Intraseasonal Drainage Network Dynamics in a Headwater Catchment of the Italian Alps

Abstract

In the majority of existing studies, streams are conceived as static objects that occupy predefined regions of the landscape. However, empirical observations suggest that stream networks are systematically and ubiquitously featured by significant expansion/retraction dynamics produced by hydrologic and climatic variability. This contribution presents novel empirical data about the active drainage network dynamics of a 5 km 2 headwater catchment in the Italian Alps. The stream network has been extensively monitored with a biweekly temporal resolution during a field campaign conducted from July to November 2018. Our results reveal that, in spite of the wet climate typical of the study area, more than 70% of the observed river network is temporary, with a significant presence of disconnected reaches during wet periods. Available observations have been used to develop a set of simple statistical models that were able to properly reconstruct the dynamics of the active stream length as a function of antecedent precipitation. The models suggest that rainfall timing and intensity represent major controls on the stream network length, while evapotranspiration has a minor effect on the observed intraseasonal changes of drainage density. Our results also indicate the presence of multiple network expansion and retraction cycles that simultaneously operate at different time scales, in response to distinct hydrological processes. Furthermore, we found that observed spatial patterns of network dynamics and unchanneled lengths are related to the underlying heterogeneity of geological attributes. The study offers novel insights on the physical mechanisms driving stream network dynamics in low-order alpine catchments.

The Stream Length Duration Curve: A Tool for Characterizing the Time Variability of the Flowing Stream Length

“…About 4.5 km of temporary network is active more than 50% of the time. The median length (9.3 km, corresponding to a duration of 50%) is very similar to the mean length (9.2 km; see Durighetto et al., 2020), suggesting that the distribution of active stream lengths is not significantly skewed. In the range of durations between 10% and 90%, the slope of the SLDC is pronounced and uniform, thereby implying that the whole stream network is very dynamical, and there are no preferential values of the active length that are observed with a particularly high probability.…”

“…Accordingly, in Equation , the only nonzero terms of the joint pdf of X are those of the type p 1000, … , 00 , p 1100, … , 00 , p 1110, … , 00 , …, p 1111, … , 10 , p 1111 … 11 and a single transition from 1 to 0 is allowed in the chain. As the position of each node in the physical space is not explicitly specified in the stochastic model, a sequence of wet and dry nodes of this type is consistent with a stream network in which the active reaches, during wetting, expand either upstream or downstream (Durighetto et al., 2020). Furthermore, the hierarchical scheme is also suited to describe active networks that are not continuous in the physical space because of nonmonotonic changes of the local persistency along the network (see Figure 3 and section 5).…”

“…For more information about the study catchment and the field surveys, the reader is referred to Durighetto et al. (2020).…”

“…Therefore, the parameter p k in Equation represents the mean local persistency of the node k (i.e., the average percentage of time during which the node k is active). The mean local persistency (hereafter local persistency) can be estimated from independent field surveys as the sample mean of X k , that is, , where Na k is the number of surveys in which the node k is active and N k the number of times the node k was surveyed (see, e.g., Durighetto et al., 2020). It is worth noting that the quantity p k is a local property in space, though temporally integrated.…”

“…In the last years, however, temporary and ephemeral streams have gained increasing attention from the scientific community. Many experimental studies have been conducted in different regions of the World to quantify event‐based and seasonal dynamics of the active stream network (Agren et al., 2015; Blyth & Rodda, 1973; Day, 1978; Datry et al., 2016; Doering et al., 2007; Durighetto et al., 2020; Godsey & Kirchner, 2014; Goulsbra et al., 2014; Gregory & Walling, 1968; Jaeger et al., 2007; Jensen et al., 2017, 2019; Lovill et al., 2018; Malard et al., 2006; Peirce & Lindsay, 2015; Roberts & Klingeman, 1972; Shaw, 2016; Shaw et al., 2017; van Meerveld et al., 2019; Whiting & Godsey, 2016; Zimmer & McGlynn, 2017). These field surveys revealed that stream network expansion/contraction generated by climate variability represents a general rule rather than an exception, and a major fraction of the existing drainage network is, in most circumstances, dynamical (e.g., Datry et al., 2014).…”