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Water Resources Management

, Volume 31, Issue 15, pp 4731–4744 | Cite as

Participatory Modeling Workshops in a Water-Stressed Basin Result in Gains in Modeling Capacity but Reveal Disparity in Water Resources Management Priorities

  • Alex Mayer
  • Enrique R. Vivoni
  • David Kossak
  • Kathleen E. Halvorsen
  • Agustin Robles Morua
Article
  • 181 Downloads

Abstract

Participatory modeling workshops were held in Sonora, México, with the goal of developing water resources management strategies in a water-stressed basin. A model of the water resources system, consisting of watershed hydrology, water resources infrastructure, and groundwater models, was developed deliberatively in the workshops, along with scenarios of future climate and development. Participants used the final version of the water resources systems model to select management strategies. The performance of the strategies was based on the reliability of meeting current and future demands at a daily time scale over a year’s period. Pre- and post-workshop surveys were developed and administered. The survey questions focused on evaluation of participants’ modeling capacity and the utility and accuracy of the models. The selected water resources strategies and the associated, expected reliability varied widely among participants. Most participants could be clustered into three groups with roughly equal numbers of participants that varied in terms of reliance on expanding infrastructure vs. demand modification; expectations of reliability; and perceptions of social, environmental, and economic impacts. The wide range of strategies chosen and associated reliabilities indicate that there is a substantial degree of uncertainty in how future water resources decisions could be made in the region. The pre- and post-survey results indicate that participants believed their modeling abilities increased and beliefs in the utility of models increased as a result of the workshops.

Keywords

Participatory modeling Water scarcity 

Notes

Acknowledgements

This work has been partially supported by National Science Foundation award CBET 1014818. We acknowledge the excellent facilitation of the workshops by Ana Cristina Pacheco. Finally, we are indebted to the workshop participants for their time and energy.

References

  1. Acharya A, Lamb K, Piechota T (2013) Impacts of climate change on extreme precipitation events over flamingo Tropicana watershed 1. JAWRA J Am Water Resour Assoc 49(2):359–370CrossRefGoogle Scholar
  2. Addison P, Rumpff L, Bau S, Carey J, Chee Y, Jarrad F et al (2013) Practical solutions for making models indispensable in conservation decision-making. Divers Distrib 19(5–6):490–502CrossRefGoogle Scholar
  3. Agua de Hermosillo (2013) Aguah en números, Agua de Hermosillo, http://www.aguadehermosillo.gob.mx/inicio/organismo/aguah-en-numeros, accessed March 12, 2013
  4. Babbar-Sebens M, Mukhopadhyay S, Singh V, Piemonti A (2015) A web-based software tool for participatory optimization of conservation practices in watersheds. Environ Model Softw 69:111–127CrossRefGoogle Scholar
  5. Bousquet F, Tréibul G (2005) Synergies between multi-agent systems and role-playing games in companion modeling for integrated natural resource management in Southeast Asia. In Kachitvichyanukul V, Purintrapiban U, Utayopas P (eds.). Proceedings of the 2005 international conference on simulation and modelling, Bangkok, pp 461-469Google Scholar
  6. Brenna E (2012) Perceptions of water conditions and management in the Sonora River Basin, Sonora, Mexico (Master's Thesis). Michigan Technological University, HoughtonGoogle Scholar
  7. Butler C, Adamowski J (2015) Empowering marginalized communities in water resources management: addressing inequitable practices in participatory model building. J Environ Manag 153:153–162CrossRefGoogle Scholar
  8. Cash D, Clark W, Alcock F, Dickson N, Eckley N, Guston D (2003) Knowledge systems for sustainable development. Proc Natl Acad Sci 100(14):8086–8091CrossRefGoogle Scholar
  9. Comisión Estatal del Agua de Sonora (CEA) (2005) Estudio geo-hidrogeologico de las sub-cuencas de los Ríos Sonora, Zanjo, San Miguel, Mesa del Seri-La Victoria y cuenca Bacoachi. CEA-ED-081-CA1. Sonora, Comisión Estatal del Agua, p 391Google Scholar
  10. Comisión Nacional del Agua (CONAGUA). (2016) Sistema de Información Geográfica de Acuíferos y Cuencas (SIGACU@) Sigagis.conagua.gob.mx. Retrieved 19 January 2016, from http://sigagis.conagua.gob.mx/aprovechamientos/
  11. Dunnett C (1980) Pairwise multiple comparisons in the unequal variance case. J Am Stat Assoc 75(372):796–800CrossRefGoogle Scholar
  12. Ebrahim GY, Jonoski A, van Griensven A, Di Baldassarre G (2013) Downscaling technique uncertainty in assessing hydrological impact of climate change in the upper Beles River basin, Ethiopia. Hydrol Res 44(2):377–398CrossRefGoogle Scholar
  13. Gaddis E, Falk H, Ginger C, Voinov A (2010) Effectiveness of a participatory modeling effort to identify and advance community water resource goals in St. Albans, Vermont. Environ Model Softw 25(11):1428–1438CrossRefGoogle Scholar
  14. Gray S, Chan A, Clark D, Jordan R (2012) Modeling the integration of stakeholder knowledge in social–ecological decision-making: benefits and limitations to knowledge diversity. Ecol Model 229:88–96CrossRefGoogle Scholar
  15. Gurung TR, Bousquet F, Trébuil G (2006) Companion modeling, conflict resolution, and institution building: sharing irrigation water in the Lingmuteychu watershed, Bhutan. Ecol Soc 11(2):36CrossRefGoogle Scholar
  16. Howell W (2013) Global Risks 2013. World Economic Forum, Cologny/Geneva, SwitzerlandGoogle Scholar
  17. Jones N, Perez P, Measham T, Kelly G, d’Aquino P, Daniell K, Dray A, Ferrand N (2008) Evaluating participatory modeling: developing a framework for cross-case analysis. Environ Manag 44(6):1180Google Scholar
  18. Kummu M, Ward P, de Moel H, Varis O (2010) Is physical water scarcity a new phenomenon? Global assessment of water shortage over the last two millennia. Environ Res Lett 5(3):034006. doi: 10.1088/1748-9326/5/3/034006 CrossRefGoogle Scholar
  19. Langsdale S, Beall A, Bourget E, Hagen E, Kudlas S, Palmer R, Tate D, Werick W (2013) Collaborative modeling for decision support in water resources: principles and best practices. J Am Water Resour Assoc 49(3):629–638CrossRefGoogle Scholar
  20. Laniak G, Olchin G, Goodall J, Voinov A, Hill M, Glynn P et al (2013) Integrated environmental modeling: a vision and roadmap for the future. Environ Model Softw 39:3–23CrossRefGoogle Scholar
  21. Malve O, Hjerppe T, Tattari S, Väisänen S, Huttunen I, Kotamäki N et al (2016) Participatory operations model for cost-efficient monitoring and modeling of river basins — a systematic approach. Sci Total Environ 540:79–89CrossRefGoogle Scholar
  22. Mayer, A.S., Winkler, R., and Fry, L. (2014) Classification of watersheds into integrated social and biophysical indicators with clustering analysis, Ecological Indicators, 45, 340-349Google Scholar
  23. Meenu R, Rehana S, Mujumdar P (2012) Assessment of hydrologic impacts of climate change in Tunga-Bhadra river basin, India with HEC-HMS and SDSM. Hydrol Process 27(11):1572–1589CrossRefGoogle Scholar
  24. Ostrom E (2009) Understanding institutional diversity. Princeton University Press, PrincetonGoogle Scholar
  25. Pahl-Wostl C (2007) Transitions towards adaptive management of water facing climate and global change. Water Resour Manag 21(1):49–62CrossRefGoogle Scholar
  26. Pahl-Wostl C (2009) A conceptual framework for analysing adaptive capacity and multi-level learning processes in resource governance regimes. Glob Environ Chang 19(3):354–365CrossRefGoogle Scholar
  27. Pahl-Wostl C, Craps M, Dewul A, Mostert E, Tabara D, Taillieu T (2007) Social learning and water resources management. Ecol Soc 12(2):5 URL: http://www.ecologyandsociety.org/vol12/iss2/art5/ CrossRefGoogle Scholar
  28. Renger M, Kolfschoten G, Vreede G (2008) Challenges in collaborative modelling: a literature review and research agenda. Int J Simul Process Model 4(3/4):248–263CrossRefGoogle Scholar
  29. Robles-Morua A, Halvorsen K, Mayer A, Vivoni E (2014) Exploring the application of participatory modeling approaches in the Sonora River basin, Mexico: results of a workshop to assess the usefulness and impacts of models in water-related risk perceptions. J Environ Modeling Software 52:273–282CrossRefGoogle Scholar
  30. Robles-Morua A, Che D, Mayer A, Vivoni E (2015) Hydrological assessment of proposed reservoirs in the Sonora River basin, Mexico, under historical and future climate scenarios. Hydrol Sci J 60(1):50–66CrossRefGoogle Scholar
  31. Rousseeuw P (1987) Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. J Comput Appl Math 20:53–65CrossRefGoogle Scholar
  32. Scholz G, Dewulf A, Pahl-Wostl C (2014) An analytical framework of social learning facilitated by participatory methods. Syst Pract Action Res 27(6):575CrossRefGoogle Scholar
  33. van den Belt M (2004) Mediated modeling. Island Press, Washington, DCGoogle Scholar
  34. Veldkamp T, Wada Y, de Moel H, Kummu M, Eisner S, Aerts J, Ward P (2015) Changing mechanism of global water scarcity events: impacts of socioeconomic changes and inter-annual hydro-climatic variability. Glob Environ Chang 32:18–29CrossRefGoogle Scholar
  35. Vivoni E, Rodríguez J, Watts C (2010) On the spatiotemporal variability of soil moisture and evapotranspiration in a mountainous basin within the north American monsoon region. Water Resour Res 46(2). doi: 10.1029/2009wr008240
  36. Voinov A, Bousquet F (2010) Modelling with stakeholders. Environ Model Softw 25(11):1268–1281CrossRefGoogle Scholar
  37. von Korff Y, Daniell K, Moellenkamp S, Bots P, Bijlsma R (2012) Implementing participatory water management: recent advances in theory, practice, and evaluation. Ecol Soc 17(1). doi: 10.5751/es-04733-170130
  38. Vörösmarty C, Pahl-Wostl C, Bunn S, Lawford R (2013) Global water, the anthropocene and the transformation of a science. Curr Opin Environ Sustain 5(6):539–550CrossRefGoogle Scholar
  39. Whitten G, Hann M, Robles-Morua A, Mayer AS, Vivoni ER (2014) Enhancing the link between surface and groundwater models for climate change assessment of water supply and demand in Northwest Mexico. In: Ames DP, Quinn NWT, Rizzoli AE (eds) 7th Intl. Congress on Environmental Modelling and Software, San Diego, 17 June 2014Google Scholar
  40. Wiek A, Binder C, Scholz R (2006) Functions of scenarios in transition processes. Futures 38(7):740–766CrossRefGoogle Scholar
  41. Zorrilla P, Carmona G, De la Hera Á, Varela-Ortega C, Martínez-Santos P, Bromley J, Jorgen Henriksen H (2009) Evaluation of Bayesian networks as a tool for participatory water resources management: application to the upper Guadiana Basin in Spain. Ecol Soc 15(3):12 URL: http://www.ecologyandsociety.org/vol15/iss3/art12/ CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2017

Authors and Affiliations

  1. 1.Department of Civil and Environmental EngineeringMichigan Technological UniversityHoughtonUSA
  2. 2.School of Earth and Space Exploration, School of Sustainable Engineering and the Built EnvironmentArizona State UniversityTempeUSA
  3. 3.Martell Forestry Inc.GaylordUSA
  4. 4.Department of Social Sciences, School of Forest Resources and Environmental ScienceMichigan Technological UniversityHoughtonUSA
  5. 5.Departamento de Ciencias del Agua y del Medio AmbienteInstituto Tecnológico de SonoraCuidad ObregónMexico

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