RASTER-BASED ANALYSIS APPLIED TO CLIMATIC AND HYDROLOGIC TIME-SERIES

Drought directly affects surface water and streamflow volumes, influencing annual, seasonal and daily discharge patterns. These patterns determine many of the physical and biological properties of a stream. Natural short- and long-term variation of streamflow is part of the normal response to climate whereas artificial fluctuations can disrupt the natural processes of a river.

Recognizing and discriminating natural drought variations from artificial fluctuations and disturbances within the streamflow record is critical to understanding river systems and thus developing management efforts to achieve more natural flow regimes. This is especially important when water resources are reduced during drought periods or decreased due to high demand.

A new procedure using dual timescale graphs is presented to visualize key water resources parameters such as streamflow, snow water equivalent, temperature, or drought index characteristics across various timescales. Daily, weekly, seasonal, annual and interannual patterns for a parameter are easily recognized on a single graph.

When multiple graphs are shown, temporal and spatial variability are displayed simultaneously. Such graphs are useful in the following ways:

1) Obtaining new and additional information from historic records,

2) Identifying the characteristics of magnitude, frequency, duration, timing, and distribution for any hydrologic event of interest,

3) Showing streamflow response to climatic conditions,

4) Using visual techniques to summarize the water resources of an area,

5) Observing the hydrologic effects of public policy actions, and

6) Facilitating communication across disciplines of social and natural scientists, resource managers, policy makers, and the general public by showing the observed data of interest.

Example graphs were developed from two large snowmelt dominated river systems in the western United States, the Upper and Middle Snake River and Upper Colorado River Basins. Data from select U.S. Geological Survey (USGS) streamflow stations were used along with National Oceanic and Atmospheric Administration (NOAA) drought indices, and Natural Resources Conservation Service (NRCS) snow courses and SNOTEL sites.