Multi‐Objective Optimization of Managed Aquifer Recharge

Abstract

This study demonstrates the utilization of a multi-objective hybrid global/local optimization algorithm for solving managed aquifer recharge (MAR) design problems, in which the decision variables included spatial arrangement of water injection and abstraction wells and time-variant rates of pumping and injection. The objective of the optimization was to maximize the efficiency of the MAR scheme, which includes both quantitative and qualitative aspects. The case study used to demonstrate the capabilities of the proposed approach is based on a published report on designing a real MAR site with defined aquifer properties, chemical groundwater characteristics as well as quality and volumes of injected water. The demonstration problems include steady state and transient scenarios. The steady state scenario demonstrates optimization of spatial arrangement of multiple injection and recovery wells, whereas the transient scenario was developed with the purpose of finding optimal regimes of water injection and recovery at a single location. Both problems were defined as multi-objective problems. The scenarios were simulated by applying coupled numerical groundwater flow and solute transport models: MODFLOW-2005 and MT3D-USGS. The applied optimization method was a combination of global (the non-dominated sorting genetic algorithm [NSGA-2]) and local (the Nelder-Mead downhill simplex search algorithms). The analysis of the resulting Pareto optimal solutions led to the discovery of valuable patterns and dependencies between the decision variables, model properties, and problem objectives. Additionally, the performance of the traditional global and the hybrid optimization schemes were compared.

Water Distribution from Artificial Recharge via Infiltration Basin under Constant Head Conditions

“…The relevant scientific research and engineering practices about this technology can be found across all continents except for Antarctica [16][17][18][19][20]. Infiltration basin, riverbank filtration and recharge well are the dominant managed aquifer recharge technologies at global scale [21][22][23]. This research deals with the impacts of vadose zone factors on artificial recharge via the infiltration basin using modeling exercises.…”

Evaluation of the Offsets of Artificial Recharge on the Extra Run-Off Induced by Urbanization and Extreme Storms Based on an Enhanced Semi-Distributed Hydrologic Model with an Infiltration Basin Module

“…Among the various methods of managed aquifer recharge, the recharge well, riverbank filtration, and the infiltration basin are the most common [11]. Although modeling studies have predominantly focused on recharge well technology [11], the infiltration basin, because of its lower costs [12,13], is the most prevalent artificial recharge technique globally [11,14,15].…”

Optimizing Managed Aquifer Recharge Locations in California's Central Valley Using an Evolutionary Multi‐Objective Genetic Algorithm Coupled With a Hydrological Simulation Model

“…The few studies that have used SO frameworks for MAR have solely focused on aquifer storage and recovery (Al‐Maktoumi et al., 2020; Forghani & Peralta, 2018; Hernandez et al., 2014; Marchi et al., 2016). For example, Fatkhutdinov & Stefan (2019) used a multi‐objective SO to identify optimal well locations and recharge rates in a hypothetical test case. Ebrahim et al.…”

“…The few studies that have used SO frameworks for MAR have solely focused on aquifer storage and recovery (Al-Maktoumi et al, 2020;Forghani & Peralta, 2018;Hernandez et al, 2014;Marchi et al, 2016). For example, Fatkhutdinov & Stefan (2019) used a multi-objective SO to identify optimal well locations and recharge rates in a hypothetical test case. Ebrahim et al (2016) developed a MODFLOW groundwater model for a catchment in Oman and combined it with an optimization algorithm to increase aquifer recharge by optimizing extraction and recovery rates subject to water level constraints.…”