Changes in Discharge in an Agricultural Watershed in Iowa: Modeling and Projections

Our improved capability to adapt to future changes in discharge is unavoidably linked to our capability to predict the magnitude or at least the direction of these changes. The importance of improving discharge projections is particularly relevant in an agricultural state like Iowa. Iowa has been affected by a sequence of extreme events over the most recent years, with the flood events of 1993, 2008, 2010, 2013 and 2014 interrupted by the droughts of 2012 and summer 2013. It is clear that too much or too little water will have severe economic and societal impacts for this state, and the agricultural U.S. Midwest more generally. Therefore, being able to increase our confidence in the direction and magnitude of the projected changes in discharge (from low to high flow) will be of key importance for improving our mitigation and management strategies during both flooding and droughts.

Here we focus on the Raccoon River at Van Meter, Iowa, and use a statistical approach to examine projected changes in discharge. We build on statistical models using rainfall and harvested corn and soybean acreage to explain the observed stream flow variability. We then use projections of these two predictors to examine the projected discharge response. Results are based on seven state-of-the-art global climate models (GCMs) produced under the Fifth Coupled Model Intercomparison Project (CMIP5), and two representative concentration pathways (RCPs 4.5 and 8.5). We find that there is not a strong signal of change in the discharge projections under the RCP 4.5. On the other hand, the results for the RCP 8.5 point to a stronger changing signal, in particular increasing trends in the upper part of the discharge distribution. Examination of two hypothetical agricultural scenarios indicates that these increasing trends could be potentially offset by decreasing the extent of the agricultural production. Finally, we discuss how to move forward with the concept of return period for engineering design and management in a non-stationary world.