Examining the Intra-annual Variance in Streamflow: What is the Contribution from Climate Variability?

Thursday, 18 December 2014
Sheng Ye1, Hong-Yi Li1, Shuai Li1,2 and L. Ruby Leung1, (1)Pac NW National Lab, Richland, WA, United States, (2)Wuhan University, Wuhan, China
Assessing the influence of climate forcing on streamflow, and how it varies from place to place is an important component of catchment hydrology. A great number of studies have explored this issue analytically or empirically. One widely used framework is the Budyko curve, which describes catchments by the partition of precipitation between flow and evapotranspiration at annual scale. Both climate change and human activities such as water management and land use have important effects on the seasonal water balance. However, with the increased complexity of soil water storage change at seasonal scale, more research is needed to extend the Budyko framework for the intra-annual relationship between climate and streamflow. In this study, we extended the equation quantifying the propagation of variability from climate to runoff at annual scale to monthly scale. Besides the aridity index (AI), the variance ratio between soil storage change and precipitation as well as the covariance among the soil water storage, precipitation and evapotranspiration could also play significant roles in intra-annual variability. The new equation was then applied to 232 catchments across the continental US for validation. The calculated variance ratio and the observed variance ratio of runoff and precipitation agree reasonably well. The new relationship suggested that when the intra-annual variability in precipitation is larger, the amount of intra-annual variability propagating to streamflow is dominated by the annual AI. When the variability in precipitation is small, the interaction between soil water storage and climate has to be taken into account, which may be also related to the vegetation type. This new analytical framework will improve the understanding of the close interactions between climate, soil, vegetation and topography at the catchment scale, and has the potential to facilitate the parameterization of coupled ecological and hydrological processes in the land surface and earth system models.