ALBERT

Description: In this study, the Mean Transit Time and Mixing Model Analysis methods are combined to unravel the runoff generation process of the San Francisco River basin (73.5 km**2) situated on the Amazonian side of the Cordillera Real in the southernmost Andes of Ecuador. The montane basin is covered with cloud forest, sub-páramo, pasture and ferns. Nested sampling was applied for the collection of streamwater samples and discharge measurements in the main tributaries and outlet of the basin, and for the collection of soil and rock water samples. Weekly to biweekly water grab samples were taken at all stations in the period April 2007-November 2008. Hydrometric data, Mean Transit Time and Mixing Model Analysis allowed preliminary evaluation of the processes controlling the runoff in the San Francisco River basin. Results suggest that flow during dry conditions mainly consists of lateral flow through the C-horizon and cracks in the top weathered bedrock layer, and that all subcatchments have an important contribution of this deep water to runoff, no matter whether pristine or deforested. During normal to low precipitation intensities, when antecedent soil moisture conditions favour water infiltration, vertical flow paths to deeper soil horizons with subsequent lateral subsurface flow contribute most to streamflow. Under wet conditions in forested catchments, streamflow is controlled by near surface lateral flow through the organic horizon. Exceptionally, saturation excess overland flow occurs. By absence of the litter layer in pasture, streamflow under wet conditions originates from the A horizon, and overland flow.

Description: We investigated controls on the water chemistry of a South Ecuadorian cloud forest catchment which is partly pristine, and partly converted to extensive pasture. From April 2007 to May 2008 water samples were taken weekly to biweekly at nine different subcatchments, and were screened for differences in electric conductivity, pH, anion, as well as element composition. A principal component analysis was conducted to reduce dimensionality of the data set and define major factors explaining variation in the data. Three main factors were isolated by a subset of 10 elements (Ca2+, Ce, Gd, K+, Mg2+, Na+, Nd, Rb, Sr, Y), explaining around 90% of the data variation. Land-use was the major factor controlling and changing water chemistry of the subcatchments. A second factor was associated with the concentration of rare earth elements in water, presumably highlighting other anthropogenic influences such as gravel excavation or road construction. Around 12% of the variation was explained by the third component, which was defined by the occurrence of Rb and K and represents the influence of vegetation dynamics on element accumulation and wash-out. Comparison of base- and fast flow concentrations led to the assumption that a significant portion of soil water from around 30 cm depth contributes to storm flow, as revealed by increased rare earth element concentrations in fast flow samples. Our findings demonstrate the utility of multi-tracer principal component analysis to study tropical headwater streams, and emphasize the need for effective land management in cloud forest catchments.

Description: We investigated controls on the water chemistry of a South Ecuadorian cloud forest catchment which is partly pristine, and partly converted to extensive pasture. From April 2007 to May 2008 water samples were taken weekly to biweekly at nine different subcatchments, and were screened for differences in electric conductivity, pH, anion, as well as element composition. A principal component analysis was conducted to reduce dimensionality of the data set and define major factors explaining variation in the data. Three main factors were isolated by a subset of 10 elements (Ca2+, Ce, Gd, K+, Mg2+, Na+, Nd, Rb, Sr, Y), explaining around 90% of the data variation. Land-use was the major factor controlling and changing water chemistry of the subcatchments. A second factor was associated with the concentration of rare earth elements in water, presumably highlighting other anthropogenic influences such as gravel excavation or road construction. Around 12% of the variation was explained by the third component, which was defined by the occurrence of Rb and K and represents the influence of vegetation dynamics on element accumulation and wash-out. Comparison of base- and fast flow concentrations led to the assumption that a significant portion of soil water from around 30 cm depth contributes to storm flow, as revealed by increased rare earth element concentrations in fast flow samples. Our findings demonstrate the utility of multi-tracer principal component analysis to study tropical headwater streams, and emphasize the need for effective land management in cloud forest catchments.

Description: We investigated controls on the water chemistry of a South Ecuadorian cloud forest catchment which is partly pristine, and partly converted to extensive pasture. From April 2007 to May 2008 water samples were taken weekly to biweekly at nine different subcatchments, and were screened for differences in electric conductivity, pH, anion, as well as element composition. A principal component analysis was conducted to reduce dimensionality of the data set and define major factors explaining variation in the data. Three main factors were isolated by a subset of 10 elements (Ca2+, Ce, Gd, K+, Mg2+, Na+, Nd, Rb, Sr, Y), explaining around 90% of the data variation. Land-use was the major factor controlling and changing water chemistry of the subcatchments. A second factor was associated with the concentration of rare earth elements in water, presumably highlighting other anthropogenic influences such as gravel excavation or road construction. Around 12% of the variation was explained by the third component, which was defined by the occurrence of Rb and K and represents the influence of vegetation dynamics on element accumulation and wash-out. Comparison of base- and fast flow concentrations led to the assumption that a significant portion of soil water from around 30 cm depth contributes to storm flow, as revealed by increased rare earth element concentrations in fast flow samples. Our findings demonstrate the utility of multi-tracer principal component analysis to study tropical headwater streams, and emphasize the need for effective land management in cloud forest catchments.

Description: In this study, the Mean Transit Time and Mixing Model Analysis methods are combined to unravel the runoff generation process of the San Francisco River basin (73.5 km2) situated on the Amazonian side of the Cordillera Real in the southernmost Andes of Ecuador. The montane basin is covered with cloud forest, sub-páramo, pasture and ferns. Nested sampling was applied for the collection of streamwater samples and discharge measurements in the main tributaries and outlet of the basin, and for the collection of soil and rock water samples. Weekly to biweekly water grab samples were taken at all stations in the period April 2007–November 2008. Hydrometric data, Mean Transit Time and Mixing Model Analysis allowed preliminary evaluation of the processes controlling the runoff in the San Francisco River basin. Results suggest that flow during dry conditions mainly consists of lateral flow through the C-horizon and cracks in the top weathered bedrock layer, and that all subcatchments have an important contribution of this deep water to runoff, no matter whether pristine or deforested. During normal to low precipitation intensities, when antecedent soil moisture conditions favour water infiltration, vertical flow paths to deeper soil horizons with subsequent lateral subsurface flow contribute most to streamflow. Under wet conditions in forested catchments, streamflow is controlled by near surface lateral flow through the organic horizon. Exceptionally, saturation excess overland flow occurs. By absence of the litter layer in pasture, streamflow under wet conditions originates from the A horizon, and overland flow.

Description: Field observations of runoff generation in pristine montane cloud forests are scarce. However, this knowledge is important for a sustainable natural resources management. Here we report results of a study carried out in the San Francisco River basin (75,3 km2) located on the Amazonian side of the Cordillera Real in the southernmost Andes of Ecuador. The basin is mainly covered with cloud forest, sub-páramo, pasture and ferns. A nested sampling approach was used for the collection of stream water samples and discharge measurements in the main tributaries and outlet of the basin. Additionally, soil and rock water samples were collected. Weekly to biweekly water grab samples were taken at all stations in the period April 2007 to November 2008. Hydrometric, mean residence time and mixing model approaches allowed identifying the main hydrological processes that control the runoff generation in the basin. Results clearly reveal that flow during dry conditions mainly consists of lateral flow through the C-horizon and cracks in the top weathered bedrock layer. The data shows that all catchments have an important contribution of this deep water to runoff, no matter whether pristine or deforested. During normal to low precipitation intensities, when antecedent soil moisture conditions favor water infiltration, vertical flow paths to deeper soil horizons with subsequent lateral sub-surface flow contributes most to streamflow. Under wet conditions in forested catchments streamflow is controlled by near-surface lateral flow through the organic horizon, and it is unlikely that Horton overland flow occurs during storm events. By absence of the litter layer in pasture streamflow under wet conditions primarily originates from the rooted surface layers and the A horizon, and Hortonian overland flow during extreme events.