In the ecological risk assessment, we have to make decisions based on many kinds of imperfect knowledge. For example, when we set limitations for point sources, there may be an uncertainty on relationship between a chemical concentration in effluent and that in environment, and hence it may be difficult to predict an environmental concentration using the information about effluent. Another example is that the environmental quality criteria are determined to protect the ecosystems, but the ecosystems are much more complicated and the criteria may not protect the ecosystems effectively. We apply information-gap decision theory to set effluent limitations for point sources based on scientific underpinnings rather than based on groundless predictions even under severe uncertainty. Information-gap decision theory derives the decision that is most robust to uncertainty, by guaranteeing an acceptable outcome under the largest degree of uncertainty without requiring information about the extent of parameter uncertainty at the outset. Our framework enables us to derive decisions to deal with severe uncertainty in ecological risk management of chemicals.