Abstract:Physically based and spatially distributed modelling of catchment hydrology involves the estimation of block or whole-hillslope permeabilities. Invariably these estimates are derived by calibration against rainfall±runo response. Rarely are these estimates rigorously compared with parameter measurements made at the small scale. This study uses a parametrically simple model, TOPMODEL, and an uncertainty framework to derive permeability at the catchment scale. The utility of expert knowledge of the internal catchment dynamics (i.e. extent of saturated area) in constraining parameter uncertainty is demonstrated. Model-derived estimates are then compared with core-based measurements of permeability appropriately up-scaled. The observed dierences between the permeability estimates derived by the two methods might be attributed to the role of intermediate scale features (natural soil pipes). An alternative method of determining block permeabilities at the intermediate or hillslope scale is described. This method uses pulse-wave tests and explicitly incorporates the resultant eects of phenomena such as soil piping and kinematic wave migration. The study aims to highlight issues associated with parameterizing or validating distributed models, rather than to provide a de®nitive solution. The fact that the permeability distribution within the Borneo study catchment is comparatively simple, assists the comparisons. The ®eld data were collected in terrain covered by equatorial rainforest. Combined ®eld measurement and modelling programmes are rare within such environments. #
This paper synthesizes the results of a 15-year study (1988-2003) assessing the changes in slope and catchment erosion and sediment sources within the Segama catchment in Sabah, Malaysia, that was selectively-logged using a combination of tractor and high-lead logging techniques between December 1988 and June 1989 and then left to regenerate naturally. Comparisons are drawn with date on slope erosion rates and sediment sources in adjacent primary forest catchments.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.