Improving runoff simulation in the Western United States with Noah-MP and variable infiltration capacity

Abstract

Streamflow predictions are critical for managing water resources and for environmental conservation, especially in the water-short Western United States. Land surface models (LSMs), such as the variable infiltration capacity (VIC) model and the Noah LSM with multiparameterization options (Noah-MP), play an essential role in providing comprehensive runoff predictions across the region. Virtually all LSMs require parameter estimation (calibration) to optimize their predictive capabilities. Here, we focus on the calibration of VIC and Noah-MP models at a 1/16° latitude–longitude resolution across the Western United States. We first performed global optimal calibration of parameters for both models for 263 river basins in the region. We find that the calibration significantly improves the models' performance, with the median daily streamflow Kling–Gupta efficiency (KGE) increasing from 0.37 to 0.70 for VIC, and from 0.22 to 0.54 for Noah-MP. In general, post-calibration model performance is higher for watersheds with relatively high precipitation and runoff ratios, and at lower elevations. At a second stage, we regionalize the river basin calibrations using the donor-basin method, which establishes transfer relationships for hydrologically similar basins, via which we extend our calibration parameters to 4816 hydrologic unit code (HUC)-10 basins across the region. Using the regionalized parameters, we show that the models' capabilities to simulate high and low flow conditions are substantially improved following calibration and regionalization. The refined parameter sets we developed are intended to support regional hydrological studies and hydrological assessments of climate change impacts.