Maladaptive learning in Peru's integrated water resources management

Ruxandra Popovici, Zhao Ma, Anna E. Erwin, Linda S. Prokopy, Carlos Renzo Zeballos Velarde, Edwin Fredy Bocardo Delgado, José Porfirio Pinto Cáceres

Resultado de la investigación: Contribución a una revistaArtículorevisión exhaustiva

Resumen

In complex watershed management systems, learning from mistakes and adapting the rules accordingly is important. Our study investigates the interaction between two groups of stakeholders in a government-led Integrated Water Resources Management (IWRM) program in Peru's Colca Valley: 1) local water users at the community level and 2) regional water agency officials. We examined how learning and adaptation happened or did not happen for both stakeholder groups. We collected data through 90 semi-structured interviews with local water users in three Colca Valley communities and water agency officials, as well as participant observation during meetings between the two groups. We found that both stakeholder groups learned and adapted to each other's responses in a dynamic way. Nevertheless, the type of adaptation that occurred was maladaptive because it sustained the program flaws that reinforced the gap between the IWRM policies of regional water agencies and the water management priorities and incentives of local water users. We found that while there was an initial top-down and bottom-up sharing of information, water agency officials generally did not have the capacity to implement lessons learned and often dismissed negative feedback voiced by local water users. At the community level, water users had limited incentives to comply with IWRM requirements because the rules disadvantaged them economically. As a result, they learned to withhold information from water agency officials. We label this phenomenon maladaptive learning and argue that it leads to outcomes that are mutually non-beneficial for both stakeholder groups.

Idioma originalInglés
Páginas (desde-hasta)209-217
Número de páginas9
PublicaciónEnvironmental Science and Policy
Volumen127
DOI
EstadoPublicada - ene. 2022

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