A Tale of two Storms: Using Stable Water Isotopes to Investigate Hydrological Processes Under a Changing Climate

Stable isotopic methods in hydroclimate monitoring are powerful for improving water resources management, but applications are limited, especially in semi-arid regions where such management is needed most. In this study, we show that we can address shortcomings related to lack of a seasonal signal using stable water isotopic signatures measured over the eastern San Francisco Bay Area of California during two contrasting events. We use hydrometric data from a gauged watershed in the study area and isotopic signatures of rain sampled at more than 20 locations during two contrasting storm events (Winter Storm Olive in February, 2023 and a warmer atmospheric river event in March 2023), and apply a solute transport model with a travel-time approach to examine predicted watershed responses and potential water tracing applications. The observed range in δ O in the rain samples is similar for both storms, about 5‰. However, the distributions do not overlap – the mean air temperature during Olive was about 2 C, and the mean δ O of the rain samples is -12‰, while the AR event had a mean temperature of about 9 C and a mean δ O of -6‰, close to the long-term average δ O measured in local precipitation. In the model results, event size exerts a strong control on the relative amounts of runoff vs pre-event water in the stream, while uncertainty in stream hydrograph separation is related to the degree of contrast between precipitation/runoff and pre-event water. Key to flood prediction, adaptation and mitigation, especially in coastal urban areas, is knowledge of the contributing water sources and timing of flows in streams and other features susceptible to flooding. The strong contrast in stable isotopes between these two events over the same area, illustrates the potential to use stable isotope signatures to track the transport and mixing of event water through natural and engineered watersheds.