Probabilistic flood forecasting based on multi-model MCP

The pr obabilistic flo od fo recasting can pro v ide a predictio n inter val w ith a certain reliabilit y, and can be used to e2 v aluat e the reliability of fo recasting results. It can pro v ide an im portant basis fo r floo d co ntro l scheduling . We too k Wa ng jia2 ba cr oss2sectio n, a key f lo od contr ol sectio n of H uaihe River, as the resear ch object. Based on the predict ion results of API and XAJ mo dels, using t he M odel condit ional pr ocesso r ( MCP) to deduce the co nditio na l pro ba bility distributio n function of the for ecasting runo ff of floo ds o f different m agnitudes, w e r ealized pro babilistic flo od fo recasting . T he pr edictio n results w ere analyzed in terms of the dete rministic precision evaluatio n o f m edian number and the r eliability ev aluat ion of pro babilis2 tic for ecasting . The r esults show ed that the M CP pr obabilistic floo d fo recasting has a high r eliability, a nd its median number predictio n has a hig her pr edictio n accur acy t ha n the determinist ic mo del, indicating that M CP has a certain ability of co rr ec2 tion and prediction.

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