Abstract:
This thesis presents the spatial and temporal variability of d²H and d18O isotope signatures in the precipitation of a south ecuadorian montane cloud forest catchment. During the investigation period from 02.09.2010 to 25.12.2010 event sampling of freefall and throughfall was conducted along an altitudinal transect (1800m a.s.l. to 2800m a.s.l.) to investigate possible effects of altitude and land use on the isotope signature in precipitation. The data is further used to determine deuterium excess and the temporal variability during the investigation period. Temporal variability is mostly controlled by the prevailing air mass. During most time of the year, the study area is strongly affected by tropical trade winds. Due to the large input of reevaporated moisture to the air masses, which takes place during their passage over the amazon basin and during the orographic uplift at the slopes of the Andes, trade wind-related precipitation is highly enriched in heavy isotopes. High values in deuterium excess, which is used to asses the contribution of reevaporated moisture in precipitation, were observed during times of strong influence of trade winds. From Mid-October on, an ebbing of trade winds from the amazon basin was observed and the influence of other air masses rose. This change in weather patterns is consistent with considerably lower isotope signatures and deuterium excess in precipitation. Therefore, it can be concluded that the degree of reevaporation is low-er at that time. Spatial variability is mainly affected by the altitude effect, which reaches values of -1,12‰ × 100m-1 in the case of d²H and -0,22‰ × 100m-1 in the case of d18O in the study area. On average, throughfall is enriched compared to freefall by 2,28‰ of ²H and 0,31‰ of d18O, respectively. In combination with measurements of the isotope signatures of adjacent streams the data from this study allows determining and quantifying preferential path ways of water in the catchment and can be used to validate a hydrologic simulation model and to generate mixing models that allow to quantify the mean residence time of water in the catchment.
