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Fine-Resolution Hydrologic Flux Modeling of the Muskegon River Watershed Using ILHM

This study employs the Integrated Landscape Hydrology Model (ILHM) to simulate terrestrial hydrologic fluxes in the Muskegon River Watershed (~7400 km²). The model integrates multiple domains for large-scale, fine-resolution analysis. Detailed input data, including land use, soil texture, and climate variables, supports the model's eight-year simulation from 1980 to 2007. Findings highlight the impacts of land use change and climate variability on groundwater recharge, precipitation patterns, and seasonal water table dynamics. The preliminary climate change scenarios indicate potential shifts in hydrology through increased flooding and changes in recharge rates by the year 2090.

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Fine-Resolution Hydrologic Flux Modeling of the Muskegon River Watershed Using ILHM

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  1. Fine-Resolution, Regional-Scale Terrestrial Hydrologic Fluxes Simulated with the Integrated Landscape Hydrology Model (ILHM) David W Hyndman Anthony D Kendall

  2. Unprecedented Changes Land Use Intensification Climate Change Land Use Change USCB and USDA IPCC AR4 Pijanowski (Purdue)

  3. 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

  4. 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

  5. Expanded Model Domain • ~19,000 km2 • 100 to 400m grid cells • 28-year simulation • 1980 – 2007 • Hourly timesteps

  6. 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)

  7. Uncalibrated Streamflow Predictions 3711 sq. km • Baseflows well simulated, regardless of scale – some regional bias • Total discharge error less than 6% of annual precipitation 629 sq. km 43 sq. km

  8. ET and Recharge Averages (1980 – 2007) • Highly spatially variable • Soils, land use, climate variability • Recharge strongly sensitive to lake-effect precipitation

  9. 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

  10. Preliminary Climate Change Scenarios • Average of 24 GCM outputs • A1B, A2, & B1 scenarios • Offset observed data using modeled anomalies

  11. Changes to Groundwater Recharge • Average 2090 - 2099 • More frequent snowmelt in all scenarios • Smaller persistent snowpack • Reduced spring recharge • Less fall recharge

  12. 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

  13. 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

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