Scaling surface and subsurface flow processes in hydrologic models

Abstract

Hydrologic models have improved significantly over the past 50 years, transforming from empirically-based and spatially-lumped to physically-based and distributed. In light of these advances, new challenges such as scaling have emerged. Although challenges related to scaling in hydrology have been investigated for decades, they still persists throughout the measurement and modeling communities. This dissertation investigates hydraulic scaling in hydrologic models with three specific objectives: (i) quantify how simulated flowpath and runoff response timing characteristics varying with spatial model resolution; (ii) develop an approach for estimating scale-dependent routing process parameters based on model resolution; and (iii) apply the scaling approach in a multi-scale model calibration application. To overcome scaling effects on simulated streamflow dynamics, an upscaling framework is developed to minimize the surface and subsurface travel time differences between conceptual model representations and distributed topographic-based methods. Surface roughness and hydraulic conductivity are modified to increase and/or decrease the surface and subsurface flow velocities and associated travel times. Results show that the scaling approach leads to streamflow responses from coarse model resolutions that are consistent with responses from fine model resolutions. The scaling method is used in a model calibration application. Surface and subsurface routing parameters are upscaled to a coarse model resolution and calibrated using runoff derived from USGS streamflow measurements. The calibrated parameters are then downscaled to a fine model resolution and the resulting fine scale model performance are verified. The scaling approach accounts for changes in flowpath processes and adjusts model parameters such that the magnitude and timing of hydrologic responses from coarse model resolutions are consistent with fine scale models. An application of this scaling approach is in using coarser scale models for calibration and uncertainty analyses to decrease computational demands. The study reveals non-linear relationships between model resolution, topographic and surface/subsurface routing characteristics in the Ohio River Basin. The scaling approach and findings provide insights for improving the representation of flowpath processes in Earth System Models or other large-scale modeling applications.