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