We study tree structures termed optimal channel networks (OCNs) that minimize the total gravitational energy loss in the system, an exact property of steady-state landscape configurations that prove dynamically accessible and strikingly similar to natural forms. Here, we show that every OCN is a so-called natural river tree, in the sense that there exists a height function such that the flow directions are always directed along steepest descent. We also study the natural river trees in an arbitrary graph in terms of forbidden substructures, which we call k-path obstacles, and OCNs on a d-dimensional lattice, improving earlier results by determining the minimum energy up to a constant factor for every d >= 2. Results extend our capabilities in environmental statistical mechanics.

River landscapes and optimal channel networks

Bertuzzo, Enrico
Membro del Collaboration Group
;
CALDARELLI, GUIDO
Membro del Collaboration Group
;
Maritan, Amos
Membro del Collaboration Group
;
Rinaldo, Andrea
Membro del Collaboration Group
2018

Abstract

We study tree structures termed optimal channel networks (OCNs) that minimize the total gravitational energy loss in the system, an exact property of steady-state landscape configurations that prove dynamically accessible and strikingly similar to natural forms. Here, we show that every OCN is a so-called natural river tree, in the sense that there exists a height function such that the flow directions are always directed along steepest descent. We also study the natural river trees in an arbitrary graph in terms of forbidden substructures, which we call k-path obstacles, and OCNs on a d-dimensional lattice, improving earlier results by determining the minimum energy up to a constant factor for every d >= 2. Results extend our capabilities in environmental statistical mechanics.
File in questo prodotto:
Non ci sono file associati a questo prodotto.
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3280174
Citazioni
  • ???jsp.display-item.citation.pmc??? 7
  • Scopus 22
  • ???jsp.display-item.citation.isi??? 21
  • OpenAlex ND
social impact