EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Uncertainty in the modelling of large scale flood events in the Barotse floodplain, Zambia

Tom Willis1, Mark Smith1, Donall Cross2, Andrew Hardy3, Georgina Ettritch3, Happiness Malawo4, Mweemba Sinkombo4, Cosmas Chalo4, and Chris Thomas5
Tom Willis et al.
  • 1School of Geography, University of Leeds, Leeds, UK
  • 2Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, UK
  • 3Department of Geography and Earth Sciences, Aberystwyth University, Aberystwyth, UK
  • 4Water Resource Management Authority, Mongu, Zambia
  • 5College of Science, University of Lincoln, Lincoln, UK

The Barotse floodplain in the Western Province of Zambia, is a major feature of the Upper Zambezi River, covering an area of 11,000km2, and is inundated annually by a flood cycle that ranges from minimum values in September, to peak levels in April. The annual flooding of the area provides a number of challenges, and critically is a significant component of the life cycle of mosquitos, the principle vector for the transmission of malaria. A research project, FLOODMAL, has been developed to apply process based modelling approaches to the life cycle of the mosquito in the floodplain. A significant component of this approach is the development of a 1D-2D model which can be used to predict the formation of water bodies that are essential to the mosquito breeding cycle. This research presents the uncertainties associated with developing the flood model, with an emphasis on model performance through simulation time. In a typical model exercise, the calibration of input parameters are associated with ensuring that model performance is optimised for representing the peak of a flood event. This can be at the cost of providing a consistent level of model performance throughout a simulation, which is essential in this research.

Using the LISFLOOD-FP computer code, and TanDEM-X1 terrain data, a baseline model of the Barotse floodplain was developed for the 2009 and 2018 events. A set of initial model runs identified key processes to be represented in the model, including evaporation and infiltration. The calibration of the model was focused on defining parameters for surface roughness, channel roughness, evaporation, infiltration, and defining channel topography. A number of datasets were available for model calibration, such as LandSAT imagery to compare observed and modelled extent at various points throughout the year, and downstream river gauge data. To further understand the uncertainties associated with the modelling, sensitivity analysis was undertaken using an emulator- based approach to define the contribution of the input parameters to overall model variance. The results indicate that parameters that control the movement of water across the floodplain (surface roughness) are generally the most significant of the inputs at all points in the year, although the level of this significance changes at different phases.

How to cite: Willis, T., Smith, M., Cross, D., Hardy, A., Ettritch, G., Malawo, H., Sinkombo, M., Chalo, C., and Thomas, C.: Uncertainty in the modelling of large scale flood events in the Barotse floodplain, Zambia , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19000,, 2020


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  • CC1: Comment on EGU2020-19000, Chiara Arrighi, 06 May 2020

    Hi Tom, I was not kidding when I said "mosquitos and cars are both dangerous". In African countries floods often cause malaria/cholera outbreak which leads to fatalities. In ''developed'' countries the main cause of fatalities is related to car use in flooded roads. It is interesting to see how the relationship between flood risk and health has such different patways. (I've been working mostly about cars and floods, but I had some experience in sub-saharan countries).

    • AC1: Reply to CC1, Tom Willis, 06 May 2020

      Hi Chiara, it’s a really good question, and you’re right, the difference in what is considered risk really does depend on where you are in the world. It was interesting working on this project, where the emphasis of risk is on the drying phase of a flood rather than the maximum depths and extents, which is what tends to happen in the UK. Calibration of hydrodynamic models in the UK tend to focus on making sure this part of the model is right, rather occasionally at the expense of this part of the flood event, and it tends to get overlooked. What experience have you had in Sub-Saharan countries? Is it flood related?

      • CC3: Reply to AC1, Chiara Arrighi, 06 May 2020

        I worked on this project and as facilitator in many country workshops, one in Lusaka. May be you can find some useful geodatasets in that site...

  • CC2: Comment on EGU2020-19000, Joanne Williams, 06 May 2020

    Thanks Tom, good to see connections being made between physics and health impacts. Interesting work.

    • AC2: Reply to CC2, Tom Willis, 06 May 2020

      Yes it is! I would be interesting to see more projects where this is happening, and understanding how uncertainties in these models might propagate themselves through the modelling chain