Hydrologic Model Parameter Estimation in Ungauged Basins using Simulated
SWOT Discharge Observations
Abstract
In situ gauge networks are often used in hydrological model calibration,
but these networks are limited or nonexistent in many regions. The
upcoming Surface Water Ocean Topography (SWOT) mission promises to fill
this observation gap by providing discharge estimates for rivers with
widths greater than 100 meters. Proxy SWOT discharge estimates derived
from an observing system simulation experiment and Monte Carlo methods
are used to assess SWOT observation utility for model parameter
selection in regions devoid of in situ gauges. The sensitivity of the
parameter selection to measurement error and observation temporal
frequency is also evaluated. Single-point and multi-point parameter
selection is performed for ten sub-basins within the Susitna River and
upper Tanana River basins in Alaska. SWOT is expected to observe Alaskan
river points 4-7 times per 21-day repeat cycle with 120 km swath
coverage. For an expected SWOT discharge error of 35%, parameter
estimation is successful for 60% and 90% of sub-basins using
single-point and multi-point selection, respectively. Decreasing
observation frequency to simulate lower latitudes resulted in success
for only 20% of midlatitude and 10% of tropical sub-basins for
single-point selection, whereas multi-point selection was successful in
80% of midlatitudes and 70% of tropical sub-basins. Single-point
parameter selection was much more sensitive to SWOT discharge error than
multi-point parameter selection. The results strongly support the use of
multi-point parameter selection over single-point parameter selection,
yielding robust results nearly independent of observation error with
approximately half the sensitivity to observation frequency.