Delineating Equivalent Cross-Sections for Semi-Distributed Hydrologic Modelling at Large Scales

Wednesday, 17 December 2014
Urooj Khan1, Hoori Ajami2, Narendra Kumar Tuteja1 and Ashish Sharma2, (1)Bureau of Meteorology, Environment and Research Division, Canberra, Australia, (2)University of New South Wales, School of Civil and Environmental Engineering, Sydney, NSW, Australia
Recently, a new approach of modelling over an equivalent cross-section was developed to reduce the computational time/effort in distributed hydrologic modelling at large catchment scale. In this approach, equivalent cross sections constitute the modelling elements and are formulated by weighting the topographic and physiographic properties of the part or entire first-order sub-basins. Model simulations are performed at the scale of equivalent cross-sections using a 2-dimensional, Richards’ equation based distributed hydrological model. Simulated fluxes from every cross section are multiplied by the respective area from which the equivalent cross-sections were formulated in a first-order sub-basin. These fluxes are aggregated at a catchment scale to estimate the total fluxes.

Despite the improvement in computational efficiency using the equivalent cross-section approach, delineation of the equivalent cross-sections across regional scales remains a challenge due to large amount of spatial data processing involved. Here, we developed a workflow based approach to automate the pre- and post-processing steps involved in delineation and modelling of equivalent cross-sections. A series of tools are developed to automate the equivalent cross-section delineation process, model simulations across multiple cross sections, and visualizing model results. The automation steps include: delineation of first order sub-basins of a catchment using a digital elevation model, landform delineation in every first order sub-basin based on topographic and geomorphic properties of the sub-basin/catchment, formulation of equivalent cross sections and extraction of relevant biophysical parameters (vegetation and soils) using spatially distributed land cover and soil information. The automation procedure improves the usability of the proposed approach and significantly reduces the model setup time for large catchment scale simulations.