Mathematical programming for the support of strategic decisions in river water management
The first aim of this PhD-project is to develop and evaluate decision support methods for optimal allocation of water given that supply and demand are distributed in space and variable in time. The hypothesis is that Linear Programming (LI) or Mixed Integer Linear Programming (MILP) approaches are suitable for this purpose.
The second aim is related to the need to acquire data on weather, water levels in reservoirs and discharges of rivers in a georeferenced and real time way. The hypothesis is that the Sensor Web Enablement (SWE) standard, developed by the Open Geospatial Consortium is an appropriate basis for setting up and managing spatially distributed real-time sensor networks.
The considered suppliers of water are rivers and dammed reservoirs while the demand is for domestic, agricultural (irrigation) and industrial use, hydro power generation and wetland preservation. The study area is the Pacalori land development project area in the Los Rios Province in Ecuador.