Analysis and Research on Basic Model of Hydrogeological Parameters Based on Sensitivity Analysis
Download as PDF
Author(s)
Xiaodong Zhang, Xiaobo Yang, Kangnan Cheng, Xin Yue, Xixi Liu
Corresponding Author
Xiaodong Zhang
Abstract
This paper discusses the sensitivity and uncertainty analysis methods of multi-parameters related to model parameters and model simulation performance. Multi-parameter sensitivity analysis based on Monte Carlo simulation can evaluate the relative importance of multiple parameters in the model. Sensitivity uncertainty analysis can quantitatively evaluate model performance. The case study shows that the number of optimized parameters can be reduced by the sensitivity analysis method. Moreover, before the parameter optimization of the model, the simulation accuracy of the model can be determined based on the sensitivity analysis. For example, the same model can obtain higher simulation accuracy in Chaohe River than in river. The difference of this same model in different watersheds is due to the imperfection of the model structure on the one hand, and the data errors used for modeling on the other hand. The parameter optimization results show that the parameter sensitivity and the overall performance evaluation method of the model are reasonable.
Keywords
Sensitivity, Hydrogeological parameters, Model analysis
Acknowledgments
None
References
[1] Borgonovo, Emanuele, et al. “Making the Most out of a Hydrological Model Data Set: Sensitivity Analyses to Open the Model Black‐box.” Water Resources Research,vol.53, no.9, pp.7933-7950,2017.
[2] Mockler, Eva M., Fiachra E. O’Loughlin, and Michael Bruen. “Understanding hydrological flow paths in conceptual catchment models using uncertainty and sensitivity analysis.” Computers & Geosciences,vol. 9, no.1, pp.66-77,2016.
[3] Emery, Charlotte M., et al. “Temporal Variance-based Sensitivity Analysis of the River-routing Component of the Large-scale Hydrological Model ISBA–TRIP: Application on the Amazon Basin.” Journal of Hydrometeorology,vol. 17,no.12, pp.3007-3027,2016.
[4] Khalid, K., et al. “Application on One-at-a-time Ssensitivity Analysis of Semi-distributed Hydrological Model in Tropical Watershed.” International Journal of Engineering and Technology, vol.8, no.2, pp.132-136,2016.
[5] Welde, Kidane, and Bogale Gebremariam. “Effect of Land Use Land Cover Dynamics on Hydrological Response of Watershed: Case study of Tekeze Dam Watershed, Northern Ethiopia.” International Soil and Water Conservation Research,vol. 5,no.1, pp.1-16,2017.
[6] Zhang, Junlong, et al. “Assessment of Parameter Uncertainty in Hydrological Model Using a Markov-Chain-Monte-Carlo-based Multilevel-Factorial-Analysis Method.” Journal of Hydrology, vol.53,no.8, pp.471-486,2016.
[7] Del Giudice, Giuseppe, and Roberta Padulano. “Sensitivity Analysis and Calibration of a Rainfall-runoff Model with the Combined use of EPA-SWMM and Genetic Algorithm.” Acta Geophysica, vol.64, no.5, pp.1755-1778,2016.
[8] Unice, K. M., et al. “Characterizing Export of Land-based Microplastics to the Estuary-Part II: Sensitivity Analysis of an Integrated Geospatial Microplastic Transport Modeling Assessment of Tire and Road Wear Particles.” Science of the Total Environment,vol. 6, no.4, pp.1650-1659,2019.
[9] Mahrez, Boulabeiz, et al. “GIS-based GALDIT Method for Vulnerability Assessment to Seawater Intrusion of the Quaternary Coastal Collo Aquifer (NE-Algeria).” Arabian Journal of Geosciences, vol.11, no.4, pp.71-72,2018.
[10] Maina, Fadji Zaouna, and Alberto Guadagnini. “Uncertainty Quantification and Global Sensitivity Analysis of Subsurface Flow Parameters to Gravimetric Variations during Pumping Tests in Unconfined Aquifers.” Water Resources Research,vol. 54, no.1,pp. 501-518,2018.