Community-based Monitoring of Water Resources in Remote Mountain Regions

Remote mountain regions are often represented by pockets of poverty combined with accelerated environmental change. The combination of harsh climatic and topographical conditions with limited infrastructure puts severe pressures on local livelihoods, many of which rely strongly on local ecosystem services (ESS) such as agricultural production and water supply. It is therefore paramount to optimise the management of ESS for the benefit of local people. This is hindered by a scarcity of quantitative data about physical processes such as precipitation and river flow as well as qualitative data concerning the management of water and land. National and conventional scientific monitoring networks tend to be insufficient to cover adequately the spatial and temporal gradients. Additionally, the data that are being collected often fail to be converted into locally relevant and actionable knowledge for ESS management. In such conditions, community-based monitoring of natural resources may be an effective way to reduce this knowledge gap. The participatory nature of such monitoring also enhances knowledge co-production and integration in locally-based decision-making processes. Here, we present the results of a 4-year consortium project on the use of citizen science technologies for ecosystem services management (Mountain-EVO). The project analyzed ecosystem service dynamics and decision-making processes and implemented a comparative analysis of experiments with community-based monitoring of water resources in 4 remote mountain regions, i.e. Peru, Nepal, Kyrgyzstan, and Ethiopia. We find that community-based monitoring can have a transformative impact on local ESS management, because of its potential to be more inclusive, polycentric, and context-driven as compared to conventional monitoring. However, the results and effectiveness of community-based approaches depend strongly on the natural and socio-economic boundary conditions. As such, this requires a tailored and bottom-up approach to implementation, which ideally isrooted in locally-based set of actors that can act as catalysts for knowledge co-production between the scientific community and local ESS users.