  The Alqueva Multi-Purpose Project (EFMA) is a massive abduction and storage
infrastructure system in the Alentejo, which has a water quality monitoring
network with almost thousands of water quality stations distributed across
three subsystems: Alqueva, Pedrog\~ao, and Ardila. Identification of pollution
sources in complex infrastructure systems, such as the EFMA, requires
recognition of water flow direction and delimitation of areas being drained to
specific sampling points. The transfer channels in the EFMA infrastructure
artificially connect several water bodies that do not share drainage basins,
which further complicates the interpretation of water quality data because the
water does not flow exclusively downstream and is not restricted to specific
basins.
  The existing user-friendly GIS tools do not facilitate the exploration and
visualisation of water quality data in spatial-temporal dimensions, such as
defining temporal relationships between monitoring campaigns, nor do they allow
the establishment of topological and hydrological relationships between
different sampling points.
  This thesis work proposes a framework capable of aggregating many types of
information in a GIS environment, visualising large water quality-related
datasets and, a graph data model to integrate and relate water quality between
monitoring stations and land use. The graph model allows to exploit the
relationship between water quality in a watercourse and reservoirs associated
with infrastructures.
  The graph data model and the developed framework demonstrated encouraging
results and has proven to be preferred when compared to relational databases.
