摘要：Streambeds are critical hydrological interfaces: their physical properties regulate the rate, timing, and location of fluxes between aquifers and streams. Streambed vertical hydraulic conductivity (Kv) is a key parameter in watershed models, so understanding its spatial variability and uncertainty is essential to accurately predicting how stresses and environmental signals propagate through the hydrologic system. Most distributed modeling studies use generalized Kv estimates from column experiments or grain-size distribution, but Kv may include a wide range of orders of magnitude for a given particle size group. Thus, precisely predicting Kv spatially has remained conceptual, experimental, and/or poorly constrained. This usually leads to increased uncertainty in modeling results. There is a need to shift focus from scaling up pore-scale column experiments to watershed dimensions by proposing a new kind of approach that can apply to a whole watershed while incorporating spatial variability of complex hydrological processes. Here we present a new approach, Multi-Stemmed Nested Funnel (MSNF), to develop pedo-transfer functions (PTFs) capable of simulating the effects of complex sediment routing on Kv variability across multiple stream orders in Frenchman Creek watershed, USA. We find that using the product of Kv and drainage area as a response variable reduces the fuzziness in selecting the “best” PTF. We propose that the PTF can be used in predicting the ranges of Kv values across multiple stream orders.
