Distributed Hydrologic Modeling using GIS and Topmodel

Presentation at 19th Annual AGU Hydrology Days, Fort Collins, Colorado, August 16-20.

David Tarboton
Utah State Univerisity, Logan, Utah, 84322-8200.  Ph 435 797 3172.  Fax 435 797 3663.  email dtarb@cc.usu.edu

Ross Woods, Charles Pearson, Ude Shankar, Roddy Henderson, Richard Ibbitt
National Institute of Water and Atmospheric Research, P.O. Box 8602, Christchurch, New Zealand.  Ph +63 3 348 8987.  Fax +64 3 348 5548.


 

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Table of Contents

Distributed Hydrologic Modeling using GIS and Topmodel

Objectives

Overview

Location Map of the Grey River

Grey Digital Elevation Model

Channel Network Extraction 

Order 5 subbasin delineation

Order 2 subbasin delineation

Vegetation

Depth Weighted Macroporosity

Rain and streamflow gauges

Rainfall

Rainfall interpolation

Hydrologic Model

Topmodel (Based on Beven and Kirkby, 1979 and later)

Implementation (additions/modifications)

Potential Evapotranspiration (following Maidment D. R. (editor), 1993, Handbook of Hydrology, Chapter 4 on Evaporation by W J Shuttleworth.)

PPT Slide

Interception (adapted following Ibbitt, 1971)

Soil Zone

Pattinson Creek

PPT Slide

PPT Slide

PPT Slide

PPT Slide

PPT Slide

PPT Slide

Grey at Dobson

PPT Slide

Rainfall (lack of simple) dependence on elevation

Rainfall interpolation and adjustment

Rainfall interpolation

Parameters

Basin average precipitation

PPT Slide

Summary and Conclusions

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Home Page: http://www.neng.usu.edu/dtarb

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Abstract

This paper describes a distributed modeling approach applied to modeling stream flow in the 3817 km2 Grey River in New Zealand.  We have assembled and used a modeling system centered on TOPMODEL, for the simulation of saturation excess runoff based upon topography, but included other components to represent all the hydrologic processes deemed relevant.  Precipitation was spatially interpolated from twenty five rain gauges using linear interpolation on Delauney triangles and scaling by an annual rainfall surface to represent orographic effects.  The model included components for estimating reference evapotranspiration from temperature, modeling interception and throughfall, an unsaturated zone soil layer that delayed water inputs to the saturated zone and provided infiltration excess runoff generation capability, and a kinematic wave channel routing component.  Procedures were developed to generate model input files from digital elevation model and land resource inventory Geographic Information System (GIS) data.  Model elements are subwatersheds automatically extracted based upon the channel network extracted from the digital elevation model and a specified stream order threshold.  Model element parameters are linked to GIS information averaged over each subwatershed.  We were able to handle subdivision into up to 200 subwatersheds.  The model was calibrated using an interactive calibration package utilizing the Gauss-Marquardt method.  The calibration uses scale multipliers to retain GIS landcover derived relative differences between parameters across subwatersheds.  Model parameters were first calibrated against a small subwatershed for one year then independently tested there for a later year. The calibration used precipitation measured at this small watershed while the validation exercised the precipitation interpolation methodology.  The model was then applied to the whole Grey basin, with the same parameters and compared to flow measured at the basin outlet, and eight other water level recorders in the basin. Our results indicate that streamflow estimates are sensitive to uncertainty in the precipitation due to variability and orographic effects and that this precipitation uncertainty dominates over uncertainty in other basin characteristics.  We discuss efforts to reconcile the spatial pattern of rainfall with rain gage and stream flow measurements across this watershed.