【摘要】：為了提高洪水預(yù)報(bào)的精度和預(yù)見期,本文提出了一種耦合數(shù)值天氣預(yù)報(bào)和多目標(biāo)參數(shù)優(yōu)化的洪水預(yù)報(bào)方法。利用基于ε網(wǎng)格的帶精英策略的非支配排序遺傳算法(ε-NSGAⅡ)對(duì)分布式水文 土壤 植被模型(DHSVM)進(jìn)行了自動(dòng)率定,并將歐洲中期天氣預(yù)報(bào)中心(ECMWF)的24小時(shí)累積降水預(yù)報(bào)信息進(jìn)行等權(quán)重加權(quán)集合平均,驅(qū)動(dòng)DHSVM模型進(jìn)行洪水預(yù)報(bào)。結(jié)果表明對(duì)于整體流量過(guò)程線而言,預(yù)見期在8天以內(nèi)較為可靠,其預(yù)報(bào)值與實(shí)測(cè)值的相對(duì)平均誤差(RME)在20%范圍之內(nèi)。相對(duì)于傳統(tǒng)的確定性洪水預(yù)報(bào),引入集合數(shù)值天氣預(yù)報(bào)后能夠延長(zhǎng)洪水預(yù)報(bào)的預(yù)見期,為發(fā)展洪水預(yù)報(bào)方法提供一種有效途徑。
[Abstract]:In order to improve the accuracy and prediction period of flood forecasting, a flood forecasting method coupled with numerical weather forecasting and multi-objective parameter optimization is proposed in this paper. The distributed hydrological soil vegetation model (DHSVM) was automatically determined by using the non-dominant sorting genetic algorithm with elitist strategy based on 蔚 grid (蔚-NSGA 鈪，

本文編號(hào)：2473067