Characterizing the Hydrologic Variability of Meadows in the San Bernardino Mountains Abby Dimicco, Kayla Smith, Dr. Hillary Jenkins abrielle_dimicco@redlands.edu, kayla_smith@redlands.edu University of Redlands, Department of Environmental Studies, 1200 E. Colton Ave, Redlands, CA 92374
I. Abstract Climate is changing in Southern California. Climate models predict an increase in the frequency of extremely wet and extremel y dry seasons, creating whiplash events that impact groundwater availability. Meadows are grassland ecosystems with shallow (<2 meters) water tables that provide key ecosystem services and act as early indicators of forest hydrologic health. Because meadows are early warning signs, we use them here to assess the effect of an ever-changing climate on forest health in the San Bernardino Mountains. In this study we characterize the hydrology of 4 meadow sites, using piezometers at each site to measure the water table depth and compare this with climate variables over multiple temporal and spatial scales. Piezometer data includes discrete po int data (established and collected in the summer of 2022) and historical data (data loggers that measure depth to water every 30 minu tes in Bluff and Lodgepole) and point data (collected by previous students in the summers of 2015, 2017, 2019, and 2021). After analyzing this data, we found that Broomflat is the driest and least hydrologically healthy, Lodgepole is the wettest and most healthy, while Bluff (proximal to Lodgepole) and Wildhorse are moderately healthy. Bluff and Lodgepole show seasonal variability reflective of connection with climate, although Bluff does not exhibit strong connection with precipitation in recent years, likely the result of a decline in hydrology health. Bluff and Lodgepole are well represented by a water balance model that includes evapotranspirati on, temperature, radiation, relative humidity, rain and snowfall; however, a strong correlation between river incision and water table depth may explain intrameadow variability. This suggests that meadows with incised river systems are more likely to lose water and become hydrologically distressed. We find evidence that precipitation correlates well with Lodgepole Meadow in 2022, but Bluff, Wildhorse, and Broomflat Meadows are no longer responding to precipitation. Understanding this hydrologic variability in montane meadows provides important context for how forest ecosystems in Southern California will adapt to a changing climate.
III. Healthy VS Unhealthy Meadow
IV. Results 1. Can we characterize the spatial and temporal variability of meadow hydrology in the San Bernardino Mountains?
Spatial Variability Depth to Water (mm)
Bluff Lodgepole
8C Wildhorse
Figures 8A, B, and C: Spatial Interpolation of Water Table Depth of Lodgepole and Bluff (8A), Wildhorse (8B), and Broomflat (8C) Meadows during June 2022. Blue colors (negative values) mean the water table is above the land surface while red colors (positive values) denote a water table that is drier and further from the surface. Points represent the locations of piezometers installed in each meadow. All piezometers in Wildhorse and Broomflat were installed during this research project.
II. Field Methods
Temporal Variability
• Lodgepole and Bluff are characterized by a shallow water table while Broomflat exhibits the deepest water table, although all 4 meadows show variability from West to East.
Figure 1: Map of Lodgepole, Bluff, Wildhorse, and Broomflat Meadows in relation to the University of Redlands Figures 9 & 10: Temporal Graph of Lodgepole & Bluff Water Table Depths at Each Piezometer Location between November, 2021 and June, 2022.
Piezometers installed in 4 Meadow Sites to Measure subsurface Hydrology
2. What drives groundwater variability in meadows?
Bluff
Inputs- rainfall & snowfall
Water Balance • Inputs = Outputs + Change in Storage
• When inputs exceed outputs, water is added to the system
Lodgepole
Change in storage
calculated after Dyer, 2015 following Turc (1961)
Outputsevapotranspiration Figure 11: Water Balance Diagram
Figure 2: Map of Lodgepole Meadow and Bluff Meadow with piezometer locations
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Lodgepole - 13 piezometers Bluff - 11 piezometers Offloaded data from HOBO water level loggers Measured temp & humidity Measured water table depth with water level meter
Calculating Water Loss Inputs = Rain + Snow vs. Outputs = Evapotranspiration
Used temperature, humidity, and radiation to calculate ET Used water balance to Water Lost = (Rain + Snow) – ET calculate water loss • Used water loss to model WT(i) =WT(i-1) + WaterLost(i) water table depth
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Modeling the Water Table
River Incision
• Incision also drives groundwater availability
Figure 3: Map of Broomflat Meadow with piezometer locations
• Built 30 piezometers • Installed 15 piezometers in Broomflat and 15 in Wildhorse • Drilled w/ automatic auger & manual auger • Inserted piezometer into ground • Measured out wire & attached HOBO logger to one end and cap to other end • Inserted logger into piezometer
V. Conclusions 1. Can we characterize the spatial and temporal variability of meadow hydrology in the San Bernardino Mountains? • Yes! There is less water table variability in Lodgepole & more rapid fluctuation in Bluff over seasonal times scales (November to June) • We can rank all 4 meadows from most to least Hydrologically Healthy:
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1. Lodgepole
2. Bluff
3. Wildhorse
4. Broomflat
2. What drives groundwater variability in meadows?
3. How reliant are meadow ecosystems on seasonal water availability? Is this degradation dependent?
• Larger incision=deeper water table= less healthy Figure 12: River Incision of Wet and Dry season at each Piezometer Location at Bluff & Lodgepole
Wildhorse
Figure 7: water table diagram retrieved from livescience.com
• Climate (Inputs of Precipitation and Snowfall versus Output of Evapotranspiration) • River Morphology (greater incision leads to water loss)
• River Incision Index: function of depth to water & proximity to well location
Broomflat
Unhealthy Meadow • Reduced storage of water • Deep water table • Dry vegetation • Deeper river incision
• shallow = wet • deep = dry
• Over Time, wells in Bluff and Lodgepole follows similar patterns across each meadow • More water table variability in Bluff and less variability in Lodgepole
Bluff
Lodgepole
• • •
Healthy Meadow • Surface flow from precipitation or runoff • Shallow water table • Percolation & groundwater recharge
8B
8A
Figure 6: unhealthy meadow diagram retrieved from nps. gov
Figure 5: healthy meadow diagram retrieved from nps. gov
Broomflat
Figure 13: Model of Water Table Depth (red) based on Water Balance Model compared with Actual Depths in Bluff (yellow) and Lodgepole (blue)
3. How reliant are meadow ecosystems on seasonal water availability? Is this degradation dependent?
Figure 4: Map of Wildhorse Meadow w/ piezometer locations
• Healthy meadows are reliant; unhealthy meadows are not • If you distress a meadow enough, it alters dependence on climate variables (more precipitation will not save meadow) • Meadow-Climate connection broken
• Precipitation drives groundwater variability
VI. Acknowledgements
• Lodgepole follows precipitation • Bluff, Broomflat, and Wildhorse not responding to precipitation (not reliant on precipitation) Figure 14: Bluff & Lodgepole Depth to Water Compared to Precipitation
Figure 15: Average Water Table Depth of Each Meadow Compared to Precipitation Rates from 2015-2022
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Advisor: Professor Hillary Jenkins U.S. Fish & Wildlife Forest Service Wildlands Conservancy Donor: Mrs. Lea Summer Science Research Program