Using GEOframe-NewAGE for operational modelling

Finally we did it ! Thanks to ARPA Basilicata and the work of my co-authors, Marialaura Bancheri  (GS) and Salvatore Manfreda (GS)  this long term objective of mine had a first realisation. We think GEOframe is a brilliant platform for operational hydrology, due to its flexibility and expandability.
we did not produce much new science with this paper. However, I think the introduction is brilliant, the explanation of how the models work of unsurpassed clarity, thanks to the use of EPNs, and, obviously, the system informatics really outstanding. You can find below the Figure representing the core modelling structure with this graphic system.

 Below you also find the representation of  how routing was implemented.  The latter figure shows how a dam was inserted in modelling. Because the EPN is actually reflected into the internal informatics, based of Net3, the dam can be inserted or excluded, according to what we want to simulate, without breaking the model, just on the basis of scripting.

It will be interesting from now on to monitor  how the system actually work in the operational context, and we will give proper information of it in the future. The paper is open access on Water, and you can see it here.

Material for the GEOframe Winter School - Rainfall-Runoff

Here we are introducing some modules for rainfall runoff modelling present in GEOframe. Some of them where actually refined for the Civil Protection of the Basilicata Region.

Schedule

• Deconstructing the catchment (YouTube video)
• The Embedded Reservoir Model (YouTube video). On this I was maybe not clearly enough. ERM in itself is not clear on the fact that ERM is not a model in the traditional sense. It is actually the composition of four components. For instance, the runoff one is a simple non linear reservoir. Working with sim files, we can rearrange them also in different ways and obtain different "modelling solutions"
• TheNet3 Infrastructure (YoutTube Video)
• LUCA (YouTube video)
• Examples of Application
• The Posina Catchment (Abera et al., 2017a)(YouTube video)
• The Blue Nile (Abera et al. 2017b) (YouTube video)
• The Basilicata Civil Protection (YouTube video)

Exercises

• The set of sim files and the Jupyter notebook are here
• The Python script by Christian Massari to create automatically the required subfolders. It is here.

General references to Rainfall-Runoff


Beven, K. (2012), Ranfall Runoff, the primer, Wiley-Blackwell

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

References besides the one already used

For seeing how to represent lumped hydrological models (you can give a look to this paper here)

Abera, W.W. (2016), Modelling water budget at a basin scale using JGrass-NewAge system. PhD thesis, University of Trento

Bancheri, Marialaura (2017) A flexible approach to the estimation of water budgets and its connection to the travel time theory. PhD thesis, University of Trento.

Formetta, Giuseppe (2013) Hydrological modelling with components: the OMS3 NewAge-JGrass system. PhD thesis, University of Trento.

Formetta, G., Antonello, A., Franceschi, S., David, O., & Rigon, R. (2014). Hydrological modelling with components: A GIS-based open source framework, 55(C), 190–200. http://doi.org/10.1016/j.envsoft.2014.01.019

Patta, C, Costruzione di un modello idrologico di stima della disponibilità idrica in area pedemontana, Tesi di laurea (in Italian), Politecnico di Torino, 2018

For open questions about rainfall-runoff see also the Meledrio Posts.

Previous Winter School page

All Winter School pages

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Is possible to get the runoff for European Countries ?

This is a conversation between two groups of the CLIMAWARE project of some general interest. Further information about global or continental scale hydrology can be found in some previous posts.

Dear Alberto and Riccardo, 

we are writing about the data we need for the project CLIMAWARE. 

The objective of out analysis is to estimate the impacts on agricolture of modification of:

1)  soil use

2)  anything due to the changed water availability as a consequence of the climate change. 

We are thinking to consider two time frames, the first up to 2020, the second up to 2040 (this because the estimation of soil use variation are available for these two dates and to do an analysis on the national scale for all the Countries of the European Community. 

Martina

Alberto's answer:

Dear Martina,

for what I know, there are not detailed projections at this scale. I saw studies on the largest basins (as  Danube) where all is solved by putting R = P- E (runoff = precipitation - potential evapotranspiration). For what I know, nobody looks at the national scale, for the reasons that the river basins do not coincide with nations areas.

There are regional studies (not about the countries but  for Southern Europe, for instance) made by Giorgi’s group or by Julich’s colleagues using their Earth system model. 

Bruno Majone answer:

Dear Martina,

what you are opening is a Pandora’s vessel. I try to explain it better. To deal with water availability at European scale, there are many different approaches. The simplest is to do a hydrological budget simply by using the available climatic projections. Alternatively, one can use hydrological models working at pan-european scale that can be fed directly by the projections themselves. For any of the choices the real problem is selecting the right forcings. There isn’t a reference dataset: there are various “ensemble” of simulations derived from various climate models, each one of them following a different pathways scenarios.  The reference initiative for Europe is Euro-cordex that gathers the modelling work of various research groups that perform experiments with global and regional climate models, and scale down the results from a coarse grid of 125 km to one of around 25 km (see the pdf). Considering the results of these models one should observe that usually they have strong biases that need to be corrected. Otherwise the water budgets can be extremely wrong. For what I know, inside the Euro-Cordex group there are groups that are examining and providing scenarios by using various techniques of bias correction, but I am not sure that they are already available and usable. 

If your interest is to have annually aggregated data by country, I personally would not explore thid road because I believe that the effort to contact the active groups, download huge datasets and precess them could be overwhelming.

I would try instead to contact groups that already have hydrological models setup at European scale and are already estimating climate change impacts. Alberto mentioned the Julich group, but another possibility could be JRC. They have their model LIFSFLOOD set up at 5*5 km of resolution (and it could be that they already have used it to do some impact studies).  At this point you should ask for they to send some gridded data of runoff and afterwards aggregate them at country level.

Quickness and exactitude

I put here an internal review of one of our manuscript, because, I hope, it can be useful in general. The topic is evaluating the rainfall runoff of a small catchment (but I hoped it was en estimation of the global hydrological cycle, even if without evapotranspiration measurements).

"The paper is written in a good English (finally). However good English does not mean is a good paper. It lacks of focus and is not concise (lack of exactitude and quickness, see at the end of the post). Objectives are not clear, and the novelties of the paper not evident. However, I am not desperate to obtain at the end something reasonable: but this just because I know the amount of work behind it, and, in part, the row-material.

Making a rainfall-runoff model cannot be usually considered an exercise at the frontier of our science (citing conversations with Ignacio Rodriguez-Iturbe. However, it could be, as testified by Gunther Bloschl's ERC). It, making rainfall-runoff, I mean, certainly can bring information about a certain basin. However, in our case, the works of N* and M* already filled this space. So what it is the goal of this paper ?

The initial idea was to assess the uncertainty in prediction of discharges by using appropriate statistical techniques. In particular, the idea was to assess the uncertainty inherent to rainfall extrapolation from point measurements to spatial measurements. 

This task has been only partially fulfilled. For the following reasons: errors due to instruments precision were not included (just the hypothesis of perfect functioning measures was applied);  the way rainfall has been included in the model (is not yet clear if average rainfall, one point for each hillslope was used, average rainfall volume for any information or other approximations were utlised: and no sensitivity analysis with respect to the way distribute rainfall was squeezed into the model was performed); the interplay between rainfall and discharge forecasting is not well developed, at least as it could be, i.e. explaining how it works inside the whole procedure is not explained well.  

Therefore the overall rainfall prediction analysis is incomplete, and I expect it would be completed for the thesis. 

The technical novelty we apply in this work is that we use a calibration tool (LUCA) to assess variograms, and we do it at hourly time step, while others do usually at daily time step. A few questions here: how much this approach improves rainfall estimates ? i.e., taking uncalibrated variograms and/or constant variograms (not varying in time) how much difference do we get ? How much this affects the forecasting of the volumes of water? Which comprehensive effect has this on the forecasting of the discharges ?

It could be that all of these approximation have negligible effects on the forecasting of discharges. But this would be indeed good to know and an achievement, which was not obtained so far. 

A second topic of interest was the simulation of the whole hydrological cycle, and a tentative to close the hydrological budget with the Priestley-Taylor simulation of evapotranspiration. This simulations were done but not shown at all in the manuscript. Why not ? Do the simulated discharges and the  simulated ET sum to the total volume of rainfall ? If not, which interpretation do we have about the missing mass ?  Are we able to assess the uncertainty in predictions of each single component of the hydrological cycle obtained with this method? Are we able to observe interannual variability (both in discharges and evapotranspiration, and, if the case, in storage) ? Is this variability estimate reliable, at least as a gross budget ?

Having missed to answer to each one of the questions above the paper results a wandering around that breaks our karma (citation from Vijay K. Gupta).  Please save us with more rigor. 

Regarding quickness and exactitude, I suggest the reading of Italo Calvino's Six Memos for the next Millennium.^1^2

^1 - Here a video seminar on the Six Memos by Paolo Granata
^2 - Hainging around, in a digression maybe, and unfortunately in Italian, the Discorso sulla Matematica (Talk on Mathematics) inspired and guided by Calvino's lectures, written by Gabriele Lolli

What is the minimal geomorphology-based hydrological model?

This is one of the objects of the research Alban de Lavenne, a Ph.D. student of Christophe Cuddenec pursued here in Trento, during his three months stay the last Fall. Similar approaches can be found in the work by Fenicia, and especially in Fenicia et al., 2008. Fenicia 2008, is a must-read paper, since it is well written, and smart. However there, the  Authors did not use any geomorphic information as guideline in their modeling but just a scheme based on reservoirs, which is, in my view, out-of-date. Which is kind of a pity, considering that we know very much of the morphology of river, even when they are ungauged. Thanks to SRTM, ASTER, and other topographic data, the topology and geometry of river networks, and Earth's elevation is known with unsurpassed precision all over the World, and therefore, the first step to predict what happens in ungauged basins would be to use their geo-morphology, which, in fact, was shown to be important in many papers.

Alban used in his investigation a few simple geomorphological unit hydrograph schemes based on the width function:

• 1F1U1P: 1 velocity applied to entire flow path length
• 1F2U2P: 2 velocities (respectively on hillslope and channelized length) -
• 2F2U3P: 1 velocity for surface flow, 1 velocity for subsurface flow
• 2F3U4P: 2 velocities for surface flow, 1 velocity for subsurface flow

In this context, "velocity" can be read also as "mean travel time" since the relation between the two quantities is given by the appropriate lengths measured along the flow paths.

In any case, the poster you can retrieve below the figure (click on the figure) tells it all. 

A simple and trivial consideration about rainfall return period in relation with a spatial analysis, and discharges

Statistics at station, i.e. evaluated at ground measurements stations do not reflect the statistics of the areal event. This is obvious. However, even today, I read a report where the guys:

1. estimated the return period of rainfall in several point 
2. used the estimated depths to infer the spatially varying rainfall intensities
3. use these rainfalls as inputs of a rainfall-runoff model to obtain extreme discharges

In between there are a lot of technicalities, often useless. The point is, which is clear to the most, I hope, that, when moving from point 1 to point 2, one assumes that all the measured events are isochronous, which is not (otherwise we could not have let say 200 hundred return period events each year ia a space-wide area).  The above operation actually correspond to consider a precipitation with a higher return period than established (usually following some design criterion) and therefore maximise excessively the discharges.

What one should do is instead:

1. studying the spatial statistics of precipitation to enable a stochastic weather generator^1^2
2. run in continuos time her/his rainfall-runoff model for a long period, say 20 years if one wants to get some statistics a return period of 4 years,
3. analyse the results and extracting the statistics of the discharges (i.e. their return period), eventually extracting the extreme events

The validity of each component of the modelling chain should have been tested against available data (of the basin) independently.  Traditionally engineers do not like to simulate events at continuos time, and prefer to model events. This latter approach, however, has several drawbacks, and especially:

• one has to determine the initial conditions (which also introduce a bias in the return period) of the catchments (models that do not have this problem cannot be good models)
• fall back into the issue of determining a spatially distributed rainfall with a certain return period

Engineers usually also neglect the role of snow in producing discharges. This cannot be neglect, except than in particular climatic conditions. Using continuos time simulations also implies the use of some parameterisation of evapotranspiration (and therefore requires a model like JGrass-NewAGE).

^1 - Remarkably using a weather generator can also allows the inclusion of foreseen trends (either in precipitation characteristics, as depth, interstorm inter-arrival time, or evapotranspiration or radiation).

^2 -  Usually these models are site depedent. Therefore, waiting for a spatial stochastic weather generator, one should run several copies of the weather generator, each one for each sites where there can be information to drive it, and subsequently, using the spatial data, spatially interpolate at each time-step the desired quantity.

My Past Research on Physico-Statistical Modelling of the Water Cycle at Basin Scale

While GEOtop [J24, J25] is for process-based modelling of the mass and energy budgets at a small scale, in order to model larger catchments, which include abstraction works or hydraulic structures, it was decided to implement a new modelling system JGrass-NewAGE [J34].  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 is 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 wants to keep 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.
From the point of view of the information technology used to implement the modelling  [J41, A44, A49, A50], the system is based on the OMS v 3 system, which allows the use of modern, object-oriented strategies for the structuring of the deployment of the software and, at the same time, furnishing not a model, but various, interchangeable, modeling solutions (MS) that can be adapted to the problems in hand and the practical demands of the problem being solved.
The modeling system, as well as the components to model the physical processes themselves, also includes various tools for the processing of input data (for example, Kriging tools), including all the tools of the Horton Machine [eb3] for the processing of digital terrain data, and the tools for the treatment and interpretation of the output data, for the calibration of model parameters, and (in perspective) for continuous data assimilation.
With this in mind, an effort that is currently being made is that of creating an opportune digital watershed scheme that can accommodate the needs of the various modeling conceptualizations and the identification of areas that are hydrologically "similar" that can be treated conjointly during the calculation of flows and storage. At the moment, model solutions use standard implementations.  [J34, J41, A50] contains the description of the rainfall-runoff part of the modelling system; [J43] is a verification of the radiation budgets components; [J44] is an example of simplified snow modelling.  As a standard, any components is verified by itself against the data relative to the process that it describes, using various automatic calibration procedures, and quantitative objective functions. [J34, J41] using the infrastructure show how increased geomorphological (and processes) information affects the quality of reproduction of the hydrologic response. [j44] explains the watershed partition, based on a generalisation of the Pfafstetter numbering scheme, that guide the functioning of the JGrass-NewAGE system.

References 

In English:

[J24] - Rigon R., Bertoldi G e T. M. Over, GEOtop: A distributed hydrological model with coupled water and energy budgets, Vol. 7, No. 3, pages 371-388

[J25] Bertoldi G. R. Rigon e T. M. Over, Impact of watershed geomorphic char- acteristics on the energy and water budgets, Vol. 7, No. 3, pages 389-394, 2006

[J34] - Formetta, G.; Mantilla, R.; Franceschi, S., Antonello A., Rigon R., The JGrass- NewAge system for forecasting and managing the hydrological budgets at the basin scale: models of flow generation and propagation/routing, Geoscientific Model Development Volume: 4 Issue: 4 Pages: 943-955, DOI: 10.5194/gmd-4- 943-201, 2011

[A49] Formetta G., Antonello A., Franceschi S., David O. and Rigon R., The informatics of the hydrological modelling system JGrass-NewAge, 2012 International Congress on Environmental Modelling and Software Managing Resources of a Limited Planet, Sixth Biennial Meeting, Leipzig, Germany R. Seppelt, A.A. Voinov, S. Lange, D. Bankamp (Eds.) http://www.iemss.org/society/index.php/iemss- 2012-proceedings, 2012

[j36] - Formetta G., Rigon R., Chavez J.L., David O., The short wave radiation model in JGrass-NewAge System, Geosci. Model Dev., 6, 915-928, 2013, www.geosci-model-dev.net/6/915/2013/
doi:10.5194/gmd-6-915-2013

[J39] - Formetta G., Antonello A., Franceschi S., David O., and Rigon R., Hydrological modelling with components: A GIS-based open-source framework, Environmental Modelling & Software, 5 (2014), 190-200

[j42] - Formetta G., David O., Kampf S., Rigon R., The Cache la Poudre river basin snow water equivalent modeling with NewAge-JGrass, accepted GMD, 2014

[j44] Formetta G. , Antonello A. , Franceschi S. , David O., Rigon R.,  Digital watershed representation within the NewAge-JGrass system. Boletin Geologico y Minero, 125 (3): 371-381, 2014. ISSN: 0366-0176

In Italian:

[A44] Antonello A., Franceschi S., Formetta G., Rigon R., L’infrastruttura NewAGE per la previsione e la gestione dei bilanci idrici a scala di bacino: I - La struttura informatica, in Atti XXXII Convegno di Idraulica e Costruzioni Idrauliche, Palermo, 14-17 Settembre 2010

[A45] Formetta G., Franceschi S., Antonello A., Cordano E., Mantilla R., Rigon R., Il sistema NewAGE per la previsione e la gestione dei bilanci idrici a scala di bacino. II - I modelli di generazione, aggregazione e propagazione del deflusso. in Atti XXXII Convegno di Idraulica e Costruzioni Idrauliche, Palermo, 14-17 Settembre 2010

[A50] Formetta G., Rigon R, Le nuove componenti modellistiche di JGrass-NewAGE, Atti del XXXIII Convegno di Idraulica e costruzioni Idrauliche, Brescia, 10-15 settembre 2012

My Past Research on Rainfall-Runoff (Peak Flows) Modelling and related topics

These works of mine reagards event base prediction of discharges based on the Geomorphological Unit Hydrograph. They show that the detailed knowledge of a river basin's morphology allows one to frame the main features of the  hydrological response in terms of a minimal set of dynamical parameters.  This is relevant insomuch as the form of river networks can now be derived with automatic high resolution and objective remote-sensing techniques.  Typically, the required dynamical parameters are the mean flow velocity in the network and distribution of residence times of water in the hillslopes.

In this context, the variance of the GIUH is proven to depend mostly on the structure of the pathways followed by the single volumes of effective rainfall from their release points to the control cross-section (geomorphological dispersion) [J1] rather than on the hydrodynamic dispersion; the latter becoming  relevant only at the large scale.
Generally, it is possible to determine with precision the first moment, the variance, the  skewness, and the kurtosis of the hydrological response of a river basin  as a whole [A3, A9].  In [A7, J12] the production mechanisms of effective rainfall and the  characteristic contributions of the hillslopes are studied. As a result it was observed that rarely is the  response time of the hillslopes negligible when calculating the hydrological response of the  river basin as a whole.
In  [A18, A19, J21] the use of width functions in the construction of the GIUH and the concept
of including information about initial moisture conditions for the basis are further developed.
In this way it was observed that, with varying fractions of saturated river basin, the hillslopes
and channels contributed different fractions to the flood wave;  the hillslopes being particularly
important under conditions of extreme saturation of the basin [J21].
The formulation of the GIUH on the basis of width functions has also given semi-analytical
results regarding peak times and maximum discharges for a basin [J31].
All of these studies brought to the implementation of part of the Horton Machine [eb-3], and on the model Peakflow (e.g. http://www.jgrasstools.org).

The post on the lecture given at Montpellier contains the rational and an explicitation of the assumption made in such type of modelling.

More recently, the study of the hydrological response was directed mainly towards the investigation
of runoff production mechanisms on hillslopes (actually in researches related to the hillslope stability),  in relation to the soil depth [J33, J35, J37] and brought new insights to the concept of hydrological connectivity. These studies overcome the results in [A29] that, while interesting, assume simplistic hillslope setups. Parallel efforts, which are reported in Physico-Statistical Modelling of the Hydrological Cycle, were made in overcoming the limitations of event based modelling.

The paper [j47] is a review taken from a historical-critical point of view of the theory of the geomorphological unit hydrograph that also enlarge the view to the modern theories for describing water fluxes by travel time. It also serves as the starting point for future research in this directions.

References

In English:

[J1] - Rinaldo, A., A. Marani and R. Rigon, Geomorphological dispersion, Water Resources Research, 27(4), 513-525, 1991

[J12] - Rinaldo A., G. K. Vogel, R., Rigon and I. Rodriguez-Iturbe, Can one gauge the shape of a basin?, Water Resources Research, (31)4, 1119-1127, 1995.

[A18] - Rigon, R., Cozzini A., Pisoni S. Getting the Rescaled Width Function and the Derived WGIUH. The Geomatic Workbooks, (http://geomatica.ing.unico.it), 2001

[A19] - Rigon, R., Cozzini A., Pisoni S. Looking for a new method of estimating solid discharges in small alpine watersheds. The Geomatic Workbooks, vol. 2, (http://geomatica.ing.unico.it), 2001

[J21] - D’Odorico, P. e R. Rigon, Hillslope and channel contributions to the hydrologic response, submitted to Water Resour. Res., 2003

[A29] - Panciera, R., Chirico G.B., Rigon R., Grayson R. Contributing Area Dynamics produced by Saturation Excess Runoff. Atti del XXIX Convegno di Idraulica e Costruzioni Idrauliche, Settembre 2004

[eb-3] - R.Rigon, E. Ghesla, C. Tiso and A. Cozzini, The Horton Machine, pg. viii, 136, ISBN 10:88-8443-147-6, University of Trento, 2006

[J31] - R. Rigon, P. D’Odorico, and G. Bertoldi, The geomorphic structure of the runoff peak, Hydrol. Earth Syst. Sci. Discuss., 8, 1031-1058, doi:10.5194/hessd-8- 1031-2011, 2011

[J33] - Lanni, C.; McDonnell, J. J.; Rigon, R., On the relative role of upslope and downslope topography for describing water flow path and storage dynamics: a theoretical analysis, Hydrological Processes Volume: 25 Issue: 25 Pages: 3909-3923, DEC 15 2011, DOI: 10.1002/hyp.8263

[J35] - Lanni C., J. McDonnell JJ, Hopp L., Rigon R., "Simulated effect of soil depth and bedrock topography on near-surface hydrologic response and slope stability" in Earth Surface Processes and  Landforms, v. 2012, (In press). - URL: http://onlinelibrary.wiley.com/doi/10.1002/esp.3267/abstract . - DOI: 10.1002/esp.3267

[J37] - Lanni C., Borga M., Rigon R., and Tarolli P., Modelling catchment-scale shallow landslide occurrence by means of a subsurface flow path connectivity index, Hydrol. Earth Syst. Sci. Discuss., 9, 4101-4134, www.hydrol-earth-syst-sci- discuss.net/9/4101/2012/ doi:10.5194/hessd-9-4101-2012,
HESS

[J47] - Rigon R.,  Bancheri M.,  Formetta G.,  deLavenne A. , The geomorphic unit hydrograph from a historical-critical perspective, accepted in Earth Sci. Proc. & Landforms, 2015


In Italian:

[A3] - Rigon, R., Influenza della morfologia di un bacino montano sui caratteri della risposta idrologica, Atti del XXXII Convegno di Idraulica e di Costruzione idrauliche, Firenze, 1992.

[A7] - Rigon, R., Formulazione del trasporto per tempi di residenza: un‘alternativa ai modelli di pioggia efficace nel calcolo della risposta idrologica, Atti del XXIV Convegno di Idraulica e di Costruzione idrauliche, Napoli, 1994

[A9] - Rigon, R., P. D’Odorico e L. Parra, Metodi geomorfologici di inferenza della risposta idrologica, Atti del XXV Convegno di Idraulica e di Costruzioni idrauliche, Torino, 1996.

[A13] - D’Odorico, P., M. Marani e R. Rigon, Questioni geomorfologiche e previsione delle piene nei bacini fluviali, Atti XXVI Convegno di Idraulica e Costruzioni Idrauliche, Vol II, 73, 1998

[A24] - Rinaldo A., M. Marani, A. Fornasiero, G. Botter, S. Silvestri, A. Bellin, Rigon R., M. Ferri, F. Baruffi, A. Rusconi. Modelli geomorfologici - Montecarlo per la valutazione del tempo di ritorno delle piene fluviali: fiume Brenta chiuso a Bassano. Atti del XXVIII Convegno di Idraulica e Costruzioni Idrauliche, vol. 1, pp.271-278, 2002

Old water contribution to streamflow: Insight from a linear Boussinesq model

This is a paper by Aldo Fiori one one of the most interesting issues in Hydrology, just appeared in Water Resources Research (Fiori, 2012). I already talk on this issue in the blog one year ago or so. Now Aldo comes back with a new paper which I will start to read avidily.

This is an excerpt from his  introduction, with some references:

"The understanding of the main physical processes which rule runoff generation in catchments is limited by the so-called ‘‘old water paradox.’’ The latter states that a (sometimes significant) fraction of the runoff volume after a rainfall event is pre-event, or ‘‘old.’’ Experiments with passive tracers suggest that most of the water contributing to stormflow is pre-event [Neal and Rosier, 1990; Sklash, 1990; McDonnell, 2003; Kirchner, 2003; Botter et al., 2010], with percentages often close to 75% of the total flow [Buttle, 1994]. This experimental evidence, which seems to invalidate most of the existing rainfall-runoff models, have been explained by means of a few mechanisms [Beven, 2002]. Among the latter is the propagation of pressure waves with high celerity [e.g., Beven, 1981], the capillary fringe-ridging hypothesis [see, e.g., Sklash and Farvolden, 1979 ; Gillham, 1984 ; McDonnell, 1990 ; Cloke et al., 2006; Fiori et al., 2007], and transmissivity feedback or macropore flow [McDonnell and Buttle, 1998]. The issue is still a matter of debate [McDonnell et al., 2010], and the principal physical processes controlling the release of old water and the partition between old and new water are still poorly understood. This problem has a crucial impact on several processes of interest in hydrology, for example, the development of meaningful rainfall-runoff models and the analysis of solute transport in catchments, which is often performed in terms of travel time distribution [e.g., McGuire and McDonnell, 2006]. Among the processes which may control the age of water we point here at the ‘‘potentially under-appreciated importance of old ground- water input to streams,’’ and ‘‘we thus need to have a better understanding of where and when old groundwater inputs are important’’ (both statements by McDonnell et al. [2010])."

On the side of pressure wave, I would add the reference to the work by Rasmussen et al., (2000) which refers to an experiment of percolation through saprolite, and the  paper by Torres et al. (1998) where these pressure waves are seen in the field (see also the Commentary by Torres 2002).

Certainly in producing a retardation in travel times concurs also the slowness of flow in unsaturated conditions (e.g. Lanni et al., 2012a,b which apparently talk about shallow landslides, but, in fact, talk also about hillslopes' residence time) but still they do not explain enough of the very large age of water in streams.

However,  measuring travel times and interpreting them is not all that easy (e.g. Rinaldo et al. 2011, with an important reference to Niemi, 1977), and maybe some measurements should be rethought.

Talking about vague references (to me, obviously), some work by Jean Yves Parlange, on fast propagation of water in soils, could be interestingly related to this topic.  But this is just a stub for future literature investigations (for instance the paper on sound waves referred here should be related to the fast propagation of pressure waves).

In any case, again a lot of stuff to read.

References

Beven, K. (1981), Kinematic subsurface stormflow, Water Resour. Res., 17, 1419–1424.

Beven, K. J. (2002), Rainfall-Runoff Modelling, The Primer, 360 pp., John Wiley, Hoboken, N. J.

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