Tejedor, Alejandro

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Tejedor, Alejandro
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alejandro.tejedor@sorbonne.ae
ORCID
0000-0002-3800-5304
Scopus Author ID
25625316200
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  • Publication
    Channel Network Control on Seasonal Lake Area Dynamics in Arctic Deltas
    (2020)
    Tejedor, Alejandro 
    ;
    Foufoula-Georgiou, Efi
    ;
    Piliouras, Anastasia
    ;
    Rowland, Joel
    ;
    Schwenk, Jon
    ;
    Vulis, Lawrence
    The abundant lakes dotting arctic deltas are hotspots of methane emissions and biogeochemical activity, but seasonal variability in lake extents introduces uncertainty in estimates of lacustrine carbon emissions, typically performed at annual or longer time scales. To characterize variability in lake extents, we analyzed summertime lake area loss (i.e., shrinkage) on two deltas over the past 20 years, using Landsat-derived water masks. We find that monthly shrinkage rates have a pronounced structured variability around the channel network with the shrinkage rate systematically decreasing farther away from the channels. This pattern of shrinkage is predominantly attributed to a deeper active layer enhancing near-surface connectivity and storage and greater vegetation density closer to the channels leading to increased evapotranspiration rates. This shrinkage signal, easily extracted from remote sensing observations, may offer the means to constrain estimates of lacustrine methane emissions and to develop process-based estimates of depth to permafrost on arctic deltas.
    Scopus© Citations 4  640  68
  • Publication
    Climate Signatures on Lake And Wetland Size Distributions in Arctic Deltas
    (2021)
    Tejedor, Alejandro 
    ;
    Vulis, Lawrence
    ;
    Zaliapin, Ilya
    ;
    Rowland, Joel C.
    ;
    Foufoula-Georgiou, Efi
    Lake areas in arctic deltas exhibit a lognormal distribution associated with a simple mechanistic growth process. 2. Wetland areas exhibit a power law distribution consistent with inundated topography. 3. Colder arctic deltas have larger average lake sizes, likely due to thicker permafrost restricting sub-lake hydrologic connectivity.
    Scopus© Citations 3  32  24
  • Publication
    Dynamic Clusters to Infer Topologic Controls on Environmental Transport of River Networks
    (2022)
    Tejedor, Alejandro 
    ;
    Roy, Juthika
    ;
    Singh, Arvind
    The knowledge of structural controls of river networks (RNs) on transport dynamics is important for modeling and predicting environmental fluxes. To investigate impacts of RN’s topology on transport processes, we introduce a systematic framework based on the concept of dynamic clusters, where the connectivity of subcatchments is assessed according to two complementary criteria: minimum- and maximum-flow connectivity. Our analysis from simple synthetic RNs and several natural river basins across the United States reveals the key topological features underlying the efficiency of flux transport and aggregation. Namely, the timing of basin-scale connectivity at low-flow conditions is controlled by the abundance of topologically asymmetric junctions (side-branching), which at the same time, result in a slow-down of the flux convergence at the outlet (maximum-flow). Our results, when compared with observed topological trends in RNs as a function of climate, indicate that humid basins exhibit topologies which are “naturally engineered” to slow-down fluxes.
    Scopus© Citations 3  62  16
  • Publication
    Earthcasting: Geomorphic Forecasts for Society
    (2021)
    Tejedor, Alejandro 
    ;
    Ferdowsi, B
    ;
    Gartner, J. D
    ;
    Nardin, W
    ;
    Miller, K. L.
    ;
    Kasprak, A.
    ;
    Johnson, K. N
    Over the last several decades, the study of Earth surface processes has progressed from a descriptive science to an increasingly quantitative one due to advances in theoretical, experimental, and computational geosciences. The importance of geomorphic forecasts has never been greater, as technological development and global climate change threaten to reshape the landscapes that support human societies and natural ecosystems. Here we explore best practices for developing socially relevant forecasts of Earth surface change, a goal we are calling “earthcasting”. We suggest that earthcasts have the following features: they focus on temporal (1–100years) and spatial (1m–10km) scales relevant to planning; they are designed with direct involvement of stakeholders and public beneficiaries through the evaluation of the socioeconomic impacts of geomorphic processes; and they generate forecasts that are clearly stated, testable, and include quantitative uncertainties. Earthcasts bridge the gap between Earth surface researchers and decision-makers, stakeholders, researchers from other disciplines, and the general public. We investigate the defining features of earthcasts and evaluate some specific examples. This paper builds on previous studies of prediction in geomorphology by recommending a roadmap for (a) generating earthcasts, especially those based on modeling; (b) transforming a subset of geomorphic research into earthcasts; and (c) communicating earthcasts beyond the geomorphology research community. Earthcasting exemplifies the social benefit of geomorphology research, and it calls for renewed research efforts toward further understanding the limits of predictability of Earth surface systems and processes, and the uncertainties associated with modeling geomorphic processes and their impacts.
    Scopus© Citations 2  222  53
  • Publication
    Evolution and transformation of early modern cosmological knowledge: a network study
    (2020)
    Tejedor, Alejandro 
    We investigated the evolution and transformation of scientifc knowledge in the early modern period, analyzing more than 350 diferent editions of textbooks used for teaching astronomy in European universities from the late ffteenth century to mid-seventeenth century. These historical sources constitute the Sphaera Corpus. By examining diferent semantic relations among individual parts of each edition on record, we built a multiplex network consisting of six layers, as well as the aggregated network built from the superposition of all the layers. The network analysis reveals the emergence of fve diferent communities. The contribution of each layer in shaping the communities and the properties of each community are studied. The most infuential books in the corpus are found by calculating the average age of all the out-going and in-coming links for each book. A small group of editions is identifed as a transmitter of knowledge as they bridge past knowledge to the future through a long temporal interval. Our analysis, moreover, identifes the most impactful editions. These books introduce new knowledge that is then adopted by almost all the books published afterwards until the end of the whole period of study. The historical research on the content of the identifed books, as an empirical test, fnally corroborates the results of all our analyses.
    Scopus© Citations 15  614  109
  • Publication
    First‐Order River Delta Morphology Is Explained by the Sediment Flux Balance From Rivers, Waves, and Tides
    (2022)
    Tejedor, Alejandro 
    ;
    Broaddus, C. M
    ;
    Vulis, L. M
    ;
    Nienhuis, J. H
    ;
    Brown, J
    ;
    Foufoula‐Georgiou, E
    ;
    Edmonds, D. A
    We present a novel quantitative test of a 50-year-old hypothesis which asserts that river delta morphology is determined by the balance between river and marine influence. We define three metrics to capture the first-order morphology of deltas (shoreline roughness, number of distributary channel mouths, and presence/absence of spits), and use a recently developed sediment flux framework to quantify the river-marine influence. Through analysis of simulated and field deltas we quantitatively demonstrate the relationship between sediment flux balance and delta morphology and show that the flux balance accounts for at least 35% of the variance in the number of distributary channel mouths and 42% of the variance in the shoreline roughness for real-world and simulated deltas. We identify a tipping point in the flux balance where wave influence halts distributary channel formation and show how this explains morphological transitions in real world deltas.
      16  1Scopus© Citations 6
  • Publication
    Graph-Guided Regularized Regression of Pacific Ocean Climate Variables to Increase Predictive Skill of Southwestern U.S. Winter Precipitation
    (2021)
    Tejedor, Alejandro 
    ;
    Stevens, Abby
    ;
    Willett, Rebecca
    ;
    Mamalakis, Antonios
    ;
    Foufoula-Georgiou, Efi
    ;
    Randerson, James T.
    ;
    Smyth, Padhraic
    ;
    Wright, Stephen
    Understanding the physical drivers of seasonal hydroclimatic variability and improving predictive skill remains a challenge with important socioeconomic and environmental implications for many regions around the world. Physics-based deterministic models show limited ability to predict precipitation as the lead time increases, due to imperfect representation of physical processes and incomplete knowledge of initial conditions. Similarly, statistical methods drawing upon established climate teleconnections have low prediction skill due to the complex nature of the climate system. Recently, promising data-driven approaches have been proposed, but they often suffer from overparameterization and overfitting due to the short observational record, and they often do not account for spatiotemporal dependencies among covariates (i.e., predictors such as sea surface temperatures). This study addresses these challenges via a predictive model based on a graph-guided regularizer that simultaneously promotes similarity of predictive weights for highly correlated covariates and enforces sparsity in the covariate domain. This approach both decreases the effective dimensionality of the problem and identifies the most predictive features without specifying them a priori. We use large ensemble simulations from a climate model to construct this regularizer, reducing the structural uncertainty in the estimation. We apply the learned model to predict winter precipitation in the southwestern United States using sea surface temperatures over the entire Pacific basin, and demonstrate its superiority compared to other regularization approaches and statistical models informed by known teleconnections. Our results highlight the potential to combine optimally the space–time structure of predictor variables learned from climate models with new graph-based regularizers to improve seasonal prediction.
      7Scopus© Citations 12
  • Publication
    River Delta Morphotypes Emerge From Multiscale Characterization of Shorelines
    (2023)
    L. Vulis
    ;
    Tejedor, Alejandro 
    ;
    H. Ma
    ;
    J. H. Nienhuis
    ;
    C. M. Broaddus
    ;
    J. Brown
    ;
    D. A. Edmonds
    ;
    J. C. Rowland
    ;
    E. Foufoula‐Georgiou
    Delta shoreline structure has long been hypothesized to encode information on the relative influence of fluvial, wave, and tidal processes on delta formation and evolution. We introduce here a novel multiscale characterization of shorelines by defining three process-informed morphological metrics. We show that this characterization yields self-emerging classes of morphologically similar deltas, that is, delta morphotypes, and also predicts the dominant forcing of each morphotype. Then we show that the dominant forcings inferred from shoreline structure generally align with those estimated via relative sediment fluxes, while positing that misalignments arise from spatiotemporal heterogeneity in deltaic sediment fluxes not captured in their estimates. The proposed framework for shoreline characterization advances our quantitative understanding of how shoreline features reflect delta forcings, and may aid in deciphering paleoclimate from images of ancient deposits and projecting delta morphologic response to changes in sediment fluxes.
      5  1
  • Publication
    Robustness assessment of complex networks using the idle network
    (2022)
    Tejedor, Alejandro 
    ;
    Engsig, Marcus
    ;
    Moreno, Yamir
    Network robustness is an essential system property to sustain functionality in the face of failures or targeted attacks. Currently, only the connectivity of the nodes resilient to an attack is used to assess robustness. We propose to incorporate the properties of the emerging connectivity of the nodes that are affected by the attack (idle network), which is demonstrated to contain relevant information about network robustness, improving the accuracy of its assessment. Our work shows that the information contained in the idle network offers a potential to generalize models, enabling them to estimate robustness for unseen attacks.
      6Scopus© Citations 1  1
  • Publication
    The Entropic Braiding Index : A Robust Metric to Account for the Diversity of Channel Scales in Multi‐Thread Rivers
    (2022)
    Tejedor, Alejandro 
    ;
    Jon Schwenk
    ;
    Maarten Kleinhans
    ;
    Ajay B. Limaye
    ;
    Lawrence Vulis
    ;
    Paul Carling
    ;
    Holger Kantz
    ;
    Efi Foufoula‐Georgiou
    The Braiding Index (BI), defined as the average count of intercepted channels per cross-section, is a widely used metric for characterizing multi-thread river systems. However, it does not account for the diversity of channels (e.g., in terms of water discharge) within different cross-sections, omitting important information related to system complexity. Here we present a modification of BI, the Entropic Braiding Index (eBI), which augments the information content in BI by using Shannon Entropy to encode the diversity of channels in each cross section. eBI is interpreted as the number of “effective channels” per cross-section, allowing a direct comparison with the traditional BI. We demonstrate the potential of the ratio BI/eBI to quantify channel disparity, differentiate types of multi-thread systems (braided vs. anastomosed), and assess the effect of discharge variability, such as seasonal flooding, on river cross-section stability
    Scopus© Citations 4  41  16