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Empirical Hydrologic Predictions for Southwestern Poland and Their Relation to Enso Teleconnections

DOI: 10.2478/v10018-010-0002-y

Keywords: El Ni o, hydrology, time series, forecasting, Poland

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Abstract:

Recent investigations confirm meaningful but weak teleconnections between the El Ni o/Southern Oscillation (ENSO) and hydrology in some European regions. In particular, this finding holds for Polish riverflows in winter and early spring as inferred from integrating numerous geodetic, geophysical and hydrologic time series. The purpose of this study is to examine whether such remote teleconnections may have an influence on hydrologic forecasting. The daily discharge time series from southwestern (SW) Poland spanning the time interval from 1971 to 2006 are examined. A few winter and spring peak flows are considered and the issue of their predictability using empirical forecasting is addressed. Following satisfactory prediction performance reported elsewhere, the multivariate autoregressive method is used and its modification based on the finite impulse response filtering is proposed. The initial phases of peak flows are rather acceptably forecasted but the accuracy of predictions in the vicinity of local maxima of the hydrographs is poorer. It has been hypothesized that ENSO signal slightly influences the predictability of winter and early spring floods in SW Poland. The predictions of flood wave maxima are the most accurate for floods preceded by normal states, less accurate for peak flows after La Ni o episodes and highly inaccurate for peak flows preceded by El Ni o events. Such a finding can be interpreted in terms of intermittency. Before peak flows preceded by El Ni o there are temporarily persistent low flows followed by a consecutive melting leading to a considerable intermittency and hence to difficulties in forecasting. Before peak flows preceded by La Ni o episodes there exist ENSO-related positive temperature and precipitation anomalies in SW Poland causing lower, but still considerable, intermittency and thus better, but not entirely correct, predictability of hydrologic time series.

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