An environmental sustainability index for agricultural systems

An index for quantifying environmental sustainability (ESI) for U.S. High Plains agricultural systems was developed and evaluated. A performance-based approach was adopted for the ESI, employing the EPIC (Erosion Productivity Impact Calculator) model for simulation of long-term environmental impacts associated with agricultural systems. Fifteen indicators of environmental sustainability were selected to represent a two-pronged framework for characterizing environmental sustainability. This framework is based on an agricultural system's: (1) impact on sustaining soil and water resources, including inherent soil productivity and groundwater availability and (2) potential to degrade the off-site environment through leaching and runoff of nutrients, pesticides and sediment. Based on this framework, two axioms were developed to establish a sustainability datum from which environmental sustainability of agriculture systems can be gauged.;Performance of the ESI was evaluated utilizing case study analysis. Sixteen case study scenarios were developed based on prevalent corn and wheat agricultural production systems in Baca County, located in southeastern Colorado. The 16 scenarios comprise four crop management systems and four predominant soil types for the study area. The crop management systems included both irrigated and dryland systems as well as continuous-crop and rotational systems. Principal components analysis was employed to assess the information content of the 15 sustainability indicators and the overall performance of the ESI. Uniformly-weighted multiplicative and additive aggregations of the 15 sustainability indicators also were evaluated. Principal components analysis was repeated for the 16 case study scenarios for time frames of 50, 100, 200, and 300 years to evaluate the effect of temporal scale on the performance of the index. Sensitivity analysis was performed to assess the impacts of uncertainty on the ESI. For the portfolio of case study scenarios, the ESI was found to be very responsive to variations in crop management system, slightly less responsive to variations in soil type, and relatively insensitive to variations in input parameters. The ESI clearly distinguished the rotational crop management systems with a higher level of sustainability as compared to the continuously cropped systems.