4.6 Article Proceedings Paper

The detection and correction of snow water equivalent pressure sensor errors

期刊

HYDROLOGICAL PROCESSES
卷 18, 期 18, 页码 3513-3525

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JOHN WILEY & SONS LTD
DOI: 10.1002/hyp.5795

关键词

snow water equivalent measurement; snow pressure sensor error correction; snow hydrology

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Snow water equivalent (SWE) sensors can experience errors when the base of the snow cover is at the melting temperature, the snow can support shear stresses (assumed to occur at densities greater than 200 kg m(-3)), and the rate of snowmelt on the sensor is different than on the surrounding ground. Either undermeasurement or overmeasurement errors may occur at critical times when the snow cover transitions from winter to spring conditions and at the start of periods of rapid snowmelt. Parameters to determine the onset of SWE sensor undermeasurement errors are defined by a negative rate of change for SWE, a negative rate of change for snow density, and an increasing snow depth. For the onset of overmeasurement errors, the rate of change for SWE will be positive while snow depth decreases and the snow density rate of change exceeds a defined positive threshold. When the snow temperature and density error conditions and the three under- or over-measurement error-indicator parameters are satisfied at the same time, an SWE sensor error has started. Real-time correction of the errors is done by multiplying the average snow cover density, set at the start of the error, with the snow depth. Once the error event ends, when the corrected SWE and SWE sensor data intersect, SWE is again determined from SWE sensor measurements. SWE sensor errors were accurately detected and corrected for five different sensors located in maritime and intermountain climatic zones when high-quality SWE sensor, snow or air temperature, and snow depth measurements were available. Implementation of the error detection and correction method requires simultaneous measurements of SWE, snow depth, and snow temperature near the ground. Improved error correction can be achieved by incorporating precipitation data and estimates of snow density due to retained rain or snow melt. Copyright (C) 2004 John Wiley Sons, Ltd.

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