Real-time hydrograph modelling in the upper Nysa Kłodzka river basin (SW Poland): a two-model hydrologic ensemble prediction approach

Abstract

A new system for computing the multimodel ensemble predictions of water levels, known as HydroProg, is applied in the process of real-time modelling and forecasting riverflow in the upper Nysa Kłodzka basin (SW Poland). The HydroProg system automatically produces early warnings against high flows on a basis of prognoses from external hydrologic models which are run in a cloud-like fashion using the real-time hydrometeorological observations. The predictions offered by the models serve as ensemble members and become inputs to HydroProg which does data pre- and post-processing as well as computes multimodel ensemble predictions. The HydroProg system is used in this paper to verify the operational hypothesis that a two-model ensemble hydrologic prediction, solely based on two prognoses computed from the multi- and univariate autoregressive statistical models, reveals better skills than the individual members. The analysis is conducted for all lead times and selected phases of high flow development, including a rising limb of hydrograph but excluding a peak flow. The investigation is carried out using the first HydroProg prototype that works experimentally for the upper Nysa Kłodzka basin (SW Poland). The implementation offers 3-h predictions of water levels, based on the regularly (15 mins) calibrated and updated individual models (the emphasis is put on two models, but other models are also presented for reference) which become inputs to the multimodel ensemble solution (mainly the two-model approach, with the six-model solution presented for comparison). The most significant high flows that occurred in the study area between 01/09/2013 and 31/08/2015 have been investigated. It has been found that for slightly rising water level the two-model ensemble is recommended which, for a subsequently moderately or rapidly rising limb of hydrograph, should be replaced by the vector autoregressive model.