Development of regional parameter estimation equations for a macroscale hydrologic model

Abstract

A methodology for developing regional parameter estimation equations, designed for application to continental scale river basins, is described. The approach, which is applied to the two-layer Variable Infiltration Capacity (VIC-2L) land surface hydrologic model, uses a set of 34 unregulated calibration or “training” catchments (drainage areas 10 2–10 4 km 2) distributed throughout the Arkansas–Red River basin of the south central U.S. For each of these catchments, parameters were determined by: a) prior estimation of two of the model parameters (saturated hydraulic conductivity and pore size distribution index) from the U.S. Soil Conservation Service State Soil Geographic Data Base (STATSGO) data base; and b) estimation of the remaining seven parameters via a search procedure that minimizes the sum of squares of differences between predicted and observed streamflow. The catchment parameters were then related to 11 ancillary distributed land surface characteristics extracted from STATSGO, and 17 variables derived from station meteorological data. The seven regression equations explained from 54 to 76% of the variance of the parameters. The most frequently occurring ancillary variables were the average permeability, saturated hydraulic conductivity, and SCS hydrologic Group B (typically soils with moderately high infiltration rates) fraction derived from STATSGO, and the average temperature and standard deviation of fall precipitation. The method was tested by comparing simulations using the regional (regression equation) parameters for six unregulated catchments not in the parameter estimation set. The model performance using the regional parameters was quite good for most of the calibration and validation catchments, which were humid and semi-humid. The model did not perform as well for the smaller number of arid to semi-arid catchments.