Controls on hydrological (dis)connectivity in a headwater-dominated sub-catchment: Insights through process-based integrated hydrology simulations
Abstract
Hydrological (dis)connectivity, in the sense of surface and subsurface runoff (dis)connectivity, emerges from the formation of spatial flow patterns across scales. As such, hydrological connectivity can not be directly measured, but often manifests itself in observable hydrological signatures, such as hydrographs and water balance. These signatures are indeed good indicators of the temporal evolution of connectivity, especially in first-order catchments where the hydrograph directly corresponds to the meteorological forcing. However, it is unclear to what extent the hydrographs of headwater-dominated streams can reveal information on the evolution of connectivity in a sub-catchment. This contribution aims to answer this question by synthesizing findings of preliminary studies by the authors and a new numerical study. The new numerical study considers integrated hydrology in a 15 km2 sub-catchment in the East River Watershed, Colorado, USA, namely the Lower Triangle (LT). The LT is fed by high-energy mountain streams from its headwater catchments, which contribute the majority of the discharge measured at the LTs outlet. We run a series of simulations with varying soil parameters and forcing. We then use particle tracking to compute flow paths and residence times for these simulations. Finally, we compare and contrast emerging flow path configurations with classical indices of hydrological connectivity from the literature, and relate them to the hydrograph at the outlet of the domain. The results of our study imply that, especially in headwater-dominated sub-catchments, it is likely to get the right hydrograph for the wrong reason. This is relevant for model applications that are interested in quantities beyond the catchment hydrograph, for example biogeochemical models driven by hydrological fluxes. Here, the incorrect representation of the hydrological connectivity may lead to incorrect hotspots of biogeochemical activity. Due to the multi-scale nature of processes, such errors will aggregate across scales, leading to incorrect spatial patterns of chemical species.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2021
- Bibcode:
- 2021AGUFM.H33J..01O