Knowledge base session2 p_claggett
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  • EGSC has compiled census housing data from 1940 to 2010 for the entire Bay watershed to inform the reconstruction of historical residential land uses. NAQWA is compiling historical agricultural census data to further support the modeling of historic land uses in the Bay watershed.

Knowledge base session2 p_claggett Knowledge base session2 p_claggett Presentation Transcript

  • Modeling Urbanization in the Chesapeake Bay Watershed Peter Claggett, Fred Irani, Renee Thompson, and David Donato October 29, 2013 Delaware Watershed Forum •U.S. Department of the Interior •U.S. Geological Survey
  • Chesapeake Bay Watershed, U.S.A.
  • Future Population in Chesapeake Region 60 Population (millions) 50 40 IPCC SRES A2 30 B2 A1 B1 Trend 20 10 0 1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 Year
  • The Chesapeake Bay Land Change Model (CBLCM) Purposes: 1. To provide the specific land-use data input needs for the Watershed Model, accommodating the best available regional data. 2. To inform restoration strategies and policies through simulating alternative future land use scenarios.
  • The Bay TMDL: A Restoration Blueprint Total Maximum Daily Load (TMDL) allocation: The amount of nitrogen, phosphorus, and sediment that the Chesapeake Bay can receive while sustaining water clarity, dissolve oxygen, and chlorophyll-a levels that support living resources. States and localities are required to implement Best Management Practices to reduce nutrient and sediment loads by 2025. States and localities are required to maintain reductions forever.
  • 2010 2000 1990 1980 1970 1960 1950 1940 Housing Density Counties Chesapeake Bay Census Total Housing Units Units per Acre 0.0 - 0.1 0.2 0.3 - 0.5 0.6 - 1.0 1.1 - 2.0 2.1 - 3.0 3.1 - 5.0 5.1 - 10.0 10.1 - 75.3 0 Updated analysis following methods outlined by Hammer, et al., 2004.
  • How does the CBLCM work? Population Projections Housing Projections Employment Projections Infill/ Redevelopment Density Assumptions Land Suitable for development Residential and Commercial Land Demand Factors Affecting Location of Growth US Census 1980 - 2010 Urban-----------Suburban---------------Rural Development Location, Extent, and Patterns 1984 - 2006 Probability of development Fine-scale Allocation and Simulation of Development
  • Value Probability (yr. 2010) High : 16.8061 High Anne Arundel County Low Low : 0.00213435 Prince George’s County
  • Value Housing Density (yr. 2010) 2100) High : 16.8061 High Anne Arundel County Low : 0.00213435 Low Prince George’s County
  • 2100 2090 2080 2070 2060 2050 2040 2030 2020 2010 Prince George’s County Anne Arundel County
  • 2100 v1 v100 v9… v8 v7 v6 v5 v4 v3 v2 Anne Arundel County Prince George’s County
  • Future Infrastructure (2006) Green Development (2040) Trend: Simulation #1 #2 Suitability High Low
  • Core Forest Extent Pre- and Post-Development 180,000 * Based on 23 simulations and use of the GUIDOS software. Brackets represent +/- 2 standard deviations from the mean 160,000 140,000 120,000 100,000 80,000 yr. 2006 extent yr. 2040 extent 60,000 40,000 20,000 York Lebanon Lancaster Dauphin Chester Berks Adams Baltimore St. Mary's Prince George's Montgomery Howard Harford Frederick Charles Cecil Carroll Calvert Baltimore 0 Anne Arundel A c r e s
  • Chesapeake Bay Alternative Future Development Scenarios Strong Infill & Redevelopment Land-Use Planning Sustainable Chesapeake Rural Downzoning TREND LaissezFaire Conserve Green Infrastructure Weak Weak Land Conservation Strong
  • Farmland Conversion to Development 2006 - 2025 Forest Infill Conservation Baseline Farmland Loss Baseline: - 433,347 acres Infill: - 377,931 acres Conservation: - 468,738 acres
  • Forest & Wetland Conversion to Development 2006 - 2025 Forest Infill Conservation Baseline Forest Loss Baseline: - 441,724 acres Infill: - 352,648 acres Conservation: - 408,427 acres