Retrospective analysis of low flows at headwater watersheds in Wyoming
Understanding summer low-flow variability and change in the mountainous West has important implications for water allocations downstream and for maintaining water availability for drinking water supply, reservoir storage, industrial, agricultural, and ecological needs. Wildfires and insect infestations are classical disturbance hydrology topics. It is unclear, however, what are their effects on streamflow and in particular low-flows, when vegetation disturbances are overlapping in time and combined with highly variable and potentially changing local climate. The purpose of this study, therefore, is to quantify changes in low-flows resulting from disturbance in headwater streams.
Here we present a retrospective analysis based on: (1) 49-75 complete water years (wy) of daily streamflow data (USGS) for 14 high-elevation headwater watersheds with varying areas (60-1730 km2, 86-100% of watershed area >2000masl) and evergreen forest cover (15-82%), (2) 25-36 complete wy of daily snow-water equivalent accumulation (SWE) and precipitation data from Wyoming SNOTEL stations, (3) burned area boundaries for 20wy (MTBS project), (4) aerial surveys by R1, R2, R4 Forest Service Regions for 18wy (data on tree mortality).
We quantify the change in various low-flow characteristics (e.g. post-snowmelt baseflow, Q90 and Q95, 3-,7-, 30- and 90-day annual minima etc.) while accounting for local inter- and multi-annual climate variability by using SWE accumulation data, as it integrates both temperature and precipitation changes. Our approach differs from typical before-after field-based investigation for paired watersheds, as it provides a synthesis over large temporal and spatial scales, resulting in spectrum of possible hydrologic responses due to varying disturbance severity.
Quantifying the changes in low-flows and low-flow variability will improve our understanding and will facilitate water management and planning at local state-wide level.
(the text is as appears @ AGU2016 conference site)
Original poster size: 170 x 101 cm
From my 14 watersheds, North Brush is the one with the highest tree mortality footprint. On the lower map I have shown the tree mortality footprint due to different mortality agents. The Mountain Pine Beetle is the main cause of tree mortality at this watershed, but these areas are overlapping with the areas affected by Spruce Beetle and fir mortality. Additionally, the forest in this watershed is managed, I am also showing the clear-cut and patch cut footprints (upper map).
These forest disturbances are shown together with the 7-day minima and the peak SWE z-score on the same time-line. The graph shows the anomalies above/below the long-term mean, expressed in standard deviations. The lines are centered 5-year moving averages based on the annual data (the bars). La Nina and El Nino years are also indicated because at that time we (Scott Miller & I) were discussing ENSO effects on our local climate & hydrology.
Left: I am showing the timeline with vegetation disturbances. The new area with tree mortality per year is with green, the areas with clear-cut and partial cut (forest management) are with yellow, and the wildfires are with red color. I have plotted them on the same time-line and same y-scale (% area from the watershed). In this detail I am showing only the graphs for the top 3 disturbed watersheds: North Brush, Rock Creek, and Hams Fork, while overview for all 14 can be found in the poster.
Right: This detail shows the timing and proportion of baseflow and snowmelt-dominated runoff for all 14 watersheds (y-axis, 1-14). The timing and runoff proportion (x-axis) for the three distinctive runoff periods are visualized with cyan (pre-snowmelt), blue (snowmelt), and green (post-snowmelt). The timing and runoff proportion are expressed as long-term mean and standard deviation.
This is probably my favorite figure from this poster, because it visualizes that on average for these 14 high-elevation headwater watersheds in Wyoming, about 80% of the annual runoff passes through the gauging station within 2-3 months when the annual snowmelt event is.
1. National Science Foundation (EPS 1208909) though the Wyoming Center for Environmental
Hydrology and Geophysics (WyCEHG) [project funding]
2. University of Wyoming Office of Research and Economic Development [project funding]
3. Wyoming Women in Science and Engineering (WWISE) program [travel grant]
4. Wyoming Center for Environmental Hydrology and Geophysics (WyCEHG), funded by NSF EPS 1208909 [additional travel funding]