基于多重优化灰色模型的三峡库区香溪河支流回水区水华变化趋势预测研究

三峡水库蓄水后,支流香溪河夏季水体富营养化严重,水华现象暴发频繁,水质污染严重.为预知香溪河库湾水华暴发程度与分布区域,以叶绿素-a为指标,引入灰色伯努利模型,并运用参数优化、含参马尔科夫误差修正、子序列独立优化等多重优化理论对模型进行改进,验证模型的优化效果.同时,利用该优化模型对2015年夏季香溪河近10个点位的叶绿素-a平均浓度变化趋势进行短期预测,结果表明,预测值与实际值相差较小,该模型能够基本反映香溪河近几年的水华变化趋势,目前香溪河库湾XX06~XX08和XX02点位区域分别为水华暴发高危区和局部次高危区,叶绿素-a浓度远高于水华阈值,有较高的水华暴发风险.与传统灰色预测相比,该预测方法的精确度和对波动序列的适应性更好.

Prediction of algal bloom variation in backwater areas of tributaries in Three-Gorges Reservoir based on multiple optimized grey model

The Xiangxi River branch of the Three-Gorges Reservoir suffers from severe eutrophication with the frequent occurrence of algae blooms in summer. To predict the spatial and temporal dynamics of algae blooms, we applied a grey Bernoulli model with improved parameter calibration and Markov theory with arguments for error modification and subset independent optimization were introduced. The performance of the optimized model for short-term predictions of the average chlorophyll concentration was verified using measurements at ten sampling sites in the Xiangxi River in the summer of 2015. The results show that predicted values are generally in accordance with the observations and that the optimized model is able to reproduce the spatial variation of chlorophyll concentration in Xiangxi Bay. At present, the sites XX06~XX08 were high risk regions for algae bloom development, with average chlorophyll concentration strongly exceeding the bloom threshold. Site XX02 was found to be less vulnerable to bloom occurrence. Compared with conventional grey models, the optimization method performs better both in terms of precision and stability for swing sequence.