This post collects the Notebook used in my classes of Hydraulic Constructions and Hydrology for estimating the IDF curves. It is actually a work in progress.

For who wants to start with Python (for hydrologists), I suggest to give a look to my blog post "Python for Hydrologists". Here a brief summary, for the laziest.

- Python in Hydrology
- Python programming guide for Earth Scientists
- A hands-on introduction to using Python in the Atmospheric and Oceanic sciences

Soil Physics with Python: Transport in the Soil-Plant-Atmosphere System, by Bittelli et al, is al, is a book on soil science which is quite appealing (as seen the TOC): the kindle version cost reasonably but I do not have it. Python programs are available here.

An overview of Scientific libraries and softwares of general use in Python is given at scipy.org, from which I extract these links to documentation:

- Python Scientific Lecture Notes a comprehensive set of tutorials on the scientific Python ecosystem.
- Lectures on scientific computing with Python by J.R. Johansson.
- Introduction to Statistics an introduction to the basic statistical concepts, combined with a complete set of application examples for the statistical data analysis with Python (by T. Haslwanter). Another here, by Kevin Sheppard.
- Jupyter notebooks are a splendid way to organise calculations. They are used below for documenting the my calculations.

3 - Estimating the parameters of a Gumbel distribution with

4 - Pearson's Test

5 - Fitting the curves (some error here)

7 - Reading and plotting a Raster ASCII File (and its statistics)

Paperopoli 2

Paperopoli 4

For who wants to do the same numerics with R, she should look "A few R scripts useful for hydrologists".

Being new to the blogging world I feel like there is still so much to learn. Your tips helped to clarify a few things for me as well as giving..

ReplyDeletePHP training in chennai

The article provided by you is very nice and it is very helpful to know the more information.keep update with your blogs .I found a article related to you..once you can check it out.

ReplyDeletepython online training