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Changes in the fate and partitioning of water at the pedon to catchment scale as a consequence of Mountain Pine Beetle induced tree mortality in Lodgepole Pine ( Pinus Contorta ) forests. Adrian Harpold, Paul Brooks, Joel Biederman , David Reed, Ethan Gutmann , and David Gochis.
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Changes in the fate and partitioning of water at the pedon to catchment scale as a consequence of Mountain Pine Beetle induced tree mortality in Lodgepole Pine (PinusContorta) forests. Adrian Harpold, Paul Brooks, Joel Biederman, David Reed, Ethan Gutmann, and David Gochis
Research Question and Hypotheses • Research Question: • How does the fate and partitioning of water differ between healthy and MPB-effected forests at the pedon to small catchment scale? • Hypotheses: Increased solar radiation on the ground/snow surface and increased turbulence following tree die-off will cause (or framed as the alternative hypotheses that water yields, soil moisture will go up following pine beetle attack): • Increased sublimation from the snowpack in MPB-effected stands and similar SWE:P ratios in healthy and MPB-effected forests (Joel’s findings), • Increased evaporation of soil water in MPB-effected stands and similar water vapor losses in healthy and MPB-effected forests.
Figure 1: Site Overview • Need to show several scales at CP site to capture all relevant instrumentation
Table 1: Site characteristics • Mostly Joels tables, plus additional met and soils data
Figure 2: Time series of climate/forcing • The story hinges around similar forcing and climate, so time series of • Precip and snow depth • Solar radiation • Temperature • Vapor pressure deficit • Wind
Figure 3: Precipitation isotopes and LMWL • These lines are used in subsequent figures. Both sites LMWL differ slightly from the GMWL. CP’s LMWL has a slope of 7.94 and intercept of 12.9, suggesting that it is slight enriched in deterium (colder site or weather patterns). The NWT site has a slope of 7.84 and an intercept of 6.4. Both site produce similar LMWL slopes with snow and rain data, but differ in their deterium excess (they are smaller than what Joel shows for snow only).
Figure 5: Snowpack isotopes (adapted from Biderman et al., 2012) • Basically a rip-off from Joel’s paper, but I think its an important point to make, SWE:P is around 0.7 and at least 15% of those losses are sublimation.
Figure 6: Soil moisture and isotope profiles • I want to show the isotopic evolution of the soil water profile to show 1. the sites are similar, 2. how the wetting front changes (the shape of this curve indicate the evaporation rate). The green figures are closer to legible (might want to reverse x-axes). I think this is cool data and better than showing it as a time series, like figure 8 and 9 do for the surface and GW. • The data show relative consistent soil isotope profiles (both with depth and between sites) during snowmelt (defined as when the water table is within the soil profile). During the growing-season and later into the fall the water becomes enriched due to a combination of evaporation and transpiration and mixing with more enriched precip.
Figure 7: Soil water evaporation lines • The soil water evaporation lines, where applicable, in healthy (a,d,g), infested pre 2008 (b,e,h), and infested in 2008/2009 (c,f,i) at depths of 10, 30, and >60 cm. The 10 cm depth shows evidence of evaporation at the impacted sites (b,c) with slopes of 5.7 to 6.9, corresponding to relative humidity greater than 90%. The deeper 30 and 60 cm water is also enriched relative to the LMWL, but no clear evaporation trends, suggesting the wetting front never passed 30 cm? In contrast the healthy forest has no evaporation signal at shallow depths and all samples plot on the LMWL.
Figure 8: Shallow GW timing and evap lines • Again, this figure needs some work and could be divided, but look at the green figures for formatting. • This figure shows the timing of shallow groundwater head and stable isotope response at the three sites, as well as the evaporation lines at the sites. The isotope response at NWT reflects a deeper and slower responding regional groundwater table that lags the head response and plots with deuterium excess relative to the LMWL. In contrast the impacted sites reflect the shallower and faster responding hydrology at CP, but also indicate that the soil water evap signal is likely propagated to the shallow GW.
Figure 9: Surface water timing and evap lines • Similar to Figure 8: • Not sure how to plot discharge at Niwot? • May just have evap figure.
Figure 10: Summary of data (snowmelt and post snowmelt) vs LMWL • This figure shows the average values (with 1 stddev error bars) for the soil, shallow groundwater, surface water, and precipitation. The data are divided into snowmelt (when water tables are with 2 m of the surface) and post-snowmelt. I will work to make them easier to see. • There is much less variability and deviation from the LMWL during snowmelt. The average 018 in the grey and red stands is 1-2%. heavier than the LMWL and consitent with sublimated snowpack values, whereas soil water in green stands plot on the LMWL. Post snowmelt all the soil water becomes enriched in heavy isotopes, but only impacted stands suggest evaporation. The shallow groundwater and surface water are similar during snowmelt and post-snowmelt, suggesting that the pulse of snowmelt sustains ground and surface water through the growing season.
Table 2: Water balance calculations • This is the last missing pieces of data to add. My hope is that we can have independent measurements of soil evap and transpiration the compare those to the ET flux at the towers (as to not rely on those estimates directly). • I’m also not sure how to hand runoff because our measurements are not comparable at the two sites. The data also indicate that the bulk of the shallow GW and surface water is from upslope snow water (ie regional GW) at NWT so these data are hard to interpret. My suggestion is to estimate a Q for CP and compare that Bied and Bear and estimate a Q+Recharge for Niwot. Estimating water fluxes using GW head is very problematic at NIWOT because the regional water table gradient changes direction over the season. My approach is to minimize the reliance on runoff data by assuming Q=P-Sublimation-E-T, which will be the pedon scale water subsidy term, which we will compare to catchment Q.
Figure 11: Water balance bar chart • All of this data is made up except P, sublimation, and measured Q. See previous slide for how I plan to calculate these. This is really the key figure showing clearly how the water balance could change after beetle infestation. This will allow us to clear talk about compensating factors on vapor fluxes.
