A minimalist model for coevolving supply and drainage networks

Numerous complex systems, both natural and artificial, are characterized by the presence of intertwined supply and/or drainage networks. Here, we present a minimalist model of such coevolving networks in a spatially continuous domain, where the obtained networks can be interpreted as a part of either the counter-flowing drainage or co-flowing supply and drainage mechanisms. The model consists of three coupled, nonlinear partial differential equations that describe spatial density patterns of input and output materials by modifying a mediating scalar field, on which supply and drainage networks are carved. In the two-dimensional case, the scalar field can be viewed as the elevation of a hypothetical landscape, of which supply and drainage networks are ridges and valleys, respectively. In the three-dimensional case, the scalar field serves the role of a chemical signal, according to which vascularization of the supply and drainage networks occurs above a critical ‘erosion’ strength. The steady-state solutions are presented as a function of non-dimensional channelization indices for both materials. The spatial patterns of the emerging networks are classified within the branched and congested extreme regimes, within which the resulting networks are characterized based on the absolute as well as the relative values of two non-dimensional indices.

[1]  Dennis G. Zill,et al.  Advanced Engineering Mathematics , 2021, Technometrics.

[2]  A. Porporato,et al.  Channelization cascade in landscape evolution , 2020, Proceedings of the National Academy of Sciences.

[3]  A. Porporato,et al.  Variational analysis of landscape elevation and drainage networks , 2019, Proceedings of the Royal Society A.

[4]  Milad Hooshyar,et al.  Linear layout of multiple flow-direction networks for landscape-evolution simulations , 2019, Environ. Model. Softw..

[5]  A. Maritan,et al.  Optimal transport from a point-like source , 2020, Continuum Mechanics and Thermodynamics.

[6]  Richard Barnes,et al.  Accelerating a fluvial incision and landscape evolution model with parallelism , 2018, Geomorphology.

[7]  R. Huddleston Structure , 2018, Jane Austen's Style.

[8]  A. Porporato,et al.  On the theory of drainage area for regular and non-regular points , 2018, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[9]  Enrico Facca,et al.  Towards a Stationary Monge-Kantorovich Dynamics: The Physarum Polycephalum Experience , 2016, SIAM J. Appl. Math..

[10]  Dingbao Wang,et al.  Hydrologic controls on junction angle of river networks , 2017 .

[11]  Henrik Ronellenfitsch,et al.  Global Optimization, Local Adaptation, and the Role of Growth in Distribution Networks. , 2016, Physical review letters.

[12]  Matthias Schlottbom,et al.  Notes on a PDE System for Biological Network Formation , 2015, 1510.03630.

[13]  Isaac Siwale ON GLOBAL OPTIMIZATION , 2015 .

[14]  G. Buttazzo,et al.  On the equations of landscape formation , 2014 .

[15]  Jean Braun,et al.  A very efficient O(n), implicit and parallel method to solve the stream power equation governing fluvial incision and landscape evolution , 2013 .

[16]  J. Perron,et al.  The root of branching river networks , 2012, Nature.

[17]  Michael F. Hutchinson,et al.  A differential equation for specific catchment area , 2011 .

[18]  A. Rinaldo,et al.  Structure and controls of the global virtual water trade network , 2011, 1207.2306.

[19]  K. Painter,et al.  A User's Guide to Pde Models for Chemotaxis , 2022 .

[20]  J. Pelletier Fractal behavior in space and time in a simplified model of fluvial landform evolution , 2007 .

[21]  Tullio Tucciarelli,et al.  MAST solution of advection problems in irrotational flow fields , 2007 .

[22]  Alexander Martin,et al.  A simulated annealing algorithm for transient optimization in gas networks , 2007, Math. Methods Oper. Res..

[23]  Chenghu Zhou,et al.  An adaptive approach to selecting a flow‐partition exponent for a multiple‐flow‐direction algorithm , 2007, Int. J. Geogr. Inf. Sci..

[24]  Marcelo O Magnasco,et al.  Structure, scaling, and phase transition in the optimal transport network. , 2006, Physical review letters.

[25]  Paul H. J. Kelly,et al.  A dynamic topological sort algorithm for directed acyclic graphs , 2007, ACM J. Exp. Algorithmics.

[26]  C. Schmeiser,et al.  Global existence for chemotaxis with finite sampling radius , 2006 .

[27]  Yong Yu,et al.  Optimal routing on complex networks , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.

[28]  M. Alber,et al.  Multiscale dynamics of biological cells with chemotactic interactions: from a discrete stochastic model to a continuous description. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.

[29]  M. Durand Architecture of optimal transport networks. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[30]  R. Bras,et al.  Vegetation-modulated landscape evolution: Effects of vegetation on landscape processes, drainage density, and topography , 2004 .

[31]  M. Chaplain,et al.  Mathematical Modelling of Angiogenesis , 2000, Journal of Neuro-Oncology.

[32]  D. Manoussaki A mechanochemical model of angiogenesis and vasculogenesis , 2003 .

[33]  S. N. Dorogovtsev,et al.  Evolution of networks , 2001, cond-mat/0106144.

[34]  Björn Birnir,et al.  The scaling of fluvial landscapes , 2001 .

[35]  Pablo G. Debenedetti,et al.  Supercooled liquids and the glass transition , 2001, Nature.

[36]  Tom J. Coulthard,et al.  Landscape evolution models: a software review , 2001 .

[37]  J R Banavar,et al.  Topology of the fittest transportation network. , 2000, Physical review letters.

[38]  Sue Abdinnour-Helm Network design in supply chain management , 1999 .

[39]  Amos Maritan,et al.  Size and form in efficient transportation networks , 1999, Nature.

[40]  J. Koenderink,et al.  The Structure of Relief , 1998 .

[41]  J. Krug Origins of scale invariance in growth processes , 1997 .

[42]  Qian-Ping Gu,et al.  Efficient parallel and distributed topological sort algorithms , 1997, Proceedings of IEEE International Symposium on Parallel Algorithms Architecture Synthesis.

[43]  Kan Chen Simple learning algorithm for the traveling salesman problem , 1996, adap-org/9608003.

[44]  L. Evans Partial Differential Equations and Monge-Kantorovich Mass Transfer , 1997 .

[45]  A. Rinaldo,et al.  Fractal River Basins: Chance and Self-Organization , 1997 .

[46]  J. Murray,et al.  A mechanical model for the formation of vascular networks in vitro , 1996, Acta biotheoretica.

[47]  A. Simpson,et al.  An Improved Genetic Algorithm for Pipe Network Optimization , 1996 .

[48]  G. Vojta,et al.  Fractal Concepts in Surface Growth , 1996 .

[49]  Meakin,et al.  Minimum energy dissipation river networks with fractal boundaries. , 1995, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[50]  Warrick Dawes,et al.  The significance of topology for modeling the surface hydrology of fluvial landscapes , 1994 .

[51]  M. Cross,et al.  Pattern formation outside of equilibrium , 1993 .

[52]  Jan J. Koenderink,et al.  Local features of smooth shapes: ridges and courses , 1993, Optics & Photonics.

[53]  I. Rodríguez‐Iturbe,et al.  Self-organized fractal river networks. , 1993, Physical review letters.

[54]  Several Duality Theorems for Interlocking Ridge and Channel Networks , 1991 .

[55]  Michel Minoux,et al.  Networks synthesis and optimum network design problems: Models, solution methods and applications , 1989, Networks.

[56]  Aimo A. Törn,et al.  Global Optimization , 1999, Science.

[57]  Zhang,et al.  Dynamic scaling of growing interfaces. , 1986, Physical review letters.

[58]  S. Rachev The Monge–Kantorovich Mass Transference Problem and Its Stochastic Applications , 1985 .

[59]  R. L. Russell,et al.  Normal and mutant thermotaxis in the nematode Caenorhabditis elegans. , 1975, Proceedings of the National Academy of Sciences of the United States of America.

[60]  L. Segel,et al.  Initiation of slime mold aggregation viewed as an instability. , 1970, Journal of theoretical biology.

[61]  C. D. Murray THE PHYSIOLOGICAL PRINCIPLE OF MINIMUM WORK , 1931, The Journal of general physiology.

[62]  C D Murray,et al.  The Physiological Principle of Minimum Work: I. The Vascular System and the Cost of Blood Volume. , 1926, Proceedings of the National Academy of Sciences of the United States of America.