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.

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).

GRAL

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).

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. 
• Water on Earth (optional). 
• The hydrological cycle (YouTube)
• The hydrosphere parts (optional). 
• Modern hydrological information (YouTube). 
• The water budget (YouTube). 
• The energy budget (YouTube) 
• Fluxes, Reservoirs, Residence times (optional) 
• The Budyko scheme. 
• Further Readings
2. T - A terrain analysis  primer. 
• Elevation, Slopes, Curvatures. (YouTube)
• River network delineation. 
• Contributing areas. 
• Geomorphic laws (optional)
• Further Readings
3. L - Introduction to QGIS. Introduction to the JGrasstools in OMS.
4. T - A little of Statistics and Probability. 
• Descriptive Statistics
• Location indicators  (YouTube)
• Form and Shapes of data
• Tests of hypothesis
• Stationarity And Ergodicity
• Further readings on Statistics (see also here)
• Probability's Axioms (optional)
• Univariate distributions
• Further readings on Probability
5. L -  Delineation of catchments' characteristics with JGrasstools and QGIS.
6. T - Precipitations. Mechanisms  of formation of precipitation. Ground based statistics. Extreme precipitations. 
• See the points 6 to 11 in this post.
• Further readings (Point 1-5 and 17 in the Precipitations' post)
7. L - Intro to Python - Loading/reading files. Time series and their visualisation. (See Notebook 0 an 1 here.)
8. T - Extreme precipitation statistics (parameters' estimation)
• See points 12-15 in the Precipitations post
• Further readings (Point 1-5 and 17 in the Precipitations' post)
9. L - Estimation of extreme distributions parameters. (See Notebook 2 to 5 here.)
10. T -  Radiation (YouTube 2017). 
• The Sun (YouTube 2017)
• Stefan-Boltzmann law and radiation spectrum (YouTube 2017)
• Sun  to Earth (YouTube 2017)
• Coping with latitude and longitude (YouTube 2017)
• Atmospheric Absorptions (YouTube 2017)
• Clouds (YouTube 2017)
• Coping with terrain (YouTube 2017)
• Long wave radiation (YouTube 2017)
• Table of symbols
• Further readings:
• Corripio, J. G. (2002). Modelling the energy balance of high altitude glacierised basins in the Central Andes. Ph.D Dissertation, 1–175.
• Corripio, J. G. (2003). Vectorial algebra algorithms for calculating terrain parameters from DEMs and solar radiation modelling in mountainous terrain. Int. J. Geographical Information Science, 17(1), 1–23. 
• Formetta, G., Rigon, R., Chávez, J. L., & David O. (2013). Modeling shortwave solar radiation using the JGrass-NewAge system. Geoscientific Model Development, 6(4), 915–928. http://doi.org/10.5194/gmd-6-915-2013 
• Formetta, G., Bancheri, M., David, O., & Rigon, R. (2016). Performance of site-specific parameterizations of longwave radiation. Hydrology and Earth System Sciences, 20(11), 4641–4654. http://doi.org/10.5194/hess-20-4641-2016
11. L - Estimation of shortwave and longwave radiation in a catchment (data, executables, sim files are available through Zenodo. Who is interested in the source code and further information, plese refers to GEOframe or the Github GEOframe components site). 
• A brief rehearsal of the matter given by Michele Bottazzi (M.B.) (YouTube)
• Estimation of solar radiation with JGrass-NewAGE components (YouTube) by M.B. Part I
• Estimation of solar radiation with JGrass-NewAGE components by M.B. (YouTube) Part II
12. T - Spatial interpolation of environmental data
• Some concepts about the spatial representation of environmental quantities (YouTube 2017)
• Simple Kriging (YouTube 2017) (This is more or less covered in Raspa work from page 75)
• More on variance and covariance (YouTube 2017)
• Further readings
• Dispense Geostatistica G. Raspa. 
• A. Bellin slides
13. L - Practical spatial interpolation of rainfall and temperature.  
• Data, sim files, etc 
• Video lectures by Marialaura Bancheri (Parte I, II e III)
14. T - Water in soils. - Darcy-Buckhingham law- Soil water retention curves and hydraulic conductivity. 
• Soils (YouTube 2017)
• Texture and Structure of soils (YouTube 2017)
• Aquifers (optional)
• Definitions (YouTube 2017)
• Darcy-Buckingham law (YouTube 2017)
• Soil Water RetentionCurves (YouTube 2017)
• Hydraulic Conductivity
• Conductivity in unsaturated soils
• Saturated conductivity
• Further readings
• Soil depth
• Soil Water Retention Curves
• The old post on soils
• Preferential flow in hillslopes
• Ning Lu's lectures on soil water
15. L - Numerical experiments on soil water retention curves and hydraulic conductivity.
• Soil Water Retention curves (data)
• Saturated Hydraulic Conductivity (data)
16. T -  Richards equation and its extensions.
• Mass conservation - Richards equation (YouTube2017)
• Pedotransfer Functions (Used during the lab 15) - (YouTube2017)
• Simplifications of Richards 1D in a hillslope (YouTube2017)
• Phenomenology of infiltration (according to Richards equation) in a hillslope (YouTube2017)
• Macropores (Optional)
• Water Tables equations (Optional)
• Water in soils measures
• Notation Summary
• Further Readings (or view)
• Older presentation, slides and Audios
• Video talk given at a Summer School
• A lecture on this topic at Todini's Symposium (a little advanced)
• Preferential flows
• Bimodal Water retention Curves
• An R package for getting soil hydrology
• About the Petri Net representation of Richards 1d
17. L - Experiments with a Richards 1D simulator
• Readme First
• Data
• Notebooks: Input; Outputs
• Explanation of the sim file (YouTube by Niccolò Tubini: Part Ihttps://www.youtube.com/watch?v=e3vGgHQXvTM and II)
• Executable, Source Code and Data
• Another Richards 1D solver
18. T - Elements of theory of evaporation from water and soils - Dalton. Penman-Monteith. Priestley-Taylor
• The Thermodynamical origin of evaporation (YouTube2017)
• Vapor transport by turbulence (YouTube2017)
• Evaporation from free water surfaces (YouTube2017)
• Evaporation from soils (YouTube2017)
• Penman-Monteith (YouTube2017)
• Further Readings
• About Drying Porous media
19. T - Estimation of evaporation and Transpiration at hillslope scale
• Transpiration (YouTube2017)
• Estimation of ET over large areas (YouTube2017)
• Evaporation and Transpiration from the energy budget (YouTube2017)
20. L -  Estimation of evaporation and transpiration at catchment scale
21. T - Water movements in a hillslope and runoff generation
• See the posts on runoff generation
• Hymod as an example of the "reservoirs" models (YouTube2017)
22. T - On the impact of climate change on the hydrological cycle (YouTube2017)

Verifications and tests 2017

Questions of the 2017 intermediate test.
Grades of the intermediate test.

Water supply systems and Stormwater management infrastructures 2017

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. 
• New goals for Urban hydrology
• The sewage systems devices
• Local control on the hydrological cycle
• The law of public works
• The past and the future
• Further readings
2. T - Statistical properties of ground precipitations. Mechanisms  of formation of precipitation. Ground based statistics. Extreme precipitations.  
• See the points 6-11 in the Precipitations post
• Further readings (Point 1-5 and 17 in the Precipitations' post)
3. L - Explorative data analysis. Investigating data with Python (or R).  
4. T - Extreme precipitations. Around the concept of return period. Extreme distributions. 
• See points 12-15 in the Precipitations post
• Further readings (Point 1-5 and 17 in the Precipitations' post)
5. L - Estimation of Extreme distributions with Python (or R)
6. T - Element for the design of storm water management infrastructures.  
• The storm water drainage network (SWDN)
• Urban cases
• Pipes (slides from Roberto Magini)
• The estimation of the flood wave (the IUH case) and the Hydraulic design of the SWDN
7. L - Short introduction to QGIS for representing urban infrastructures. 
• Introduction to QGIS by Elisa Stella and Daniele Dalla Torre. For other information about tools installation, see the bottom of the page.
• Using QGIS and GISWater to feed SWMM
• Material/Data of the lab
• Video classes on QGIS/GISWATER (discovered by Pasini & Rocari)
• Create subcatchments
• Homogenize the subcatchment layer and insert it in the database
• Geometric information subcatchments
• Average Slope
• Impervious
• Simp, Routeto
• https://www.youtube.com/watch?v=HJIGH-ndcJ4

1. T - Element for the design of storm water management infrastructures. - II 
• An example with a linear reservoir system 
• The so called "metodo italiano" (optional)
• Further readings
2. L - Simple estimations of the maximum discharge via Python
3. T - Pumping stormwaters.
4. L - Designing some part of a sewer network with SWMM and Python. 
• The Python Notebook is here
• The Data used in the notebook here
• Using QGIS and GISWater for creating the inputs for SWMM (YouTube  by Elisa Stella: Part I, II and III)

Clean water supply - Aqueducts

As a  general, simple and descriptive reference, the first six chapters of Maurizio Leopardi's book can be useful :

• Utilizzo Idropotabile
• Il trasporto in pressione
• Dimensionamento idraulico delle condotte
• Acquedotto con sollevamento meccanico
• Serbatoi
• Reti di distribuzione

Here the class lectures:

1. T - Aqueducts in 2020
• Equations for aqueducts networks
• Mass and energy Conservation
2. L - Introduction to EPANET (and related GIS)(YouTube2017)
3. T - Aqueducts' distribution networks: the water demand and some design indications)
• Equations for aqueducts network
4. T - External aqueducts
5. T - Introduction to intakes  for water supply
6. T - Water uptakes
7. L - Reservoirs
8. L - Design and verification of distribution networks with EPANET - 
9. T - Houses' infrastructures
10. T - Urban Drainage Systems
11. L - Design and verification of distribution networks with EPANET - I I (YouTube on Water Demand)

Tools

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. 
• LaTeX: il sistema per la scrittura e la composizione di testi matematici ed ingegneristici. Il testo di Lorenzo Pantieri e Tommaso Gordini è un piccolo gioiello. 

Installation Instructions (for Windows) by Daniele Della Torre:

SWMM: http://growworkinghard.altervista.org/epa-swmm-how-to-install-step-by-step/

GISWATER: http://growworkinghard.altervista.org/giswater-11-install-windows/

QGIS: http://growworkinghard.altervista.org/qgis-2-18-how-to-install-step-by-step-on-windows/

and this for the Java RE:

http://growworkinghard.altervista.org/install-jre-step-by-step-on-windows-march-2017/

Domande della prova intermedia 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.

• Git is the version control system that we use for maintaining track of our source code (see here why to use a version control system). Our codes, as some could know are on Github, which uses Git.
• Gradle is the builder we chose for building our system (for who knows make, it is a more modern version of it. Why using a building system).
• Travis CI is a system of continuous integration which allows for compiling our code while committing it to the Github server. It makes us having a working fresh code that merges all the latest changes ready-made. 

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. 

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

• Peter Fiske, How to write a winning resumè

However, I found fun to read also 

• A. Ruben, Regrettable resumè,  Part 1,  Part 2

and intersting:

• D. Jensen, Resumè wisdom

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:

1. http://www.vitae.ac.uk/researchers/1373/Academic%20CVs.html
2. http://blogs.nature.com/naturejobs/2011/09/27/38-tips-on-writing-an-academic-cv
3. http://www.guardian.co.uk/higher-education-network/2011/dec/06/how-towrite-academic-cv
4. http://blogs.nature.com/naturejobs/2011/09/27/38-tips-on-writing-an-academic-cv
5. http://www.careers.utoronto.ca/myCareer/resumeInterview/cv.aspx
6. http://www.guardian.co.uk/higher-education-network/2011/dec/06/how-towrite-academic-cv
7. http://www.vitae.ac.uk/researchers/1373/Academic%20CVs.html
8. http://www.guardian.co.uk/higher-education-network/2011/dec/06/how-towrite-academic-cv
9. http://www.virginia.edu/vpr/postdoc/docs/CVCoverLetters.pdf
10. http://abouthydrology.blogspot.it/2014/09/my-cv.html

Finally a visual guide (in Italian). So, I believe you have enough material to start with.

Modelling the water budget of the Upper Blue Nile basin using the JGrass-NewAge model system and satellite data

This paper must be read after its companion on rainfall published in Atmospheric Research. There we were concerned with rainfall estimates over the large areas of Upper Blue Nile (UBN). Here we move on to estimate all the other components of the water budget. A similar goal was searched at small scales and with different tools, in this other paper about Posina catchment. So the paper can be considered sort of complimentary and covering a range of possibilities allowed by the JGrass-NewAGE system.

The paper abstracts reads: 

"The Upper Blue Nile basin is one of the most data-scarce regions in developing countries, hence, the hydrological information required for informed decision making in water resources management is limited. The hydrological complexity of the basin, tied with the lack of hydrometerological data, means that most hydrological studies in the region are either restricted to small subbasins where there are relatively better hydrometeorological data available, or at the whole basin scale but at very coarse time scales and spatial resolutions. In this study we develop a methodology that can improve the state-of-art by using the available, but sparse, hydrometerological data and satellite products to obtain the estimates of all the components of the hydrological cycle (precipitation, evapotranspiration, discharge, and storage). To this scope, we use the JGrass-NewAge system and various remote sensing products. The satellite products SM2R-CCI is used for obtaining the rainfall inputs; SAF EUMETSAT for cloud cover fraction for proper net radiation estimation; GLEAM for comparison with estimated ET; and GRACE gravimetry data for comparison of the total water storage amounts available. Results are obtained at daily time-steps for the period 1994-2009 (16 years), and they can be used as a reference for any water resource development activities in the region. The overall long term mean budget analysis shows that precipitation of the basin is 1360 ±230 mm per year. Evapotranspiration covers 56% of the yearly budget, runoff is 33%. Storage varies from minus 10% to plus 17% of the budget. "

The manuscript was submitted to HESS and went trough  a first round of revision (see the Discussion page). A revised manuscript was submitted. Please find below (on Zenodo):

• The answers to reviewers
• The new manuscript
• The complimentary material, including the shapefile of the UBN and the original figures.

The paper is now accepted and available at the HESS site.