Parameter optimisation for a better representation of drought by LSMs: Inverse modelling vs. sequential data assimilation

Hydrology and Earth System Sciences

Volumn 21, Issue 9, 2017, Pages 4861-4878

  Dewaele, Hélène ^a   Munier, Simon ^a   Albergel, Clément ^a   Planque, Carole ^a   Laanaia, Nabil ^a   Carrer, Dominique ^a   Calvet, Jean Christophe ^a  

^a CENTRE NATIONAL DE RECHERCHES MÉTÉOROLOGIQUES   (France)

Author keywords

[No Author keywords available]

Indexed keywords

RAIN; UNCERTAINTY ANALYSIS;

ABOVE GROUND BIOMASS; AVAILABLE WATER CONTENTS; COMPLEX METHODS; INTERANNUAL VARIABILITY; INVERSE MODELLING; LAND DATA ASSIMILATION SYSTEMS; LAND SURFACE MODELS; PARAMETER OPTIMISATION;

INVERSE PROBLEMS;

ABOVEGROUND BIOMASS; AGRICULTURAL LAND; ANNUAL VARIATION; CROP YIELD; DATA ASSIMILATION; DROUGHT; EXPERIMENTAL STUDY; FEASIBILITY STUDY; INVERSE ANALYSIS; LAND SURFACE; LEAF AREA INDEX; OPTIMIZATION; PARAMETERIZATION; RAINFED AGRICULTURE; SOIL WATER; TIME SERIES ANALYSIS; WATER CONTENT;

FRANCE;

EID: 85030529960     PISSN: 10275606     EISSN: 16077938     Source Type: Journal    
DOI: 10.5194/hess-21-4861-2017     Document Type: Article

References (57)

1. Agreste: Annual statistical surveys over France, available at: http://agreste.agriculture.gouv.fr/(last access: September 2017), 2015.
2. Agreste Bilans: Agreste, Publications, Chiffres et Données No. 11, Bilan conjoncturel de l'année agricole 2001, 16 pp., available at: www.agreste.agriculture.gouv.fr/IMG/pdf/BILAN2001NOTE. pdf (last access: February 2017), 2001.
3. Agreste Bilans: Agreste, Publications, Chiffres et Données Agriculture, Bilan conjoncturel Novembre 2003, 2 pp., available at: http://agreste.agriculture.gouv.fr/IMG/pdf/conjenc10311.pdf (last access: February 2017), 2003.
4. Agreste Bilans: Agreste, Publications, Chiffres et Données No. 10-11, Bilan conjoncturel 2007, 40 pp., available at: www. agreste.agriculture.gouv.fr/IMG/pdf/bilan2007note.pdf (last access: February 2017), 2007.
5. Agreste Bilans: Agreste, Publications, Chiffres et Données Agriculture No. 7, Bilan conjoncturel 2011, 45 pp., available at: www. agreste.agriculture.gouv.fr/IMG/pdf-bilan2011note.pdf (last access: February 2017), 2011.
6. Albergel, C., Calvet, J.-C., Mahfouf, J.-F., Rüdiger, C., Barbu, A. L., Lafont, S., Roujean, J.-L., Walker, J. P., Crapeau, M., and Wigneron, J.-P.: Monitoring of water and carbon fluxes using a land data assimilation system: a case study for southwestern France, Hydrol. Earth Syst. Sci., 14, 1109-1124, https://doi.org/10.5194/hess-14-1109-2010, 2010.
7. Al Majou, H., Bruand, A., Duval, O., Le Bas, C., and Vauer, A.: Prediction of soil water retention properties after stratification by combining texture, bulk density and the type of horizon, Soil Use Manage., 24, 383-391, https://doi.org/10.1111/j.1475-2743.2008.00180.x, 2008.
8. Barbu, A. L., Calvet, J.-C., Mahfouf, J.-F., Albergel, C., and Lafont, S.: Assimilation of Soil Wetness Index and Leaf Area Index into the ISBA-A-gs land surface model: grassland case study, Biogeosciences, 8, 1971-1986, https://doi.org/10.5194/bg-8-1971-2011, 2011.
9. Barbu, A. L., Calvet, J.-C., Mahfouf, J.-F., and Lafont, S.: Integrating ASCAT surface soil moisture and GEOV1 leaf area index into the SURFEX modelling platform: a land data assimilation application over France, Hydrol. Earth Syst. Sci., 18, 173-192, https://doi.org/10.5194/hess-18-173-2014, 2014.
10. Baret, F., Weiss, M., Lacaze, R., Camacho, F., Makhmara, H., Pa-cholczyk, P., and Smets, B.: GEOV1: LAI and FAPAR essential climate variables and FCOVER global time series capitaliz-ing over existing products, Part 1: Principles of development and production, Remote Sens. Environ., 137, 299-309, 2013.
11. Bastos, A., Gouveia, C. M., Trigo, R. M., and Running, S. W.: Analysing the spatio-temporal impacts of the 2003 and 2010 extreme heatwaves on plant productivity in Europe, Biogeo-sciences, 11, 3421-3435, https://doi.org/10.5194/bg-11-3421-2014, 2014.
12. Becker-Reshef, I., Vermote, E., Lindeman, M., and Justice, C.: A generalized regression-based model for forecasting winter wheat yields in Kansas and Ukraine using MODIS data, Remote Sens. Environ., 114, 1312-1323, 2010.
13. Cabelguenne, M. and Debaeke, P.: Experimental determination and modelling of the soil water extraction capacities of crops of maize, sunflower, soya bean, sorghum and wheat, Plant Soil, 202, 175-192, https://doi.org/10.1023/A:1004376728978, 1998.
14. Calvet, J.-C.: Investigating soil and atmospheric plant water stress using physiological and micrometeorological data, Agr. Forest Meteorol., 103, 229-247, 2000.
15. 2-enrichment effects using an interactive vegetation SVAT scheme, Agr. Forest Meteorol., 108, 129-152, 2001.
16. Calvet, J.-C., Noilhan, J., Roujean, J., Bessemoulin, P., Ca-belguenne, M., Olioso, A., and Wigneron, J.: An interactive vegetation SVAT model tested against data from six contrasting sites, Agr. Forest Meteorol., 92, 73-95, 1998.
17. Calvet, J.-C., Gibelin, A.-L., Roujean, J.-L., Martin, E., Le Moigne, P., Douville, H., and Noilhan, J.: Past and future scenarios of the effect of carbon dioxide on plant growth and transpiration for three vegetation types of southwestern France, At-mos. Chem. Phys., 8, 397-406, https://doi.org/10.5194/acp-8-397-2008, 2008.
18. Calvet, J.-C., Lafont, S., Cloppet, E., Souverain, F., Badeau, V., and Le Bas, C.: Use of agricultural statistics to verify the interannual variability in land surface models: a case study over France with ISBA-A-gs, Geosci. Model Dev., 5, 37-54, https://doi.org/10.5194/gmd-5-37-2012, 2012.
19. Canal, N., Calvet, J.-C., Decharme, B., Carrer, D., Lafont, S., and Pigeon, G.: Evaluation of root water uptake in the ISBA-A-gs land surface model using agricultural yield statistics over France, Hydrol. Earth Syst. Sci., 18, 4979-4999, https://doi.org/10.5194/hess-18-4979-2014, 2014.
20. Capa-Morocho, M., Rodriguez-Fonseca, B., and Ruiz-Ramoz, M.: Crop yields as a bioclimatic index of El Nino impact in Europe: Crop forecast implications, Agr. Forest Meteorol., 198-199, 42-52, https://doi.org/10.1016/j.agrformet.2014.07.012, 2014.
21. Carrer, D., Roujean, J.-L., Lafont, S., Calvet, J.-C., Boone, A., Decharme, B., Delire, C., and Gastellu-Etchegorry, J.-P.: A canopy radiative transfer scheme with explicit FA-PAR for the interactive vegetation model ISBA-A-gs: impact on carbon fluxes, J. Geophys. Res.-Biogeo., 118, 1-16, https://doi.org/10.1002/jgrg.20070, 2013.
22. Carrer, D., Meurey, C., Ceamanos, X., Roujean, J.-L., Calvet, J.-C., and Liu, S.: Dynamic mapping of snow-free vegetation and bare soil albedos at global 1 km scale from 10-year analysis of MODIS satellite products, Remote Sens. Environ., 140, 420-432, https://doi.org/10.1016/j.rse.2013.08.041, 2014.
23. Copernicus: LAI GEOV1, available at: http://land.copernicus.eu/global/(last access: September 2017), 2015.
24. Crow, W. T., Kumar, S. V., and Bolten, J. D.: On the utility of land surface models for agricultural drought monitoring, Hydrol. Earth Syst. Sci., 16, 3451-3460, https://doi.org/10.5194/hess-16-3451-2012, 2012.
25. Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bid-lot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kallberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J. J., Park, B. K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., and Vitart, F.: The ERA-Interim reanalysis: configuration and performance of the data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553-597, https://doi.org/10.1002/qj.828, 2011.
26. Eitzinger, J., Trnka, M., Hösch, J., Žalud, Z., and Dubrovský, M.: Comparison of CERES, WOFOST and SWAP models in simulating soil water content during growing season under different soil conditions, Ecol. Model., 171, 223-246, https://doi.org/10.1016/j.ecolmodel.2003.08.012, 2004.
27. Faroux, S., Kaptué Tchuenté, A. T., Roujean, J.-L., Masson, V., Martin, E., and Le Moigne, P.: ECOCLIMAP-II/Europe: a twofold database of ecosystems and surface parameters at 1km resolution based on satellite information for use in land surface, meteorological and climate models, Geosci. Model Dev., 6, 563-582, https://doi.org/10.5194/gmd-6-563-2013, 2013.
28. Ferrant, S., Gascoin, S., Veloso, A., Salmon-Monviola, J., Claverie, M., Rivalland, V., Dedieu, G., Demarez, V., Ceschia, E., Probst, J.-L., Durand, P., and Bustillo, V.: Agro-hydrology and multi-temporal high-resolution remote sensing: toward an explicit spatial processes calibration, Hydrol. Earth Syst. Sci., 18, 5219-5237, https://doi.org/10.5194/hess-18-5219-2014, 2014.
29. Folberth, C., Skalsky, R., Moltchanova, E., Balkovic, J., Azevedo, L. B., Obersteiner, M., and van der Velde, M.: Uncertainty in soil data can outweigh climate impact signals in global crop yield simulations, Nat. Commun., 7, 11872, https://doi.org/10.1038/ncomms11872, 2016.
30. Ford, T. W., Harris, E., and Quiring, S. M.: Estimating root zone soil moisture using near-surface observations from SMOS, Hy-drol. Earth Syst. Sci., 18, 139-154, https://doi.org/10.5194/hess-18-139-2014, 2014.
31. Ghilain, N., Arboleda, A., Sepulcre-Cantò, G., Batelaan, O., Ardö, J., and Gellens-Meulenberghs, F.: Improving evapotranspiration in a land surface model using biophysical variables derived from MSG/SEVIRI satellite, Hydrol. Earth Syst. Sci., 16, 2567-2583, https://doi.org/10.5194/hess-16-2567-2012, 2012.
32. Gibelin, A.-L., Calvet, J.-C., Roujean, J.-L., Jarlan, L., and Los, S. O.: Ability of the land surface model ISBA-A-gs to simulate leaf area index at the global scale: Comparison with satellites products, J. Geophys. Res., 111, D18102, https://doi.org/10.1029/2005JD006691, 2006.
33. Ichii, K., Wang, W., Hashimoto, H., Yang, F., Votava, P., Michaelis., A. R., and Nemani, R. R.: Refinement of rooting depths using satellite based evapotranspiration seasonality for ecosystem modelling in California, Agr. Forest Meteorol., 149, 1907-1918, 2009.
34. Jung, M., Reichstein, M., and Bondeau, A.: Towards global empirical upscaling of FLUXNET eddy covariance observations: validation of a model tree ensemble approach using a biosphere model, Biogeosciences, 6, 2001-2013, https://doi.org/10.5194/bg-6-2001-2009, 2009.
35. Kowalik, W., Dabrowska-Zielinska, K., Meroni, M., Raczka, U. T., and de Wit A.: Yield estimation using SPOT-VEGETATION products: A case study of wheat in European countries, Int. J. Appl. Earth Obs. Geoinf., 32, 228-239, https://doi.org/10.1016/j.jag.2014.03.011, 2014.
36. Krinner, G., Viovy, N., de Noblet-Ducoudré, N., Ogée, J., Polcher, J., Friedlingstein, P., Ciais, P., Sitch, S., and Prentice, I. C.: A dynamic global vegetation model for studies of the coupled atmosphere-biosphere system, Global Biogeochem. Cy., 19, GB1015, https://doi.org/10.1029/2003GB002199, 2005.
37. Li, S., Wheeler, T., Challinor, A., Lin, E., Ju, H., and Xu, Y.: The observed relationship between wheat and cli-mate in China, Agr. Forest Meteorol., 150, 1412-1419, https://doi.org/10.1016/j.agrformet.2010.07.003, 2010.
38. Loubet, B., Laville, P. Lehuger, S., Larmanou, E., Fléchard C., Mascher N., Genermont S., Roche R., Ferrara, R. M., Stella, P., Personne, E., Durand B., Decuq C., Flura, D., Mas-son, S., Fanucci, O., Rampon, J.-N., Siemens, J., Kindler, R., Gabrielle B., Schrumpf, M., and Cellier P.: Carbon, nitrogen and Greenhouse gases budgets over a four years crop rotation in northern France, Plant Soil, 343, 109-137, https://doi.org/10.1007/s11104-011-0751-9, 2011.
39. Masson, V., Le Moigne, P., Martin, E., Faroux, S., Alias, A., Alkama, R., Belamari, S., Barbu, A., Boone, A., Bouyssel, F., Brousseau, P., Brun, E., Calvet, J.-C., Carrer, D., Decharme, B., Delire, C., Donier, S., Essaouini, K., Gibelin, A.-L., Giordani, H., Habets, F., Jidane, M., Kerdraon, G., Kourzeneva, E., Lafaysse, M., Lafont, S., Lebeaupin Brossier, C., Lemonsu, A., Mahfouf, J.-F., Marguinaud, P., Mokhtari, M., Morin, S., Pigeon, G., Sal-gado, R., Seity, Y., Taillefer, F., Tanguy, G., Tulet, P., Vincendon, B., Vionnet, V., and Voldoire, A.: The SURFEXv7.2 land and ocean surface platform for coupled or offline simulation of earth surface variables and fluxes, Geosci. Model Dev., 6, 929-960, https://doi.org/10.5194/gmd-6-929-2013, 2013.
40. Miralles, D. G., Holmes, T. R. H., De Jeu, R. A. M., Gash, J. H., Meesters, A. G. C. A., and Dolman, A. J.: Global land-surface evaporation estimated from satellite-based observations, Hydrol. Earth Syst. Sci., 15, 453-469, https://doi.org/10.5194/hess-15-453-2011, 2011.
41. Munier, S., Carrer, D., Planque, C., Camacho, F., Albergel, C., and Calvet, J.-C.: Satellite Leaf Area Index: global scale analysis of the tendencies per vegetation type over the last 17 years, Remote Sens. Environ., submitted, 2017.
42. Nachtergaele, F., van Velthuize, H., Verelst, L., Wiberg, D., Batjes, N., Dijkshoorn, K., van Engelen, V., Fischer, G., Jones, A., Montanarella, L., Petri, M., Prieler, S., Teixeira, E., and Shi, X.: Harmonized World Soil Database (version 1.2), 2012, available at: http://webarchive.iiasa.ac.at/Research/LUC/External-World-soil-database/HWSD-Documentation.pdf (last access: December 2014), 2012.
43. Olesen, J. E., Trnka, M., Kersebaum, K. C., Skjelvag, A. O., Seguin, B., Peltonen-Sainio, P., Rossi, F., Kozyra, J., and Mi-cale, F.: Impacts and adaptation of European crop production systems to climate change, Euro. J. Agronomy., 34, 96-112, https://doi.org/10.1016/j.eja.2010.11.003, 2011.
44. Piedallu, C., Gégout, J.-C., Bruand, A., and Seynave, I., Mapping soil water holding capacity over large areas to predict potential production of forest stands, Geoderma, 160, 355-366, https://doi.org/10.1016/j.geoderma.2010.10.004, 2011.
45. Portoghese, I., Iacobellis, V., and Sivapalan, M.: Analysis of soil and vegetation patterns in semi-arid Mediterranean landscapes by way of a conceptual water balance model, Hydrol. Earth Syst. Sci., 12, 899-911, https://doi.org/10.5194/hess-12-899-2008, 2008.
46. Quiroga, S., Fernández-Haddad, Z., and Iglesias, A.: Crop yields response to water pressures in the Ebro basin in Spain: risk and water policy implications, Hydrol. Earth Syst. Sci., 15, 505-518, https://doi.org/10.5194/hess-15-505-2011, 2011.
47. Ritchie, J. T. and Otter, S.: Description and performance of CERES-wheat: A user-oriented wheat yield model, ARS wheat yield project, 38, 159-175, 1985.
48. Rüdiger, C., Albergel, C., Mahfouf, J.-F., Calvet, J.-C., and Walker, J. P.: Evaluation of Jacobians for Leaf Area Index data assimilation with an extended Kalman filter, J. Geophys. Res., 115, D09111, https://doi.org/10.1029/2009JD012912, 2010.
49. Soylu, M. E., Istanbulluoglu, E., Lenters, J. D., and Wang, T.: Quantifying the impact of groundwater depth on evapotranspiration in a semi-arid grassland region, Hydrol. Earth Syst. Sci., 15, 787-806, https://doi.org/10.5194/hess-15-787-2011, 2011.
50. Szczypta, C., Decharme, B., Carrer, D., Calvet, J.-C., Lafont, S., Somot, S., Faroux, S., and Martin, E.: Impact of precipitation and land biophysical variables on the simulated discharge of European and Mediterranean rivers, Hydrol. Earth Syst. Sci., 16, 3351-3370, https://doi.org/10.5194/hess-16-3351-2012, 2012.
51. Szczypta, C., Calvet, J.-C., Maignan, F., Dorigo, W., Baret, F., and Ciais, P.: Suitability of modelled and remotely sensed essential climate variables for monitoring Euro-Mediterranean droughts, Geosci. Model Dev., 7, 931-946, https://doi.org/10.5194/gmd-7-931-2014, 2014.
52. Tanaka, K., Takizawa, H., Kume, T., Xu, J., Tantasirin, C., and Suzuki, M.: Impact of rooting depth of soil hydraulic properties on the transpiration peak of an evergreen forest in northern Thailand in the late dry season, J. Geophys. Res., 109, D23107, https://doi.org/10.1029/2004JD004865, 2004.
53. Van Dam, J. C., Huygen, J., Wesseling, J. G., Feddes, R. A., Kabat, P., Van Walsum, P. E. V., Groenendijk, P., and Van Diepen, C. A.: Theory of SWAP version 2.0. Simulation of water flow, solute transport and plant growth in the Soil-Water-Atmosphere-Plant environment, Report 71, Sub department of Water Resources, Wageningen University, Technical document, 45, 1997.
54. Van Der Velde, M., Tubiello, N. F., Vrieling, A., and Bouraoui, F.: Impacts of extreme weather on wheat and maize in France: evaluating regional crop simulations against observed data, Climatic Change, 113, 751-765, https://doi.org/10.1007/s10584-011-0368-2 2012.
55. Van Diepen, C. A., Wolf, J., Van Keulen, H., and Rappoldt, C.: WOFOST: a simulation model of crop production, Soil Use Manage., 5, 16-24, 1989.
56. Wang, S., Fu, B. J., Gao, G. Y., Yao, X. L., and Zhou, J.: Soil moisture and evapotranspiration of different land cover types in the Loess Plateau, China, Hydrol. Earth Syst. Sci., 16, 2883-2892, https://doi.org/10.5194/hess-16-2883-2012, 2012.
57. Weedon, G. P., Balsamo, G., Bellouin, N., Gomes, S., Best, M. J., and Viterbo, P.: The WFDEI meteorological forcing data set: WATCH Forcing Data methodology applied to ERA-Interim reanalysis data, Water Resour. Res., 50, 7505-7514, https://doi.org/10.1002/2014WR015638, 2014.