Using Densely Distributed Soil Moisture Observations for Calibration of a Hydrologic Model

Abstract

Abstract Calibration is a crucial step in hydrologic modeling that is typically handled by tuning parameters to match an observed hydrograph. In this research, an alternative calibration scheme based on soil moisture was investigated as a means of identifying the potentially heterogeneous calibration needs of a distributed hydrologic model. The National Weather Service’s (NWS) Hydrology Laboratory Research Distributed Hydrologic Model (HL-RDHM) was employed to carry out such a calibration, along with concentrated in situ soil moisture observations from the Iowa Flood Studies (IFloodS) field campaign in Iowa’s Turkey River basin. Synthetic, single-pixel experiments were conducted in order to identify parameters relevant to soil moisture dynamics and to test the ability of three calibration procedures (discharge, soil moisture, and hybrid based) to recapture prescribed parameter sets. It was found that three storage parameters of HL-RDHM could be consistently identified using soil moisture RMSE as the objective function and that the addition of discharge-based calibration led to more consistent parameter identification for all 11 storage and release parameters. Expanding to full-basin experiments, these three calibration procedures were applied following an investigation to find the most advantageous method of distributing the point-based calibrations carried out at each pixel collocated with an IFloodS observation site. A method based on pixel similarity was deemed most appropriate for this purpose. Additionally, streamflow simulations calibrated with soil moisture showed improvement in RMSE and Nash–Sutcliffe efficiency (NSE) for all calibration–validation events despite a short calibration period, a promising result when considering calibration of ungauged basins. However, supplementary evaluation metrics show mixed results for streamflow simulations, suggesting further investigation is required.