Large Scale Hydrology

Large Scale Hydrology is a fact. Its growth  became important especially in conjunction with the studies about the climate crisis and today many outstanding colleagues work in building and managing hydrological models at global or continental scale.
I participated a few months ago to a session of the Globaqua project where I was exposed to some of these researches.  The models mentioned at the meeting  by Alberto Pistocchi of JRC were LISFLOOD e SWAT. Ralph Merz used HBV and mHm. I know,  from other readings, that also VIC and  PCR-GLOBWB are of this kind of global models, an probably there exist many others (JULES can be another).

There are two aspects of these modelling efforts that can be discussed. The science behind their formulations and parameterisations, and the data sets used to drive them. 

Regarding the first aspects,  science, I think the efforts my colleagues do are necessary and, simplifications they work with have to be made. However,  science in their models is far from being assessed (but if I would myself be working on the same topics, I would probably use the same shortcuts to arrive to some result).  My concern is that in these efforts,  sometimes (I say sometimes but I mean often) hydrological models become a commodity, and their quality is given for granted. Maybe the climate change community with its models of everywhere (and everything) which fail locally had some negative influence on this attitude. As a matter of fact, that discarding  details and details of the processes and still the global results obtained are correct remains quite unproven. 

Regarding data, collecting data globally to run the models is certainly an enterprise. The goal of building these large standard datasets to be used by models and modelers is actually important by itself, and it is a pity that people do not think how to share this knowledge base. An effort for open data and open protocols for digesting them in models is a need.

 In turn there are two great data collection domains: the assessment of hydro-meteo forcing and the parametrizations of soil and vegetation properties.
While  the effort of measuring and providing meterorological data  is shared with meteorologists and climatologists, the terrestrial data sets are less available, of more uncertain application, and often too coarse grained. Or, maybe, this is just my impression. My impression actually is that the assumptions of the congruence in the use of the terrestrial data are made for sake of convenience, and according to a mute agreement not to go in deep in the analysis of their usefulness. The representativity of the data used depends mostly on how much heterogeneity  is possible to neglect: it was a topic which had its popularity in the nineties, but seems a little bit behind the scene now.  Probably the goal now, in this phase of the projects, is to have an infrastructure working, more than forecasting precision, or crystal clear science. 

The emergence of the global scale hydrology, was the title of a very beautiful paper by Peter Eagleson (a citation) (WRR, 1986), and the argument also of  Shuttleworth (1988) which I suggest as a must-to-read papers. This long history means that the topic has more than one thread. 

Notable works, instead of being river basin centred are more focused on the water cycle as a whole. For instance, it came to my attention the work of  of Trenberth  (GS) and coworkers, and of  Oki and coworkers.  Eric Wood  and his coworkers pushed the idea that the global hydrological cycle can be studied by high-resolution models driven by high-resolution remote sensing: and this is still another plot of the story.

Anyway, how much it is the uncertainty of these global water and energy budgets is revealed by the comparison of fluxes as given by OKI’s figure (the one you see in this post), which estimates practically null the outflow of groundwaters in oceans, with a recent study by Kwon et al (2014) that suggests that groundwater could be as much as 80% of the whole contribution of water to the oceans from continental masses.

CUASHI recently dedicated one of its cyberseminars series to the topic (see here and these google links).

The matter, as usual, is to discerne, in this "hot" production, what is good and what is better.  Sometimes being wrong is not so important if this makes science to proceed.
Further readings are below. 

References and further links

Aeschbach-Hertig, W., & Gleeson, T. (2012). Regional strategies for the accelerating global problem of groundwater depletion. Nature Geoscience, 5(12), 853–861. doi:10.1038/ngeo1617

Alcamo, J., Döll, P., Henrichs, T., Kaspar, F., Lehner, B., Rosch, T., and  Siebert, S. (2003). Global estimates of water withdrawals and availability under current and future “business-as-usual” conditions. Hydrological Sciences Journal, 48(3), 339–348. doi:10.1623/hysj.48.3.339.45278 

Ball, P. - H2O, a biography of water, Phoenix ed., 1999

Bergström, S., 1976. Development and application of a conceptual runoff model for Scandinavian catchments, SMHI Report RHO 7, Norrköping, 134 pp.

Burek, P., van der Knijff, J., de Roo, A., LISFLOOD. Distributed water balance and flood simulation model. Revised User Manual. JRC Technical Reports - EUR 26162 EN, 2013.

Dai, A., and K. E. Trenberth (2002), Estimates of freshwater discharge from continents: Latitudinal and seasonal variations, J. Hydrometeorol., 3(6), 660–687, doi:10.1175/1525-7541(2002) 003<0660:EOFDFC>2.0.CO;2.

Dai, A., I. Y. Fung, and A. D. Del Genio (1997), Surface observed global land precipitation variations during 1900–88, J. Clim., 10(11), 2943–2962, doi:10.1175/1520-0442(1997)010<2943: SOGLPV>2.0.CO;2.

Dai, A., T. T. Qian, K. E. Trenberth, and J. D. Milliman (2009), Changes in continental freshwater discharge from 1948 to 2004, J. Clim., 22(10), 2773–2792, doi:10.1175/2008JCLI2592.1.

Eagleson, P, The Emergence of Global-Scale Hydrology, Water Resources Research,  1986

eWaterCycle project: http://www.globalhydrology.nl/

Gentine, P., Troy, T. J., Lintner, B. J., & Findell, K. L. (2012). Scaling in Surface Hydrology: Progress and Challenges. Journal of Contemporary Water Research and Education, 147, 28–40.

Kumar, R., B. Livneh, and L. Samaniego (2013), Toward computationally efficient large-scale hydrologic predictions with amultiscale regionalization scheme, Water Resour. Res., 49, 5700–5714, doi:10.1002/wrcr.20431.

Kwon, E. Y., G. Kim, F. Primeau, W. S. Moore, H.-M. Cho, T. DeVries, J. L. Sarmiento, M. A. Charette, and Y.-K. Cho (2014), Global estimate of submarine groundwater discharge based on an observationally constrained radium isotope model, Geophys. Res. Lett., 41, 8438–8444, doi:10.1002/ 2014GL061574. 

Liang, X., D. P. Lettenmaier, E. F. Wood, and S. J. Burges, 1994: A Simple hydrologically Based Model of Land Surface Water and Energy Fluxes for GSMs, J. Geophys. Res., 99(D7), 14,415-14,428. 

Neltsch, SL, Arnold, JG., Kiniri, JR, Williams, J., Soil & Water Assessment Tool Theoretical Documentation Version 2009. 

Oki, T., and S. Kanae (2006), Global hydrological cycles and world water resources, Science, 313(5790), 1068–1072, doi:10.1126/ science.1128845.

Oki, T., K. Musiake, H. Matsuyama, and K. Masuda (1995), Global atmospheric water balance and runoff from large river basins, Hydrol. Processes, 9(5–6), 655–678, doi:10.1002/ hyp.3360090513.

Samaniego, L., R. Kumar, and S. Attinger (2010), Multiscale parameter regionalization of a grid‐based hydrologicmodel at the mesoscale, Water Resour. Res., 46, W05523, doi:10.1029/2008WR007327. (see also www.ufz.de/mhm)

Seibert, J. and Vis, M. (2012). Teaching hydrological modeling with a user-friendly catchment-runoff-model software package. Hydrology and Earth System Sciences, 16, 3315–3325, 2012 (http://www.geo.uzh.ch/en/units/h2k/services/hbv-model).

Shiklomanov, I. A. (2000). World water resources: a new appraisal and assessment for the 21st century; 1998, 1–40.

Shuttleworth, W.I., 1988. Macrohydrology-the new challenge for process hydrology. I. Hydrol., 100: 31-56. 

Trenberth, K. E., L. Smith, T. Qian, A. Dai, and J. Fasullo (2007a), Estimates of the global water budget and its annual cycle using observational and model data, J. Hydrometeorol., 8(4), 758–769, doi:10.1175/JHM600.1.

Trenberth, K. E., J. T. Fasullo, and J. Kiehl (2009), Earth’s global energy budget, Bull. Am. Meteorol. Soc., 90(3), 311–323, doi:10.1175/2008BAMS2634.1.

Voisin, N., Wood, A. W., & Lettenmaier, D. P. (2008). Evaluation of Precipitation Products for Global Hydrological Prediction. Journal of Hydrometeorology, 9(3), 388–407. doi:10.1175/2007JHM938.1

Vörösmarty, C. J. (2000). Global Water Resources: Vulnerability from Climate Change and Population Growth. Science, 289(5477), 284–288. doi:10.1126/science.289.5477.284

Van Beek, L.P.H., and Bierkens, M.F.P., The Global Hydrological Model PCR-GLOBWB:Conceptualization, Parameterization and Verification, Utrecht University, 2009 (http://vanbeek.geo.uu.nl/suppinfo/vanbeekbierkens2009.pdf)

Wood, E. F., et al. (2011), Hyperresolution global land surface modeling: Meeting a grand challenge for monitoring

Earth’s terrestrial water, Water Resour. Res., 47, W05301, doi:10.1029/2010WR010090.

Xie, P., and P. A. Arkin (1996), Analyses of global monthly precipitation using gauge observations, satellite estimates, and numerical model predictions, J. Clim., 9(4), 840–858, doi:10.1175/ 1520-0442(1996)009<0840:AOGMPU>2.0.CO;2.