A novel probabilistic model to explain drainage network evolution

Borse, Dnyanesh; Biswal, Basudev

doi:10.1016/j.advwatres.2022.104342

Cited by 5 publications

(4 citation statements)

References 46 publications

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“…The model follows preferential headward growth of channels from boundary or outlets, where the preferences is probabilistically determined based on the downstream length of the evolving streams. Refer to (Borse & Biswal, 2023) for detailed information about the model.…”

Section: Results: Basin Area Distribution Analysis Across Islandsmentioning

confidence: 99%

“…These patterns suggest that river networks are unique type of tree networks that might be arising due to certain similar geomorphic processes leading to such configuration. These scaling laws are also used by the river network simulation models to compare the modelled networks with real networks by comparing the exponents (Borse & Biswal, 2023;Hooshyar et al, 2020;Paik & Kumar, 2008;Rodríguez-Iturbe et al, 1992). The quantitative understanding of such networks helps us to understand the underlined principles hidden in the pattern formation.…”

Section: Introductionmentioning

confidence: 99%

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Power Law Distribution of Independent Basin Areas in Fluvial Landscapes

Borse,

Biswal

2024

Preprint

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River networks around the world exhibit statistical scaling laws, including the distribution of independent basin sizes in landscapes. The widespread occurrence of these patterns in various landscapes suggests that there are fundamental, but not yet fully understood, processes responsible for these power law distributions. This study investigates the distribution of independent basin areas across 25 islands worldwide, revealing a clear adherence to a power law pattern. The research suggests that the power law exponent is influenced by landscape boundary characteristics, such as the compactness coefficient and fractal dimension, with the exponent value increasing with these factors. Furthermore, the study demonstrates the development of power law patterns in basin areas using a probabilistic network growth model. This model, based on a preferential headward growth mechanism, underscores the significant roles of boundary conditions and headward growth dynamics in the self-organization of power law patterns in fluvial landscapes.

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Section: Results: Basin Area Distribution Analysis Across Islandsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Power Law Distribution of Independent Basin Areas in Fluvial Landscapes

Borse,

Biswal

2024

Preprint

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“…Therefore, the rapid generation of artificial networks is of considerable interest. Ghosh et al (2006) present an application for generating artificial sewer networks using the dendritic and space filling ‘Tokunaga’ fractal tree geometry, Bonnet (2009) proposes a model to simulate channel network genesis and landscape erosion, and Borse and Biswal (2023) a model to explain river network evolution.…”

Section: Discussionmentioning

confidence: 99%

Morphometric properties, scaling laws and hydrologic response of the Greater Paris combined sewer system

Achour,

Chahinian,

Chancibault

et al. 2023

Hydrological Processes

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Morphometric properties of channel networks are useful tools to classify catchments and calculate their hydrological response. Scaling laws have been established for Optimal Channel Networks (OCNs), which are defined based on a generative geomorphological mechanism of minimizing the total energy dissipation. However, sewer networks obey engineering efficiency rules and are conceived based on local optimizations, both in time and space, for minimal costs. Not all the scaling laws have been verified for artificial sewer networks found in urban areas. This raises questions regarding the applicability of OCN scaling laws to sewer networks and their potential impact on the shape of the Geomorphological Instantaneous Unit Hydrograph (GIUH). Hence, this work aims to study the morphometric properties of the Greater Paris combined sewer system through a case study on twelve nested subcatchments. A two‐step methodology is used. First, the morphometric properties are analysed using the reference Horton‐Strahler, Rodríguez‐Iturbe and Moussa‐Bocquillon scaling laws. The results show that Horton‐Strahler's laws of bifurcation are verified while the length and area laws are not always verified. Rodriguez‐Iturbe and Moussa‐Bocquillon laws are verified with slightly different values of the descriptors in comparison to OCNs. Second, these morphometric properties are used to calculate four GIUHs: the reference Width Function (GWF), the Nash unit hydrograph (GN) using Horton‐Strahler ratios, the Nash Unit Hydrograph equivalent (GNe) using Moussa‐Bocquillon descriptors, and the Hayami function (GH) solution of the diffusive wave equation. We identified four catchments for which the scaling laws are verified and therefore all GIUHs are similar while for four other catchments the scaling laws are not verified and strongly impact the GIUHs. These morphometric descriptors and the GIUHs can be considered as ‘hydrological signatures’ of Combined Sewer Systems (CSSs) and are useful for the comparison and classification of hydrological responses.

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“…The network shown in Fig. 2a was generated using a probabilistic model proposed by Borse and Biswal 14 . This model, implemented on a 250×250 grid, simulates the probabilistic headward growth of channel networks which is assumed to be proportional to the pixel's length to the outlet.…”

Section: Methodsmentioning

confidence: 99%

Emergence of efficient channel networks in fluvial landscapes

Borse,

Biswal

2023

Preprint

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Channel networks across fluvial landscapes are believed to have evolved to minimize energy expenditure[1–3], as evidenced by the similarities between computer-generated optimal channel networks (OCNs) and real networks[4,5]. However, the specific mechanisms driving energy minimization in fluvial landscapes remain largely elusive[6]. Here we propose that randomness has a profound role in landscape evolution[7] and that efficient channel networks emerge when the probability of a channel pixel changing its flow direction decreases with drainage area. The proposed probabilistic growth model then employs a power function to simulate channel-network evolution, with positive exponent (𝜂) values leading to asymptotic decrease of energy expenditure. An interpretation of this result is energy minimization tendency of river networks is a result of landscape evolution following specific adaptive rules rather than being the cause of landscape evolution itself. A greater 𝜂 ensures a greater restriction on the role of randomness and thus results in a more stable channel network configuration, and vice versa. Interestingly, the most efficient networks are observed to emerge always at 𝜂 =0.5, suggesting that randomness plays an important but limited role in the emergence of efficient channel networks. The proposed framework holds promise for explaining the evolution of other tree-like networks in nature and for developing more efficient optimization methods for practical applications.

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A novel probabilistic model to explain drainage network evolution

Cited by 5 publications

References 46 publications

Power Law Distribution of Independent Basin Areas in Fluvial Landscapes

Power Law Distribution of Independent Basin Areas in Fluvial Landscapes

Morphometric properties, scaling laws and hydrologic response of the Greater Paris combined sewer system

Emergence of efficient channel networks in fluvial landscapes

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