AWARE characterization factors in Peru encompassing El Niño and climate change events: does increased water availability guarantee less water scarcity?

Purpose: Water scarcity is a critical environmental challenge which will be exacerbated by the effects of climate change and increased human demand. Hence, more precise and realistic methods of quantifying this impact are necessary. In this sense, the present study proposes updated water scarcity characterization factors (CFs) for watersheds in Peru using the AWARE method. The novelty is linked to the consideration of present and future conditions, as well as quasi-cyclical climatic events such as El Niño. Methods: The approach adopted for the estimation of regionalized CFs used regional and official databases as data input for water availability, human demands, and the official delineation of watersheds. Moreover, future CFs in climate change scenarios were based on data from the Meteorological and Hydrological National Service (SENAMHI), which projected water availability using three climate models from the 5th phase of the Climate Model Intercomparison Project (CMIP5). In contrast, CFs calculated for El Niño events were estimated considering a retrospective approach, using historical data on both water availability and demand. The computation of the CFs includes a sensitivity analysis based on the Spearman rank correlation and quantitative and qualitative uncertainty analysis, considering Monte Carlo simulation and Pedigree Matrix, respectively. Results and discussion: There are notable differences in terms of spatial and temporal variability between the original and updated water scarcity CFs which are linked to the global nature of the databases used in the original CF calculations. Annual updated CFs were up to 34-fold higher than the original CFs. Monthly CFs during El Niño events were lower than the updated CFs, which may be masking the actual water scarcity levels in some areas. Future CFs showed variability between the three models; however, they converge in identifying high levels of water scarcity in the South Pacific coastal watersheds, while in the tributary watersheds of the Amazon River low levels of water scarcity will be maintained. Conclusions: The proposed updated water scarcity CFs for the Peruvian context improve the computation and representativeness of the water scarcity levels. Furthermore, the replication of this approach to other countries can improve the accuracy of the LCA results, and the updated CFs can be used as input for territorial planning and direct agricultural expansion. Future CFs revealed the urgent need to develop adaptation actions to reduce future social, economic, and environmental impacts of the extreme events of droughts or floods exacerbated by climate change effects.