Efficient Use of Prior Information to Calibrate the Gridded Surface Subsurface Hydrologic Analysis (GSSHA) Hydrology Model
Abstract
The purpose of this document is to provide guidance on the use of two computer-based calibration functionalities recently developed for the Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model. These new capabilities enable the incorporation of soft data, or prior information (i.e., extra observations which pertain directly to the estimable parameters, primarily in attempts to stabilize the calibration process). These new calibration methods are not only efficient (measured in terms of forward-model, call-run requirements) but also effective in that they result in physically acceptable models usable for subsequent prediction. This document describes how to use these new functionalities to calibrate a GSSHA model as well as benefits that can be derived in the process. Spatially explicit, physics-based models such as GSSHA (Downer and Ogden 2003a,b) support a more realistic characterization of the physical aspects of watersheds and a more transparent simulation and evaluation of project alternatives than is possible with traditional hydrologic simulation models (viz., lumped and semi-distributed model structures). Such models have the potential to predict with greater reliability than lumped hydrologic model structures (Moore and Doherty 2005). However, they also have the potential to easily become highly parameterized, particularly when deployed to simulate a heterogeneous watershed on a continuous basis. Simulation times with such models are often far greater than with lumped and semi-distributed hydrologic models. It is this combination of computationally intensive, forward model run times and the potential for a highly dimensional, specified adjustable model parameter space which presents a unique challenge for the computer-based calibration of spatially explicit, physics-based hydrologic models. In particular, this combination necessitates the use of a calibration method that is as efficient as possible.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 01, 2014
- Accession Number
- ADA609351
Entities
People
- Brian E. Skahill
- Charles W Downer
Organizations
- Engineer Research and Development Center