Detection of changes in hydrologic system memory associated with urbanization in the Great Lakes region

Abstract

The change of long memory with urbanization in a regional hydrologic system was investigated using both stochastic time series models and a physically based hydrologic model. Based on observed streamflow at five USGS gauge stations in the Great Lakes region, objective fractional autoregressive integrated moving average (FARIMA) model identification and estimation procedures were used for daily streamflow. The recently improved Variable Infiltration Capacity (VIC) model with urban representation was applied to simulate the water and energy response in 16 basins in the region with various degrees of urbanization. The VIC model was driven by different years' land use/cover maps, including a year 1992 base map, and year 2010 and 2030 maps projected by the Land Transformation Model. The ability of the VIC model to capture long memory of observed daily streamflow was evaluated before applying the FARIMA model to all 16 basins. Overall, the northern portion of the domain generally has larger long-term hydrologic dependence than the southern portion. Simulated streamflow statistics show that the long memory in the hydrologic system has decreased with urbanization. In order to interpret the long memory change with urbanization from a physical point of view, spectral analysis was conducted to examine the spectrum change of soil moisture content with urbanization. The decrease in simulated streamflow long memory relates to the decreased low-frequency power and amplitude of soil moisture in the deep soil layer. The long-term response of surface water systems to urbanization should be considered by water resources and urban planners.