Decision making in environmental management is faced with uncertainties associated with related environmental variables and processes. Decision makers are inclined to use resources to acquire better information in one or more uncertain variable(s). Typically, with limited resources available, characterizing the feasibility of such investment is desirable yet complicated. In the context of reducing inherent uncertainty, decision makers need to tackle two difficult questions, first, the optimal selection of variable(s) and second, the optimal level of information collection which produces maximum gain in benefits. We develop a new framework to assess the socioeconomic value of potential decisions of collecting additional information for given variable(s) to reduce inherent uncertainty. The suggested framework employs advanced social welfare concepts to facilitate eliciting the social acceptability of decisions to collect better information. The framework produces estimates of changes in utility levels and willingness to pay for target population using the benefit transfer method. The practicality of the framework is established using the following common problems in the field of water resources: 1) the uncertainty in exposure to health risk due to drinking a groundwater source contaminated with a carcinogen, 2) the uncertainty in non point source pollution loadings due to unknown hydrologic processes variability, and 3) the equity level in allocating mitigation responsibilities among polluters. For the three applications, the social acceptability of potential decisions is expressed in monetary terms which represent an extension on typical cost benefit analysis by including the socioeconomic value of a decision. The specific contribution of this research is a theoretical framework for a detailed preliminary analysis to transform and represent the given problem in useable terms for the social welfare analysis. The practical framework is attractive because it avoids the need to employ prohibitively expensive survey-based contingent valuation methods. Instead, the framework utilizes benefit transfer method, which imposes a theoretical behavioral structure on population characteristics such as age and income and to produce empirical estimates for a new problem setting.