Valuing water quality change using a coupled economic-hydrological model

Liu, Hongxing; Gopalakrishnan, Sathya; Browning, D.W.; Sivandran, G.

doi:10.1016/j.ecolecon.2019.03.006

Cited by 19 publications

(4 citation statements)

References 31 publications

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“…The SWAT output variables have successfully been used to apply different economic valuation methods depending on the ES valued, as market prices, avoided costs, replacement costs, mitigation or restoration cost, or even less common valuation methods such as choice experiments or hedonic pricing (Pascual et al, 2010). This demonstrates the versatility with which the results of this model can be used for the economic valuation of ES (Liu et al, 2019). Finally, this review has also collected a set of cases of economically based evaluations of different types of management scenarios that have been based on the use of SWAT.…”

Section: Discussionmentioning

confidence: 96%

“…To complement the calculation of the WQIs, regressions were used to establish the relationships between SWAT‐based N, P, sediment concentrations, and the variables dissolved oxygen (DO), biological oxygen demand (BOD), and fecal coliforms. Also in the United States, in this case in Ohio, in a medium‐sized agricultural watershed, Liu et al (2019) used modeled Secchi disk depth results to estimate the economic value of esthetic appreciation ES of freshwater landscapes.…”

Section: Characterization Of the Selected Studiesmentioning

confidence: 99%

“…One of these is Choi and Ready (2021), who applied the SWAT output water quality results to estimate the WQI values obtained by applying different scenarios to conduct a choice experiment survey. The other relevant valuation of cultural ES was conducted by Liu et al (2019), who used Secchi disk depths obtained from SWAT to conduct a hedonic pricing method and estimate the economic impact in terms of esthetic appreciation of the improvement of water clarity.…”

Section: Characterization Of the Selected Studiesmentioning

confidence: 99%

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Using the Soil and Water Assessment Tool (SWAT) to quantify the economic value of ecosystem services

Garcia

2023

River

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Modeling tools simulate the functioning of ecosystems and their interactions with human activities, helping decision makers understand how interventions impact ecosystems and evaluate management strategies. This leads to informed decisions that balance human development and environmental protection. Among these models, Soil and Water Assessment Tool (SWAT) stands out for its ability to simulate multiple biophysical processes that can be linked to the provision of ecosystem services (ES). Although SWAT has been successfully applied for the evaluation of ES, the development of complementary approaches that translate the results of SWAT into monetary terms is still in its early stages. To narrow this gap, this review article aims to provide a comprehensive assessment of the literature on the relationship between SWAT model results and economic analysis. Specifically, the review summarizes the research conducted on the use of SWAT model results to estimate economic values, including the different methodologies used and the types of economic values estimated. The review will also discuss the limitations and challenges of these approaches, provide a critical evaluation of the strengths and weaknesses of the research in this area, and provide recommendations to strengthen SWAT application for the economic evaluation of management strategies.

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Section: Discussionmentioning

confidence: 96%

Section: Characterization Of the Selected Studiesmentioning

confidence: 99%

Section: Characterization Of the Selected Studiesmentioning

confidence: 99%

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Using the Soil and Water Assessment Tool (SWAT) to quantify the economic value of ecosystem services

Garcia

2023

River

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“…The value of water quality can be partially recovered from housing transactions where improvements in water quality are capitalized in higher home values (Poor et al, 2007; Walsh et al, 2017; Wolf & Klaiber, 2017). Secchi depth is a commonly used water quality measure (Gibbs et al, 2002; Liu et al, 2019; Walsh et al, 2011) because of the scale and accessibility of in situ monitoring data across the United States (Wolf & Kemp, 2021), with property values increasing between $498 (Walsh et al, 2011) and $11,330 (Moore et al, 2020) for a one‐foot improvement in water transparency. This effect is spatially limited to homes near a waterbody (Walsh et al, 2011; Walsh et al, 2017; Wolf & Klaiber, 2017) and will vary with ambient water conditions, with greater gains from water quality improvement observed at lower ambient conditions (Boyle et al, 1999; Smeltzer & Heiskary, 1990; Zhang et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Staying afloat: The effect of algae contamination on Lake Erie housing prices

Wolf

Gopalakrishnan

Klaiber

2022

American J Agri Economics

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Lake Erie has experienced unprecedented harmful algal blooms since the early 2000s, prompting the 2012 Great Lakes Water Quality Agreement between the United States and Canada, which aims to reduce lakewide phosphorous loadings by 40%. Little is known about the economic benefits from this agreement, especially to near lake homeowners. We provide key information on the benefits of harmful algal bloom cleanup by linking housing transactions in 2003 to 2015 from seven Ohio counties bordering Lake Erie with measures of water quality using remote-sensing images. We further control for endogenous algae production using instrumental variables derived from hydrological processes that link Maumee River runoff to nutrient concentrations in Lake Erie. Using a semiparametric approach, we find the impact of harmful algal blooms on housing prices is spatially limited to properties within 1.2 km of Lake Erie. For the average near lake homeowner, a 1 μg/L increase in algae concentrations is expected to decrease property values by 1.7% ($2205). In aggregate, fulfilling the Great Lakes Water Quality Agreement will provide a yearly benefit of up to $42.9 million, fully covering the current annual expenditure on water quality improvement.

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