policy for the
application of such practices in the north-west of Vietnam.
10.6.2 Methods
10.6.2.1 Models
This study applied Mathematical Programming-based Multi-Agent Systems (MPMAS), an integrated modeling approach used in order to evaluate the adoption of
soil conservation practices in north-western Vietnam, and to suggest policy options
that would promote sustainable agriculture. Scientists are the target users of the
model, one that integrates farm decisions on investment and production with the
biophysical processes that occur, from soil nutrients to crop yields, as presented in
Fig. 10.16, in which the available nutrient levels are calculated from rainfall, soil
nutrient stock through the decomposition process, and mineral fertilizers, then the
crop yields estimated through yield response functions, as follows:
Agent decisions were simulated using an optimization across two phases of
investment and production, and were based on the availability of land, labor and
capital, as agents’ detailed plans showed the areas of land to be used for specific
crops such as maize, cassava or rice, plus how many animals should be raised and
the quantity of outputs that should be sold or consumed for subsistence. Information
related to cropping decisions, as well as production outputs, was used to estimate
the biophysical data, including crop residuals, nutrient uptake, nutrient balance,
nutrients remaining in the soil and the productivity of crops for the next optimization, and these were applied directly into the Tropical Soil Productivity Calculator
(TSPC) (Fig. 10.16), which was used to calculate available nutrients in the soil, the
rate of soil erosion, crop yields and the biomass residuals for all agents in the next
period. The update cycle for soil nutrient content is also shown in Fig. 10.16.
Initially, the yields, stover, soil erosion and nutrient balance of all the cropping
7 This section was written by Dang Viet Quang, Pepijn Schreinemachers and Thomas Berger.
10 Integrated Modeling of Agricultural Systems in Mountainous Areas
405