The Virtual Hydrologists Project and other initiatives about Hydrology History

This is to bring to your attention to a very welcomed initiative of the American Geophysical Union. In thee words of Efi-Foufula Georgiou (GS):
"We are happy to announce the launch of a new initiative within our Hydrology section—the Virtual Hydrologists Project (VHP). The scope of VHP is to preserve the legacy of eminent hydrologists who have shaped the field of hydrologic sciences and education by making their scientific work easily accessible to the community. VHP is a living project, which will continually invite the community to contribute material, additions, and/or corrections toward building a comprehensive library to be enjoyed by all generations of hydrologists—from junior to senior researchers".

"We started in 2016 with four inaugural entries: Robert Horton (1875–1945), Walter Langbein (1907–1982), James C. I. Dooge (1922–2010), and Paul Witherspoon (1919–2012). More will follow, and a committee has been formed to advice on the growth of the project."

Some years ago AGU produced also a series of interviews which are now on YouTube:

• C. V. Theis (1985) interviewed by John Bredehoeft 
• R. K. Linsley (1986) interviewed by Simon Ince and R.A. Clark
• John R. Philip (1995) interviewed by Stephen Burges 
• James C. I. Dooge (1995) interviewed by David R. Dawdy 
• Terence O’Donnell (1995) interviewed by David R. Dawdy 
• David R. Dawdy (1995) interviewed by Terence O’Donnell 
• Mark F. Meier (1995) interviewed by Gordon Young
• Gilbert White (1996) interviewed by Mary Fran Myers 
• Peter S. Eagleson (1997) interviewed by Stephen Burges

In the same line, Keith Beven (GS, RG) started a parallel initiative  the "History of Hydrology Wiki" which can be worth to visit.

Learn from the masters !

A few R scripts useful for hydrologists

These are the script I use as templates for my short (very short) classes (Hydrology and Hydraulic Constructions/Urban Hydrology) when I introduce R. Reading a good R textbook or manual would be important, indeed to understand what I am doing. These scripts have to be "studied", meaning that operations are commented but for really understand them, any command should be studied.  Since data comes in various formats, it is shown how to deal with them.

Knowledge of what R Studio is is given for granted.

 - A quick introduction to R (Knitr pdf)
   This assume almost no priori knowledge of R. However you have to know how to load and execute    a script  in Rstudio. I suggest that, once loaded the script, you execute one command at time. You will know what vector and data frame are, and how to access their data.

 - Simple plot in R (Knitr pdf)
   It generates some random data (normally and uniformly) distributed. Plots them as a time series, as an histogram as a empirical cumulative distribution function.

 - Reading rainfall data and plotting them (Knitr pdf, the dataset, the Readme of the data)
    It reads data in cvs format, which come in many columns, each for one year; does some data treatment, melts the columns to produce a time series object, plots them, does the statistics of non-raining days and raining days. Estimates the autocorrelation function.

-  Reading the data of discharges of River Adige (Knitr pdf, the dataset, Readme file)
   It reads the data from a very rudimental file. Transforms the data in a reasonable time series, and plots it.  It introduces also the use of boxplots.

-  Estimating  depth duration frequency (ddf) curves of Duckburg with R  the dataset, Readme file)
   Starting from the annual maxima of given duration (as given in Italy) it interpolates the data with a Gumbel pdf using a couple of standard techniques. Uses Pearson ranking for getting the best estimator. After obtaining the probabilities for the various durations, it uses linear interpolation for getting the parameters of the idf curves. I admit, it is not a great statistics exercise. Let say, it is the standard we use in Italy. All is done step by step. The smart reader can shorten the procedures a lot. In principle is not difficult to automate the whole procedure, producing from the initial data table the final product.

• Elaboration of 1 hour rainfall (Knitr) 
• Elaboration of 3 hours (knitr), 6 hours (knitr), 12 hours (knitr), 24 hours (knitr)
• Summary of elaborations (data)

Urban Streams: five CUAHSI cyberseminars

As many knows, I teach Hydraulic Constructions, which means, in my case aqueducts and sewage systems. Recently, I tried to renovate my view on the latter topic by looking at recent directions and works on urban hydrology. In this phase of renovation, I found very useful the CUAHSI cyberseminars on Urban Streams which are available on youtube (also addressed by Dr. Anne Jefferson here).

Here below, please find the seminars.

Green infrastructure, groundwater and the sustainable city
Larry Band (GS, RG), Institute for the Environment at University of North Carolina

Watershed context and the evolution of urban streams

Derek Booth, Bren School of Environmental Management at UC Santa Barbara

The Little Stringybark Creek project
Tim Fletcher (GS), University of Melbourne

Contaminants of emerging concern as agents of ecological change in urban streams
Emma Rosi-Marshall (GS, RG), Cary Institute of Ecosystem Studies and Baltimore Ecosystem Study

Stormwater-Stream Connectivity: Process, Context, and Tradeoffs
Anne Jefferson (GS, RG, blog), Kent State University

Process based simulation of the hydrological cycle

The one below is a concept paper (or a review, under certain aspects) of researchers that thought at a certain moment of their carrier that lumped models were not enough. Criticism was often raised on this type of models (sometimes by bad modellers or by researchers in love with their own products: nobody's perfect).  Who follows me knows that both lumped (yes, up to a point) and distributed models are in my past research. Whatever party you belong to,  I think the paper is a good reading which summarises a lot of issues and give a view of the current state-of-art.

Clicking on the picture above, please find the paper's pdf.

A little history of Soil Science

A little and interesting history of Soils can be found in one of the EGU blog which I follow.

Here.

Water, Soil, Forests (The man who planted trees, III)

This is the presentation given for the annual day of forests. I am talking about the interaction of water (the hydrological cycle) with vegetation, soil and climate. As a modeller, I conclude about the challenge to model all of these complexities at various spatial and temporal scales. The other posts on the same topic are here.

Click on the Figure to see the presentation in Italian. Click here for the English version.
The short video synthesis made  (in Italian) for public who could not participate is here below.

Nice papers to read:

Bearup, L. A., Maxwell, R. M., Clow, D. W., & McCray, J. E. (2014). Hydrological effects of forest transpiration loss in bark beetle-impacted watersheds. Nature Climate Change, 4(6), 481–486. http://doi.org/10.1038/nclimate2198

Benavides-Solorio, J. de D., & MacDonald, L. H. (2005). Measurement and prediction of post-fire erosion at the hillslope scale, Colorado Front Range. International Journal of Wildland Fire, 14(4), 457–18. http://doi.org/10.1071/WF05042

Bentz, B., Logan, J., MacMahon, J., Allen, C. D., Ayres, M., Berg, E., et al. (2013). Bark beetle outbreaks in western North America: Causes and consequences, 1–46.

Brovkin, V. (2002).  Vegetation-Climate Interactions . Journ. Phys. IV France, (12), 57–72.

Blöschl, G., Ardoin-Bardin, S., Bonell, M., Dorninger, M., Goodrich, D., Gutknecht, D., et al. (2007). At what scales do climate variability and land cover change impact on flooding and low flows? Hydrological Processes, 21(9), 1241–1247. http://doi.org/10.1002/hyp.6669

Brown, A. E., Zhang, L., McMahon, T. A., Western, A. W., & Vertessy, R. A. (2005). A review of paired catchment studies for determining changes in water yield resulting from alterations in vegetation. Journal of Hydrology, 310(1-4), 28–61. http://doi.org/10.1016/j.jhydrol.2004.12.010

Brown, A. E. (2008, March 10). Predicting the effect of forest cover changes on flow duration curves. (L. Zhang, A. Western, & T. A. McMahon, Eds.).

Brubaker, K., Entekhabi, D., & Eagleson, P. S. (1993). Estimation of Continental Precipitation Recycling. Water Resources Res., 6(6), 1077–1089.

Eltahir, A. B., & Bras, R. L. (1994). Precipitation Recycling in the Amazon Basin. Quarterly Journal of the Royal Meteorological Society, 120, 861–880.

Entekhabi, D., Rodriguez-Iturbe, & Bras, R. L. (1992). Variability in Large-Scale Water Balance with Land Surface-Atmosphere Interaction. Journal of Climate, 5, 798–813.

Fatichi, S., Pappas, C., & Ivanov, V. Y. (2015). Modeling plant-water interactions: an ecohydrological overview from the cell to the global scale. Wiley Interdisciplinary Reviews: Water, n/a–n/a. http://doi.org/10.1002/wat2.1125

Jenny, H. (1958). Role of the plant factor in the pedogenic functions. Ecology, 39(1), 5–16.

Johansen, M. P., Hakonson, T. E., & Breshears, D. D. (2001). Post-fire runoff and erosion from rainfall simulation: contrasting forests with shrublands and grasslands. Hydrological Processes, 15(15), 2953–2965. http://doi.org/10.1002/hyp.384

Johnson, D. L., Keller, E. A., & Rockwell, T. K. (1990). Dynamic pedogenesis: New views on some key soil concepts, and a model for interpreting quaternary soils. Quaternary Research, 33(3), 306–319. http://doi.org/10.1016/0033-5894(90)90058-S

Miles, J. (1985). The pedogenic effects of different species and vegetation types and the implications. Journal of Soil Science, 36, 371–384.

Pielke, R. A., Sr. (2001). Influence of the spatial distribution of vegetation and soils on the prediction of cumulus convective rainfall, 1–28.

Tague, C., & Dugger, A. L. (2010). Ecohydrology and Climate Change in the Mountains of the Western USA - A Review of Research and Opportunities. Geography Compass, 4(11), 1648–1663. http://doi.org/10.1111/j.1749-8198.2010.00400.x

Trenberth, K. E. (1999). Atmospheric Moisture Recycling: Role of Advection and Local Evaporation. Journal of Climate, 12, 1368–1381.

Renjin

Renjin is a JVM-based interpreter for the R language. For Java developers  of scientific application, I think it is a must (but still I need to test it). It can be used in various ways and offers itself a simple interface to be used. The fraction of packages ported into it is here. 
For an introduction you can watch this webinar. But obviously you can have more by browsing Rnjin website.

Among others, gvSIG uses Renjin for making calculations.  The source code is available on GIThub.

Click on the Figure to go to Renjin website.