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RESEARCH PRODUCT

The value of perfect and imperfect information in lake monitoring and management.

Niina KotamäkiVilja KoskiHeikki HämäläinenJuha KarvanenKristian MeissnerSalme Kärkkäinen

subject

Environmental Engineering010504 meteorology & atmospheric sciencesOperations researchComputer sciencevesien tilapäätöksentekoympäristönhoitoContext (language use)Expected value of perfect informationmonitorointi010501 environmental sciencesperfect informationinformaatio01 natural sciencesjärvetdecision makingValue of informationenvironmental managementlakesEnvironmental Chemistry14. Life underwaterWaste Management and Disposaltilastolliset mallit0105 earth and related environmental sciencesCost–benefit analysisPerfect information15. Life on landimperfect informationPollutionvalue of informationVariable (computer science)ympäristövalvonta13. Climate actionValue (economics)Profitability index

description

Highlights • Knowledge on the value of monitoring can assist decision-making in lake management. • We calculate value of perfect information theoretically. • We estimate value of imperfect information with Monte Carlo type of approach. • Generally, monitoring is profitable to invest in if VOI exceeds the cost. • Additional monitoring is profitable even if the lake is in good condition a priori. Uncertainty in the information obtained through monitoring complicates decision making about aquatic ecosystems management actions. We suggest the value of information (VOI) to assess the profitability of paying for additional monitoring information, when taking into account the costs and benefits of monitoring and management actions, as well as associated uncertainty. Estimating the monetary value of the ecosystem needed for deriving VOI is challenging. Therefore, instead of considering a single value, we evaluate the sensitivity of VOI to varying monetary value. We also extend the VOI analysis to the more realistic context where additional information does not result in perfect, but rather in imperfect information on the true state of the environment. Therefore, we analytically derive the value of perfect information in the case of two alternative decisions and two states of uncertainty. Second, we describe a Monte Carlo type of approach to evaluate the value of imperfect information about a continuous classification variable. Third, we determine confidence intervals for the VOI with a percentile bootstrap method. Results for our case study on 144 Finnish lakes suggest that generally, the value of monitoring exceeds the cost. It is particularly profitable to monitor lakes that meet the quality standards a priori, to ascertain that expensive and unnecessary management can be avoided. The VOI analysis provides a novel tool for lake and other environmental managers to estimate the value of additional monitoring data for a particular, single case, e.g. a lake, when an additional benefit is attainable through remedial management actions.

10.1016/j.scitotenv.2020.138396https://pubmed.ncbi.nlm.nih.gov/32481219