Edison Timbe

Addressing sources of uncertainty in runoff projections for a data scarce catchment in the Ecuadorian Andes

Future climate projections from general circulation models (GCMs) predict an acceleration of the global hydrological cycle throughout the 21st century in response to human-induced rise in temperatures. However, projections of GCMs are too coarse in resolution to be used in local studies of climate change impacts. To cope with this problem, downscaling methods have been developed that transform climate projections into high resolution datasets to drive impact models such as rainfall-runoff models. Generally, the range of changes simulated by different GCMs is considered to be the major source of variability in the results of such studies. However, the cascade of uncertainty in runoff projections is further elongated by differences between impact models, especially where robust calibration is hampered by the scarcity of data.Here, we address the relative importance of these different sources of uncertainty in a poorly monitored headwater catchment of the Ecuadorian Andes. Therefore, we force 7 hydrological models with downscaled outputs of 8 GCMs driven by the A1B and A2 emission scenarios over the 21st century. Results indicate a likely increase in annual runoff by 2100 with a large variability between the different combinations of a climate model with a hydrological model. Differences between GCM projections introduce a gradually increasing relative uncertainty throughout the 21st century. Meanwhile, structural differences between applied hydrological models still contribute to a third of the total uncertainty in late 21st century runoff projections and differences between the two emission scenarios are marginal.

Global Climate Change Impacts on Local Climate and Hydrology

Global climate change will most likely have a severe impact on local climate and hydrological cycling in the tropical montane rainforest. We used a simple statistical downscaling technique for eight general circulation models and two IPCC AR4 emission scenarios (A1B, A2) to forecast feasible local climate conditions for the San Francisco river basin for three future time slices (2010–2039, 2040–2069, 2070–2099). These simulations were then used as forcing data for an ensemble of seven catchment scale rainfall-runoff models to investigate the effects on local hydrological fluxes. Precipitation for both emission scenarios is expected to increase, especially in the months May and June. These increases in precipitation input will lead to even more dynamic discharges as today. However, part of the increasing water input is compensated by raising evapotranspiration due to higher temperatures. Finally, we give an outlook on feasible future trends of water-related ecosystem services under climate change.