A NEW APPROACH FOR PREDICTING FARMERS ADAPTIVE BEHAVIOR AT THE LARGE WATERSHED SCALE: IMPLICATIONS FOR WATER QUALITY UNDER CLIMATE CHANGE

The predicted changes in the climatic patterns (higher temperatures, changes in extreme precipitation events, and higher levels of humidity) will affect agricultural activity. The concept of adaption to new conditions either climatic or economic is an important aspect of the agricultural decision-making process (Arbuckle et al., 2013). Adopting cover crops, reduced tillage, extending the drainage systems, adjusting crops management are only a few examples of adaptive actions. When private benefits are present (increased profits, reduced risk), these actions can be easily implemented. However, each adaptive action has a different impact on water quality (i.e. cover crops and no-till have a positive impact on water quality, while tile drainage has a negative one).

The goal of this research is to determine the changes in water quality under different climate scenarios when farmers undertake these adaptive measures. To answer this research question, we estimate the likelihood that these actions will occur, identify the agricultural areas where these actions are most likely to be implemented, thus creating possible scenarios, and simulate water quality associated with each of these scenarios under different climate scenarios. We apply our modeling efforts to the whole Upper-Mississippi River Basin Basin (UMRB) and the Ohio-Tennessee River Basin (OTRB); critical areas in achieving the goals set by the Gulf of Mexico Dead Zone Task Force (Rabotyagov et al., 2014).

The likelihood of each adaptive agricultural action is estimated using data from a survey conducted in 2012. The survey used a large, representative sample of farmers in the Corn Belt to elicit behavioral intentions regarding different agricultural adaptation strategies (no-till, cover crops, tile drainage). We use these data to study the relationship between intent to adapt, farmer characteristics, farm characteristics, and weather characteristics to predict the probability of adoption for each action. Next, we use these estimated probabilities to create different large scenarios for the two large scale-watersheds. Finally, we simulate the impact of these scenarios on water quality using water quality models (Soil and Water Assessment Tool) calibrated for UMRB-OTRB areas (Panagopoulos et al., 2014) under different climate scenarios.