102551 Potential Impact of Climate Change on Crop Yield of Major Crops in Northern High Plains of Texas.

Poster Number 455-816

See more from this Division: ASA Section: Climatology and Modeling
See more from this Session: Honoring the Contributions of Laj Ahuja: Building Bridges Among Disciplines By Synthesizing and Quantifying Soil and Plant Processes for Whole Systems Modeling Poster

Wednesday, November 9, 2016
Phoenix Convention Center North, Exhibit Hall CDE

Ripendra Awal, Ali Fares, Ram Ray, Alton B. Johnson and Eric Risch, College of Agriculture and Human Sciences, Prairie View A&M University, Prairie View, TX
Abstract:
Agricultural practices are climate dependent and variation in crop yield from year to year is related to growing-season weather effects. Thus, the study on potential impact of climate change and increasing climate extremes on agriculture is essential for the sustainability of agricultural systems and for policy making purposes. The main objectives of this study were to (i) analyze the potential impact of climate change on crop yields of major crops and (ii) evaluate different adaptation measures to minimize climate change impact on crop yields in Northern High Plains of Texas. The statistical downscaling model was used to generate projected daily climate data at each grid of the study area. The climate data for three future periods, i.e. 2020s, 2055s and 2090s, were generated using outputs from selected General Circulation Models (GCMs) under different emission scenarios. Cropping system model which incorporates the effect of environmental variables and management practices, e.g. DSSAT, was used to model crop yield in the current and future projection periods. Cropping system model was also used to evaluate different adaptation measures (e.g. shifts in sowing date, change in application rate of irrigation water, increased fertilizer application etc.).

See more from this Division: ASA Section: Climatology and Modeling
See more from this Session: Honoring the Contributions of Laj Ahuja: Building Bridges Among Disciplines By Synthesizing and Quantifying Soil and Plant Processes for Whole Systems Modeling Poster