Friday, February 24, 2017

Scale & Hydrology in 2020

This is the second lecture given at Potenza. The topic Salvatore Manfreda (GS) gave me is about how to move from one scale to another in Hydrological Modeling. I started from distribute modelling. My point there is that, for some tasks, distributed modelling can be scaled up to millions of square kilometers, and so,  upscaling theory is, in principle, not necessary.
But clearly this is a provocative statement I made just for pushing away some misconceptions.
Then I passed to consider other ways to upscale problems. Through simplifications, integration, heuristic thinking.  Eventually I gave a sight to "theories of all" that were so popular the last dacades and still remain possibilities and ideas to explore. By clicking on the figure you go on the presentation.

Wednesday, February 22, 2017

JGrass-NewAGE: the first Potenza lecture

This is the presentation of JGrass-NewAGE structure and achievements. A lot of posts were dedicated to it. But there is always space for new perspectives and details, since it is a work in progress where talented students of mine put all of their efforts.
JGrass-NewAGE has grown to a stable and operational set of OMS components, documented in the GEOframe blog. We also developed good practice for software design and traceability of our efforts meanwhile that could be interesting to know.
Aficionados will recognize (by clicking on the figure) that the presentation contains various topics already largely spread in other posts. However, there are a few small little things that could be interesting. Or, BTW, the arrangement given here to the matter, can clarify some choices that could have been seen obscure in other occasions (the slides are in Italian but contain link to other material and papers in English).

Monday, February 13, 2017


Times ago we had the Gruppo Italiano delle Catastrofi Idrogeologiche (GNDC, Italian Group of Hydrological and Geological Hazards). But as the site testifies it languished. When Civil Protection beaome more dominant, not maybe the knowledge, but certainly the funding went in other directions (or was it just the natural fate of all things ?), and the all the initiatives stopped. The discussion never slept, and, BTW the Italian Hydrology is much stronger now than used to be.
So it is now the time for a new scientific initiative, with renovate objectives, to fill the gap between research and practice in defending our beautiful country from flooding. This is Gruppo Alluvioni. If they're roses they'll bloom (Time will tell).

Monday, February 6, 2017

Hydrology 2017

This year I decided to introduce strong news in my Hydrology course.  Not only a change of topics, but also a change of perspective. I increased widely the hours in the lab (up to 60%) of the class, and I arranged the lectures in a way that they could be followed by a three hour laboratory. Almost no lecture will be without numerical experiments. Another innovation is the use of Python instead of R.
I made this because of the large endorsement Python had among hydrologist and because:

  •  its object oriented structure is much more firm than the R one. 
  •  Besides, Python seems to be easy to learn by engineering students. 
  • Some of my colleagues seem to agree to converge toward the use of Python in their classes
R remains the first choice to do statistics. However, we have limited time. The class is 60 hours, and the material to convey a lot.
Here it is the foreseen schedule of the class:
Corso di Idrologia 2017

Legend: T - Theoretical lecture  - L - Laboratory class (this can include theoretical parts, but mostly students will exercise with tools)
  1. T - Introduction to the class
  2. T - A terrain analysis  primer. 
  3. L - Introduction to QGIS. Introduction to the JGrasstools in OMS.
  4. T - A little of Statistics and Probability. 
  5. L -  Delineation of catchments' characteristics with JGrasstools and QGIS.
  6. T - Precipitations. Mechanisms  of formation of precipitation. Ground based statistics. Extreme precipitations. 
  7. L - Intro to Python - Loading/reading files. Time series and their visualisation.
  8. T - Extreme precipitation statistics (parameters' estimation)
  9. L - Estimation of extreme distributions parameters. 
  10. T -  Radiation
  11. L - Estimation of shortwave and longwave radiation in a catchment. 
  12. T - Spatial interpolation - Some concepts about the spatial representation of hydrological quantities. Inverse distance weighting. Ordinary Kriging. Detrended Kriging. 
  13. L - Practical spatial interpolation of rainfall and temperature.  
  14. T - Water in soils. - Darcy-Buckhingham law- Soil water retention curves and hydraulic conductivity. 
  15. L - Numerical experiments on soil water retention curves and hydraulic conductivity.
  16. T -  Richards equation and its extensions.
  17. L - Simulation of infiltration with the Richards equation (1d)
  18. T - Water movements in a hillslope and runoff generation. 
  19. L - Runoff estimation at hillslope scale.
  20. T - Elements of theory of evaporation from water and soils - Dalton. Penman-Monteith. Priestley-Taylor
  21. L - Estimation of potential evapotranspiration with Penman-Monteith and Prietley-Taylor.
  22. T - Vegetation role in the hydrological cycle and transpiration.
  23. L - Estimation of transpiration at catchment scale.
  24. T -  Snow. Snow water and energy budgets. 
  25. L - Degree-Day/Regina Hock's models of snow budget
  26. T - On the impact of climate change on the hydrological cycle

Saturday, February 4, 2017

Water supply systems and Stormwater management infrastructures 2017

Work in progress !!! Starts 02/27

This year I decide to renovate the teaching of my class of "Hydraulic Constructions".  Usually, under this name, one thinks to dams, levees, or other infrastructures. In fact, what I will  teach is how to design a water supply system for a city or for a city district, and how to design the infrastructures for storm water management.

This the foreseen schedule of the course. L Means a laboratory class, where the students are asked to calculate, think or project something. Actually it will be that I will do stuff for them, introducing some tools and asking them to repeat and complete the task on their dataset. Tentatively, it will be a "learning by doing approach" which I used also the last years but to a minor extent. 

I have 60 hours in total over thirteen weeks. So the schedule could be the following one

Storm waters
  1. T - Introductory Class
  2. T - Statistical properties of ground precipitations. Mechanisms  of formation of precipitation. Ground based statistics. Extreme precipitations.  
  3. L - Explorative data analysis. Investigating data with Python (or R)
  4. T - Extreme precipitations. Around the concept of return period. Extreme distributions. 
  5. L - Estimation of Extreme distributions with Python (or R)
  6. T - Element for the design of storm water management infrastructures.  Two urban cases. 
  7. L - Short introduction to GIS for representing urban infrastructures. 
  8. T - Urban flood wave: a primer. 
  9. L - Introduction to EPA SWMM
  10. T - Designing a sewer system with a small synthesis of  pipes hydraulics. 
  11. L - Designing some part of a sewer network with SWMM and Python. 
  12. T - Pumping stormwaters.
  13. L - Discussion and analysis of students projects 

Clean water supply - Aqueducts
  1. T - Aqueducts in 2020
  2. L - Introduction to EPANET and related GIS
  3. T - Introduction to intakes  for water supply
  4. L - Some hydraulic infrastructure for aqueducts
  5. T - External aqueducts
  6. L - Water buildings.  EPANET
  7. T - Aqueducts' distribution networks - Theory and numerics
  8. L - Design and verification of distribution networks with EPANET - I 
  9. T - Houses' infrastructures
  10. L - Design and verification of distribution networks with EPANET - II


During the class I will introduce sever tools for calculations. 
  • Python - Python is a modern programming languages. It will be used for data treatment, estimation of the idf curves of precipitation, some hydraulic calculation and data visualisation. I will use Python mostly as a scripting language to bind and using existing tools. 
  • SWMM - Is an acronym for Storm Water Management System. Essentially it is a model for the estimation of runoff adjusted to Urban environment. I do not endorse very much its hydrology. However, it is the most used tools by colleagues who cares about storm water management, and I adopt it. It is not a tool for designing storm water networks, and therefore, some more work should be done with Python to fill the gaps.
  • EPANET Is the tool developed by EPA to estimate water distribution networks. 

Friday, February 3, 2017

A few steps into Git, Gradle and Travis use

To improve the way we interact and maintain our codes, we started to use more and more some of the many tools that the programmers' market offers.
So, Marialaura Bancheri provided us a small lecture with exercises in order all the group  of students (and I) are up-to-date.  I hope, this will be useful also for others.  To access them, you can click on the Figure above. The tools (in Github)  integrate well also with Zenodo that can provide a DOI to any tagged software release. 
Previous material on GIT (using Egit) can be found here
Life is better using these tools. 

Thursday, February 2, 2017

Some suggestions for writing a good resume (or a CV)

I was asked to teach something to our students about how writing a CV (or, better, a resumè).  So I prepared this talk you find below, on clicking on the figure. It is in Italian, but my sources are mostly in English, so, below, please find them, which cover almost all I said.

The big source is
However, I found fun to read also 
and intersting:
They give you the right guidance to understand and interpret what you find around in Internet. To the contents of those writings, I added a comment of Leonardo da Vinci's resumè which I commented a couple of days ago.
For Academic resumè and CVs, I also added some examples, including mine:
So, I believe you have enough material to start with.