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Conservation Innovation GrantIntroductory Meeting

November 9, 2006Institute of Water ResearchMichigan State University

East Lansing, MI

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Agenda

1. Introductions

All

2. Targeting Conservation Practices: the proactive approach

Institute of Water Research

3. High Impact Targeting Demonstration

Institute of Water Research

4. Background and Organizational Structure

MDA & Institute of Water Research

5. Opportunities and Roles

All

6. Discussion, Feedback, Questions

All

7. Next Steps

All

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Contrasting Hillsides

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The Need to Target Proactively

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High Impact Targeting (HIT)

HIT is a web-accessible system that allows users to identify and prioritize, at multiple-scales, areas at high-risk for sediment loading. The data delivered through HIT are the product of results from the Spatially Explicit Delivery Model (SEDMOD)¹ and the Revised Universal Soil Loss Equation (RUSLE)².

1. Fraser. May 1999

2. Renard, Foster, Weesies, McCool, Yoder. 1996.

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Rainfall

SupportPractice

Land Cover

Landuse/Tillage

Soil ClayContent

Soil Erodibility

DEM

Delivery Ratio

Soil Erosion

Sediment Yield

Sediment Yield

SEDMOD/RUSLE Methodology

SurfaceRoughness

SoilTexture

Distance toStream

Weighting

C Factor

K Factor

R Factor

P Factor

LS Factor

RUSLE

SEDMOD

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Prioritization of 8-digit HUCs Using 90m Resolution Data(Great Lakes Basin)

Estimated Potential Sediment LoadingContributed from Cropland (tons/yr.)

Source: Ouyang, Bartholic, Selegean (2005)

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Prioritization of 12-digit HUCs Using 10m Resolution Data (Lower Maumee River Watershed – NW Ohio)

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Watershed Acres TillageTotal Sediment

(tons)Reduction

(tons)Percent Change

Garret 18,065 current practice 1,591 0 0%

Garret no till on worst 5% 1,322 269 17%

Garret no till on worst 10% 1,223 368 23%

Wolf 17,440 current practice 286 0

Wolf no till on worst 5% 216 69

Wolf no till on worst 10% 202 84

Applying BMP (no-till) on highest risk acres in contrasting watersheds

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Slide “A” shows a 30 square mile area of watershed that can be examined to rapidly locate and magnify high risk contributing areas.

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“B” shows an enlarged map area

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“C” shows further enlargement with a photographic image of the area.

C

0 2,000 feet

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“D” shows this resolution with the photo overlaid with the sediment risk layer.

D

0 2,000 feet

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Specific problem areas can be interpreted from slide “E” by overlaying the sediment risk layer over the photograph.

0 1,000 feet

E

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Slide “F” shows contour lines and three example areas of high sediment delivery.

1) High sediment deliveries 2) Potential concentrated flow 3) High sediment delivery no riparian buffer

F

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3

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Line of Sight in Blue, Model-predicted Flow in Yellow

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Line of Sight in Blue, Traces of Gullies in Yellow

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Closer Look at Trace of a Gully

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Upstream Site Installed Grass Buffer

If an existing BMP GIS layer is available, it can be incorporated into the model to further improve targeting efforts.

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• Benefits– Allows for prioritization of areas with a high risk for

sediment loading– Watershed and field-level resolutions– Spatially distributed C-factor (weighted and averaged

by county-level tillage data from CTIC)

• Limitations– RUSLE does not account for ephemeral gully erosion– 10 meter resolution DEMs not available for all areas– SEDMOD processing can take over a week to finish

Benefits and Limitations of the Methodology

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Making the Data Web-Accessible:In order to realize the benefits of the HIT modeling process, the data needs to be readily available to decision makers.

HIT front page.

User selects a watershed.

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Making the Data Web-Accessible:

User has the option to view data for the entire 8-digit watershed in three formats:

Tabular

Bar Graph

Spatial

Those options are also available for viewing sub-watersheds of the 8-digit watershed.

In this example, the user chooses to compare sub-watersheds, instead of looking at just one.

Users can choose from multiple scales and formats to view data.

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Making the Data Web-Accessible:

Several watersheds will be compared.

Cost benefit analyses will be run for each of two BMPs:

No Till on the worst 5% of areas

Mulch till on the worst 5% of areasTotals and rates will be calculated for

each sub-watershed.

Sediment data will be analyzed.

Build a results table

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Making the Data Web-Accessible:Table Results

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Making the Data Web-Accessible:Closer look at the tabular results

Results sorted by BMP cost per ton reduction (by clicking on column title).

BMP cost/acre provided by NRCS.HIT uses NRCS value to

calculate total cost of BMP in a particular watershed.

This can help an organization determine where (and which) conservation efforts will yield the maximum return in sediment reduction within its budget.

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Making the Data Web-Accessible:Same data displayed in the table is also available in bar graph format.

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Making the Data Web-Accessible:

If Wade Creek is identified as the targeted watershed, the user can use HIT to connect to Digital Watershed in order to explore Wade Creek’s high risk areas spatially.

Viewing the data spatially

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• More options for entering the system

• Increase the BMP options

• Ability to query results

• Expand number of watersheds modeled

Future Expansion of HIT

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• SEDMOD/RUSLE methodology facilitates prioritization of areas in terms of sediment loading at the watershed, sub-watershed, and field levels.

• HIT system makes SEDMOD/RUSLE results readily accessible over the web.

• HIT allows results to be explored in either tabular, bar graph, or spatial formats.

• Empowers conservation districts, field staff, and agricultural operators to target areas at high-risk for sediment loading.

HIT Summary

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35.9.116.206/hit/hit.asp

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MDA

IWR

Determine reduction targets

Cost/benefit analysis

of BMPs

Conservation Districts

Develop and deliver outreach plan

Farmers

CIG Specialists

Interface with

Model sediment yield in select watersheds

Build and refine on-line HIT system

Provide user feedback CREP

Technicians

MDEQ

Monitoring

CIG Technical Flow

Feedback provided by a Technical Advisory Committee

Year 1

Year 1

Year 1

Year 1-Year 2

On-going

On-going

On-going

On-going

NRCS

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MDA

Composition of Advisory Committee and Planned Inputs

MSUEMACD Farm Bureau

Estimate levels of farmer participation

Identify high risk erosion areas

MDEQ

Water quality info

MDNR

Advisory Committee

Inputs

Other inputs

Identify Targeted Sub-watersheds

Representatives of

FSA NRCSWatershed Orgs IWR

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IWR

Composition of IWR Technical Committee

MSU Ag Engineering

MACD Farm Bureau

Ease of system use

Modelingimprovements

Outreacheffectiveness

Technical Committee

Inputs

HIT utility

Refine and enhance HIT technical capacity

Representatives of

FSA NRCSWatershed Orgs CREP Technicians

CIG Specialists MDA

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MDA

IWR

Number of farmers and organizations receiving conservation education

MDEQ

CIG Program Evaluation

Conservation Districts

Participants and enrolled acres as a % of potential

participants and acres

Unique hits on HIT website

Quantify reductions in sediment loadings

Estimate long term water quality improvements

Provides

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• How will NRCS, MDA, and IWR determine sediment reduction “targets”?

– Use HIT models to come up with numbers to shoot for.

• Utilize the specialists to do some ground-truthing, get a sense if the worst 5% of areas predicted by the HIT model are actually the worst 5%.

– We need to remember that these are targets, not deliverables.

– Could also establish targets for specialists.• Numbers of farmers engaged with the program, dependent

on sub-watershed and degree of engagement.

Opportunities and Roles

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• How will MDA and IWR evaluate the cost-benefit of BMPs?

– Cost is the easy part.

– Benefit is harder. • What type of benefit?

– Water quality?– Habitat improvement?– Project’s focus is sediment reduction.– Might be able to include Phosphorus into the analysis by

looking at the soils.• Have to make some assumptions, it is not possible to come

up with precise estimates for efficacy of all BMPs. • Each watershed will provide list of BMPs utilized, to give us a

starting point.

Opportunities and Roles

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• How will the Conservation Districts and IWR develop an outreach plan?

– Get the HIT web system in place.– Recruit for focus groups, initiate dialogs with potential

users/groups.– Tailor it based on initial conversations with potential

users.– Utilize pre-existing outreach programs (319 or CSP).

Opportunities and Roles

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• What are the primary responsibilities of the CIG Specialists? What will they do in the first year?

– Familiarize themselves with HIT tool, provide initial feedback to IWR.

– Familiarize themselves with conservation planning, MEAP, EQIP, other programs. Maybe in the form of a training program (after conservation districts assess their respective backgrounds).

– Start informing the public about the program• Meeting, interacting with watershed groups, building rapport with

farmers.

– Later-on: ground-truthing HIT model predictions.

Opportunities and Roles

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• How often will the Advisory Committee meet?– Semi-annual– First meeting probably not until after February.

• Potential Advisory Membership– Exec. Dir Conservation Districts (Lori Phelan)– Each district could recommend a local watershed group rep.– M-DNR – Bill Mortz (Wildlife Division)– FSA – Dale Allen could recommend someone– MSUE – Jane Herber or Alan Krizeek (sp.?)– NRCS – Kevin Wickey– DEQ – Meghan McMahon

Opportunities and Roles

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• How often will the Technical Committee meet?

– Potential Technical Membership• Spicer• DEQ – John Esch

– 1st meeting?

Opportunities and Roles

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• Establish advisory committees.– Advisory: MDA– Technical: IWR

• Set up introductory meetings between MDA, IWR, and CIG Specialists (once they have been hired)

• IWR begins building HIT data.• After assessing each Specialist’s background, the

Conservation Districts and MDA will develop a list of training needs for the specialists.

• Specialists familiarize themselves with MEAP, EQIP, CRP, other programs identified on the training list.

• Conservation Districts provide lists of most common BMPs to IWR and MDA.

Next Steps

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Thanks for Caring and Acting to Sustain

Water Resources

http://www.iwr.msu.edu

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