资源环境科技发展态势分析平台

The permeability architecture has a major influence on hillslope flow-path and hydro-geochemistry. To constrain this architecture and overcome equifinality in the diagnosis of hillslope flow-paths within hydrologic transport models, different types of complementary data (e.g., tracer) have been recommended. However, there is still little information on the extent to which such complementary data can unravel the permeability architecture, and where and when to measure such data to most efficiently constrain models. Here, we couple a Richards-based flow and transport model with extensive long-term field measurements to compare the relative value of different types of hydrometric and tracer data in discriminating between contrasting permeability (or saturated hydraulic conductivity ()) architectures, in the absence of macropore flow. Our results show that compared to streamflow and water table observations, stream tracer data has a stronger evaluative potential to constrain hillslope vertical pattern in , in particular during seasons when flow is on average low (e.g., winter or summer). Tracer data from within the hillslope are even more helpful to discriminate between different vertical patterns in K_s than stream tracer data. This suggests a higher evaluative potential for hillslope tracer observations. This evaluative potential of hillslope data depends on where and when the data is collected, and increases with depth from the soil surface, with distance from the stream and during seasons when flow is low. The findings also emphasize the importance of incorporating hillslope permeability architecture in hydrologic transport models in order to reduce the uncertainty in the predictions of stream water quality.

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