Filling gaps in daily rainfall data: a statistical approach
Daily rainfall data are one of the basic inputs in hydrological and ecological modeling and in assessing water quality. However, most data series are too short to perform reliable and meaningful analyses and possess significant number of missing records. The study focuses on developing a methodology to fill the gaps in daily rainfall series considering data of twenty rainfall stations from Brahmani Basin, Rachi, India. A probabilistic approach is adopted to generate data for filling on missing...[Show more]
|Collections||ANU Research Publications|
|Source:||MODSIM2013, 20th International Congress on Modelling and Simulation|
|Access Rights:||Open Access|
|01_Hasan_Filling_gaps_in_daily_rainfall_2013.pdf||454.39 kB||Adobe PDF|
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