Scaling behaviour of hydrological fluxes and variables: Empirical studies using a hydrological model and remote sensing data

The effects of small-scale heterogeneity in land surface characteristics on the large-scale fluxes of water and energy in the land-atmosphere system has become a central focus of many of the climatology research experiments. The acquisition of high resolution land surface data through remote sensing and intensive land-climatology field experiments (such as HAPEX and FIFE) has provided data to investigate the interactions between microscale land-atmosphere interactions and macroscale models. One essential research question is how to account for the small-scale heterogeneities and whether 'effective' parameters can be used in the macroscale models. To address this question of scaling, is important to carry out modelling studies by analysing the spatial behaviour of process-based, distributed land-atmospheric models and available data from land surface climate experiments such as those designed under ISLSCP (e.g. FIFE and BOREAS) and HAPEX (e.g. HAPEX-MOBILY, HAPEX-SAHEL) and GEWEX (e.g. GCIP) and from smaller scale remote sensing experiments. Using data from FIFE'87 and WASHITA'92, a soil moisture remote sensing experiment, analyses are presented on how the land surface hydrology during rain events and between rain event varies; specifically, runoff during rain events, evaporation between rain events and soil moisture. The analysis with FIFE'87 data suggests that the scale at which a macroscale model becomes valid, the representative elementary scale (REA), is of the order of 1.5-3 correlation lengths, which for the land processes investigated appear to be about 750-1250 m. For the Washita catchment data, analysis of soil-based infiltration data supports an REA of this spatial scale, but model derived and remotely sensed soil moisture data appear to suggest a larger scale. Statistical self-similarity is investigated to further understand how soil moisture scales over the Washita catchment and to provide a basis for macroscale models.

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