Projection of future drought and extreme events occurrence in Goodwater Creek Experimental Watershed, Midwestern US

Authors: GAUTAM, SAGAR - Argonne National Laboratory; COSTELLO, CHRISTINE - Pennsylvania State University; Baffaut, Claire; THOMPSON, ALLEN - University Of Missouri; SADLER, EDWARD - Retired ARS Employee

Submitted to: Hydrological Sciences Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/23/2021
Publication Date: 6/21/2021
Citation: Gautam, S., Costello, C., Baffaut, C., Thompson, A., Sadler, E.J. 2021. Projection of future drought and extreme events occurrence in Goodwater Creek Experimental Watershed, Midwestern US. Hydrological Sciences Journal. 66(6):1045-1058. https://doi.org/10.1080/02626667.2021.1906878.
DOI: https://doi.org/10.1080/02626667.2021.1906878

Interpretive Summary: Expected future changes in precipitation (P) and temperature (T) will have impacts on the frequency of droughts and extreme events, and predicting these impacts is essential for managing natural resources in agricultural regions. Earlier studies defined dry or wet periods based on P and T. However, P and T do not fully reflect the effects of excessive P and T, and streamflow and soil moisture may be more relevant to agriculture. This study compared future (2016-2075) and historic (1980-2015) dry and wet periods based on P, T, stream flow, and soil moisture, and extreme P and T events. The comparison was based on future P and T projections for two emission scenarios and a computer model that uses these P and T projections to simulate streamflow and soil moisture for the Goodwater Creek Experimental Watershed, a Northeast Missouri agricultural watershed. The results indicated both a decline in summer precipitation and more frequent and longer summer droughts for both emission scenarios. Even though the results indicated an increase in spring precipitation in the future, they showed more frequent spring droughts when those were based on stream flow and soil moisture. This highlights the importance of process representation for drought risk analysis. This research helps agriculture and natural resource managers plan for and adapt to a changing climate, and decide what further analyses are necessary.

Technical Abstract: Predicting the impacts of projected change in precipitation (P) and temperature (T) on occurrence of drought and extreme events are essential for managing natural resources and setting policy. This study compares future occurrence of excessively dry and wet periods based on P, T, stream flow, soil moisture, and extreme P and T events. The comparisons are based on coupled future climate projections from multiple Earth system models downscaled using site-specific weather data and hydrologic model outputs for the Goodwater Creek Experimental Watershed, Missouri, USA. The use of multiple drought indices, downscaled climate data, and process model output facilitated drought prediction comparison for different land surface processes and its comparison. The P and T extremes and droughts were calculated using standardized indices. The results based on drought and extreme indices indicate increased frequency and duration of drought in the future, primarily due to a projected decline in summer precipitation resulting in summer droughts. The streamflow and soil water-based drought indices indicated increased spring drought risks in the future despite a precipitation increase indicating the importance of process representation with hydrologic models for drought computation.