 Abstract | The interaction between climate and land-surface hydrology is extremely important in relation to long term water
resource planning. This is especially so in the presence of global warming and massive land use change, issues which
seem likely to have a disproportionate impact on developing countries. This thesis develops tools aimed at the study
and prediction of climate effects on land-surface hydrology (in particular streamflow), which require a minimum
amount of site specific data. This minimum data requirement allows studies to be performed in areas that are data
sparse, such as the developing world.
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A simple lumped dynamics-encapsulating conceptual rainfall-runoff model, which explicitly calculates the evaporative
feedback to the atmosphere, was developed. It uses the linear streamflow routing module of the rainfall-runoff model
IHACRES, with a new non-linear loss module based on the Catchment Moisture Deficit accounting scheme, and is referred
to as CMD-IHACRES. In this model, evaporation can be calculated using a number of techniques depending on the data
available, as a minimum, one to two years of precipitation, temperature and streamflow data are required. The model
was tested on catchments covering a large range of hydroclimatologies and shown to estimate streamflow well. When
tested against evaporation data the simplest technique was found to capture the medium to long term average well but
had difficulty reproducing the short-term variations.
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A comparison of the performance of three limited area climate models (MM5/BATS, MM5/SHEELS and RegCM2) was conducted
in order to quantify their ability to reproduce near surface variables. Components of the energy and water balance
over the land surface display considerable variation among the models, with no model performing consistently better
than the other two. However, several conclusions can be made. The MM5 longwave radiation scheme performed worse than
the scheme implemented in RegCM2. Estimates of runoff displayed the largest variations and differed from observations
by as much as 100%. The climate models exhibited greater variance than the observations for almost all the energy and
water related fluxes investigated.
¶
An investigation into improving these streamflow predictions by utilizing CMD-IHACRES was conducted. Using
CMD-IHACRES in an 'offline' mode greatly improved the streamflow estimates while the simplest evaporation technique
reproduced the evaporative time series to an accuracy comparable to that obtained from the limited area models alone.
The ability to conduct a climate change impact study using CMD-IHACRES and a stochastic weather generator is also
demonstrated. These results warrant further investigation into incorporating the rainfall-runoff model CMD-IHACRES
in a fully coupled 'online' approach. |
