This is indeed a very strange blog. All feed up the same day, February 18, 2011 with 54 post about various data set. Two at least did not escape my attention.
The global Evapotranspiration map made by Antonio Trabucco for the CGIAR-CSI :
Also the reference to the global DEM derived from the satellite Aster measurements is of interest for hydrologists, and according to some paper are better than SRTM data.
These are not the only good data you can find there!
Two other source of information about GIS data are remarkable: those from Robert T Wilson and those one can find in Tomislav Hengl wiki Spatial-Analyst at the page of global data sets. Another source of interesting data is here where you can find addresse a map of runoff data by NCAR/UCAR and some interesting considerations.
My reflections and notes about hydrology and being a hydrologist in academia. The daily evolution of my work. Especially for my students, but also for anyone with the patience to read them.
Saturday, December 31, 2011
Naming Rivers
This is a variation on the themes inspected by Boetti and his wife in their "The thousand rivers". In this case, what is inspected is the name with which the river are addressed. Terms like "fork", "canal". Beside, the technology is outstanding. Below, please find the Great Britain.
The original sites, images, and explanation regarding how the maps where realized, can be found at: http://spatialanalysis.co.uk/2011/08/naming-rivers-and-places/
The blog itself is very interesting to follow.
The case of United States is:
The blog itself is very interesting to follow.
Friday, December 9, 2011
Open Source Software and Intellectual Properties
People often think that using an Open Source License for Software left freedom for any behavior. In fact, this is not the case. Here you can find a presentation by Bruno Lowagie where he discussed the related issues and obligations.
Open source requires ethics, is a demanding exercise, and it is not about robbery.
Open source requires ethics, is a demanding exercise, and it is not about robbery.
Wednesday, November 30, 2011
WRR Editors' choice award
From this year AGU established the Water Resources Research Editors' award, as reported in the AGU Hydrology Section Newsletter, an interesting reading per se. As Praveen Kumar writer: "The selection is
made by the WRR Editors based on technical significance, novelty, originality, presentation, and broader implications of the publication". And here they are the nominees (less than 1% of the papers published by the journal):
• Julien J. Harou, Josué Medellín-Azuara, Tingju Zhu, Stacy K. Tanaka, Jay R. Lund, Scott Stine,
Marcelo A. Olivares, and Marion W. Jenkins, “Economic consequences of optimized water management for a prolonged, severe drought in California” (doi:10.1029/2008WR007681).
• Luis Samaniego, Rohini Kumar, and Sabine Attinger, “Multiscale parameter regionalization of
a grid based hydrologic model at the mesoscale” (doi:10.1029/2008WR007327).
• Elizabeth H. Keating, John Doherty, Jasper A. Vrugt, and Qinjun Kang, “Optimization and
uncertainty assessment of strongly nonlinear groundwater models with high parameter dimensionality” (doi:10.1029/2009WR008584).
• Dmitri Kavetski and Martyn P. Clark, “Ancient numerical daemons of conceptual hydrological modeling: 2. Impact of time stepping schemes on model analysis and prediction” (doi:10.1029/2009WR008896).
• Lance F. W. Lesack and Philip Marsh, “River̺to̺lake connectivities, water renewal, and aquatic habitat diversity in the Mackenzie River Delta” (doi:10.1029/2010WR009607)
As any choice, it is a personal one. However, compare our own research with these papers' arguments and writing could be helpful. Just history will say if they will become benchmarks papers. Interesting to note, from the DOI that 2 of them had a quite long review process. Just the last one saw the light the same year it was submitted.
made by the WRR Editors based on technical significance, novelty, originality, presentation, and broader implications of the publication". And here they are the nominees (less than 1% of the papers published by the journal):
• Julien J. Harou, Josué Medellín-Azuara, Tingju Zhu, Stacy K. Tanaka, Jay R. Lund, Scott Stine,
Marcelo A. Olivares, and Marion W. Jenkins, “Economic consequences of optimized water management for a prolonged, severe drought in California” (doi:10.1029/2008WR007681).
• Luis Samaniego, Rohini Kumar, and Sabine Attinger, “Multiscale parameter regionalization of
a grid based hydrologic model at the mesoscale” (doi:10.1029/2008WR007327).
• Elizabeth H. Keating, John Doherty, Jasper A. Vrugt, and Qinjun Kang, “Optimization and
uncertainty assessment of strongly nonlinear groundwater models with high parameter dimensionality” (doi:10.1029/2009WR008584).
• Dmitri Kavetski and Martyn P. Clark, “Ancient numerical daemons of conceptual hydrological modeling: 2. Impact of time stepping schemes on model analysis and prediction” (doi:10.1029/2009WR008896).
• Lance F. W. Lesack and Philip Marsh, “River̺to̺lake connectivities, water renewal, and aquatic habitat diversity in the Mackenzie River Delta” (doi:10.1029/2010WR009607)
As any choice, it is a personal one. However, compare our own research with these papers' arguments and writing could be helpful. Just history will say if they will become benchmarks papers. Interesting to note, from the DOI that 2 of them had a quite long review process. Just the last one saw the light the same year it was submitted.
Tuesday, November 29, 2011
Historic and benchmark papers for hydrology up to 1980
Here the list with the links to the paper or books (especially thanks to Google digitalizations, which are apparently downloadable as pdfs) and links to wikipedia or web biographies (to be updated). I am limiting the citations to 1980 included. A you noticed I change the title, since many colleagues pointed out papers that are not strictly "hydrological" but nevertheless they changed their view on the subject.
Before 1900
A. Vallisneri, Lezione accademica intorno all'origine delle fontane, Ertz, Venezia, 1714.
(see also http://www.vallisneri.it/)
Dalton, J., Meteorological Observations and Essays (2 ed.). Harrison and Crosfield, Manchester, 1834
Mulvany, T. J. (1851) On the use of self-registering rain and flood gauges in making observations of the relations of rain fall and of flood discharges in a given catchment. Proceedings of the Institution of Civil Engineers of Ireland 4, 18–33.
Darcy, H., Les Fontaines Publiques de la Ville de Dijon, Dalmont, Paris, 1856
Gauckler P. G., 1867, Etudes Théoriques et Pratiques sur l’Ecoulement et le Mouvement des Eaux, Comptes Rendus de l’Académie des Sciences, Tome 64: pp. 818–822.
1900 - 1950
Bowen IS (1926) The ratio of heat losses by conduction and by evaporation from any water surface.
Physical Rev 27:779–787
Richards, L.A., Capillary conduction of liquids through porous mediums, Physics 1: 318-333, 1931
Sherman, L. K. (1932) Streamflow from rainfall by unit-graph method. Engineering News Record 108, 501–505.
Thornthwaite, C. W. & Holzman, B. (1939) The determination of evaporation from land and water surfaces. Monthly Weather Rev. 67, 4-11.
1900 - 1950
Green, W. H., and G. A. Ampt. 1911. Studies on soil physics. J. Agric. Sci. 4(1): 1-2
Horton, R. E. (1919) Rainfall interception. Monthly Weather Rev. 47, 603-623.
Thiessen AH (1911) Precipitation averages for large areas. Monthly Weather Report 39: 1082--1084.
Horton, R. E. (1919) Rainfall interception. Monthly Weather Rev. 47, 603-623.
Ross, C. N. (1921) The calculation of flood discharge by the use of a time contour plan. Transactions of the Institution of Engineers, Australia 2, 85–92.
Bowen IS (1926) The ratio of heat losses by conduction and by evaporation from any water surface.
Physical Rev 27:779–787
Richards, L.A., Capillary conduction of liquids through porous mediums, Physics 1: 318-333, 1931
Sherman, L. K. (1932) Streamflow from rainfall by unit-graph method. Engineering News Record 108, 501–505.
Horton, R., 1933. The role of infiltration in the hydrological cycle, Trans., Am. Geophysical Union, 14, 446-460.
Thornthwaite, C. W. & Holzman, B. (1939) The determination of evaporation from land and water surfaces. Monthly Weather Rev. 67, 4-11.
Theis CV (1940), The source of water derived from wells: essential factors controlling the response of an aquifer to development. Civ Eng 10 (5):277–280
Horton, R. E., Erosional development of streams and their drainage basins: hydro-physical approach to quantitative morphology, Geological Society of America Bulletin 56 (3): 275-370, 1945.
Penman, H.L. 1948. Natural evaporation from open water, bare soil, and grass. Proc. Roy. Soc. London A193:120-146.
Thornthwaite, C. W. (1948) An approach toward a rational classification of climate. Geographical Rev. 38, 55-94.
1951 - 1960
Penman, H.L. 1948. Natural evaporation from open water, bare soil, and grass. Proc. Roy. Soc. London A193:120-146.
Thornthwaite, C. W. (1948) An approach toward a rational classification of climate. Geographical Rev. 38, 55-94.
Terzaghi, K., 1950. Mechanics of landslides, in Paige, S., Application of Geology to Engineering Practice (Berkey Volume) Geological Society of America, Boulder, Colorado, p. 83-123.
1951 - 1960
Swinbank, W. C. (1951) The measurement of vertical transfer of heat and water vapour and momentum in the lower atmosphere with some results. J. Meteorology 8, 135-145.
Leopold, Luna B., and Maddock, T. Jr., 1953, The Hydraulic Geometry of Stream Channels and Some Physiographic Implications, U.S. Geological Survey Professional Paper 252, 56p.
Leopold, Luna B., and Maddock, T. Jr., 1953, The Hydraulic Geometry of Stream Channels and Some Physiographic Implications, U.S. Geological Survey Professional Paper 252, 56p.
Schumm, S.A., 1956, Evolution of drainage systems and slopes in badlands at Perth Amboy, New Jersey: Geological Society of America Bulletin, v. 67, p. 597-646.
Dooge, J. C. I. (1959) A general theory of the unit hydrograph, Journal of Geophysical Research 64, 241–256.
Linsley, R. K. & Crawford, N. H. (1960) Computation of a synthetic streamflow record on a digital computer. International Association of Scientific Hydrology Publication 51, 526–53
Hack, J.T., and Goodlett, J.C., 1960, Geomorphology and forest ecology of a mountain region in the central Appalachians: U.S. Geological Survey Professional Paper 484, 84 p.
Kalman, R. E.,1960. A new approach to linear filtering and prediction problems. Transactions of the ASME, Journal of Basic Engineering, 82: 35–45.
Bergeron, T., 1960, Operation and results of ‘Project Pluvius’, in, Physics of Precipitation: American Geophysical Union Monograph no. 5. p. 152-157.
Hack, J.T., and Goodlett, J.C., 1960, Geomorphology and forest ecology of a mountain region in the central Appalachians: U.S. Geological Survey Professional Paper 484, 84 p.
Kalman, R. E.,1960. A new approach to linear filtering and prediction problems. Transactions of the ASME, Journal of Basic Engineering, 82: 35–45.
Theil, H. e van de Panne, C., 1960. Quadratic programming as an extension of conventional quadratic maximisation. Manage. Sci., 7: 1-20
1961 - 1970
Kalman, R. E. e Bucy, R. S., 1961. New results in linear filtering and prediction theory. Transactions of the ASME – Journal of Basic Engineering, Series 83D: 95–108.
Hewlett J.D., and A. R. Hibbert, Moisture and Energy Conditiond within a Sloping Soil Mass during drainage, Jour. Geophys. Res., Vol 68., No. 4, 1963
Rubin, J., and Steinhardt, R., 1963. Soil water relations during rain infiltration: 1. Theory. Soil Science Society of America Proceedings, v. 27, p. 246-251.
Betson, R. P. (1964), What is watershed runoff ? J. Geophys. Res. 69(8), 1541-1552
Henderson, F. M. & Wooding, R. A. (1964) Overland flow and groundwater flow from a steady rainfall of finite duration. Journal of Geophysical Research 69, 1531–1540.
Craig H, and L. I. Gordon, Deuterium and oxygen 18 variations in the ocean and the marine atmosphere, in Stable Isotopes in Oceanographic Studies and Paleotemperatures, edited by E. Tongiorgi, CNR, Pisa 1965
Monteith, J. L. (1965) Evaporation and environment. In: The State and Movement of Water in Living Organisms (Proc. 19th Symp. Soc. Exp. Biol., Swansea 1964), 205-234. Academic Press, for The Society for Experimental Biology, UK.
Henderson, F. M. & Wooding, R. A. (1964) Overland flow and groundwater flow from a steady rainfall of finite duration. Journal of Geophysical Research 69, 1531–1540.
Craig H, and L. I. Gordon, Deuterium and oxygen 18 variations in the ocean and the marine atmosphere, in Stable Isotopes in Oceanographic Studies and Paleotemperatures, edited by E. Tongiorgi, CNR, Pisa 1965
Monteith, J. L. (1965) Evaporation and environment. In: The State and Movement of Water in Living Organisms (Proc. 19th Symp. Soc. Exp. Biol., Swansea 1964), 205-234. Academic Press, for The Society for Experimental Biology, UK.
Whipkey, R. Z. (1965) Subsurface stormflow from forested slopes. Bull. Int. Assoc. Sci. Hydrol. 10(2), 74-85
Wooding, R. A., 1965. A hydraulic modeling of the catchment-stream problem. 1. Kinematic wave theory. Journal of Hydrology, 3, 254-267.
Hewlett, J. D. & Hibbert, A. R. (1967) Factors affecting the response of small watersheds to precipitation in humid areas. In: International Symposium on Forest Hydrology (ed. by W. E. Sopper &H. W. Lull), 275-290. Pergamon, Oxford, UK
M. J. Kirkby & R. J. Chorley (1967): Throughflow, overland flow, and erosion , International Association of Scientific Hydrology. Bulletin, 12:3, 5-21
Mandelbrot, B.B., and J.R. Wallis, Noah, Joseph and operational Hydrology, Water Resour. Res, Vol 4, No 5, 1968
Ragan, R. M. (1968) An experimental investigation of partial area contributions. In: Hydrological Aspects of the Utilization of Water, Reports and Discussions (Proc. IAHS Assembly at Bern), 241-251. IAHS Publ. 76.
Shreve, R.L.: Stream lengths and basin areas in topologically random channel networks, J. Geol., 77, 397--414, 1969
Cunge, J. A., 1969. On the subject of flood propagation computation method (Muskingum method), J. Hydr. Res., 7(2): 205–230.
Mandelbrot, B.B., and J.R. Wallis, Robustness of the Rescaled Range R/S in the measurement of Noncyclic long run statistical dependence,Water Resour. Res, Vol 5, No 5, 1969
Philip, J.R. "Theory of infiltration." (1969). Advances in Hydroscience. v. 5, p. 215-296
Pinder, G. F. & Jones, J. F. (1969) Determination of the ground-water component of peak discharge from the chemistry of total runoff. Water Resour. Res. 5(2), 438-445.
Dunne, T. & Black, R. D. (1970) Partial area contributions to storm runoff in a small New England watershed. Water Resour. Res. 6, 1296-1311.
Dunne, T., and Black, R.D., 1970, An experimental investigation of runoff production in permeable soils: Water Resources Research, v. 6, no. 2, p. 478-490
Mehra, R.K., 1970. On the identification of variances and adaptive Kalman filtering. IEEE Trans. Automat. Contr., Vol. AC 15:175-184.
J.E. Nash, J.V. Sutcliffe, River flow forecasting through conceptual models part I — A discussion of principles, Journal of Hydrology Volume 10, Issue 3, April 1970, Pages 282-290
1971 - 1980
Weyman, D. R. (1970) Throughflow on hillslopes and its relation to the stream hydrograph. Bull. Int. Assoc. Sci. Hydrol. 15, 25-33.
Freeze, R. A. (1971), Three-dimensional, transient, saturated–unsaturated flow in a groundwater basin.
Water Resources Research 7, 347–366.
Freeze, R. A. (1972), Role of subsurface flow in generating surface runoff: 1. Base flow contributions to channel flow. Water Resources Research 8, 609–623
Freeze, R. A. (1972), Role of subsurface flow in generating surface runoff: 2. Upstream source areas.
Water Resources Research 8, 1272–1283.
Priestley, C. H. B. & Taylor, R. J. (1972) On the assessment of surface heat flux and evaporation using large scale parameters. Monthly Weather Rev. 100, 81-92.
Freeze, R. A. (1971), Three-dimensional, transient, saturated–unsaturated flow in a groundwater basin.
Water Resources Research 7, 347–366.
Eagleson, P. S. (1972), Dynamics of flood frequency, Water Resour. Res., 8(4), 878–898, doi:10.1029/WR008i004p00878.
Freeze, R. A. (1972), Role of subsurface flow in generating surface runoff: 2. Upstream source areas.
Water Resources Research 8, 1272–1283.
Priestley, C. H. B. & Taylor, R. J. (1972) On the assessment of surface heat flux and evaporation using large scale parameters. Monthly Weather Rev. 100, 81-92.
McNaughton, K. G.; Black, T. Andrew. 1973. Study of Evapotranspiration from a Douglas Fir Forest Using the Energy Balance Approach. Water Resources Research 9(6) 1579-1590 dx.doi.org/10.1029/WR009i006p01579
Dooge J.C.I., Linear theory of hydrologic systems (Technical bulletin / United States Department of Agriculture) Agricultural Research Service, U.S. Dept. of Agriculture, 1973
Jarvis, P. G. (1976) The interpretation of the variations in leaf water potential and stomatal conductance found in canopies in the field. Phil. Trans. Royal Soc. London B 273, 593-610.
Wood, E. F. (1976) An analysis of the effects of parameter uncertainty in deterministic hydrologic models. Water Resources Research 12, 925–932.
Mualem, Y., A new model predicting the hydraulic conductivity of unsaturated porous media. Water Resour. Res. 12:513–522, 1976
Matalas, N. C. e Wallis, J. R., 1973. Eureka! It fits a Pearson type 3 distribution, Water Resour. Res., 9(2): 281–289.
Price, R. K., 1973. Variable Parameter Diffusion Methods for Flood Routing, Rep INT 115, Hydraulics Research Station, Wallingford, Tech. Report
Wyman, D.R., 1973. Measurements of the downslope flow of water in a soil, Journal of Hydrology, 20, 267-288.
Zawadzki, I. I., 1973. Statistical Properties of Precipitation Patterns., J. Appl. Meteor., vol. 12, Issue 3, pp.459-472
Feddes, R. A., E. Bresler, and S. P. Neuman (1974), Field test of a modified numerical model for water uptake by root systems,Water Resour. Res., 10(6), 1199–1206, doi:10.1029/WR010i006p01199.
Campbell, R.H., 1975. Soil slips, debris flows, and rainstorms in the Santa Monica Mountains and vicinity, southern California: U.S. Geological Survey Professional Paper 851, 51 p.
Feddes, R.A., Kowalik P., Kolinska-Malinka, Zaradny, Simulation of field water uptake by plants using a soil water dependent root extraction function, Journal of Hydrology Volume 31, Issues 1-2, September 1976, Pages 13-26
Wood, E. F. (1976) An analysis of the effects of parameter uncertainty in deterministic hydrologic models. Water Resources Research 12, 925–932.
Mualem, Y., A new model predicting the hydraulic conductivity of unsaturated porous media. Water Resour. Res. 12:513–522, 1976
Harr, R. D. (1977) Water flux in soil and subsoil on a steep forested slope. J. Hydrol. 33, 37-58.
Young, P.C. e Whitehead P., 1977. A recursive approach to time-series analysis for multivariable systems. International Journal of Control 25(3): 457-482.
Anderson, M. G. & Burt, T. P. (1978) The role of topography in controlling throughflow generation. Earth Surf. Processes 3, 331-344.
Clapp R.B., and G. M. Hornberger, Empirical Equation for Some Soil Hydraulic Properties, Water Resour. Research, vol 14, No 4, 1978
Clapp R.B., and G. M. Hornberger, Empirical Equation for Some Soil Hydraulic Properties, Water Resour. Research, vol 14, No 4, 1978
Eagleson, P. S. (1978), Climate, soil, and vegetation: 1. Introduction to water balance dynamics, Water Resour. Res., 14(5), 705–712, doi:10.1029/WR014i005p00705
Eagleson, P. S. (1978), Climate, soil, and vegetation: 2. The distribution of annual precipitation derived from observed storm sequences, Water Resour. Res., 14(5), 713–721, doi:10.1029/WR014i005p00713.
Beven., K. J., M.J.. Kirkby, A physically based, variable contributing area model of basin hydrology, Hydrological Sciences bulletin-des Sciences Hydrologiques, 24, 1,3/1979
Mosley, M. P. (1979) Streamflow generation in a forested watershed, New Zealand. Water Resour Res. 15(4), 795-806.
Rodríguez-Iturbe I, Valdés JB, 1979. The geomorphologic structure of the hydrologic response. Water Resources Research, 15, 1117-1142.
Shuttleworth, W. J. & Calder, I. R. (1979) Has the Priestley-Taylor equation any relevance to forest evaporation? J. Appl. Met. 18, 639-646.
Sklash, M. G. & Farvolden, R. N. (1979) The role of groundwater in storm runoff. J. Hydrol. 43, 45-65.
Caine, N., 1980, The rainfall intensity-duration control of shallow landslides and debris flows; Geografiska Annaler, v. 62A, p. 23-27
Spear RC and Hornberger GM (1980) Eutrophication in Peel Inlet: II. Identification of critical uncertainties via generalized sensitivity analysis. Water Research 14: 43--49.
Topp, G.C., J.L. Davis, and A.P. Annan. 1980. Electromagnetic determination of soil water content: Measurements in coaxial transmission lines. Water Resour. Res. 16:574–582.
van Genuchten, M. T., A closed-form equation for predicting the hydraulic conductivity of unsaturated soils, Soil Sci. Soc. Am. J., 44, 892– 898, 1980.
Renzo Rosso provided to me a first list of Benchmark publications, and is promising others. Also Roberto Greco, Francesco Silvestro and Stefano Orlandini, Ezio Todini and Rudy Rossetto contributed. Other papers came from Jeff McDonnel pages
To be updated with everyone's contribute.
Monday, November 28, 2011
Benchmark papers in Hydrology
Solicited by the request of a colleague, I started to to think which are the ten papers that most influenced my work as hydrologist. In the meantime I am thinking, I can point out the series that Jeff McDonnell is editing a series for IAHS, called Benchmark papers in Hydrology.
Actually, he is providing some of the papers from his website at OSU. Obviuously it would be nice to have, let say, the best historic 100 papers available. Let see what we can do.
Actually, he is providing some of the papers from his website at OSU. Obviuously it would be nice to have, let say, the best historic 100 papers available. Let see what we can do.
Monday, November 7, 2011
GeoPaparazzi is now for free in Android Market
Friday, November 4, 2011
JGrass-NewAge system first publication
JGrass-NewAGE started as a project for Adige River Basin Authority. The goal was to study, besides the peak flows, droughts, and integrating it with a database, a GIS system, still maintaining the possibility to change parts of the whole system at the necessity. Indeed all the ideas expressed in the GEOFRAME talk
at 2008 CUAHSI meeting. The pillar on which we wanted to base that effort was also to have open source, multiplatform, software, possibly developed with open source resources.
We chose to use up-to-date software engineering solutions and therefore we looked for developing software by components. As explained in another posts we first chose OpenMI and eventually OMS v3 as components framework. We are currently happy with this choice and finally the whole system seems to work incrementally.
The publication on GMD hopefully speaks by itself about what the system does (but many aspects of this enterprise will be explained in other papers). What we hope that this effort can attract the work of other producers of components to enrich the choices that users can do.
at 2008 CUAHSI meeting. The pillar on which we wanted to base that effort was also to have open source, multiplatform, software, possibly developed with open source resources.
We chose to use up-to-date software engineering solutions and therefore we looked for developing software by components. As explained in another posts we first chose OpenMI and eventually OMS v3 as components framework. We are currently happy with this choice and finally the whole system seems to work incrementally.
The publication on GMD hopefully speaks by itself about what the system does (but many aspects of this enterprise will be explained in other papers). What we hope that this effort can attract the work of other producers of components to enrich the choices that users can do.
Monday, October 24, 2011
The presentation I gave last friday in Montpellier
I was guest of Roger Moussa, and in the committee of the graduation of Dennis Hallema. My talk summarize my efforts in modeling except the recent Boussinesq equation related work. The title was
The main ideas is that we need different types of models for different scopes, and that this models can be implemented with sound informatics, and without having to redo it again from the scratch. The talk, in a sense, complements the post I made on my future research activities, by specifying the "methods" with which I will envision to do them. Many live for the motto: getting the right answer for the right reason. I support the idea that for getting the right answer you need sound models. The link under the picture will bring you to the presentation.
Tuesday, October 18, 2011
A collection of Classical and Historical Paper on Geophysical Fluid Dynamics
were posted on the web by G.K Vallis of Princeton Exeter University and can be found here. The collection includes PDFs about
It could constitute a nice reading for many.
History of Circulation or Dynamics
This section contains papers that give a historical account or interpretation of something, rather than being original research papers in themselves.Atmospheric Dynamics
This section contains papers on atmospheric dynamic and circulation. The current emphasis is on large-scale phenomena and the general circulation.Oceanic Dynamics
This section contains papers on oceanic dynamics and circulation. The current emphasis is on meso- and large-scale phenomena and the general circulation.Geophysical Fluid Dynamics
This section contains papers on dynamics in general, including geophysical fluid dynamics, turbulence theory, instabilities, etc., that is of interest to both oceanographers and atmospheric scientists. It includes papers by Coriolis, Kelvin, Taylor, Ertel, Rossby, Eady, Charney, Phillips, Welander and others.Climate, Radiation etc
Contains just a very few (at the moment) papers on climate, radiation etc., that are not particularly dynamical.It could constitute a nice reading for many.
Marco Borga's talk
Marco concentrated mainly on the interplay between rainfall and the catchment structure, as derived from the data of his Hydrate EU project. Interestingly he introduced (after, he said, initial suggestions from Jim Smith) some spatial moments (i.e. the moments of the spatial distribution of the rainfall with respect to the catchment) to quantify the storm movements during flood events. His results shows that usually storm can be considered almost stationary (on average) over the catchments, but some events are more strongly characterized than other, and especially, concentrating close to the mountain ridge. This cannot be obviously a general result, since around the World the relative position of the relative location of storm to the catchment can be different. What is of general importance is that the space-time evolution of storms can be of some relevance in producing flash floods, and that now we have a statistical tool for quantifying these storms.
Here it is Marco's abstract on his seminar: Spatial moments of catchment rainfall: rainfall spatial organisation, basin morphology and flood response
"In this talk I will introduce a general analytical framework for assessing the dependence existing between spatial rainfall organisation, basin morphology and runoff response. The analytical framework builds upon a set of spatial rainfall statistics (termed ‘spatial moments of catchment rainfall’) which describe the spatial rainfall organisation in terms of concentration and dispersion statistics as a function of the distance measured along the flow routing coordinate. The introduction of these statistics permits derivation of a simple relationship for the quantification of storm velocity at the catchment scale. The talk illustrates the development of the analytical framework and explains the conceptual meaning of the statistics by means of application to five extreme flash floods occurred in various European regions in the period 2002-2007. High resolution radar rainfall fields and a distributed hydrologic model are employed to examine how effective are these statistics in describing the degree of spatial rainfall organisation which is important for runoff modelling. This is obtained by quantifying the effects of neglecting the spatial rainfall variability on flood modelling, with a focus on runoff timing. The size of the study catchments ranges between 36 to 982 km2. The analysis reported here shows that the spatial moments of catchment rainfall can be effectively employed to isolate and describe the features of rainfall spatial organization which have significant impact on runoff simulation. These statistics provide essential information on what space–time scales rainfall has to be monitored, given certain catchment and flood characteristics, and what are the effects of space–time aggregation on flood response modeling."
Meeting with Stuart Lane
Stuart was concerned about the connectivity of the river network and to understand how the upstream connectivity affects the downstream hydrology. His message is that restoration or actions taken in a certain position of a river network can easily cause an apparently random result if the information deriving from the netwok connectivity is not accounted for. But, obviously, his arguments have the main focus on the ecology of rivers which is differently affected by the connectivity. Conceptually a step forward.
Here it is Stuart's abstract on his seminar: Catchment organisation and the flux of water and material
"In this seminar I will think about the importance of understanding catchment organization in terms of the functioning of watersheds. Tracer studies have told us, for many years, that catchments organize themselves - the signals that go in to a basin (e.g. rainfall, eroded soil) look very different to those that come out (e.g. river discharge, suspended sediment concentration). But, we have made less progress in understanding the spatial structure that leads to this organization, something that is crucial to prioritizing what to do where in river catchments. I will begin by presenting new ways of modelling this structure, and then show what this might mean: (1) for flood generation; (2) for the effects of land management upon diffuse pollution; and (3) for the watershed organization of salmonid populations. I will conclude by noting that critical to progress in this area is new forms of hydrological conceptualization and the development of innovative experiments to test such ideas."
Lane, S. N., S. M. Reaney, and A. L. Heathwaite (2009), Representation of landscape hydrological connectivity using a topographically driven surface flow index, Water Resour. Res., 45, W08423, doi:10.1029/2008WR007336.
and the invited commentary on Hydrological processes:
Lane, S.N., What makes a fish (hydrologically) happy? A case for inverse modelling, Hydrol. Process. 22, 4493–4495 (2008). DOI: 10.1002/hyp.7145
In the mood of "thinking different" also this paper can bring some interesting information:
Lane, S.N., N. Odoni, C. Landstrom, S J Whatmore, N Ward, and S Bradley (2010) Doing flood risk science differently: an experiment in radical scientific method: doing flood risk science differently, Trans Br. Geogr.
Monday, October 17, 2011
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:
Bibliography of others will follow. Anyone of them is a champion in publishing. So there is lot to read.
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.
Thursday, October 6, 2011
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.
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.
Sunday, October 2, 2011
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.
Here you will find the presentation. Hopefully a paper will come out from it.
Thursday, September 8, 2011
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
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
Friday, August 26, 2011
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.
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.
Tuesday, August 23, 2011
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.
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.
Monday, August 8, 2011
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.
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.
Tuesday, July 26, 2011
Quantifying uncertainty
I saw on EOS an announcement regarding a new website, QUEST, or quantifying uncertainty in ecosystem studies. Hydrology in fact needs an effort to quantify uncertainties, but this is usually ignored.
It is quite a few years that I fly around of this issue, and probably next year I would try to dig a more little deep in literature.
The sources of uncertainty in hydrological modeling are at least three:
- the input data (which can derive from chaotic dynamics)
- the approximation contained in equations
- the parameterizations of constants which can be heterogeneous (highly variable, if not random in space)
When thinking to inputs, the paradigm is rainfall. It is usually estimated just a few points in the domain with large errors. Then, the local estimates needs to be interpolated and extrapolated in space, introducing further errors. Rainfall itself is very irregular in time and space at all of the scales, which means that you can capture just the statistics of its behavior (and this left you out in the cold with other errors).
When looking at flows, i.e. at their mathematical description in equations, one has to think that they are eminently a thermodynamical product where some fluctuations need to be neglected and described with suitably averaged properties, which could be no possible (significant).
Besides, usually the system described is made up of many non-linearly connected subsystems, and in practical implementations the nonlinearities and the feedbacks are simplified or even neglected. Moreover, equations need to be discretized on grid, which introduce itself approximations.
Finally, saying that some processes are governed by heterogeneities, we also state that the information they contain is algorithmically incompressible (e.g. Chaitin), and there is no way to represent it in short strings. The latter syndrome is the one well described by Borges in "The Exactitude of Sciences", but also in Noam Chomsky's book, Rules and Representation, where at page 8 he cites Stephen Weinberg, and goes so deep in asking if we can really know reality, and what it means.
In any case, the hydrological community, started to take care of it from a long time (here it is a recent abstract with hopefully a good literary review, and here, the work by Beven, Gupta and Wagener), but they started to work especially on the assessment of parameter uncertainty (even if GLUE pretends to be of more general validity). A recent assessment is also in this work by Goetzinger and Bardossy which can provide access to further concepts and bibliography.
However, many hydrological models produce just time series, and therefore the uncertainty reduce to understand (and sometimes to compare) a couple of time series: the measured time serie and the modeled time serie. Good hydrological models are those that reproduce the time series with a good agreement. This is quantified, often but not always, with the use of indexes. The mean square error or its root, the Nash-Sutcliffe, the minimax objective function, average absolute percentage error, the index of agreement, the coefficient of determination, are a few of them.
This is certainly a narrow perspective to look at the topic. Both the measured and the simulated series are, in fact, affected by errors, and therefore one should not compare the two series directly , but the time series including their errors. I believe that this would coincide to adopting a Bayesian perspective of the problem (e.g D'Agostini 2003 - Bayesian Reasoning in Data Analysis, A critical Introduction) and will turn into data assimilation (e.g. Kalnay, Atmospheric Modeling, Data Assimilation and Predictability, 2003) with the defect that, at this point, data and models are so entangled that it would be difficult to extricate them (but not impossible, I guess).
We can also observe that a model usually produces more than a single time series. So "a prediction" becomes the "predictions" and the uncertainty spreads in all of them.
Besides, we did not mention, spatial patterns: before we claims for their uncertainty, we have to recognize that we should quantify them. How can we do ? And for extension are we able to identify spatio-temporal patterns ? And therefore when we can decide if two of these patterns are the same (neglecting noises). Indicators of statistical equality would probably give miserable scores if applied to two or three dimensional fields.
Someone has ideas ?
It is quite a few years that I fly around of this issue, and probably next year I would try to dig a more little deep in literature.
The sources of uncertainty in hydrological modeling are at least three:
- the input data (which can derive from chaotic dynamics)
- the approximation contained in equations
- the parameterizations of constants which can be heterogeneous (highly variable, if not random in space)
When thinking to inputs, the paradigm is rainfall. It is usually estimated just a few points in the domain with large errors. Then, the local estimates needs to be interpolated and extrapolated in space, introducing further errors. Rainfall itself is very irregular in time and space at all of the scales, which means that you can capture just the statistics of its behavior (and this left you out in the cold with other errors).
When looking at flows, i.e. at their mathematical description in equations, one has to think that they are eminently a thermodynamical product where some fluctuations need to be neglected and described with suitably averaged properties, which could be no possible (significant).
Besides, usually the system described is made up of many non-linearly connected subsystems, and in practical implementations the nonlinearities and the feedbacks are simplified or even neglected. Moreover, equations need to be discretized on grid, which introduce itself approximations.
Finally, saying that some processes are governed by heterogeneities, we also state that the information they contain is algorithmically incompressible (e.g. Chaitin), and there is no way to represent it in short strings. The latter syndrome is the one well described by Borges in "The Exactitude of Sciences", but also in Noam Chomsky's book, Rules and Representation, where at page 8 he cites Stephen Weinberg, and goes so deep in asking if we can really know reality, and what it means.
In any case, the hydrological community, started to take care of it from a long time (here it is a recent abstract with hopefully a good literary review, and here, the work by Beven, Gupta and Wagener), but they started to work especially on the assessment of parameter uncertainty (even if GLUE pretends to be of more general validity). A recent assessment is also in this work by Goetzinger and Bardossy which can provide access to further concepts and bibliography.
However, many hydrological models produce just time series, and therefore the uncertainty reduce to understand (and sometimes to compare) a couple of time series: the measured time serie and the modeled time serie. Good hydrological models are those that reproduce the time series with a good agreement. This is quantified, often but not always, with the use of indexes. The mean square error or its root, the Nash-Sutcliffe, the minimax objective function, average absolute percentage error, the index of agreement, the coefficient of determination, are a few of them.
This is certainly a narrow perspective to look at the topic. Both the measured and the simulated series are, in fact, affected by errors, and therefore one should not compare the two series directly , but the time series including their errors. I believe that this would coincide to adopting a Bayesian perspective of the problem (e.g D'Agostini 2003 - Bayesian Reasoning in Data Analysis, A critical Introduction) and will turn into data assimilation (e.g. Kalnay, Atmospheric Modeling, Data Assimilation and Predictability, 2003) with the defect that, at this point, data and models are so entangled that it would be difficult to extricate them (but not impossible, I guess).
We can also observe that a model usually produces more than a single time series. So "a prediction" becomes the "predictions" and the uncertainty spreads in all of them.
Besides, we did not mention, spatial patterns: before we claims for their uncertainty, we have to recognize that we should quantify them. How can we do ? And for extension are we able to identify spatio-temporal patterns ? And therefore when we can decide if two of these patterns are the same (neglecting noises). Indicators of statistical equality would probably give miserable scores if applied to two or three dimensional fields.
Someone has ideas ?
Wednesday, July 13, 2011
New GEOtop presentations given at the Summer School on Surface Hydrology in Marsico Nuovo
Thank you to Salvatore Manfreda for having organized this event which I found fruitful and interesting. General Information on the summer School can be found here. What it is reported below are just the sequence of my seminars: actually a five parts seminar given in four hours.
First hour covers the motivation behind GEOtop, and its structure in terms of grids, equations, and boundary conditions.
The second hour covers the snow modeling (almost all of it, excluding snow compaction). Its equations and boundary conditions.
The third and fourth hours cover Richards equation (above), its extension to deal with saturated and freezing soils, and some material regarding landslide modeling with (and without) GEOtop (below).
The material is far from being complete. But it is better to have them now, a little broken, than never. The Authors ask people using this material to cite the appropriate GEOtop papers appeared in Journal of Hydrometeorology, Hydrological Processeses, and recently on The Cryosphere. Soon the user manual of GEOtop will be available. Continue to watch the blog !
First hour covers the motivation behind GEOtop, and its structure in terms of grids, equations, and boundary conditions.
The second hour covers the snow modeling (almost all of it, excluding snow compaction). Its equations and boundary conditions.
The third and fourth hours cover Richards equation (above), its extension to deal with saturated and freezing soils, and some material regarding landslide modeling with (and without) GEOtop (below).
The material is far from being complete. But it is better to have them now, a little broken, than never. The Authors ask people using this material to cite the appropriate GEOtop papers appeared in Journal of Hydrometeorology, Hydrological Processeses, and recently on The Cryosphere. Soon the user manual of GEOtop will be available. Continue to watch the blog !
Monday, July 11, 2011
udig got a spatial toolbox
I think to it as a milestone to which I contributed a little during the years, even if the full merit needs to be done to Andrea Antonello and Silvia Franceschi: "the Hydrologis".
The idea was to give a transparent (encapsulated) way to add spatial models to a GIS. As told in previous blogs, the way was found in following the OMS3 framework ideas, after having tried hard with OpenMI. Andrea did more by using OMS3 annotations to automatically create the input-output interface, and manual like help, to any OMS3 compliant module. Any information can be found at
udig spatial toolbox a.k.a. OMS3box. However, do not use the 0.7.1 code but use the more recent one that can be found at the jgrasstools download page.
I do not know if Andrea and Silvia fully realize the importance of what they created. It is a big jump to a new type of GIS where the usual paradigms for connecting models, data and visualization, are suddenly changed.
Researchers can now program their model following the OMS3 lines, and having them fully endowed with graphic I/O, help, without taking care of the details of making it.
Certainly programming a Jgrasstool is still a challenge for novices, and much work has to be done to smooth the learning curve of it. Especially writing manuals ;-)
Great work Andrea and Silvia: congratulations !
The idea was to give a transparent (encapsulated) way to add spatial models to a GIS. As told in previous blogs, the way was found in following the OMS3 framework ideas, after having tried hard with OpenMI. Andrea did more by using OMS3 annotations to automatically create the input-output interface, and manual like help, to any OMS3 compliant module. Any information can be found at
udig spatial toolbox a.k.a. OMS3box. However, do not use the 0.7.1 code but use the more recent one that can be found at the jgrasstools download page.
I do not know if Andrea and Silvia fully realize the importance of what they created. It is a big jump to a new type of GIS where the usual paradigms for connecting models, data and visualization, are suddenly changed.
Researchers can now program their model following the OMS3 lines, and having them fully endowed with graphic I/O, help, without taking care of the details of making it.
Certainly programming a Jgrasstool is still a challenge for novices, and much work has to be done to smooth the learning curve of it. Especially writing manuals ;-)
Great work Andrea and Silvia: congratulations !
Saturday, June 18, 2011
The geomorphic structure of Peak Flows
Finally this paper was published in HESS, and can be found at
http://www.hydrol-earth-syst-sci.net/15/1853/2011/hess-15-1853-2011.html with its companion paper and discussions.
It is the fourth of a sequence of papers that started at the very beginning of my hydrological carrier (as from the ISI catalog):
GEOMORPHOLOGICAL DISPERSION, RINALDO, A; MARANI, A; RIGON, WATER RESOURCES RESEARCH Volume: 27 Issue: 4 Pages: 513-525 Published: APR 1991
CAN ONE GAUGE THE SHAPE OF A BASIN, RINALDO, A; VOGEL, GK; RIGON, R; et al., WATER RESOURCES RESEARCH Volume: 31 Issue: 4 Pages: 1119-1127 Published: APR 1995
HILLSLOPE AND CHANNELS CONTRIBUTIONS TO THE HYDROLOGIC RESPONSE: D'ODORICO, P; RIGON, R, WATER RESOURCES RESEARCH Volume: 39 Issue: 5 - Published: MAY 1 2003
But in these papers, we can possibly include, also:
A NOTE ON FRACTAL CHANNEL NETWORKS, MARANI, A; RIGON, R; RINALDO, A, WATER RESOURCES RESEARCH Volume: 27 Issue: 12 Pages: 3041-3049 Published: DEC 1991
GEOMORPHOLOGICAL WIDTH FUNCTIONS AND THE RANDOM CASCADE, MARANI, M; RINALDO, A; RIGON, R; et al., GEOPHYSICAL RESEARCH LETTERS Volume: 21 Issue: 19 Pages: 2123-2126 Published: SEP 15 1994
In fact, all began in trying to understand the topology of river networks with the hope, of which we had confirmations, that topology and geometry play a role in shaping the hydrograph. The discover was that the river networks were fractal (we actually learned it from La Barbera and Rosso, 1989, and Tarboton et al., 1988), and the width function has a multifractal imprint.
However, on these structures, the river networks, the signal passing though has its own dynamics which is advective but also dispersive. How dynamics interacts with geometry? In the first paper on geomorphological dispersion we showed that geometry usually dominates hydrodynamics. So, a precise account for hydrodynamics is usually not necessary to reconstruct the main features of a hydrograph.
A few year later, however, we realized that our model was a little too simple, since using flood wave celerities in channels were not enough to account for the process. We needed at least to include a further celerity, to account for the travel time of water in hillslopes. This was already clearly envisioned at least by Bras and van Der Tak, 1990 but we introduced it in the formalism of the Geomorphological Unit Hydrograph. Besides, we investigated more the role of dispersion. Getting the signal of an ideal uniform rainfall can we solve the reverse problem of understanding the form of the basin which generated a given hydrograph ? While without diffusion and dispersion we were able to statistically reverse the signal, i.e. obtaining basin shapes very similar to the original one, increasing diffusion makes any effort more and more difficult, until the complete loss of any detailed information. However, we were able to characterize diffusion influence on the moments of distribution, and showed that the average residence time is not affected at all by dispersion (therefore it maintains the imprinting of the topology and geometry of the river network) and gave a formula for the second moment of the hydrograph. Works cited in the Peak Flows paper report subsequent research on topic by Saco and Kumar (see References), and by Botter and Rinaldo. Later on, Botter and Rinaldo, 2010 moved also to study the recession curves.
BTW one of the open questions, actually a missing link for completing the whole picture was the inclusion in the picture of a runoff generating mechanism, since all our consideration were essentially based on the assumption that we were able to single out an "effective rainfall", i.e. that part of the precipitation that produces the flood hydrograph. We attacked this problem in D'Odorico and Rigon, 2003 where we implemented a completely saturation excess theory of it, and showed how the extension of partial saturated areas affect heavily the hydrologic response, and therefore the estimation of any residence time statistics (during the writing we found that Sivapalan, Beven and Wood, wow, already tried it in the old-fashioned IUH theory).
What about the peak flows ? Here it comes the present paper:
This paper develops a theoretical framework to investigate the core dependence of peak flows on the geo- morphic properties of river basins. Based on the theory of transport by travel times, and simple hydrodynamic characterization of floods, this new framework invokes the linearity and invariance of the hydrologic response to provide analytical and semi-analytical expressions for peak flow, time to peak, and area contributing to the peak runoff. These results are obtained for the case of constant-intensity hyetograph using the Intensity-Duration-Frequency (IDF) curves to estimate extreme flow values as a function of the rain- fall return period. Results show that, with constant-intensity hyetographs, the time-to-peak is greater than rainfall duration and usually shorter than the basin concentration time. More- over, the critical storm duration is shown to be independent of rainfall return period as well as the area contributing to the flow peak. The same results are found when the effects of hydrodynamic dispersion are accounted for. Further, it is shown that, when the effects of hydrodynamic dispersion are negligible, the basin area contributing to the peak discharge does not depend on the channel velocity, but is a geomorphic propriety of the basin. As an example this framework is applied to three watersheds. In particular, the runoff peak, the critical rainfall durations and the time to peak are calculated for all links within a network to assess how they increase with basin area.
Note: I probably forgot some Siva contributions in this story, just do a "Sivapalan" search on the Water Resources Research site to have an idea of his contributions.
References
Botter, G. and A. Rinaldo (2003), Scale effect on geomorphologic and kinematic dispersion, Water Resour. Res., 39, 1286, doi:10.1029/2003WR002154.
Botter, G. (2010), Stochastic recession rates and the probabilistic structure of stream flows, Water Resour. Res., 46, W12527, doi:10.1029/2010WR009217.
La Barbera, P., and R. Rosso (1989), On the Fractal Dimension of Stream Networks, Water Resour. Res., 25(4), 735-741.
Saco, P. M. and P. Kumar (2002), Kinematic dispersion in stream networks 1. Coupling hydraulic and network geometry, , 38, 1244, doi:10.1029/2001WR000695.
Saco, P. M. and P. Kumar (2002), Kinematic dispersion in stream networks 2. Scale issues and self-similar network organization, , 38, 1245, doi:10.1029/2001WR000694.
Saco, P. M. and P. Kumar (2004), Kinematic dispersion effects of hillslope velocities, Water Resour. Res., 40, W01301, doi:10.1029/2003WR002024
M., K. Beven, and E. Wood (1987), On Hydrologic Similarity 2. A Scaled Model of Storm Runoff Production, Water Resour. Res., 23(12), 2266-2278.
Tarboton, D., R. Bras, and I. Rodriguez-Iturbe (1988), The Fractal Nature of River Networks, Water Resour. Res., 24(8), 1317-1322.
van der Tak, L., and R. Bras (1990), Incorporating Hillslope Effects Into the Geomorphologic Instantaneous Unit Hydrograph, Water Resour. Res., 26(10), 2393-2400.
http://www.hydrol-earth-syst-sci.net/15/1853/2011/hess-15-1853-2011.html with its companion paper and discussions.
It is the fourth of a sequence of papers that started at the very beginning of my hydrological carrier (as from the ISI catalog):
GEOMORPHOLOGICAL DISPERSION, RINALDO, A; MARANI, A; RIGON, WATER RESOURCES RESEARCH Volume: 27 Issue: 4 Pages: 513-525 Published: APR 1991
CAN ONE GAUGE THE SHAPE OF A BASIN, RINALDO, A; VOGEL, GK; RIGON, R; et al., WATER RESOURCES RESEARCH Volume: 31 Issue: 4 Pages: 1119-1127 Published: APR 1995
HILLSLOPE AND CHANNELS CONTRIBUTIONS TO THE HYDROLOGIC RESPONSE: D'ODORICO, P; RIGON, R, WATER RESOURCES RESEARCH Volume: 39 Issue: 5 - Published: MAY 1 2003
But in these papers, we can possibly include, also:
A NOTE ON FRACTAL CHANNEL NETWORKS, MARANI, A; RIGON, R; RINALDO, A, WATER RESOURCES RESEARCH Volume: 27 Issue: 12 Pages: 3041-3049 Published: DEC 1991
GEOMORPHOLOGICAL WIDTH FUNCTIONS AND THE RANDOM CASCADE, MARANI, M; RINALDO, A; RIGON, R; et al., GEOPHYSICAL RESEARCH LETTERS Volume: 21 Issue: 19 Pages: 2123-2126 Published: SEP 15 1994
In fact, all began in trying to understand the topology of river networks with the hope, of which we had confirmations, that topology and geometry play a role in shaping the hydrograph. The discover was that the river networks were fractal (we actually learned it from La Barbera and Rosso, 1989, and Tarboton et al., 1988), and the width function has a multifractal imprint.
However, on these structures, the river networks, the signal passing though has its own dynamics which is advective but also dispersive. How dynamics interacts with geometry? In the first paper on geomorphological dispersion we showed that geometry usually dominates hydrodynamics. So, a precise account for hydrodynamics is usually not necessary to reconstruct the main features of a hydrograph.
A few year later, however, we realized that our model was a little too simple, since using flood wave celerities in channels were not enough to account for the process. We needed at least to include a further celerity, to account for the travel time of water in hillslopes. This was already clearly envisioned at least by Bras and van Der Tak, 1990 but we introduced it in the formalism of the Geomorphological Unit Hydrograph. Besides, we investigated more the role of dispersion. Getting the signal of an ideal uniform rainfall can we solve the reverse problem of understanding the form of the basin which generated a given hydrograph ? While without diffusion and dispersion we were able to statistically reverse the signal, i.e. obtaining basin shapes very similar to the original one, increasing diffusion makes any effort more and more difficult, until the complete loss of any detailed information. However, we were able to characterize diffusion influence on the moments of distribution, and showed that the average residence time is not affected at all by dispersion (therefore it maintains the imprinting of the topology and geometry of the river network) and gave a formula for the second moment of the hydrograph. Works cited in the Peak Flows paper report subsequent research on topic by Saco and Kumar (see References), and by Botter and Rinaldo. Later on, Botter and Rinaldo, 2010 moved also to study the recession curves.
BTW one of the open questions, actually a missing link for completing the whole picture was the inclusion in the picture of a runoff generating mechanism, since all our consideration were essentially based on the assumption that we were able to single out an "effective rainfall", i.e. that part of the precipitation that produces the flood hydrograph. We attacked this problem in D'Odorico and Rigon, 2003 where we implemented a completely saturation excess theory of it, and showed how the extension of partial saturated areas affect heavily the hydrologic response, and therefore the estimation of any residence time statistics (during the writing we found that Sivapalan, Beven and Wood, wow, already tried it in the old-fashioned IUH theory).
What about the peak flows ? Here it comes the present paper:
This paper develops a theoretical framework to investigate the core dependence of peak flows on the geo- morphic properties of river basins. Based on the theory of transport by travel times, and simple hydrodynamic characterization of floods, this new framework invokes the linearity and invariance of the hydrologic response to provide analytical and semi-analytical expressions for peak flow, time to peak, and area contributing to the peak runoff. These results are obtained for the case of constant-intensity hyetograph using the Intensity-Duration-Frequency (IDF) curves to estimate extreme flow values as a function of the rain- fall return period. Results show that, with constant-intensity hyetographs, the time-to-peak is greater than rainfall duration and usually shorter than the basin concentration time. More- over, the critical storm duration is shown to be independent of rainfall return period as well as the area contributing to the flow peak. The same results are found when the effects of hydrodynamic dispersion are accounted for. Further, it is shown that, when the effects of hydrodynamic dispersion are negligible, the basin area contributing to the peak discharge does not depend on the channel velocity, but is a geomorphic propriety of the basin. As an example this framework is applied to three watersheds. In particular, the runoff peak, the critical rainfall durations and the time to peak are calculated for all links within a network to assess how they increase with basin area.
Note: I probably forgot some Siva contributions in this story, just do a "Sivapalan" search on the Water Resources Research site to have an idea of his contributions.
References
Botter, G. and A. Rinaldo (2003), Scale effect on geomorphologic and kinematic dispersion, Water Resour. Res., 39, 1286, doi:10.1029/2003WR002154.
Botter, G. (2010), Stochastic recession rates and the probabilistic structure of stream flows, Water Resour. Res., 46, W12527, doi:10.1029/2010WR009217.
La Barbera, P., and R. Rosso (1989), On the Fractal Dimension of Stream Networks, Water Resour. Res., 25(4), 735-741.
Saco, P. M. and P. Kumar (2002), Kinematic dispersion in stream networks 1. Coupling hydraulic and network geometry, , 38, 1244, doi:10.1029/2001WR000695.
Saco, P. M. and P. Kumar (2002), Kinematic dispersion in stream networks 2. Scale issues and self-similar network organization, , 38, 1245, doi:10.1029/2001WR000694.
Saco, P. M. and P. Kumar (2004), Kinematic dispersion effects of hillslope velocities, Water Resour. Res., 40, W01301, doi:10.1029/2003WR002024
M., K. Beven, and E. Wood (1987), On Hydrologic Similarity 2. A Scaled Model of Storm Runoff Production, Water Resour. Res., 23(12), 2266-2278.
Tarboton, D., R. Bras, and I. Rodriguez-Iturbe (1988), The Fractal Nature of River Networks, Water Resour. Res., 24(8), 1317-1322.
van der Tak, L., and R. Bras (1990), Incorporating Hillslope Effects Into the Geomorphologic Instantaneous Unit Hydrograph, Water Resour. Res., 26(10), 2393-2400.
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