Calibration of the LINGRA-N model to simulate herbage yield of grass monocultures and permanent grassland in Slovenia

Tjaša POGAČAR, Domen IPAVEC, Janko VERBIČ, Lučka KAJFEŽ-BOGATAJ

Abstract


In this study, we calibrated the LINGRA-N model using the minimization of RMSE, and proceeded to evaluate its performance. We simulated herbage dry matter yield of cock's foot (Dactylis glomerata L.) and perennial ryegrass (Lolium perenne L.) in Jablje in the period 1998–2013, and multiplespecies grassland in Ljubljana (S72) in 1974–1993. The overall performance of LINGRA-N is fair for perennial ryegrass (RMSE% < 25%) and good for cock’s foot and S72 (RMSE% < 15%). The index of agreement (d) suggests that LINGRA-N is not calibrated well enough to simulate the interannual herbage yield variability for S72, so the model cannot yet be used for the simulation of multi-species grassland herbage yield. In contrast, the herbage yields of cock’s foot and perennial ryegrass in Jablje are simulated correctly (with d values 0.84 and 0.78, respectively). One of our further goals is to use the calibrated model on a specific location for the simulation of the herbage yield of grass monocultures under various weather conditions as well as for the simulation of climate change effect on it.


Keywords


grasses; gramineae; dry matter content; crop yield; statistical data; statistical methods; models; simulation; weather data

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References


ARSO – climatological data. 2014. Slovenian Environment Agency (http://www.arso.gov.si/): database output

Barrett P.D., Laidlaw A.S. 2005. Grass growth modelling: to increase understanding and aid decisionmaking on-farm. V: Utilization of grazed grass in temperate animal systems. Murphy J.J. (ed.). Wageningen, Wageningen Academic Publishers: 79-88

Barrett P.D., Laidlaw A.S., Mayne C.S. 2005. GrazeGro: a European herbage growth model to predict pasture production in perennial ryegrass swards for decision support. European Journal of Agronomy, 23: 37-56; DOI: 10.1016/j.eja.2004.09.006

Bouman B.A.M., Schapendonk A.H.C.M., Stol W., Van Kraalingen D.W.G. 1996. Description of the growth model LINGRA as implemented in CGMS. Quantitative Approaches in Systems Analysis, 7: 11-56

CPVO – soil data. 2014. Centre of soil and environmental science, Biotechnical Faculty, University of Ljubljana (http://web.bf.unilj. si/cpvo/): database output

Herrmann A., Michael K., Kornher A. 2005. Performance of grassland under different cutting regimes as affected by sward composition, nitrogen input, soil conditions and weather – a simulation study. European Journal of Agronomy, 22: 141- 158; DOI: 10.1016/j.eja.2004.02.002

Jego G., Belanger G., Tremblay G.F., Jing Q., Baron V.S. 2013. Calibration and performance evaluation of the STICS crop model for simulating timothy growth and nutritive value. Field Crops Research, 151: 65-77; DOI: 10.1016/j.fcr.2013.07.003

Kapun S. 2005. Pridelovanje pasje trave. Naše travinje 1, 1: 10-11

KIS – herbage yield data of grass monocultures. 2014. Agricultural Institute of Slovenia (http://www.kis.si/): database output

Lazzarotto P., Calanca P., Fuhrer J. 2009. Dynamics of grass-clover mixtures – An analysis of the response to management with the PROductive GRASsland Simulator (PROGRASS). Ecological Modelling, 220: 703-724; DOI: 10.1016/j.ecolmodel.2008.11.023

Merot A., Bergez J.E., Wallach D., Duru M. 2008. Adaptation of a functional model of grassland to simulate the behaviour of irrigated grasslands under a Mediterranean climate: The Crau case. European Journal of Agronomy, 29: 163-174; DOI: 10.1016/j.eja.2008.05.006

Persson T., Höglind M., Gustavsson A.M., Halling M., Jauhiainen L. et al. 2014. Evaluation of the LINGRA timothy model under Nordic conditions. Field Crops Research, 161: 87-97; DOI: 10.1016/j.fcr.2014.02.012

Pogačar T., Kajfež-Bogataj L. 2011. LINGRA: model za simulacijo rasti in pridelka travne ruše. Acta agriculturae Slovenica, 97, 3: 319-327

Saxton K.E., Rawls W.J. 2006. Soil water characteristic estimates by texture and organic matter for hydrologic solutions. Soil Science Society of America Journal, 70: 1569-1578 ; DOI: 10.2136/sssaj2005.0117

Schapendonk A.H.C.M., Stol W., Van Kraalingen D.W.G., Bouman B.A.M. 1998. LINGRA, a sink/source model to simulate grassland productivity in Europe. European Journal of Agronomy, 9: 87-100; DOI: 10.1016/S1161- 0301(98)00027-6

Shibu M.E., Leffelaar P.A., Van Keulen H., Aggarwal P.K. 2010. LINTUL3, a simulation model for nitrogen-limited situations: Application to rice. European Journal of Agronomy, 32: 255-271; DOI: 10.1016/j.eja.2010.01.003

Smit H.J., Metzger M.J., Ewert F. 2008. Spatial distribution of grassland productivity and land use in Europe. Agricultural Systems, 98: 208-219; DOI: 10.1016/j.agsy.2008.07.004

SURS – grassland data. 2014. Statistical office of the Republic of Slovenia. http://pxweb.stat.si/pxweb/Database/Okolje/Okolje. asp (17. 12. 2014)

Tajnšek A. 2003. Deset let trajnih poskusov IOSDV v Sloveniji, Jable in Rakičan 1993–2003. In: Namen in cilj trajnih poljskih poskusov IOSDV Jable in IOSDV Rakičan. Žalec, 12. 12. 2003. Tajnšek A., Čeh Brežnik B., Kocjan Ačko D. (eds.). Proceedings of the conference, Slovensko agronomsko društvo: 7-24

Tehnološka priporočila za zmanjšanje občutljivosti kmetijske pridelave na sušo: poljedelstvo, travništvo, zelenjadarstvo in hmeljarstvo. 2008. Ljubljana, Ministry of Agriculture, Forestry and Food: 44 p. http://www.arsktrp.gov.si/fileadmin/arsktrp.gov.si/p ageuploads/Aktualno/Aktualno/2013/Tehnoloska_p riporocila_za_zmanjsanje_obcutljivosti_na_suso.pd f (18. 11. 2013)

Trnka M., Eitzinger J., Gruszczynsk G., Buchgraber K., Resch R., Schaumberger A. 2006. A simple statistical model for predicting herbage production from permanent grassland. Grass and Forage S cience, 61: 253-271; DOI: 10.1111/j.1365- 2494.2006.00530.x

Van Oijen M., Höglind M., Hanslin H.M., Caldwell N. 2005. Process-based modeling of Timothy regrowth. Agronomy Journal, 97: 1295-1303; DOI: 10.1111/j.1365-2494.2006.00530.x

Willmott C.J. 1982. Some comments on the evaluation of model performance. Bulletin of the American Meteorological Society, 63: 1309-1313; DOI: 10.1175/1520- 0477(1982)063<1309:SCOTEO>2.0.CO;2

Wolf J. 2006. Grassland data from PASK study and testing of LINGRA in CGMS. ASEMARS Project report no. 2. Wageningen, Alterra: 38 p.

Wolf J. 2012. LINGRA-N: Simple generic model for simulation of grass growth under potential, water limited and nitrogen limited conditions. User guide for LINGRA-N. Wageningen, Wageningen University (available on agreement): 65 p.

Žalud Z., Trnka M., Ruget F., Hlavinka P., Eitzinger J., Schaumberger A. 2006. Evaluation of crop model STICS in the conditions of the Czech Republic and Austria. In: Proceedings of the conference Bioclimatology and water in the land (poster), Strecno, 11.-14. 9. 2006: 7 p. http://www.cbks.cz/sbornikStrecno06/prispevky/Po sterII_clanky/P2-16.pdf (11. 11. 2013)

Žitek D. 1991. Dinamika razvoja pridelka travne ruše pri različnem gnojenju v enem letu. Bachelor thesis. Ljubljana, University of Ljubljana, Biotechnical Faculty, Department of Agronomy: 128 p.




DOI: http://dx.doi.org/10.14720/aas.2015.105.1.12

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