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The evolution of norms and their influence on performance among self-governing irrigation systems in the Southwestern United States Cover

The evolution of norms and their influence on performance among self-governing irrigation systems in the Southwestern United States

By: Kelsey Cody  
Open Access
|Apr 2019

Figures & Tables

figures/ijc2019-2019017_fig_007.jpg
Map 1:

Patterns of European colonization, Counties, and major streams in the URGB.

Table 1:

Historical origins and legal context of URGB irrigation systems.

Irrigation system traitsTaos acequiasCostilla acequiasConejos acequiasAnglo systems
Earliest irrigation1670s1850s1850s1870s
Recognition in US law1850s2000s2000s1870s
De facto water rights in past between systemsRepartimientoRepartimientoRepartimientoPrior appropriation
De facto water rights in present between systemsRepartimientoPrior appropriationPrior appropriationPrior appropriation
De facto water rights in past within systemsNeed and prior useNeed and prior useNeed and prior usePro-rata shares
De facto water rights in present within systemsNeed and prior useNeed and prior usePro-rata sharesPro-rata shares
Irrigated land tenureVara stripsVara stripsPLSSPLSS
Sample size18121823

The sample contains one acequia in Rio Grande County, but is included within Conejos County for simplicity. Additional descriptive statistics available from the author on request.

Table 2:

Hypotheses, rationales, and supporting literature.

HypothesisRationaleKey literature
H1: Hispanic irrigation systems will adopt rules and technologies that promote equality and collective action at higher frequencies than Anglo systems.Historical selective pressure for cooperative norms drives their internalization, and these norms then drive the adoption of rules and technologies that promote collective action and deter competitive behavior.Richerson et al. 2002; Nowak 2006; Tucker and Taylor 2007; Prediger et al. 2011; Ghate, et al. 2013; Carballo et al. 2014; Henrich 2014; Talhelm et al. 2014; van der Kooij et al. 2015; Jaeggi et al. 2016; Makowsky and Smaldino, 2016; Gavrilets and Richerson 2017
H2: Where rules are congruent with competitive norms, as with Anglo systems, monitoring agents will reduce water use violations, improve average crop production, and decrease crop production equality.Internalized norms of competition will amplify the deterrent effect of enforcement, and monitoring agents enforcing competitive rules will generate higher average crop production at the expense of the equality of crop production.Ostrom 2000; Rustagi et al. 2010; Kinzig et al. 2013; Cody et al. 2015; Rode et al. 2015; Smith et al. 2017; Smith 2018
H3: Where rules are congruent with cooperative norms, as with acequias from Costilla and Taos, monitoring agents will have no effect or a negative effect on water use violations, decrease average crop production, and increase crop production equality.Internalized norms of cooperation will render the deterrent effect of enforcement negligible or deleterious due to crowding-out, monitoring agents enforcing cooperative rules will generate more equal crop production at the expense of average crop production due to crowding-in.Ostrom 2000; Rustagi et al. 2010; Falk et al. 2012; Kinzig et al. 2013; Smith 2014; Rode et al. 2015; Turner et al. 2016; Gunda et al. 2018
H4: Where competitive rules are incongruent with cooperative norms, as with acequias from Conejos, monitoring agents will increase water use violations, reduce average crop production, and reduce crop production equality.Attempts to enforce rules counter to norms will generate conflict as irrigators actively oppose the rules and as monitoring agents fail to effectively enforce water allocations, leading to a breakdown of collective action.Ostrom 2000; Kamran and Shivakoti 2013; Vollan et al. 2013; Hoogesteger 2015; Rode et al. 2015
Table 3:

Variable names, data sources and descriptive statistics.

Variable nameData sourceDescriptive stats
Independent variables
 AcequiaOSE; DNRN: 71
PERCENT ACEQUIA: 67.6
 Ditch typeOSE; DNRN: 71
ANGLO: 23
OTHER COLORADO ACEQUIAS: 18
COSTILLA ACEQUIAS: 12
TAOS ACEQUIAS: 18
 Monitoring agent2013 SurveyN: 71
PERCENT WITH MONITOR: 71.2
Control variables
 Fewer days of water available than normal in 20122013 SurveyN: 71
Min: −200
Med: −30
Mean: −45.7
Max: 61
SD: 54.5
 Days water is normally available2013 SurveyN: 71
Min: 15.0
Med: 134.0
Mean: 137.1
Max: 274.0

SD: 68.5
 Rotate water delivery in scarcity2013 SurveyN: 71
PERCENT ROTATING IN SCARCITY: 76.1
 Normally rotate water delivery2013 SurveyN: 71
PERCENT NORMALLY ROTATING: 59.2
 Labor required2013 SurveyN: 71
PERCENT REQUIRE LABOR: 40.8
 Inter-system sharing arrangements present2013 SurveyN: 71
PERCENT SHARING: 22.5
 High capacity groundwater wells present2013 SurveyN: 71
PERCENT WITH WELLS: 45.1
 Vegetable gardens present2013 SurveyN: 71
PERCENT WITH GARDENS: 25.4
 Long lots present2013 SurveyN: 71
PERCENT LONG LOTS: 31.0
 Change water allocations in scarcity2013 SurveyN: 71
PERCENT CHANGING ALLOCATIONS: 78.9
 Percent Hispanic2010 US CensusN: 71
Min: 0.0
Med: 41.8
Mean: 40.5
Max: 100.0
SD: 24.0
 Water not allocated by private rights2013 SurveyN: 71
PERCENT NOT ALLOCATING BY PRIVATE RIGHTS: 46.5
 Dependency ratio2010 US CensusN: 71
Min: 0.0
Med: 23.5
Mean: 25.1
Max: 88.9
SD: 12.5
 Hold annual meeting2013 SurveyN: 71
PERCENT WITH ANNUAL MEETING: 80.3
 Percent renters2010 US CensusN: 71
Min: 0.0
Med: 17.2
Mean: 17.5
Max: 50.00
SD: 9.6
 Percent hydric soilsNRCSN: 71
Min: 0.0
Med: 17.1
Mean: 18.7
Max: 63.3
SD: 16.1
 Average farm area in hectaresOSE; TCA; DNRN: 69
Min: 0.4
Med: 38.9
Mean: 77.9
Max: 669.9
SD: 121.9
 System area in hectaresOSE; TCA; DNRN: 71
Min: 8.3
Med: 256.3
Mean: 30368
Max: 47475.7
SD: 7850.4
 Sprinkler irrigation present2013 SurveyN: 71
PERCENT SPRINKLER IRRIGATED: 46.5
 Bylaws present2013 SurveyN: 71
PERCENT WITH BYLAWS: 67.6
 US state2013 SurveyN: 71
PERCENT NEW MEXICO: 25.4
 Per capita voting present2013 SurveyN: 71
PERCENT VOTE PER CAPITA: 78.9
Dependent variables
 Frequency of water use violations2013 SurveyN: 71
Never: 31
Less than Once Per Year: 19
Once Per Year: 11
More than Once Per Year: 8
Often: 2
 2011–2014 Average system average NDVI in julyGoogle
Earth Engine; USGS Landsat
N: 71
Min: 0.0859
Med: 0.4499
Mean: 0.4316
Max: 0.6434
SD: 0.1199
 2011–2014 Average system spatial standard deviation of NDVI in julyGoogle
Earth Engine; USGS Landsat
N: 71
Min: 0.0431
Med: 0.2081
Mean: 0.2080
Max: 0.3110
SD: 0.0590

The methods used to measure these variables are available from the author on request.

Table 4:

13 features that ought to improve collective action on an irrigation system.

FeatureTaos acequias (percent)Costilla acequias (percent)Conejos acequias (percent)Anglo systems (percent)
No high capacity groundwater wells100.083.345.413.0
No sprinklers88.975.050.017.4
Per capita voting94.491.788.952.2
Labor required for water access88.966.711.113.0
Rotational water delivery88.983.361.121.7
Water not allocated by private rights94.483.327.84.3
Changing water allocations in scarcity94.475.066.778.3
Monitoring agent present100.066.755.665.2
Annual meeting100.066.766.782.6
Long lots present100.033.30.00.0
Vegetable gardens present88.916.70.00.0
Ongoing inter-system sharing arrangements55.616.75.613.0
Bylaws present100.033.355.669.6

The presence of these features is used to assess the relative preponderance of cooperative norms as opposed to competitive norms. The percentage of each ditch type which possess the trait in question is also given. More information on how and why these variables were selected is available from the author on request.

figures/ijc2019-2019017_fig_001.jpg
Figure 1:

Relatedness between irrigation systems based on the features in Table 4. Taos acequias all fall within the same cluster, with some Costilla acequias interspersed. A small cluster of Costilla acequias also emerges, and all but two of the remaining Costilla acequias falls within a third cluster which is two thirds Hispanic. Anglo systems and Conejos acequias make up the vast majority of the final cluster, which has a sub-cluster comprised entirely of acequias.

figures/ijc2019-2019017_fig_002.jpg
Figure 2:

PCA shows the relatedness between irrigation systems based on the features in Table 4. Taos remains apart from the other systems, with Costilla acequias being largely distinct from Anglo systems. Conejos acequias range from being more closely aligned with Costilla acequias to nearly identical to Anglo systems.

figures/ijc2019-2019017_fig_003.jpg
Figure 3:

Geographic and cultural distribution of cooperation-engendering features from Table 4. The differences between all ditch types are significant (p<0.01).

figures/ijc2019-2019017_fig_004.jpg
Figure 4:

Predicted probability of water misuse occurring once per year or more due to an interaction between a monitoring agent and different ditch types. 95% confidence intervals.

figures/ijc2019-2019017_fig_005.jpg
Figure 5:

Predicted average NDVI over the study period due to an interaction between a monitoring agent and different ditch types. 95% confidence intervals.

figures/ijc2019-2019017_fig_006.jpg
Figure 6:

Predicted average spatial standard deviation of NDVI over the study period due to an interaction between a monitoring agent and different ditch types. 95% confidence intervals.

Table 5:

Results with respect to norms, water rights, and monitoring.

Ditch typeNormsWater rightsMonitoring agentWater use violationsAverage crop productionEquality of crop production
Anglo systemsCompetitivePro-rata sharesYes(−)(+)(=)
No(+)(−)(=)
Conejos acequiasCooperativePro-rata sharesYes(+)(−)(=)
No(−)(+)(=)
Costilla & Taos acequiasCooperativeNeed and prior useYes(=)(−)(+)
No(=)(+)(−)

The sign in parenthesis indicates the direction of differences observed between systems with a monitoring agent and no agent when compared to the same Ditch Type.

DOI: https://doi.org/10.18352/ijc.910 | Journal eISSN: 1875-0281
Language: English
Published on: Apr 25, 2019
Published by: Uopen Journals
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2019 Kelsey Cody, published by Uopen Journals
This work is licensed under the Creative Commons Attribution 4.0 License.