EnergySim: an R package Spatial

Abstract

The compilation of resource assessments is standard for regions with known energy or mineral wealth across the country. Resource assessments provide statistical insight into the spatial occurrence and probable accumulation. At the same time, environmental or ecological assessments provide insight into the levels and patterns of natural resources associated with ecosystems in a region. The marriage of resource assessments with social and environmental assessments is a crucial step toward understanding the trade-offs in extracting a given resource. The ability to integrate these seemingly disparate assessments and to quantify the potential trade-offs or impacts of resource development are of broad interest (Bernknopf et al. (2014) and Haines et al. (2014)). A fundamental challenge to this type of integrated resource assessment lies in reconciling the uncertainty associated with resource assessments while quantifying the environmental impacts when the specific footprint of development is unknown. The framework proposed by Haines et al. (2014) addresses this challenge. The conceptual framework relies on Monte-Carlo simulation to assess the potential impacts of resource development by using energy or mineral assessments and quantified relationships between development and observed changes in environmental or social measures. This R package is the first attempt to implement this conceptual framework. energySim implements a link between subsurface resources represented by and resources found at the land surface. While the Powell Center Working Group addressed both energy and mineral assessments (Haines et al. 2014), this package focuses only on the USGS Continuous Petroleum Assessments. A pre-defined set of quantifiable relationships (such as land conversion and soil loss) are provided, but the package is structured to accommodate any user defined relationship. The user defined relationships should be implemented for a single Monte Carlo iteration within a single callable function. User designed functional relationships should be built as a set, where one function prepares inputs (i.e. puts them in the proper format for use in other functions) and a separate function calculates the functional relationship. Consult the source code and consider the combined functionality of the prepareRusle and rusle functions for guidance on how to create your own functions.