River deltas are depositional landforms built directly downstream of many rivers and carrying fluxes to the shoreline via a complex set of channels. River deltas exhibit a large variability in their morphology as a consequence of the physical processes that shape them, e.g., external forcings such as tides and waves, or sediment composition. Understanding and quantifying the patterns imprinted on the landscape as a function of the physical processes that created them will enable us to infer processes from observed imagery and also pave the way to a quantitative approach to delta classification, which is currently lacking. My research on this topic has attempted to fill this scientific and applied-research void by studying river deltas through the lens of their channel networks. My work has focused on (1) developing a mathematical framework for delta connectivity and vulnerability assessment based on graph theory [Tejedor et al., 2015a]; (2) defining a set of metrics to quantify the structure and flux partition of delta channel network [Tejedor et al., 2015b, Tejedor et al., 2016]; and (3) identifying first order principles underlying delta self-organization, showing evidence that delta networks achieve configurations that maximize the diversity of water and sediment flux delivery to the shoreline. [Tejedor et al., 2017a].
Landscape topography is the expression of the dynamic equilibrium between external forcings, such as climate and tectonics, and the underlying lithology. The form, spatial arrangement and dynamics of landforms are archives that document the history of landscape evolution. My research in this field capitalizes on high spatial and temporal resolution data collected from an unique experimental facility that allows to self-evolve landscape topographies under different uplift rates and rainfall intensities. Our previous results revealed an emergent hierarchical erosional signature of steady-state landscapes, which is spatially-variable but time-invariant and in which the likelihood of eroding above or below the landscape median depends on the specific geomorphic regime, e.g., hillslope versus fluvial [Tejedor et al. 2017b] In my ongoing research on this topic, preliminary analysis reveals the generation of climatic driven knickpoints during the onset of the transient state produced by an increase in rainfall intensity.
Connectivity is at the same time the result and the driver of many processes acting on natural and engineered systems. The analysis of the networked structures emerging from system connectivity reveals mechanisms behind the properties of the underlying natural processes. My research on this field focuses on developing theory and applications relevant to environmental problems and to improving our understanding of the Earth system. My work has focused on (1) defining metrics to quantify fundamental properties of delta channel network, wherein directionality and the planarity are key features [Tejedor et al., 2015a,b]; (2) developing a new framework where network robustness is assessed within a dual connectivity framework, acknowledging both the joint dynamics of the Active and Idle Networks [Tejedor et al., 2017c]; and (3) studying the dynamics of diffusion processes acting on directed multiplex networks (coupled multilayer networks where at least one layer consists of a directed graph), showing a new phenomenology, which is genuinely induced by the directionality of the links: the emergence of a prime regime of coupling for which directed multiplex networks exhibit a faster diffusion at an intermediate degree of coupling than when the two layers are fully coupled [Tejedor et al., 2018a,b]