Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

Advertisement

Combining snow water equivalent data from multiple sources to estimate spatio-temporal trends and compare measurement systems

  • Published:
Journal of Agricultural, Biological, and Environmental Statistics Aims and scope Submit manuscript

Abstract

Owing to the importance of snowfall to water supplies in the western United States, governmentagencies regularly collect data on snow water equivalent (the amount of water in snow) over this region. Several differentmeasurementsystem, of possibly different levels of accuracy and reliability, are in operation: snow courses, snow telemetry, aerial markers, and airborne gamma radiation. Data are available at more than 2,000 distinct sites, dating back a variable number of years (in a few cases to 1910). Historically, these data have been used primarily to generate flood forecasts, and short-term (intra-annual) predictions of streamflow and water supply. However, they also have potential for addressing the possible effects of long-term climate change on snowpack accumulations and seasonal water supplies. We presenta Bayesian spatio-temporalanalysis of the combined snow water equivalent (SWE) data from all four systems that all ows for systematic differences in accuracy and reliability. The primary objectives of our analysis are (1) to estimate the long-term temporal trend in SWE over the western U.S. and characterizehow this trend variesspatially, with quantifiable estimates of variability, and (2) to investigate whether there are systematic differences in the accuracy and reliability of the four measurement systems. We find substantial evidence of a decreasing temporal trend in SWE in the Pacific North west and northern Rockies, but no evidence of a trend in the intermountain region and southern Rockies. Our analysis also indicates that some of the systems differ significantly with respect to their accuracy and reliability.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Aguado, E. (1990), “Elevational and Latitudinal Patterns of Snow Accumulation and Departures from Normal in the Sierra Nevada,” Theoretical and Applied Climatology, 42, 177–185.

    Article  Google Scholar 

  • Brooks, S. P., and Gelman, A. (1998), “General Methods for Monitoring Convergence of Iterative Simulations,” Journal of Computational and Graphical Statistics, 7, 434–455.

    Article  MathSciNet  Google Scholar 

  • Carroll, S. S. (1995), “Modeling Measurement Errors When Estimating Snow Water Equivalent,” Journal of Hydrology, 172, 247–260.

    Article  Google Scholar 

  • Carroll, S. S., and Carroll, T. R. (1989), “Effect of Uneven Snow Cover on Airborne Snow Water Equivalent Estimates Obtained by Measuring Terrestrial Gamma Radiation,” Water Resources Reseurch, 25, 1505–1510.

    Article  Google Scholar 

  • — (1990), “Estimating the Variance of Airborne Snow Water Equivalent Estimates Using Computer Simulation Techniques,” Nordic Hydrology, 21, 35–46.

    Google Scholar 

  • Carroll, S. S., Carroll, T. R., and Poston, R. W. (1999), “Spatial Modeling and Prediction of Snow-Water Equivalent Using Ground-Based, Airborne, and Satellite Snow Data,” Journal of Geophysical Research, 104, 19623–19629.

    Article  Google Scholar 

  • Carroll, S. S., and Cressie, N. (1996), “A Comparison of Geostatistical Methodologies Used to Estimate Snow Water Equivalent,” Water Resources Bulletin, 32, 267–278.

    Google Scholar 

  • — (1997), “Spatial modeling of snow water equivalent using covariance estimated from spatial and geomorphic attributes,” Journal of Hydrology, 190, 42–57.

    Article  Google Scholar 

  • Carroll, S. S., Day, G. N., Cressie, N., and Carroll, T. R. (1995), “Spatial Modelling of Snow Water Equivalent Using Airborne and Ground-Based Snow Data,” Environmetrics, 6, 127–139.

    Article  Google Scholar 

  • Cayan, D. R. (1996), “Interannual Climate Variability and Snowpack in the Western United States,” Journal of Climate, 9, 928–948.

    Article  Google Scholar 

  • Changnon, D., McKee, T. B., and Doesken, N. J. (1993), “Annual Snowpack Patterns Across the Rockies: Long-Term Trends and Associated 500-mb Synoptic Patterns,” Monthly Weather Review, 121, 633–647.

    Article  Google Scholar 

  • Gelfand, A. E., and Sahu, S. K. (1999), “Identifiability, Improper Priors, and Gibbs Sampling for Generalized Linear Models,” Journal of the American Statistical Association, 94, 247–253.

    Article  MATH  MathSciNet  Google Scholar 

  • Gelman, A., Meng, X.-L., and Stern, H. (1996), “Posterior Predictive Assessment of Model Fitness via Realized Discrepancies” (with discussion), Statistica Sinica, 6, 733–760.

    MATH  MathSciNet  Google Scholar 

  • Gelman, A., and Rubin, D. B. (1992), “Inference from Iterative Simulation Using Multiple Sequences” (with discussion), Statistical Science, 7, 457–472.

    Article  Google Scholar 

  • Gleick, P. H. (1987), “Regional Hydrologic Consequences of Increases in Atmospheric CO2 and Other Trace Gases,” Climate Change, 10, 137–161.

    Article  Google Scholar 

  • Hartman, R. K., Rost, A. A., and Anderson, D. M. (1995), “Operational Processing of Multi-source Snow Data,” Proceedings of the Western Snow Conference, 147–151.

  • Huang, H. C., and Cressie, N. (1996), “Spatio-Temporal Prediction of Snow Water Equivalent Using the Kalman Filter,” Computational Statistics and Data Analysis, 22, 159–175.

    Article  MathSciNet  Google Scholar 

  • Isaacson, J. D., and Zimmerman, D. L. (2000), “Combining Temporally Correlated Environmental Data from two Measurement Systems,” Journal of Agricultural, Biological, and Environmental Statistics, 5, 64–83.

    Article  MathSciNet  Google Scholar 

  • Lettenmaier, D. P., and Sheer, D. P. (1991), “Climatic Sensitivity of California Water Resources,” Journal of Water Resources Planning and Management, 117, 108–125.

    Article  Google Scholar 

  • McCabe, A. J., and Legates, S. R. (1995), “Relationships Between 700hPa Height Anomalies and 1 April Snowpack Accumulations in the Western USA,” International Journal of Climatology, 14, 517–530.

    Article  Google Scholar 

  • McGinnis, D. L. (1997), “Estimating Climate-Change Impacts on Colorad o Plateau Snowpack using Downscaling Methods,” Professional Geographer, 49, 117–125.

    Article  Google Scholar 

  • Palmer, P. L. (1988), “The SCS Snow Survey Water Supply Forecasting Program: Current Operations and Future Directions,” Proceedings of the Western Snow Conference, Kalispell, MT, pp. 43–51.

  • Royle, J. A., and Berliner, L. M. (1999), “A Hierarchical Approach to Multivariate Spatial Modeling and Prediction,” Journal of Agricultural, Biological, and Environmental Statistics, 4, 29–56.

    Article  MathSciNet  Google Scholar 

  • Serreze, M. C., Clark, M. P., McGinnis, D. L., Pulwarty, R. S., and Armstrong, R. A. (1999), “Climatological Characteristics of the Western U. S. Snowpack from SNOTEL Data,” Water Resources Research, 35, 2145–2160.

    Article  Google Scholar 

  • Smith, B. J. (2000), Bayesian Output Analysis Program (BOA), Version 0.5.0 for S-Plus and R, http://www. public-health.uiowa.edu/BOA.

  • Spiegelhalter, D. J., Best, N. G., Carlin, B. P., and van der Linde, A. (in press), “Bayesian Measures of Model Complexity and Fit,” Journal of the Royal Statistical Society, Series B, in press.

  • Wikle, C. K., Berliner, L. M., and Cressie, N. (1998), “Hierarchical Bayesian Space-Time Models,” Environmental and Ecological Statistics, 5, 117–154.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Cowles, M.K., Zimmerman, D.L., Christ, A. et al. Combining snow water equivalent data from multiple sources to estimate spatio-temporal trends and compare measurement systems. JABES 7, 536–557 (2002). https://doi.org/10.1198/108571102753

Download citation

  • Received:

  • Revised:

  • Issue Date:

  • DOI: https://doi.org/10.1198/108571102753

Key Words