Accuracy of Snow Water Equivalent Estimated From GPS Vertical Displacements: A Synthetic Loading Case Study for Western U.S. Mountains
| Autor: | Eric E. Small, T. Enzminger, Adrian A. Borsa |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Environmental Engineering
010504 meteorology & atmospheric sciences business.industry 0208 environmental biotechnology 02 engineering and technology Water equivalent Snow Civil Engineering 01 natural sciences Physical Geography and Environmental Geoscience 020801 environmental engineering Remote sensing (archaeology) Global Positioning System Environmental science business 0105 earth and related environmental sciences Water Science and Technology Remote sensing |
| Zdroj: | Water Resources Research, vol 54, iss 1 |
| ISSN: | 1944-7973 0043-1397 |
| DOI: | 10.1002/2017wr021521 |
| Popis: | GPS monitoring of solid Earth deformation due to surface loading is an independent approach for estimating seasonal changes in terrestrial water storage (TWS). In western United States (WUSA) mountain ranges, snow water equivalent (SWE) is the dominant component of TWS and an essential water resource. While several studies have estimated SWE from GPS-measured vertical displacements, the error associated with this method remains poorly constrained. We examine the accuracy of SWE estimated from synthetic displacements at 1,395 continuous GPS station locations in the WUSA. Displacement at each station is calculated from the predicted elastic response to variations in SWE from SNODAS and soil moisture from the NLDAS-2 Noah model. We invert synthetic displacements for TWS, showing that both seasonal accumulation and melt as well as year-to-year fluctuations in peak SWE can be estimated from data recorded by the existing GPS network. Because we impose a smoothness constraint in the inversion, recovered TWS exhibits mass leakage from mountain ranges to surrounding areas. This leakage bias is removed via linear rescaling in which the magnitude of the gain factor depends on station distribution and TWS anomaly patterns. The synthetic GPS-derived estimates reproduce approximately half of the spatial variability (unbiased root mean square error ∼50%) of TWS loading within mountain ranges, a considerable improvement over GRACE. The inclusion of additional simulated GPS stations improves representation of spatial variations. GPS data can be used to estimate mountain-range-scale SWE, but effects of soil moisture and other TWS components must first be subtracted from the GPS-derived load estimates. |
| Databáze: | OpenAIRE |
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