This paper discusses the problem of finding an optimal satellite constellation for the SOLVE (Satellites Observing Lakes and Vegetation Environments) Mission. A key requirement of this mission is a temporal resolution of several observations per day. A semi-analytical approach is proposed. After some analytical design steps which reduces the problem space to circular sun synchronous orbits, a genetic algorithm is used for finding all remaining orbital parameters. The result is an easy to use tool which allows to study cost impact from given science requirements enabling a good understanding of the relation between temporal, spatial resolution and cost.