资源环境科技发展态势分析平台

Spatial parameter fields are required to model hydrological processes across diverse landscapes. Transfer functions are often used to relate parameters to spatial catchment attributes, introducing large uncertainties. Quantifying these uncertainties remains a key challenge for large scale modelling. This paper extends the multiscale parameter regionalisation (MPR) technique to consider parameter uncertainties. We evaluate this method of producing nationally consistent parameter fields, which maintain a constant relationship between model parameters and catchment attributes, across 437 catchments in Great Britain (GB). By sampling multiple transfer function parameters, we produce thousands of possible model parameter fields which are constrained within an uncertainty framework. This is compared to spatially homogeneous parameter sets constrained for individual catchments. The nationally consistent MPR parameter fields perform well (KGE* > 0.75) across 60% of catchments. Performance is similar or better than catchment-constrained parameters (KGE* drop < 0.1) across 82% of catchments. Advantages of our national parameter fields include (1) improved representation of flows within catchments, (2) more robust performance between calibration and evaluation periods and (3) spatial parameter fields reflecting hydrologically meaningful variation in catchment characteristics. By including uncertainties, we show that hydrographs produced using MPR have smaller uncertainty bounds which are better able to encompass flows. As the first application of MPR to both the DECIPHeR modelling framework and GB, we developed transfer functions and identified key catchment attributes to constrain model parameters, which are transferrable to other models alongside the addition of uncertainty. Methodologies presented here are informative for future regionalisation efforts in GB and elsewhere.

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