Knowledge base session2 p_claggett
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Transcript of Knowledge base session2 p_claggett
• U.S. Department of the Interior• U.S. Geological Survey
Peter Claggett, Fred Irani, Renee Thompson, and David Donato
October 29, 2013Delaware Watershed Forum
Modeling Urbanizationin the
Chesapeake Bay Watershed
Chesapeake Bay Watershed, U.S.A.
Future Population in Chesapeake Region
IPCC SRES
1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 21000
10,000,000
20,000,000
30,000,000
40,000,000
50,000,000
60,000,000
A2B2A1B1Trend
Year
Po
pu
lati
on
(m
illio
ns
)
The Chesapeake Bay Land Change Model (CBLCM)
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.
Purposes:
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.
The Bay TMDL: A Restoration Blueprint
1940 Housing Density1950 Housing Density1960 Housing Density1970 Housing Density1980 Housing Density1990 Housing Density2000 Housing Density
Updated analysis following methods outlined by Hammer, et al., 2004.
2010 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
How does the CBLCM work?Population
ProjectionsEmployment Projections
Residential and Commercial Land Demand
Urban-----------Suburban---------------Rural
Density Assumptions
Land Suitable for development
Housing Projections
Infill/Redevelopment
US Census 1980 - 2010
Fine-scale Allocation and Simulation of Development
DevelopmentLocation, Extent, and
Patterns1984 - 2006
Probability of development
Factors Affecting Location of Growth
Probability (yr. 2010)
Legend
thu00_dens2.img
ValueHigh : 16.8061
Low : 0.00213435Low
High
Prince George’s County
Anne ArundelCounty
Housing Density(yr. 2010)
Housing Density(yr. 2100)
Legend
thu00_dens2.img
ValueHigh : 16.8061
Low : 0.00213435Low
High
Prince George’s County
Anne ArundelCounty
2010202020302040205020602070208020902100
Prince George’s County
Anne ArundelCounty
2100 v12100 v22100 v32100 v42100 v52100 v62100 v72100 v82100 v9…2100 v100
Prince George’s County
Anne ArundelCounty
Future Development (2040)Trend: Simulation #1
Future Development (2040)Trend: Simulation #2
Green Infrastructure (2006)Green Infrastructure (2040)Trend: Simulation #1
High
Low
Suitability
Green Infrastructure (2040)Trend: Simulation #2
Anne
Aru
ndel
Balti
mor
e
Calv
ert
Carr
oll
Cecil
Char
les
Fred
erick
Harf
ord
How
ard
Mon
tgom
ery
Prin
ce G
eorg
e's
St. M
ary'
s
Balti
mor
e
Adam
s
Berk
s
Ches
ter
Daup
hin
Lanc
aste
r
Leba
non
York
0
20,000
40,000
60,000
80,000
100,000
120,000
140,000
160,000
180,000
Core Forest Extent Pre- and Post-Development
yr. 2006 extentyr. 2040 extentA
cres
* Based on 23 simulations and use of the GUIDOS software. Brackets represent +/- 2 standard deviations from the mean
Chesapeake Bay Alternative Future Development Scenarios
Land-UsePlanning
Land Conservation
TREND
Weak
Strong
Weak Strong
SustainableChesapeake
Conserve Green
Infrastructure
Infill &Redevelopment
Laissez-Faire
Rural Down-zoning
BaselineInfillForest Conservation
Farmland Conversion to Development2006 - 2025
Baseline: - 433,347 acresInfill: - 377,931 acresConservation: - 468,738 acres
Farmland Loss
BaselineInfillForest Conservation
Forest & Wetland Conversion to Development2006 - 2025
Baseline: - 441,724 acresInfill: - 352,648 acresConservation: - 408,427 acres
Forest Loss