Hack's law in a drainage network model: A Brownian web approach

TL;DR

This paper demonstrates that Hack's law exponent in a drainage network model is 2/3 by using a Brownian web approach, linking the tributary structure to stochastic process limits.

Contribution

It establishes a rigorous connection between a drainage network model and Brownian web theory, deriving Hack's law exponent analytically.

Findings

Hack's law exponent is 2/3 in the model

The watershed area converges to a Brownian excursion process

Both the network and its dual converge to the Brownian web

Abstract

Hack [Studies of longitudinal stream profiles in Virginia and Maryland (1957). Report], while studying the drainage system in the Shenandoah valley and the adjacent mountains of Virginia, observed a power law relation $l\sim a^{0.6}$ between the length $l$ of a stream from its source to a divide and the area $a$ of the basin that collects the precipitation contributing to the stream as tributaries. We study the tributary structure of Howard's drainage network model of headward growth and branching studied by Gangopadhyay, Roy and Sarkar [Ann. Appl. Probab. 14 (2004) 1242-1266]. We show that the exponent of Hack's law is $2/3$ for Howard's model. Our study is based on a scaling of the process whereby the limit of the watershed area of a stream is area of a Brownian excursion process. To obtain this, we define a dual of the model and show that under diffusive scaling, both the original network and its dual converge jointly to the standard Brownian web and its dual.