Friday, August 19, 2016

Estimating the water budget components and their variability in a Pre-Alpine basin with JGrass-NewAGE

This paper shows the estimation of whole water budget in a 100 hundred square kilometers catchment of the Prealps, the Posina catchment.  The challenge here is to close the water budget with a coarse-grained model. The basin has alla the complexeties such a basin can have, and snow has to be taken into accounts.
Input data available are discharges measured in several gauges and hydrometeorological data measured in twelve meteo stations. However, evapotranspiration is not explicitly measured, neither are the water table levels.

The paper starts with treatign carefully the water inputs, and, chosing Kriging as a method for interpolation, detailed how to do it with the new tools offered by Jgrass-NewAGE (all the posts here).  It also discusses the separation of precipitation in snow and rainfall, and illustrates a way to do it by using MODIS data. Closing the water budget further requires some trick for separating water storage in soils and evapotranspiration. The paper devises a method for doing it, in assuming that the water storage is nullified after an appropriate set of years, called Budyko's time. The final outcomes is a reasonable estimate of any of teh components of the hydrological cycle at various time scale, and spatially distributed according to a partition of the catchments in hydrologic response units (HRU), as those depicted in the figure above. In any case, you can have the details of the story by reading the paper itself, by clicking on the figure or here.
Information related to this paper can also be found in the post dedicated to Abera's Ph.D. defense.
The preprint has been submitted to Advances in Water Resources.

Thursday, August 18, 2016

Reservoirology

The current idea in many modern modelling systems (at catchment scale) is that the hydrology of control volumes can be reduced to a set of interconnected reservoirs (Fenicia et al., 2008; Tague et al., 2010; Clark et al., 2008; Hrachowitz et al., 2013). Each one of these reservoir can be thought as “well mixed”, meaning that each water reservoir acts like a chemical reactor where all what comes in is uniformly distributed across the reservoir and perfectly mixes (and instantaneously too) with everything already present. Some of these reservoirs have a geographical identification (as happened in the geomorphologic unit hydrograph, eg. Rinaldo and Rodriguez-Iturbe, 1996), some others have a functional reason and we could call them “embedded”, or with no-geographical reference. They are used especially to disentangle processes, to attribute the right travel time to water, and, more prosaically, to get right quantitative adjustements to the various outputs, discharge, first of all. 

This way of working is quite necessary (but remind Todini’s adage: first they had a linear reservoir -Sherman, 1932 -, then they introduced a sequence of linear reservoirs - Nash, 1957, after, they made the reservoirs non linear, Dooge, 1959; finally was a mess, Sagawara, 1967) but the separation (or the composition, it depends from the point of view) of the domain in parts is somewhat that remains to be demonstrated.

In using these simplifications  nobody of the researchers mentioned goes through a direct simplification of coupled (hydrological) equations at the finer scale and coarse grain them^1, but directly adopts the paradigm of reservoirs and validate it, nowadays technologically, by using a set of GOFs (goodness of fit) indicators. 

This system is, IMO, intrinsically weak but I, like the others, adopted it. A statistical theory is missing, and I believe that it will arise from the travel time theories

In the revamp of  these reservoirs' theories, the attention to the spatial distribution of the reservoirs should find again its place. Distinguishing, “vertically”, reservoirs as canopy, surface, vadose zone and groundwater storage is a necessity that is widely recognised and should be deployed. Reservoirs “lateral” aggregation (by using convolutions or following new paradigms) is the follow up (see also Rigon et al., 2016a). Embedded chains of reservoirs should be also necessary, as invoked by those who study small catchments experimentally (e.g. Birkel, 2011). All should be investigated carefully, and complexity added after implementing “ad hoc” experiments, or using appropriate datasets. 

This scenery would not be complete if these models would limit themselves to consider just the forecasting of discharges. They should also convey a reasonable set of processes to close the water budget. Next would be to include appropriate simplifications of the energy budget, a necessary companion. The latter, however, was never tried so far in coarse grained models.

Notes

^1 Perhaps Paolo Reggiani et al, 1998 tried it in a generic way, making experience on Gray’s previous work, and Todini did it, his own way with Topkapy, i.e. Liu and Todini, 2002; see also Todini, 2007 and my talk here. Paolo's work is certainly to be reconsidered.

References

Birkel, C., Soulsby, C., & Tetzlaff, D. (2014). Developing a consistent process-based conceptualization of catchment functioning using measurements of internal state variables. Water Resources Research, 50(4), 3481–3501. http://doi.org/10.1002/2013WR014925

Clark, M. P., A. G. Slater, D. E. Rupp, R. A. Woods, J. A. Vrugt, H. V. Gupta, T. Wagener, and L. E. Hay (2008), Framework for Understanding Structural Errors (FUSE): A modular framework to diagnose differences between hydrological models, Water Resour. Res., 44, W00B02, doi:10.1029/2007WR006735.

Dooge J,  (1959) - This reference was suggested by Ezio Todini, but I did not find it (the one talking of non-linear reservoirs).

Fenicia F, Savenije HHG, Matgen P, Pfister L, 2008. Understanding catchment behavior through stepwise model concept improvement. Water Resour. Res. 44(1): W01402. ISSN 0043-1397. doi:10.1029/2006WR005563. 

Gray, W., Lijennse, A, Kolar, R.L, Blain, C.A., Mathematical tools for changing spatial scales in the analysis of physical systems, CRC Press, Boca Raton, 1994

Hrachowitz, M., Savenije, H., Bogaard, T. A., Tetzlaff, D., & Soulsby, C. (2013). What can flux tracking teach us about water age distribution patterns and their temporal dynamics? Hydrology and Earth System Sciences, 17(2), 533–564. http://doi.org/10.5194/hess-17-533-2013

Liu and Todini (2002), Towards a comprehensive physically-based rainfall-runoff model, Hydrology and Earth System Sciences, 6(5), 859–881

Nash, J.E., 1958, The form of the instantaneous unit hydrograph, IUGG General Assembly of Toronto, Vol III, IAHS pub. no. 45, 1141-121. 

Reggiani, P., M. Sivapalan, and S. M. Hassanizadeh (1998), A unifying

Rinaldo A & Rodríguez-Iturbe I, 1996. Geomorphological theory of the hydrological response. Hydrol. Process. 10(6): 803–829. ISSN 1099-1085. doi:10.1002/(SICI)1099- 1085(199606)10:6<803::AID-HYP373>3.0.CO;2-N. 

Rigon R., Bancheri M., Formetta G., & de Lavenne, A. (2015). The geomorphological unit hydrograph from a historical-critical perspective. Earth Surface Processes and Landforms, n/a–n/a. http://doi.org/10.1002/esp.3855

Rigon R., Bancheri M, Green T., Age-ranked hydrological budgets and a travel time description of catchment hydrology,Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-210, in review, 2016.

Sherman, L. K., Streamflow from rainfall by the unit hydrograph method, Eng. News-Record 108, 501-505, 1932. 

Sugawara, 1967, The flood forecasting by a seried storage type model, IAHS Publication no. 85, 1-6

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


Todini, E. (2007). Hydrological catchment modelling: past, present and future. Hess, 11(1), 468–482.

Sunday, August 7, 2016

Sparse thoughts (on the foundations of a Thermodynamics of Hydrological Systems)

Assume you have a control section in which you include a natural landscape. Fluxes of energy and mass across the boundary of the control volume are more or less understood. What is not understood is the arrangement these fluxes can have inside the control volume, and how to describe their complexity (would be entropy their measure ?).

Make this conceptual experiment. Think that inside the volume there is only a bare soil (it is in itself an extraordinary simplification to think that soil is simple), and think another system where you have grass growing on the soil.   Make it simpler ! Just have a substance inside the control volume, and air (which is still very complicate because of turbulence).

The problem at this level is primarily descriptive. How to describe the content of the control volume ?

According to physics, we have (1) to define the way the internal stuff interacts with the incoming fluxes (of mass, momentum and energy) (2) understanding or making some assumption on the stability and form of what is inside.

Stability has certainly to do with the phase of the system, which assumes that the matter has a certain organisation. We have a weak knowledge of it. We are used to specify the organisation  as phases of matter, but how in physics (chemistry ?, biology ?)  can be described complex patterns of organisation is not clear.

Without any doubt, we have to add the complex concepts of temperature of the system, its pressure, its volume, its chemical potential and how to fluxes reorganise what is inside.
It is also certainly true that form counts and we have to distinguish  surfaces of separation between substances.  Even if we are talking of inhanimated substances, so far. 

But, if we intoduce or growing systems (that can be still inhanimated), this become more and more complicate, if we introduce self-reproducing systems (life ?) the path of knowledge becomes even more steep and challenging.

Is this way of thinking reductionism ? It could be, but it is not. 

Antireductionists claim that a system is more than its parts, formally this is like to say that 1+1 \neq 2 and seems a nonsense. For me this means that  a system is its parts plus the interactions that the parts can establish between themselves and the outer boundaries. 

That's kind of elementary mathematics that connections between points grow more than exponentially and the number of interactions grow equally likely, such that a small brain has as many connections comparable to the whole number of protons in the known universe.

So one quality of the system, besides the matter it is composed of, is given by the number of interactions that it is composed on.

Even if we limit our arguments to inanimate matter, these interactions are usually not computable, and this make the system unknowable, and destroys, in my view, the naive idea that I am a reductionist.

Anyway, out of philosophy, and parachuting us back to earth, this needs that we need something new to describe interactions among parts. Being a hydrologist, I would be interested in knowing how to approach organisation in hydrological system.

Further reading: this post on Information theory, this post on Thermodynamics, this post on "What is life" (and my professorship talk), graph theories. Ruddel's papers. Kleindon book. Azimuth's posts.



Wednesday, August 3, 2016

Is Navier-Stokes equation enough ?

This is just a place holder at the moment, to be better developed in future. The question is to generalize the Navier-Stokes (NS) equation in presence of gradient of temperature and the triggering of convection, an topic I am interested in for understanding how evapotraspiration works.

The standard view of the phenomenon is that NS is enough, and it is sufficient to couple it with the energy budget. An equation of state connecting density and temperature is necessary to close the set of equations. 

This understanding correspond to the perceptual model that air is heated "slowly" without creating motion, and subsequently differences in density trigger the convection. 

However, for what I know, it could not be like this. According to Onsager theories, there should be air movements triggered directly by temperature gradients.  Mass fluxes, I mean. Therefore, which is the dominant process at the beginning of the convection (i.e. the density gradient or the the temperature gradient) could be a question of scale. I think it could be an interesting issue to investigate, theoretically, numerically, and experimentally.  If some reader knows literature on the subject, s/he can freely put a comment.

Wednesday, July 20, 2016

OMS Summer School 2016 - What we actually did

This is what we actually did at the Summer School on OMS3. Here you will find slides and material (actually, it is already presented in the Colorado State University site), but I will document here a little more. (Still a work in progress)

Instructors

Wuletawu Abera (University of Trento, Italy)
Olaf David (Colorado State University, Fort Collins, US)
Giuseppe Formetta (Centre for Ecology and Hydrology, Wallingford, UK)
Tim Green (Agricultural Research Service, Fort Collins, US)
Greg McMaster (Agricultural Research Service, Fort Collins, US)
Scott Peckham (University of Colorado, Boulder, US)
Riccardo Rigon (University of Trento, Italy)
Francesco Serafin (University of Trento, Italy)
Marialaura Bancheri (University of Trento, Italy) 



Monday -  Introduction, Component-based Modeling Concepts 

09:00 - 12:30 Scope of the class
  • Class introduction (Rigon) - I could not be present, so someone talk in my place. 
          I think what I would have to tell you is here.
          Other information on Naming things in hydrology is here. However, Scott's                presentation 2 is pretty informative.
14:00 - 17:30 Getting Started with OMS(David)

Tuesday -  OMS Introduction

09:00 - 12:30 
  • Component Integration (David)  Presentation 
  • The Water tank example (Peckham, David) 
        watertank.pdfwatertank.zipwatertank_example.pdf

      The water tank  example is very simple, but very illustrative of what a model is. Today there is a         tendency to think lumped models as a set of tanks with rules for moving water. I will do a post             soon for it.

14:00 - 17:30 OMS Basic Building Blocks (cont.) Step By Step 
  • Project structure, components, simulations, file formats, annotations, etc. (Overviewexamples.zip )
  • Simulation Development. (scripting, testing, component connectivity, Examples
  • Thornwaite Waterbalance Model example
References: Annotations, DSL, CSV, OMSConsole

Wednesday Modeling Applications I

09:00 - 12:30 Hydrological modelling JGrass-NewAGE (Abera)
         Presentation, LWRB.zip, DMW.zip

14:00 - 17:30 Model calibration algorithms in NewAge-JGrass(Formetta)

        Presentation, prj-adige.zip, prj-snow.zip

References on JGrass-NewAGE can be found here. References on the Horton Machine can be found here. Maybe for most of you is a mystery what Pfafstetter numbering is. You can find information here. If someone has further doubts on components, they are documented on the GEOFRAME blog. If you do not have experience with calibration algorithms, you could start from some recent paper by Hoshin Gupta.

Addedum. Giuseppe added also a presentation of what he did on simulating landslides triggering with GEOtop (by embedding it in OMS3).

Thursday Modeling Applications II 

09:00 - 12:30 Agricultural Ecosystem Services (AgES) Watershed Model (Green)
      Presentation, Ages-Brazil.zip
  • Model Description  
  • How to run AgES in the OMS Console (Quick Start)
  • Brazil case study (streamflow)
  • Colorado, USA case study (distributed soil moisture)
AGEs is a "storages" based model, meaning that, as many other modern models, is based on the concept of intercommunicating storages. Physical contents are highly parameterised, but the model works. One of the model characteristic, which is common to other agricultural-oriented hydrological models, is the subdivision in small parcels with multiple communications among them (called Hydrologic Response Units). Interesting also the slides regarding the complexity of models.

14:00 - 17:30 Plant growth modeling with AgES (McMaster)
     Presentation


Monday, July 11, 2016

The first taste of Ne3 (netree) (at IEMSs in Toulouse)

We had this presentation, this morning at IEMSs, about some of the many lines of work where Francesco Serafin (his blog here) is developing his Ph.D research. The origin of the work is that modelling basins is to model hillslopes (or Hydrologic Response Units, HRUs) connected by a river network. Most of what happens in HRUs is independent from what happens in the others. Some instead is aggregated by river network. So why do not use this natural structure to organise modelling and processes (and send them in parallel, when possible, using the tree structure) ?
Actually this can grow more, since many systems (a plant, ecological interactions, hydrological interactions), can be seen described over a graph of interactions. So the Ne3 can become a more general way to investigate natural systems. However, you can enjoy the presentation, by clicking on the figure above.  Ne3 source code written so far in on Github.

Sunday, July 10, 2016

JGrass-NewAGE at IEMSs in Toulouse 2016

JGrass-NewAGE is growing and the readers of this blog know it. We are presenting the state-of-art-of the infrastructure in Tolouse IEMSs biennial meeting, and the presentation that will be given by Marialaura Bancheri is below (click on the Figure).
Improvements are not only on the number of components, but also in their internals. Many components now runs faster and are less error-prone. At the end of the presentation you can find the links to relevant papers. Enjoy!