Monday, February 6, 2012

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. 
Notes:

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

No comments:

Post a Comment