These slides come to highlight the work of Jost von Hardenberg, Elisa Palazzi, Silvia Terzago and others in downscaling the projection of GCM in order to obtain very local statistics of climate suitable to be applied, for instance, at the scale of river Adige or its main tributaries.]]>

These slides come to highlight the work of Jost von Hardenberg, Elisa Palazzi, Silvia Terzago and others in downscaling the projection of GCM in order to obtain very local statistics of climate suitable to be applied, for instance, at the scale of river Adige or its main tributaries.]]>

This develops the formalism of residence time as promoted by Botter, Rinaldo, Bertuzzo et al.]]>

This develops the formalism of residence time as promoted by Botter, Rinaldo, Bertuzzo et al.]]>

It discusses the coarse-graining of the Priestley-Taylor equation for estimating evapotranspiration]]>

It discusses the coarse-graining of the Priestley-Taylor equation for estimating evapotranspiration]]>

Abstract. This talk is about the GEOtop and JGrass-NewAge model, their physical bases, their informatics based on older (the first) and new (the latter) programming paradigms, the lessons I learned in building them with my group of people in an academic environment, their future, and the understanding that there is no the best model, but certainly a better way to do models. Hydrological modelling was for long time, and still is, almost a synonym of simulating rainfall-runoff. Recently, however, the scope of hydrology became wider, even among engineers. Modelling in hydrology now certainly still means modelling discharges, but also modelling snow, evapotranspiration and turbulent exchanges, and surface/subsurface interactions. With the goal of reproducing the whole picture of the terrestrial hydrological fluxes, my coworkers and I worked together in the last decade to build new models and new types of models. We started from the lesson by P. Eagleson, and we built first the process-based (grid based) GEOtop model. GEOtop is “terrain-based” (it is based on the use of digital terrain models and uses the knowledge of interaction between morphology and process) “distributed” (all the simulated variables are calculated for each pixel of the basin) model of “the water cycle” (it simulates all the components of the water cycle, accounting for both the mass budget and the energy budget, the two budget equations being coupled through the temperature of the soil, which controls evaporation, hydraulic conductivity, and accumulation of the snowpack). However, this GEOtop was intimidating many, either for the complexity of the process and its internals, and possibly not adapted to large scale modelling where faster solutions are required. Therefore we also worked on a different, more parsimonious model, called JGrass-NewAGE. From the lesson learned by implementing and maintaining GEOtop, we also found necessary to build the new model on new informatics. This system sacrifices process details in favour of efficient calculations. It is made of components apt at returning statistical hydrological quantities, opportunely averaged in time and space. One of the goals of this implementation effort was to create the basis for a physico-statistical hydrology in which the hydrological spatially distributed dynamics are reduced into low dimensional components, when necessary surrogating the internal heterogeneities with "suitable noise" and a probabilistic description. Unlike other efforts of synthesis, JGrass-NewAge keeps the spatial description explicit, at various degrees of simplicity. This has been made possible by opportune processing of distributed information which, in this way, has become part of the model itself.]]>

Abstract. This talk is about the GEOtop and JGrass-NewAge model, their physical bases, their informatics based on older (the first) and new (the latter) programming paradigms, the lessons I learned in building them with my group of people in an academic environment, their future, and the understanding that there is no the best model, but certainly a better way to do models. Hydrological modelling was for long time, and still is, almost a synonym of simulating rainfall-runoff. Recently, however, the scope of hydrology became wider, even among engineers. Modelling in hydrology now certainly still means modelling discharges, but also modelling snow, evapotranspiration and turbulent exchanges, and surface/subsurface interactions. With the goal of reproducing the whole picture of the terrestrial hydrological fluxes, my coworkers and I worked together in the last decade to build new models and new types of models. We started from the lesson by P. Eagleson, and we built first the process-based (grid based) GEOtop model. GEOtop is “terrain-based” (it is based on the use of digital terrain models and uses the knowledge of interaction between morphology and process) “distributed” (all the simulated variables are calculated for each pixel of the basin) model of “the water cycle” (it simulates all the components of the water cycle, accounting for both the mass budget and the energy budget, the two budget equations being coupled through the temperature of the soil, which controls evaporation, hydraulic conductivity, and accumulation of the snowpack). However, this GEOtop was intimidating many, either for the complexity of the process and its internals, and possibly not adapted to large scale modelling where faster solutions are required. Therefore we also worked on a different, more parsimonious model, called JGrass-NewAGE. From the lesson learned by implementing and maintaining GEOtop, we also found necessary to build the new model on new informatics. This system sacrifices process details in favour of efficient calculations. It is made of components apt at returning statistical hydrological quantities, opportunely averaged in time and space. One of the goals of this implementation effort was to create the basis for a physico-statistical hydrology in which the hydrological spatially distributed dynamics are reduced into low dimensional components, when necessary surrogating the internal heterogeneities with "suitable noise" and a probabilistic description. Unlike other efforts of synthesis, JGrass-NewAge keeps the spatial description explicit, at various degrees of simplicity. This has been made possible by opportune processing of distributed information which, in this way, has become part of the model itself.]]>

MeteoIO introduction given by Mathias Bavey in Bozen. ]]>

MeteoIO introduction given by Mathias Bavey in Bozen. ]]>

This contains the presentation given by Francesco Serafin for his master degree in Civil and Environmental Engineering]]>

This contains the presentation given by Francesco Serafin for his master degree in Civil and Environmental Engineering]]>

Mathematical models play a fundamental role in many scientific and en- gineering fields in today’s world. They are used for example in geotechnics to evalute the hillslope stability, in weather science to predict weather trends and produce weather reports, in structural design to study the resistance to stress, and in fluid dynamics to compute fluid flows and air flows. Consequently mathematical models are evolving all the time: more and more new numerical methods are being invented to solve the Partial Dif- ferential Equations (PDE)s that describe physical problems with increasing precision, and more and more complex and efficient processor units are being created to reduce the computational time. Therefore, the code into which the mathematical models are translated has to be “dynamic” in order to be easily updated on the basis of the con- tinuous developments (Formetta et al. (2014) [16]). On the other hand, completely different physical problems are often de- scribed using similar PDEs. For this reason, the numerical methods which provide solutions to different problems can be the same. This suggest the implementation of an IT infrastructure that hosts a standard structure for solving PDEs and that can serve various disciplines with the minimum of hassles. This work is focused on the application of what is envisioned above, with the main purpose of the creation of an abstract code for implementing every type of mathematical model described by PDEs. We work on hydrological topics but we hope to design a structure of general interest. Obviously the final goal of any work of this type is to find a proper numerical solver, and therefore, part of the thesis is devoted to the analysis of the problem under scrutiny, and the description of the solution found.]]>

Mathematical models play a fundamental role in many scientific and en- gineering fields in today’s world. They are used for example in geotechnics to evalute the hillslope stability, in weather science to predict weather trends and produce weather reports, in structural design to study the resistance to stress, and in fluid dynamics to compute fluid flows and air flows. Consequently mathematical models are evolving all the time: more and more new numerical methods are being invented to solve the Partial Dif- ferential Equations (PDE)s that describe physical problems with increasing precision, and more and more complex and efficient processor units are being created to reduce the computational time. Therefore, the code into which the mathematical models are translated has to be “dynamic” in order to be easily updated on the basis of the con- tinuous developments (Formetta et al. (2014) [16]). On the other hand, completely different physical problems are often de- scribed using similar PDEs. For this reason, the numerical methods which provide solutions to different problems can be the same. This suggest the implementation of an IT infrastructure that hosts a standard structure for solving PDEs and that can serve various disciplines with the minimum of hassles. This work is focused on the application of what is envisioned above, with the main purpose of the creation of an abstract code for implementing every type of mathematical model described by PDEs. We work on hydrological topics but we hope to design a structure of general interest. Obviously the final goal of any work of this type is to find a proper numerical solver, and therefore, part of the thesis is devoted to the analysis of the problem under scrutiny, and the description of the solution found.]]>

This deals with the assessment of several parameterizations of longwave radiation. The parametes were calibrated using a calibration tool on Ameriflux data.]]>

This deals with the assessment of several parameterizations of longwave radiation. The parametes were calibrated using a calibration tool on Ameriflux data.]]>

This presentation deals with the parameterisation (modelling) of net long wave radiation. It is deemed useful for estimation of both snow cover evolution and evapotranspiration ]]>

This presentation deals with the parameterisation (modelling) of net long wave radiation. It is deemed useful for estimation of both snow cover evolution and evapotranspiration ]]>

Marco Marani, from Padova University and Duke, presented a work on the soil-water-plants continuum. He emphasize the role of roots in modifying the soil water distribution, otherwise controlled by Darcy flows. However, he also studied and talked about the influence of the soil-plants-atmosphere continuum. ]]>

Marco Marani, from Padova University and Duke, presented a work on the soil-water-plants continuum. He emphasize the role of roots in modifying the soil water distribution, otherwise controlled by Darcy flows. However, he also studied and talked about the influence of the soil-plants-atmosphere continuum. ]]>

Andrea D’Alpaos finally talked about tidal networks, their formation, their shapes, their similarity or dissimilarity from river networks. All of it in a blend of equations, analysis in the field and lab experiments. ]]>

Andrea D’Alpaos finally talked about tidal networks, their formation, their shapes, their similarity or dissimilarity from river networks. All of it in a blend of equations, analysis in the field and lab experiments. ]]>

Gianluca Botter talked about the travel time distribution approach to catchment scale transport. A topic that intersects also the “old water paradox” querelle, but is, in general, pretty effective in getting the distribution of pollutants. This approach has a long story that put its roots, in Gedeon Dagan’s work, as well as in Rodriguez-Iturbe geomorphic unit hydrograph. Andrea own papers on Mass response function with Sandro Marani can also be considered at the foundations of this presentation. ]]>

Gianluca Botter talked about the travel time distribution approach to catchment scale transport. A topic that intersects also the “old water paradox” querelle, but is, in general, pretty effective in getting the distribution of pollutants. This approach has a long story that put its roots, in Gedeon Dagan’s work, as well as in Rodriguez-Iturbe geomorphic unit hydrograph. Andrea own papers on Mass response function with Sandro Marani can also be considered at the foundations of this presentation. ]]>

Enrico Bertuzzo covered instead the new topic of water borne diseases and their spreading along rivers. The way Enrico and coworkers analysed the problem, certainly inherited many notions and ideas sprout the early studies on river networks structure by Andrea (I had a part in it), but also on recent and domain specific achievements and findings. In the presentation he cited just one paper, but the research outcomes on the topic are certainly copious and exciting.]]>

Enrico Bertuzzo covered instead the new topic of water borne diseases and their spreading along rivers. The way Enrico and coworkers analysed the problem, certainly inherited many notions and ideas sprout the early studies on river networks structure by Andrea (I had a part in it), but also on recent and domain specific achievements and findings. In the presentation he cited just one paper, but the research outcomes on the topic are certainly copious and exciting.]]>

Modeling impacts of climate change on evapotranspiration and soil moisture spatial patterns in an alpine catchment.]]>

Modeling impacts of climate change on evapotranspiration and soil moisture spatial patterns in an alpine catchment.]]>

This contains the description of the use of GEOtop 2.0 in simulating the ecohydrology of a mountain environment]]>

This contains the description of the use of GEOtop 2.0 in simulating the ecohydrology of a mountain environment]]>

This is my report on the application of the Water Directive and the Flood EU directive in Italy, I gave at the Graz Alpine Convention/Planalp meeting. ]]>

This is my report on the application of the Water Directive and the Flood EU directive in Italy, I gave at the Graz Alpine Convention/Planalp meeting. ]]>

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This is the presentation given by Andrea Rinaldo in Trento for the opening day of the 2014 Doctoral School. ]]>

This is the presentation given by Andrea Rinaldo in Trento for the opening day of the 2014 Doctoral School. ]]>

This is the second talk given at AGU Fall Meeting 2013. It complements the first talk by presenting something of the new snow modelling, and freezing soil algorithms]]>

This is the second talk given at AGU Fall Meeting 2013. It complements the first talk by presenting something of the new snow modelling, and freezing soil algorithms]]>

This is the presentation (INVITED) for the AGU 2013 Session on High resolution modelling (Dec 10, 2013, session H21M)]]>

This is the presentation (INVITED) for the AGU 2013 Session on High resolution modelling (Dec 10, 2013, session H21M)]]>

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