Wednesday, May 30, 2012

Brutsaert-Parlange Special Issue on WRR and the symposium in their honor

There was a call for a special issue of Water Resources Research in honor to Wildfried Brutsaert and Jean-Yves Parlange to which I would like to contribute. Their sites already talk abour their outstanding contribution to Hydrology.
Here below W. Brusaert (on the left) with S. Islam (on the right) at the recent I. Rodriguez-Iturbe's Symposium
And J.Y. Parlange with M. Sivapalan and V. Isham (from the left) at the same event
Interestingly in this call John Selker indicates some additional topics that raised my curiosity, especially because some key papers, which I was able to retrieve, were included as a reference:

  • Solutions to the Blasius Equation
Analytical approximations to the solution of the Blasius equation,” J.-Y. Parlange, R.D. Braddock and G. Sander, Acta Mech. 38:119-125 (1981). 

Solving the Boussinesq equation using solutions of the Blasius equation,” W.L. Hogarth and J.-Y. Parlange, Water Resour. Res. 35:885-887 (1999).
  • Recirculating Flows
“Spherical cap bubbles with laminar wakes,” J.-Y. Parlange, J. Fluid Mech. 37:257-263 (1969).
“Recirculation within a fluid sphere at moderate Reynolds numbers,” D.A. Barry and J.-Y. Parlange, J. Fluid Mech. 465:293-300 (2002).
  • Molecular diffusion into a turbulent atmosphere
A theory for local evaporation (or heat transfer) from rough and smooth surfaces at ground level,” Brutsaert, W., Water Resour. Res., 11(4), 543-550 (1975).
The roughness length for water vapor, sensible heat, and other scalars,” W. Brutsaert, J. Atmos. Sci., 32(10):2028-2031 (1976).
  • Parameterization of capillary properties of soils 
“Probability laws for pore size distributions,” W. Brutsaert, Soil Sci. 101:85-92 (1966). Not the same paper but "The Permeability of a Porous Medium Determined from Certain Probability laws of Pore Size Distribution".

A concise parameterization of the hydraulic conductivity of unsaturated soils,” W. Brutsaert, Adv. Water Resour., 23, 811-815 (2000).
  • Bulk transfer characteristics of the turbulent atmospheric boundary layer
The applicability of planetary boundary layer theory to calculate regional evapotranspiration,” Brutsaert, W. and J.A. Mawdsley, Water Resour. Res., 12:852-858 (1976).
  • Sound wave propagation in soils
The propagation of elastic waves in unconsolidated unsaturated granular mediums,” W. Brutsaert, J. Geophys. Res., 69:243-257 (1964).
The velocity of sound in soils near the surface, as a function of moisture content,” W. Brutsaert and J.N. Luthin. J. Geophys. Res., 69:643-652 (1964).

For more information, contact John Selker at Prof. John Selker, Biological & Ecological Engineering
rm 210 Gilmore Hall, Oregon State University, Corvallis, Oregon 97331-3906, tel: +1-541-737-6304, cell: +1-541-829-0137, fax: +1-541-737-2082,

The special issue come after a Symposium in Parlange's and Brutsaert's honor whose interesting material can be found at this Cornell site. All the contributions are listed and available here.

Friday, May 25, 2012

Remote Sensing of Snow

Preparing the slides for my hydrological class, and aiming to overview (just a little indeed) measurements methods, I discovered prof Hongjie Xie page, from which I withdraw some information. This was for me the excuse to copy and download some reference on passive microwaves and optical sensor dedicated to snow. Below it is a report of the page (with the bibliography a little edited to cope with available papers).

"Since the middle of the 1960’s, a number of satellite-derived snow products have been available, with a few available in near-real time through Internet (Bitner et al, 2002).
Space-board passive microwave radiometer, such as SMMR (Scanning Multichannel Microwave Radiometer), SSM/I (Special Sensor Microwave/Imager), and AMSR-E (Advanced Microwave Scanning Radiometer-Earth Observing System), can penetrate clouds to detect microwave energy emitted by snow and ice and provide information on SWE or snow depth and thus estimating runoff (Pulliainen, 2006; Wulder et al., 2007). Since the 1970s, SWE retrieval from space-borne passive microwave has been investigated Space-borne passive microwave data are well suited to snow cover monitoring because of characteristics such as all weather imaging, a wide swath width with frequent overpass times, and a long available time series (Derksen et al., 2004). But the coarse spatial resolution (25 km of AMSR-E is the best available now) hinders their application in operational hydrological modeling and snow-caused disasters monitoring (Foster et al., 2003; Dressler, et al. 2006; Pulliainen,2006). Optical sensors such as AVHRR (Advanced Very High Resolution Radiometer), MODIS (Moderate Resolution Imaging Spectraradiometer), SPOT and Landsat have been well developed to produce snow cover maps with high spatial resolution (Salonmonson & Appel, 2004; Brown et al., 2007; Dozier&Painter, 2004). But due to the inherent limitation, optical sensors cannot see the earth surface when cloud is present. High cloud blockage becomes the biggest problem in applying snow products from optical sensor (Klein & Barnett, 2003; Zhou et al., 2005; Tekeli et al., 2005; Ault et al., 2006; Liang et al. 2008 a, b; Wang et al., 2008a, b; Wang and Xie 2009)"


Ault T.W.,⁎, Czajkowski K.P., Benko T., Coss J., Struble J., Spongberg A., Templin M.,  Gross C., Validation of the MODIS snow product and cloud mask using student and NWS cooperative station observations in the Lower Great Lakes Region, Remote Sensing of Environment 105 (2006) 341–353

Bitner D., T. Carroll, D. Cline and P. Romanov, 2002: An assessment of the differences between 
three satellite snow cover mapping techniques, Hydrological Processes 16:3723–3733.

Brown R., Derksen C., Wang L, Assessment of spring snow cover duration variability over northern Canada from satellite datasets,  Remote Sensing of Environment 111 (2007) 367–381

C. Derksen C.,Brown, R., Walker A., Merging Conventional (1915–92) and Passive Microwave (1978–2002) Estimates of Snow Extent and Water Equivalent over Central North America, Journal of Hydromet, 5,  2004, 850-861

Dozier J,  Painter T.H, Multispectral and hyperspectral remote sensing of alpine snow, Annu. Rev. Earth Planet. Sci. 2004. 32:465–94 doi: 10.1146/

Dressler,K. A., Leavesley,G. H.,  Bales R. C. and Fassnacht S. R., Evaluation of gridded snow water equivalent and satellite snow cover products for mountain basins in a hydrologic model, Hydrol. Process. 20, 673–688 (2006)

Foster, J.L.,  Sunb C., Walkerd J.P.,  Kelly R., Changa A., Dong J.,  Powell U, Quantifying the uncertainty in passive microwave snow water equivalent observations, Remote Sensing of Environment 94 (2005) 187–203

Klein A, Barnett A.C., Validation of daily MODIS snow cover maps of the Upper Rio Grande River Basin for the 2000–2001 snow year, Remote Sensing of Environment 86 (2003) 162–176

Liang T., Zhang X., Xie X, Wu C., Feng Q, Huang X, Chen Q., Toward improved daily snow cover mapping with advanced combination of MODIS and AMSR-E measurements, Remote Sensing of Environment xxx (2008) xxx-xxx

Pulliainen J., Mapping of snow water equivalent and snow depth in boreal and sub-arctic zones by assimilating space-borne microwave radiometer data and ground-based observations, Remote Sensing of Environment, Volume 101, Issue 2, 30 March 2006, Pages 257-269, ISSN 0034-4257, 10.1016/j.rse.2006.01.002.

Salomonson V.V, Appel, I., Estimating fractional snow cover from MODIS using the normalized difference snow index, Remote Sensing of Environment 89 (2004) 351 – 360

Tekelia A.E., Akyurek Z., Sorman A., Sensoy A, Sorman U., Using MODIS snow cover maps in modeling snowmelt runoff process in the eastern part of Turkey, Remote Sensing of Environment 97 (2005) 216 – 230

Wang X., Xie H., Liang T., and  Huang X., Comparison and validation of MODIS standard and new combination of Terra and Aqua snow cover products in northern Xinjiang, China, Hydrol. Process. 23, 419–429 (2009) DOI: 10.1002/hyp.7151

Wulder, M.A., T. A. Nelson,  Derksen C, Seemann D,  Snow cover variability across central Canada (1978–2002) derived from satellite passive microwave data,  Climatic Change (2007) 82:113–130 DOI 10.1007/s10584-006-9148-9

Zhou X, Xieb H.,  Hendrickx J.M.H., Statistical evaluation of remotely sensed snow-cover products with constraints from streamflow and SNOTEL measurements, Remote Sensing of Environment 94 (2005) 214–231

Experimental Hydrology Wiki

Today, while looking for snow pillow images I discovered this Experimental Hydrology wiki  with some interesting information. About the same subject, obviously the CUAHSI site is also a source of many resources: but since the many documents present there, is sometimes more difficult to find the stuff you are looking for.

This is what the wiki authors say:

"It will help us to learn about, recommend, question and discuss new / established / basic / advanced methods of experimental hydrology.

It will help us to avoid reinventing the wheel each time we start out measuring something we haven't measured before.
It will help us not to make the same mistakes others have made before us.
It will help us to share new ideas and concepts.
It will help us to find the methodology and the equipment suitable for our investigation.

All experimental hydrologists are welcome to contribute with their knowledge and experience!"

Saturday, May 19, 2012

A paper in Nature on Scientific Software

The news was brought to me by Martin Davis who had from Stefan Steiner.  The paper is:  The case for open computer programs and was published in Nature.

Here it is what Martin says:

"The paper raises the argument for open source software to a higher plane, that of being a necessary component of scientific proof. It points out that the increasing use of computational science as a basis for scientific discovery implies that open source must become a standard requirement for documentation. Apparently some journals such as Science already require source code to be supplied along with submissions of articles. Amongst other advantages, access to source code is an essential element of peer review.
An interesting example they mention is the infamous HadCRUT and CRUTEM3 meteorological datasets. One of the (few) salient criticisms levelled at this information during Climategate was the inability to reproduce the results by re-running the software. (Mind you, the software was probably a pile of crufty old Fortran programs mashed up by Perl scripts, so maybe it's just as well)"

This clearly reflect what I already wrote in some of my posts:

Monday, May 14, 2012

Utilizing Online Resources for Hydrological Research

I got from LinkedIn this website where Mamhud illustrates several on-line resources by means of videos.

The blog and the site itself are full of interesting information and useful for any hydrologist.