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Abstract The Mississippi Embayment aquifer is one of the largest alluvial groundwater aquifers in the United States. It is being excessively used, located along the lower Mississippi River covering approximately 202,019 km2(78,000 square miles). Annual average groundwater depletion in the aquifer has been estimated at 5.18 billion cubic meters (Gm3) (4.2 million acre‐feet) in 1981–2000. However, since 2000, annual groundwater depletion has increased abruptly to 8 Gm3(2001–2008). In recent years, multi‐state efforts have been initiated to improve the Mississippi Embayment aquifer sustainability. One management strategy of interest for preserving groundwater resources is managed aquifer recharge (MAR). In this study, we evaluate the impact of different MAR scenarios on land and water use decisions and the overall groundwater system using an economic model able to assess profitability of crop and land use decisions coupled to the Mississippi Embayment Regional Aquifer Study (MERAS) hydrogeologic model. We run the coupled model for 60 years by considering the hydrologic conditions from the MERAS model for the years 2002–2007 and repeating them 10 times. We find MAR is not economically attractive when the water cost is greater than $0.05/m3. Groundwater storage is unlikely to improve when relying solely on MAR as groundwater management strategy but rather should be implemented jointly with other groundwater conservation policies.
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Optimizing Managed Aquifer Recharge Locations in California's Central Valley Using an Evolutionary Multi‐Objective Genetic Algorithm Coupled With a Hydrological Simulation Model
Abstract Managed aquifer recharge (MAR) can provide long‐term storage of excess surface water for later use. While decades of research have focused on the physical processes of MAR and identifying suitable MAR locations, very little research has been done on how to consider competing factors and tradeoffs in siting MAR facilities. This study proposes the use of a simulation‐optimization (SO) framework to map out a cost‐effectiveness frontier for MAR by combining an evolutionary algorithm with two objective functions that seek to maximize groundwater storage gains while minimizing MAR cost. We present the theoretical framework along with a real‐world application to California's Central Valley. The result of the SO framework is a Pareto front that allows identifying suitable MAR locations for different levels of groundwater storage gain and associated MAR project costs, so stakeholders can evaluate different choices based on cost, benefits, and tradeoffs of MAR sites. Application of the SO framework to the Central Valley shows groundwater can be recharged from high‐magnitude (95th percentile) flows at a marginal cost of $57 to $110 million per km3. If the 10 percent largest flows are recharged the total groundwater storage gain would double and the marginal costs would drop to between $30 and $50 million per km3. If recharge water is sourced from outside local basins (e.g., the Sacramento‐San Joaquin Delta), groundwater storage gain is approximately 25%–80% greater than can be achieved by recharging local flows, but the total cost is about 10%–15% higher because of additional lift cost.
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- Award ID(s):
- 1716130
- PAR ID:
- 10415856
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Water Resources Research
- Volume:
- 59
- Issue:
- 5
- ISSN:
- 0043-1397
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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