1. The Impact of Climate Change on a Humid, Equatorial Catchment in Uganda.
Lucinda Mileham, Dr Richard Taylor, Dr Martin Todd
Department of Geography – University College London

2. Why is it important in Uganda
Changing Climate
Africa has experienced a mean continental 20th Century warming of 0.7 °C
The periods of greatest warming are and post 1970, with the five warmest years on record occurring since 1988.
decrease in runoff of 17 % in major river basins
Predicted temperature increase of between 2-6 °C by 2100
Accompanied by evaporative increases of % by 2080
Changes in the seasonality and intensity of future precipitation
Why is it important in Uganda
Dependence on rainfall-fed agriculture
Reliance on localised (untreated) sources of water
Groundwater is the only reliable source of potable water
Current population of 25.8 million is estimated to more than double by 2025

3. Main Objective Specific objectives
To quantify the impacts of climate change on groundwater recharge and surface runoff in Uganda, East Africa.
Specific objectives
To evaluate the ability of a RCM to reproduce the current ( ) climate at scales appropriate for hydrological modelling.
To develop a soil-moisture balance model for groundwater modelling operating at a scale which allows coupling with a RCM.
To quantify the impacts of climate change (2070 to 2100) on catchment-scale terrestrial water resources in Uganda.

4. PRECIS
What is PRECIS? (Providing Regional Climates for Impacts Studies)
A simple-to-use PC-based RCM, has been developed by the Hadley Centre (UK) specifically to address the need for countries to make regional-scale climate predictions.
Model resolution 25 or 50 km²
Daily time-step
Boundary conditions - A three member ensemble of central experiments ( )
- ECMWF ERA 40 reanalysis experiment
- A three member ensemble of SRES A2 scenario experiments ( )
- A single SRES B2 scenario experiment
User defined emission scenarios, and specification of output levels
Limited user manipulation – land use, inland water features and topography can be changed but model parameterizations cannot be altered.

5. Study Area / Method Catchment Scale River Mitano catchment.
2, 098 km 2
High relief and incised drainage reflect a runoff-dominated regime
Land use - Agriculture (79 %), Grassland (17 %) wetland (3 %), small areas of forest and plantation

6. Regional scale - PRECIS Mean Climatology
Bi-modal precipitation regime
Good representation of the temporal distribution of precipitation
Overestimation of precipitation between December-March

7. PRECIS
CRU
VasCLIMO
TRMM
GPCC
GPCP

8. Catchment-scale validation of precipitation
<10 % error in mean annual precipitation
Better representation of Sep-Nov rainy season
Magnitude remains poorly resolved in Jan-Mar
Poor representation of peak Precipitation in first rains

9. Future PRECIS Change (2070-2100) cont …
Increased precipitation July-December
Shift in timing of peak seasons
Mean annual precipitation increase of 14 %
3.5 °C increase in Temperature
53 % increase in PET

10. Soil moisture balance model (SMBM)
Simulates changes in soil moisture (‘green water’) and provides estimates of rainfall-fed, groundwater recharge and runoff (infiltration excess)
Can be run as a lumped parameter model OR as a semi-distributed model by running for different soil, slope and vegetation characteristics.
Critically, can be run using gridded RCM or downscaled GCM data.

11. SMBM calibration (1965 – 1979)
Validated against discharge data from the River Mitano gauging station
Poor performance is due to lag responses
Stormflow is significantly better represented than baseflow due to its shorter lag response
Should only be used to represent baseflow and stormflow on annual and longer timescales
SMBM reproduces well the mean annual recharge and runoff

12. Mean monthly delta factors
Difference between and modelled precipitation.
All seasons exhibit small increases in precipitation across Uganda
Delta factors 0.9 to 1.8
Mean monthly factor
Applied to daily data
DJF
MAM
JJA
SON

13. Effect on Hydrology
14 % increase in Recharge
84 % increase in Runoff.

14. Changes in Daily Precipitation Distribution
Monthly Delta factors fail to account for changes in the daily precipitation distribution
Reduction in small precipitation events (<10 mm)
Increase in large precipitation events (>10 mm)
Variable results for extreme precipitation events
The distribution of precipitation is key for modelling of recharge and runoff

15. Impacts on hydrology The transformation method –
matches future precipitation
and historical precipitation
distributions.
66 % increase in Recharge
123 % increase in Runoff
Fails to account for changes
in occurrence

16. Conclusion
PRECIS does a reasonable job at representing the climate of east Africa
Observational uncertainty is large
SMBM represents well the mean annual catchment recharge and runoff
Recharge and runoff are sensitive to the distribution of precipitation
Increase in the magnitude and intensity of precipitation
Large increases in evapotranspiration and temperature
Increases in surface runoff and groundwater recharge under future climates