Global sensitivity analysis of yield output from the water productivity model

This study includes a global sensitivity analysis of the water productivity model AquaCrop. The study rationale consisted in a comprehensive evaluation of the model and the formulation of guidelines for model simplification and efficient calibration. The global analysis comprehended a Morris screening followed by a variance-based Extended Fourier Amplitude Sensitivity Test (EFAST) under diverse environmental conditions for maize, winter wheat and rice. The analysis involved twenty-two different climate-crop-soil-meteorology combinations. The main objectives were to distinguish the model's influential and non-influential parameters, and to examine the yield output sensitivity. For the AquaCrop model, a number of non-influential parameters could be identified. Making these parameters fixed would be a step towards model simplification. Also, a list of influential parameters was identified. Despite the dependence of parameter ranking on environmental conditions, guiding principles for priority parameters were formulated for calibration in diverse conditions, valuable to model users. For this model that focuses on modelling yield response to water, parameters describing crop responses to water stress were not often among those showing highest sensitivity. Instead, particular root and soil parameters, relevant in the determination of water availability, were influential under various conditions and merit attention during calibration. The considerations made in this study about sensitivity analysis method (Morris vs. EFAST), prior parameter ranges, target functions and ranking variation according to environmental conditions can be extrapolated to other conditions and models, if done with the necessary precaution. Yield output variability of AquaCrop tested with global Morris and EFAST techniques.Morris and EFAST give similar but not identical results.Sensitivity rankings depend on environment, target output and prior parameter range.Guidelines for priority parameters given for calibration in specific settings.Non-influential AquaCrop parameters identified to be fixed for model simplification.

[1]  A. Saltelli,et al.  A quantitative model-independent method for global sensitivity analysis of model output , 1999 .

[2]  Stefano Tarantola,et al.  Sensitivity analysis of the rice model WARM in Europe: Exploring the effects of different locations, climates and methods of analysis on model sensitivity to crop parameters , 2010, Environ. Model. Softw..

[3]  A. Saltelli,et al.  Tackling quantitatively large dimensionality problems , 1999 .

[4]  P. Steduto,et al.  Validation and testing of the AquaCrop model under full and deficit irrigated wheat production in Iran , 2011 .

[5]  D. Raes,et al.  AquaCrop — The FAO Crop Model to Simulate Yield Response to Water: II. Main Algorithms and Software Description , 2009 .

[6]  Dirk Raes,et al.  UNRAVELLING CROP WATER PRODUCTIVITY OF TEF (ERAGROSTIS TEF (ZUCC.) TROTTER) THROUGH AQUACROP IN NORTHERN ETHIOPIA , 2011, Experimental Agriculture.

[7]  Dirk Raes,et al.  Cereal yield stabilization in Terai (Nepal) by water and soil fertility management modeling , 2013 .

[8]  Jon C. Helton,et al.  Uncertainty and sensitivity analysis techniques for use in performance assessment for radioactive waste disposal , 1993 .

[9]  Max D. Morris,et al.  Factorial sampling plans for preliminary computational experiments , 1991 .

[10]  Anthony J. Jakeman,et al.  Ten iterative steps in development and evaluation of environmental models , 2006, Environ. Model. Softw..

[11]  John R. Williams,et al.  A general, process-oriented model for two competing plant species , 1992 .

[12]  D. Raes,et al.  AquaCrop—The FAO Crop Model to Simulate Yield Response to Water: III. Parameterization and Testing for Maize , 2009 .

[13]  Marco Acutis,et al.  Sensitivity analysis for a complex crop model applied to Durum wheat in the Mediterranean. , 2010 .

[14]  S. Evett,et al.  Validating the FAO AquaCrop Model for Irrigated and Water Deficient Field Maize , 2009 .

[15]  A. Saltelli,et al.  Sensitivity analysis of an environmental model: an application of different analysis methods , 1997 .

[16]  A. Saltelli,et al.  Sensitivity Anaysis as an Ingredient of Modeling , 2000 .

[17]  J. Nash,et al.  River flow forecasting through conceptual models part I — A discussion of principles☆ , 1970 .

[18]  Gianni Bellocchi,et al.  Comparison of sensitivity analysis techniques: A case study with the rice model WARM , 2010 .

[19]  B. Croke,et al.  Addressing ten questions about conceptual rainfall–runoff models with global sensitivity analyses in R , 2013 .

[20]  R Lardy,et al.  Sensitivity analysis for models of greenhouse gas emissions at farm level. Case study of N(2)O emissions simulated by the CERES-EGC model. , 2011, Environmental pollution.

[21]  Peter A. Vanrolleghem,et al.  Uncertainty in the environmental modelling process - A framework and guidance , 2007, Environ. Model. Softw..

[22]  J. Seinfeld,et al.  Automatic sensitivity analysis of kinetic mechanisms , 1979 .

[23]  Patrick Willems,et al.  Assessment of the sensitivity and prediction uncertainty of evaporation models applied to Nasser Lake, Egypt , 2010 .

[24]  X. Y. Sun,et al.  Three complementary methods for sensitivity analysis of a water quality model , 2012, Environ. Model. Softw..

[25]  C. Ciric,et al.  Use of sensitivity analysis to identify influential and non-influential parameters within an aquatic ecosystem model , 2012 .

[26]  R. Hilborn,et al.  Fisheries stock assessment and decision analysis: the Bayesian approach , 1997, Reviews in Fish Biology and Fisheries.

[27]  Dirk Raes,et al.  SOWING STRATEGIES FOR BARLEY (HORDEUM VULGARE L.) BASED ON MODELLED YIELD RESPONSE TO WATER WITH AQUACROP , 2012, Experimental Agriculture.

[28]  D. Raes,et al.  Simulating Yield Response of Quinoa to Water Availability with AquaCrop , 2009 .

[29]  David Makowski,et al.  Global sensitivity analysis for calculating the contribution of genetic parameters to the variance of crop model prediction , 2006, Reliab. Eng. Syst. Saf..

[30]  Roberto Confalonieri,et al.  Monte Carlo based sensitivity analysis of two crop simulators and considerations on model balance , 2010 .

[31]  Patrick Willems,et al.  Model uncertainty analysis by variance decomposition , 2010 .

[32]  Kevin McNally,et al.  A Workflow for Global Sensitivity Analysis of PBPK Models , 2011, Front. Pharmacol..

[33]  Jing Wang,et al.  Parameter sensitivity analysis of crop growth models based on the extended Fourier Amplitude Sensitivity Test method , 2013, Environ. Model. Softw..

[34]  Pete Smith,et al.  Sensitivity of crop model predictions to entire meteorological and soil input datasets highlights vulnerability to drought , 2012, Environ. Model. Softw..

[35]  D. Raes,et al.  AquaCrop-The FAO Crop Model to Simulate Yield Response to Water: I. Concepts and Underlying Principles , 2009 .

[36]  Pasquale Steduto,et al.  A systematic and quantitative approach to improve water use efficiency in agriculture , 2007, Irrigation Science.

[37]  Andrea Saltelli,et al.  An effective screening design for sensitivity analysis of large models , 2007, Environ. Model. Softw..

[38]  Paola Annoni,et al.  Sixth International Conference on Sensitivity Analysis of Model Output How to avoid a perfunctory sensitivity analysis , 2010 .

[39]  Francisco Javier Elorza,et al.  Sensitivity analysis of distributed environmental simulation models: understanding the model behaviour in hydrological studies at the catchment scale , 2003, Reliab. Eng. Syst. Saf..

[40]  E. Mashonjowa,et al.  Using seasonal climate forecasts to improve maize production decision support in Zimbabwe , 2011 .

[41]  A. Saltelli,et al.  The role of sensitivity analysis in ecological modelling , 2007 .

[42]  Stefano Tarantola,et al.  Sensitivity Analysis as an Ingredient of Modeling , 2000 .