Hello
I'm currently trying to create a chi-map using topotoolbox for matlab. In the available literature most of the calculations use a single mn ratio (0.45-0.5) for the entire area, and some others do a sensitivity analysis in order to get the best mn ratio per watershed. However, I don't know whether the calculations would improve using the best mn ratio per stream or it really doesn't matter because the sensitivity analysis is good enough in a calculation per watershed.
By the way, I'm working in an landscape highly controlled by faults activity.
Any comments will be appreciated.
Best Regards
Lester
Hola Lester Olivares
maybe this entry in the topotoolbox blog can be useful to you https://topotoolbox.wordpress.com/2017/10/24/bayesian-optimization-of-the-mn-ratio/
they explain the way the code optimizes the mn ratio by comparing subsets of streams along a catchment
Hi Luis Alberto Astudillo Sotomayor
Sure, I did see the link and if this is correct then we should assume that the watershed calculation of mn ratio is the best way to approach this problem. However, sometimes you can get a huge range of different values for the same watershed.
So I think that my question is what is the standard deviation value acceptable for a bayesian optimization? and what happens when your standard deviation is larger than that particular threshold? what method shall I use then?
By the way, thank you for your feedbacks
Apparently, the best way is to do the Bayesian optimization, but there are some other issues to keep in mind, such as base level differences between watersheds, lithology and differential uplift. I strongly recommend the use of the TAK toolbox prepared by Adam Forte and Kelin Whipple. And their papers. Links below:
https://asu.pure.elsevier.com/en/publications/criteria-and-tools-for-determining-drainage-divide-stability
https://www.researchgate.net/publication/330550461_Short_communication_The_Topographic_Analysis_Kit_TAK_for_TopoToolbox
- Badges
- Science topic