Preprints
https://doi.org/10.5194/gmd-2020-338
https://doi.org/10.5194/gmd-2020-338

Submitted as: development and technical paper 01 Dec 2020

Submitted as: development and technical paper | 01 Dec 2020

Review status: a revised version of this preprint is currently under review for the journal GMD.

Modeling Land Use and Land Cover Change: Using a Hindcast to Estimate Economic Parameters in gcamland v2.0

Katherine V. Calvin, Abigail Snyder, Xin Zhao, and Marshall Wise Katherine V. Calvin et al.
  • Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park, MD, 20740, USA

Abstract. The world has experienced a vast increase in agricultural production since the middle of the last century. Agricultural land area has also increased at the expense of natural lands over this period, though at a lower rate than production. Future changes in land use and cover have important implications not only for agriculture but for energy, water use, and climate. However, these future changes are driven by a complex combination of uncertain socioeconomic, technological, and other factors. Estimates of future land use and land cover differ significantly across economic models of agricultural production, and efforts to evaluate these economic models over history have been limited. In this study, we use an economic model of land use, gcamland, to systematically explore a large set of model parameter perturbations and alternate methods for forming expectations about uncertain crop yields and prices. We run gcamland simulations with these parameter sets over the historical period in the United States to explore model fitness and to identify combinations that improve fitness. We find that an adaptive expectation approach minimizes the error between simulated outputs and observations, with parameters that suggest that for most crops landowners put a significant weight on previous information. Interestingly, for corn, where ethanol policies have led to a rapid growth in demand, the resulting parameters show that a larger weight is placed on more recent information. We conclude with the observation that historical modeling exercises such as this study are valuable both for understanding real world drivers of land use change and for informing modeling of future land use change.

Katherine V. Calvin et al.

 
Status: final response (author comments only)
Status: final response (author comments only)
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Katherine V. Calvin et al.

Katherine V. Calvin et al.

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Short summary
Land use and land cover (LULCC) has changed historically and is expected to change in the future. These changes are driven by a complex combination of factors. In this paper, we use an economic model of LULCC to systematically explore a large set of model parameter perturbations and alternate methods for forming expectations about uncertain crop yields and prices. We identify combinations that best replicate historical LULCC in the United States.