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Visualizing And Analyzing Time-series Data Using A Raster Time Map Approach

Congress: 2015
Author(s): Richard Koehler (Erie, CO, USA)


Keyword(s): Sub-theme 10: Management of water resources,
AbstractThe objective of this paper is to provide the audience new tools and data visualization methods that provide greater insight and understanding of the hydrologic process especially when dealing with very large and multiple environmental datasets.

This innovative method uses a "raster time map", or raster hydrograph, approach which allows daily, weekly, monthly, seasonal, annual and inter-annual patterns to be identified simultaneously. Additionally by applying geographic information system methods to the raster hydrograph, new data configuration metrics and novel multilayer analyses are possible.

Results from example case studies show a superior way to indentify streamflow patterns, quickly locate data artifacts and questionable values, provide a comprehensive dataset overview and establish a foundation for new metrics and visualization methods.

This presentation provides a basic change in ideas and methods used by water resources professionals when analyzing time-series data. de Pessôa, J. A. 2014. Pluviometric ID: precipitation characteristics at a glance. Atmosph. Sci. Lett.. doi: 10.1002/asl2.501

Dott, C. E. and R. Koehler. 2010. Impacts of earlier snowmelt on patterns of streamflow in southwest Colorado rivers. Geological Soc. of Amer. Annual Meeting, Program & Abstracts. Denver. CO.

Gochis,D., D. L. Brito-Castillo, and W. J. Shuttleworth. 2006. Correlations between sea surface temperatures and warm season stream flow in northwest Mexico. International Journal of Climatology. Royal Meteorological Society

Grant, G., C. Tague, A. Jefferson. 2010. Streamflow Response to Climate Warming in Mountainous Regions: Integrating the Effects of Snowpack and Groundwater Dynamics. MTNCLIM 2010 Mountain Climate Research Conference. Blue River, Oregon

Koehler, R. 2004, Raster-based Analysis and Visualization of Hydrologic Time-Series. Ph.D. dissertation, University of Arizona. Tucson, AZ, 189p.

Koehler, R. 2007. An Alternative Approach to Measuring Hydrologic Change; A Comparison Study Between Raster-Based Analysis and "Indicators of Hydrologic Alteration". Hydrology Days AGU regional conference. Colorado State University. Ft. Collins, CO

Long, K. S. 1994. Time Scale Analysis Can Assess Hydrologic Cumulative Impacts. WRP Technical Note HY-IA-2.2. U.S. Army Engineer Waterways Experiment Station, Vicksburg, MS.

McDonald, Alyson. 2010. Hydrologic Impacts of Saltcedar Control Along a Regulated Dryland River. Ph.D. Dissertation, Texas A&M University, College Station, TX

McGarigal, K., SA Cushman, and E Ene. 2012. FRAGSTATS v4: Spatial Pattern Analysis Program for Categorical and Continuous Maps. UMass Amherst, MA.

Moore, S.K., et al., 2009. Recent trends in paralytic shellfish toxins in Puget Sound, relationships to climate, and capacity for prediction of toxic events. Harmful Algae 8, 463–477 doi:410.1016/ j.hal.2008.1010.1003.

Olden, J.D., and N.L. Poff. 2003. Redundancy and the choice of hydrologic indices for characterizing streamflow regimes. River Research and Applications 19:101-121.

Strandhagen, E., Marcus, W.A., and Meacham, J.E. 2006. Views of the rivers: representing streamflow of the greater Yellowstone ecosystem. Cartographic Perspectives, no. 55, Fall.

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