Projected Changes in Discharge in an Agricultural Watershed in Iowa |
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| Authors: | Gabriele Villarini Enrico Scoccimarro Kathleen D White Jeffrey R Arnold Keith E Schilling Joyee Ghosh |
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| Affiliation: | 1. IIHR‐Hydroscience & Engineering, The University of Iowa, 306 C. Maxwell Stanley Hydraulics Laboratory, Iowa City, Iowa;2. National Institute of Geophysics and Volcanology, Bologna, Italy;3. Euro‐mediterranean Center on Climate Change, Lecce, Italy;4. Institute for Water Resources, U.S. Army Corps of Engineers, Alexandria, Virginia;5. Iowa Geological Survey, The University of Iowa, 306 C. Maxwell Stanley Hydraulics Laboratory, Iowa City, Iowa;6. Department of Statistics and Actuarial Science, The University of Iowa, 306 C. Maxwell Stanley Hydraulics Laboratory, Iowa City, Iowa |
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| Abstract: | Our improved capability to adapt to the future changes in discharge is linked to our capability to predict the magnitude or at least the direction of these changes. For the agricultural United States Midwest, too much or too little water has severe socioeconomic impacts. 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 discharge variability. We then use projections of these two predictors to examine the projected discharge response. Results are based on seven global climate models part of the Coupled Model Intercomparison Project Phase 5 and two representative concentration pathways (RCPs 4.5 and 8.5). There is not a strong signal of change in the discharge projections under the RCP 4.5. However, the results for the RCP 8.5 point to a stronger changing signal related to larger projected increases in rainfall, resulting in increased trends, in particular, in the upper part of the discharge distribution (i.e., 60th percentile and above). Examination of two hypothetical agricultural scenarios indicates that these increasing trends could be alleviated by decreasing the extent of the agricultural production. We also discuss how the methodology presented in this study represents a viable approach to move forward with the concept of return period for engineering design and management in a nonstationary world. |
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| Keywords: | climate variability/change rivers/streams/flooding precipitation streamflow time series analysis |
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