Research Article Discovery of hydrometeorological patterns

Abstract:Hydrometeorological patterns can be dened as meaningful and nontrivial associations between hydrological and meteorological parameters over a region. Discovering hydrometeorological patterns is important for many applica-tions, including forecasting hydrometeorological hazards ( oods and droughts), predicting the hydrological responses of ungauged basins, and lling in missing hydrological or meteorological records. However, discovering these patterns is challenging due to the special characteristics of hydrological and meteorological data, and is computationally complex due to the archival history of the datasets. Moreover, dening monotonic interest measures to quantify these patterns is dicult. In this study, we propose a new monotonic interest measure, called the hydrometeorological prevalence index, and a novel algorithm for mining hydrometeorological patterns (HMP-Miner) out of large hydrological and meteorolog-ical datasets. Experimental evaluations using real datasets show that our proposed algorithm outperforms the nave alternative in discovering hydrometeorological patterns eciently