Articles | Volume 20, issue 1
Hydrol. Earth Syst. Sci., 20, 143–159, 2016
Hydrol. Earth Syst. Sci., 20, 143–159, 2016

Research article 18 Jan 2016

Research article | 18 Jan 2016

Diagnosing hydrological limitations of a land surface model: application of JULES to a deep-groundwater chalk basin

N. Le Vine1, A. Butler1, N. McIntyre1,2, and C. Jackson3 N. Le Vine et al.
  • 1Department of Civil and Environmental Engineering, Imperial College London, London, UK
  • 2Centre for Water in the Minerals Industry, the University of Queensland, St. Lucia, Australia
  • 3British Geological Survey, Keyworth, UK

Abstract. Land surface models (LSMs) are prospective starting points to develop a global hyper-resolution model of the terrestrial water, energy, and biogeochemical cycles. However, there are some fundamental limitations of LSMs related to how meaningfully hydrological fluxes and stores are represented. A diagnostic approach to model evaluation and improvement is taken here that exploits hydrological expert knowledge to detect LSM inadequacies through consideration of the major behavioural functions of a hydrological system: overall water balance, vertical water redistribution in the unsaturated zone, temporal water redistribution, and spatial water redistribution over the catchment's groundwater and surface-water systems. Three types of information are utilized to improve the model's hydrology: (a) observations, (b) information about expected response from regionalized data, and (c) information from an independent physics-based model. The study considers the JULES (Joint UK Land Environmental Simulator) LSM applied to a deep-groundwater chalk catchment in the UK. The diagnosed hydrological limitations and the proposed ways to address them are indicative of the challenges faced while transitioning to a global high resolution model of the water cycle.

Short summary
– A strategy to diagnose hydrological limitations of a Land Surface Model – Land Surface Model adaptation for hydrological applications – Highlights challenges faced while moving towards high resolution modelling