Assessment of Conceptual Model Uncertainty in Groundwater Modeling (Case Study: Najafabad Aquifer of Gavkhouni Basin)

Document Type : Research Article


1 Department of Water Engineering, College of Aburaihan, University of Tehran, Iran.

2 Department o Water Resources, Water Research Institute (WRI), Tehran, Iran

3 Department of Water Engineering, College of Aburaihan, University of Tehran, Iran


Groundwater‌ modeling is the foundation for quantitative analysis of groundwater resources, the successful assessment of which depends on its stable and reliable simulation. Because groundwater models are‌ an approximation‌ of reality, it is impossible to quite determine a system's properties through modeling or to mathematically describe the complex properties of a hydrogeological system. Therefore, inherently, all models have a degree of uncertainty, and as a result, the existence of uncertainty in the groundwater model sets managerial decisions in relation to it at risk of failure. The purpose of this study is to explain a method for quantitative recognition of groundwater uncertainty and how model uncertainty can be used as a tool to better realize the modeled system and provide the information needed to help make more informed decisions. A quantitative investigation of groundwater modeling was performed in Najafabad located in Isfahan province. Three conceptual models were‌ created for Najafabad aquifer by different geological settings, recharging, and model boundaries. Conceptual models were developed in steady-state for 2018-2019 and calibrated using observational data. All models were validated using available water level data of 2018-2019. The models reliably simulated the water level in the aquifer. To select the best model, the model selection criteria (AIC, AICC, BIC, and KIC) was used. The results showed that model number 1 with the highest weight and the least uncertainty was introduced as the best model.


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Volume 8, Issue 4
April 2022
Pages 1081-1097
  • Receive Date: 10 September 2021
  • Revise Date: 31 January 2022
  • Accept Date: 31 January 2022
  • First Publish Date: 20 February 2022