Enhancement of lag time query on hydrologic data using clipping technique and logic-based correlation

Lag time is a fundamental property on hydrology. However, lag time query may take large amount of space and time. In this paper, we explore clipping, a simple discretization technique, to resolve space and time complexity and enhance the accuracy of lag time query on clustering. The result shows that the hydrologic data are satisfied with clipping and hence they could be classified using clipping technique and logic-based correlation with less space and time.