Meeting Roger Moussa research

which I do not have time yet to comment broadly (post should be considered a stub). In the last two months Roger Moussa, Stuart Lane, and Marco Borga came and gave a seminar in Trento. The topic were all centered about the river catchments but everyone of the lecturer had a different accent.
Here it is a little of summary of Moussa talk.

Roger was mainly concerned with agricultural catchments, and their peculiarities. There were two or three themes to enlighten:
 - agricultural catchment derives from a deep intervention of the natural hydrography, and this obviously affects the hydrological response. In one of his paper he does some virtual experiments in which he compares the hydrologic response of the real catchment with the supposed natural one.
 - the variation of hydraulic properties of soil after tillage, and in general, after the agricultural practice. - the role of vegetation, epitomized by a banano cultivation, in preferential collecting the rainfall.

 Here it is the abstract of Roger's seminar: Model calibration and analysis of model performance :Case of distributed hydrological modelling of flood events from the plot to the catchment scale.

 "During the last decades, flood events which occurred in the Mediterranean zone are a major threat to human life and infrastructures. This situation handicaps development, necessitating the use of modeling approaches for prediction of sites prone to flooding, planning of damage minimization activities, and for environmental prediction of the impact on runoff, erosion and pollutant transport. Moreover, hydrological processes are largely variable in space due to human impact in agricultural and urban zones, causing hydrological discontinuities such as channels, field limits, drains, and tillage practices. MHYDAS (Modélisation HYdrologique Distribuée des AgroSystèmes / Distributed Hydrological Modelling of AgroSystems), a physically based distributed hydrological model, was especially developed to model flood events taking into account hydrological discontinuities. Application cases are shown on catchments from the plot scale (1000 m²) to large scales (2000 km²) in various agro-hydro-climatic conditions : i) to assess the optimal subdivision into sub-catchments for distributed hydrological modeling applications; ii) to study the spatio-temporal distribution of rainfall and the soil hydrodynamic properties; iii) to define a parameterisation strategy, and to compare various multi-objective functions and analyze the significance of well-known criteria functions."

With Roger we actually discussed a little more about other issues regarding the topic of comparing data and simulations.  Some considerations derived:

- Discharge data ata should always be checked independently from the outcomes of the model.  To verify their correlation structure, and their statistics, i.e. lag times (discharges from rainfall), centroids, time to peak, volumes, runoff coefficients, etc.

- Be conscious of which data you really use, and distinguish model also for their use of data: do they use vegetation information ? Soil information ? What is really distributed in your catchment data set ?

- Do not use excess of distributed information that you cannot justify.

- Keep in mind which are the objective of your modeling. Improving discharge prediction ? Improving calibration methods ? What else ?

- Do not give for granted that the first period in a data set is the calibration one.  Sometimes invert calibration and validation !!!

- Always use  objective indicator of godness of fit (GOF): but be aware that they can hide some important features, and the best GOFs performances not always means a bette prediction (Roger has a paper on it).


Finally he also, as well as me, felt the need for an infrastructure to support modeling. His institution promote Openfluid, a C++ framework.


Roger's bibliography:

Chahinian N, Moussa R, Andrieux P, Voltz M. 2005. Comparison of infiltration models to simulate flood events at the field scale. Journal of Hydrology, 306: 191-214.

Chahinian N, Voltz M, Moussa R, Trotoux G. 2006. Assessing the impact of hydraulic properties of a crusted soil on overland flow modelling at the field scale. Hydrological Processes, 20 : 1701-1722.

Charlier JB, Cattan P, Moussa R, Voltz M. 2008. Hydrologic behaviour and modelling of a volcanic tropical cultivated catchment. Hydrological Processes, 22 : 4355-4370.

Charlier JB, Moussa R, Cattan P, Cabidoche YM, Voltz M. 2009. Modelling runoff at the plot scale taking into account rainfall partitioning by vegetation: application to stemflow of banana (Musa spp.) plant. Hydrology and Earth System Sciences, 13, 2151-2168.

Cheviron B, Gumiere SJ, Le Bissonnais Y, Moussa R, Raclot D, 2010. Sensitivity analysis of distributed erosion models: Framework. Water Resources Research, vol. 46, W08508, 13 p.

Gomez-Delgado F, Roupsard O, Le Maire G, Taugourdeau S, Bonnefond JM, Perez A, van Oijen M, Vaast P, Rapidel B, Voltz M, Imbach P, Harmand JM, Moussa R. 2011. Modelling the hydrological behaviour of a coffee agroforestry basin in Costa Rica. Hydrology and Earth System Sciences, 15, 369–392.

Gumiere S, Raclot D, Cheviron B, Davy G, Louchart X, Fabre JC, Moussa R, Le Bissonnais Y, 2011. MHYDAS-Erosion a distributed single-storm water erosion model for agricultural catchment. Hydrological Processes,  in Press .

Lagacherie P, Rabotin M, Colin F, Moussa R,  Voltz M, 2010. Geo-MHYDAS: A  discretization procedure of Cultivated Landscapes for distributed hydrological modelling. Computers & Geosciences, 36 (2010) 1021–1032.

Moussa R. 2008a. Effect of channel network topology, basin segmentation and rainfall spatial distribution on the GIUH transfer function. Hydrological Processes, 22 : 395-419

Moussa R. 2008b. What controls the width function shape, and can it be used for channel network comparison and regionalization?. Water Resources Research, 44, 20 p., W08456.

Moussa R. 2010. When monstrosity can be beautiful while normality can be ugly: assessing the performance of event-based flood models. Hydrological Sciences Journal, 55(6), 1074 – 1084.

Moussa R, Chahinian N. 2009. Comparison of different multi-objective calibration criteria using a conceptual rainfall-runoff model of flood events. Hydrology and Earth System Sciences, 13, 519-535.

Moussa R, Voltz M, Andrieux P. 2002. Effects of the spatial organization of agricultural management on the hydrological behaviour of a farmed catchment during flood events. Hydrological Processes 16 : 393-412 (DOI: 10.1002/hyp.333).

Moussa R, Chahinian N, Bocquillon, C. 2007. Distributed hydrological modelling of a Mediterranean mountainous catchment - model construction and multi-site validation. Journal of Hydrology 337: 35-51.

Moussa R, Colin F, Rabotin M. 2011. Invariant morphometric properties of headwater subcatchments. Water Resources Research, in Press.

 Bibliography of others will follow. Anyone of them is a champion in publishing. So there is lot to read.

I really loved his computers which I used since the beginning of my reasearch life

since 89, I guess. I had very little trouble with them, and could dedicate the time that others were spending to fix their motherboards, cards, software and hardware to do hydrology, or just enjoy life.

He is narating here:



And talking:



What he accomplished, in the word of Anton Ego:

Yes, I think I do. After reading a lot of overheated puffery about your new cook, you know what I'm craving? A little perspective. That's it. I'd like some fresh, clear, well seasoned perspective. Can you suggest a good wine to go with that?

R.I.P.

Presentation about landslides triggering given at IWL2

I was trying to convey the idea that landslide triggering is tricky and complex. But simple settings have a simple behavior, especially when we look at statistics. Nevertheless complexity is behind the curtain. The right one, I mean, that depends on vegetation distribution, soils use, heterogenous soil depth, and the fact that landslides are a very local phenomenon.

Here you will find the presentation. Hopefully a paper will come out from it.

On the relative role of upslope and downslope topography for describing water flowpath and storage dynamics: a theoretical analysis

Hydrological studies have shown, for many years now, that catchments organize themselves. The signals that go into a basin (in our case rainfall) look different to those that come out of it (i.e.river discharge), due to hydrodynamics, flow path geometry, and topology effects (e.g. Rinaldo et al., 1991, 1995; D’Odorico and Rigon, 2003; Botter and Rinaldo, 2003). However, tracer campaigns (e.g.,isotope studies) and their interpretation have shown that the whole dynamic is more complex than first naively expected (e.g., Soulsby et al., 2009), and that “the total catchment storage is likely to be much greater than the dynamic storage inferred by hydrometric data alone, and needs to be invoked to explain some nonlinearity in rainfall-runoff responses in relation to antecedent conditions” (Birkel et al., 2011). For instance, in many catchment settings, dynamically expanding and contracting riparian saturation zones can play a major role in producing the real (proper) travel time of water (Fiori and Russo, 2008, Russo and Fiori, 2008, Tetzlaff et al., 2007). At the same time, the small-scale topographic variations in the bedrock and the filling and spilling of water into depressions and over the bedrock micro-topography (Tromp-van Meerveld and McDonnell, 2006; Hopp and McDonnell, 2009) can control the subsurface flow routing. Several researchers have also reported the role played by geological landscape features. The lack of confining layers in jointed and fractured bedrock and the local variations in its hydraulic conductivity may strongly influence water storage dynamics in the overlying soil layer (Pierson, 1977; Wilson and Dietrich, 1987; Montgomery et al., 2002).
The overall model of the spatial structure that leads to flow and storage organization (something that is crucial to prioritizing what to do and where to do it in river catchments) brings, therefore, to a system of reservoirs which, uphill, can be defined on the basis of bedrock geometry and permeability, and, close to the riparian zones, on the basis of various storage areas that interact dynamically with the stream network.

In this paper, we analyze the case where topography (i.e., lateral flow) is recognized as the predominant control for subsurface flow mechanisms. This is generally the case in mountain regions with moderate to steep topography (Tetzlaff et al., 2009a) where a shallow (highly conductive) soil layer lies on an impervious bedrock substrate (Western et al., 2004). Under these conditions, the availability of storage for water is limited almost exclusively to soil drainable porosity (e.g., Hilberts et al., 2005; Cordano and Rigon, 2008), complex riparian dynamics are less important, and can, as a first approximation, be neglected. Moreover, elevation potential dominates total hydraulic potential, and thus topography represents a good proxy (in theory) for water flow paths (e.g., Seibert et al., 2007; McNamara et al., 2005) and spatial patterns of soil moisture (e.g., Schmidt and Persson, 2003).
The fact that elevation potential dominates total hydraulic potential led to assume that local topography could represent a good way for describing hydrological processes at the hillslope/catchment scale.
Upon this belief, topographic indices have been developed and used as proxies to represent the role of topography on subsurface flow paths and soil-water storage dynamics. However, over the years these indices proved to be insufficient to explain an increasing number of case studies (e.g. Burt and Butcher, 1986; Western et al., 1999; Seibert et al., 1997) and brought to several reconsiderations of the matter, of which we briefly report.

The paper is available on Hydrological Processes Preview, and is the same paper presented in a previous post when submitted.

References

Birkel C, Tetzlaff D, Dunn SM, Soulsby C. 2011. Using time domain and geographic source tracers to conceptualise streamflow generation processes in lumped rainfall-runoff models. Water Resources Research. 47. W02515. Doi:10.1029/2010WR009547.

Botter, G, Rinaldo, A. 2003. Scale effect on geomorphologic and kinematic dispersion. Water Resour. Res. 39(10): 1286. Doi:10.1029/2003WR002154.
Burt TP, Butcher DP. 1985. Topographic controls of soil moisture distributions. J. Soil Sci. 36: 469 – 486.

Cordano E, Rigon R. 2008. A perturbative view on the subsurface water pressure response at hillslope scale, Water Resour. Res. 44. W05407. Doi:10.1029/2006WR005740.

D’Odorico P, Rigon R. 2003. Hillslope and channel contributions to the hydrologic response, Water Resour. Res. 39(5): 1113–1121. Doi:10.1029/2002WR001708.

Fiori A, Russo D. 2008. Travel Time Distribution in a Hillslope: Insight from Numerical Simulations. Water Resour. Res. 44. W12426. Doi:10.1029/2008WR007135.

Hilberts A, Troch P, Paniconi C. 2005. Storage-dependent drainable porosity for complex hillslopes. Water Resour. Res. 41. W06001. Doi:10.1029/2004WR003725.

Hopp L, McDonnell JJ. 2009. Connectivity at the hillslope scale: Identifying interactions between storm size, bedrock permeability, slope angle and soil depth. Journal of Hydrology 376(3-4): 378-391.DOI: 10.1016/j.jhydrol.2009.07.047

McNamara P, Chandler D, Seyfried M, Achet S. 2005. Soil moisture states, lateral flow, and streamflow generation in a semi-arid, snowmelt-driven catchmen. Hydrol. Process. 19: 4023– 4038.

Montgomery DR, Dietrich WE, Heffner JT. 2002. Piezometric response in shallow bedrock at CB1: Implications for runoff generation and landsliding. Water Resour. Res. 38(12): 1274. Doi:10.1029/2002WR001429.

Pierson TC. 1977. Factors controlling debris-flow initiation on forested hillslopes in the Oregon Coast Range, Ph.D. dissertation, 166 pp., Univ. of Wash., Seattle.

Rinaldo A, Marani A, Rigon R. 1991. Geomorphological dispersion. Water Resour. Res 27(4): 513–525.

Rinaldo A, Vogel GK, Rigon R, Rodriguez-Iturbe I. 1995. Can one gauge the shape of a basin?. Water Resour. Res. 31(4):1119–1127.

Russo D, Fiori A. 2008. Equivalent Vadose Zone Steady-State Flow: An Assessment its Capability to Predict Transport in a Realistic Combined Vadose Zone - Groundwater Flow System. Water Resour. Res. 44. W09436. Doi:10.1029/ 2007WR006170.

Seibert J, Bishop KH, Nyberg L. 1997. A test of TOPMODEL's ability to predict spatially distributed groundwater levels. Hydrological Processes 11: 1131–1144.

Seibert J, McGlynn BL. 2007. A new triangular multiple flow-direction algorithm for computing upslope areas from gridded digital elevation models. Water Resour. Res. 43. W04501, Doi:10.1029/2006WR005128. 

Schmidt F, Persson A. 2003. Comparison of DEM Data Capture and Topographic Wetness Indices. Precision Agricolture 4: 179-192.

Soulsby C, Tetzlaff D, Hrachowitz M. 2009. Tracers and transit times: Windows for viewing catchment scale storage?. Hydrological Processes 23: 3503-3507.

Tetzlaff D, Soulsby C, Bacon PJ, Youngson AF, Gibbins CN, Malcolm IA. 2007. Connectivity between landscapes and riverscapes—A unifying theme in integrating hydrology and ecology in catchment science?. Hydrological Processes 21: 1385–1389

Tetzlaff D, Seibert J, McGuire KJ, Laudon H, Burns DA, Dunn SM, Soulsby C. 2009a. How does landscape structure influence catchment transit times across different geomorphic provinces?. Hydrological Processes 23: 945 – 953.

Tromp-van Meerveld HJ, McDonnell JJ. 2006. Threshold relations in subsurface stormflow: 2. The fill and spill hypothesis. Water Resour. Res. 42(2). DOI: 10.1029/2004WR003800.

Western AW, Grayson RB, Blöschl G, Willgoose GR, McMahon TA. 1999. Observed spatial organization of soil moisture and its relation to terrain indices. Water Resour. Res. 35 (3). DOI: 10.1029/1998WR900065.

Western AW, Zhou SL, Grayson RB, McMahon TA, Bloschl G, Wilson DJ, 2004. Spatial correlation of soil moisture in small catchments and its relationship to dominant spatial hydrological processes. Journal of Hydrology 286 (1-4): 113-134. Doi: 10.1016/j.jhydrol.2003.09.014.

Wilson CJ, Dietrich WE. 1987. The contribution of bedrock groundwater flow to storm runoff and high pore pressure development in hollows, in Erosion and Sedimentation in the Pacific Rim, IAHS Publ., vol. 165, edited by R. L. Beschta et al.: 49–60, Int. Assoc. of Hydrol Sci., Wallingford, UK

A new version of GEOtop with a Draft User Manual available

Dear all,


we have updated GEOtop to the milestone version 1.45.


It is the result of the great effort of Stefano Endrizzi and Stephan
Gruber by the University of Zurich.


This new version includes:
- simplified I/O based on keywords
- other important debugged problems
The version is positioned in the trunk of the SVN in Bozen/Bolzano:
https://dev.fsc.bz.it/private/repos/geotop/trunk/GEOtop_1.45

Furthermore, the draft version of the USERS MANUAL is ready to be
downloaded from the link:
http://cl.ly/2X24303x3b0x293l112M
Please let me know your comments on the manual in order to improve the
final version.

For who who did not read previous post about, GEOtop is a process-based hydrological models that, given the meteorological data and soil parameters in input, allows to know in
each point of the domain and in each time step:

the evaporation of the soil
the transpiration of the vegetation
the radiation and energy fluxes at the Earth surface
the pore water pressure in the soil
the water-table movements in saturated zone
the water discharge in an outlet
the temperature and ice content in the soil
the height and density of the snow
the mass balance of a glacier

Furthermore, thanks to the post-process software GEOtopFS (GEOtop
Factor of Safety), it calculates:

the dynamic probability of slope instability during a precipitation
event


The wiki-page is not completely up-to-date. But we are working to get it ready.

A quick guide to writing a solid peer review

This recent contribution by Nicholas and Gordon can be found here from the EOS AGU Journal of July the 12th. This below the flowchart:

The paper is really a good guide. However, it does not tell all the truth. What moves me as a reviewer (not considering that I accepted duties as associate editor or editor) is the curiosity to know a piece of exciting research a little before the rest of the guys. On the other hand, the expectations, are very often, not maintained by the incoming papers, and very few reward the efforts. However, this allows you to know what people thinks is important today, as opposed to what you (me) think it is, and is all experience gained. This can be summarized as: reviewing keep you close to active research.

A second aspect is that rarely you are completely expert of the subject treated. Most of the details of a paper from Authors you did not frequent before (on a topic you supposedly know enough), refers to paper and methods that you do not completely possess. This add sweat to your work, since you need to search and look to other papers to review one. The positive of this that you increase your knowledge. And the efforts are usually paid back with self-consciousness of what you know of a subject.

With time experience and erudition grow, and therefore the task or reviewing becomes easier, because you start to recognize the presence or absence of the structural patterns that makes of a paper a good paper. Outstanding paper are obviously matter or the science they contain.

Now, going back to my reviews.

Doing Ph. D. Studies

I found this nice and ironic presentation of what a Ph.D is. It is entitled Ph.D. School in picture.

There you will find the explanation of the mysterious figure above. Looking at the related post is also interesting. For instance at: Successful Ph.D. students.
A other pearl from the same Author is the post about getting tenure. Worth to read carefully to the end.