Disentangling the effects of climate and urban growth on streamflow for sustainable urban development: A stochastic approach to flow regime attribution

Abstract

In urban watersheds, climate variability and change, urban growth, and stormwater management can act concurrently over time to shape and alter the streamflow dynamics. Yet, when assessing the impacts of urbanization on streamflow, these factors are rarely taken simultaneously into consideration. There is thus an emerging need for approaches that allow disentangling the hydrological impacts of land cover change from those due to climate, in the context of long-term, historical changes in urban landscapes. This is here termed flow regime attribution. We demonstrate in this study the ability of a stochastic mechanistic model to perform flow regime attribution. The modeling approach is applied to the Watts Branch watershed, located in metropolitan Washington D.C., United States. To carry out the flow regime attribution, the model is used to compute streamflow indicators of hydrological alteration and perform parameter sensitivity analysis. The application of the model shows that in Watts Branch urban growth drives the long-term temporal trend in streamflow. The mean and variance of streamflow increase at the end of the gauging period by 2 and 7 times, respectively, their value relative to an only climate (no urban growth) scenario. The results show that climate mainly amplifies or dampens the temporal trend according to wet/dry variations in annual rainfall. Further, the model facilitates the attribution process by allowing the derivation of streamflow indicators that directly depend on the model parameters. The proposed modeling approach may be useful for assessing the long-term flow behavior of urban watersheds, and informing sustainable urban development decisions.