Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Building a coherent hydro-climatic modelling framework for the data limited Kilombero Valley of Tanzania
Stockholm University, Faculty of Science, Department of Physical Geography.
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. , p. 44
Series
Dissertations from the Department of Physical Geography, ISSN 1653-7211 ; 63
Keywords [en]
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: urn:nbn:se:su:diva-142201ISBN: 978-91-7649-844-6 (print)ISBN: 978-91-7649-845-3 (electronic)OAI: oai:DiVA.org:su-142201DiVA, id: diva2:1091736
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: 2018-01-13Bibliographically approved
List of papers
1. Comparing global precipitation data sets in eastern Africa: a case study of Kilombero Valley, Tanzania
Open this publication in new window or tab >>Comparing global precipitation data sets in eastern Africa: a case study of Kilombero Valley, Tanzania
2016 (English)In: International Journal of Climatology, ISSN 0899-8418, E-ISSN 1097-0088, Vol. 36, no 4, p. 2000-2014Article in journal (Refereed) Published
Abstract [en]

In the face of limited or no precipitation data, global precipitation data sets (GPDs) may provide a viable alternative to gauge or ground radar data. This study aims to provide guidance to the choice of GPDs targeting scales relevant to water resources management in data poor regions. Specifically, the 34 000 km(2) Kilombero Valley in central Tanzania, where water resource management is seen as integral to poverty reduction and food security, is used as a case study for performance evaluation of seven GPDs and their ensemble mean against the Tropical Rainfall Measuring Mission (TRMM) multi-satellite precipitation analysis research-grade product v7 (TRMMv7). The GPDs include one satellite rainfall product [Climate Prediction Center morphing technique v1.0 CRT (CMORPH)], three reanalysis products [Climate Forecasting System Reanalysis (CFSR), European reanalysis interim (ERA-i) and Modern Era Retrospective-Analysis for Research and Applications (MERRA)] and three interpolated data sets [Climate Research Unit Time Series 3.21 (CRU), Global Precipitation and Climatology Center v6 data set (GPCC) and University of Delaware Air Temperature and Precipitation v3.01 data set (UDEL)]. Standard statistical performance measures and spatial patterns were evaluated for the common overlap time period 1998-2010. For this region, the principal seasonality of the climatology was well represented in all GPDs; however, the intraseasonal variability and the spatial precipitation patterns were less well represented. The ensemble mean and GPCC had the best performance with regard to the analysis of the time series while CMORPH and GPCC had the best performance with regard to the spatial pattern analysis. These results indicate that the spatial scale intended for application is a major factor impacting the suitability of a given GPD for hydrometrological studies that form a basis for development of water management strategies.

Keywords
climate, evaluation, Kilombero Valley, reanalysis, satellite rainfall product, Tanzania, TRMM, water resource management
National Category
Earth and Related Environmental Sciences
Research subject
Physical Geography
Identifiers
urn:nbn:se:su:diva-129198 (URN)10.1002/joc.4476 (DOI)000372036800032 ()
Available from: 2016-06-10 Created: 2016-04-17 Last updated: 2018-01-24Bibliographically approved
2. Interpreting characteristic drainage timescale variability across Kilombero Valley, Tanzania
Open this publication in new window or tab >>Interpreting characteristic drainage timescale variability across Kilombero Valley, Tanzania
Show others...
2015 (English)In: Hydrological Processes, ISSN 0885-6087, E-ISSN 1099-1085, Vol. 29, no 8, p. 1912-1924Article in journal (Refereed) Published
Abstract [en]

We explore seasonal variability and spatiotemporal patterns in characteristic drainage timescale (K) estimated from river discharge records across the Kilombero Valley in central Tanzania. K values were determined using streamflow recession analysis with a Brutsaert-Nieber solution to the linearized Boussinesq equation. Estimated K values were variable, comparing between wet and dry seasons for the relatively small catchments draining upland positions. For the larger catchments draining through valley bottoms, K values were typically longer and more consistent across seasons. Variations in K were compared with long-term averaged, Moderate-resolution Imaging Spectroradiometer-derived monthly evapotranspiration. Although the variations in K were potentially related to evapotranspiration, the influence of data quality and analysis procedure could not be discounted. As such, even though recession analysis offers a potential approach to explore aquifer release timescales and thereby gain insight to a region's hydrology to inform water resources management, care must be taken when interpreting spatiotemporal shifts in K in connection with process representation in regions like the Kilombero Valley.

Keywords
characteristic drainage timescale, streamflow recession analysis, Kilombero Valley, water resources management
National Category
Physical Geography
Research subject
Physical Geography
Identifiers
urn:nbn:se:su:diva-142200 (URN)10.1002/hyp.10304 (DOI)000352564200004 ()
Available from: 2017-04-27 Created: 2017-04-27 Last updated: 2018-01-24Bibliographically approved
3. Advancing understanding in data limited conditions: Estimating contributions to streamflow across Tanzania’s rapidly developing Kilombero Valley
Open this publication in new window or tab >>Advancing understanding in data limited conditions: Estimating contributions to streamflow across Tanzania’s rapidly developing Kilombero Valley
(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.

Keywords
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:nbn:se:su:diva-142193 (URN)
Available from: 2017-04-27 Created: 2017-04-27 Last updated: 2018-01-24Bibliographically approved
4. Statistical downscaling of global precipitation datasets in data limited regions: a case study of Kilombero Valley, Tanzania
Open this publication in new window or tab >>Statistical downscaling of global precipitation datasets in data limited regions: a case study of Kilombero Valley, Tanzania
(English)Manuscript (preprint) (Other academic)
Abstract [en]

This study explored the potential for spatial downscaling of Global precipitation datasets (GPD) to improve streamflow simulation in data limited regions. Specifically, we used Kilombero Valley in central Tanzania as an example of an area characterized by rapid large scale agricultural intensification where observational data are limited. Two catchments in Kilombero Valley were considered as case studies to explore the potential of downscaling GPDs based on the three downscaling methods: quantile mapping (QM), daily percentages (DP) and model based bias correction (ModB). The downscaled GPDs were then evaluated based on streamflow simulations. A simple bucket-type runoff model (HBV) was used to simulate streamflow for the two catchments using rain gauge, non-downscaled and downscaled precipitation data as input. Investigated GPDs include two satellite rainfall products, three reanalysis products and three interpolated products. Results showed that applying QM based on limited observed data tends to aggravate streamflow simulations due to a potential lack of representativeness of a rain gauge observation at the scale of a hydrological catchment. ModB improved results for all GPD downscaling and combining QM and ModB improved simulations yet further (but only in some cases). These results indicate that there are benefits in using an integrated approach, for example combining streamflow and rain gauge data to downscale GPDs, in order to bridge the scale mismatch between precipitation data and water management scale.

Keywords
Statistical dowscaling, Quantile mapping, HBV, CMORPH, TRMM, CFSR, ERA-i, MERRA, CRU, GPCC, UDEL, Kilombero, Tanzania, Eastern Africa, Precipiation
National Category
Physical Geography
Research subject
Physical Geography
Identifiers
urn:nbn:se:su:diva-142195 (URN)
Available from: 2017-04-27 Created: 2017-04-27 Last updated: 2018-01-24Bibliographically approved

Open Access in DiVA

Building a coherent hydro-climatic modelling framework for the data limited Kilombero Valley of Tanzania(1680 kB)66 downloads
File information
File name FULLTEXT02.pdfFile size 1680 kBChecksum SHA-512
8fc16ef1b705ba22c7104d4eebf039fe164285b014ea06485d4a4952d43f2fc02e531055548490ce1d8bd221b633665ef425e54de7b3a5dd099bfa522bf73678
Type fulltextMimetype application/pdf

Search in DiVA

By author/editor
Koutsouris, Alexander
By organisation
Department of Physical Geography
Physical Geography

Search outside of DiVA

GoogleGoogle Scholar
Total: 70 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

isbn
urn-nbn

Altmetric score

isbn
urn-nbn
Total: 462 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf