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The study presents a novel computational intelligence algorithm designed to optimise energy consumption in an environmental monitoring process: specifically, water level measurements in flooded areas. This algorithm aims to obtain a trade-off between accuracy and power consumption. The implementation constitutes a data aggregation and fusion in itself. A harsh environment can make the direct measurement of flood levels a difficult task. This study proposes a flood level estimation, inferred through the measurement of other common environmental variables. The benefit of this algorithm is tested both with simulations and real experiments conducted in Doñana, a national park in southern Spain where flood level measurements have traditionally been done manually.