Stage-monitoring network optimization using GIS
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The South Florida Water Management District (SFWMD) has a large and expanding stage-monitoring network in need of optimization. The basic optimization problem is to keep in operation the least number of stage-monitoring stations (sites where the surface water elevation is constantly measured) in the best possible locations without having a serious loss of information. Two different methodologies, one for lakes, where water levels tend to be smooth and planar, and one for streams, where water levels can have significant changes produced by the varying hydraulic properties along the courses, are needed for optimizing the networks. Several optimization methods were tested including simulated annealing, genetic algorithm and tabu search. Tabu search was used as the definitive optimization method for both lakes and streams. Both methodologies also need a spatial interpolation method because both need to estimate water elevations in specific points. The methodology for lakes uses inverse square viii distance weighting as the spatial interpolation method. The methodology for streams requires the use of HEC-RAS software developed by the US Army Corps of Engineers as the spatial interpolation method. The error of estimation of surface water elevations is performed via the root mean square error in both methodologies. Several cases located in lakes and streams in the Lake Kissimmee River Basin of the SFWMD are used to develop and test the methodologies. Additionally to the definitive methodology for stations in streams, two different but closely related earlier methodologies are developed, one for steady flow and the other for unsteady flow. Daily data are considered in the methodologies for stations in lakes and stations in streams with steady flow. In the case of stations with unsteady flow, it was determined that the data resolution should be at least one hour and flow and stage values should be instantaneous. Good results are obtained for the cases of stations in lakes and stations in streams with steady flow. For the case of stations in streams with unsteady flow, results are inconclusive. In addition to the optimization methodologies, a set of stage-network optimization guidelines are proposed.