Welcome to G-EMMA, software written to facilitate end-member mixing analysis within a GLUE uncertainty assessment framework.
Using mixing model approaches to separate the different components of a hydrograph has a long and successful history in the hydrological community. However, the application of mixing models suffers from uncertainty in both the identification of the correct sources (end-members) and the unavoidable spatiotemporal variation in end-member concentrations. Before G-EMMA, no method accounted for both these sources of uncertainty.
G-EMMA is a novel method of uncertainty assessment in end-member mixing analysis, based on generalized likelihood uncertainty estimation, and has been successfully applied to a lowland polder catchment, part of the Haarlemmermeer. This catchment provided for a difficult test case, due to a large spatial variability in end-member concentrations, and a large number of different distinguishable water types. G-EMMA was better able to deal with the large number of and spatial variation in end-members than the traditional approach, suggesting possible application over a wider range of catchments than traditional EMMA.
The G-EMMA procedure and its application to a Dutch polder catchment have been published in a scientific paper (Delsman et al., 2013).
Published applications of G-EMMA:
I wrote this software as part of my PhD research "Adaptation to drought and salinization in the groundwater - surface water system" (visit website (in Dutch)), within the Knowledge for Climate, Climate Proof Fresh Water Supply program. I hope it can be of use to other researchers,
Joost Delsman, April 2013