Computing structural and functional flow and sediment connectivity with a new aggregated index: A case study in a...

Area of Science:

• Hydrology
• Geomorphology
• Environmental Science

Background:

• Hydrological connectivity in large catchments is complex, influenced by natural and human factors.
• Existing methods for modeling flow and sediment connectivity (FSC) have limitations in capturing these dynamics.

Purpose of the Study:

• To propose and test a new aggregated index (AIC) for modeling structural and functional flow and sediment connectivity (FSC).
• To compare the performance of AIC with an existing index (Borselli's) in a Mediterranean catchment.

Main Methods:

• Developed an aggregated index (AIC) using topography, C-RUSLE, RUSLE2 rainfall erosivity, residual topography, and soil permeability.
• Applied AIC and Borselli's index to a 380 km² Mediterranean catchment with diverse land uses and lithology.
• Utilized LiDAR-derived DEM, D-Infinity algorithm, and data from 12 weather stations for high-resolution simulations.

Main Results:

• AIC produced a normal distribution of connectivity values, unlike Borselli's approach, offering a wider range.
• Both indices showed similar differences in structural FSC (FSC-st) across land uses, aligning with soil erosion rates.
• AIC better reflected spatial characteristics at sub-catchment scales and captured spatio-temporal dynamics of functional FSC (FSC-fn).

Conclusions:

• The new aggregated connectivity index (AIC) is a suitable tool for geomorphic and hydrological studies at catchment scale.
• AIC provides a more robust representation of hydrological connectivity and sediment dynamics compared to existing methods.
• Understanding seasonal variations in FSC-fn is crucial for predicting runoff and sediment responses throughout the year.