Various methods are available to measure or estimate the quantity of water present in a snowpack. Historically, the National Weather Service has relied on direct measurements taken at first order and cooperative weather stations. Because of the great spatial variability in snow cover density, point measurements are often of limited utility in identifying snow water equivalent (SWE) values over a given area or watershed. Increasingly, remote sensing techniques and physical models have been used to supplement point measurements of SWE and to improve areal estimates of snow water equivalent. This paper compares daily first-order SWE observations from five stations across the northern Great Plains with those estimated from passive microwave remotely sensed data and from an energy and mass balance model (SNTHERM). A commonly utilized SWE algorithm is applied to Special Sensor Microwave/Imager (SSM/I) data across the northern Great Plains during the 1990s. Various filtering algorithms are applied to eliminate those situations in which the SSM/I SWE algorithms are known to be ineffectual. Airborne gamma estimates are also included in the comparison but are limited to only a few observations a year. Although the modeled SWE is generally in good agreement with the observed SWE, there is a tendency for the SNTHERM model to underestimate SWE, but it is typically within the margin of error of the observations. The microwave SWE algorithm apparently overestimates SWE significantly late in the season, compared to in situ observations, likely a result of snow grain growth during snow metamorphism.