Sunday, December 31, 2017

Baldocchi's Classics

I took the  freedom to reproduce Dennis Baldocchi's classic. The original post is on his website to which I dedicated another post. A must for who is interested in Soil-Vegetation-Atmosphere interactions.  I just added the link to the publications (on the title when pdf is open).
As a post of mine, it can be seen as a companion of the two recent posts on plant-atmosphere interactions where further references are presented (I and II).


Agriculture and Climate

1. Lobell, D.B., Schlenker, W. and Costa-Roberts, J., 2011. Climate trends and global crop production since 1980. Science, 333(6042): 616-20.

2. Lobell, D.B. and Gourdji, S.M., 2012. The influence of climate change on global crop productivity. Plant Physiology, 160(4): 1686-97.

3. Foley, J.A. et al., 2011. Solutions for a cultivated planet. Nature, 478(7369): 337-42.

4. Rosenzweig, C. and Parry, M.L., 1994. Potential impact of climate-change on world food-supply. Nature, 367(6459): 133-138.

Biogeochemistry

1. Bolin, B. and H. Rodhe. 1973. Note on Concepts of Age Distribution and Transit-Time in Natural Reservoirs. Tellus 25:58-62.

Boundary Layer Micrometeorology
1. Kaimal, J. C., Y. Izumi, J. C. Wyngaard, and R. Cote. 1972. Spectral Characteristics of Surface-Layer Turbulence. Quarterly Journal of the Royal Meteorological Society 98:563-&.

2. Hogstrom, U. 1988. Non-Dimensional Wind and Temperature Profiles in the Atmospheric Surface-Layer - a Re-Evaluation. Boundary-Layer Meteorology 42:55-78.
https://link.springer.com/article/10.1007%2FBF00119875?LI=true

3. Kaimal, J. C. and J. C. Wyngaard. 1990. The Kansas and Minnesota Experiments. Boundary-Layer Meteorology 50:31-47.
https://link.springer.com/article/10.1007/BF00120517

4. Wyngaard, J.C., 1992. Atmospheric-Turbulence. Annual Review of Fluid Mechanics, 24: 205-233.
http://www.annualreviews.org/doi/abs/10.1146/annurev.fl.24.010192.001225

5. Hogstrom, U. 1996. Review of some basic characteristics of the atmospheric surface layer. Boundary-Layer Meteorology 78:215-246.
https://link.springer.com/article/10.1007%2FBF00120937?LI=true

6. Foken, T., 2006. 50 Years of the Monin–Obukhov Similarity Theory. Boundary-Layer Meteorology, 119(3): 431-447.

7. Wyngaard, J. C. 1990. Scalar Fluxes in the Planetary Boundary-Layer - Theory, Modeling, and Measurement. Boundary-Layer Meteorology 50:49-75.
https://link.springer.com/article/10.1007/BF00120518

Canopy Conductance

1. Finnigan, J. J. and M. R. Raupach. 1987. Transfer processes in plant canopies in relation to stomatal characteristics. Pages 385-429 in E. Zeiger, editor. Stomatal Function. Stanford University Press, Palo Alto, CA.

2. Raupach, M.R., 1995. Vegetation-atmosphere interaction and surface conductance at leaf, canopy and regional scales. Agricultural and Forest Meteorology, 73(3-4): 151-179.

3. Kelliher, F.M., Leuning, R., Raupach, M.R. and Schulze, E.-D., 1995. Maximum conductances for evaporation from global vegetation types. Agricultural and Forest Meteorology, 73(1-2): 1-16.

Canopy micrometeorology and turbulence

1. Denmead, O. T. and E. F. Bradley. 1987. On Scalar Transport in Plant Canopies. Irrigation Science 8:131-149.
https://link.springer.com/article/10.1007/BF00259477

2. Finnigan, J., 2000. Turbulence in Plant Canopies. Annu. Rev. Fluid Mech., 32(1): 519-571.

3. Raupach, M.R. and Thom, A.S., 1981. Turbulence in and above Plant Canopies. Annual Review of Fluid Mechanics, 13: 97-129.
http://www.annualreviews.org/doi/abs/10.1146/annurev.fl.13.010181.000525?journalCode=fluid

4. Raupach, M. R., J. J. Finnigan, and Y. Brunet. 1996. Coherent eddies and turbulence in vegetation canopies: The mixing-layer analogy. Boundary-Layer Meteorology 78:351-382.
https://link.springer.com/article/10.1007/BF00120941


CO2 Fluxes, Pioneering Studies


1. Monteith, J. L. and G. Szeicz. 1960. et. Quarterly Journal of the Royal Meteorological Society 86:205-214.
http://onlinelibrary.wiley.com/doi/10.1002/qj.49708636810/abstract


J2. Desjardins, R. 1974. Technique to Measure Co2 Exchange under Field Conditions. International Journal of Biometeorology 18:76-83.
https://link.springer.com/article/10.1007/BF01450667


3. Anderson, D. E., S. B. Verma, and N. J. Rosenberg. 1984. Eddy-correlation measurements of CO2, latent-heat, and sensible heat fluxes over a crop surface. Boundary-Layer Meteorology 29:263-272.


CO2 Fluxes, syntheses

1. Baldocchi, D.D., 2008. TURNER REVIEW No. 15. 'Breathing' of the terrestrial biosphere: lessons learned from a global network of carbon dioxide flux measurement systems. Australian Journal of Botany 56, 1-26.

2. Beer, C., Reichstein, M., Tomelleri, E., Ciais, P., Jung, M., Carvalhais, N., Rodenbeck, C., Arain, M.A., Baldocchi, D., Bonan, G.B., Bondeau, A., Cescatti, A., Lasslop, G., Lindroth, A., Lomas, M., Luyssaert, S., Margolis, H., Oleson, K.W., Roupsard, O., Veenendaal, E., Viovy, N., Williams, C., Woodward, F.I., Papale, D., 2010. Terrestrial Gross Carbon Dioxide Uptake: Global Distribution and Covariation with Climate. Science 329, 834-838.

3. Luyssaert, S., Inglima, I., Jung, M., Richardson, A.D., Reichsteins, M., Papale, D., Piao, S.L., Schulzes, E.D., Wingate, L., Matteucci, G., Aragao, L., Aubinet, M., Beers, C., Bernhoffer, C., Black, K.G., Bonal, D., Bonnefond, J.M., Chambers, J., Ciais, P., Cook, B., Davis, K.J., Dolman, A.J., Gielen, B., Goulden, M., Grace, J., Granier, A., Grelle, A., Griffis, T., Grunwald, T., Guidolotti, G., Hanson, P.J., Harding, R., Hollinger, D.Y., Hutyra, L.R., Kolar, P., Kruijt, B., Kutsch, W., Lagergren, F., Laurila, T., Law, B.E., Le Maire, G., Lindroth, A., Loustau, D., Malhi, Y., Mateus, J., Migliavacca, M., Misson, L., Montagnani, L., Moncrieff, J., Moors, E., Munger, J.W., Nikinmaa, E., Ollinger, S.V., Pita, G., Rebmann, C., Roupsard, O., Saigusa, N., Sanz, M.J., Seufert, G., Sierra, C., Smith, M.L., Tang, J., Valentini, R., Vesala, T., Janssens, I.A., 2007. CO2 balance of boreal, temperate, and tropical forests derived from a global database. Global Change Biology 13, 2509-2537.

Dry Deposition

1. Wesely, M. L. and B. B. Hicks. 2000. A review of the current status of knowledge on dry deposition. Atmospheric Environment 34:2261-2282.
http://www.sciencedirect.com/science/article/pii/S1352231099004677

2. Wesely, M. L. 1989. Parameterization of surface resistances to gaseous dry deposition in regional-scale numerical models. Atmospheric Environment 23:1293-1304.

3.Wesely, M. L. and B. B. Hicks. A review of current status of knowledge on dry deposition, 2000 Atmospheric Environment 34:2261-2282.
http://www.sciencedirect.com/science/article/pii/S1352231099004677

4. Fowler, D., K. Pilegaard, M. A. Sutton, P. Ambus, M. Raivonen, J. Duyzer, D. Simpson, H. Fagerli, S. Fuzzi, J. K. Schjoerring, C. Granier, A. Neftel, I. S. A. Isaksen, P. Laj, M. Maione, P. S. Monks, J. Burkhardt, U. Daemmgen, J. Neirynck, E. Personne, R. Wichink-Kruit, K. Butterbach-Bahl, C. Flechard, J. P. Tuovinen, M. Coyle, G. Gerosa, B. Loubet, N. Altimir, L. Gruenhage, C. Ammann, S. Cieslik, E. Paoletti, T. N. Mikkelsen, H. Ro-Poulsen, P. Cellier, J. N. Cape, L. Horváth, F. Loreto, Ü. Niinemets, P. I. Palmer, J. Rinne, P. Misztal, E. Nemitz, D. Nilsson, S. Pryor, M. W. Gallagher, T. Vesala, U. Skiba, N. Brüggemann, S. Zechmeister-Boltenstern, J. Williams, C. O'Dowd, M. C. Facchini, G. de Leeuw, A. Flossman, N. Chaumerliac, and J. W. Erisman. 2009. Atmospheric composition change: Ecosystems–Atmosphere interactions. Atmospheric Environment 43:5193-5267.
http://www.sciencedirect.com/science/article/pii/S1352231009006633


Ecosystem Atmosphere Interactions

1. Watson, A. and J. Lovelock. 1983. Biological homeostasis of the global environment: the parable of Daisyworld. Tellus 35b:286-289.

2. Odum, E. P. 1969. Strategy of Ecosystem Development. Science 164:262-270.


Ecosystem Structure and Function

1. Van Bodegom, P. M., J. C. Douma, J. P. M. Witte, J. C. Ordoñez, R. P. Bartholomeus, and R. Aerts. 2012. Going beyond limitations of plant functional types when predicting global ecosystem-atmosphere fluxes: exploring the merits of traits-based approaches. Global Ecology and Biogeography 21:625-636.
http://onlinelibrary.wiley.com/doi/10.1111/j.1466-8238.2011.00717.x/abstract

2. Reich, P. B., M. B. Walters, and D. S. Ellsworth. 1997. From tropics to tundra: Global convergence in plant functioning. PNAS 94:13730-13734.

3. Wright, I. J., P. B. Reich, M. Westoby, D. D. Ackerly, Z. Baruch, F. Bongers, J. Cavender-Bares, F. A. Chapin, J. H. C. Cornelissen, M. Diemer, J. Flexas, E. Garnier, P. K. Groom, J. Gulias, K. Hikosaka, B. B. Lamont, T. Lee, W. Lee, C. Lusk, J. J. Midgley, M.-L. Nava, Ü. Niinemets, J. Oleksyn, N. Osada, H. Poorter, P. Poot, L. Prior, V. I. Pyankov, C. Roumet, S. C. Thomas, M. G. Tjoelker, E. J. Veneklaas, and R. Villar. 2004. The worldwide leaf economics spectrum. Nature 428:821-827.

Eddy Covariance Flux measurements

1. Moore, C. J. 1986. Frequency response corrections for eddy covariance systems. Boundary Layer Meteorology 37:17-35.

2. McMillen, R. T. 1988. An Eddy-Correlation Technique with Extended Applicability to Non-Simple Terrain. Boundary-Layer Meteorology 43:231-245.
https://link.springer.com/article/10.1007%2FBF00128405?LI=true

3. Baldocchi, D. D., B. B. Hicks, and T. P. Meyers. 1988. Measuring biosphere-atmosphere exchanges of biologically related gases with micrometeorological methods. Ecology. 69:1331-1340.

4. Foken, T. and B. Wichura. 1996. Tools for quality assessment of surface-based flux measurements. Agricultural and Forest Meteorology 78:83-105.
http://www.sciencedirect.com/science/article/pii/0168192395022481

5. Aubinet, M. et al., 2000. Estimates of the annual net carbon and water exchange of European forests: the EUROFLUX methodology. Advances in Ecological Research, 30: 113-175.
http://www.sciencedirect.com/science/article/pii/S0065250408600185

6. Baldocchi, D.D., 2003. Assessing the eddy covariance technique for evaluating carbon dioxide exchange rates of ecosystems:past, present and future. Global Change Biol, 9: 479-492.

7. Lee, X.H., Massman, W.J., 2011. A Perspective on Thirty Years of the Webb, Pearman and Leuning Density Corrections. Boundary-Layer Meteorology 139, 37-59.

Energetics of crop production

1. Monteith, J. L. 1977. Climate and Efficiency of Crop Production in Britain. Philosophical Transactions of the Royal Society of London Series B-Biological Sciences 281:277-294.

2. Loomis, R. S. 1971. Agricultural Productivity. Annual Review of Plant Physiology 22:431-&.
http://www.annualreviews.org/doi/pdf/10.1146/annurev.pp.22.060171.002243

3. Lemon, E., D. W. Stewart, and Shawcroft, R.W.. 1971. Sun work in a cornfield. Science 174:371
http://science.sciencemag.org/content/174/4007/371


Energy Balance Closure


1. Wilson, K., Goldstein, A., Falge, E., Aubinet, M., Baldocchi, D., Berbigier, P., Bernhofer, C., Ceulemans, R., Dolman, H., Field, C., 2002. Energy balance closure at FLUXNET sites. Agricultural and Forest Meteorology 113, 223-243.

2. Foken, T. 2008. The energy balance closure problem: An overview. Ecological Applications 18:1351-1367.

3. Leuning, R., van Gorsel, E., Massman, W.J., Isaac, P.R., 2012. Reflections on the surface energy imbalance problem. Agricultural and Forest Meteorology 156, 65-74.

Evaporation

1. Monteith, J. L. 1965. Evaporation and Environment. Pages 205-234 Symposium Society of Experimental Biology XIX.

2. Monteith, J. L. 1981. Evaporation and Surface-Temperature. Quarterly Journal of the Royal Meteorological Society 107:1-27.

3. Jarvis, P.G. and McNaughton, K.G., 1986. Stomatal Control of Transpiration - Scaling up from Leaf to Region. Advances in Ecological Research, 15: 1-49.
https://www.sciencedirect.com/science/article/pii/S0065250408601191

4. Raupach, M.R., 2001. Combination theory and equilibrium evaporation. Quarterly Journal of the Royal Meteorological Society, 127(574): 1149-1181.
http://onlinelibrary.wiley.com/doi/10.1002/qj.49712757402/full

5. Shuttleworth, W.J., 2007. Putting the 'vap' into evaporation. Hydrology and Earth System Sciences 11, 210-244.

6. Katul, G. G., R. Oren, S. Manzoni, C. Higgins, and M. B. Parlange. 2012. Evapotranspiration: A process driving mass transport and energy exchange in the soil-plant-atmosphere-climate system.
Reviews of Geophysics 50.

Flux Footprint

1. Schmid, H. P. 2002. Footprint modeling for vegetation atmosphere exchange studies: a review and perspective. Agricultural and Forest Meteorology 113:159-183.

2. Vesala, T., U. Rannik, M. Leclerc, T. Foken, and K. Sabelfeld. 2004. Flux and concentration footprints. Agricultural and Forest Meteorology 127:111-116.

3. Hsieh, C. I. and G. Katul. 2009. The Lagrangian stochastic model for estimating footprint and water vapor fluxes over inhomogeneous surfaces. International Journal of Biometeorology 53:87-100.

Flux Processing, Partitioning and Gap filling

1. Falge, E., D. Baldocchi, R. Olson, P. Anthoni, M. Aubinet, C. Bernhofer, G. Burba, R. Ceulemans, R. Clement, and H. Dolman. 2001. Gap filling strategies for long term energy flux data sets. Agricultural and Forest Meteorology 107:71-77.

2. Reichstein, M., Falge, E., Baldocchi, D., Papale, D., Aubinet, M., Berbigier, P., Bernhofer, C., Buchmann, N., Gilmanov, T., Granier, A., Grunwald, T., Havrankova, K., Ilvesniemi, H., Janous, D., Knohl, A., Laurila, T., Lohila, A., Loustau, D., Matteucci, G., Meyers, T., Miglietta, F., Ourcival, J.-M., Pumpanen, J., Rambal, S., Rotenberg, E., Sanz, M., Tenhunen, J., Seufert, G., Vaccari, F., Vesala, T., Yakir, D., Valentini, R., 2005. On the separation of net ecosystem exchange into assimilation and ecosystem respiration: review and improved algorithm. Global Change Biology 11, 1424-1429.
http://onlinelibrary.wiley.com/doi/10.1111/j.1365-2486.2005.001002.x/abstract

3. Moffat, A.M., Papale, D., Reichstein, M., Hollinger, D.Y., Richardson, A.D., Barr, A.G., Beckstein, C., Braswell, B.H., Churkina, G., Desai, A.R., Falge, E., Gove, J.H., Heimann, M., Hui, D., Jarvis, A.J., Kattge, J., Noormets, A., Stauch, V.J., 2007. Comprehensive comparison of gap-filling techniques for eddy covariance net carbon fluxes. Agricultural and Forest Meteorology 147, 209-232.


Gross Primary Production from Remote Sensing, Regional and Global Upscaling

1. Running, S. W., D. D. Baldocchi, D. Turner, S. T. Gower, P. Bakwin, and K. Hibbard (1999), A global terrestrial monitoring network, scaling tower fluxes with ecosystem modeling and EOS satellite data, Remote Sensing of the Environment., 70, 108-127.

2. Anav, A., P. Friedlingstein, C. Beer, P. Ciais, A. Harper, C. Jones, G. Murray-Tortarolo, D. Papale, N. C. Parazoo, P. Peylin, S. Piao, S. Sitch, N. Viovy, A. Wiltshire, and M. Zhao. 2015. Spatiotemporal patterns of terrestrial gross primary production: A review. Reviews of Geophysics: doi 10.1002/2015RG000483.

3. Xiao, X., C. Jin, and J. Dong. 2014. Gross Primary Production of Terrestrial Vegetation. Pages 127-148 in J. M. Hanes, editor. Biophysical Applications of Satellite Remote Sensing. Springer Berlin Heidelberg.
https://link.springer.com/chapter/10.1007/978-3-642-25047-7_5

4. Beer, C., Reichstein, M., Tomelleri, E., Ciais, P., Jung, M., Carvalhais, N., Rodenbeck, C., Arain, M.A., Baldocchi, D., Bonan, G.B., Bondeau, A., Cescatti, A., Lasslop, G., Lindroth, A., Lomas, M., Luyssaert, S., Margolis, H., Oleson, K.W., Roupsard, O., Veenendaal, E., Viovy, N., Williams, C., Woodward, F.I., Papale, D., 2010. Terrestrial Gross Carbon Dioxide Uptake: Global Distribution and Covariation with Climate. Science 329, 834-838.


Hyperspectral remote sensing and surface Fluxes

1. Gamon, J. A., et al. (2011), SpecNet revisited: bridging flux and remote sensing communities, Canadian Journal of Remote Sensing, 36, S376-S390.
http://www.tandfonline.com/doi/abs/10.5589/m10-067?journalCode=ujrs20

2. Ustin, S. L., D. A. Roberts, J. A. Gamon, G. P. Asner, and R. O. Green. 2004. Using imaging spectroscopy to study ecosystem processes and properties. Bioscience 54:523-534.


3. Porcar-Castell, A., E. Tyystjarvi, J. Atherton, C. van der Tol, J. Flexas, E. E. Pfundel, J. Moreno, C. Frankenberg, and J. A. Berry. 2014. Linking chlorophyll a fluorescence to photosynthesis for remote sensing applications: mechanisms and challenges. Journal of Experimental Botany 65:4065-4095.

Instruments

1. Wyngaard, J. C. 1981. Cup, Propeller, Vane, and Sonic Anemometers in Turbulence Research. Annual Review of Fluid Mechanics 13:399-423.
http://www.annualreviews.org/doi/abs/10.1146/annurev.fl.13.010181.002151?journalCode=fluid

2. Werle, P., F. Slemr, K. Maurer, R. Kormann, R. Mücke, and B. Jänker. 2002. Near- and mid-infrared laser-optical sensors for gas analysis. Optics and Lasers in Engineering 37:101-114.

3. Long, S. P., P. K. Farage, and R. L. Garcia. 1996. Measurement of leaf and canopy photosynthetic CO2 exchange in the field. Journal of Experimental Botany 47:1629-1642.


Land-Atmosphere-Climate Interactions

1. Dickinson, R. E. 1983. Land surface processes and climate-surface albedos and energy balance. Advances in Geophysics 25:305-353.
http://www.sciencedirect.com/science/article/pii/S0065268708601764

2. Sellers, P.J. et al., 1997. Modeling the exchanges of energy, water, and carbon between continents and the atmosphere. Science, 275(5299): 502-509.

3. Bonan, G. B., K. W. Oleson, M. Vertenstein, S. Levis, X. B. Zeng, Y. J. Dai, R. E. Dickinson, and Z. L. Yang. 2002. The land surface climatology of the community land model coupled to the NCAR community climate model. Journal of Climate 15:3123-3149.

4. Bonan, G. B. 2008. Forests and climate change: forcings, feedbacks, and the climate benefits of forests. Science 320:1444-1449.

5. Jackson, R. B., J. T. Randerson, J. G. Canadell, R. G. Anderson, R. Avissar, D. D. Baldocchi, G. B. Bonan, K. Caldeira, N. S. Diffenbaugh, C. B. Field, B. A. Hungate, E. G. Jobb, Protecting climate with forests, Environmental Research Letters, 3, 4, 2008

6. Foley, J. A., R. DeFries, G. P. Asner, C. Barford, G. Bonan, S. R. Carpenter, F. S. Chapin, M. T. Coe, G. C. Daily, H. K. Gibbs, J. H. Helkowski, T. Holloway, E. A. Howard, C. J. Kucharik, C. Monfreda, J. A. Patz, I. C. Prentice, N. Ramankutty, and P. K. Snyder. 2005. Global consequences of land use. Science 309:570-574.


Leaf Area Index and Canopy Structure

1. Wilson, J. W. 1965. Stand Structure and Light Penetration. I. Analysis by Point Quadrats. Journal of Applied Ecology 2:383-390.
https://www.jstor.org/stable/2401487?seq=1#page_scan_tab_contents

2. Lang, A. R. G. 1987. Simplified estimate of leaf area index from transmittance of the sun's beam. Agricultural and Forest Meteorology 41:179-186.
http://www.sciencedirect.com/science/article/pii/0168192387900785

3. Chen, J.M., 1996. Optically-based methods for measuring seasonal variation of leaf area index in boreal conifer stands. Agricultural and Forest Meteorology, 80(2-4): 135-163.

4. Lefsky, M. A., W. B. Cohen, G. Parker, and D. J. Harding. 2002. Lidar remote sensing for ecosystem studies. Bioscience 52:19-30.

5. Jonckheere, I. et al., 2004. Review of methods for in situ leaf area index determination: Part I. Theories, sensors and hemispherical photography. Agricultural and Forest Meteorology, 121(1-2): 19-35.

6. Ryu, Y., Sonnentag, O., Nilson, T., Vargas, R., Kobayashi, H., Wenk, R., Baldocchi, D.D., 2010. How to quantify tree leaf area index in an open savanna ecosystem: A multi-instrument and multi-model approach. Agricultural and Forest Meteorology 150, 63-76.


Leaf Boundary Layers

1. Leuning, R. 1983. Transport of Gases into Leaves. Plant Cell and Environment 6:181-194
http://onlinelibrary.wiley.com/doi/10.1111/1365-3040.ep11587617/abstract

2. Schuepp, P., 1993. Tansley Review No. 59. Leaf Boundary Layers. New Phytologist 125, 477-507.


Leaf Energy Balance


1. Paw U, K. T. and W. Gao. 1988. Applications of solutions to non-linear energy budget equations. Agricultural and Forest Meteorology 43:121-145.
http://www.sciencedirect.com/science/article/pii/0168192388900871

2. Leuning, R. 1989. Leaf Energy Balances - Developments and Applications. Philosophical Transactions of the Royal Society of London Series B-Biological Sciences 324:191-206.


Leaf photosynthesis/transpiration/stomatal conductance models
1. Jarvis, P. G. 1976. Interpretation of Variations in Leaf Water Potential and Stomatal Conductance Found in Canopies in Field. Philosophical Transactions of the Royal Society of London Series B-Biological Sciences 273:593-610.

2. Farquhar, G. D., S. V. Caemmerer, and J. A. Berry. 1980. A Biochemical-Model of Photosynthetic Co2 Assimilation in Leaves of C-3 Species. Planta 149:78-90.

3. Farquhar, G.D. and Sharkey, T.D., 1982. Stomatal Conductance and Photosynthesis. Annual Review of Plant Physiology and Plant Molecular Biology, 33: 317-345.
http://www.annualreviews.org/doi/abs/10.1146/annurev.pp.33.060182.001533?journalCode=arplant.1

4. Collatz, G.J., Ball, J.T., Grivet, C. and Berry, J.A., 1991. Physiological and environmental regulation of stomatal conductance, photosynthesis and transpiration: a model that includes a laminar boundary layer. Agricultural and Forest Meteorology, 54(2-4): 107-136.
http://www.sciencedirect.com/science/article/pii/0168192391900028

5. Leuning, R., 1995. A Critical-Appraisal of a Combined Stomatal-Photosynthesis Model for C-3 Plants. Plant Cell and Environment, 18(4): 339-355.
http://onlinelibrary.wiley.com/doi/10.1111/j.1365-3040.1995.tb00370.x/abstract


Leaf-Canopy Modeling, Carbon, Water and Heat Fluxes and Microclimate
1. DeWit, C. T. 1965. Photosynthesis of leaf canopies. Centre for Agricultural Publications and Documentation.

2. Duncan, W. G., R. S. Loomis, W. A. Williams, and R. Hanau. 1967. A Model for Simulating Photosynthesis in Plant Communities. Hilgardia 38:181-&.

3. Sinclair, T. R., C. E. Murphy, and K. R. Knoerr. 1976. Development and Evaluation of Simplified Models for Simulating Canopy Photosynthesis and Transpiration. Journal of Applied Ecology 13:813-829.
http://www.jstor.org/stable/2402257?seq=1#page_scan_tab_contents

4. Goudriaan, J. 1977. Crop micrometeorology: a simulation study.

5. Norman, J.M., 1979. Modeling the complete crop canopy. In: B.J. Barfield and J.F. Gerber (Editor), Modification of the aerial environment of plants. , American Society of Agricultural Engineering, St. Joseph, MI, pp. 249
https://www.abebooks.com/9780916150150/Modification-Aerial-Environment-Plants-ASAE-0916150151/plp

6. Raupach, M.R. and Finnigan, J.J., 1988. Single-Layer Models of Evaporation from Plant Canopies Are Incorrect but Useful, Whereas Multilayer Models Are Correct but Useless - Discuss. Australian Journal of Plant Physiology, 15(6): 705-716.
http://www.publish.csiro.au/fp/PP9880705

7. Baldocchi, D. D. and P. C. Harley. 1995. Scaling carbon dioxide and water vapor exchange from leaf to canopy in a deciduous forest: model testing and application. Plant, Cell and Environment 8:1157-1173.
http://onlinelibrary.wiley.com/doi/10.1111/j.1365-3040.1995.tb00625.x/abstract

8. dePury, D. G. G. and G. D. Farquhar. 1997. Simple scaling of photosynthesis from leaves to canopies without the errors of big-leaf models. Plant Cell and Environment 20:537-557.

9. Amthor, J. S. 1994. Scaling Co2-Photosynthesis Relationships from the Leaf to the Canopy. Photosynthesis research 39:321-350.
https://link.springer.com/article/10.1007/BF00014590

Methane

1. Cicerone, R.J. and Oremland, R.S., 1988. Biogeochemical aspects of atmospheric methane. Global Biogeochem. Cycles, 2: 299-327.

2. Conrad, R., 1989. Control of methane production in terrestrial ecosystems. In: M.O. Andreae and D.S. Schimel (Editors), Exchange of Trace Gases between Terrestrial Ecosystems and the Atmosphere. Wiley, Chichester, UK, pp. 39-58.
https://www.amazon.com/Exchange-Terrestrial-Ecosystems-Atmosphere-Workshop/dp/0471925519

3. Conrad, R., 1996. Soil microorganisms as controllers of atmospheric trace gases (H-2, CO, CH4, OCS, N2O, and NO). Microbiological Reviews, 60(4): 609-+.

4. Whalen, S.C., 2005. Biogeochemistry of Methane Exchange between Natural Wetlands and the Atmosphere. Environmental Engineering Science, 22(1): 73-94.
http://online.liebertpub.com/doi/pdf/10.1089/ees.2005.22.73

5. Bridgham, S. D., H. Cadillo-Quiroz, J. K. Keller, and Q. L. Zhuang. 2013. Methane emissions from wetlands: biogeochemical, microbial, and modeling perspectives from local to global scales. Global Change Biology 19:1325-1346.

Phenology

1. Richardson, A. D., T. F. Keenan, M. Migliavacca, Y. Ryu, O. Sonnentag, and M. Toomey. 2013. Climate change, phenology, and phenological control of vegetation feedbacks to the climate system. Agricultural and Forest Meteorology 169:156-173.

2. Kramer, K., I. Leinonen, and D. Loustau. 2000. The importance of phenology for the evaluation of impact of climate change on growth of boreal, temperate and Mediterranean ecosystems, an overview. International Journal of Biometeorology 44:67-75.

3. Menzel, A., T. H. Sparks, N. Estrella, E. Koch, A. Aasa, R. Ahas, K. Alm-KÜBler, P. Bissolli, O. G. BraslavskÁ, A. Briede, F. M. Chmielewski, Z. Crepinsek, Y. Curnel, Å. Dahl, C. Defila, A. Donnelly, Y. Filella, K. Jatczak, F. MÅGe, A. Mestre, Ø. Nordli, J. PeÑUelas, P. Pirinen, V. RemiŠOvÁ, H. Scheifinger, M. Striz, A. Susnik, A. J. H. Van Vliet, F.-E. Wielgolaski, S. Zach, and A. N. A. Zust. 2006. European phenological response to climate change matches the warming pattern. Global Change Biology 12:1969-1976.


Planetary Boundary Layer and Surface Flux Feedbacks
1. McNaughton, K.G. and Spriggs, T.W., 1986. A Mixed-Layer Model for Regional Evaporation. Boundary-Layer Meteorology, 34(3): 243-262.
https://link.springer.com/article/10.1007%2FBF00122381?LI=true

2. Raupach, M.R., 1998. Influences of local feedbacks on land-air exchanges of energy and carbon. Global Change Biology, 4(5): 477-494.
http://onlinelibrary.wiley.com/doi/10.1046/j.1365-2486.1998.t01-1-00155.x/abstract

3. Juang, J.-Y., G. Katul, M. Siqueira, P. Stoy, and K. Novick. 2007. Separating the effects of albedo from eco-physiological changes on surface temperature along a successional chronosequence in the southeastern United States. Geophysical Research Letters 34.

4. van Heerwaarden, C. C., J. Vilà-Guerau de Arellano, A. F. Moene, and A. A. M. Holtslag. 2009. Interactions between dry-air entrainment, surface evaporation and convective boundary-layer development. Quarterly Journal of the Royal Meteorological Society 135:1277-1291.

5. Juang, J. Y., G. G. Katul, A. Porporato, P. C. Stoy, M. S. Siqueira, M. Detto, H. S. Kim, and R. Oren. 2007. Eco-hydrological controls on summertime convective rainfall triggers. Global Change Biology 13:887-896.

6. Juang, J. Y., G. G. Katul, A. Porporato, P. C. Stoy, M. S. Siqueira, M. Detto, H. S. Kim, and R. Oren. 2007. Eco-hydrological controls on summertime convective rainfall triggers. Global Change Biology 13:887-896.


Radiative Transfer in vegetation (Phytoactinometry)

1. Lemeur, R. and Blad, B.L., 1974. A critical review of light models for estimating the shortwave radiation regime of plant canopies. Agricultural Meteorology, 14(1-2): 255-286.
http://www.sciencedirect.com/science/article/pii/0002157174900247

2. Ross, J., 1976. Radiative Transfer in Plant Communities. In: J.L. Monteith (Editor), Vegetation and the Atmosphere, vol 1. Academic Press, London.
https://www.cambridge.org/core/journals/experimental-agriculture/article/vegetation-and-the-atmosphere-ed-monteith-j-l-london-academic-press-1975-vol-1-principles-pp-298-10-vol-2-case-studies-pp-459-15/04F40452ABFD73983036C698417851F1
(https://jrls2017.to.ee/download/m59a7aaf73b44f)

3. Ross, J. 1980. The Radiation Regime and Architecture of Plant Stands. Dr. W Junk, The Hague. http://link.springer.com/book/10.1007%2F978-94-009-8647-3

4. Myneni, R.B., Ross, J. and Asrar, G., 1989. A review on the theory of photon transport in leaf canopies. Agricultural and Forest Meteorology, 45(1-2): 1-153.
http://www.sciencedirect.com/science/article/pii/0168192389900026

5. Ustin, S. L., S. Jacquemoud, and Y. Govaerts. 2001. Simulation of photon transport in a three-dimensional leaf: implications for photosynthesis. Plant Cell Environ 24:1095-1103.

6. Jacquemoud, S., W. Verhoef, F. Baret, C. Bacour, P. J. Zarco-Tejada, G. P. Asner, C. Francois, and S. L. Ustin. 2009. PROSPECT plus SAIL models: A review of use for vegetation characterization. Remote Sensing of Environment 113:S56-S66.


Scientific Method


1. Tuomivaara, T., P. Hari, H. Rita, and R. Hakkinen. 1994. The guide-dog approach: a methodology for ecology. Department of Forest Ecology publications.


Soil Respiration


1. Raich, J., Schlesinger, W., 1992. The global carbon dioxide flux in soil respiration and its relationship to vegetation and climate. Tellus 44B, 81 - 90.

2. Trumbore, S., 2009. Radiocarbon and Soil Carbon Dynamics. Annu. Rev. Earth Planet. Sci. Annual Reviews, Palo Alto, pp. 47-66.

3. Kuzyakov, Y., Gavrichkova, O., 2010. REVIEW: Time lag between photosynthesis and carbon dioxide efflux from soil: a review of mechanisms and controls. Global Change Biology 16, 3386-3406.
http://onlinelibrary.wiley.com/doi/10.1111/j.1365-2486.2010.02179.x/abstract

Soil Respiration, Flux-Gradient and Chamber measurements


1. Livingston, G.P. and Hutchinson, G.L., 1995. Enclosure-based measurement of trace gas exchange: Applications and sources of error. In: R.C. Harriss (Editor), Biogenic trace gases: Measuring emissions from soil and water. Blackwell Scientific, London, pp. 14-51.

2. Hutchinson, G.L. and Rochette, P., 2003. Non-Flow-Through Steady-State Chambers for Measuring Soil Respiration: Numerical Evaluation of Their Performance. Soil Sci Soc Am J, 67(1): 166-180.

3. Maier, M., and H. Schack-Kirchner (2014), Using the gradient method to determine soil gas flux: A review, Agricultural and Forest Meteorology, 192


Soil-Plant-Atmosphere Continuum

1. Shawcroft, R. W., E. R. Lemon, L. H. Allen, D. W. Stewart, and S. E. Jensen. 1974. SOIL-PLANT-ATMOSPHERE MODEL AND SOME OF ITS PREDICTIONS. Agricultural Meteorology 14:287-307.

2. Jarvis, P. G., W. R. N. Edwards, and H. Talbot. 1981. Models of Plant and Crop Water Use. Pages 151-193 in D. A. Rose and D. A. Charles-Edwards, editors. Mathematics and Plant Physiology. Academic Press, London.

3. Tuzet, A., A. Perrier, and R. Leuning. 2003. A coupled model of stomatal conductance, photosynthesis and transpiration. Plant Cell and Environment 26:1097-1116.

4. Katul, G., R. Leuning, and R. Oren. 2003. Relationship between plant hydraulic and biochemical properties derived from a steady-state coupled water and carbon transport model. Plant Cell Environ 26:339-350.


Soils, moisture, heat, CO2

1. Clapp, R.B. and Hornberger, G.M., 1978. Empirical Equations for Some Soil Hydraulic-Properties. Water Resources Research, 14(4): 601-604.

2. van Genuchten, M.T. and Sudicky, E.A., 1999. Recent advances in Vadose zone flow and transport modeling. In: M. Parlange and J.W. Hopmans (Editors), Vadose Zone Hydrology. Oxford Press, New York, pp. 155-193.
https://www.amazon.com/Vadose-Zone-Hydrology-Cutting-Disciplines/dp/0195109902

3. Simunek, J. and Suarez, D.L., 1993. Modeling of carbon-dioxide transport and production in soil. 1. Model development. Water Resources Research, 29: 487-497.


Stable isotopes

1. Bowling, D.R., Pataki, D.E., Randerson, J.T., 2008. Carbon isotopes in terrestrial ecosystem pools and CO2 fluxes. New Phytologist 178, 24-40.

2. Dawson, T.E., Mambelli, S., Plamboeck, A.H., Templer, P.H., P.Tu, K., 2002. Stable isotope in plant ecology. Annual Review Ecology Systematics 33, 507-559.

3. Griffis, T. J. (2013), Tracing the flow of carbon dioxide and water vapor between the biosphere and atmosphere: A review of optical isotope techniques and their application, Agricultural and Forest Meteorology, 174
http://www.sciencedirect.com/science/article/pii/S0168192313000373


Stomatal Optimization Models


1. Cowan, I. and G. Farquhar. 1977. Stomatal function in relation to leaf metabolism and environment. Symposium of the Society of Experimental Biology 31:471-505.

2. Hari, P., A. Makela, E. Korpilahti, and M. Holmberg. 1986. Optimal control of gas exchange. Tree Physiology 2:169-175.
https://academic.oup.com/treephys/article-abstract/2/1-2-3/169/1623649

3. Makela, A., F. Berninger, and P. Hari. 1996. Optimal Control of Gas Exchange during Drought: Theoretical Analysis. Annals of Botany 77:461-468.

4. Katul, G., S. Manzoni, S. Palmroth, and R. Oren. 2010. A stomatal optimization theory to describe the effects of atmospheric CO2 on leaf photosynthesis and transpiration. Annals of Botany 105:431-442


Trace Gas Exchange, VOCs


1. Fuentes, J.D. et al., 2000. Biogenic hydrocarbons in the atmospheric boundary layer: A review. Bulletin of the American Meteorological Society, 81(7): 1537-1575.

2. Monson, R.K. and Holland, E.A., 2001. Biospheric trace gas fluxes and their control over tropospheric chemistry. Annual Review of Ecology and Systematics, 32: 547-+.

3. Sharkey, T.D. and Yeh, S., 2001. Isoprene emission from plants. Annual Review of Plant Physiology and Plant Molecular Biology, 52(1): 407-436.

4. Megonigal, J.P., Hines, M.E. and Visscher, P.T., 2003. Anaerobic Metabolism: Linkages to Trace Gases and Aerobic Processes. In: H.D. Holland and K.K. Turekian (Editors), Treatise on Geochemistry. Pergamon, Oxford, pp. 317-424.

5. Laothawornkitkul, J., J. E. Taylor, N. D. Paul, and C. N. Hewitt. 2009. Biogenic volatile organic compounds in the Earth system. The New phytologist 183:27-51.
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Friday, December 22, 2017

Estimating water budgets with JGrass-NewAGE

We already talked about water budgets, and the papers of ours that deals with it (see below). Because in this Fall AGU meeting there was a dedicated session, we presented an abstract:

Recently we presented two papers one dedicated to the estimation of the water budget components in a small, basin, the Posina catchment [Abera et al., 2017], and the other in a large basin, the Blue Nile [Abera et al., 2017b]. Closing the budget in the two cases was different. Worth to say, it was much more difficult to close the budget at Posina, since at the large scale satellite platform can reasonably help to validate the results. At the smallest scale ground measurements usually available do not guarantee the closure of the budget without making additional hypothesis and remote sensing data cannot give very much help.  The hypothesis that we made is that the groundwater storage comes back to the initial level after a certain time, that we called Budyko time, TB. This time can be fixed arbitrarily, for instance, to five years and then varied to assess, through these trials the uncertainty of the budget. The large scale case was largely supported by remote sensing data, instead, either for calibration and/or validation. This contribution explains how we actually did, clarifies some aspects of the informatics necessary to obtain it and openly discusses the issues risen in our work. We also consider varying configuration of the water budget schemes at the subbasin level, and how this affects the estimates.
Finally we analyse the problem of travel times [e.g. Rigon et  al., 2016a, Rigon et al, 2016b]  as it comes out from considering the multiple fluxes and storages and discuss how much they can be realistic. All considerations and  simulations are based on the JGrass-NewAGE system [Formetta et al., 2014] and its evolution presented in Bancheri [2017].

As we say in the presentation, we could not talk about the travel times. However there are several other places where you can find about, here. 
Clicking on the above Figure, you will see the presentation that was used in NewOrleas. However, on Youtube, we uploaded an extended version with comments. 

References

Abera, W., Formetta, G., Borga, M., & Rigon, R. (2017). Estimating the water budget components and their variability in a pre-alpine basin with JGrass-NewAGE. Advances in Water Resources, 104, 1–18. http://doi.org/10.1016/j.advwatres.2017.03.010

Abera, W., Formetta, Brocca, L., & Rigon, R. (2017), Modelling the water budget of the Upper Blue Nile basin using the JGrass-NewAge model system and satellite data. Hydrol. Earth Syst. Sci., 21, 3145–3165, 2017

Rigon, R., Bancheri, M., & Green, T. R. (2016). Age-ranked hydrological budgets and a travel time description of catchment hydrology. Hydrology and Earth System Sciences, 20(12), 4929–4947. http://doi.org/10.5194/hess-20-4929-2016
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Thursday, December 21, 2017

Copulas

So finally, I was obliged to try to understand what Copulas are. Put it simply. They are functions that connect marginal distributions to their multivariate distribution. Sklar (1959) theorem shows that the copula exists and is unique for any pair. Restricting to bivariate distribution function for sake of simplicity, Sklar theorem establish that the joint cumulative distribution $H(x,y)$ of any pair of continuous random variable (X,Y) may be written as as:
$$
H(x,y) = C(F(x),G(y)) \ \ \ \forall x, y \in \mathbb{R}
$$
where $F(x)$ and $G(y)$ are the marginal distributions of $X$ and $Y$. $C$, the copula, can be though as a function such that:
$$
C:\, [0,1]^2 \mapsto [0,1]
$$



Obviosly just in the Platonic world where you know $H$,$F$ and $G$, you can determine the unknown $C$. In practice you work with much less information, where you have the marginals, $F$ and $G$ and, maybe some information about the correlation of the random variables they describe.
So you have to infer the multivariate distribution, by selecting, as usual I would say, the copulas among a large set of copulas templates.
This is what is written for instance in Genest and Favre 2007, a paper particularly directed to hydrologists. So, for your introduction to Copulas you can probably start from that paper. However, I came to it, by its citation in Ebrechts, 2009. Traditional references on the subject are the books by Joe (1997) and Nelsen (1999) but a nice review paper (therefore more synthetic) is Frees and Valdez 1998.
Particularly relevant copulas are useful to understand correlations among variables, and the so called empirical copulas (e.g. Genest and Favre, 2007) can be used to this scope.
Among Hydrological application, I can mention, among others, De Michele and Salvadori (2002), Salvadori and De Michele (2004), Grimaldi and Serinaldi (2006), and Serinaldi et al., 2009.

References

  • De Michele, C. (2003). A Generalized Pareto intensity-duration model of storm rainfall exploiting 2-Copulas. Journal of Geophysical Research, 108(D2), 225–11. http://doi.org/10.1029/2002JD002534
  • Embrechts, P. (2009). Copulas: a personal view, 1–18.
  • Frees, E. W., & Valdez, E. A. (1999). Understanding Relationships Using Copulas. North American Actuarial Journal, 2(1), 1–25. 
  • Genest, C., & Favre, A. A.-C. (2007). Everything you always wanted to know about copula modeling but were afraid to ask. Journal of Hydrologic Engineering, 347–368. http://doi.org/10.1061/ASCE1084-0699200712:4347
  • Genest, C., & Nešlehová, J. (2007). A primer on copulad for count data. Astin Bulletin, 37(02), 475–515. http://doi.org/10.1017/S0515036100014963
  • Grimaldi, S., & Serinaldi, F. (2006). Asymmetric copula in multivariate flood frequency analysis. Advances in Water Resources, 29(8), 1155–1167. http://doi.org/10.1016/j.advwatres.2005.09.005
  • Joe, H. 1997 . Multivariate models and dependence concepts, Chapmanand Hall, London. 
  • Mikosch, T. (2006). Copulas: Tales and facts. Extremes, 9(1), 3–20. http://doi.org/10.1007/s10687-006-0015-x
  • Nelsen, R. B. 1999 . An introduction to copulas, Springer, New York. 
  • Salvadori, G., & De Michele, C. (2004). Frequency analysis via copulas: Theoretical aspects and applications to hydrological events. Water Resources Research, 40(12), 194–17. http://doi.org/10.1029/2004WR003133
  • Serinaldi, F., Bonaccorso, B., Cancelliere, A., & Grimaldi, S. (2009). Probabilistic characterization of drought properties through copulas. Physics and Chemistry of the Earth, 34(10-12), 596–605. http://doi.org/10.1016/j.pce.2008.09.004
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Monday, December 18, 2017

On Complex Network Representation and Computation of Hydrological Quantities

Francesco Serafin participated for us to the AGU fall meeting presenting part of his work. They gave him a poster, actually the poster whose image is below. It is about the representation of Hydrological models as a network of interactions.

You can access a more readable version of the poster by clicking on the Figure. A similar, more recent presentation, given for IEMSS 2018 at Fort Collins can be found below:


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Saturday, December 16, 2017

Marialaura Bancheri defense

The Ph.D. Thesis of Marialaura Bancheri is already available in a previous post. On december 14, she finally defended it. This is the video of her performance. Her topics are: research reproducibility, GEOFRAME, reservoir based modelling (or semidistributed modelling) of the hydrological cycle, travel times theory re-interpreted in the perspective of reservoirs modelling.

I have no doubt that it could be very useful to all who are interested in our recent work and to all those that try to interpret catchment scale behavior through travel times. Marialaura was an outstanding student, is an exceptional team manager, and she is looking for an appropriate post-doc position.
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Wednesday, December 13, 2017

Monday's discussion on evapotranspiration - Part II - The soil-plants fluxes

The first post treated transpiration from the point of view of the atmosphere control volume. There is a “below” though. Below is composed by leaves, trunks/stems, roots. Roots, in turn, are being inserted in soil from where they sip water and nutrients.
Water in soil is understood to be moved by Richards equation (with all the possible variations or extensions), essentially a Stokesian flow (therefore laminar) in the bundle of soil pores.
Plants do not have a pumping heart and therefore has been since long time argued how they can move water up until the tallest leaves that, can be as high as 150 m above soil level. Some plants do not have either a real “vascular” system in the sense we mean for animals, with arteries and veins. They have indeed specialised interconnected cells to move water up, called collectively xylem, and specialised interconnected cells to move around sucrose and the products of photosynthesis (especially to fruits and roots) called phloem.

So the xylem is the place were to look for ascending water. But how water moves in it ? Since Hales (1727), reported in Holbrook and Zwieniecki (2005), the theory invoked was the cohesion-tension one, which is well illustrated in the introduction of e.g. Holbrook and Zwieniecki (2005), which is open (on Amanazon). Other references include Tyree (2003), which is satisfying from the conceptual point of view but not from the point of view of equations. From this side, possibly Steudle (2001) and Strook et al., (2014) are better. Also Pickard (1981) remains a good reference.
The problems to be understood in xylem water movement is how cohesion-tension works. Under normal conditions, atmosphere is very arid and, for instance at normal temperatures, assuming a 50% of specific humidity of air, it correspond to a pressure of -100MPa (e.g. Jensen at al, 2016), while at roots is usual conditions, water is at much higher pressure, ~ -1.5MPa, meaning, that the gradient of pressure along a plant of ten can be as high are 10 MPa/m (see also Nobel, 2009).
Therefore water is “pulled” and we have to face with the counterintuitive idea that water resist to a tension. For liquids to resist to tensile forces, it is necessary that no bubble is nucleated inside the liquid that disrupt the liquid continuity (creating emboli, e.g. Fsher, 1948). Eventually mechanisms for refilling the vessels have also to be required for understanding the real functioning of plants. This is actually matter of research.
Very much attention to the physics of the process, is also paid in the recent review by Jensen et al, (2016). There also the phloem flux is covered with quite detail and reference therein is large and up-to date. Reading the papers I cited, that are just a few in my collection, can be a starting point for understanding the problem, and this is an advise that I am experimenting myself.
Personally, being highly ignorant of plants physiology, I also require to study it overall. A reference I am following is a classic textbook, Taiz and Zeiger (2002), but a more physical-chemical-mathematical approach ca be found in Nobel (2009).
My first look at the above papers make me remain with the idea that too details hide a possible, more integrated and macroscopic treatment of the matter, at level of single tree, without having necessarily to cope with each cellular movements of water. In fact a look to plants functioning as a whole, is what we, hydrologists are looking for.
Concentrating on plants does not mean we have the whole picture, since soil-plant(s) interactions must be accounted for. We already said that, especially in this case, Richards equation is considered the equation describing water flow in soil. Richards equation, however, is a partial differential equation, ideally written at the Darcy scale, while soil-water-plant interactions happen at the smallest scale of roots. Pickard (1981) gives a description of roots structure but this is therefore not enough to understand well what happens. Soil scientists are bold, and therefore they use a sort of brute-force attack to the problem, where the Darcy scale is ignored and Richards equation is used at small scale where one root link can be associated “mechanistically” to an elementary control volume. A good and up-to-date illustration of this approach is given, for instance in Schröder (2013) Ph.D. Thesis. The only trick used to differentiate the usual approach for adapting it to root interactions is to add two type of conductivities. But please read Schröder (2013) and Huber et al. (2014) to have full and detailed account of it. Companion to this approach is the use of some root model, for instance as Root Typ (Pagès et al., 2004). The latter model are useful also alone, cause the information they contain of roots architecture and density, factors that certainly any theory cannot neglect.


So, I hope to have indicated some initial lectures of which you find the reference below. Below below you also find a bunch of other references, some from the same Authors, that could probably be a good second lecture.

References

A wild bunch of references

  • Aroca, R., Porcel, R., & Ruiz-Lozano, J. M. (2011). Regulation of root water uptake under abiotic stress conditions. Journal of Experimental Botany, 63(1), 43–57. http://doi.org/10.1093/jxb/err266
  • Bouda, M., & Saiers, J. E. (2017). Dynamic effects of root system architecture improve root water uptake in 1-D process-based soil-root hydrodynamics. Advances in Water Resources, 1–53. http://doi.org/10.1016/j.advwatres.2017.10.018
  • Carminati, A., Moradi, A. B., Vetterlein, D., Vontobel, P., Lehmann, E., Weller, U., et al. (2010). Dynamics of soil water content in the rhizosphere. Plant and Soil, 332(1-2), 163–176. http://doi.org/10.1007/s11104-010-0283-8
  • Couvrer, V. (2017, October 30). Emergent properties of plants hydraulic architecture: a modelling study. 
  • Debenedetti, P. G. (2012). Stretched to the limit. Nature Physics, 1–2. 
  • Delory, B. M., Baudson, C., Brostaux, Y., Lobet, G., Jarden, du, P., Pagès, L., & Delaplace, P. (2015). archiDART: an R package for the automated computation of plant root architectural traits, 1–20.
  • Fiscus, E. L. (1975). The Interaction between osmotic- and pressure-induced water flow in plats roots, 55, 917–922. 
  • Fisher, J. C. (1948). The Fracture of Liquids. Journal of Applied Physics, 19(11), 1062–1067. http://doi.org/10.1063/1.1698012
  • Hartvig, K. (2016). Osmotically driven flows and maximal transport rates in systems of long, linear, porous pipes. arXivfluid, 1–18. 
  • Hildebrandt, A., Kleidon, A., & Bechmann, M. (2016). A thermodynamic formulation of root water uptake. Hydrology and Earth System Sciences, 20(8), 3441–3454. http://doi.org/10.5194/hess-20-3441-2016
  • Hodge, A., Berta, G., Doussan, C., Merchan, F., & Crespi, M. (2009). Plant root growth, architecture and function. Plant and Soil, 321(1-2), 153–187. http://doi.org/10.1007/s11104-009-9929-9
  • Holbrook, N. M., Burns, M. J., & Field, C. B. (1995). Negative Xylem Pressures in Plants: A Test of the Balancing Pressure Technique. Science, 270(5239), 1–3. 
  • Huber, K., Vanderborght, J., Javaux, M., & Vereecken, H. (2015). Simulating transpiration and leaf water relations in response to heterogeneous soil moisture and different stomatal control mechanisms. Plant and Soil, 394(1-2), 1–18. http://doi.org/10.1007/s11104-015-2502-9
  • Huber, K., Vanderborght, J., Javaux, M., Schröder, N., Dodd, I. C., & Vereecken, H. (2014). Modelling the impact of heterogeneous rootzone water distribution on the regulation of transpiration by hormone transport and/or hydraulic pressures. Plant and Soil, 384(1-2), 93–112. http://doi.org/10.1007/s11104-014-2188-4
  • Iversen, C. M., McCormack, M. L., Powell, A. S., Blackwood, C. B., Freschet, G. T., Kattge, J., et al. (2017). A global Fine-Root Ecology Database to address below-ground challenges in plant ecology. New Phytologist, 215(1), 15–26. http://doi.org/10.1111/nph.14486
  • Janbek, B., & Stokie, J. (2017). Asymptotic and numerical analysis of a porous medium model for transpiration-driven sap flow in trees. arXivfluid, 1–24. 
  • Javaux, M., Couvreur, V., Vanderborght, J., & Vereecken, H. (2013). Root Water Uptake: From Three-Dimensional Biophysical Processes to Macroscopic Modeling Approaches. Vadose Zone Journal, 12(4), 0–16. http://doi.org/10.2136/vzj2013.02.0042
  • Javaux, M., Schröder, T., Vanderborght, J., & Vereecken, H. (2008). Use of a Three-Dimensional Detailed Modeling Approach for Predicting Root Water Uptake. Vadose Zone Journal, 7(3), 1079–1088. http://doi.org/10.2136/vzj2007.0115
  • Jensen, K. H., Berg-Sørensen, K., Bruus, H., Holbrook, N. M., Liesche, J., Schulz, A., et al. (2016). Sap flow and sugar transport in plants. Reviews of Modern Physics, 88(3), 320–63. http://doi.org/10.1103/RevModPhys.88.035007
  • Jorda, H., Perelman, A., Lazarovitch, N., & Vanderborght, J. (2017). Exploring Osmotic Stress and Differences between Soil–Root Interface and Bulk Salinities. Vadose Zone Journal, 0(0), 0–13. http://doi.org/10.2136/vzj2017.01.0029
  • Kalbacher, T., Delfs, J.-O., Shao, H., Wang, W., Walther, M., Samaniego, L., et al. (2011). The IWAS-ToolBox: Software coupling for an integrated water resources management. Environ Earth Sci, 65(5), 1367–1380. http://doi.org/10.1007/s12665-011-1270-y
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Friday, December 1, 2017

Krigings paper

Finally we submitted the Kriging paper. Interpolation of hydrological quantities is a necessity in hydrological modeling. Since the beginning of last century, various techniques were implemented to obtain it:
or other types of interpolation 

We prefer Kriging. This paper accounts for the implementation of Krigings inside the JGrass-NewAGE system


The paper can be seen here. However, you can find all the material of the paper on the OSF platform. We tried to share everything from code to data and even the simulation we have performed. Therefore, in principle, any reader could try our software and reproduce our result.  
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