|Heilman, Philip - Phil|
Submitted to: Multiobjective Decision Support System Conference
Publication Type: Proceedings
Publication Acceptance Date: 7/14/1996
Publication Date: N/A
Interpretive Summary: A method is described which can estimate how much it costs farmers to cut on the amounts of sediment, fertilizers and pesticides which enter ground or surface water. The first step is to use a computer program called a Decision Support System to rank a number of alternative farm management system based on the objectives of farmers and people living downstream. The esecond step is to estimate how much it would cost farmers to implement the management practice that is selected. The difference between what a farmer is currently earning and what he would earn with the management system which takes into account the objectives of people living downstream is the amount that would need to be paid to the farmer to make him want to adopt the management system voluntarily. An example of a representative farm from the deep loess hills of western Iowa is used to illustrate the method.
Technical Abstract: Multiobjective decision support systems can be a powerful tool to improve natural resource management in agriculture. When the decision is the selection of a land management system from the point of view of all of society, a problem may arise. Some of the objectives will reflect the interests of land managers and others by those affected offsite. An important issue is how to encourage the adoption of improved management systems if they are in society's overall interest, but not in the land manager's interest, as happens with nonpoint source water pollution. Further economic analysis is needed to encourage the adoption of improved management systems, as a complement to multiobjective decision support systems. A farm scale optimization model can be used to estimate the expected cost to a farmer of adopting management systems which will abate the production of agricultural pollutants. An example from the deep loess hills of western Iowa illustrates this approach.