An improved calibration technique to address high dimensionality and non-linearity in integrated groundwater and surface water models

Rafiei, Vahid and Nejadhashemi, A. Pouyan and Mushtaq, Shahbaz and Bailey, Ryan T. and An-Vo, Duc-Anh ORCID: https://orcid.org/0000-0001-7528-7139 (2022) An improved calibration technique to address high dimensionality and non-linearity in integrated groundwater and surface water models. Environmental Modelling and Software, 149:105312. pp. 1-15. ISSN 1364-8152


Abstract

The calibration of integrated groundwater-surface water models is often associated with high dimensionality and stagnation around local optimum solutions. Since these models are computationally demanding and also non-linear, finding their global optimum solution requires efficient optimization techniques. Here, we introduce the Multi-Memory Particle Swarm Optimization (MMPSO) algorithm. The swarm cognitive capacity is enhanced to minimize the number of local optimums and calibrate the model based on sub-objective functions. We used the MMPSO to simultaneously calibrate groundwater head, streamflow, baseflow, and nitrate loads in the SWAT-MODFLOW-RT3D model with 78 sensitive parameters. The results demonstrate that enhancing the cognitive capacity led to a marked improvement in discovering the global optimum solution. Furthermore, we evaluated the calibrated model's performance to quantify groundwater nitrate loads to streams and characterize the shallow surficial aquifer under intensive fertilizer land use. The results show the effectiveness of the MMPSO algorithm for calibrating complex hydrogeochemical models for large-scale applications.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Permanent restricted access to Published version in accordance with the copyright policy of the publisher.
Faculty/School / Institute/Centre: Current - Institute for Life Sciences and the Environment - Centre for Applied Climate Sciences (1 Aug 2018 -)
Faculty/School / Institute/Centre: Current - Institute for Life Sciences and the Environment (1 Aug 2018 -)
Date Deposited: 24 Jan 2022 05:16
Last Modified: 21 Sep 2022 00:15
Uncontrolled Keywords: groundwater; nitrate; SWAT-MODFLOW-RT3D; high dimensionality; particle swarm optimization; Great Barrier Reef
Fields of Research (2008): 04 Earth Sciences > 0406 Physical Geography and Environmental Geoscience > 040603 Hydrogeology
01 Mathematical Sciences > 0103 Numerical and Computational Mathematics > 010303 Optimisation
Fields of Research (2020): 30 AGRICULTURAL, VETERINARY AND FOOD SCIENCES > 3002 Agriculture, land and farm management > 300201 Agricultural hydrology
Socio-Economic Objectives (2008): D Environment > 96 Environment > 9605 Ecosystem Assessment and Management > 960503 Ecosystem Assessment and Management of Coastal and Estuarine Environments
Socio-Economic Objectives (2020): 18 ENVIRONMENTAL MANAGEMENT > 1803 Fresh, ground and surface water systems and management > 180399 Fresh, ground and surface water systems and management not elsewhere classified
Identification Number or DOI: https://doi.org/10.1016/j.envsoft.2022.105312
URI: http://eprints.usq.edu.au/id/eprint/46923

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