Fine-Resolution, Regional-Scale Terrestrial Hydrologic Fluxes Simulated with the Integrated...
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![Page 1: Fine-Resolution, Regional-Scale Terrestrial Hydrologic Fluxes Simulated with the Integrated Landscape Hydrology Model (ILHM) David W Hyndman Anthony D.](https://reader038.fdocuments.us/reader038/viewer/2022110213/5697bf991a28abf838c91639/html5/thumbnails/1.jpg)
Fine-Resolution, Regional-Scale Terrestrial Hydrologic Fluxes
Simulated with the Integrated Landscape Hydrology Model
(ILHM)
David W Hyndman
Anthony D Kendall
![Page 2: Fine-Resolution, Regional-Scale Terrestrial Hydrologic Fluxes Simulated with the Integrated Landscape Hydrology Model (ILHM) David W Hyndman Anthony D.](https://reader038.fdocuments.us/reader038/viewer/2022110213/5697bf991a28abf838c91639/html5/thumbnails/2.jpg)
Unprecedented Changes
Pijanowski (Purdue)
Land Use Change
IPCC AR4
Climate Change Land Use Intensification
USCB and USDA
![Page 3: Fine-Resolution, Regional-Scale Terrestrial Hydrologic Fluxes Simulated with the Integrated Landscape Hydrology Model (ILHM) David W Hyndman Anthony D.](https://reader038.fdocuments.us/reader038/viewer/2022110213/5697bf991a28abf838c91639/html5/thumbnails/3.jpg)
Integrated Landscape Hydrology Model (ILHM)
– Integrates 4 domains of hydrologic modeling
– Intended for large-scale, fine-resolution simulations
– Modular code, readily expandable– Readily incorporates GIS, remote sensing inputs
![Page 4: Fine-Resolution, Regional-Scale Terrestrial Hydrologic Fluxes Simulated with the Integrated Landscape Hydrology Model (ILHM) David W Hyndman Anthony D.](https://reader038.fdocuments.us/reader038/viewer/2022110213/5697bf991a28abf838c91639/html5/thumbnails/4.jpg)
Muskegon River Watershed, MI
– ~7400 km2
– Climate & ecological gradients• Lake effect precipitation• Deciduous/Mixed transition
– Major historical land use change• Forest Agriculture• Agriculture Forest and Urban
![Page 5: Fine-Resolution, Regional-Scale Terrestrial Hydrologic Fluxes Simulated with the Integrated Landscape Hydrology Model (ILHM) David W Hyndman Anthony D.](https://reader038.fdocuments.us/reader038/viewer/2022110213/5697bf991a28abf838c91639/html5/thumbnails/5.jpg)
Expanded Model Domain
– ~19,000 km2
• 100 to 400m grid cells
– 28-year simulation• 1980 – 2007• Hourly timesteps
![Page 6: Fine-Resolution, Regional-Scale Terrestrial Hydrologic Fluxes Simulated with the Integrated Landscape Hydrology Model (ILHM) David W Hyndman Anthony D.](https://reader038.fdocuments.us/reader038/viewer/2022110213/5697bf991a28abf838c91639/html5/thumbnails/6.jpg)
Select Input Data Types
– GIS Inputs• Land use• Soil texture• Subsurface geologic maps• Elevation map
– Gage climate data• Precipitation• Solar radiation• Windspeed• Relative humidity• Air/soil temperatures
– Distributed remotely sensed inputs• NEXRAD precipitation• Satellite Leaf Area Index (LAI)
![Page 7: Fine-Resolution, Regional-Scale Terrestrial Hydrologic Fluxes Simulated with the Integrated Landscape Hydrology Model (ILHM) David W Hyndman Anthony D.](https://reader038.fdocuments.us/reader038/viewer/2022110213/5697bf991a28abf838c91639/html5/thumbnails/7.jpg)
Uncalibrated Streamflow Predictions
– Baseflows well simulated, regardless of scale – some regional bias– Total discharge error less than 6% of annual precipitation
43 sq. km
629 sq. km
3711 sq. km
![Page 8: Fine-Resolution, Regional-Scale Terrestrial Hydrologic Fluxes Simulated with the Integrated Landscape Hydrology Model (ILHM) David W Hyndman Anthony D.](https://reader038.fdocuments.us/reader038/viewer/2022110213/5697bf991a28abf838c91639/html5/thumbnails/8.jpg)
ET and Recharge Averages (1980 – 2007)
– Highly spatially variable• Soils, land use, climate variability
– Recharge strongly sensitive to lake-effect precipitation
![Page 9: Fine-Resolution, Regional-Scale Terrestrial Hydrologic Fluxes Simulated with the Integrated Landscape Hydrology Model (ILHM) David W Hyndman Anthony D.](https://reader038.fdocuments.us/reader038/viewer/2022110213/5697bf991a28abf838c91639/html5/thumbnails/9.jpg)
Monthly Watershed-Average Fluxes
– 2 annual recharge pulses: snowmelt/spring & early fall– ET dominates during the growing season– Storage in snowpack and soil are important to dynamics
![Page 10: Fine-Resolution, Regional-Scale Terrestrial Hydrologic Fluxes Simulated with the Integrated Landscape Hydrology Model (ILHM) David W Hyndman Anthony D.](https://reader038.fdocuments.us/reader038/viewer/2022110213/5697bf991a28abf838c91639/html5/thumbnails/10.jpg)
Preliminary Climate Change Scenarios
– Average of 24 GCM outputs• A1B, A2, & B1 scenarios
– Offset observed data using modeled anomalies
![Page 11: Fine-Resolution, Regional-Scale Terrestrial Hydrologic Fluxes Simulated with the Integrated Landscape Hydrology Model (ILHM) David W Hyndman Anthony D.](https://reader038.fdocuments.us/reader038/viewer/2022110213/5697bf991a28abf838c91639/html5/thumbnails/11.jpg)
Changes to Groundwater Recharge
– Average 2090 - 2099– More frequent
snowmelt in all scenarios• Smaller persistent
snowpack• Reduced spring
recharge
– Less fall recharge
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Climate Change Implications
– Higher spring water tables
– More frequent spring floods
– More seasonal wetlands
– Earlier decline of summer water table
– Lower summer baseflows
– Longer low-flow period
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Summary
– Good predictions without site-specific calibration– Variability is the rule:
• Groundwater recharge typically treated as a static input in groundwater models
• Strong spatial and temporal variability at all scales• Even 425 m resolution here not sufficient to fully
describe land use and soils
– Gradients in precipitation and temperature well below typical climate model resolutions• Lake effect not well described by climate models