EDSSs are designed to provide environmental managers and decision-makers with the information and tools they need to make informed decisions about environmental issues.

Social media data is not typically used in EDSSs, as it is not considered to be a reliable source of environmental information.

Models are used in EDSSs to predict future environmental conditions, simulate the effects of different management actions, and visualize environmental data.

Disaster response is not typically considered to be an application of EDSSs, as EDSSs are designed to provide information and tools for long-term environmental management.

EDSSs face a number of challenges, including data integration and interoperability, model uncertainty and validation, and user acceptance and adoption.

EDSSs can provide a number of benefits, including improved decision-making, increased transparency and accountability, and enhanced public participation.

Desktop-based EDSSs are no longer as common as web-based, mobile, and cloud-based EDSSs.

Stakeholders play a crucial role in the development and implementation of EDSSs, providing input and feedback, helping to validate and calibrate the models, and using the EDSS to make informed decisions.

EDSSs are evolving rapidly, with key trends including increased use of artificial intelligence and machine learning, integration of real-time sensor data, and development of cloud-based EDSSs.

EDSSs face a number of challenges, including data quality and availability, model uncertainty, and user acceptance and adoption.

Decision support modules are not typically included in EDSSs, as the primary purpose of an EDSS is to provide information and tools to support decision-making, rather than to make decisions itself.

Uncertainty analysis plays a crucial role in EDSSs, helping to quantify the uncertainty associated with model predictions, helping decision-makers understand the limitations of the EDSS, and improving the accuracy of the EDSS models.

Machine learning models are not typically used in EDSSs, as they are not as well-suited for environmental modeling as deterministic, stochastic, and agent-based models.

User engagement is crucial in the development and implementation of EDSSs to ensure that the EDSS meets the needs of the users, to help validate and calibrate the EDSS models, and to promote user acceptance and adoption of the EDSS.

Water pricing is not typically considered to be an application of EDSSs in water resources management.