Abstract
Since maize, peanut, and cotton are economically valuable crops in the southeast United States, their yield amount changes in a future climate are attention-grabbing statistics demanded by associated stakeholders and policymakers. The Crop System Modeling—Decision Support System for Agrotechnology Transfer (CSM-DSSAT) models of maize, peanut, and cotton are, respectively, driven by the North American Regional Climate Change Assessment Program (NARCCAP) Phase II regional climate models to estimate current (1971–2000) and future (2041–2070) crop yield amounts. In particular, the future weather/climate data are based on the Special Report on Emission Scenarios (SRES) A2 emissions scenario. The NARCCAP realizations show on average that there will be large temperature increases (~2.7 °C) and minor rainfall decreases (~−0.10 mm/day) with pattern shifts in the southeast United States. With these future climate projections, the overall future crop yield amounts appear to be reduced under rainfed conditions. A better estimate of future crop yield amounts might be achievable by utilizing the so-called weighted ensemble method. It is proposed that the reduced crop yield amounts in the future could be mitigated by altering the currently adopted local planting dates without any irrigation support.
Highlights
In order to assess the impacts of weather/climate on agricultural production in the southeastUnited States, the North American Regional Climate Change Assessment Program (NARCCAP) PhaseI multi-model regional climate models were employed as a driver in the state-of-art Crop SystemModeling—Decision Support System for Agrotechnology Transfer (CSM-DSSAT) crop models to estimate three crop yields for the period of 1981–2003 in our previous study [1]
The main objectives of this paper are (a) to project the potential effects of climate change on crops cultivated in the southeast United States, (b) to achieve a more reliable crop yield projection compared to the commonly-used regular ensemble mean projection, and (c) to explore the suitability of adaptation planning to cope with the projected effects of climate change
This area corresponds to the Coastal Plain in Georgia, where soils are not very fertile because of their high content of sand and highly meteorized clay minerals, as well as for their poor drainage conditions
Summary
In order to assess the impacts of weather/climate on agricultural production in the southeastUnited States, the North American Regional Climate Change Assessment Program (NARCCAP) PhaseI multi-model regional climate models were employed as a driver in the state-of-art Crop SystemModeling—Decision Support System for Agrotechnology Transfer (CSM-DSSAT) crop models to estimate three crop (maize, peanut, and cotton) yields for the period of 1981–2003 in our previous study [1]. In order to assess the impacts of weather/climate on agricultural production in the southeast. United States, the North American Regional Climate Change Assessment Program (NARCCAP) Phase. I multi-model regional climate models were employed as a driver in the state-of-art Crop System. Modeling—Decision Support System for Agrotechnology Transfer (CSM-DSSAT) crop models to estimate three crop (maize, peanut, and cotton) yields for the period of 1981–2003 in our previous study [1]. It was shown that downscaling is an inevitable step before using any coarse-scale climate model forecasts in dynamical crop models and crop yield amount estimations could be improved by using weighted multi-model ensemble methods. The authors are mainly considering in the current study how climate change is expected to affect agriculture in the southeast United States. The estimated total value of cotton, maize, and peanut for Alabama, Georgia, and Florida in 2019 was $2.55 billion
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