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UCL Home  /  Geography  /  People  /  Academic Staff  /  Richard Taylor  /  Research  /  Lucinda Mileham (PhD, 2004-2008)

Lucinda Mileham (PhD, 2004-2008)

The impact of climate change on terrestrial hydrology in a humid, equatorial catchment

Lucinda Mileham Elena Glacier


  • Lucinda is currently preparing a manuscript detailing the validation of the regional climate model, PRECIS, in the Upper Nile Basin of Uganda. Previous papers from her doctoral dissertation are listed (with lniks) below. High-resolution climate data generated from PRECIS experiments is available via the link below. Lucinda successfully defended and completed her doctoral dissertation in December 2008.



  1. Mileham, L., Taylor, R.G., Todd M., Tindimugaya, C. and J. Thompson, 2009. Climate change impacts on the terrestrial hydrology of a humid, equatorial catchment: sensitivity of projections to rainfall intensity. Hydrological Sciences Journal Vol. 54(4), pp. 727-738.
  2. Mileham, L., Taylor, R.G., Thompson, J., Todd, M. and Tindimugaya, C., 2008. Impact of rainfall distribution on the parameterisation of a soil-moisture balance model of groundwater recharge in equatorial Africa. Journal of Hydrology, Vol. 359, pp. 46-58.


  • NERC PhD Studentship (2004-2008)

Project partners

  • Water Resources Management Directorate, Ministry of Water and Environment (Uganda)

Project rationale
In Africa, mean continental surface temperatures have increased by approximately 0.7°C over the 20th Century and a further warming of 0.2 to 0.5 °C per decade is predicted for 2070-2100 (Hulme et al., 2001). This rise in surface air temperatures is expected to have significant impacts on terrestrial hydrology, an integral part of the climate system. Predicted hydrological changes in equatorial Africa where warming of 1.4°C is expected by 2050 (IPCC, 2001), include (1) an increase in precipitation of 5 to 30% from December to February (DJF) and 5 to 10 % from June to August (JJA) (Joubert and Hewitson, 1997), (2) increased evaporative demand (19 to 27%) (Hulme et al., 1999), and (3) greater runoff (Arnell, 1999). There remains, however, great uncertainty and variability in the spatial and temporal distribution of these changes. As the human response to climate change will generally be conducted at the catchment scale, evidence from low-resolution General Circulation Models (GCMs) and macro-scale hydrological models is of limited use to catchment-scale decision support systems for climate-induced hydrological change.

Catchment-scale analyses of the hydrological impacts of climate change are especially important in equatorial Africa where rainfall-fed agriculture and domestic water supplies are strongly influenced by climate variability and significant increases in water demand are anticipated from high population growth rates (3.6 %). Current estimates of freshwater resources (e.g. Shikomanov, 2000) and predictions of freshwater resources as a result of climate change (e.g. Kamga, 2001; Arnell, 2003; Legesse et al., 2003; Vörösmarty et al., 2005; Wit and Stankiewicz, 2006; Messager et al., 2006) are commonly defined in terms of mean annual river discharge. Such estimates and predictions not only disregard soil water (i.e., water transpired by plants) though it sustains almost all agricultural production in equatorial Africa but they also fail to indicate the proportion of freshwater available ephemerally as stormflow (i.e. runoff) and more enduringly as groundwater. The latter is the principle source of potable water in urban areas and often the only source available to dispersed rural communities. Understanding quantitatively the impact of climate variability and change on both catchment stores (i.e. soil water, groundwater) and flows (i.e. river discharge) is of critical importance to the development of strategies for adapting to climate change.

Previous research in the humid tropics has highlighted the importance of heavy precipitation events (>10 mm×day-1) to the magnitude of groundwater recharge (Taylor and Howard, 1996). The area averaging of local precipitation events in time and space that occurs in gridded output from climate models and gridded datasets (e.g., CRU2, UDEL, VASCLIMO), dilutes heavy or extreme precipitation events towards more moderate mean (Durman et al., 2001). This smoothing is expected to influence the estimation of groundwater recharge in tropical Africa but has yet to be investigated. The dearth of sustained measurements of groundwater head in the tropics constrains our understanding of recharge processes and calibration of recharge models. As observed by the Intergovernmental Panel on Climate Change in 2001 and 2007 (IPCC, 2001; 2007), groundwater is the major source of water across much of the world but the potential effects of climate change remain largely unstudied and poorly resolved.

Dynamical downscaling of GCMs can be achieved using a Regional Climate Model (RCM). The performance of the RCM is, however, strongly dependent upon how well boundary conditions, derived from reanalysis data (e.g. NCEP, ERA15, ERA40) or GCM simulations, represent the regional climatology. Operating at a grid resolution of 10 to 50 km, RCMs offer a better representation of mesoscale forcings associated with inland water bodies, vegetation characteristics, and relief that strongly influence terrestrial hydrology. Greater topographical control is critical as it improves the spatial and temporal distribution of orographic precipitation not represented in GCMs (Kotlarski et al., 2005, Giorgi et al., 1994; Jones et al., 1995; Christensen et al., 1997). A significant limitation to the performance of RCMs is the lack of good-quality high resolution observations to use as boundary conditions or for model validation. In East Africa, meteorological observations are sparse, incomplete or not readily available. A quantitative analysis of error and uncertainty in RCM-generated precipitation and temperature is a necessary precursor to climate impact studies employing RCM-derived estimates of climate variability and change.

Numerous studies of recent trends and variability in monthly climate over Africa have been conducted at regional and national scales (e.g., Fauchereau et al., 2003; Hulme et al., 2001, Kruger and Shongwe, 2004; Mahe et al., 2001; Malhi and Wright, 2004; Misra, 2003, Moron, 1997; Schreck and Semazzi, 2004; Unganai and Mason, 2001; Sun et al., 1999; Vizy and Cook, 2003). This research has, however, primarily concentrated on the mean annual cycle of precipitation and temperature (Kotlarski et al., 2005). Few studies have investigated daily modelled precipitation or temperature, especially in the humid tropics. At the daily time step, RCMs have been shown to simulate too many light precipitation events compared to station data (Christensen et al., 1998; Kato et al., 2001) but produce more realistic statistics of heavy precipitation capturing extreme events entirely absent in GCMs (Christensen et al., 1998; Jones, 1999). For climate change studies, multi-year to multi-decadal simulations are required to provide meaningful climate statistics, to identify significant systematic model errors and climate changes relative to internal model and observed climate variability, and to allow the atmospheric model to equilibrate with the land surface conditions (e.g Jones et al., 1997; Machenhaur et al., 1998; Christensen 1999; McGregor et al., 1999; Kato et al., 2001).

Overall aim:
This research seeks to determine quantitatively the impact of climate change on catchment hydrology and freshwater resources in a humid, equatorial catchment in Uganda.

Specific research objectives include:
• to evaluate the ability of a regional climate model (RCM), PRECIS (Providing Regional Climates for Impact Studies), to reproduce the magnitude and distribution, both spatial and temporal, of precipitation (1960 to 1990) in Uganda;
• to evaluate the ability of a RCM-driven soil-moisture balance model to represent the terrestrial hydrology (1960 to 1990) of a humid, equatorial catchment in Uganda; and
• to quantify the impacts of climate change (2070 to 2100) on catchment-scale terrestrial water resources in Uganda.