Tuesday, August 9, 2022

WHETGEO-2D an open source tool for solving the 2D Richards equation

For new readers, WHETGEO stands for Water HEat and Transport in GEOframe. It is a set of models that deals with the processes in soils. The paper describes the 2D version of it, at least its initial deployment, since the system was built on the idea of expandability. The paper and its abundant supporting material a a step towards a series of further analyses of  the water behaviour in the vadose and saturated zones.

DeAnn Presley painting (https://www.agronomy.k-state.edu/about/people/faculty/presley-deann/)
The paper was submitted to environmental Modelling and Software and can be found  here.  Extensive material and video about WHETGEO 2D can be found among the material of the GEOframe Summer School

Sunday, August 7, 2022

Nobody applied to this call ! Reactions by Solomon Vimal ( How to Mobilize Top Tech Talent Towards Hydrology)

In a blog post, followed by a list-serv email, Prof. Rigon exclaimed,  “Digital Hydrologists from around the world unite! Nobody applied for this call”! His project focuses on building digital earth twins for the hydrologic cycle using advanced cyber infrastructure and software architecture solutions that are unusual in the field of hydrology in most hydrology groups around the world. He added, “Klemeš, V. (1986) reflected on dilettantism in Hydrology [... we cannot] manage complex interactions and feedback with poorly based informatics”. Prof. Rigon’s outcry indeed makes one think: “Ehi, out there, is anybody interested? Anybody interested in a PhD in this topic?”

It prompted me (Salomon Vimal, see below note by rr) to think -- what can be done to attract top informatics talent into hydrology?

Asterisks marks rr notes that you can find at the bottom.

Hydrology is a tiny field. We are a small sub-field of civil engineering. Among say 100 students who leave high school, conservatively, perhaps 1 in every 3-5 (maybe more!) years of graduation will reach the field of hydrology if lucky, and often by chance. This is an estimate on the basis that nobody in my circles from high school even knows what hydrology is. A subset of them may sign up to list-servs. A small subset (say 1/10) of professors would forward it to interested students in relevant MS programs. The incentives of a PhD salary in Italy, especially $ *, is relatively small compared to what most people with above average skills in tech industry get, so this filters a good portion of them out. Taken together with the fact that 95% of good software tech is developed by only a tiny fraction of the top percentile of the coders (more on this below), it is important to look for the tech talent with a different strategy to attract the cream-dela-creme. These call for a closer look at the tech talent pool and incentives to have them move to the small field **.

Let’s look at Stack Overflow’s (SO) skilled pool of talent. Let's assume SO is a good representative slice of the world's tech talent (which it indeed is). Some observations based on data on distribution of tech talent that can be drawn from Stack Overflow data queries at data.stackexchange.com. It may be helpful to look at how many people, with what skill level, contribution, and reputation are out there. There are 18M total SO users (see the query here). 95% of all activity is by 1M people with a 80 reputation. 80% of all activity is by 0.3M people with 850 reputation. 70% of all activity is by 100K people with 2K reputation. 50% of all activity is by 37K users with 7K reputation. The query example here can be modified to examine percentiles. But the point made here is simple. Most of the work comes from a very small fraction of programmers. For reference, I asked as well as answered 17 questions (a balanced karma) and only a few of my questions were actually appreciated and this puts my reputation score at ~880 (Aug, 2022) which accrued over 5 years or so, and I fall into the bucket of the top 0.3M users, i.e. top 1.6 percentile (by score) reputed users who make 80% of all contributions. My score is nothing compared to the top 50-100K users. While I generally feel comfortable to say that I am good with programming (with over 10 years of experience in Python), I certainly would not apply for the informatics job above, as I do not think I have sufficient skills to start contributing to the informatics/architectural aspect of the project without proper training in CS/IT. I would perhaps defer this position to someone with a score of >2-5K in SO or a degree in CS/IT. Using the query engine and the SQL language offered in Stack Data, one may try to find good metrics like rising stars on SO using one of the many threads on such metrics and pick the good ones to hire from such lists and write to them individually rather than wait for them to find the PhD job post***.

We may consider joint-specializations in PhD: In my previous company (RMS.com), flood models were built using GPU computing. Most of the hydrologists were unable to program with the GPU, but it was indeed developed in academia in a PhD work by someone at Penn State who had a PhD major in hydrology and minor in informatics — computational science, if I remember correctly. Most PhD programs do not offer such minor course work based specialization. Maybe universities can team up with the CS departments and offer a joint PhD in CS - this could be a solution to be attractive to a broader audience. I have no idea about the ground realities of bureaucracy that may impede such a solution, but I recall a double PhD in river science was offered at U. of Trento some years ago. ****

Let’s not forget the blackhole which attracts and retains top talent: Google alone has ~27K engineers (here, estimated for 2022) a good majority of whom are on SO, like the top user. The bulk of the good ones who do 50% of all activities are perhaps already taken by such Big Tech companies so PhD programs are not left with any good ones who have high reputation in SO. I know that Big Tech companies do have a similar approach to identifying top tech talent. If one prefers to do hiring in the more traditional way, one may write to CS department heads in some select universities in global cities that are in countries that would typically consider a move to Italy for PhD.

Consider the places where the bulk of tech talent comes from: The bulk of the top CS talent is arguably in US/China - clearly leaders in tech companies, products and talent - most of them perhaps won't move to Italy for PhD. This basically rules out many top university graduates. We are then left with some of the good institutes in other countries well-known for their contribution to global tech talent. India, for example, has a very strong IT workforce. But, it is better to focus on cities rather than countries in the case of CS expertise. In my experience cities that are Silicon Valley Like (SVL) in various countries might be good places to look. If I were to hire tech talent, I would simply look in the developing SVLs such as Tel Aviv, Bangalore and the NCR Region of India -- which certainly have a very strong talent pool in CS, perhaps not comparable to Bay Area or Shenzhen. I do not know the equivalent SVs of other countries but numerous articles like this one exist which enlist them. 

Finally, salaries: Horton wrote about a related issue in hydrologic research (Horton, 1937): "Men of highest degree of knowledge and experience in hydrologic matters are not likely to be employed by government salaries". The cream-dela-creme of the SVLs worldover will get salaries that will be well beyond the incentives of the PhD. In such a scenario, it may be sensible to adopt a different hiring approach and reach out to CS departments of universities strategically and identify candidates who have a demonstrable great level of skill in informatics which we are interested in and fully incentivize them to move to hydrology. For example CS graduates with say 3-5 years of experience from such SVLs may be interested in moving to Italy for the international experience and the good (alternate) life experience, even if the salary cannot per se incentivize a move. *****

It is indeed important for the field of hydrology to thrive with good software personnel who are also sought in all fields of science and all other domains of human pursuit. I hope we all agree this is a core problem with hiring good IT talent. Hydrologists need to hire top IT talent comparable with Big Tech companies to truly create good software as most of the good stuff comes from a small portion of skilled coders. It may be a good idea to give such hiring strategies a careful consideration. I hope my rambling is useful to hydrologists to reflect and find a good solution or hiring strategy.

Solomon Vimal

Solomon Vimal is an avid reader of the About Hydrology blog since 2011. He completed a PhD in hydrology in 2022 from University of California, Los Angeles on the topic, “Climate Change Impacts on Millions of Lakes”. He is now the founder and CEO of Geothara, a tech company currently incubated as a startup company at UCLA’s summer accelerator program and part of the 2022 cohort of the Runway Postdoc program at Cornell Tech in New York City. 

About Geothara: Geothara offers geographic change detection and visualization software to help its users explore the changing world using satellite images and a novel, up to 30% more accurate trend detection technique via a patent-pending technology that enables smarter location-specific decisions.

Comments by rr

* However, I would make not just a point of salary. The salary of a PhD student is not high but enough to live in Italy, if you are a young guy. Obviously you expect that the sacrifice bring some benefits. I cannot judge myself, but I believe that you can learn something from studying in Trento that you cannot learn elsewhere.

** small field (if we restrict our focus on digital hydrology) but important for life on Earth and for any community if we think that all is about water availability. After all everything which is alive requires water.

*** when we have our son, I felt somewhat inadequate to the role of father. Then I simply did (and I am doing) it. Never the fear should to succeed to stop you. Try ! PhD is a learning process.

**** That degree would be great to be set up but the start it is subject to the uncertainties and foresight of academic policies

***** unfortunately in Italy the salary is established once forever by the state (ok, maybe the single Universities could give some incentives). I will investigate what is possible.

Friday, August 5, 2022

Nobody Applied to this call ! Follow up by Keith Beven

 Keith Beven (GS), answered to my previous post and I think it is relevant to bring to the knowledge of everyone his point of view: 

"Dear Riccardo,


This is clearly something I have been interested in for a long time – in fact I was writing about models of everywhere long before digital twins became the parlance to use.


I attach some papers that you have not cited but would seem to be relevant. "

He also added in a second mail:

"I should perhaps have added that if you look at those papers you will see that I think there is one really important innovation associated with models of everywhere that carries over to the digital twins (where the latter is applied at appropriate scales) and that is the use of visualisations in testing models as hypotheses – including the use of information from local stakeholders.    You gain little from applying models at hyperresolution when hyperresolution is 1km for example (see the hyperresolution ignorance paper).   "

From Keith's "Still Dynamics" book (click on the image for the book)

Here the paper he cited:

Beven, Keith J., and Ruth E. Alcock. 2012. “Modelling Everything Everywhere: A New Approach to Decision-Making for Water Management under Uncertainty.” Freshwater Biology. https://doi.org/10.1111/j.1365-2427.2011.02592.x.

Beven, Keith, Hannah Cloke, Florian Pappenberger, Rob Lamb, and Neil Hunter. 2015. “Hyperresolution Information and Hyperresolution Ignorance in Modelling the Hydrology of the Land Surface.” SCIENCE CHINA Earth Sciences 58 (1): 25–35. https://doi.org/10.1007/s11430-014-5003-4.

Beven, Keith. 2019. “How to Make Advances in Hydrological Modelling.” Hydrology Research 50 (6): 1481–94. https://doi.org/10.2166/nh.2019.134.

Blair, Gordon S., Keith Beven, Rob Lamb, Richard Bassett, Kris Cauwenberghs, Barry Hankin, Graham Dean, et al. 2019. “Models of Everywhere Revisited: A Technological Perspective.” Environmental Modelling & Software 122 (December): 104521. https://doi.org/10.1016/j.envsoft.2019.104521.

Panta rhei is new picture book by Keith, while Still Dynamics is only available on pdf now. 

P.S. - On the same topic we recently submitted a paper to HESSD:

Rigon, Riccardo, Giuseppe Formetta, Marialaura Bancheri, Niccolò Tubini, Concetta D’Amato, Olaf David, and Christian Massari. 2022. “HESS Opinions: Participatory Digital Earth Twin Hydrology Systems (DARTHs) for Everyone: A Blueprint for Hydrologists.” Hydrology and Earth System Sciences Discussions, 1–38.  Updated manuscript here

Thursday, August 4, 2022

Nobody applied to this call ! Hydrology needs people willing to work on digital hydrology either computer scientists, physicists, mathematicians and, yes, hydrologists

The call is the one below and nobody applied to the call. I am willing to try to get a new call for it but this time I hope that someone show up with the appropriate background and, above all, the appropriate will.  


Ph.D. position on building a Digital eArth Twin of Hydrology  (DARTHs)

Reference persons: Riccardo Rigon (abouthydrology@gmail.com)
Website of the call: https://www.unitn.it/en/phd-nrrp-calls (further information coming soon on the site)

We are seeking for a pro-active individual either with a degree in environmental engineering, physics, mathematics with the will to work on the informatics infrastructure of the GEOframe/OMS3 system or someone with a degree in Informatics or Computer Science willing to mix their knowledge with the needs of Hydrology and Earth System Sciences in order to provide services to computer modelling and forecasting of hydrological quantities. The system being developed is being applied to the Po river catchments for the forecasting of droughts and the assessment of water availability and will be subsequently extended to the whole Italy.
The starting point is the project currently being developed at the basin Authority of river Po and will be based on the informatics of the GEOframe/OMS3/CSIP (Object Modelling System/Cloud Service integration platform).
The duties and the scope of the PhD work could vary according to the candidate background and attitude and can include: improvements of the workflows of the platform towards the direction to obtain a DARTH, improving the parallelism of computation in the cloud (by modifying OMS3/CSIP or using other tools like Airflow and Kubernetes), providing visual AR/VR interfaces to the workflow, cleaning the entire platform and evolve it.

In this project imagination and willing to challenge theirselves comes before than any already acquired knowledge.

The Ph.D. will be in an international context which include the participation of Colorado State University (dr. Olaf David) for OMS3/CSIP, Pisa University (dr. Marco Danelutto) for parallel computing, University of Saskatchewan (dr. Martyn Clark and dr. Wouter Knoben) for shared workflow and ourselves in Trento (dr. Riccardo Rigon, dr. Giuseppe Formetta, dr. Niccolò Tubini). We do not exclude the possibility to open further collaboration with colleagues of the University of Trento or the Trentino Research System. Besides the work will be in strict contact with the Po river basin authority for which the infrastructure will be deployed. The candidate is assumed to spend at least 6 months in Colorado State University and 6 months at the Po river basin Authority.
The interested candidate are invited to contact dr. Riccardo Rigon at abouthydrology@gmail.com. The official call is at https://www.unitn.it/en/phd-nrrp-calls
For who interested in deepening the knowledge about the Digital eArth Twins of Hydrology (DARTH) a concept paper was written for Hydrology and Earth System Science and can be found here.
The infrastructure built will be open source, built with open-source tools, openly documented by using literate programming and literate computing workflows. It will also makes it easier to share public open data, and, at the same time, getting their elaboration back. FAIR principles are already at the core of the existing infrastructure, as it can be deduced from http://abouthydrology.blogspot.com/2022/03/geoframe-essentials.html and http://abouthydrology.blogspot.com/search/label/DARTH

I understand that the topic is challenging and needs an environmental engineer (she, he, they) who like informatics or a computer scientist who likes to work outside traditional computer science topics. Or a physicist or a mathematician (originally I graduated in Physics, for instance).  But I think the work is very exciting, unique but, at the same time, opening job perspective everywhere in the environmental field. So please who is interested write to me. This call was not  considered a good one but hydrological science cannot move on without this kind of persons. 

Tuesday, August 2, 2022

A reminder for my hydrological modelling students

The experience of working to real catchments cases is really frustrating most of the times. I indicated in this lecture that there are several accidents that makes the real modelling complicate and prone to bring unsatisfying results.  But I want to encourage them reminding what my art professor told me about the Piero della Francesca painting below.

The painting portraits Battista Sforza on the left and Federico di Montefeltro on the right. The woman i pale as the fashion of the age required.  Her portrait is probably posthumous. The clear light comes from the far landscape and it has been studied to bring the two figures in foreground. What is far away and what is close are perfectly fuse together and they symbolize a divine order, dominated by mathematical laws that make the humans not as mortal but as ideally eternal, due to their moral superiority. 
However if we look at the persons who are represented, they cannot be considered handsome examples of a man or a woman. Maybe bit even for the beauty standards of that age. The humans can be ugly but the painting is a masterpiece.  

Coming to us, our fitting of models to reality can give, for many reasons, ugly results. Discharges or other quantities not fitting that good that we want. But this misbehavior, if explained can bring to new interpretations of the processes, new research pathways, new insights. The same as the paintings. The fitting can be bad, but the work around them a masterpiece.  So do not get depressed when this happens. 

Sunday, July 31, 2022

The Water Resources Management Methods in Agricolture Course

 This is a place holder at present- Material will be uploaded progressively during the August month

Foreseen topics to be treated:

15 hours about theory of evaporation from soil and transpiration from plants. (Why to irrigate and when to irrigate)

15 hours designing an irrigation network (How to irrigate)

10 Saving water and money when irrigating (How much it costs to farmers and society)

15 designing an irrigation system

3 seminars: Digital Systems to manage irrigation; Water Harvesting in developing Countries; Irrigation of urban parks.

1 Study visit

Wednesday, July 27, 2022

Droughts effects on Bondone from a Mesiano Window commented

This is the image of Monte Bondone that I saw this morning from the class where I was testing my hydrology course students. 

I realized that I could have asked them to comment the hydrologic status of the hillslope they were seeing (or the geomorphology indeed). Because in these days droughts it is hitting. The argument could be that one.  So let take the Figure above and trace some lines as below. 

If you follow line one, better seen in the initial figure, you can see mostly conifers and probably some beech tree. Their color is dark and they are in little valley-hollow. The plants there are not probably under stress. Same as along most of line 3 which follows in the first part a convex-divergent topography  but probably in the first part there is still enough soil humidity (a closer check would be necessary though) while in the second part there is a concave, convex topography which is markedly green, and not apparently under stress yet.  In the upper part where there are not trees, but bushes and grasses which are loosing their color and manifest the dryness of the top soil (we are in a "nose", however). 

For paths 2 on the nose, trees are essentially absent, soil shallow and "bushes" dry as well.  Path 4 has a little different topography. Only in the middle it seems dry, while in the other parts, soil should be deeper and soil moisture present enough to maintain the trees dark green. Soil deep but not too deep. Path 5 in fact is on a conoid (an alluvial fan) and trees there are markedly brown. Whilst a local check remains certainly necessary, the possible interpretation is that on the alluvial fan, composed mainly by gravel and alluvial detritus, the water infiltrates deeper and is  not that available to plants root. 

Please observe also that between 1 and 5 there is a furrow that during storms hosts a waterfall and there water is surely more present than elsewhere. 

All is fictional obviously but I bet you cannot give a better interpretation.