Chance Constrained Programming Models for Risk-Based Economic and Policy Analysis of Soil Conservation

The random nature of soil loss under alternative land-use practices should be an important consideration of soil conservation planning and analysis under risk. Chance constrained programming models can provide information on the trade-offs among pre-deterrnined tolerance levels of soil loss, probability levels of satisfying the tolerance levels, and economic profits or losses resulting from soil conservation to soil conservation policy makers. When using chance constrained programming models, the distribution of factors being constrained must be evaluated. If random variables follow a log-normal distribution, the normality assumption, which is generally used in the chance constrained programming models, can bias the results. Many economic and policy analyses of soil con-servation [Wade and Heady; Walker and Tim-mons; Kramer, McSweeny, and Stavros] as well as soil conservation planning have been conducted based on the long-run average soil loss through employing the University Soil Loss Equatio