Saturday, October 12, 2019

Understanding and Modelling the Earth System with Machine Learning (USMILE) - Synergy

The bad thing about ERC grants (and ERC Synergy grants) is that usually very low information is available about them. Which is quite contradictory, since being those (supposed to be) the best and visionary projects in a certain field, they should be open to the masses who should learn a lot from them. Among the Synergy grants approved just yesterday, there is this one, which is certainly of interest for hydrologists, which aims to focus of new models of the global Earth. Actually somewhere in the press, was mentioned the word hybrid (physics-ML) modelling of observation of Earth system, which means that it is not all about machine learning (this is the ML above) but also the integration of these models with traditional equations solvers.  The colleague who proposed the project are, as you can verify, all brilliant top scientists: Veronika Eyring (a modeller, climatologits, GS ), Markus Rechstein (a biogeo-chemist with modelling abilities, @Reichstein_BGC, GS), Gustau Camps-Vall (head of a signal processing and visualisation group@isp_uv_es, GS) and Pierre Gentine ( Hydrologic Cycle, Land-Atmosphere-interactions, turbulence, convection, soil moisture, looking at the global scale, GS). 

Browsing (click on the GS above), their impressive paper production, one can have an idea of what their project can be, but some particular papers, as this one, recent, in Nature, can be considered as a “proof of concept” of the project, I guess. 

More divulgative material can be found, instead here. Mark Reichstein explain also some of the concepts of using deep learning in the Global Cycle Cycles in Stockholm here.  

Thursday, October 10, 2019

Virtual Reality, Augmented Reality and Mixed Reality in Hydrology and Earth System Science

I did some searches on the web to see if there are application of virtual reality (VR), augmented reality (AR) or mixed reality (MR) (see also here for a tech-magazine type of introduction) around that could be used in hydrology.
On the general issues there are many information on the web, but if you think that reading a book can save a lot of time, this book is Augmented Reality by Dieter Schmalstieg and Tobias Höllerer.
These technologies are largely advertised by the big IT companies (e.g. Google). Incredible user experiences and interactions with data can be seen in the scifi movies we watch daily. Application in Earth Sciences are scarce though. 

To be short for what regards hydrology: I found application in Iowa, in Germany and a group of people that moves around the Virtual Geosciences Conferences (from which I robbed the image) and in general, geologist found simple and direct applications of it. In hydrology just relatively few papers: by Su et al (2008), by Billen et al. , (2018), and those cited below of the Julich Forschungszentrum (JF).
In Iowa there is an active group of hydroinformatics. They have a VR/AR/MR page here and because their involvement in real time flood forecasting, their work is mainly in that direction. In the US there is NOOA that has done some activity, but especially looking to the global planet and the space. NOOA, not surprisingly (?), is more interested in dissemination of results through virtual reality than using virtual reality in supporting Earth Science Research.
In Germany I found a few experiences. One is the group working at "Data Assimilation for Improved Characterization of Fluxes across Compartmental Interfaces” that includes ESA, a few good Universities and research centers. Their site is, however cryptic about results. Their focus is to support data assimilation. The JF plays in it a central role with its models, and they, in fact, have something to show. In fact, browsing Lars Bike website, one can also find some publications (e.g., Yan et al, 2019Rink et al., 2018Rink et al, 2017Helbig et al., 2015, Bilke et al., 2014) that can be useful to read for understanding some directions to go.
To have the very best experiences of the VGS, the best thing is to browse their 2018 proceedings



There is not very much around beyond that, and therefore, I think there is a lot of room to use them in Earth sciences.
From my model builder and user I see exciting the possibility to interact in a more immersive way with input and output of models.
Notwithstanding we are usually looking for the Holy Grail of simplified models, we have to get used to manage and have a supervision of more large data sets, maybe also as a necessary step to get simpler models.
Input data are many and complicate to grasp if the model has to describe complex reality and patterns are not that visible at the first sight since we have to educate our eyes, as any guy using a microscope, or a telescope knows, since the Galileo times.
As a modeler, I would like the data must be visualized and modified promptly for changing simulations behavior. I also dream that the models could be driven by human interaction in real time, changing parameters on the fly copying with the changes the flow of measures impose. Like we were driving a starship.
Obviously this model/data navigation needs to be recorded and re-analyzed afterwards to learn better what has happened (an this further requires tools)
In our field, visual data are usually spatially distributed datasets or graphs and distributed datasets could cover static quantities like the terrain topography, the landscape, or dynamical quantities as soil moisture, temperature, water velocity and, possibly, also some other less trivial quantities like entropy fluxes, water celerity, nutrients concentration.
Brought to the fields those data can be useful to setup measures, tp drive field inspection, “learn by seeing" data and the situation together in an immersive environment, where discrepancy between what expected and what seen can become evident than in traditional situations.
There are non secondary application to education which seems trivial to VR/MR/AR experts, because virtual reality classes seem actually be already available. However if we look carefully, these cover usually very elementary topics and seldom support high education (with exceptions, see Aubert et al, 2015). What I could find is here, and here for example, with incursions ob the psychology of learning here.
Clearly VR/AR could interact also with crowd science initiatives, as has been already envisioned, but could be certainly enhanced.

For the interested there is also a Journal, Virtual Reality, where something interesting about water can be actually found (but I confess I am not able to evaluate how good the journal is).


References

Aubert, A. H., Schnepel, O., Kraft, P., Houska, T., Plesca, I., Orlowski, N., and Breuer, L.: Studienlandschaft Schwingbachtal: an out-door full-scale learning tool newly equipped with augmented reality, Hydrol. Earth Syst. Sci. Discuss., 12, 11591–11611, https://doi.org/10.5194/hessd-12-11591-2015, 2015.
Bilke, L., Fischer, T., Helbig, C. et al. Environ Earth Sci (2014) 72: 3881. https://doi.org/10.1007/s12665-014-3785-5
Billen, M. I., Kreylos, O., Hamann, B., Jadamec, M. A., Kellogg, L. H., Staadt, O., & Sumner, D. Y. (2008). A geoscience perspective on immersive 3D gridded data visualization. Computers & Geosciences, 34(9), 1056–1072. http://doi.org/10.1016/j.cageo.2007.11.009
Kromer, R. (2018). VGC2018, 1–101.
Helbig C, Bilke L, Bauer H-S, Böttinger M, Kolditz O (2015) MEVA - An Interactive Visualization Application for Validation of Multifaceted Meteorological Data with Multiple 3D Devices. PLoS ONE 10(4): e0123811. https://doi.org/10.1371/journal.pone.0123811
Rink, K., Bilke, L., Kolditz, O., (2017) Setting up Virtual Geographic Environments in Unity, in Workshop on Visualisation in Environmental Sciences (EnvirVis), Rink K., Middel A. , Zeckzer D. and Bujack R. Eds., 978-3-03868-040-6
Karsten Rink, Cui Chen, Lars Bilke, Zhenliang Liao, Karsten Rinke, Marieke Frassl, Tianxiang Yue & Olaf Kolditz (2018) Virtual geographic environments for water pollution control, International Journal of Digital Earth, 11:4, 397-407, https://doi.org/10.1080/17538947.2016.1265016
Su, S., Cruz-Neira, C., Habib, E., & Gerndt, A. (2009). Virtual hydrology observatory: an immersive visualization of hydrology modeling. In I. E. McDowall & M. Dolinsky (Eds.), (Vol. 7238, pp. 72380H–9). Presented at the IS&T/SPIE Electronic Imaging, SPIE. http://doi.org/10.1117/12.807177
Yan C., Rink K., Bilke L., Nixdorf E., Yue T., Kolditz O. (2019) Virtual Geographical Environment-Based Environmental Information System for Poyang Lake Basin. In: Yue T. et al. (eds) Chinese Water Systems. Terrestrial Environmental Sciences. Springer, Cham

Wednesday, October 9, 2019

Comments on: Thinking on Optimal Theories in Hydrology

I think the comments made by Christian Massari on yesterday post require some deepening.


He wrote:

C - .. I have some comments from your text….

C - I went trough it and I enjoyed a lot the reading. The patterns like perspective is something that is there, closer to reality than the classical Eulerian approach where objects are divided in elements and physical quantities are attempted to be described for a number of discretized points (with point-based physical laws ) of what you called “shapes”. Is this approach really valid?
R - The question is well posed. To really answer to this, we should be able to build a “statistical mechanics” out of the finer scales to obtain the behavior at the larger scales.
This is, for instance, the case of Richards equation which is, in its essence, mass conservation plus a hypothesis about pore filling and emptying, plus an intrinsic assumption about the randomness of the medium (pore dimensions are connected randomly). These hypotheses leaves behind macropores and preferential flow (I know how to include them, however) but produces a working equation at the Darcy scale. It is less clear for other compartments of the hydrological cycle.
If we have a catchment, the traditional lumped approach is to consider it composed by hydrologic response units (HRUs) that then interacts to get the whole catchment rules (the big picture, often called semi-distributed). To my knowledge, the model Topkapi (Liu and Todini, 2002) are obtained by integration of the smaller scale hydrology, Topmodel (Beven and Kirkby, 1979, Beven and Freer, 2001) is another type of aggregation (related to the production of the runoff by saturation excess), the Geomorphic Instantaneous Unit Hydrograph (GIUH, Rodriguez Iturbe and Valdez, 1979; Rigon et al, 2016) a way to aggregate HRUs using travel time concepts. (I wrote about this here). All of them are types of aggregation of fluxes driven by a scope (getting the saturated area, getting the discharge, a.k.a the hydrologic response) and it is not clear if they can be aggregated when the goal is wider (for instance getting all the fluxes and the energy budget).
Gray (1982) and coworkers, (references later) envisioned a method of integration over space and time to make emerge laws bottom up that were subsequently popularised by the work by Reggiani et al. (1999, 2003). However, their work is based on the naive assumption that the topology of the interactions is irrelevant. Topology of interactions is instead fundamental to get the right fluxes at the large scale and it is explicit (and simplified) in both Richards and GIUH (but, as we said, at the price to let something out). So we should envision a way to built HRUs and make them to interact properly. This is also when known in physics, where the process of aggregation implies the “renormalization” of interactions. Kenneth Wilson got the Nobel prize for getting a clue of it. For renormalization working, however, the system must have certain properties of scale invariance, in which the form of the equation remain invariant but the coefficients change of magnitude. Notably Richards equation is almost scale invariant (e.g Sposito, 1997) and we are now able to verify it numerically. Most of the systems we deal with are, however, not self-similar and equations must change when changing scale.
In this context a guiding principle could be to search for emerging conservation laws (e.g. Baez et al., 2018), from which extract budgets' equations.
At present we can only make hypotheses, and, classically, think HRUs as reservoirs connected by empirical laws of fluxes, whose behavior can be tested in various ways, including the use of tracers. It is the practical trick that many of us use with some satisfaction (maybe the more clear statements about this approach are in the work by Fabrizio Fenicia: see Fenicia et al. (2016) for an example). On this type of models we wrote a paper, yesterday accepted in WRR. In this paper we deal with the representation of the models, but in reality representation methods reveal the assembly of compartmental models and a give clear suggestions on how to obtain travel times equations (the topic of an incoming paper). However the answer to your question is: at present we do not really know.

C - Is the whole system the simple sum of the the parts?
R - I said before, talking about Reggiani et al. that no, this is not the case. The topology of interactions counts.
C - Maybe this is true as we move to the microscopic scale but even at this scale things are organized in shapes (i.e., molecules). So it seems a scale dependent problem. So we have the chance for every system or compartment to use the “right" scale to describe processes and properties as patterns.
R -True
C -At that scale there is an undoubtedly existing organizing/optimality principle that is able to make that shape recognizable and distinguished from the rest, a complex system behaving as whole and having certain relation with the rest.
R -Right

C - You talked about three main processes/systems like turbulence, water flow in vegetation and river network organization but of course we could identify others which are not only related to water movement but also for instance to soil properties, meteo forcing organization (e.g. rainfall and temperature and humidity patterns induced by landscape) and so on…
R -Right

C - This could a be direction we could take for example by looking at pattern like modelling (Grimm et al. 2005).
R - Pattern based dynamics is a successful story that works with individuals interacting by a rule. This is not very much different to our lumped model, except for the fact that these interactions can be at discrete times. However, they are not essentially different. The issue remains to get the law of interaction right (or approximately right). These systems, as we did with systems of ordinary differential equations are representable by Petri nets, on graphs, and topological methods are available to get some clue of their collective behavior.
C - I am honest I am not in the topic so I need to study it but it seems something interesting. How we could join our forces?
Because we do not have the machinery (yet, but probably forever) to perform renormalisations, we need to deduce empirically both the patterns and the fluxes among patterns at the aggregated scale. To this scope smart use of remote sensing is essential. Eventually we could be able to do an operation of reverse engineering and understand how to deduce them from basic (finer scale laws).
We, observers, have the task of identifying these patterns or shapes based on observations (ground and remote sensing) also by unconventional ways (i.e. Clemens), you modelers, will have the task of translating in mathematical ways the the existence of these shapes and patterns as well as the relation between them (which are likely again the results of optimality principles).
R - Right.

References

  • Baez, J. C., Lorand, J., Pollard, B. S., & Sarazola, M. (2018). Biochemical Coupling Through Emergent Conservation Laws. arXiv.org, 1–13.
  • Beven,K., and M. J. Kirkby (1979), A physically based, variable contributing area model of basin hydrology, Hydrol. Sci. Bull.,24, 43-69
  • Beven, K., & Freer, J. (2001). A dynamic TOPMODEL. Hydrological Processes, 15(10), 1993–2011. http://doi.org/10.1002/hyp.252
  • Fenicia, F., Kavetski, D., Savenije, H. H. G., & Pfister, L. (2016). From spatially variable streamflow to distributed hydrological models: Analysis of key modeling decisions. Water Resources Research, 52(2), 954–989. http://doi.org/10.1002/2015WR017398
  • Gray WG. Constitutive theory for vertically averaged equations describing steam-water ̄ow in porous media. Water Resour Res 1982;18(6):1501±1510.
  • Grimm, V., Revilla, E., Berger, U., Jeltsch, F., Mooij, W. M., Railsback, S. F., et al. (2005). Pattern-Oriented Modeling of Agent-Based. Science, 310, 987–992.
  • Z. Liu, E. Todini. Towards a comprehensive physically-based rainfall-runoff model. Hydrology and Earth System Sciences Discussions, European Geosciences Union, 2002, 6 (5), pp.859-881.
  • Reggiani, P., Hassanizadeh, S. M., Sivapalan, M., & Gray, W. G. (1999). A unifying framework for watershed thermodynamics: constitutive relationships. Advances in Water Resources, 23(1), 15–39. http://doi.org/10.1016/S0309-1708(99)00005-6
  • Reggiani, P., & Schellekens, J. (2003). Modelling of hydrological responses: the representative elementary watershed approach as an alternative blueprint for watershed modelling. Hydrological Processes, 17(18), 3785–3789. http://doi.org/10.1002/hyp.5167
  • Rigon, R., Bancheri, M., Formetta, G., & de Lavenne, A. (2015). The geomorphological unit hydrograph from a historical-critical perspective. Earth Surface Processes and Landforms, 41(1), 27–37. http://doi.org/10.1002/esp.3855
  • Rodríguez-Iturbe I, Valdés JB. 1979. The geomorphologic structure of hydrologic response. Water Resources Research 15(6): 1409–1420.
  • Sposito, G. (1997). Scaling Invariance and the Richards Equation (pp. 1–23), in G. Sposito (Ed. Scale dependence and scale invariance in hydrology, Cambridge University Press

Tuesday, October 8, 2019

Thinking on Optimal Theories in Hydrology

In Nature we have to deal with forms that we somewhat recognize and distinguish from the rest (Thom, R., 1975). These forms (shapes), as we know since D'Arcy Thomson (1917, see also Ball, 2013), have functionalities that are shaped by some dynamics that we struggle since then (and maybe before) to find and understand. Because forms and functional forms are so ubiquitous we are brought to think that there is some design to produce them (Zanella,  G. Sopra una conchiglia fossile nel mio studio, About a Fossil shell in my room) but this is from the science point of view an error of perspective (Monod, J., 1970) and an undecidable question. K. Lorenz, on the other side warns often that evolution does not produce always functional forms (or behaviours) but let grow also unnecessary “neutral” stuff which is not useful nor a handicap. The discussion can grow very general and philosophical, and pursuing it could be the topic of another post.
We are interested here to grasp the grow of forms and patterns by means of methods that are proper of mathematics, physics and chemistry (on the illuminating example of E. Schroedinger, What is life ?, 1944). It is to be remarked here that to appeal to hard sciences does not mean a priori a reductionist approach, in which the systems are pruned apart and loose their quality. This is especially true for living systems but also for complex Earth science cycles as the hydrological one, and we aim to keep the systems and their dynamics together, emphasizing the interactions that makes forms to emerge at various scales. 

The general but qualitative understanding of the physics and mathematics related to these problems, is that, deprived of its teleology to be investigated elsewhere and eventually, behind forms and patterns there is some “optimality principle” or, stated in other words, that Newtonian mechanics, physics and chemistry of complex systems evolve solutions that require spatio-temporal structures and patterns. The creation of “forms” is extended not only to the immediately appearance that we perceive with our (highly biased by evolution, though) senses, but are minimal or maximal solutions when observed from the point of view of a certain variable. Unfortunately we are not really able to move, based on the present knowledge, from the basic principles to the appropriate laws of structures interactions, just through derivation of statistical law or integration over degrees of freedom.

The theories of optimality assume among the driving forces moving the dynamics of a system in Nature there are some extensive quantities like, for instance, entropy that are pushed to increase. For instance entropy, because,  entropy of a closed thermodynamic system is shown to grow. In fact this is a principle of Equilibrium Thermodynamics. However,  in Non Equilibrium Thermodynamics  it can be derived, at least  for some simple systems, i.e. is not anymore a principle,  (e.g. see the Thermodynamics derivation of evaporation in Monsoon and Baldocchi, 2014).
Moreover, in open systems, entropy of a subsystem can decrease, so in such context it cannot be used to understand the asymptotic state of the system. Fortunately,  the rate of production of entropy could. As a matter of fact, in non-equilibrium, non-autonomous, open systems, asymptotic states could not be so relevant, and instead what matters are “intermediate asymptotics” as pointed out for fluid dynamics by Barenblatt, 1996 and, before Baranblatt, by Ilya Prigogine work on dissipative structures, i.e. structures that are identified because, they represents steady (or at least somewhat persisting) states of a (thermo)dynamic system out of equilibrium.

It can happen, for instance, that intermediate asymptotics are obtained by minimizing energy dissipation, i.e. the quantity of energy that is transformed into heat (or non-usable energy). This is the case of river networks (Rodriguez-Iturbe et al., 1992) and implies that the maximum entropy of the comprehensive system is obtained as slowly as possible, meaning that the available energy is used at its best for producing work.

This behavior seems logically correct for living systems, and seems justified by evolution and selection: the most efficient survives and reproduces (Virgo, 2001) but is intriguing the fact that river networks are not living systems and anyway they obey such a type law.  Therefore it seems implied that some general dynamic law is the origin of all (e.g. Prigogine, 1945). The mathematical problem is all but trivial, and such minimization (or maximization) problems has received recently the attention of the Field prize (e.g. see the work of Alessio Figalli), but, forgive me if I dare to say that is simpler than the physical problem to understand why certain equations that bring to optimisation problems are valid. Anyway, optimisation problems are mathematically obtained by expressing the large scale dynamics of the (river) networks as a functional to be optimised (actually expressed in Rodriguez-Iturbe et al work in discrete form). In optimal channel network (by Rodriguez-Iturbe et al, 1992), this functional is, obtained by using the basic Newton law (in appropriate form) and some additional hypothesis, derived from observations or educated guesses. One would like to obtain it without heuristics but this seems out of our present possibilities notwithstanding the large literature on optimal transportation networks (e.g Barabasi, Network science, 2018). It should be noted, however, that the case of networks is produced by some twofold optimality: a tradeoff between maintaining an optimal transport and optimally maintaining the the structure that conveys optimally the transported.

An epitome of structure analysis is also the Navier-Stokes equation and turbulence. Here we have the formation of structures that dissipate kinetic energy, the vortexes, actually of all dimension from the scale of observation to the dissipation scale.
We recognize these patterns as preferential flow of energy, or, in the case of turbulence as a form of quasi-random disorganization whose structure is particularly evident in the 4/3 Kolmogorov law. In this case, the equation is directly the Newton law (plus Newton’s hypothesis on stresses), so, despite the complexity of the outcomes, the physics is very directly reduced to mathematics which, BTW, in this case is unable to completely solve the problem.

A third piece of the elephant is the water flow in vegetation. It happens to maintain the temperature of the plant system in a range acceptable for plants to comfortably survive subject to weather and climate forcings and at the same time, not secondarily or maybe primarily, fix $CO_2$ to build their structure and carbohydrates trough photosynthesis. So plants need to optimise their fit to varying weathers for maximizing their production. A plant can be decomposed in its main structural parts: root, steams, leaves and their functional counterparts, xylem and phloem (e.g. Stroock et al., 2014), each part can be disassembled back to the singles cells and chloroplasts. But after the reductionist operation, plants overall functioning remain partially elusive and resistant to quantitative treatment if we do not treat plant’s part as a system (with a lot of osmoregulatory subsystems, e.g. Perri et al., 2019) and ecosystems where plants of various species interacts in competition, cooperation and coopetition for light, water, nitrogen, or phosphorus. The structure of plant and ecosystems and their interactions, evidently does not violate basic physical laws, their functioning respect mass and energy conservation, and momentum (of water, for instance) is peculiarly dissipated to obtain the scope of water supply to very high height and very negative pressures (up to -30 MPa). Optimization here involves various aspects, including the scaling of xylem dimensions (e.g. Olson et al., 2014), to obtain optimal sapping performances. Besides, recent work by Hildebrandt et al. (2016) shows evidence of optimal use of water when the energy budget is properly accounted for.
Soils are not a passive medium, first because themselves contain a lot of aggregated microbic biota (so far mainly neglected in hydrological analyses) and secondly because it is the environment where soil-roots interact. Also in soil, even according to more traditional views, there are optimisation processes when, during evaporation, the rate of water uptake is maintained constant up to critical soil water content (stage I evaporation) after which, evaporation strongly decreases (stage II evaporation). This is provided by a series of feedbacks among small and large soil pores, viscous forces and cohesion processes still not well understood (but kind of well described in Lehman et al., 2008).

Hydrology in the critical zone (CZ, the elephant) is therefore overwhelming difficult because it is the compendium of optimisation processes regulated by networks, vegetation, NS equations and water flowing in soil. According to what we focus on, we can isolate various non trivial dynamics. However the challenge is to model their comprehensive interplay for which still we do not have appropriate mathematics, observations and tools.

Comments following this link

References
  • Ball, Philip (7 February 2013). "In retrospect: On Growth and Form". Nature. 494 (7435): 32–33. doi:10.1038/494032a.
  • Barabási, Albert-László (2018). Network science. Cambridge University Press. ISBN 978-1107076266.
  • Barenblatt, G.I. (1996), Scaling, self-similarity, and intermediate asymptotics, Cambridge University Press, 1996
  • D’Arcy W. Thomson (2017), On growth and forms, Cambridge university Press
  • Hildebrandt, A., Kleidon, A., & Bechmann, M. (2016). A thermodynamic formulation of root water uptake. Hydrology and Earth System Sciences, 20(8), 3441–3454. http://doi.org/10.5194/hess-20-3441-2016
  • Lehmann, P., Assouline, S., & Or, D. (2008). Characteristic lengths affecting evaporative drying of porous media. Physical Review E, 77(5), 354–16. http://doi.org/10.1103/PhysRevE.77.056309
  • Chance and Necessity: An Essay on the Natural Philosophy of Modern Biology by Jacques Monod, New York, Alfred A. Knopf, 1971, ISBN 0-394-46615-2
  • Olson M.E., AnfodilloT., Rosell J.A., Petit G., Crivellaro A., Isnard S., León-Gómez C., Aalvarado CardenasL.O., Castorena M. (2014). Universal hydraulics of the flowering plants: Vessel diameter scales with stem length across angiosperm lineages, habits and climates. Ecology Letters 17 (8), 988–997.
  • Perri, S., Katul, G. G., & Molini, A. (2019). Xylem‐ phloem hydraulic coupling explains multiple osmoregulatory responses to salt‐stress. New Phytologist, nph.16072–51. http://doi.org/10.1111/nph.16072
  • Prigogine, Ilya (1945). "Modération et transformations irréversibles des systèmes ouverts". Bulletin de la Classe des Sciences, Académie Royale de Belgique. 31: 600–606
  • Rodriguez-Iturbe I. , Rinaldo R., R. Rigon, Bras R.L., Marani A. and Ijjasz- Vasquez E.J. (1992), Energy dissipation, runoff production, and the 3-dimensional structure of river basin, Water Resources Research, (28)4, 1095-1103.
  • Schroedinger, E. (1944), What is Life ?, Cambridge University Press
  • Stroock, A. D., Pagay, V. V., Zwieniecki, M. A., & Michele Holbrook, N. (2014). The Physicochemical Hydrodynamics of Vascular Plants. Annu. Rev. Fluid Mech., 46(1), 615–642. http://doi.org/10.1146/annurev-fluid-010313-141411
  • Thom, R. (1975), Structural stability and morphogenesis, An Outline of a General Theory of Models, Addison-Wesley
  • Virgo, N. (2011, March 23). Thermodynamics and structure of Living Systems, Ph.D. dissertation, University of Sussex

Tuesday, October 1, 2019

Discharge predictions on the Netravati River Basins using GEOframe-NewAGE

Giuseppe Formetta (GS) started to collaborate with some Indian colleagues for predicting discharges of Netravati River Basins. He used a modelling solution out of those from GEOframe-NewAGE to get his results and and presented the results at the last meeting of the Italian Hydrological Society held in Bologna. You can see the results of this work in the slides below.

He used CHIRPS data for precipitation and substantially a version of Hymod for any HRU to get runoff. Results are quite interesting.

Sunday, September 22, 2019

A little, non conclusive, reflection on the non-linear evolution of hydrology (and science)

It seems that some science (and our in particular, where isolating experiments is often impossible and we have to deal with complexity and just observations) proceeds upon tradition accepting it passively and without discussion of the mainstream ideas, and there is a large inertia to adopt new views. Legacy to old and even wrong ideas has its own reasons. First they were not completely unreasonable (but people apply also to unreasonable ideas with absolute dedication, which is so diffuse that, I guess is due to some evolutive selection). Then, after a first acceptance by the community, a lot of people adapted their work, calibrated their parameterizations, designed their experiments and push them to the limit before accepting the idea that new paradigms are necessary. I think some reflected on this before (i.e. Kuhn, The Structure of Scientific revolution, 1962)
However, this reflection came to me by a couple of readings: the paper on the 23th problems in hydrology (Bloeschl et al., 2019), which I coauthored with other 200 or so and observing the case of evaporation from capillaries. Let’s start from the latter case.

Some theory was known since 1918 and 1921 with the work of Lucas (1918) and Washburn (1921), e.g. in Ramon and Oron, 2008. For what it seems it has not been used for a century in studies about soil water flows or plants xylem motion despite it could have had some contents to promote. In particular to increase the knowledge in the cohesion-tension theory. Textbooks struggle to find the reasons for which plants can develop depressions so high as -30 MPa (Strook et al., 2014) and, using the statics physics contained in the Young-Laplace law, need to find nanometer interstices in leaves to get this results (even the notable Nobel, 2017, book). These papers failed or, a least, are not convincing me. I believe the cause is purely dynamical and driven by atmospheric demand as those old papers would suggest. Why almost nobody referred to those old papers and argued accordingly ?

The 23th open questions in hydrology, while letting me unsatisfied, brought to me thinking which are the achievements of Hydrology since Green-Ampt (Buckingham, Sherman, Richards), let say the first part of the XX century, to get a perspective. To a superficial reader it could appear that a lot was already there and therefore we did not assist to any “scientific revolution”. It is really clear to me that to really understand it, we should reread the old papers, with appropriate eyes, though. In our paper on IUH (Rigon et al., 2016), we claim that we tend to read old contributions with contemporary view and see in pioneering papers concepts that were not actually there. The list collected by various authors in benchmark papers selections can also be a place were to start. Appropriate analyses has to be done (and interest in History of Hydrology is growing) to fully understand ourselves as contemporary hydrologist.
I have to reflect and read a little more.

References

Tuesday, September 17, 2019

Advances in Richards 2D presentation at the Italian Hydrological Society meeting

The work of Niccolò Tubini is going who already developed a very solid Richards1D (with ponding),  code coupled with the energy budget is proceeding towards a 2D version on unstructured grids coupled, at present with a 1D de Saint-Venant equation. This is the summary of the work done so far given at the Italian Hydrological society meeting in Bologna.

Actually the de Saint-Venant coupling is not yet ready but it will be very soon. Stay tuned. Click on the figure for getting the presentation.

Friday, September 6, 2019

Quantum Computing will change the hydrologists life ?

I struggle for most of my scientific life with computing issues. The main focus was to choose the right language: C over FORTRAN first, then C++ and Java, and finally Java plus Python recently, passing trough various experiences with BASIC, Smalltalk, the Wolfram Language, R).
And with the language a programming paradigm, from old "go to"s to procedural programming, from procedural programming to functional programming and object oriented programming. It has been a long journey a little aside from the main stream of my colleagues, once FORTRANers, now mostly PYTHONers (and MATLABbers though) and it still continues.
However all of this was in the big stream of computer machines working with processors built in a certain way. Since many years from now the focus moved then in parallelizing the codes to serve vectorial chips, multicores processors, and factories of computers sharing tasks (and I confess I remained a little behind in this).

Now, in a decade or so (but I suspect in twenty years) the traditional way of writing algorithms will change: no more bits but Qbits. The era of quantum computing seems just behind the curtain.
To this scope documentation start to be present and remarkably IBM provides some tutorials if you want to start training yourself. You can start from Qiskit by Qiskit.org

Wednesday, September 4, 2019

Stomatal resistance and Transpiration

There are several factor influencing water vapor availability in the leaves’ viscous layer and we can start from the water availability in soil. To get into the root, water of some capillaries must be close to roots. Experimental studies about soil tend to say that flux (to the atmosphere) is sustained at the maximum rate to a critical point of soil suction. Does roots cease to sip water when water is not anymore a connected phase ? Or can roots extract water from vapor ? Or what else ? I do not feel that these questions were answered properly in literature, but I also confess I missed some reading so far of the papers where the coupling soil-roots has been treated explicitly.

The other big topic is the physiological reaction to water scarcity. Plants in fact can close stoma: they are like a tap which is being closed with an effect in literature is known as “stomatal resistance”. It cuts the evaporative flux to oppose to the evaporation demand and the reduction is usually represented as a multiplicative factor, the stomatal conductance (actually the inverse of a resistance) which multiply the driving force, which is given as a different of water vapor concentration between the zone very close to the available liquid water and a zone in the viscous boundary layer (VBL) a little apart, such that:
$$Tr = g_l (c(z_0) - c(z))$$
where $T_r$ is transpiration, $g_l$ the stomatal conductance, $c(z_0)$ is the water vapor concentration close to the leaves surface and $c(z)$ is is the vapor concentration at distance $z$.
There is a variety of plants actions that regulate the stomatal resistance which are summarised in the isohydric and anisohydric behavior (Martinéz-Vilalta and Garcia-Forner, 2016). In the first case, the plant progressively closes the stoma as reaction to water stress to maintain as much as possible a balanced water content. In the other case the plant delays stoma closure in the measure it can resist to manifestation of cavitation and produces in its interior a very uneven water distribution. Actually the stomatal resistance $g_s$ is not the only one affecting plants. Plants have roots and a steam that convey water fluxes and also the flux there is traditionally treated as a viscous flow with some resistance. In that cases though, the driving force is the gradient of water potential or, if we prefer the Nobel (1999) view, of the chemical potential (of which the water potential is a particular expression).
Assuming an almost stationary situation along the root-stem-leaves system, the connection between plants compartments can be manipulated within the electric circuitry analogy (resistances sums to obtain a total resistance, as $g_v = 1/g_r+1/g_s+1/g_l$).
This model allows to obtain the suction in leaves, which, in turn, controls the quantity of water vapor in stomatal cavities.
The resistances are further unknown in the coupled water-energy-momentum system that determines evaporation, heat transfer and the water budget, however $g_l$ has been found to be connected to carbon cycle productivity trough the so called Ball-Berry formula (1987, BB). BB (see also Collatz et al, 1991) has been built out of empirical bases and it was subsequently modified (e.g Verhoef and Egea, 2014) to include physiological reactions and the production of abscisic acid, ABA (Buckley, 2017).
To obtain the final result of transpiration, (besides the determination of roots and stem resistances), there is the further problem of the coupling of stoma with the VBL. Again the tradition assume quasi-stationarity of the fluxes and therefore uses the resistance metaphor, assigning to the VBL a resistance according to an integrated Fick’s law. Also in this case, resistances are summed to obtain the comprehensive flux law that regulates the water ascending.
New questions arise: which is the dominant between the two resistances ? Is the resistance metaphor really applicable ?


A couple of papers, in particular, Manzoni et al., 2013 and Bonan et al. 2014 offer two remarkable points of view of the matter. Manzoni is more interested to processes, equations and general issues with plants hydraulics. Bonan et al. goal is the implementation of a model of the soil-plant-atmosphre continuum and therefore its appendixes can be useful to understand some of the details that can be perceived as ambiguous by the beginners in the field. Bonan's treatment is “traditional” being based on the set of assumptions all literature use which give you back an already well packaged simplification of the physics involved. Manzoni et al. put more emphasis on the biophysical aspects and their connections with plants physiology and use partial differential equations to illustrate the concepts. Both of them have a large list of references and, together with the recent work of Verohef and Egea (2016, VE) and the work of Dewar, 2002, can be a solid start for any study of the subject. VE in particular, compare various approaches to modelling the water stress and discuss their ability to reproduce experimental data. One of its main interest is to clarify if either water content or the water pressure explains better plant’s transpiration behavior. VE approach is very practical, since it does not discuss the rational behind the different approaches but just use and test them. The final verdict that pressure explain more properly: this is not so clear indeed until the end. Apparently the result is counter-intuitive with respect the organization of the paper that starts from empirical observation that transpiration follow a two-stage behavior (similar to the one seen in soils) when actual (daily) relative transpiration is plotted against the water available. Therefore there is no better that read it to get the vision clear.

References
  • Ball, J. T., Woodrow, J. B., & Berry, J. A. (1987). A model predicting stomatal conductance and its contribution to the control of photosynthesis under different environmental conditions. Progress in Photosynthesys Research, 4, 221–224. http://doi.org/10.1007/978-94-017-0519-6_48
  • Bonan, G. B., Williams, M., Fisher, R. A., & Oleson, K. W. (2014). Modeling stomatal conductance in the earth system: linking leaf water-use efficiency and water transport along the soil–plant–atmosphere continuum. Geoscientific Model Development, 7(5), 2193–2222. http://doi.org/10.5194/gmd-7-2193-2014
  • Buckley, T. N. (2017). Modeling Stomatal Conductance. Plant Physiology, 174(2), 572–582. http://doi.org/10.1104/pp.16.01772
  • Collatz, G. J., Ball, J. T., Grivet, C., & Berry, J. A. (1991). Physiological and environmental regulation of stomatal conductance, photosynthesis and transpiration: a model that includes a laminar boundary layer,. Agricultural and Forest Meteorology, 54, 107–136.
  • Dewar, R. C. (2002). The Ball-Berry-Leunning and Trdieu-Davis stomata models: synthesis and extension with a spatially ggregated picture of guard cell function, 25, 1383–1398. http://doi.org/10.1046/j.1365-3040.2002.00909.x
  • Martínez-Vilalta, J., & Garcia-Forner, N. (2016). Water potential regulation, stomatal behaviour and hydraulic transport under drought: deconstructing the iso/anisohydric concept. Plant, Cell and Environment, 40(6), 962–976. http://doi.org/10.1111/pce.12846
  • Manzoni, S., Vico, G., Porporato, A., & Katul, G. (2013). Biological constraints on water transport in the soil-plant-atmosphere system. Advances in Water Resources, 51(C), 292–304. http://doi.org/10.1016/j.advwatres.2012.03.016
  • Nobel, P. (1991). Pysicochemical and environmental plant physiology (pp. 1–637). S.Diego (CA): Academic Press, Inv.
  • Verhoef, A., & Egea, G. (2014). Modeling plant transpiration under limited soil water: Comparison of different plant and soil hydraulic parameterizations and preliminary implications for their use in land surface models. Agricultural and Forest Meteorology, 191, 22–32. http://doi.org/10.1016/j.agrformet.2014.02.009

Tuesday, September 3, 2019

FOSS4G Bucharest 2019

In FOSS4G FOSS stands for Free and Open Source Software 4G for Geospatial. It is a great association that since fifteen years promotes open source spatial tools. It is the arena were great tools like GRASS, QGIS, GvSIG, Gdal, and our Horton Machine found the place to tell about their potential. It is a group of friends that meet every year with enthusiasm to compare their achievements and their perspective.  This here FOSS4G was in Bucharest, and the great news is that many of the talks were recorded and are now available for browsing. You can find them by clicking on the Figure below.
I includes the talk by Andrea Antonello about the new version of GEOpaparazzi working on Android and IOS !

Friday, August 30, 2019

Using colors in science and color blindness

Recently we send to reviewers a paper dealing with graphs. After the first revision we realised that we should have paid some attention to the colors we use, especially because they are meant to convey information (a lot of) to any reader. One over eight people is known to suffer of some color-blind limitation and therefore it is worth to made efforts to get color-blind friendly palettes of colors (yes, it is not just a question of percentages).

This topic has been addressed in various papers Wong [2011]; Johnson and Hertig [2014]; Keene [2015]; Stauffer et al. [2015]; Nuez et al. [2018] and we refer to those papers for the main issues in making a good choice of colors. There are various colorblind types, the three more diffuse ones ;being: protanopia, deuteranopia, or tritanopia Wong [2011] and we have tried to to understand how these people perceive our graphics.
As Rudis et al. [2018] says graphs and drawing must be ”spanning as wide a palette as possible so as to make differences easy to see, perceptually uniform, meaning that values close to each other have similar-appearing colors and values far away ;from each other have more different-appearing colors, consistently across the range of values; robust to colorblindness, so that the above properties hold true for people with common forms of colorblindness, as well as in grey scale printing ..”,
To understand how colors appear to color-blind people, or to our dog, we can use the information in other website, for instance the one by Martin Krizywinsky.
But I suppose you want to use some desktop based software to do your representations. We have a little choice here. I used the web-based software by David Nichols, which can be found here. R-software users can use the VIRIDIS package but also observe that the popular ggplot2 has its own dedicated palettes. I also know for experience that Python matplotlib already does concerned default choices in this field, as apparent from the central figure of this post. Java programmers can browse Contrast-Finder. Finally if you wants just to do-it-yourself, you can read this stack-overflow thread.
If you are interested to maps, you can give a look here.

Now you cannot escape the necessity to do colorblind friendly drawings.

References

Friday, August 23, 2019

What to keep in mind for a Ph.D. interview

We finished yesterday our interviews for selecting the new cohort of PhD students. (In our system we have a call a year, where we select and enroll all the students). So, I am in the best condition to do some comments and give some advise to future applicants. 

The first observation is that we where there to select the “best students” and therefore we were trying to put the applicants in comfortable conditions. * What we did was to ask the applicants to describe themselves and their research proposal and made some questions about their topic. Nothing apparently special.

In front of us we had people of very different ages and maturity: from 24 to 46 years old. People with different motivations and from different countries and continents. And we did not pretended from them the same attitude and skills.  In the younger, we were requiring enthusiasm, an outstanding CV in the studies they had, but we were less demanding on  pretending from them a comprehensive knowledge of literature. In the older we were more tight on analyzing their specific skills and in try to understand if they could complete, and at which level, the tasks implicit in doctoral studies after years spent out of Academia.
To the older, besides having done something, even in the different fields, we were requiring to demonstrate flexibility and attitude to work in group. We were in fact looking for mature personalities (both in the young and the old actually) but, at the same time, trying to avoid those who could not interact positively with the environment they will eventually stick for the future three/four years. 

Concept One: we search for the best fit. In all of our candidate we were looking for appropriate competence and proactivity: but this was a prerequisite. Be sure: excluding some very rare cases which are apparent, for their evident unicity, "we are all equidistant from Nobel prizes" performances. Therefore there are “best” applicants but, among the best, "best fit” applicants. Above all if we think that science is more a team work than matter for lonely nerds.

Concept two: how do you fit and do you really want to fit ? As I told, the applicant who gets the position, eventually has to stick with the environment around and deal with a supervisor. Therefore a suggestion I feel to give is: it is not forbidden to contact your potential supervisor in advance. This does not imply any commitment by anybody but allows to understand better each other. This can also  be functional  to build a successful research proposal, or to understand if you can (or want) fit with that guy without be driven crazy later.  Ph.D. studies are demanding for themselves and especially in a competitive environment as our University can be. Maybe, at the end of your conversation, you do not exactly want to do it. However, there is a chance that you love it. Then, go ahed. Ph.D. can be one of the best periods of your life. 

Concept three: professors pretend to know where their sub-discipline is going and what is best looking for. So, please, do not try to challenge too much their beliefs (see also point 1 and 2). 
Instead you can try to understand if their scientific methods combine with yours, and, in case, how you could interpret their work with your skills. 
As I wrote elsewhere, do not come to me pretending me to be your butler. A good professor can  recognize to be wrong but you will be his/her PhD student and s/he is pretending to suggest the way to go along with you on top of her/his experience and dictating, at least at the beginning, the methods to use. It can be matter of discussion though (that's what PhD work is made of).  However, you have to convince him/her politely that a new perspective is better  before s/he changes her/his.  Besides, keep in mind that a good professor can estimate the effort, pain and costs to pursue the  goal you suggest and pay attention to what s/he says about.

A checklist. Going to the matter, we pretend you:
  • to show solid backgrounds (not necessarily erudition) and attitude to learn
  • having an appropriate knowledge of the literature of the subject on which you want to work on;
  • know what your professor does in his research, which tools he uses and so on;
  • show to be able to express "research questions”;
  • show that you that you can be "focused" and can obtain what is needed (papers, softwares, procedures, patents etc) in limited amount of time (three/four years)
Keep in mind that true research is not an application of some tool but is to delineated new challenges first and solve them eventually. Who is not able to understand what a scientific problem is, cannot be a successful researcher and not even a good Ph.D student. 

Finally:
  • be open to acquire and investigate new tools (during your research life, you will be required to evolve them several times) 

Thursday, August 8, 2019

JSWMM essentials

Interest around urban hydrology has been growing steadily during the last years, and recently had the opportunity to be published in large diffusion scientific journals as Nature. For years the mainstream hydrology has mostly dedicated its attention to "natural" catchments, while considering of secondary importance what happens in cities. Now that most of the people live in cities, and humans are clearly a global agent that affects climate and the whole Earth System, urban hydrology start to be seen under a different light. How works hydrology in cities ? And, for my own interests, how to model and eventually design cities' hydrology ?

My starting point is that good tools developed for generic hydrology should work also for cities. However, over the years some tools specialised for cities and captured the attention of the community of researchers that dedicated to it. Among those is EPA SWMM v5.1.
Actually, EPA SWMM is a rainfall-runoff model but its developer added tools for treating cities specifics, excluding,  a real system for designing storm water networks, a.k.a. pluvial sewers.
With the Master Thesis by Daniele Dalla Torre faced this issue to add to SWMM a designing tool, based on a simplified geomorphic unit based approach. In the meanwhile he found reasonable to port most of SWMM to Java and to embed it in OMS v3. Therefore SWMM became JSWMM and it is available at the GEOframe repository JSWMM inherit everything from SWMM and its i/o files can be run as they are in SWMM. JSWMM clone of SWMM has some evolutionary advantage with respect to SWMM (a part from the designing module which is not existing in the original). Inside JSWMM, in fact, any draining area is processed in parallel from the others, using the Net3 algorithms and this parallelism is made without any intervention of the user. Besides, in future, any appropriate module from GEOframe, could be used to estimate the desired element of the hydrological cycle. Including Richards-1d for infiltration or the coming soon 2D de Saint-Venant module.

No manual is actually ready but the draft of his master thesis (in English) can be used to understand JSWMM internals and his dissertation presentation can be used for the same scope.

Material (to be uploaded soon)

Tuesday, July 16, 2019

Snow, Ice and Permafrost

On Friday 19, 2019, there will be an event the event "climb for climate". I will be representing the University of Trento and give a short divulgative talk. The result can be found here below.
There I briefly summarise three of the topics related on the cryosphere on which I and my colleague Alberto Bellin (GS) and our group did something.  Snow, glaciers and permafrost, not only are hydrological topics, they are certainly among the most fascinating ones.

Thursday, June 27, 2019

GEOframe Winter School 2020 - It is time to apply !


The second edition on the Winter School on GEOframe will be held between January 8 and 17, 2020 in Trento, Italy.  The course is devoted to Ph.D. Students, Post-docs, Young researchers (and Professionals!) interested in estimating all the components of the hydrological cycle (rainfall, evapotranspiration, snow-melting, and river discharge).  The system they will learn allows to work out very small catchments and continental basins as well (e.g. Abera et al., 2017a,b) up to build operational solutions as the one used in in Basilicata.

The aim of the course is to enable participants to run their own simulations and eventually on their own catchments and estimate the hydrological budget components.
With respect to the 2019 Winter School, there will be more practice and more detailed work on evapotranspiration and rainfall-runoff. It will be much more focused on exercises and on getting the water budget performed under various hypotheses on models' structure.


The provisional topics will be:

Teachers will be:

Prof. Riccardo Rigon, Ph.D.
Prof. Giuseppe Formetta, Ph.D.
Marialaura Bancheri, Ph.D.
Michele Bottazzi, Ph.D. candidate
Niccolò Tubini, Ph.D. student
Daniele Dalla Torre, research assistant

The provisional topics will be:

  • January 8 -   Installation and introduction to the Object Modelling System Infrastructure and Jupyter
  • January 9 -   Interpolation of hydrometeorological datasets and elements of parameters calibration with LUCA and particle swarm tools
  • January 10 - Hydrologic Response Units delineation and treatment of spatial features.
  • January 13 - Estimation of evaporation and transpiration 
  • January 14 - Rainfall-Runoff I - Representation of semidistributed models with the Extended Petri Nets. The embedded reservoir (ERM -see also here) and other available models. Discussing  inputs data to models and modelling solutions. 
  • January 15 - Rainfall-Runoff - II  - How Net3 works (see also here). Preparing the topology and the simulation files.  Connecting and disconnecting components. Running modelling solutions. 
  • January 16 - Rainfall-Runoff - III Calibration issues, multisite calibrations and first results production
  • January 17 - Results production and presentation.   Hints for estimating travel times. Crowd-based-hydrology.
To have an idea of the topics, the interested researchers should give look at the material (slides, video etc. of the 2019 Winter School).  The material of the first three days remains very similar (but refined) to the old one. Therefore, for students is possible also to participate only to the second week (at the same cost, but saving some lodging) but, in that case, is mandatory to follow the on-line courses and tutorials  relative of 8-9-10 January topics and having done the exercises before December 15. We will offer prompt online support to them up to that date and no support whatsoever on the same topics later or  between 13-17 of January for clear reasons of course efficiency and organisation.  The refined material of the first three days will be available on the Winter School website  from November 15, 2019.

With respect to the 2019 School, there will be more practice and more detailed material on Evapotranspiration and Rainfall-Runoff. For every 40 minutes of talk there will be 70 minutes of supervised exercise for a total of 8 hour a day of activities. 

Cost of the School is 350 Euros for who will subscribe before November 15, 400 Euros for others. A discount of 20 Euros is granted to fellows of the Italian Hydrological Society (subscriptions for students are available at the IHS-SII site for 10 Euros to students and 20 to seniors). Who attended the last year school can participate free of charge, upon subscription. Inclusive of the costs will be coffee breaks and lunch at the Cafeteria of Department of Civil, and one social dinner for all the schoolmates Environmental and Mechanical Engineering. 

Website for the enrollment go here (To be active from October 15 2019).

For any further information, please fill free to contact me at riccardo.rigon <at> unitn.it

Thursday, June 13, 2019

Some new Ph.D. positions

The new call for the 2019 doctoral position is out. I am interested in topic "D1/D2 - Agricultural, Environmental and hydro-meteorological sciences and engineering”. There are a few available doctoral grants which will be given to a selection of applicants, according to the rule specified in the call. I am interested in students who wants actively collaborate to the WATZON Prin Project. So please peruse the WATZONE project's pages to write your personal  project which the appllication requires.


Overview of the state of art of our topic

Plants water-use strategies are driven by plant functional traits (PFT) (examples are leaf size, toughness and longevity, seed size and dispersal mode, canopy height and structure, capacity for nitrogen fixation) (Mitchell et al., 2008) and in recent years, plant-physiology studies provided an increasingly detailed knowledge of plants behaviour (Schymanski and Or, 2017), but only some of them started to be inserted in ecohydrological models (e.g. Fatichi et al., 2016). Models simulating plant-hydraulic processes are still rare and confined to specific studies (Hölä et al., 2009; Mackay et al., 2015; Nikinmaa et al., 2014). Other studies account explicitly for topographic attributes and lateral water and mass exchanges (Ivanov et al., 2008; Shen et al., 2013; Tague et al., 2013), but their treatment of plant processes is often oversimplified (Zhou et al., 2013). In mountain terrain, even the effect of plot-scale (0.01-0.1 km2) spatial variability of the energy fluxes is still largely not understood (Rollinson and Kaye, 2015) notwithstanding pioneering stud- ies which account for various feedbacks are available, which show that vegetation productivity and water use do not change linearly through spatial gradients (Niedrist et al., 2016).
Research questions addressed
  1.  How specific plant water-use strategies can be implemented in hydrological models ?,
  2. Which is the relative role of biotic (PFT) versus abiotic (soils, topography, climate) processes in determining the spatial and temporal variability of ET and soil water?
  3.  Which is the right level of complexity necessary in models to upscale R3 results from plants to catchments?
  4. How to take advantage of a combination of advanced multi-sensor, multiscale observations to constrain eco-hydrological models and improve their spatial accuracy?
  5. How to leverage recent theories of transport to implement the solutes dynamics in plants ?

Other information

The candidate will take care of implementing, besides the code, the appropriate procedures for continuous integration of the evolving source code, and s/he will be also asked to maintain a regular rate of commits to the common open platform. Despite these conditions, and being free and open source, the code will be intellectual property by the coder. This will be guaranteed also by the components-based infrastructure offered by OMS3, which allows to better define the contributions of anyone.
The implementation part will be followed, accompanied by testing activities, either for mathematical consistency, and for physical consistency with experiments and field measurements.
The Ph.D. student is intended to produce, besides working and tested codes, also at least three papers in major journals (VQR Class A), of which, at least one as first Author.
All the code developed will be done in Github (or similar platform), inside the GEOframe community and will be Open Source according to the GPL v3 license.

The candidate will take care of implementing, besides the code, the appropriate procedures for continuous integration of the evolving source code, and s/he will be also asked to maintain a regular rate of commits to the common open platform. Despite these conditions, and being free and open source, the code will be intellectual property by the coder. This will be guaranteed also by the components-based infrastructure offered by OMS3, which allows to better define the contributions of anyone.The implementation part will be followed, accompanied by testing activities, either for mathematical consistency, than for physical consistency with experiments and field measurements.The Ph.D. student is intended to produce, besides working and tested codes, also at least three papers in major journals (VQR Class A), of which, at least one as first Author. Duration of the doctoral studies is three years.

Further information of the policies of the research group can be found:
P.S. - I am also considering:
  • Applicants who wants to apply to build the new GEOtop snow model but with attention to forest-snow interactions.
  • Who wants to work on the infrastructure of the OMS3, GEOframe systems.
  • Who wants to exploit the capabilities of the GEOframe system to pursue the modelling of the river Adige (and/or other rivers in the world), including human infrastructures.

The WATZON project

We had financed (small financial support indeed) a PRIN project called WATZON (WATer mixing in the critical ZONe: observations and predictions under environmental changes). It was reborn on the ashes of the Water MIX and PRECISE projects and its short description is:

"Sustainable land and water resources management is inextricably linked to a detailed knowledge of water availability in the critical zone (CZ), which is the thin outer layer of the Earth extending from the top of the tree canopy to the bottom of water aquifers, and that controls water quality and quantity, sustaining human activity. The CZ is experiencing ever-increasing pressure due to growth in human population and water demands, and changing climatic conditions. Understanding, predicting and managing intensification of water use and associated economic services in the CZ, while mitigating and adapting to rapid climate change and biodiversity decline, is now one of the most pressing societal challenges of the 21st century. Vegetation is a fundamental element of the CZ, as connects water from different storages in the subsurface zone with water in the lower atmosphere, therefore regulating water fluxes among different compartments of the CZ. Several studies in the last years have examined water mixing processes in the soil-vegetation-atmosphere system. However, because of the large spatio-temporal variability of subsurface water movement and the capability of plants to access water from both deep and shallow sources, and the resulting highly-complex feedbacks in water exchanges between vegetation and other ecohydrological compartments, fundamental scientific questions on the effect of vegetation on the hydrological cycle, especially under different climatic forcing and land-use conditions, remain unanswered.
The main objective of the project WATZON (WATer mixing in the critical ZONe: observations and predictions under environmental changes) is to advance the understanding of water mixing in the CZ by investigating ecohydrological processes of water exchange between vegetation and surface and subsurface water compartments.

Specifically, the project aims at:
  1. assessing the description of water mixing process across the CZ by using integrated high-resolution isotopic, geophysical and hydrometeorological measurements from point to catchment scale, under different physiographic conditions and climate forcing;
  2. testing water exchange mechanisms between subsurface reservoirs and vegetation, and to assess ecohydrological dynamics in different environments by coupling the high-resolution data set from different CZ study sites of the project consortium with advanced ecohydrological models at multiple spatial scales;
  3. developing a process-based conceptual framework of ecohydrological processes in the CZ to translate scientific knowledge into evidence to support policy and management decisions concerning water and land use in forested and agricultural ecosystems.

The project objectives will be achieved by integrating different methodological tools, such as environmental tracers (isotopes of hydrogen and oxygen), advanced geophysical measurements and detailed ecohydrological models, to develop an interdisciplinary and holistic comprehension of ecohydrological dynamics under different climatic forcing and land use conditions. 
The project will create a new network of study sites in Italy (Critical Zone study sites) representative for different climatic, physiographic and vegetation conditions in the Mediterranean area, including grassland, forested and agricultural ecosystems. High-resolution and detailed experimental data and observations will be collected in a consistent way across all study sites in order to identify water pools potentially involved in ecohydrological water exchanges and fine-study root water uptake dynamics. The high-quality data collected in the field and the experimental results will serve as a basis to implement and apply new-generation, robust, reliable and realistic ecohydrological models aiming at assessing water mixing and exchange mechanisms between subsurface reservoirs, vegetation and atmosphere at the root-plant scale and the stand and catchment scale. Models will be used also to develop scenario-based projections for assessing the impact of land-use change on ecosystem services under different climatic and environmental conditions. 
In addition to the foreseen significant advancement of scientific research on water mixing processes in the CZ, the other main impact of WATZON will regard the communication with stakeholders and interaction with the civil society. Involvement of the most relevant stakeholders (e.g., water agencies, river basin authorities, reclamation and irrigation districts, government agencies for forest management and protection, national parks, municipalities and regional councils) will allow to translate the acquired scientific knowledge into practices to support effective and sustainable land and water resources management across a variety of climate and physiographic settings.

Our specific efforts, in which I will work with Giacomo Bertoldi (GS) and Giuseppe Formetta will be using the Mastch-Mazia Valley measurements made by EURAC and improve its dataset and, at the same time, lead WP3 of the project: Testing water mixing mechanisms through ecohydrological modelling 

WP3 will use data and experimental results provided by the activities  to test, implement and apply robust, reliable and realistic (R3) ecohydrological models aiming at assessing water mixing and exchange mechanisms between surface, subsurface reservoirs, vegetation and atmosphere within the CROSSes. Particularly, the models will be applied at three main scales: i) the scale of the roots-stems-leaves apparatus, to analyse vegetation water uptake dynamics and their possible switches over time; ii) the stand and iii) catchment scale, to examine how plant water use affects streamflow generation within different ecohydrological regimes. The starting set of models for the project is composed by GEOtop-dv, JGrass-NewAge (JN), now called GEOframe.

Task 3.1.This task will model ecohydrological processes. Soil water flow will be modelled through 3D Richards equation, with improved parameterizations of soil water retention curves, hydraulic conductivity and treatments of hydraulic conductivity. Interaction between water and roots will be implemented. New schemes of plants hydraulics will be implemented to obtain the partition between evaporation and transpiration. Energy and the carbon budget will be modeled to properly constraint the transpiration production. Tools for accounting for water age, and tracers concentration, will be coupled to the new modules of GEOtop and GEOframe. New gridding and numerics will be devised to mimic the experiments and measurements domains.

Task 3.2. This task will couple field data and ecohydrological models at the root-stem-plant volume scale. Along with the 3D simulations, 1D models will be used. Fluxes will be analysed both in time domain and estimating residence and travel time to cope with tracers at integrated soil-plant scale. These results will be compared with those identified by isotope data and geophysical measurements in project's catchments.

Task 3.3. This task will couple field data and ecohydrological models at the stand and catchment scale. New models of plants communities functioning based on plant functional traits and optimality principles will be introduced, along with the more mechanistic ones. The model results will be compared in CRitical zOne Study Sites –(CROSSes) 2, 4, 5 and 6 against isotope data.

WP3 provide the following deliverables.
  • Deliverable 3.1: New improved components of the models GEOtop and GEOframe and their documentation at the end of each project’s year (version +1,+2,+3).
  • Deliverable 3.2: Case studies will be provided for all the experimental sites, using the various versions of the model components. All the material for the simulation will be provided to the research community online by Open Science Framework.