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Advancing understanding in data limited conditions : Estimating contributions to streamflow across Tanzania’s rapidly developing Kilombero Valley
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- Koutsouris, Alexander J., 1983- (author)
- Stockholms universitet,Institutionen för naturgeografi
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- Lyon, Steve W., 1978- (author)
- Stockholms universitet,Institutionen för naturgeografi
- (creator_code:org_t)
- English.
- Other publication (other academic/artistic)
Abstract
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- Large natural variability in, for example, climate signals and experimental design may help to overcome the data limitations and difficult conditions that typify much of the global south. This, in turn, can facilitate the application of advanced techniques to help inform management with science (which is sorely needed for guiding development). As an example on this concept, 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 Kilombero Valley, Tanzania. How water interacts across the various storages in this region, which has been targeted for rapid agricultural intensification and expansion is still largely unknown, making estimation of potential impacts (not to mention sustainability) associated with various development scenarios difficult. Our results showed that there were, as would be expected, considerable uncertainties related to the characterization of end-members in this remote system. Regardless, some robust estimates could be made on contributions to seasonal streamflow variability. For example, it appears that there is a low connectivity between the deep groundwater and the stream system throughout the year. Also, there is a considerable wetting up period required before overland flow occurs. These process insights, in turn, help interpreting hydrochemical data thereby potentially improving understanding at larger scales. Thus, in spite of large uncertainties our results highlight how improved system understanding of hydrological flows can be obtained even when working under less than perfect conditions.
Subject headings
- NATURVETENSKAP -- Geovetenskap och miljövetenskap -- Naturgeografi (hsv//swe)
- NATURAL SCIENCES -- Earth and Related Environmental Sciences -- Physical Geography (hsv//eng)
Keyword
- end-member mixing analysis (EMMA)
- generalized likelihood uncertainty estimation (GLUE)
- water resources
- sustainable development
- Kilombero Valley (KV)
- Tanzania
- Hydrology
- Physical Geography
- naturgeografi
Publication and Content Type
- vet (subject category)
- ovr (subject category)
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