Initial Evaluation of Seasonal Yield and Irrigation Demand Forecasting Frameworks for Oklahoma

Abstract

Climate variability plays a large role in agriculture. Having the proper tools to investigate the effects of climate variability in agriculture is necessary to better understand our future. Wheat, corn, and cotton are three crops important in Oklahoma. These crops can all be effected by climate variability. One method of understanding the problem is through crop modeling frameworks. The objective of this thesis is to investigate the utility of modeling frameworks in Oklahoma. The studied was carried out by using the Decision Support System for Agrotechnology Transfer - Cropping System Model (DSSAT-CSM) framework. The crops focused on are wheat, corn, and cotton. The weather data, soil data, and model configurations were tested to find out how they performed. Chapter 2 covers a wheat yield forecasting study, and chapter 3 covers irrigation demand forecasting. Overall, the models supply an understanding of how modeling frameworks are relative to Oklahoma, and can be used. The limitations to the models are input data, initial conditions, and management practices. There is still a lot of room for improvement in the models discussed in this thesis such as calibrating cultivars to the study area, but it does provide a basis for future research.