Showing posts with label Me-Myself-I. Show all posts
Showing posts with label Me-Myself-I. Show all posts

Thursday, July 10, 2025

Methodology and tools for analyzing the hydrology of catchments: four papers and a set of slides and videos.

Recently I recommended 5 papers of mine, which I consider  representative of my recent work. However, they are on the side of the theory/numerics/informatics work. Not less important are those that could be erroneously classified as applications. The four papers presented here, in fact, represent more than a straightforward run of models to individual catchments. They deploy a comprehensive methodology that integrates traditional surface water systems with new features and methods. Their approach combines mixed-resolution spatial discretization through strategic Hydrological Response Unit (HRU) refinement with accurate pre-analysis of the input multi-source validation using neutron probes (as representative of local field measurements), satellite data, and conventional discharge observations.

The modular GEOframe implementation provides flexible model configuration while preserving physical consistency and enabling validation of individual modeling components. A key finding across these papers is that careful analysis of input data can guide model organization and improve  predictions. Each paper targets complete water budget estimation, identifying inconsistencies and providing more robust assessments of catchment hydrology than traditional modeling approaches than the traditional simulation based on discharge alone.
These studies introduce  analytical tools that should become standard practice for catchment hydrology modelers and gently use Earth Observations in their specific contexts. The collective work establishes a framework where data-driven model organization, multi-source validation, and comprehensive water budget analysis modelling try to converge to advance our understanding of hydrological processes at the catchment scale.  Part of the lesson learned from these papers has been also summarized in the set of "Seven Steps in Modeling a catchment", a series of slides and videos that can be considered complementary to reading the papers.  
Much more can be done using the flexibility of the GEOframe system which remains undisclosed.

References

Abera, Wuletawu, Giuseppe Formetta, Luca Brocca, and Riccardo Rigon. 2017. “Modeling the Water Budget of the Upper Blue Nile Basin Using the JGrass-NewAge Model System and Satellite Data.” Hydrology and Earth System Sciences 21 (6): 3145–65. https://doi.org/10.5194/hess-21-3145-2017.

Andreis, D; Formetta, G.;Bancheri, M. and Rigon R., Multiple Resolution Analysis of an Alpine Basin. submitted to Water Resources Research, 2025. Preprint

Abera, Wuletawu, Giuseppe Formetta, Marco Borga, and Riccardo Rigon. 2017. “Estimating the Water Budget Components and Their Variability in a Pre-Alpine Basin with JGrass-NewAGE.” Advances in Water Resources 104 (June): 37–54. https://doi.org/10.1016/j.advwatres.2017.03.010.

Azimi, Shima, Christian Massari, Giuseppe Formetta, Silvia Barbetta, Alberto Tazioli, Davide Fronzi, Sara Modanesi, Angelica Tarpanelli, and Riccardo Rigon. 2023. “On Understanding Mountainous Carbonate Basins of the Mediterranean Using Parsimonious Modeling Solutions.” Hydrology and Earth System Sciences 27 (24): 4485–4503. https://doi.org/10.5194/hess-27-4485-2023.


Sunday, September 19, 2021

What I did in research the last five years, 2016-2021

 In the last ten years I focused on building a reliable system for doing hydrology by computer. This systems learns from the implementation of the process-based GEOtop and is based on the framework developed by ARS/USDA called OMS3. The new system is called GEOframe


I have been concerned with the fact that many results claimed on the basis of computer simulations were, in fact, not properly reliable and verifiable, do to lack of software engineering, description of the internals of the tools and availability to researchers. Moreover, also the goodness experimental science is quite dependent on the capability and reliability of models.  In my experience with the model GEOtop so far, when there have been discrepancies between data and the model, most of the time the model was right and the experiment imprecise. Sometimes though was the model GEOtop (or other that we used) wrong and we worked to improve it. Models have to be robust, reliable, realistic and their results reproducible (R4). The new system GEOframe, which is built on these premises, is not a model though. It can fit several modelling solutions and it is actually is agnostic with respect to the methods. It is designed to offer a platform to compare different modelling strategies, lumped modelling, process-grid-based modelling and whatever but avoiding to redo any time the unnecessary.
We used some ML technique in the process of calibration and we implemented also a ANN framework (in OMS3) but that part is underdeveloped at that moment. (If we expand to much, we bleed).  

The older part of the GEOframe system contains lumped based types of models. However, we have recently implemented a solver of Richards 1D [0] and 2D (paper in writing) and 3D (software in deployment). The latter implement a new algorithm for integration of non linear PDE systems which always converges and can naturally switch between groundwater, vadose zone and surface water. Soil can be hot, warm and frozen  without problems (the latter is in deployment). Besides this I worked underground in having a better estimation of evaporation and transpiration. I published very little with respect the amount of work I did on these subjects, but disentangling the theory, the misconceptions, the scale issue was (is) not very easy, and took its time. I have a first (not completely satisfactory paper, from my point of view,  on this topic, just published on Water [1] , but better ones are going to be written in the Fall 2021 and in the 2022. Finally I worked on disentagling the theory of travel time residence time. We have some paper on it, since 2016 [2,3,4,5] which are also connected to a new way to categorize and, before of it, representing  lumped-semi-distributed  models [6] in order to be able to produce some quantitative reasoning about models structure. I did not pursued very much applied work but with GEOframe growing we were able to produce some nice applications on the Posina catchment [6] (~110 km2), Blue Nile (~175000 km2) [7]. These applications, could be the basis for a comparison of traditional and ML methods. We have also ongoing  the modelling of the largest river basin in Italy, the Po river (~75000km2) and the Nera catchment (closed at some hundreds of square kilometers),  being  very interesting because affected by karst.  Those  latter two catchments could be possible candidates for applying ML techniques and doing performance comparisons, once we have collected the appropriate data. Notably in the last work (actually since the implementation of GEOtop) working on the catchment meant for me working on the water budget of which the discharge is just one element completed by evaporation, transpiration and heat turbulent transfer. I viewed the use of the energy budget necessary to describe irrigation needs by crops and vegetation in this changing climate era, and in general as a tool to support a more complete view of the hydrological cycle.

Sunday, October 18, 2020

It's time to revise the GIUH

GIUH has been a valuable approximate tool for getting the hydrologic response. A review can be found in:
The question of maximum discharges treated inside the theory can be found in
The role of hillslope and channels was treated in:
Jointly with my first paper that proved the role of the geometric/topological structure of the river network in forming the hydrologic response,
these papers constitute, on my side, quite a body of contribution on the topic.  There are other greater contributor and their work is cited in the review paper I cited for first.


However, the theory has some limitations. Its applicability is based on the:
  • assumption that the rainfall is uniformly distributed (but C. Cudennec and coworkers were able to generalize it, see review paper)
having some recipes to get the effective runoff (i.e. separation of the total rainfall in quick surface water and baseflow and, besides, in evapotranspiration). Another limitation derives from the fact that
That’s why I went back to consider simpler reservoirs systems to get a clue of the interplay of the acting processes. This research work brought to the studies on representation of these reservoir models, to get the good old models streamlined for their structure, e.g.
and see especially the interactions among processes. The preprint-paper
is (among other things) a trial to get all the types of lumped models related with understanding where the diverse theories can be plugged together. Maybe a little convoluted as way of thinking but hopefully effective.
Another remark regards that once upon a time I was looking and satisfied with discharge, now I try to check the water and the energy budget and, therefore, the overall budget. Let’s see what comes next and if I am able to close the circle.  For who is still interested to implement a GIUH solver, please look at here.

P.S. - In the whole GEOframe/NewAge stuff, river geomorphology is present through the connectivity of the Hydrologic Response Units. Hence geomorphology is not absent: it is just not present in the simple way allowed by the GIUH that permitted to obtain those remarkable semi-analytic results present in the cited papers. 

Friday, May 1, 2020

Three papers that affected my recent research

Stimulated by the quarantine and by chain letters regarding books or movies, by my FB friends, I tried to think to a similar chain for papers inviting research friends to expose five paper among those that they were important in recent years. My own five were:


But these go back quite in time and affected almost all of my research. So they do not count for the title. They are very recognized benchmark papers. Important for anyone.

The three are recent:




As in the tradition of these chains,  no explanations but the links to the papers, yes

Friday, March 10, 2017

The tale of open source codes

Prologue

Why did I choose to produce with the people directly working with me (ph.D students, master students, postdocs) open source software ?

- because is good for science
- because I am paid by a public institution
- because it is a neutral conditions that can serve the rights of all the participants (in particular mine of freely use and modify the software at my will an defend myself from who, people or institution, would like to close the software, even against me). On the other side,  my intention is clearly that my projects serve as a seed for developments of my students (or others) who can freely use the products of my research and maintaining it alive beyond me and despite me. *

I use GPL (for its interpretation, see here) but many others licences could work.

A declaration

In this way, I think, I have the right to claim to be able to use or peruse the software outcomes from my group. I declare that I want to use “fair play” rules, but, it should be clear that these rules cannot extend to limit my research freedom. People who claim the participation to papers where they give no contribution, except having producing the code that we produced together, have wrong arguments. People who claim to be involved in projects or researchers, without any other reason that I want to use the software they contribute (under GPL), have wrong arguments.
Neither they can claim that I have to warn and tell them personally what I am going to do in my research with the common code, for having their consent.
They would be right to protest, only if I would not enlighten their contribution on previous work properly.
My research for my own belief is actually very public and its evolution too. It can be found at the abouthydrology blog. My core research is shared with my teamwork. This includes just the people of whom I have direct responsibility for age and rule (Master students, Ph.D. students and postdocs) and whom I sustain with funding, my own time and ideas.

With all others, including my masters, and my former students, colleagues, friends, women and men that like my research topics and achievements, and me, I can have collaborations. This means that we can share part of our views, beliefs, discussions, fightings, friendship, papers, parts of code. However our own agendas, in this imperfect world, do not coincide, and if they do, this happens for an incredibly short time. It seems it is a declaration of distance, but it is just consciousness of how life works, and the first step to start an effective and respectful collaboration.

Q&A

Can my students refuse to develop OS software ?
No, as soon as it is the product of common intellectual efforts in which they, maybe, write the code, but I will say what to write.

Do I start collaborations in which not OS code can be developed ?
Never say never. However there should be very strong reasons because, from my side, I to support this. Certainly in projects there could be partners that develop non open source software, but this falls in the responsibilities of who gives the financial support.

Is the requirement of open sourceness enough ?
No, it isn't. Open Sourceness is useless if not followed by good practices of using open repositories and collaborative modalities of action.

Can my students refuse to learn these practices ?
For the common work no. I am not responsible for the rest. I tend to fully book their time, though.

Do I start collaborations where these practices are not followed?
I would prefer not, but I do. Certainly collaborations can be at different levels and rarely they are about co-producing software. I would not participate to joint projects where I put ideas and expertise and others write closed codes, unless they pay me or my group a lot. Really a lot. I can participate to projects where other subjects put their ideas, or ideas from literature, in their own closed code, and I put mine in OS codes. However, the situation I prefer would be a common production, as a community, of open source codes.

My own use cases

Here below I summarised (with quite large simplifications) my software history in order to further justify what I wrote above.

Professor means who puts science, time, and money (funds derived by projects). Student means who puts time and science. Companies means they put time and money and business related efforts. Agents, Subjects are generic actors of the play (they can be either students, professors or someone else). Community is the informal group that happened to gather around the projects and, eventually,  evolve them.

Case 0

Professor Z writes the initial library. On top of that A builds radiation budget. Student B writes surface water flows. Student C implements soil-atmosfere interactions. Students D writes vadose zone components. Student E writes snow treatment. Student F rewrites snow components, then rewrites most of the codes interacting with student G and student H. Student I writes codes for landslides triggering treatment. Student G writes a small but important portion of the a little but successful part of the freezing soil hydrology. Professor L hires F. F continues to rewrite parts. G start a huge operation of cleaning the code, moving it to C++, uploading it to an open repository. C comes back and starts to use the code in his research and occasionally hires H to do some ancillary work for treating data. In meantime G  has founded a company where the common code is the basis of the business. M company, initially hired by L, works on the code to refactor and enhance it. M works collaboratively with G and F. M to setup continuos integration. Student N starts to produce executables for the main operating systems and eventually on Cooker (fictional name). M embraces immediately this philosophy.


Case 1

Professor Z writes the initial library. Z writes more than fifty tools for terrain analysis. Student A (not the same as above) ports them to a major Open Source GIS. Z and A start the construction of a new GIS, say JG. Initially JG contains just the the terrain analysis tools and some simple hydrological model. They start to do schools for financing their project. This works for some years. Student B, in the meanwhile, has joined the crew and A & B funded the company AB. They live with schools, supports from a main project of Z and other resources (a main research projects). A cleans the tools' suite and inaugurates the name JGT for them. Z uses JGT in his classes.
Z, A, and B decided to join the development of UGIS. Some research projects supports them together with resources raised by the company AB on its own. Students C and students D write some further modules. UGIS  funding disappears, and UGIS slowly becomes an almost inactive project. AB brings JGT to an intermediate product ST. Z continues to USE JGT in his classes. AB finally joins the development of a new GIS, say GS.
(In the middle,  A adds new tools, AB wrote an Android app, Aapp, and expands its business. Aapp is not  related to JGT, but worth to mention). During the years A and B get a Ph.D. whose topics are related to the GIS work. Student E with a small effort brings back JGT also to a platform, OI that Z uses with his students.

Case 2

Thanks to an unexpected financial support from project 00, Professor Z hires a five students to build from the scratch a new modelling platform. For this new software enterprise, he and company AB (funded by his former students A and B) chooses the open source framework OI. He hires former student C, to help software developments and former student D and E for the general management of the project and data gathering, respectively. C works more on improving and enriching JGT (see case 1 above) which serves as a basis for the terrain analysis functional to modeling. A and B develop a full suite of model components (the new paradigm) for: temperature and rainfall interpolation, rainfall-runoff, evapotranspiration and various tools to visualise components' inputs and outputs. AB also designs and populates an SQL database that contains all the data of the projects. The projects 00 ends. The Institution that supported the project close it in a drawer.

With other financial support, former 00 project's tools are maintained in life. Open source framework OI is changed for open source framework OM with a notable reduction of code lines (but it is a huge code effort, indeed, almost entirely on AB shoulders). With embracing OM, also starts a research collaboration with professor U and W.

Student E comes into play. He realises that rainfall-runoff does not work well. AB company has to survive on its own and cannot give very much support (https://vimeo.com/144089061). E implements a new rainfall-runoff model. AB, however, hires F for a small project where he works on radiation. Eventually, E refactors F's work and highly expands it. E adds a new snow modelling component and does/refactors evapotranspiration. In doing this (pouring sweat and blood) he, however, has the guidelines of the open sources codes already written. E spends some periods at U and W. E also refactors and enhances the Kriging code. Eventually E graduates and starts his career as post-doc elsewhere. In the meanwhile he finalises his research in a series of papers.
Student G comes. He does not have programming skills, but quietly learns to use the components of E and produces some interesting papers where E is co-author.
A new student, H, comes into the game. She works first on radiation on top of E code, then she starts to implement tools for travel time analysis and another rainfall-runoff component.
Student L comes. He  has a strong attitude for informatics. He brings-in new ways to manage projects. H and L implement the OpenOpenSoftware repository, and the site BeatifulGEO (names are fictional, but tools real). H refactors the old code,  and together with L (who, sort of, leads the learning process), introduces design patterns for increasing code reusability. L provides the trickery to have continuous integration on OpenOpenSoftware using GETIT and connects software deployment to ISTOREIT to store official versions of the components. Students M and N come in to stage and start to use the code. Professor Z (with the help of H) starts to use the components with his students for his classes. Student L evolves the original OM capabilities to allow for more flexibility and to increase the computational power of the models. H brings-in her models into the new infrastructure.

Discussion and Conclusions

The above is a summary (where, I say again, I simplified many passages) of my main software enterprises. Could have they been evolved all differently (and better) if I would not have applied an open source strategy ? Probably yes, but I should have constrained the students to a contract about the property of the software. In this way I would have deprived my students of parts of their own work.
At the same time, I could not have left the software simply to them. The histories themselves show that I built my own work and research on the software we develop, and being free to use it and modifying it was a necessity. If I have needed to ask permission to use it, to sign a contract or so with someone (for instance who gave financial support), all the development would have been much more difficult to pursue. The same apply for other Actors who invested time and resources in the software development just because it was open. They are usually singles or low budget companies that could not have afforded expenses related to other type of licenses and be subjected to limitation of the software use.
Other researchers used the model. Being it free and open source was a clearly an added value for them.

Keeping the software close and commercial, besides not having scientific reasons (which require the contrary), would have obliged me to change myself in a businessman and turned away from my science. There are several cases of scientists that turned to captains of companies. But, for instance Stephan Wolfram, a gifted scientist, did not give very much contributions to science after he devoted his energies to MathematicaMathematica (probably the best computing environment ever) itself is his main achievement (which is not depreciable), despite his own claims on "New kind of Science"s.
The overburden required for managing a commercial software is not for all and has its own dynamics, that personally I  could not bear.

The fact that my code is free and open source has allowed (not without difficulties) self-instruction of new incomers. Various Agents had the possibility to start experiments and investigate new directions of development. Nobody needed to ask for starting them. Asking is a process that would have decreased dramatically people or groups pro-activity.

The Community had benefits from this policy. In some cases, single Actors could have thought that their contribution was not recognised enough and did not give to them an advantage. Their argument is  flawed. All of them had advantages from the collaborative environment and nobody (me included) could have produced what s/he has achieved without building on the shoulder of others and other open source projects.

Forgetting the above, some feel that their work is not enough protected, and being all open source, newcomers can more easily jump in and take advantage of their work.
Uncertainty on future, a competitive society, the pure necessity to find something that pays you for a decent life incline even to bests to a moderate selfishness or a moderate parasitic behavior. They do not want to give back to the community, after having got a lot from it, and act defensively.

Well, this behavior is absolutely possible if their developments do not use the original code that was produced as GPL. In particular, the components strategy used in project 2 above allows for building on top of the open source material new, undisclosed material, that anyone can use for his/her own profit, with a non open license.
I have to warn, however, that if the moderate parasitism grows too much, enthusiasm that is always necessary decreases,  the projects die, the source of benefits disappears and the community falls.

I would say that a mild parasitism is functional to the community if it is necessary to sustain the collaborative Subjects, and if eventually the Subjects give something back to the community. Parasitic Subjects themselves act in favour of the community by spreading and advertising the products, and sooner or later this will be bring benefits back (so do not blame them, they are, in any case, part of the stream).

Some Subjects actually wants an opaque management of the GPL philosophy in which people maintain an informal (but they pretend recognized) property of the software that goes beyond the copyleft and the intellectual recognition of their contribution. This would imply, in their mind: preferential redirection of funds towards them; involvement in papers or conferences contributions that use their code; veto power towards actions of thirds.
These desiderata are based on misunderstandings. It is clear that they will be involved in papers, conference, and decision. Any (wo)man and community of good-will will apply this policy in their favour, if they do not grow too greedy. But these actions are not mandatory and not even necessary. GPL does not implies them.

To be more clear, especially in hydrology, the market out there treats our model and softwares as a fungible commodity, that is, the market tends to treat all the codes as equivalent or nearly so with no regard to who produced them. (I think this is wrong, highly wrong, when brought to an excess).
But also the internal market, inside the community, treats them as commodities, meaning that, it would be dysfunctional, it would cause a waste of precious time, but any contribution is perceived as a thing that can be replaced (this is part of the not said history of 0,1,and 2 projects). Everybody is important nobody is necessary.


The A. paradox

One common argument of reluctant open sourceres  is: “I did not have still tapped the results of my own work and I should share it (statement 1)”, or "if I share it, others will use it without me and I will have no personal gain(statement 2)".
The first danger can be overcome, by an appropriate delay of the disclosure of documentation and explanatory material (I would not argue that keeping industrial secrets is useless, in general, however). That is: it is matter of having strategies that prevent the negative cases. In our field, however, being everything perceived as a commodity (see above) nobody will care to use our model or achievement instead than another one that gives what is (wrongly perceived) as similar, especially if our code is not known. Being open source with proper support actions helps model spreading.
Besides, looking at my histories (see also here), software changes fast and is, by no means, immutable. Histories 0,1, and 2 are signed by change. So the advantage one has with a new code in hands is ephemeral. In my own estimates you have just a a year of advantage for small codes, and a few years of advantage with a large and complex code. This small advantage, if you are smart, can be appropriately managed and used to produce new and more innovative code and so on. (Open sourceness is against stagnation).
Often, however, it is not the the fear of far away threats that makes problems, but the fear of close by Agents. Guy A fear that B in the group who came in after her/him, will get positions or funding with his/her work. I would say that this could happen but it is difficult. In a fair (not fear) competition A always wins over B, if the quality of B can just be attributed to codes that A developed. The real problem is when B is much better that A. But in that case, having A work for B is not important. B will get rewards instead than A almost always. For A, the best thing, in the medium range, is to collaborate with B.
What, finally I really call the A. paradox is in statement (2). If it is so easy to grab your work, then it would be equally easy to anyone to replicate it. Therefore your work is not giving to you any competing advantage, even if you keep it secret for a while. If it is not easy to grab, then, who wants to use it proficiently needs you. So you are the winner, not because you keep your code top secret, but because all the issues it solves require a complex expertise that only you, the author can have. So ….

Epilogue

Professor eventually Z disappears. Not because he dies (please do exorcisms), but because his role, in the growing group of people around projects has become more and more marginal. Subjects also acquired maturity and as well as the will to maintain the advantages that the work has produced with respect to competitors.
This passage requires that the initially informal community establish as a formal Community (they wrote here for Academics) with its rules, etiquette, and wise management. This, in turn, requires Subjects coordinate and share alike their views, plan together new developments, plan events to make the common work to grow. Balkanisation of the code (which GPL could allow) and internal conflicts (never avoidable, having the Subjects different agendas) should be managed appropriately, and this requires clear agreements, smart actions, good will, and wise arguments.
If the community grows, everybody would be safer, because cooperating is better than competing (see also coopetition).
A partial adoption of the Open Source strategy is instead very useless. Open source codes that are practically not available (as those that are open source but not freely downloadable) cannot grow a healthy community and, sooner or later, die.

* A final note

Actually even if in my intention is a project also for my students, not a few of my students do not deeply endorse it. Reasons for this can be, maybe found in their personal history, the chemistry of their bodies and minds, or something else, which is hidden to me. So far, I  overreacts feeling myself betrayed, when they dismiss in what I believe it is right. So, probably my attitude is not is not correct. Sons do whatever they want, and probably they are right to try to find their way. So I have to conclude that the above is MY dream, and I will not be upset anymore, if my academic sons search their own in a different way.

Wednesday, December 16, 2015

An overview of my research and my future envisioned work. My professorship talk

I was finally asked to do this talk, that cover my research experience, for my Full Professor appointment here at the Civil, Environmental and Mechanical Department of the University of Trento.  This the abstract:
In this talk I will cover, in brief, my last 25  years of research through my main contribution in surface hydrology, river network evolution, hyperresolution and travel-time modelling of hydrological processes, hydroinformatics. Life means “my academic life” but also some recent orientation I am taking to model the non linear interactions in the water cycle. These include plants and ecosystems, which I believe will be my next research objectives, which I will pursue with the use of my model infrastructure, based on evolving  GEOtop and JGrass-NewAGE.  I will talk a little, maybe, of thermodynamics,  hydro-informatics, and optimisation principles in natural processes (I see that I do not have a post, on this, I will do it). A little on Cryosphere processes will not be absent.


Clicking on the Figure, you will be linked to the slides of my talks (with links to literature). The talk, unfortunately is in Italian: but the slides are in English. Below, please find the youtube.

Friday, September 18, 2015

My wish list for the next 15 years

Last night I was asked by two colleagues what I would like to do in my next fifteen years of carrier. So this post goes quite on personal. I answered being happy. But this was obviously too generic.
Professionally-wise, I added
Obviously writing fifty papers is not a very high objective, and all of it seems, maybe, mundane. However, the real wish would be that ten out of my fifty papers, would be better that the ones I already co-authored (reasonably five of them). Having one of two of them becoming benchmark papers.

Friday, July 10, 2015

Water for life: the study of the network of interactions in the hydrological cycle and their effects

I wrote several time what I do. The following is the translation is the synthesis I prepared recently for high school students, hoping to fascinate them and drive them to the study of hydrology.  

My research consists in determining hydrological fluxes, from the sky to the earth, and again to the sky. In its flow, water sculpts earth surface, feeds life, sustains the ecosystems complexity, and is at the core of many economic activities.  The quantification of  water fluxes  is not trivial at all. It requires the use of sophisticated mathematics and implies a great variety of measures. By myself I make computer models. 

It would be a mistake to believe that the physical/mathematica details  of the hydrological cycle are known. All the hydrological cycle is ignited by sun’s radiation  which provides  the energy transformed in the hydrosphere in other forms and never trivially, by very complex dissipative structures.
Among  these: river networks, “lines” which cover (drain)  entire surfaces; vegetation, and plants which eat photons to fix carbon in their structures (from atmospheric C02) and produce oxygen  (from H20) using photosynthesis. My research focus in following water interactions through models.

With my collaborators, I developed two models: GEOtop and Jgrass-NewAGE.  
The first is a hyper-resolution model: it partitions a catchment with a grid cells of a few meters side and on this grid mathematically treats radiation, infiltration, evaporation, transpiration, rain and snow fall, snow metamorphism, soil freezing, and runoff production. All this complexity is not an end in itself, but is deemed necessary to understand local hydrological phenomena as soil moisture distribution, or shallow landslides triggering.
The second model instead tries to give answers at catchment scale, averaging out hydrological quantities, but without loosing the necessary and relevant information.  JGrass-NewAGE is used to understand what happens in medium rivers, as Adige, to large river basins, as Blue Nile: it also helps in understanding how hydrology affects and is affected by the climate crisis. 
Informatics has an important role in my research. JGrass-NewAGE,  more than a model is a modelling system, based on sophisticated informatics suitably developed to build environmental models and to make easier the interactions among researchers. 

Wednesday, September 10, 2014

My CV and Five Papers that represent me

For who it may concern, I am posting my up-to-date CV here. It collects what I did,  and contains information already present here (where, in addition, you have a link to the papers).

For a shorter version of my CV, please take this.
If I would asked to choose five papers that more represent my work (and me), they would be not the most cited (among them), not those in Journals with the highest impact (well ... among them), and I would select probably:
Obviously I did decent work also between 1992 and 2006. Enjoy!

For 5 more recent papers, representing the decade 2015 to 2024 please see here

Sunday, June 12, 2011

Research topics for my next 20 years

These are the research topics I posted on the call for the doctoral school of Trento (but I update regularly this post -last update is dec 2014). Who wants to know what I did (the basis to know what I will do) can find my papers and my past research topics  here.
I try to contribute to hydrology theoretical development, build tools, and apply them to some case studies (others make mainly experiments or field work: and I appreciate a lot  their work. But I will never become what I am not: if you want to deal with experiments and field work, you possibly waste your time with me). So students can get the best from me if they have attitudes that get along with my inclinations. Cause of  personal attitudes, programming skills, or the will to pursue them,  are necessary to work with me. I use  C/C++, R, and Java, and I made some posts to help people to become a little more familiar to some of these tools (R here, and Java here). Other good tools exist: but do not blame me if I do not use Fortran or Python. I did this choice long time ago and I am still convinced it was not wrong.
I produce models, free models, and  it is intended that all the tangible work in programming and tools of anyone working with me  must be free software.

Hillslope hydrology, landslide and debris flow triggering, and erosion thresholds

The goal of this research line is to develop and assess models of shallow terrain instabilities through mathematical and numerical modeling, and the validation of models by means of conceptual and field experiments. These last will be prepared jointly with other institutions, in particular we have an ongoing collaboration with Bologna University for some basins in Val di Fassa, where several data were collected, USGS (Jonathan Godt) and School of Mines (Ning Lu). To get an idea of what I am talking about, you can give a look at this post.

The basis of the research is the use of GEOtop 2.0 and GEotop-SF and their improvements. With regards to hillslope hydrology the issues right now seem to have a reasonable model (or mapping) of the soil depth, a reasonable way to represent it within the constraints of a grid, and the characterization, at the grid cell size, of the relevant hydrological parameters (for which we have some hints deriving from soil scientists).

Besides covering hillslope hydrology issues, this research is intended to move from the simple assessment of triggering through the infinite slope stability model to model of propagation and self-organization  of the stresses within hillslopes, and implementing Jonathan's and Ning's new theories.

The candidate needs also to develop tools and techniques for the assessment of the boundary and initial conditions necessary to drive the models and perform innovative statistical analysis on the spatio-temporal patterns produced by the models.

My past research on this topic can be found here.

Distributed Modelling of the Hydrological Cycle at large scales, hydrological predictability and data assimilation

This regards mainly the development of the  JGrass-NewAGE for the complete closure of the hydrological budgets, in medium to large scale modelling. This requires the implementation and testing of new physical-statistical model of the various terms of the hydrological cycle, and their application to case studies at the scale of hundreds to thousands of square kilometers. At the  moment the model has a first implementation of all the processes that is going to be thoroughly  tested, and the main interest in this research is to go beyond the simple forecasting of hydrological quantities (in space-time) to achieve  the estimation of error bounds in the predictions with the application of appropriate calibration methods, and data assimilation procedures.  The doctoral work is intended to achieve also the application of models and tools to real cases (as for instance those provided by the DMIP2 project).

My past research and further insight on the topic can be found here.

Distributed Modelling of the Cryosphere

This study involves the modelling and forecasting of the evolution of the snow cover working with the model GEOtop. Previous Ph.D researchers implemented a one dimensional energy budget of both the snowpack and freezing soil. They also posed the bases for further theoretical and numerical improvements of the model, to a 3D version, and eventually including also different constitutive relations, which could be pursued in this research.
The present proposal is especially dedicated to include (or embed) GEOtop modelling with a data assimilation system dedicated to real-time forecasting of the snow cover, depth, and status. The Ph.D. work could be oriented to assimilate either ground data than remote sensing data.

The work will be made in coordination with Mountain-eering S.r.l, a spin-off of the University of Trento, and Stephan Gruber of University of Carleton (CA). 

Starting point for this work is, at the moment, Matteo Dall'Amico Ph.D. thesis and the paper Dall'Amico et al., 2011, which I consider one of my milestones.

Information about my research on Cryospheric processes is here.

Theoretical and Numerical studies about the non equilibrium thermodynamics applied to Hydrology


Hydrology is a thermodynamical science. Each of its fluxes is waiting for a proper assessment which ties together non-equilibrium thermodynamics, and sound fluid dynamics. Little steps in this direction were already made in studying the interaction and the phase change in frozen ground, but remaining essentially in the framework of the classical quasi-equilibrium thermodynamics. Consistent steps can be made actually for most of the processes, including evaporation and transpiration,  flow in soil and groundwater, and freezing soils, building upon rational thermodynamics of irreversible processes, and the mesoscopic thermodynamics.  The theoretical work, if possible, should be completed by appropriate numerical work. It is intended that all the tangible work in programming and tools produced as free software, and using free software.

Implementation of new methods for integrating Navier-Stokes (NS) equation in rugged terrain

Having a nice and suitably implemented method of integration of NS equations is seen as the natural complements to what done so far within GEOtop.  Evapotranspiration, snow deposition, the simulation of soil temperature, all require that the interactions with the low atmosphere must be well resolved. The only way I see for doing this is adding a module that solves for turbulence. This work will be pursued in conjunction with Dino Zardi and Michael Dumbser, two outstanding colleagues of my own Department, and Michi Lehning of SLF in Davos and Ecole Politechnique of Lausanne.

There are no previous results on this topic, however, some preliminary work was made.

HydroInformatics for Hydrology

I want to investigate the theory and practice of hydrological modelling under the light of modern software engineering. It is a fact that increased knowledge about processes has not been paired by an adequate development and quality of the software that deploy it in software and models.
Software quality has been overlooked for long time, and has relevant consequences on the daily activity of scientists (not only hydrologists), especially those who use numerical models to interpret experiments,  do forecasts,  and falsify hypotheses
The bad quality of software also causes serious obstacles to the real understanding and independent  analysis of the algorithms used, and makes overwhelming difficult, if not impossible, the replicability and the reproducibility of any result, thus undermining the foundations of the scientific method. 
Beyond the scopes of traditional software engineering, or  making easier cooperative  programming, enhancing the clarity and efficiency of codes, making easier software maintenance, hydroInformatics 
applied to science, must solve the issue related to documentation of algorithms and to develop “design patterns” specific to science and hydrology,  promote replicable and reproducible research


In practice this means to enhance the system that is already at the base of JGrass-NewAGE and individuate design patterns for solver of differential equations compatible with the OMS infrastructure. Eventually this will bring  to a new version of GEOtop, completely interoperable with JGrass-NewAGE, parallelised, well documented, flexible and full of alternative processes description with the aim to increase the small communities working with these softwares. 

Previous work was summarised in Formetta et al., 2014 but also reading Jgrasstools requirements and David et al., 2013 can be useful.  This research will be pursued in tight connection with Olaf David and the ARS/USDA facility in Fort Collins.

Other info

Some topics were removed from here, to give a more sharp idea of what really I want to do. They pertain to my past research and/or to some past period. But they could come back sometimes. Following your own curiosity, you can find them here.

Epilogue

Motivated students are invited to contact me for a possible Ph.D. carrier or post-doc positions.  As general attitude in my research I believe that research must be reproducible, and I require the same discipline to my Ph.D. students and collaborators.

Tuesday, January 18, 2011

An interview (in Italian)

About my Job for high school students. An interview I gave in Italian for the project Scienza Attiva.
As you can notice that day my voice was almost gone ;-(


Friday, January 14, 2011

To my students

I chose this job (well I was also chosen) because I am curious and I like research.  To my collaborators I ask enthusiasm: knowledge will follow enthusiasm and cause serendipity.
Ignacio Rodriguez-Iturbe, one of my three masters,  told me that creativity is better than knowledge: in fact true knowledge originates from creativity. However, I have to warn my students than creativity does not come from natural skills alone, but also from consistent, and intelligent work. In a world of gifted people, is the hard and consistent that makes the difference.

In my scientific activity I realized that one can work alone, but for many objectives it is much better to work cooperatively. Working alone is the exception more than the rule in modern Academia. Bringing to some maturity GEOtopJGrass and JGrass-NewAGE would not have been possible if I had to do it all alone.

In order cooperation really works, I also realized that what I was developing needed to be openly shared, and I choose to go open  for my products (models, slides, research, papers).
As Andrea Antonello told: "the fact is that to be 'open source' does not mean to give away software for free, it is to believe that with some shared rules, many can work together and produce things that, the singles could never do". This also favour Reproducible and Replicable Research, which goes at the core of any scientific work.

Actually this was not really understood by many of my Ph.D students in the past. But now, as time pass by, they are slowly convincing themselves that cooperation can be better and much more productive than competition.

Behave. Nature challenges us already. Understanding nature is our competition.

So:

1 - Like research
2 - Work for creating enthusiasm
3 - Pursue creativity more than erudition
4 - Work hard
5 - Work cooperatively
6 - Go open without hesitation
7 - Struggle for the understanding and not with people

My scientific history in brief

I took a while to understand what I would have liked to do.
When I graduate in Physics on supersimmetries, I knew just one thing: I wanted to change subject. Reasons were many. Among them I felt myself the criticism that is nowadays present in a minority of Physicists (see Lee Smolin's  comment)  who claim that possibly Strings are not the way to obtain the Grand Unified Theory.

After the military service, I had the occasion to gain a grant in Venice, to work with Sandro Marani, a man of unsurpassed visionariness, where I quietly I approached hydrology, by studying river networks  and the way messages (the flood) propagate inside them.
Eventually we produced a paper on the fractal structure of river networks, and, I believe, an interesting contribution on understanding the shape of the hydrograph as formed by the (fractal) geomorphology of the network.

After a few years of wandering I had the occasion to pursue a doctoral degree in hydrodynamics. I worked under the supervision of Andrea Rinaldo, and in strict contact with Ignacio Rodriguez-Iturbe. The main goal was to show the dynamics behind fractals (at least in the case of river networks, and basin's landscapes). Why there were such similarities in the structure of the networks, despite the different geology, and climate conditions ? What was the rational of Horton's laws ? We ended with the Optimal channel networks theory, with some invasion in the terrain of the Self Organizing Criticality. All of this appeared in the book by Ignacio and Andrea: Fractal river networks: chance and self-organization.

Further work, mainly by Andrea Rinaldo, Amos Maritan e Jaynath Banavar has also shown that the topological structures of river networks has parallel in living beings, and possibly a trade-off by minimal energy dissipation and maximization of entropy is governing the network structures.

Collaboration of the first years, include Texas A&M, MIT, and Princeton University.
In late nineties, already assistant professor in Trento (BTW a tenured position), and having spent a couple of years in College Station, Texas, at TAMU, I did not succeeded in getting the Italian equivalent of associate professorship I finally decided to stick with Trento, and directed my work toward which are my main research activities now.

I started to write my notes on hydrology, that I will try to complete in a book sometimes (not yet assembled at the end of 2014), I started the GEOtop project, and, taking the opportunity offered by the Cofinlab 2001 that funded CUDAM, I began the adventure of JGrass.

What pushed me was:

- learning about the "rest of hydrology" that was closely unknown to me;
- learning by doing;
- believing that the best knowledge about hydrology could be captured in numerical models, and through models communicated to people, who could learn by doing and virtual experiments .
- arriving to have tools where the interactions between processes could be studied in their non-linearity;
- having models ready to be coupled with distributed data like those produced by remote sensing.

Well it took a while to arrive to a decent level in all of this.

Eventually, after some financial support by the Basin Authority of River Adige, I also started the JGrass-NewAGE project. In recent years I started a fruitful collaboration with Olaf David of CSU and ARS in Fort Collins, which I visited in summer 2014. I also collaborate on permafrost and snow studies with Stephan Gruber, of Carleton University.


My complete CV can be found here; my past research here; my future foreseen steps here.

Thursday, December 23, 2010

Just For Starting

Dear All,

I started this to make more public the discussion about my research work, papers, and feelings.
To comment ideas I see around, and accept ideas and suggestions from others. Mainly dedicated to my students and collaborators, but wide open to everybody

To understand better who I am, give a look at:

My University website  (but after four years* this blog is more representative of my activities).
My short CV with various links and further information

or at my other stuff:

Publications & Citations:
Tools & models:


But obviously I do not think I will always talk about myself.

Merry Christmas to everybody,
r^2

*Revised dec 18, 2014