Integrating socio‐economic and biophysical assessments using a land use allocation model. (30th December 2012)

• Record Type: Journal Article
• Authors: Du, Y.; Huffman, T.; Toure, S.; Feng, F.; Gameda, S.; Green, M.; Liu, T.; Shi, X.
• Is Part Of: Soil use and management. Volume 29:Number 1(2013:Mar.)
• Page Start: 140
• Page End: 149
• Publication Date: 2012-12-30
• Subjects: Agricultural land use -- agricultural policy model -- soil biophysical model -- land use allocation -- optimization; Soil management -- Periodicals; 631.4
• DOI: 10.1111/sum.12018
• Languages: English
• ISSNs: 0266-0032

Abstract

Abstract: This work is devoted to bridging the gap between large‐area, economically driven macromodels such as the Canadian Regional Agriculture Model (CRAM) and small‐area biophysically based process models used in environmental assessments through the development of a Land Use Allocation Model (LUAM). LUAM is designed to enable environmental assessments of economic scenarios to be conducted by allocating crop area changes predicted for large areas by CRAM to much smaller Soil Landscapes of Canada (SLC) polygons through an optimization method based on land capability, relative crop productivity and current land use. To develop the procedures, we used linear programming to optimize crop production for large areas under current commodity prices and land productivity ratings and then allocated the results to much smaller soil‐landscape polygons based on land capability. To assess the validity of our prototype LUAM, we compared the predicted crop areas with actual crop data from the Census of Agriculture using the method of cumulative residuals (MCR). We concluded that this version of the LUAM model can predict the location of land use to some extent, but requires further refinement. The potential for further development of LUAM using the Land Suitability Rating System (LSRS) is discussed.