Simulating regional grain yield distributions to support agricultural drought risk assessment |
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| Institution: | 1. Department of Radiology, The Permanente Medical Group, Kaiser Permanente Medical Center, Santa Clara, 700 Lawrence Expy, Santa Clara, CA 95051, United States;2. Department of Radiology and Biomedical Imaging, University of California, San Francisco, 505 Parnassus Ave, L371, San Francisco, CA 94143, United States;3. Division of Neurointerventional Radiology, Department of Radiology and Biomedical Imaging, University of California, San Francisco, 505 Parnassus Ave, L351, San Francisco, CA 94143, United States;4. Department of Neurology, University of California, San Francisco, 505 Parnassus Ave, L371, San Francisco, CA 94143, United States;1. Department of Statistics, University of Virginia, Charlottesville, VA 22904, USA;2. Department of Statistical Science, Duke University, Durham, NC 27708, USA;3. Department of Psychology, University of Virginia, Charlottesville, VA 22904, USA |
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| Abstract: | Most food insecure countries do not have long-term records of either agricultural drought or the impacts of agricultural drought on food security. This lack of data impedes famine early warning and crop insurance programs. One recent paper addresses this issue by using resampled rainfall data, a basic crop yield model, and linear regression to simulate distributions of grain yield. We expand on this process by incorporating flexible regression models and defining a set of criteria to test model performance. We also examine how well a model fit on national data can emulate yield distributions at regions within a country. We find that models with spatially varying coefficients are better able to simulate distributions than basic linear regression models. Generalized additive models also perform well but do not offer substantial improvement over varying coefficient models. We also find that simulated yield distributions are most accurate in higher producing regions that have lower within region diversity of yields. |
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| Keywords: | Food security Agricultural drought Simulating distributions |
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