A methodology for designing data colection networks in lakes and reservoirs is presented. The methodology is supported on numerical models, geostatistics and evolutionary strategies. The authors define four elementary steps for design, as follows: (i) modeling, to generate the data fields, (ii) sectoring, to make independent the regions inside the global domain, (iii) Kriging, to interpolate and get estimates from the available monitoring networks and (iv) optimization, to generate the set of locally optimal (accuracy vs costs) monitoring networks. The application case (Porce II reservoir in Colombia) is studied by splitting up the entire domain into five sub-domains (Dam, Transition, River, Stream A and Stream B). After splitting, outstanding features for each sub-domain strongly suggest further analysis. For instance, the Dam and River sub-domains have proven to be opposite (i.e. lentic vs lotic, respectively). As a result, the study case addresses the surface temperature of the Porce II reservoir and allows the recognition of structural patterns for surface temperatures.