Comparing and combining process-based crop models and statistical models with some implications for climate change
Bibliographic Data
| ID | 15545848 |
|---|---|
| Authors | Michael J Roberts (0000-0003-0552-7402, University of Hawaiʻi at Mānoa, corresponding author), Noah Braun (0000-0002-9710-0686, California Institute of Technology), Thomas R Sinclair (0000-0003-4481-7197, North Carolina State University), David B Lobell (0000-0002-5969-3476, Stanford University), Wolfram Schlenker (0000-0002-6231-9944, Earth Island Institute) |
| Year | 2017 |
| Volume | 12 |
| Issue | 9 |
| Pages | 095010-095010 |
| Publication date | 2017-09-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Environmental Research Letters (JOURNAL) |
| Journal identifiers | ISSN: 1748-9326 • E-ISSN: 1748-9326 |
| Publisher | IOP Publishing (PUBLISHER • GB) |
| DOI | 10.1088/1748-9326/aa7f33 |
| OpenAlex | W2759257303 |
| Language | EN |
| Citations received | 17 |
| References cited | 1 |
We compare predictions of a simple process-based crop model (Soltani and Sinclair 2012), a simple statistical model (Schlenker and Roberts 2009), and a combination of both models to actual maize yields on a large, representative sample of farmer-managed fields in the Corn Belt region of the United States. After statistical post-model calibration, the process model (Simple Simulation Model, or SSM) predicts actual outcomes slightly better than the statistical model, but the combined model performs significantly better than either model. The SSM, statistical model and combined model all show similar relationships with precipitation, while the SSM better accounts for temporal patterns of precipitation, vapor pressure deficit and solar radiation. The statistical and combined models show a more negative impact associated with extreme heat for which the process model does not account. Due to the extreme heat effect, predicted impacts under uniform climate change scenarios are considerably more severe for the statistical and combined models than for the process-based model
Calibration · Climate change · Climate model · Econometrics · Geography · Meteorology · Precipitation · Process (computing · Statistical model · Statistics · Agricultural risk and resilience · Climate change impacts on agriculture · Computer Science · Environmental Science · Mathematics · Rice Cultivation and Yield Improvement · Ecology
Climate change, income sources, crop mix, and input use decisions
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DeepCropNet
| Unique citing works | 17 |
|---|---|
| Citations per year | 1,89 |
| Citation span | 2017 - 2024 (8) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 17 |