the land and water connection
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The Land and Water Connection
The Pocono Kittatinny Cluster
• Conservation Cluster
• Goal: Maintain Water Quality
• Target: Big Woods, Clean Streams, Undisturbed Wetlands
Focus Areas selected per results of NLT, TNC, NFWF, USFS
Goal.
Target those Ecologically Significant Lands that are most important to the maintenance of
Healthy Waters
Ecologically Significant Lands“Headwaters, Wetlands, Floodplains”
Healthy Waters“Fishable, Swimmable, Drinkable”
How do we identify those ecologically significant lands that provide the most benefit to maintaining water quality?
What have others looked at:
USFS Forests to Faucets
Conservation Priority Index
Ability to Produce Clean Water (Forest, Ag, Rip For Cover, Rd Density, Soil Erodibility, Housing Density)
Land Use
Importance for Drinking Water Supply
Distance to Streams and Wetlands
Dependence on Private Forestlands
Soils (depth & permeability)Slope
Threat of forest conversion or poor management
Projections of Future Housing Density
From the Forest to the Faucet: Identifying the Connections of Forests, Water and PeopleRebecca WhitneyU.S. Forest Service Northeastern Area S&PF, 2007
Natural Infrastructure: Investing in Forested Landscapes for Source Water ProtectionWorld Resources Institute, 2013
Size Forest (habitat) Condition Land Cover
Percent Impervious Cover (parcel and floodplain) Feet/Miles of Riverfront Wetland and Floodplain Abundance Development Potential (modeled Impervious
Cover) Ecological Significance
Pocono Kittatinny Cluster Draft Metrics
Finding the Balance
Resiliency Groundwater Soils Slopes Relating to Water Uses (wellhead protection
areas, proximity to surface water intakes, etc.)
Other Metrics for Consideration
Watershed Modeling Soil and Water Assessment (SWAT) Generalized Watershed Loading Function Hydrological Simulation Program – Fortran (HSPF)
Combining with Economic Modeling Resource Investment Optimization System (RIOS) Resources for the Future
Requirements: Expertise, Extensive Data, Calibration(Capacity and Time)
Other Methods --Models
We don’t know the exact connection between land protection and water quality…..
(how much, where, what configuration)
We acknowledge the uncertainty
“We are now looking to set priorities using the best available knowledge and
data”
State of the Science
Peter Howell
Discussion
Evaluate the Landscape’s Ability to Maintain Water
Quality• Percent Impervious Cover• Terrestrial & Aquatic
Habitat Condition• Wetland, Riparian, &
Floodplain Density
Identify Significant Headwaters and Floodplains•Ensure Conservation Benefits Accrue to Meaningful Level•Compare to other Studies
Evaluate Project Constraints and Opportunities• Percent Match
Available• Total Capital
Needed & Cost/Acre • Probability of
Protection in 3-yrs
Methods
Network Complexity – Number of size classes
Physical Diversity– Length of connected linear miles– Diversity of Temperatures– Diversity of Gradients
Ecological Condition– Lateral connectivity – naturalness of
floodplain– Unimpeded flow– Pervious /permeable watersheds
© Anderson and Olivero, The Nature Conservancy
Resilience: Definition The capacity for renewal in a dynamic environment
- Gunderson 2000 The ability of a social or ecological system to absorb disturbances while retaining the same basic structure and ways of functioning
- IPCC 2007
Certain datasets are limited and/or inconsistent across state lines
Knowledge is limited and inconsistent in defining ecologically significant thresholds in most measured variables
Single indices do not address synergy of different threats
Multi-variable indices can begin to estimate the synergy of different threats, but assigning weights and how variables interact is very difficult given current knowledge
GIS has enabled us to use and present so many different data layers that sometimes there’s a piling on in priority setting exercises - particularly when you’re trying to represent multiple perspectives and interests, or aren’t sure of what you’re doing - that obscures what’s most important.
Limitations
Variability among the Cluster may be a limiting factor, so resulting ranks may be somewhat flat- Are we splitting hairs ?
Summary