Variation laws of ice regime and intelligent coupling forecast model in the Inner Mongolia reach of the Yellow River
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Abstract:
Due t o the special geog ra phical po sition, hy dr o2meteo rolog ical co nditio ns, and r iver course characterist ics, ice floo d al2 mo st occur s ev ery year in the Inner Mong olia reach of the Yellow Riv er. The meteo rolog ical and hydro lo gical data at t he ma in co nt rolling statio ns in t he Inner M ongo lia reach wer e analy zed, w hich sug g ested that the temper ature and flow dischar ge in2 cr ease in recent year s, the ice run date and fr eeze2up date push back while the br eak2up dat e br ings fo rw ard, and the max imum ice thickness t hins obv iously . In this paper, the appr opriate predictio n facto rs w ere selected by the co rrelatio n analysis. Ice re2 g ime intellig ent coupling fo recast model w as built using the neur al netw or k metho d based o n the g enetic algo rithm. The model was applied to for ecast the ice run date, fr eeze2up date, and break2up date at t he Bay ang aole station in the Inner Mongo lia r each. The forecast r esults o btained from different models wer e compared, and it show ed that the mult iple linear model, BP mo del, and GA2BP model have hig h passing percentages, which ar e 80%, 86. 7%, and 93. 3%, respectively. GA2BP mo del has the hig hest forecast accur acy and can pro vide the cr itical suppo rt fo r the pr evention of ice disasters in the Inner Mongo lia reach o f the Yellow River.
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