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Abstract. Land surface models (LSMs) represent terrestrial hydrology in weather andclimate modelling operational systems and research studies. We aim to improvehydrological performance in the Joint UK Land Environment Simulator (JULES)LSM that is used for distributed hydrological modelling within the newland–atmosphere–ocean coupled prediction system UKC2 (UK regional Coupled environmentalprediction system 2). Using river flow observations from gauge stations, westudy the capability of JULES to simulate river flow at 1 km2 spatialresolution within 13 catchments in Great Britain that exhibit a variety ofclimatic and topographic characteristics. Tests designed to identify wherethe model results are sensitive to the scheme and parameters chosen forrunoff production indicate that different catchments require differentparameters and even different runoff schemes for optimal results. Weintroduce a new parameterisation of topographic variation that produces thebest daily river flow results (in terms of Nash–Sutcliffe efficiency andmean bias) for all 13 catchments. The new parameterisation introduces adependency on terrain slope, constraining surface runoff production to wetsoil conditions over flatter regions, whereas over steeper regions the modelproduces surface runoff for every rainfall event regardless of the soilwetness state. This new parameterisation improves the model performanceacross Great Britain. As an example, in the Thames catchment, which hasextensive areas of flat terrain, the Nash–Sutcliffe efficiency exceeds 0.8using the new parameterisation. We use cross-spectral analysis to evaluatethe amplitude and phase of the modelled versus observed river flows overtimescales of 2 days to 10 years. This demonstrates that the modelperformance is modified by changing the parameterisation by different amountsover annual, weekly-to-monthly and multi-day timescales in differentcatchments, providing insights into model deficiencies on particulartimescales, but it reinforces the newly developed parameterisation.

geoscientific model development

Using observed river flow data to improve the hydrological functioning of the JULES land surface model (vn4.3) used for regional coupled modelling in Great Britain (UKC2)