Stream Network Dynamics of Non‐Perennial Rivers: Insights From Integrated Surface‐Subsurface Hydrological Modeling of Two Virtual Catchments

Author:

Zanetti F.1ORCID,Botter G.1ORCID,Camporese M.1ORCID

Affiliation:

1. Department of Civil Environmental and Architectural Engineering University of Padova Padova Italy

Abstract

AbstractUnderstanding the spatio‐temporal dynamics of runoff generation in headwater catchments is challenging, due to the intermittent and fragmented nature of surface flows. The active stream network in non‐perennial rivers contracts and expands, with a dynamic behavior that depends on the complex interplay among climate, topography, and geology. In this work, CATchment HYdrology, an integrated surface–subsurface hydrological model (ISSHM), is used to simulate the stream network dynamics of two virtual catchments with the same, spatially homogeneous, subsurface characteristics (hydraulic conductivity, porosity, water retention curves) but different morphology. We run two sets of simulations to reproduce a sequence of steady‐states at different catchment wetness levels and transient conditions and analyze the joint variations of the stream length (L) and discharge at the outlet (Q) with high spatio‐temporal resolutions. The shape of the L(Q) curves differs in the two catchments but does not depend on the climate forcing, as it is mainly controlled by the underlying topography. We then analyzed the suitability of the topographic wetness index and the contributing area to identify the spatial configuration of the maximum stream length in the two catchments. These two morphometric parameters provided a good estimate of the spatial distribution of the maximum flowing network in both the study catchments. Our numerical simulations indicate that ISSHMs have the potential to accurately describe the spatio‐temporal variations of the stream networks and the processes driving such dynamic behavior and that, overall, they can be useful tools to gain insights into the main physical drivers of non‐perennial streams.

Funder

H2020 Excellent Science

Publisher

American Geophysical Union (AGU)

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