Analyzing urban sub-grid processes using high-resolution land cover and an integrated hydrologic model

Wednesday, 17 December 2014
Bryant Reyes, Reed M Maxwell and Terri S Hogue, Colorado School of Mines, Golden, CO, United States
As the world rapidly urbanizes, a grasp of water resources within an urban context becomes crucial to both the policy and scientific communities. Parameterizing and understanding the interactions between the land surface and terrestrial hydrologic budgets of the urban domain within watershed and regional models is critical to this goal. The work presented here assesses the processes simulated by an integrated, coupled land surface/hydrologic model at various spatial scales in the urban domain as well as the changes in partitioning of runoff and evapotranspiration (ET) as a function of land cover heterogeneity. Two land cover datasets for the City of Los Angeles are utilized: (1) the National Land Cover Database (NLCD) dataset at a 30-m resolution that categorizes the urban domain between developed open space, and low, medium and high intensity developed land cover; and (2) an ultra high-resolution dataset that classifies the City into grass, tree, bare soil, and impervious land cover at a 0.6-m resolution. Using these datasets and hourly observed meteorological forcings, we simulate various permutations and resolutions ranging from 0.6-m to 30-m for a two year spin-up and two year study period. Our analyses shows that increasing resolution alone, while holding all other parameters constant, greatly changes timing of hydrologic events and the overall hydrologic budget with higher resolutions producing less overland flow than lower resolution models. The impact of the highly organized, yet heterogeneous, land cover typical of the urban domain is also assessed. The runoff/runon processes characteristic of these domains create variations in overland flow of up to ±20% and ±3% in ET. Finally, the impact of scaling land surface and hydrologic parameters is shown to create systematic diurnal biases in the surface energy budget in contrast to the seasonal biases seen in the hydrologic fluxes. This work, in addition to creating land surface parameters for the widely used NLCD urban land covers, illustrates nonlinear issues of scale and resolution and improves understanding of how these processes affect the surface energy and hydrologic budgets.