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. (See Notebook 0 an 1 here.)
  8. T - Extreme precipitation statistics (parameters' estimation)
  9. L - Estimation of extreme distributions parameters. (See Notebook 2 to 5 here.)
  10. T -  Radiation (YouTube 2017). 
  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
  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

No comments:

Post a Comment