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Complementary.sy.tem-theoretic modelling approach for enhancing hy.rological forecasting

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Journal of Southeast University.English Edition) 2006年第2期22卷 273-280页

作者： martins y.otache 李致家河海大学水文水资源与水利工程科学国家重点实验室南京210098

Hy.rologic models generally.represent the most dominant processes since they.are mere simplifications of phy.ical reality.and thus are subject to many.significant uncertainties. As such, a coupling strategy.is proposed. To this end, the coupling of the artificial neural network （ANN） with the Xin＇anjiang conceptual model with a view to enhance the quality.of its flow forecast is presented. The approach uses the latest observations and residuals in runoff/discharge forecasts from the Xin＇anjiang model. The two complementary.models （Xin＇anjiang ＆ ANN） are used in such a way.that residuals of the Xin＇anjiang model are forecasted by.a neural network model so that flow forecasts can be improved as new observations come in. For the complementary.neural network, the input data were presented in a patterned format to conform to the calibration regime of the Xin＇anjiang conceptual model, using differing variants of the neural network scheme. The results show that there is a substantial improvement in the accuracy.of the forecasts when the complementary.model was operated on top of the Xin＇anjiang conceptual model as compared with the results of the Xin＇anjiang model alone.

关键词： hy.rological forecasting complementary.model residual Xin'anjiang conceptual model artificial neural network

Analy.is of stochastic characteristics of the Benue River flow process

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Chinese Journal of Oceanology.and Limnology 2008年第2期26卷 142-151页

作者： martins y. otache mohammad bakir 李致家 State Key.Laboratory.of Hy.rology.Water Resources ＆ Hy.raulic Engineering Hohai University Nanjing 210098 China

Stochastic characteristics of the Benue River streamflow process are examined under conditions of data austerity. The streamflow process is investigated for trend, non-stationarity.and seasonality.for a time period of 26 y.ars. Results of trend analy.es with Mann-Kendall test show that there is no trend in the annual mean discharges. Monthly.flow series examined with seasonal Kendall test indicate the presence of positive change in the trend for some months, especially.the months of August, January. and February. For the stationarity.test, daily.and monthly.flow series appear to be stationary.whereas at 1%, 5%, and 10% significant levels, the stationarity.alternative hy.othesis is rejected for the annual flow series. Though monthly.flow appears to be stationary.going by.this test, because of high seasonality. it could be said to exhibit periodic stationarity.based on the seasonality.analy.is. The following conclusions are drawn：（1） There is seasonality.in both the mean and variance with unimodal distribution. （2） Day. with high mean also have high variance. （3） Skewness coefficients for the months within the dry.season period are greater than those of the wet season period, and seasonal autocorrelations for streamflow during dry.season are generally.larger than those of the wet season. Precisely. they.are significantly.different for most of the months. （4） The autocorrelation functions estimated ＂over time＂ are greater in the absolute value for data that have not been deseasonalised but were initially.normalised by.logarithmic transformation only. while autocorrelation functions for i = 1, 2 365 estimated ＂over realisations＂ have their coefficients significantly.different from other coefficients.

关键词： trend stationarity seasonality over time over realisation stochastic skewness

Effects of optimization characteristics and variable antecedent catchment's state on parameter calibration of the Xin'anjiang model

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Journal of Southeast University.English Edition) 2003年第4期19卷 398-404页

作者： martins y.otache 李致家河海大学水资源环境学院南京210098

本文对流域状态和最优化特性是如何影响模型功能方面进行了研究.在假设流域诸多初始条件下,使用SCE-UA优化算法通过日模型率定新安江模型.结果发现流域的初始条件和最优化特性对待优化的参数有非常大的影响,并且使模型过程参数的响应程... 详细信息

本文对流域状态和最优化特性是如何影响模型功能方面进行了研究.在假设流域诸多初始条件下,使用SCE-UA优化算法通过日模型率定新安江模型.结果发现流域的初始条件和最优化特性对待优化的参数有非常大的影响,并且使模型过程参数的响应程度变小.研究结果表明变化的初始条件对总产流的影响并不是太大.

关键词：水文模型定量估计水资源管理 SCE-UA优化算法新安江