GEOtop history up to the first public realease: part II

First Part

GEOtop 0.75

(mostly financed by COFIN 2001, THARMIT Eu Project, CUDAM - CofinLab 2001, ASI 54/2000)

With the Master thesis of Giacomo Bertoldi [2000] it was decided to throw away the PM equation for estimating evapotranspiration (actually we kept it for comparison), and to solve directly the energy budget in any point of the basin. This was the birth of GEOTOP 0.75 which is thoroughly documented in Bertoldi et al. [2011], and BTW in Rigon et al. [2006]. GEOtop 0.75 was actually a SVAT model plus an rainfall-runoff model coupled together, and was able to predict, besides the "normal hydrological observables", soil temperature.

GEOtop 0.75 needed several parameters to be run, however the modeling could have been considered parsimonious,  if its complexity was compared with its prognostic capabilities.   The user could switch-off the SVAT part and have a parametrically parsimonious rainfall-runoff model, or vice-versa s/he could switch-off the rainfall-runoff model and have a reasonably simple SVAT model. 

Large efforts were  done in cleaning the old code and improving the input-outputs quality. Wigmosta et al. [1994] original model is very similar to the version 0.75 of GEOtop (but was mostly a case of evolutionary convergence since the comparison came after the GEOtop implementation). 

In doing this version of GEOtop, we wanted to pursue the modelling of the entire surface hydrological cycle, even if a reasonable snow modeling still had to arrive. We were also looking for having a good tool for doing eco-hydrology. The revamp of eco-hydrology was in fact already seeded in Rodriguez-Iturbe's mind when I was working with him at the Texas A&M University (1994-1996), and  I was fully aware of his ideas from the beginning of the project. . 

For validation of the model, Tom Over  had a key role.  He, besides giving a lot of ideas for making the concepts behind the model clear, suggested to use the South Great Planes 97 experiment data set: that we promptly did as it appears in the first journal paper about the model Rigon et al. [2006]. In fact, one does not realize how scarce are hydrological data if he does not have a good model to cope with them.

Based partially on GEOtop 0.75 (and on the subsequent GEOtop 0.875) came all the work by Reza Entezarolmahdi who tried to create an automatic calibration system for the model. He used MOSC-EM  which, however was never really integrated in the model.  The work of Reza was really interesting for many points of view, but probably a little early with respect to our times, and scheduling. 

GEOtop 0.875

(mostly financed by TIDE EU Project, CUDAM Cofinlab COFIN 2001, THARMIT EU project)

This version finally achieved the goal of having  a snow accumulation and melt model (derived by the Utah Energy Balance -UEB- by Tarboton and Luce, [1992]) implemented by Fabrizio Zanotti [2003] with the help of Giacomo Bertoldi.  It also included a post-processor, the S-FACTOR (implemented by Christian Tiso [2003]), which used information on soil moisture to estimate the triggering of instabilites in hillslope^1.  Both the implementations were the outcome of two M.S. thesis.  Snow-melting and soil freezing are essential components in the hydrological cycle of mountain catchments and cannot not be overlooked. Landslide and debris-flow triggering are also an issue with particular relevance in mountains areas, such that floods in mountain areas are usually the combined effect of large liquid and solid discharges whose effects cannot be separated: GEOtop with this version started to be a reasonable a tool for studying all of these phenomena.  The reader can appreciate the differences among the previous version of GEOtop 0.5 and this one. Turbulent fluxes were now evaluated with a proper schematization of PBL and heat equation was quietly included in the picture; snow was modeled with a physically based (mono layered) model. 

With the version 0.875, let say 0.875b, we  also attack the problem of a sound hillslope-hydrology modeling, as ancillary to studying hillslope stability. The following is the rational behind the project, in words I wrote at that time.

"So far , our understanding of mountain catchments in fact has been based on hillslope hydrology, as reviewed for instance in Wipkey and Kirkby [1978], and  the "perceptual" hillslope model derived from the assumptions: that it is possible to neglect the transients in the water fluxes [in the sense clarified in Iverson, 2000]; that topographic gradients dominate the hydrologic response; that hydraulic conductivity strongly decreases with depth in the soil, and, not independently, that runoff occurs mostly owing to saturation excess. 

This last assumption, in turn, is  based upon the results of a long series of experiments from the late seventies on by American geomorfologists (Dunne, Black, Dietrich, Montgomery, Torres), and was supported by many others (among these: Moore, Grayson, Sivapalan, Wood). 

These above studies and research activities changed the belief spread by Horton that runoff was mostly due to a infiltration excess mechanism. Developing hydrological models based on saturation excess ideas (which involved further simplification) originated a series of models among which the already cited TOPMODEL [Beven and Kirkby,1979; Sivapalan et al, 1991; Franchini et al, 1996] is the most successful product in the rainfall-runoff area and SHALSTAB in landslide mapping. 

 There are many aspects that could be improved with respect to these modeling strategies. 

First of all:  in characterizing  the subsurface flow field more in terms of total head, even if in simplified form as in Iverson [2000], than in terms of the topographic gradient, as a first step toward the integration of the three dimensional Richards equation."

This step was implemented by the master thesis of Davide Tamanini [2003] that made GEOtop able to simulate transient subsurface flow, and both saturation excess and infiltration excess runoff.  A first parameterization of the soil water retention curves was also implemented in the model. It is this code that was used in the first journal papers on GEOtop (Zanotti et al., 2004, Rigon et al., 2006, Bertoldi et al., 2006). Upon this code was based the work by Silvia Simoni, helped by Fabrizio Zanotti, which produced the GEOtop-SF postprocessor that was able to estimate statistics of the stability of a hillslope. This work was realised to complete Simoni Ph.D. thesis  and Simoni et al., [2008]. 

In GEOtop 0.875 the integration of Richards equation followed a custom numerical scheme that was exceedingly complicate and non standard. Moreover, the integration scheme was not fully 3D, but could have been defined 2D + 1D, where "2D" stands for the lateral flow, obtained by using the Darcy Buckingham law, and 1D was the resolution of a one dimensional Richards equation. Despite these limitations, we could obtain reasonable reproduction of soil moisture distributions,  good discharges at the outlet of basins, excellent reproduction of summer soil temperatures, and what we considered a good reproduction of turbulent heat and evapotranspiration exchanges. 

GEOtop 0.9375 and subsequent versions till the first public release

(mainly financed by Projects with Servizio geologico PAT, progetto MORFEO by ASI, and EU IRASMOS and  AQUATERRA projects)

The new development started with in mind that we had sooner or later to switch to a version of GEOtop with a full 3D integration of Richards equation. Ex-post good results in our simulations for validating the code were  not enough to really cope with mainstream literature. 

However, the first new improvement of GEOtop was in the direction to include a multiple layer  modeling of snow and a first core of the freezing soil subroutines.  This task was mainly accomplished during the Ph.S thesis of Stefano Endrizzi [2007], and greatly improved in his subsequent work at Saskatoon, working with Phil Marsh and Bill Quinton, and recently at Zurich University collaborating with  Stephan Gruber. 

Why complicating even more an already complex model ?  Moreover, why getting a new snow model, if the Utah energy balance seemed to work fine, as written in Zanotti et al., 2004?

The rational behind this choice was essentially that the snow water equivalent was not enough for comparing snow measurement in the field with model outcomes. Clearly snow water equivalent (SWE) was enough just for those willing to cope with total water volume generated after snow melting, but not sufficient for studying and understanding the processes behind snowpack evolution and ablation. Nor even for having a reasonable estimate of soil temperature under the snow, and other interesting prognostics, like snow density. 

However, Stefano's efforts were not limited to snow. He worked hard, for getting a consistent integrator of Richards equation, that he based on a Newton Krilov-method (Kelley, 2003).  Besides he decided to change the surface water flow  equation and numerics, by using the shallow water equation integrated with a robust but explicit method.  This resulted in a very stable and reliable code that constitutes the core of the first public version of GEOtop. In fact Stefano decided to move from the the fraction of geometric series of  1/2 to the integer 1.

The collaboration of Stefano and Matteo Dall'Amico produced also a consistent integrator of the freezing soil moisture, after that Matteo, in his Ph.D thesis disentangled, at least for ourselves,  a lot of thermodynamics (and together, we introduced a simple, and "normal" thermodynamic notation). This work has been documented Dall'Amico Et Al., 2011. 

Various Directions 

Up to version 0.875 version GEOtop was pretty much a home made effort, mainly pursued by Master and Ph.D students of Trento University. However, since then, either because the Ph.D students became doctors and spread around, and because others discovered the potential our work, GEOtop started to became really internationally used. Han Xunjun in China used GEOtop in his data assimilation system implementing an ensemble Kalman filter (in Python). The Lausanne group under the direction of Marc Parlange, within the collaboration of Silvia Simoni, and the direct coding efforts of Thomas Egger implemented a real time version of the model that is giving its results everyday (http://lsir-hydrosys01.epfl.ch:22006/). John Albertson and his group implemented an erosion module to be coupled with GEOtop. In Trento, a version of GEOtop, called GEOtop-EO implemented a prototype of  infrastructure that includes besides the modeling core, a geographical database, with a raster service (built upon RAMADDA) and a visualization system based on JGrass. This was done for the project MORFEO.  At Bolzano, in EURAC, Giacomo Bertoldi and Stefano Dallachiesa, endowed GEOtop with an external (so far) vegetation dynamical model (itself came from elaboration of previous work by Albertson and Montaldo). Worth to mention in this section is also the work of Emanuele Cordano. He dedicated a lot of time in defining the "keyword schemes" that eventually, after some reworking,  become the standard for the I/O of GEOtop. He also started a parallel work on Boussinessq's equation which provided to us a first better idea of what Newton's method of integration is. Moreover, he studied and implemented the first NetCDF O (output) version of GEOtop. Last, but not least, Mountain-eering made of GEOtop the center of its business plan, and supported the completion of the freezing soil module, and is going to develop a new NetCDF input/output system (helped by Emanuele), and the creation of some data assimilation scheme of snow measures. 

Credits to work of the group of Lousanne should be given to have also included in GEOtop the METEO/IO environment which was the way to link the model to a real-time acquisition system.  Stefano Endrizzi himself, when at Saskatoon, discovered the work of Liston and Elder [2006] with MICROMET, and included it in the GEOtop distribution with the permission of the Authors. 

Also other player came  to the game. Arpa Val D'Aosta decided to make of GEOtop the principal tool for doing analysis on snow and permafrost, and it is going to support its improvement and usability. The Karlshrue Institute of Technology in Garmisch-Partenkirchen (and particularly Harald Kunstmann, and coworkers) adopted for simulation for one of their TERENO experiment.  

This, just to mention partial developments, not all of them yet flowed into the main version of the model. All of these efforts, in fact, could not being really unified in a single product. 

First Part

Notes:

^1 This eventually evolved into GEOtop-SF by Silvia Simoni, documented in Simoni et. al [2008]

GEOtop History up to its first public release: Part 1

``As scientists we are intrigued by the possibility of assembling our knowledge into a neat package to show that we do, after all, understand our science and its complex interrelated phenomena.'' (W.M., Kohler, 1969).  

I robbed this statement from Keith Beven's [2000] book: Rainfall-Runoff,  the primer, because it clearly represents one of the motivations that stand behind the development of GEOtop.  

As some of you may know, versioning, at the beginning of GEOtop development followed the geometric series of two. First version was  0.5, second 0.75, third 0.875, and so on.  The message was that such a model solution is never definitive (the version 1), and, besides, I was always intrigued by the Zeno's paradox, and by the versioning system of TeX (asymptotically approaching up Pi) and LaTeX (moving up to number e).

Who follow upfor the main development decided to change the versioning with a more normal sequence. That was the first public edition. Further details of this history can be found in the presentation I gave in Princeton CHAMDA II 2004, and can be found here in a revised version. 

GEOtop 0.5

The development of the first version of GEOtop (0.5) was mostly financed by the Autonomous Province of Trento through the Serraia project, and by the Italian Ministry of Research and University through the Cofin 1999 project.

The very first step was  reading and reading again  the Dara Entekabi review of modeling the whole hydrological cycle [e.g. - Marani and Rigon (eds), 1997]^1, and the development started with  the master thesis of Paolo Verardo, and his subsequent work in 1998. Around a year was spent to implement a decent model for evapotranspiration in a complex terrain environment, according to the Penman-Monteith (PM) scheme (find the formula either in Dara's lecture above, or in my lecture here), and all the necessary incoming radiation treatments. All this work was not dedicated to the PM formula which was obviously trivial to implement, but to find a proper estimation of the radiation, which included the view angle and the shadowing routine.^2

 The  problem of data  regionalization (the only data we had were those coming from traditional hydro-meteorological stations in single points and we did not have many of them) was faced for the first time. 

A part from the geomorphological data that we extract from DEMs (the "sine qua non" basis of all our work), we had to regionalize (make spatial): air-surface temperature (varying  with the elevation of the terrain), net radiation (and eventually by the evaluation of an atmospheric thickness which has to be regionalized too), and wind speed. 

In sequence it was decided to use: kriging  techniques and the hypothesis of adiabatic temperature profile (for air temperature)^3;  Brutsaert [1983] paper results (for atmosphere emissivity)^4,  and constant (or occasionally kriged) wind speed everywhere. This was performed through the use of external programs.

The heat conduction into the ground was parametrized as a linear combination of a sinusoidal function as Entekabi suggested [1997] . That work  was also inspired by the routines  of IPW (Image Processing Workbench) [Frew, 1990]. 

Actually we tried to make IPW work concurrently with the borning GEOtop: but its pervasive scripting base (scripting is good but there is a point after which it makes the code organization unclear), the discontinued support, and ignorance of IPW code internals (and just ignorance), led us to built a new system from the scratch. 

Despite of the approximations introduced, GEOtop 0.5 model worked fairly well in estimating the net longwave and shortwave radiation in any point across a basin and at any hour of the day, and could give also what appeared to us reliable estimates of the potential evapotranspiration on a daily basis. However to obtain the real evapotranspiration was a different question (and, obviously, to validate it, even a different one).  

Marco Pegoretti [1999] added to the evapotranspiration modules a rainfall-runoff model (temporary called GEOMODEL). The approach we had to the problem of rainfall-runoff  was strongly influenced by the work of Rodriguez-Iturbe and Valdes [1979] and Gupta and Waymire [1980],  and we were reluctant to abandon the simplicity of a GIUH-based model in favor of a fully distributed model (that we made later). 

Of the many ideas behind the theory of the GIUH  derives from the observation that the river basin is a complex system (an interplay of hillslopes and channels) but, at least for the forecasting of floods,  simple models work fairly well (leading to the conclusion that dynamics simplify the complexity and wipe out part of the heterogeneity underneath)^5.

The big problem in the GIUH approach however was (and is) that the determination of the effective rainfall, i.e. the correct separation of surface runoff (interpreted as the cause of the flood surge) from subsurface flow (which must be actually treated separately and routed to the channels in a slower way), especially in dependence of storm events of diverse intensity, duration and inter-arrival time. 

A model more or less contemporary to the GIUH is the TOPMODEL by Beven and Kirkby [1979]. It is based on the paradigm that runoff production is due to saturated areas (according to Dunne and Black, 1970). Thus, once one knows which areas are saturated and describes their growing during an event, the problem of the runoff coefficient is almost solved,  and routing of water to an outlet can be accomplished by some simple mechanism (the Muskingum-Cunge model at least in the original TOPMODEL papers).^6

Thus, an idea could have been to merge the best of the two formulations, the GIUH concept with the TOPMODEL. However the hypotheses on which the TOPMODEL has been based, mainly the stationarity of the hillslope subsurface fluxes,  simplifies the life of the modeler, but introduces several limitations, and needs several work-around as described in  Beven et al., [2002] to be applied with success. In fact, when the final goal of modeling,  is not simply the production of a well-fitted flood wave, but for instance the estimation of local soil moisture contents, the TOPMODEL fails to be accurate enough [e.g., Grayson and Wilson, 2002]. 

Due to its limitations, the TOPMODEL's parameters  become "effective'' parameters, and lose their original physical significance (for instance, the hydraulic conductivity cannot be validated by local field measurements), and need to be "calibrated" ex-post. Other limitations will be mentioned below when talking about the GEOTP 0.875 version. In any case, the TOPMODEL concept has been demonstrated to be a good tool to model floods in small-to -medium catchments, and has been considered the reference hydrological model for many of the researchers during the '90s. The TOPMODEL's ability to forecast floods derives also from its account (trivial indeed) of the topology and geometry of small- catchment flow paths: it was shown, in fact, that in small watersheds (up to at least 1000 square kilometers), hillslope residence time dominates the characteristic time of flood formation and that topology and geometry of river basins are sufficient with very minimalist dynamics to explain the shape of floods [e.g. Rinaldo et al, 1991; Rigon et al, 1996, Rinaldo et al., 1995, D'Odorico, 1996; D'Odorico and Rigon, 2003]. 

Upon all the above arguments, it was decided  to build a completely new subsurface and surface model, still driven by gravity (i.e. by topographic slope as the TOPMODEL and not by the total hydraulic head) but, as a first approximation to the final wishes of having a better physically-based theory, introducing the buffer to cope with infiltration into the vadose zone.  Subsurface flow was produced only by the saturated layer (including the capillary fringe), if present, and lateral surface runoff was routed as a kinematic wave (and through Manning/Gauckler-Strikler equation for velocities). 

In doing this, it was also tried  a better characterization of flow paths, with reference to the bedrock, instead of to the surface topography [see McDonnell et al., 1996]: this could be done by measuring soil depth or interpolating it for instance as in [Heimsath et al, 1997 or Roering et al, 1999; please see the overlooked  Bertoldi et al, 2006 for the details]. 

In this separation of surface and subsurface fluxes, GEOtop 0.5 was similar to the grid bases THALES [Grayson et al., 1994a,1994b] or the more recent NEWTHALES. 

At first, the version of GEOtop by Verardo-Pregoretti-Rigon (GEOTOP 0.5) could work without an explicit channel routing by assigning a locally variable roughness and hydraulic radius; if channels were determined by accurate topographic analysis, they could be explicitly treated. 

In this case, channels routing was performed by a GIUH theory as in Rinaldo et al [1995], where channel celerity and hydrodynamic dispersion were  considered spatially uniform and constant in time. 

Instead of the effective rainfall, the spatially and temporally distributed input to channels was produced by GEOtop, i.e. the GEOMODEL produced patterns of spatially distributed soil moisture, and these patterns were used to reduce the potential evapotranspiration to its real counterpart as described in Bertoldi et al., [2002].

Second Part

Notes

^1 - MIT's group, on the other side had a long tradition in this direction of modeling that originated from Pete Eagleson work in late seventies and eighties. Dara's talk in fact inherit a lot from that work. Raphael Bras, Dara Entekabi, Valeriy Ivanov, Enrique Vivoni and others themselves  implemented a model similar, in concepts, to GEOtop, tRibs. 

^2 Today GEOtop mostly uses Xavier Corripio's schemes

^3 We still use kriging, but also Glen Liston's Micromet [Liston and Elder, 2006] and MeteoIO 

^4 Various possibilities are present now, and they derive mainly from Stefano Endrizzi Ph.D. thesis.

^5 But this is to many respect debatable, since this statement refers to the closure of the basin, and from this going back to forecasting the internal distribution of discharge is impossible. Keith Beven wrote a lot on this. 

^6 Research subsequent to TOPMODEL, including ours (e.g. Lanni et al., 2011, 2012 for a review of problems and literature, and Cordano and Rigon, 2008 for a top-down derivation of TOPMODEL related equation from Richards' one) , clarified many of the limitation behind TOPMODEL approach.