Climate Change May Alter Rainfall‐Partitioning in Ways Unlikely To Be Detected in the Coming Decades

Abstract Droughts around the world have resulted in less annual streamflow relative to annual rainfall. The decrease in streamflow cannot be explained by changes in land‐use, precipitation or temperature alone. Rather, the decrease in annual streamflow has been linked to changes in annual rainfall‐partitioning. Climate change is predicted to induce similar, if not worse conditions than previous droughts. This could make the disproportionate shifts in annual streamflow more frequent or intense. Currently, most methods assume annual rainfall‐partitioning remains constant and thus are unlikely to accurately predict how climate change could impact streamflow. Our aim is to conduct a thought‐experiment to examine the various ways climate change could alter annual rainfall‐partitioning and to determine what types of changes in rainfall‐partitioning are likely to be statistically detectable in the coming decades. Using a synthetic streamflow model, we show how changing the rainfall‐runoff intercept, rainfall‐runoff slope, lag‐1 autocorrelation, standard deviation per rainfall depth and, skewness per rainfall depth alters rainfall‐partitioning. Of all the rainfall‐partitioning changes examined only the rainfall‐runoff intercept and slope are likely to be statistically detectable in the coming decades. Changes impacting lag‐1 autocorrelation of annual streamflow, standard deviation per rainfall depth and skewness per rainfall depth are unlikely to be statistically detectable in the coming decades. Although being unlikely to be statistically identified, these changes still alter both the rainfall‐runoff and streamflow‐time relationships. Rainfall‐partitioning changes that alter streamflow and are unlikely to be statistically detected in the coming decades will make prediction and allocation of water resources more challenging.