Efficient Watershed Modeling Using A Multi-site
Weather Generator For Meteorological Data
Author(s)
M. Khalili, R. Leconte & F. Brissette
Abstract
The multi-site generation of precipitation data is developed using a Richardson
(1981) WGEN-type weather generator. This approach is based on spatial
autocorrelation to analyze patterns in space and investigate the dependence of
weather data at multiple locations. Reproducing the dependence between
meteorological data at several stations should make the hydrological model
results more realistic. The Chute du diable watershed and surrounding area
located in the province of Quebec, Canada was used to test the proposed
approach. Daily spatial autocorrelations between precipitation occurrences and
amounts were successfully reproduced as well as total monthly precipitation and
monthly numbers of rainy days. A hydrological model has been used to quantify
the natural inflow process. As envisaged, the multi-site generation of weather
data produced more practical natural inflow hydrographs, compared to those
obtained using a uni-site weather generator.
Keywords: weather generator, precipitation, Markov chain, spatial autocorrelation, hydrological modeling.
1 Introduction
Weather generators can be used to generate climatic data (precipitation,
temperature, solar radiation...) with the same statistical properties as the
observed ones. Most weather generators operate for a single site, e.g. [15], [2]
and [7]. Therefore, they ignore the regional coherence and the spatial
dependence between the stations, which entail many problems in the
hydrological modeling results, obtained using the simulated time series of
meteorological data.
Keywords
weather generator, precipitation, Markov chain, spatial autocorrelation, hydrological modeling.
Related Book
Other papers in this volume
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