Advancing understanding in data-limited conditions: estimating contributions to streamflow across Tanzania’s rapidly developing Kilombero Valley

Hydrological Sciences Journal
Koutsouris, Alexander J.; Lyon, Steve W.
PublisherTaylor & Francis
Source N/A
Volume / Issue63/2
Total Pages12 pages
Article Link
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Conference / Book Title N/A
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Tagsend-member mixing analysis (EMMA); generalized likelihood uncertainty estimation (GLUE); water resources; sustainable development; Kilombero Valley (KV); Tanzania; hydrology
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Conference Date N/A
Publication DateJanuary 22, 2018
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AbstractLarge seasonal variability in precipitation patterns may help overcome data limitations and difficult conditions when characterizing hydrological flow pathways. We used a limited amount of weekly water chemistry as well as stable water isotope data to perform end-member mixing analysis (EMMA) in a generalized likelihood uncertainty estimation (GLUE) framework in a sub-catchment of the Kilombero Valley, Tanzania. While there were considerable uncertainties related to the characterization and mixing of end-members, some robust estimates could be made on contributions to seasonal streamflow variability. For example, there is a low connectivity between the deep groundwater and the stream system throughout the year. Also, a considerable wetting-up period is required before overland flow occurs. Thus, in spite of large uncertainties, our results highlight how improved system understanding of hydrological flows can be obtained even when working in difficult environments.
Created: 8/30/2018 10:14 AM (ET)
Modified: 8/30/2018 10:14 AM (ET)
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