Chappell, N.A., Bidin, K., Sherlock, M.D., and Lancaster, J.W. 2004. Parsimonious spatial representation of tropical soils within dynamic, rainfall-runoff models. In Forests, Water and People in the Humid Tropics, Bonell M. and Bruijnzeel, L.A. (Eds), Cambridge University Press, Cambridge. p 756-769.



New and more considered application of models that simulate the rainfall-runoff behaviour of tropical catchments, would greatly add to our understanding of tropical hydrology and provide greater objectivity in the assessment of water-related management issues. Choice of model is often difficult, but we believe should have consideration for the level of detailed, quantitative information that is available for the catchment under study.

Recent work has demonstrated that the functional relationship between catchment rainfall and the river-discharge generated, often requires very few (3 to 5) model catchment parameters* to be described. The use of greater numbers of catchment parameters within more complicated model-structures* (that characterise many process-based catchment models: see Beven, 2001a), therefore, should necessitate that these parameter-sets / model-structures are tested and hence 'justified' by distributed (thus inevitably, semi-quantitative) field observations. As model complexity increases, the riverflow time-series becomes predictable from a very wide range of parameter sets, so that each sensitive* parameter becomes more and more uncertain. There is, therefore, value in limiting the complexity of models (i.e., parsimony*) to allow evaluation of the component structures or parameters. Dynamic rainfall-runoff models that utilise topographic information (e.g., TOPMODEL and TOPOG_SBM / TOPOG_DYNAMIC) can have more parsimonious model structures, though this is not always the case. While the value of their topographic indices in predicting saturated areas has been tested by numerous studies over the last decade (albeit within temperate climates), their spatial distributions (in 1 to 3 dimensions) of the other model component, the soil-rock transmissivity and/or soil-rock permeability*, has received much less attention, often because of the limitations of the field data. Yet, soil-rock permeability is often seen as the most important soil-rock property specified within physics-based models.

As a result, this partial assessment of the current status of tropical catchment modelling will focus on those issues central to the parameterisation* of soil-rock permeability within those dynamic rainfall-runoff models simplified by the use of topographic information. The key points being: (a) what is the relationship between field measurements of soil-rock permeability and the 'effective values' capable of simulating the riverflow time-series ? and (b) how complex can model parameterisations of soils become before we cannot justify them statistically ?

We believe that the results of the analyses presented, demonstrates that the spatial distribution of soil permeability derived from inversion* of catchment-scale models is very different to that derived from tests on small-samples (even allowing for the severe limitations of the model inversion process). The differences are consistent with the presence of zones of preferential flow* (i.e., natural soil pipes*, percolines* and fractures) that are inadequately characterised by tests on small-samples. A new strategy for deriving measures of soil permeability integrated over whole hillslopes (hence including larger preferential flow pathways) is illustrated. Early results suggest that the results from such techniques give soil-rock permeabilities that are more consistent with those integrated over whole catchments (and hence observable by catchment models).

Clearly, addressing the issue of how best to characterise those tropical soil parameters that regulate catchment rainfall-runoff behaviour, is an important precursor to the reliable prediction of how land-use change might alter tropical soil parameters and thence streamflow generation and nutrient transport.

* see glossary

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