Characteristics of Active Water Management Organizations in the Red River Basin

Characteristics of Active Water Management Organizations in the Red River Basin

Robert R. Hearne*and Craig Kritsky

Paper Presented at theFaculty of Economics Seminar

Thammasat UniversityOctober 20, 2009

*Visiting Fulbright ScholarFaculty of EconomicsKasetsart UniversityBangkok Thailand

Department of Agribusiness and Applied EconomicsNorth Dakota State UniversityP.O. Box 6050, Fargo, N.D., 58108, [email protected]

1Hearne:Presentation Thamasat 102009

mailto:[email protected]

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Outline

1. Institutional Evolution in Water Management2. Case Study of Evolution in Red River Basin3. Adoption of Activities and Ways of Working

a. Data and Methodsb. Resultsc. Discussion

Hearne:Presentation Thamasat 102009


Water Management Institutions Institutions are the rules and norms that guide societal behavior.

Institutions provide expectations of how others will act.

Institutions can be formal, with written codes and bureaucracies, or informal, such as a rule of polite behavior.

With low population density, little scarcity, and little conflict “informal” institutions might provide sufficient norms to manage resources. Elinor Ostrom’s work has demonstrated this. But with scarcity, rivalry, heterogeneity among users and uses, potential conflict, the need to finance infrastructure more formal institutions such as written codes and bureaucracies, can be required.


Institutional Evolution .Institutions provide expectations about other’s behavior. Stable institutions provide stable expectations. But as the economic and social environment evolve either existing institutions need to evolve or new institutions need to be created.

In many aspects the study of institutional evolution is similar to industrial organization.


Institutional Evolution

Saleth and Dinar (2004) provide an excellent overview of the institutional change literature, especially as it applies to water management.

Institutional change can be induced by changes in relative prices and by economic incentives to reduce transactions costs and improve efficiency. We can expect institutional change when the benefits of implementing new rules exceed the costs of change. This institutional evolution is the result of factors that are internal to the sector involved in the transactions [Ruttan and Hayami, (1984); Williamson (1999), North (1990), and Coase (1937)]



However, public institutions and organizations maynot be guided by concerns for efficiency. Political decision makers often favor the inefficiencies of public organizations because they increase political patronage. Efforts to appeal to different constituencies may lead to overlapping roles and duties. Ideologies and factors that are external to the sector might influence decision makers [North, 1990; Williamson, 1999].



External factors that influence water management include changes in national fiscal policy, shifts in political ideology, and dramatic transformations in production practices and economic activity. Thus institutional change in the water sector can be the result of internal or external factors. A salient point of this literature is that institutions will evolve or reinvent themselves to meet changing needs, to adopt to new endogenous or exogenous pressures, and to reduce transactions costs (Saleth and Dinar, 2004; Hearne, 2004; Hearne and Donoso, 2005, Hearne, 2007).


Institutional Evolution However, public institutions and organizations maynot be guided by concerns for efficiency. Political decision makers often favor the inefficiencies of public organizations because they increase political patronage. Efforts to appeal to different constituencies may lead to overlapping roles and duties. Ideologies and factors that are external to the sector might influence decision makers [North, 1990; Williamson, 1999].

External factors that influence water management include changes in national fiscal policy, shifts in political ideology, and dramatic transformations in production practices and economic activity. Thus institutional change in the water sector can be the result of internal or external factors,


Water Management Institutions .The evolution of water institutions, in the USA and elsewhere follows a general path:1. potable water and irrigation systems and rules of use;2. water allocation systems and evolving water codes;3. single purpose infrastructure development;4. multipurpose, hydroelectric, infrastructure development.

with corresponding institutions for financing and operations;

5. Point source pollution reduction;6. more formal conflict and water reallocation institutions;7. non-point source reduction and land/water management;8. processes to address ecosystem protection and endangered species.

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New Challenges for Water Institutions

These changing economic, socio-demographic, and climatological factors will imply the need for increaased infrastructure, improved technologies, and flexible water institutions.

Flexibility is needed to reallocate water: between sectors, across political boundaries and geographical areas, between ecosystems, and intertemporally.

Perhaps the paradigm has shifted from “get the prices right” and “get the property rights right” to “get the institutions right” (Williamson, 1994).


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Why is Local Water Management Important?Water resources management at the basin level needs to be a cooperative effort.

Local water management in rural upstream areas is critical to basin concerns such as water quality and flood control.

Recent US Federal government initiatives to promote water quality imply increased efforts to reduce non-point source pollution. This implies land management and local cooperation or enforcement.

Thus local water management institutions serve local needs as well as basin needs.

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Why is Local Water Management Important?

Local water management organizations (WMOs) are responsible for stewardship of water resources for local constituency needs, they should be stakeholder driven.

Local goals of water managers:

i) Maintain secure quality potable water sources;ii) Promote drainage and flood control for local needs;iii) Provide services for irrigation, recreation, and nature conservation as required for local needs.

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Basin wide water management objectives are of greater scale due to important population and economic activities in downstream main channel cities. Objectives include:

* maintain secure water supplies; * prevent large scale flood damage;* maintain water quality and meet State/Provincial

and Federal water quality standards;* promote environmental quality;* promote regional economic development.

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Local WMOs can contribute to basin wide initiatives by:

* providing diverse and varied responses and new ideas for implementing policies

* balancing top-down centralized initiatives with bottom-up responses

* ensuring public participation and facilitating public support

* collaborating with Federal government and state/provincial agencies

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What do we know about WMOs?

In the United States, WMOs

* are becoming more common* can be characterized as citizen-based, agency based, or

public-private* many are supported by the Federal government

* NRCS* EPA

* can facilitate non-point pollution control* many are focused on non-point water pollution, recreation development, public education, and advocacy

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What does the scientific literature say about WMOs?

Very little!!!

More and more responsibility is being handed to local watershed management groups, especially under the US EPAs water quality program. But as of yet their has been little analysis of the characteristics of WMOs that can most effectively contribute to new initiatives.

This corresponds to research on irrigation water management, initial efforts focused on technical aspects and later efforts on understanding irrigation water user associations.

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What does the scientific literature say about WMOs?

A few studies have characterized WMOs in the US. But there has been little statistical analysis or evaluation.

Analysis of WMOs fits into the study of institutions which includes both economics and political science.

Institutions include informal norms, rules, laws, customs, and organizations. Many recent studies on institutional analysis have utilized Elinor Ostrom’s (1990) use of the institutional analysis and development framework.


Red River of the North Basin .An interesting case study of water management institutions: Two federal governments: US and Canada Two States and a Province: Minnesota, ND, Manitoba Three systems of water law:

riparian rights, Minnesota prior appropriation, North Dakota state control, Manitoba

Many local jurisdictions, watershed districts, water boards, conservations districts etc.

A fairly homogenous physical geography, but a variety of institutions, as a factor of different state/provincial priorities


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Red River of the North Basin Located near the geographic center of North America45,000 square miles, about a third in Manitoba.

Population of 1.3 million670,000 in Winnipeg145,000 in Fargo – Moorhead 57,000 in Grand Forks – East Grand Forks

The land area is the remains of giant Glacial Lake Agassiz, and has excellent soils. 84% of land area is dedicated towards agricultural production.Principal crops – wheat and sugarbeets


Red River of the North Basin .Because the basin is flat, mostly unregulated, with lots of snow,

and flows north (such that upstream snowmelt flows into downstream ice) flooding and drainage are principle concerns of water managers.

When flooding does occur it spreads across a wide area and can cause substantial damage.

The 1997 “flood of the century” inundated ½ of Grand Forks and almost all of East Grand Forks

Because of local ice jams there are frequent local floods along certain river segments


Red River of the North Basin: Water Quality

Water quality in the Red River Basin is generally good. Most groundwater is suitable for drinking. Most surface water is suitable for swimming and fishing, with low concentrations of nitrates and pesticides. There are impaired waters, for fish consumption, swimming, and aquatic life, but the latter are rare.

The Red River is noted for being relatively free of invasive aquatic species, such as the zebra mussel which has caused substantial damage in the Great Lakes and Mississippi Basins.

Lake Winnipeg has a valuable commercial fishing industry which employs one thousand.

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What is Interesting about the Red River Basin?Flood control and drainage remain a primary concern

Basin remains vulnerable to prolonged drought

Water quality is generally in the Basin* few non-attainment zones* pesticide and nitrate concentrations are low* groundwater is mostly potable* minimal impact of wastewater* high levels of suspended sediments* relatively free of invasive aquatic species

Lake Winnipeg has a algae problem from high nutrient levels including high levels of nitrogen and phosphates coming from Red River


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What is Interesting about the Red River Basin?

The primary land use is agriculture, with good soils.

The physical geography of the Red River Basin is somewhat homogenous, but the different political constituencies and water laws make it an interesting case study of water management institutions.

Despite different priorities, there is cooperation in the basin to achieve common needs.


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What do we know about WMOs in the Red River Basin?

Within Manitoba, Minnesota, and North Dakota there are a variety of WMOs. We have: watershed districts, water resource districts, soil and water conservation districts, conservation districts, resource conservation and development councils, tribal departments of natural resourceslake associations, and a variety of agency based and citizen based WMOs.

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There are a variety of different formats for these WMOs. * In Minnesota, many WMOs are formed along watershed boundaries. * In North Dakota the water resource boards correspond to counties. * In Manitoba, groups of municipalities form conservation districts. * In Minnesota and North Dakota many local WMOs have the power to tax.

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There are a variety of different formats for these WMOs. * There are a a variety of joint-powers agreements that formalize collaboration between small WMOs for specific projects or purposes. * Many WMOs, US conservations districts and ND water

resource districts, have been formed under 1930s legislation.* Many US WMOs receive Federal support especially from the NRCS.* Most WMOs are engaged in public education.

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What do we want to learn about WMOs in the Red River Basin?

The variety of WMOs with different formats serving similar purposes leads to some simple questions:

* What is working?* How can water management be improved by learning

from other WMOs?* Is more collaboration needed?* How can WMOs collaborate better?* Are local WMOs providing needed public participation for the establishment of water quality standards?

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What do we want to learn about WMOs in the Red River Basin?

The variety of WMOs with different formats serving similar purposes leads to some simple questions:

* Are WMOs changing with the times to meet evolving needs?

* Which WMOs can most effectively utilize increased support?

* How can extension programs and government assistance be modified to better improve WMOs? and water management?

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Methodology

An adoption study was conducted to assess the characteristics of these WMOs have participated in water quality activity, collaboration, successful grant activity etc.

Data was gathered on activities and characteristics.


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Methodology

After a series of meetings with local experts and stakeholders, two survey instruments were developed. One for organizations and one for boards.

Seventy-six Red River Basin WMOS were in the survey population:12 Minnesota WDs, 20 Minnesota SWCDs, 24 North Dakota WRDs, and 20 SCDs.

350 surveys were sent to board members


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Methodology

Table 1: 22 Dependent variables in analysisnumber of studies number of joint powers agreementsvalue of recreation projects value of potable water supply projectsvalue of wildlife habitat projects number of conservation contracts signedvalue of aquatic habitat projects acres of windbreak/shelterbelt installednumber of trees sold number of snagging and clearing effortsvalue of water quality projects miles of new or improved drainage ditchvalue of water movement projects

dollars spent on contracting

value of water retention projects miles of stream bank stabilizationtotal grant funding level of ditch maintenance per yeartotal revenue value of wetland restoration projectsvalue of education projects number of organizations collaborated with on

budgeted projects


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Methodology

Table 2: 17 Explanatory Characteristics of WMOs and Board Members

CD # of other Organizations Board Members are a Part of

In MN # of Board Members that have had Cooperative Extension TrainingLand Area # of Organizations Collaborated with on Budgeted ProjectsPopulation Presence of State or Federal Agency Employee on BoardDownstream # of Board Members that Attend Water Conferences% of Board Farmers Education/Outreach Staff Hours Per Week# of Meetings Per Year Administrative Staff Hours Per WeekBoard Member Experience Technical Staff Hours Per week# of Joint Powers Agreements


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MethodologyThere were not enough observations for an MANOVA analysis

All dependent variables were regressed against he 17 characteristics

OLS, poisson, and negative binomial models, models were attempted

The model with lowest AICC indicator was selected

When no significant variables were encountered a logit model was attempted


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Results

36 of 76 WMOS returned a survey, although there was much missing data.

181 of 350 board members completed the surveys

Regressions for four dependents variables did not produce useful results:

i) the value of wildlife habitat projects; ii) the value of aquatic habitat projects; iii) the value of potable water supply projects; and iv) the level of ditch maintenance.


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ResultsTable 3. Dependent Variable: Number of Trees Sold for Conservation DistrictsRegression: Ordinary Least Square

F-Value = 5.59

N = 20 Pr > F = 0.0046

CharacteristicParameter Estimate Pr > t

Intercept 90130.41 0.0067Population 2.01 0.0007Downstream -48970.9 0.0971# of Joint Powers Agreements -5027.86 0.2757Board Member Attendance of Management Conferences -83528.90 0.0709District Collaboration on Budgeted Projects 16902.97 0.0071Tiller -42898.40 0.1366


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Results

Table 4. Dependent Variable: Acres of Windbreaks/Shelterbelts for Conservation Districts Regression: Negative Binomial

Log Likelihood = 10769.57

N = 19


Intercept 3.68 <0.0001Population <0.01 0.0002Education/Outreach Staff Hours 0.05 0.0001Presence of a Board Member that is a State or Federal agency Employee

-1.35 0.0018

Districts Revenue <-0.01 0.85Dispersion 0.37 NA


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ResultsTable 5. Dependent Variable: Number of Conservation Contracts Signed for Conservation DistrictsRegression: Poisson


N = 21


Intercept 4.93 <0.0001Land Area Square Miles <-0.01 <0.0001Population <0.01 <0.0001Board Member Experience -0.23 <0.0001Administrative Staff Hours 0.16 <0.0001Board Member Attendance of Water Management Conferences

2.80 <0.0001

Board Members being a part of other Decision Making Bodies

-3.25 <0.0001

Board Members Cooperative Extension Training 5.83 <0.0001Presence of a Board Member that is a State or Federal agency Employee

1.01 <0.0001

District Collaboration on Budgeted Projects -0.08 <0.0001Hearne:Presentation Thamasat 102009

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ResultsTable 6. Dependent Variable: Miles of New or Improved Drainage Ditch Permitted for Watershed Districts and Water Resource DistrictsRegression: Poisson


N = 12


Intercept -6.51 <0.0001

Land Area in Square Miles <0.01 <0.0001Percentage of Farmers on Board 4.18 <0.0001# of Joint Powers Agreements -2.08 <0.0001Board Members being a part of other Decision Making Bodies

1.99 <0.0001

District Collaboration on Budgeted Projects 0.36 <0.0001


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Results

Table 7. Dependent Variable: Water Retention Value for Watershed Districts and Water Resource DistrictsRegression: Poisson Log Likelihood =

241804833.77N = 12

Characteristic

Parameter

Estimate Pr > t

Intercept 10.77 <0.0001Population <-0.01 <0.0001Board Member Experience -1.39 <0.0001District Collaboration on Budgeted Projects 9.46 <0.0001Districts Revenue <-0.01 <0.0001


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ResultsTable 8. Dependent Variable: Number of Snagging and Clearing Efforts for Watershed Districts and Water Resource DistrictsRegression: Poisson


N = 12

Characteristic

Parameter Estimate Pr > t

Intercept 3.02 <0.0001

Board Member Experience 0.14 <0.0001

Board Member Attendance of Management Conferences -2.47 0.0158Board Members being a part of other Decision Making Bodies -0.87 <0.0001


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ResultsTable 9. Dependent Variable: Value of Water Movement Projects for Water Resource Districts and Watershed Districts Regression: Negative Binomial


N = 12


Intercept 10.95 <0.0001Land Area in Square Miles <0.01 <0.0001# of Joint Powers Agreements -2.74 <0.0001Presence of a Board Member that is a State or Federal agency Employee

-1.30 0.1141

Dispersion 0.9644 NA


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Results

Table 10. Dependent Variable: Miles of Stream Bank Stabilization ImplementedRegression: Poisson

Log Likelihood = -5.28

N = 34

Characteristic

Parameter Estimate Pr > t

Intercept -4.79 0.0002

Downstream 3.08 0.0003

Technical Staff Hours -0.03 0.0075

Administrative Staff Hours 0.07 0.0005

Board Member Cooperative Extension Training 3.17 0.0294


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Results

Table 11. Dependent Variable: Value of Water Quality Projects Regression: Negative Binomial


N = 32


Intercept 14.82 <0.0001Board Member Attendance of Management Conferences

-12.83 0.0098

District Collaboration on Budgeted Project

1.24 0.0196

Dispersion 18.91 NA


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Results

Table 12. Dependent Variable: Wetland Restoration Projects Regression: Binary Logit Log Likelihood =

14.094N = 32

Characteristic

Parameter Estimate

Pr > tIntercept -3.51 0.0080



0.7348 0.0467

Districts Revenue <0.01 0.0373Hearne:Presentation Thamasat 102009

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Results

Table 13. Dependent Variable: Value of Education/Outreach Projects Regression: Negative Binomial


N = 33

Characteristic

Parameter Estimate

Pr > tIntercept 6.26 0.0002

Board Member Experience -0.62 0.0046

Board Member Attendance of Management Conferences

10.11 0.0083

Dispersion 15.03 NA


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Results

Table 14. Dependent Variable: Recreation Projects

Regression: Binary Logit Log Likelihood = 14.02

N = 33

Characteristic

Parameter Estimate

Pr > tIntercept -0.90 0.5643

Board Member Experience -0.32 0.1263

District Collaboration on Budgeted Projects

0.44 0.0583


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ResultsTable 15. Dependent Variable: Total Number of Studies

Regression: Negative Binomial


N = 32


Intercept 1.37 0.0012


Board Member Cooperative Extension Training -2.28 0.0999

Districts Revenue <0.01 0.0208

Dispersion 1.80 NA


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Results

Table 16. Dependent Variable: Data Collection Studies Regression: Poisson


N = 32


Intercept 0.22 0.6946Conservation District -0.93 0.0623Minnesota 4.32 <0.0001Downstream -2.37 <0.0001

# of Joint Powers Agreements -0.29 0.0964


Board Member Cooperative Extension Training

-3.34 0.0034Hearne:Presentation Thamasat 102009

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Results

Table 17. Dependent Variable: Engineering Studies Regression: Poisson


N = 33

Characteristic

Parameter Estimate

Pr > tIntercept 2.80 0.0179

Conservation District -4.4240 <0.0001

Land Area in Square Miles -0.0039 0.0038

District Collaboration on Budgeted Projects 0.3352 0.0155Hearne:Presentation Thamasat 102009

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ResultsTable 18. Dependent Variable: Water Quality Studies Regression: Poisson Log Likelihood = -10.01

N = 32


Intercept -4.92 0.0023Minnesota 2.03 0.0067Land Area in Square Miles <0.01 0.2516Population <0.01 0.0020Percentage of Farmers on Board 3.42 0.0164Board Member Experience -0.14 0.0013# of Joint Powers Agreements -0.11 0.3671Board Members being a part of other Decision Making Bodies

0.93 0.0019

Presence of a Board Member that is a State or Federal agency Employee

-2.83 0.0412Hearne:Presentation Thamasat 102009

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ResultsTable 19. Dependent Variable: Total Revenue Regression: Ordinary Least Square

F-Value = 6.78

N = 31

Pr > F = 0.0001


Intercept -780573 0.7326CD -2392960 0.0223Downstream -623427 0.5087Percentage of Farmers on Board -1542532 0.2133Meetings 153905.20 0.0030Technical Staff Hours 59631.63 0.0015Administrative Staff Hours 80397.36 0.0014Board Member Attendance of Management Conferences 690738.90 0.6329Board Members being a part of other Bodies -509980 0.2314Board Member Cooperative Extension Training 1441113 0.3859District Collaboration on Budgeted Projects -251360 0.1751


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ResultsTable 20. Dependent Variable: Number of Organizations Collaborated with on Budgeted Projects

Regression: Poisson


N = 31

Independent VariableParameter Estimate Pr > t

Intercept -0.81 0.0651

Minnesota 1.87 <0.0001Population <0.01 0.0015

Board Member Experience -0.03 0.0314Board Member Attendance of Water Management Conferences

0.82 0.0842

District Revenue -0.01 0.2918


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ResultsTable 21. Dependent Variable: Number of Joint Powers Agreements Regression: Poisson


N = 32

Independent Variable

Parameter Estimate

Pr > tIntercept -3.10 <0.0001

Minnesota 1.50 <0.0001Percentage of Farmers on Board 1.65 0.0079Board Member Experience -0.06 0.0140

Education/Outreach Staff Hours 0.02 0.0251Board Members being a part of other Decision Making Bodies

0.81 <0.0001

Board Member Cooperative Extension Training

1.23 0.0518Hearne:Presentation Thamasat 102009

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Results

Table 22. Dependent Variable: Total Grant Funding Regression: Negative Binomial


N = 32

Independent VariableParameter Estimate Pr > t

Intercept 13.67 <0.0001

# of Joint Powers Agreements 0.40 0.4021

Board Members being a part of other Decision Making Bodies

-1.43 0.0840

Dispersion 18.33 NA


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Results


Table 3 Alternative: Significant Variables from of 20 Regression Models

Explanatory Variables

CD In MN

Land Area

Population

Downstream

Percentage of Board Who Are Farmers

Meetings Per Year

Board Member Experience

Joint Powers Agreements

Organizations BoardMembers are a Part of

Board Members with Extension Training


Presence of Agency Employee on Board

Board Members that Attend Water Conference

Education/Outreach Staff Hours

Administrative Staff Hours Per Week

Technical Staff Hours

District Revenue

Appointed Board

Dependent Variables

For CDsTrees Sold +++ -- +++ -

Acres of Windbreaks +++ --- +++

Contracts Signed +++ +++ --- --- +++ + +++

For WDs and WRDsNew Drainage Ditch +++ +++ --- +++ +++

Water Retention Project --- --- ---Snagging & Clearing +++ --- --

Water Movement Projects +++ ---

For All WMAsStream Bank Stabilization +++ ++ +++ ---

Water Quality Projects ++ ---Wetland Restoration ++ - ++Education Projects --- +++

Recreation Projects +Number of Total Studies + +++

Data Collection Studies +++ +++ - +++

Engineering Studies --- -- +++Water Quality Studies ++ +++ +++ -- +++

Total Revenue +++ +++ +++

Collaboration +++ +++ -- +

Joint Powers Agreements +++ +++ -- +++ + ++

Total Grant Funding -+++, ++, + positive and significant variables at the 0.01, 0.05, and 0.10 significance level Variables not included in regression---,--, - negative and significant variables at the 0.01, 0.05, and 0.10 significance level

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Discussion of Pertinent Characteristics

There is an expected difference between CDs and WDs & WRDs

Board member characteristics were often significant in the type of district activities

The difference between Mn and ND districts and upstream and downstream districts is less then expected

Staffing was significant in a number fo activites, but not as significant as expected


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Board member experience is positively correlated with snagging and clearing efforts, a traditional and currently not recommended practice

Board experience is negatively correlated with 1) district collaboration (joint powers agreements and

collaborative budgeted projects) 2) water quality efforts (the number of conservation

contracts signed, and the number of water quality studies)

3) other activities (the presence of recreation projects, the dollar value of education/outreach projects).


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Board member cooperative extension training has

1) a positive relationship with the number of conservation contracts signed, the miles of stream bank stabilization efforts, and the number of joint powers agreements entered into by districts

2) an unanticipated negative correlation with studies


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Discussion of Pertinent CharacteristicsBoard member attendance at water management conferences was expected to be an important determinate of collaboration and efforts to improve basin-wide water management.

There is a negative correlation with between conference attendance and two traditional activities: snagging and clearing efforts and tree sales.

There also is a positive correlation between conference attendance and the number of conservation contracts signed by conservation districts, the value of education/outreach projects, the number of organizations collaborated with on budgeted projects.


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Water management organizations that take part in a larger number of joint powers agreements were thought to be more concerned about basin-wide problems.

The number of joint powers agreements has a negative relationship with the miles of new or improved drainage ditch permitted, the value of water movement projects, and data collection studies


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Conclusions and Observations

This study was an effort to assess characteristics that have significant influence on institutional evolution and activity

In small organizations individual personalities are important, efforts to wash away personalities may not present other significant characteristics


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Conclusions and Observations

There are some value judgments implied in this analysis1) evolution is better then maintaining traditional

activities 2) activity is better than “do little, spend little,

and leave well enough alone”

However in some smaller districts traditional might be respected by those that are board members and those that elect or appoint boards

In any case outside agencies might maintain that evolution and activity is good


Documents

Characteristics of Active Water Management Organizations in the Red River Basin