Addressing ten questions about conceptual rainfall–runoff models with global sensitivity analyses in R

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

[2]  T. McMahon,et al.  APPLICATION OF A CATCHMENT MODEL IN SOUTHEASTERN AUSTRALIA , 1975 .

[3]  E. L. Peck,et al.  Catchment modeling and initial parameter estimation for the National Weather Service River Forecast System , 1976 .

[4]  M. B. Beck,et al.  Water quality modeling: A review of the analysis of uncertainty , 1987 .

[5]  A. Jakeman,et al.  Computation of the instantaneous unit hydrograph and identifiable component flows with application to two small upland catchments , 1990 .

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

[7]  Ilya M. Sobol,et al.  Sensitivity Estimates for Nonlinear Mathematical Models , 1993 .

[8]  A. Jakeman,et al.  How much complexity is warranted in a rainfall‐runoff model? , 1993 .

[9]  V. Singh,et al.  Computer Models of Watershed Hydrology , 1995 .

[10]  A. Saltelli,et al.  Importance measures in global sensitivity analysis of nonlinear models , 1996 .

[11]  S. Sorooshian,et al.  Automatic calibration of conceptual rainfall-runoff models: sensitivity to calibration data , 1996 .

[12]  I. Littlewood,et al.  Re‐assessment of the monthly naturalized flow record for the River Thames at Kingston since 1883, and the implications for the relative severity of historical droughts , 1996 .

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

[14]  A. J. Jakeman,et al.  Identification of internal flow dynamics in two experimental catchments , 1997 .

[15]  Anthony J. Jakeman,et al.  Performance of conceptual rainfall‐runoff models in low‐yielding ephemeral catchments , 1997 .

[16]  A. Jakeman,et al.  Development of a simple, catchment-scale, rainfall-evapotranspiration-runoff model , 1998 .

[17]  Nilo Nascimento,et al.  GR3J: a daily watershed model with three free parameters , 1999 .

[18]  C. Perrin,et al.  Does a large number of parameters enhance model performance? Comparative assessment of common catchment model structures on 429 catchments , 2001 .

[19]  I. Sobola,et al.  Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates , 2001 .

[20]  Herschel Rabitz,et al.  Efficient Implementation of High Dimensional Model Representations , 2001 .

[21]  A. Saltelli,et al.  Making best use of model evaluations to compute sensitivity indices , 2002 .

[22]  V. Singh,et al.  Application and testing of the simple rainfall-runoff model SIMHYD , 2002 .

[23]  Neil McIntyre,et al.  Towards reduced uncertainty in conceptual rainfall‐runoff modelling: dynamic identifiability analysis , 2003 .

[24]  C. Perrin,et al.  Improvement of a parsimonious model for streamflow simulation , 2003 .

[25]  François Anctil,et al.  Impact of the length of observed records on the performance of ANN and of conceptual parsimonious rainfall-runoff forecasting models , 2004, Environ. Model. Softw..

[26]  Ken R. McNaught,et al.  Using Morris' randomized OAT design as a factor screening method for developing simulation metamodels , 2004, Proceedings of the 2004 Winter Simulation Conference, 2004..

[27]  Anthony J. Jakeman,et al.  A catchment moisture deficit module for the IHACRES rainfall-runoff model , 2004, Environ. Model. Softw..

[28]  E. Borgonovo Measuring Uncertainty Importance: Investigation and Comparison of Alternative Approaches , 2006, Risk analysis : an official publication of the Society for Risk Analysis.

[29]  Thibault Mathevet,et al.  A bounded version of the Nash-Sutcliffe criterion for better model assessment on large sets of basins , 2006 .

[30]  R. Srinivasan,et al.  A global sensitivity analysis tool for the parameters of multi-variable catchment models , 2006 .

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

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

[33]  Henrik Madsen,et al.  Generalized likelihood uncertainty estimation (GLUE) using adaptive Markov Chain Monte Carlo sampling , 2008 .

[34]  T. Mathevet,et al.  Confronting surface‐ and groundwater balances on the La Rochefoucauld‐Touvre karstic system (Charente, France) , 2008 .

[35]  P. Reed,et al.  Characterization of watershed model behavior across a hydroclimatic gradient , 2008 .

[36]  H. Gupta,et al.  Understanding uncertainty in distributed flash flood forecasting for semiarid regions , 2008 .

[37]  P. Reed,et al.  Sensitivity-guided reduction of parametric dimensionality for multi-objective calibration of watershed models , 2009 .

[38]  George Kuczera,et al.  Critical evaluation of parameter consistency and predictive uncertainty in hydrological modeling: A case study using Bayesian total error analysis , 2009 .

[39]  Yongqiang Zhang,et al.  Relative merits of different methods for runoff predictions in ungauged catchments , 2009 .

[40]  Anthony J. Jakeman,et al.  Assessing the impact of land use change on hydrology by ensemble modelling(LUCHEM) II: ensemble combinations and predictions , 2009 .

[41]  J. Norton Selection of Morris Trajectories for Initial Sensitivity Analysis , 2009 .

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

[43]  S. Charles,et al.  Comparison of runoff modelled using rainfall from different downscaling methods for historical and future climates , 2010 .

[44]  Jin Teng,et al.  Climate non-stationarity – Validity of calibrated rainfall–runoff models for use in climate change studies , 2010 .

[45]  A. Mangin,et al.  A multi-objective calibration framework for rainfall–discharge models applied to karst systems , 2011 .

[46]  Anthony J. Jakeman,et al.  An assessment of modelling capacity to identify the impacts of climate variability on catchment hydrology , 2011, Math. Comput. Simul..

[47]  Jing Yang,et al.  Convergence and uncertainty analyses in Monte-Carlo based sensitivity analysis , 2011, Environ. Model. Softw..

[48]  Willy Bauwens,et al.  Sobol' sensitivity analysis of a complex environmental model , 2011, Environ. Model. Softw..

[49]  Anthony J. Jakeman,et al.  An open software environment for hydrological model assessment and development , 2011, Environ. Model. Softw..

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

[51]  C. Perrin,et al.  A review of efficiency criteria suitable for evaluating low-flow simulations , 2012 .

[52]  S. Charles,et al.  Climate change and runoff in south-western Australia , 2012 .

[53]  F. Chiew,et al.  Rainfall–runoff modelling in northern Australia: A guide to modelling strategies in the tropics , 2012 .

[54]  F. Chiew,et al.  A robust methodology for conducting large-scale assessments of current and future water availability and use: A case study in Tasmania, Australia , 2012 .

[55]  C. Perrin,et al.  Neighbors: Nature’s own hydrological models , 2012 .

[56]  Paola Annoni,et al.  Estimation of global sensitivity indices for models with dependent variables , 2012, Comput. Phys. Commun..

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