Identificación de fuentes de generación de escorrentía en los Andes tropicales: estudio de múltiples modelos basados en trazadores

Abstract:

Mixing models have been applied to hydrogeochemical datasets to investigate runoff sourcing in experimental catchments. However, long-term application of these methodologies remains limited given the high costs related to the collection and hydrogeochemical analyses of water samples. In this study we applied two mixing models of different complexity to identify the runoff contributing sources (end-members) of a headwater catchment (21.7 km2) in the Ecuadorian Andes. We used a robust dataset of 19 hydrogeochemical tracers measured in weekly water samples from streamflow and eight potential end-members (precipitation, lake water, soil water, and spring water) for one-year. We applied a mixing model analysis (MMA) and an end-member mixing analysis (EMMA) to the geochemical dataset to identify the contributions from different end-members to runoff and compared the water fractions determined by both methods. Results show that both methods, MMA and EMMA, yield comparable fractions of rainfall (21.9% and 21.4%), soil water (52.7% and 52.3%), and spring water (21.1% and 28.7%) to streamflow. Results also indicate that MMA using 6 conservative tracers allows for a clear identification of the three end-members and similar proportions of water contribution to runoff than EMMA. Our findings depict the value of conducting detailed hydrogeochemical characterizations to define efficient (low cost) sampling strategies that provide valuable hydrological information that can be used by water managers. Moreover, the delineation of such strategies can help to maintain the collection of hydrogeochemical data at finer temporal resolutions for longer time periods in order to identify long-term changes in catchment hydrological behavior.

Año de publicación:

2018

Keywords:

• Modelos De Mezcla
• Fuentes geográficas
• Andes Tropicales
• Tesis De Maestria En Ecohidrologia
• HUMEDALES

Fuente:

rraae