There are inherent open problems arising when developing and running Intelligent Environmental
Decision Support Systems (IEDSS). During daily operation of IEDSS several open challenge problems
appear. The uncertainty of data being processed is intrinsic to the environmental system, which is being
monitored by several on-line sensors and off-line data. Thus, anomalous data values at data gathering level
or even uncertain reasoning process at later levels such as in diagnosis or decision support or planning can
lead the environmental process to unsafe critical operation states. At diagnosis level or even at decision
support level or planning level, spatial reasoning or temporal reasoning or both aspects can influence the
reasoning processes undertaken by the IEDSS. Most of Environmental systems must take into account the
spatial relationships between the environmental goal area and the nearby environmental areas and the
temporal relationships between the current state and the past states of the environmental system to state
accurate and reliable assertions to be used within the diagnosis process or decision support process or
planning process. Finally, a related issue is a crucial point: are really reliable and safe the decisions proposed
by the IEDSS? Are we sure about the goodness and performance of proposed solutions? How can we ensure
a correct evaluation of the IEDSS? Main goal of this paper is to analyse these four issues, review some
possible approaches and techniques to cope with them, and study new trends for future research within the
IEDSS field.
