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Sensitivity Analysis and Investigation of the Behaviour of the UTOPIA Land-Surface Process Model: A Case Study for Vineyards in Northern Italy

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Abstract

We used sensitivity-analysis techniques to investigate the behaviour of the land-surface model UTOPIA while simulating the micrometeorology of a typical northern Italy vineyard (Vitis vinifera L.) under average climatic conditions. Sensitivity-analysis experiments were performed by sampling the vegetation parameter hyperspace using the Morris method and quantifying the parameter relevance across a wide range of soil conditions. This method was used since it proved its suitability for models with high computational time or with a large number of parameters, in a variety of studies performed on different types of biophysical models. The impact of input variability was estimated on reference model variables selected among energy (e.g. net radiation, sensible and latent heat fluxes) and hydrological (e.g. soil moisture, surface runoff, drainage) budget components. Maximum vegetation cover and maximum leaf area index were ranked as the most relevant parameters, with sensitivity indices exceeding the remaining parameters by about one order of magnitude. Soil variability had a high impact on the relevance of most of the vegetation parameters: coefficients of variation calculated on the sensitivity indices estimated for the different soils often exceeded 100 %. The only exceptions were represented by maximum vegetation cover and maximum leaf area index, which showed a low variability in sensitivity indices while changing soil type, and confirmed their key role in affecting model results.

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References

  • Asseng S, Bar-Tal A, Bowden JW, Keating BA, Van Herwaarden A, Palta JA, Huth NI, Probert ME (2002) Simulation of grain protein content with APSIM-Nwheat. Eur J Agron 16: 25–42

    Article  Google Scholar 

  • Balsamo G, Bouyssel F, Noilhan J (2004) A simplified bi-dimensional variational analysis of soil moisture from screen-level observations in a mesoscale numerical weather prediction model. Q J R Meteorol Soc 130: 895–915

    Article  Google Scholar 

  • Bastidas LA, Gupta HV, Sorooshian S, Shuttleworth WJ, Yang ZL (1999) Sensitivity analysis of a land surface scheme using multicriteria methods. J Geophys Res 104(D16): 481–490

    Article  Google Scholar 

  • Bastidas LA, Hogue TS, Sorooshian S, Gupta HV, Shuttleworth WJ (2006) Parameter sensitivity analysis for different complexity land surface models using multicriteria methods. J Geophys Res 111(D20): 1–19

    Article  Google Scholar 

  • Campolongo F, Cariboni J, Saltelli A (2007) An effective screening design for sensitivity analysis of large models. Environ Model Softw 22: 1509–1518

    Article  Google Scholar 

  • Cariboni J, Gatelli D, Liska R, Saltelli A (2007) The role of sensitivity analysis in ecological modelling. Ecol Model 203: 167–182

    Article  Google Scholar 

  • Cassardo C (2012) The University of Torino land surface process interaction model in atmosphere (UTOPIA)—version 2012. Internal report 2012/01 [R/OL]. University of Turin, Department of Physics, Italy

  • Cassardo C, Ji JJ, Longhetto A (1995) A study of the performances of a land surface process model (LSPM). Boundary-Layer Meteorol 72: 87–121

    Article  Google Scholar 

  • Clapp RB, Hornberger GM (1978) Empirical equations for some soil hydraulic properties. Water Resour Res 14: 601–604

    Article  Google Scholar 

  • Confalonieri R (2010) Monte Carlo based sensitivity analysis of two crop simulators and considerations on model balance. Eur J Agron 33: 89–93

    Article  Google Scholar 

  • Confalonieri R, Bellocchi G, Bregaglio S, Donatelli M, Acutis M (2010) Comparison of sensitivity analysis techniques: a case study with the rice model WARM. Ecol Model 221: 1897–1906

    Article  Google Scholar 

  • Dickinson RE, Henderson-Sellers A, Kennedy PJ, Wilson MF (1986) Biosphere-Atmosphere Transfer Scheme (BATS) for the NCAR community climate model—NCAR/TN-275+STR NCAR technical note, Boulder, CO

  • Francone C, Cassardo C, Spanna F, Alemanno L, Bertoni D, Richiardone R, Vercellino I (2010) Preliminary results on the evaluation of factors influencing evapotranspiration processes in vineyards. Water 2: 916–937

    Article  Google Scholar 

  • Galli M, Oh S, Cassardo C, Park SK (2010) The occurrence of cold spells in the Alps related to climate change. Water 2: 363–380

    Article  Google Scholar 

  • Garratt JR (1992) The atmospheric boundary layer. Cambridge University Press, UK, p 316 pp

    Google Scholar 

  • Gao X, Sorooshian S, Gupta HV (1996) Sensitivity analysis of the biosphere–atmosphere transfer scheme. J Geophys Res 101: 7279–7289

    Article  Google Scholar 

  • Gulden LE, Yang Z-L, Niu G-Y (2008) Sensitivity of biogenic emissions simulated by a land-surface model to land-cover representations. Atmos Environ 42: 4185–4197

    Article  Google Scholar 

  • Jakeman AJ, Letcher RA, Norton JP (2006) Ten iterative steps in development and evaluation of environmental models. Environ Model Softw 21: 602–614

    Article  Google Scholar 

  • Kucherenko S, Rodriguez-Fernandez M, Pantelides C, Shah N (2009) Monte Carlo evaluation of derivative-based global sensitivity measures. Reliab Eng Syst Saf 94: 1135–1148

    Article  Google Scholar 

  • Liang X, Guo J (2003) Intercomparison of land surface parameterization schemes: Sensitivity of surface energy and water fluxes to model parameters. J Hydrol 279: 182–209

    Article  Google Scholar 

  • López-Lozano R, Baret F, Garcíade Cortázar-Atauri I, Bertrand N, Casterad MA (2009) Optimal geometric configuration and algorithms for LAI indirect estimates under row canopies: the case of vineyard. Agric For Meteorol 149: 1307–1316

    Article  Google Scholar 

  • Morris MD (1991) Factorial sampling plans for preliminary computational experiments. Technometrics 33: 161–174

    Article  Google Scholar 

  • Ortega-Farias S, Poblete-Echeverrìa C, Brisson N (2010) Parameterization of a two-layer model for estimating vineyard evapotranspiration using meteorological measurements. Agric For Meteorol 150: 276–286

    Article  Google Scholar 

  • Park SK, Droegemeier KK (1999) Sensitivity analysis of a moist 1D Eulerian cloud model using automatic differentiation. Mon Weather Rev 127: 2180–2196

    Article  Google Scholar 

  • Park SK, Droegemeier KK (2000) Sensitivity analysis of a 3D convective storm: implications for variational data assimilation and forecast error. Mon Weather Rev 128: 140–159

    Article  Google Scholar 

  • Pieri P (2010) Modelling radiative balance in a row-crop canopy: cross-row distribution of net radiation at the soil surface and energy available to clusters in a vineyard. Ecol Model 221: 802–811

    Article  Google Scholar 

  • Ratto M, Tarantola S, Saltelli A (2001) Sensitivity analysis in model calibration. GSA-GLUE approach. Comput Phys Commun 136: 212–224

    Article  Google Scholar 

  • Ravetz JR (1997) Integrated environmental assessment forum: developing guidelines for “Good Practice”, ULYSSES WP-97-1, ULYSSES project. Darmstadt University of Technology, Germany

    Google Scholar 

  • Refsgaard JC, Henriksen HJ, Harrar WG, Scholten H, Kassahun A (2005) Quality assurance in model based water management—review of existing practice and outline of new approaches. Environ Model Softw 20: 1201–1215

    Article  Google Scholar 

  • Richter GM, Acutis M, Trevisiol P, Latiri K, Confalonieri R (2010) Sensitivity analysis for a complex crop model applied to Durum wheat in the Mediterranean. Eur J Agron 32: 127–136

    Article  Google Scholar 

  • Saltelli A, Annoni P (2010) How to avoid a perfunctory sensitivity analysis. Environ Model Softw 25: 1508–1517

    Article  Google Scholar 

  • Saltelli A, Ratto M, Tarantola S, Campolongo F (2005) Sensitivity analysis for chemical models. Chem Rev 105: 2811–2827

    Article  Google Scholar 

  • Spano D, Snyder RL, Duce P, Paw UKT (2000) Estimating sensible and latent heat flux densities from grapevine canopies using surface renewal. Agric For Meteorol 104: 171–183

    Article  Google Scholar 

  • Spear RC, Grieb TM, Shang N (1994) Parameter uncertainty and interaction in complex environmental models. Water Resour Res 30: 3159–3169

    Article  Google Scholar 

  • Tarantola S, Saltelli A (2003) SAMO 2001: methodological advances and innovative applications of sensitivity analysis. Reliab Eng Syst Saf 79: 121–122

    Article  Google Scholar 

  • Trambouze W, Voltz M (2001) Measurement and modelling of the transpiration of a Mediterranean vineyard. Agric For Meteorol 107: 153–166

    Article  Google Scholar 

  • Wilson MF, Henderson-Sellers A, Dickinson RE, Kennedy PJ (1987) Sensitivity of the biosphere–atmosphere transfer scheme (BATS) to the inclusion of variable soil characteristics. J Clim Appl Meteorol 26: 341–362

    Article  Google Scholar 

  • Yang J (2011) Convergence and uncertainty analysis in Monte-Carlo based sensitivity analysis. Environ Model Softw 26: 444–457

    Article  Google Scholar 

  • Yunusa IAM, Walker RR, Lu P (2004) Evapotranspiration components from energy balance, sapflow and microlysimetry techniques for an irrigated vineyard in inland Australia. Agric For Meteorol 127: 93–107

    Article  Google Scholar 

  • Zarco-Tejada PJ, Berjón A, López-Lozano R, Miller JR, Martín P, Cachorro V, González MR, de Frutos A (2005) Assessing vineyard condition with hyperspectral indices: leaf and canopy reflectance simulation in a row-structured discontinuous canopy. Remote Sens Environ 99: 271–287

    Article  Google Scholar 

  • Zhang B, Kang S, Li F, Zhang L (2008) Comparison of three evapotranspiration models to Bowen ratio-energy balance method for a vineyard in an arid desert region of northwest China. Agric For Meteorol 148: 1629–1640

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Physics, University of Turin, Via Giuria 1, 10125, Torino, Italy

    C. Francone, C. Cassardo & R. Richiardone

  2. Department of Plant Production, CASSANDRA, University of Milan, Via Celoria 2, 20133, Milano, Italy

    C. Francone & R. Confalonieri

  3. Department of Mechanical and Aerospace Engineering, Polytechnic of Turin, Corso Duca degli Abruzzi 24, Torino, Italy

    C. Francone

  4. CINFAI, National Inter/University Consortium for Physics of the Atmosphere and Hydrosphere, Turin, Italy

    C. Cassardo & R. Richiardone

Authors
  1. C. Francone
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  2. C. Cassardo
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  3. R. Richiardone
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  4. R. Confalonieri
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Correspondence to C. Francone.

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Francone, C., Cassardo, C., Richiardone, R. et al. Sensitivity Analysis and Investigation of the Behaviour of the UTOPIA Land-Surface Process Model: A Case Study for Vineyards in Northern Italy. Boundary-Layer Meteorol 144, 419–430 (2012). https://doi.org/10.1007/s10546-012-9725-6

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  • DOI: https://doi.org/10.1007/s10546-012-9725-6

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