Comparison of sensitivity analysis techniques: A case study with the rice model WARM-Reference-Cited by-同舟云学术

Comparison of sensitivity analysis techniques: A case study with the rice model WARM

Published:2010-08 Issue:16 Volume:221 Page:1897-1906
ISSN:0304-3800
Container-title:Ecological Modelling
language:en
Short-container-title:Ecological Modelling

Author:

Confalonieri R.,Bellocchi G.,Bregaglio S.,Donatelli M.,Acutis M.

Publisher

Elsevier BV

Subject

Ecological Modeling

Reference34 articles.

1. Plackett–Burman techniques for sensitivity analysis of many-parametered models;Beres;Ecol. Model.,2001

2. Estimation of parameters describing morpho-physiological features of Mediterranean rice group for crop modelling purposes;Boschetti;Ital. J. Agrometeorol.,2006

3. An effective screening design for sensitivity analysis of large models;Campolongo;Environ. Model. Softw.,2007

4. Monte Carlo based sensitivity analysis of two crop simulators and considerations on model balance;Confalonieri;Eur. J. Agron.,2010

5. Exploratory sensitivity analysis of CropSyst, WARM and WOFOST: a case study with rice biomass simulations;Confalonieri;Ital. J. Agrometeorol.,2006

Cited by 164 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An agent-based modeling method to determine the number of flash flood warnings for improving the warning response levels;Journal of Hydrology;2024-08

2. Determining input factor importance in a compartmental model using screening methods;Communications in Statistics - Simulation and Computation;2024-06-07

3. How global sensitive is the AquaCrop model to input parameters? A case study of silage maize yield on a regional scale;Frontiers in Agronomy;2024-04-16

4. Stepwise model parametrisation using satellite imagery and hemispherical photography: Tuning AquaCrop sensitive parameters for improved winter wheat yield predictions in semi-arid regions;Field Crops Research;2024-04

5. Greylag Goose Optimization: Nature-inspired optimization algorithm;Expert Systems with Applications;2024-03