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Advancing understanding in data limited conditions: Estimating contributions to streamflow across Tanzania’s rapidly developing Kilombero Valley
Stockholm University, Faculty of Science, Department of Physical Geography.
Stockholm University, Faculty of Science, Department of Physical Geography.
(English)Manuscript (preprint) (Other academic)
Abstract [en]

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.

Keyword [en]
end-member mixing analysis (EMMA), generalized likelihood uncertainty estimation (GLUE), water resources, sustainable development, Kilombero Valley (KV), Tanzania, Hydrology
National Category
Physical Geography
Research subject
Physical Geography
Identifiers
URN: urn:nbn:se:su:diva-142193OAI: oai:DiVA.org:su-142193DiVA: diva2:1091719
Available from: 2017-04-27 Created: 2017-04-27 Last updated: 2017-05-08Bibliographically approved
In thesis
1. Building a coherent hydro-climatic modelling framework for the data limited Kilombero Valley of Tanzania
Open this publication in new window or tab >>Building a coherent hydro-climatic modelling framework for the data limited Kilombero Valley of Tanzania
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

This thesis explores key aspects for synthesizing data across spatiotemporal scales relevant for water resources management in an Eastern Africa context. Specifically, the potential of large scale global precipitation datasets (GPDs) in data limited regions to overcome spatial and temporal data gaps is considered. The thesis also explores the potential to utilize limited and non-continuous streamflow and stream water chemistry observations to increase hydrological process understanding. The information gained is then used to build a coherent hydro-climatic framework for streamflow modelling. In this thesis, Kilombero Valley Drainage Basin (KVDB) in Tanzania is used as an example of a data limited region targeted for rapid development, intensification and expansion of agriculture. As such, it is representative for many regions across the Eastern Africa. With regards to the data synthesis, two satellite products, three reanalysis products and three interpolated products were evaluated based on their spatial and temporal precipitation patterns. Streamflow data from KVDB and eight subcatchments were then assessed for quality with regards to missing data. Furthermore, recession analysis was used to estimate catchment-scale characteristic drainage timescale. Results from these streamflow analyses, in conjunction with a hydrological tracer-based analysis, were then used for improved understanding of streamflow generation in the region. Finally, a coherent modelling framework using the HBV rainfall-runoff model was implemented and evaluated based on daily streamflow simulation. Despite the challenges of data limited regions and the often large uncertainty in results, this thesis demonstrates that improved process understanding could be obtained from limited streamflow records and a focused hydrochemical sampling when experimental design natural variability were leveraged to gain a large  signal to noise ratio. Combining results across all investigations rendered information useful for the conceptualization and implementation of the hydro-climatic modelling framework relevant in Kilombero Valley. For example, when synthesized into a coherent framework the GPDs could be downscaled and used for daily streamflow simulations at the catchment scale with moderate success. This is promising when considering the need for estimating impacts of potential future land use and climate change as well as agricultural intensification.

Abstract [sv]

Denna avhandling utforskar aspekter på att syntetisera data med olika rumslig och temporal upplösning, vilket är centralt för vattenförvaltning i östra Afrika. Särskilt fokus ligger på att undersöka möjligheten till att använda globala nederbördsdataset för att fylla rumsliga och temporala luckor där data saknas. Avhandlingen undersökeräven möjligheten till att använda flödesdata med icke-kompletta tidsserier samt kemidata från vattendrag för att utöka kunskap-en om hydrologiska processer. Informationen används för att bygga upp ett integrerande ram-verk för hydro-klimatologisk modellering som exempelvis kan användas för att utforska ef-fekten av ett utökat och intensifierat jordburk på vattenresurser. I denna avhandling användes Kilomberodalens avrinningsområde (Tanzania) som exempel på ett databegränsat område där det pågår en intensiv utökning av jordbruksverksamhet. Detta område kan ses som representa-tivt för ett stort antal områden inom östra Afrika.Datasyntesen innefattade två nederbördsprodukter baserade på satellitdata, tre baserade på återanalysprodukter samt två baserade på interpolering av observervationsdata från regnmä-tare. Dessa åtta produkter utvärderades baserat på deras nederbördsmönster i rum och tid. Ut-över detta utvärderades vattenföringsdata från Kilomberodalens avrinningsområde samt åtta delavrinningsområden utifrån mängden saknad data i respektive tidsserie. Vidare användes resultaten från hydrologisk recessionsanalysför att uppskatta den karaktäristiska avrinningsti-den för avrinningsområden. Resultaten från recessionsanalysensamthydrologiskt spårämnes-försök användessedan för att utöka kunskapen om avrinningsbildning och vattenföring i om-rådet samt som stöd i valet av hydrologiskt modelleringsverktyg. Avslutningsvis användes HBV-avrinningsmodellen för att simulera daglig vattenföring. Trots utmaningen i att arbeta iett databegränsat område och de osäkerheter i resultat som detta tenderar att leda till visar resultaten att det var möjligt att använda begränsad vattenfö-ringsdata och vattenkemidata för att utöka den hydrologiska processförståelsen av området. Detta möjliggjordes genom ett experimentellt upplägg som utnyttjade till ett stort signal-till-brusförhållande under rådande förhållanden av naturlig variabilitet. Kombinerade resultat från alla genomförda studier kunde utnyttjas vid konceptualiseringen och implementeringen av ramverket för hydroklimatologisk modellering av Kilomberodalens avrinningsområde. Till exempel kunde de globala nederbördsdataseten användas för lokal modellering av flödesdata med viss framgång efter syntes och implementering i det integrerande ramverket för hydro-klimatologisk modellering. Detta är lovande med tanke på behovet av att undersöka vilken påverkan möjliga framtida förändringar i markanvändning, klimat samt jordbruk har på den lokala och regionala miljön.

Place, publisher, year, edition, pages
Stockholm: Stockholm University, 2017. 44 p.
Series
Dissertations from the Department of Physical Geography, ISSN 1653-7211 ; 63
Keyword
Hydrology, Precipitation, Recession analysis, End - member mixing analysis, EMMA, GLUE, HBV, down scaling, Quantile mapping, CFSR, CMORPH, CRU, GPCC, ERA - i, MERRA, TRMM, UDEL, Satellite, Reanalysis, Kilombero, Tanzania, Eastern Africa, Africa
National Category
Physical Geography
Research subject
Physical Geography
Identifiers
urn:nbn:se:su:diva-142201 (URN)978-91-7649-844-6 (ISBN)978-91-7649-845-3 (ISBN)
Public defence
2017-06-09, De Geersalen, Geovetenskapens hus, Svante Arrhenius väg 14, Stockholm, 13:00 (English)
Opponent
Supervisors
Funder
Sida - Swedish International Development Cooperation Agency, SWE-2011-066Sida - Swedish International Development Cooperation Agency, 2015-000032Lars Hierta Memorial Foundation, grant FO2015-0569
Note

At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 3: Manuscript. Paper 4: Manuscript.

Available from: 2017-05-17 Created: 2017-04-27 Last updated: 2017-05-23Bibliographically approved

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