Soil Systems for Upscaling Saturated Hydraulic Conductivity for Hydrological Modeling in the Critical Zone

Abstract

Successful hydrological model predictions depend on appropriate framing of scale and the spatial-temporal accuracy of input parameters describing soil hydraulic properties. Saturated soil hydraulic conductivity (K sat ) is one of the most important properties influencing water movement through soil under saturated conditions. It is also one of the most expensive to measure and is highly variable. The objectives of this research were (i) to assess the ability of Amoozemeters, wells, piezometers, and flumes to accurately represent K sat at a small catchment scale and (ii) to extrapolate K sat to a larger watershed based on available soil data and soil landscape models for simulating streamflow using the Distributed Hydrological Soil Vegetation Model. The mean K sat between Amoozemeters, wells, and flumes varied from 2.4 to 4.9 ´ 10 −7 m s −1 , and differences were not significant. Mixed trends in mean K sat for slope positions and soil series were observed. The strongest significant and consistent trend in mean K sat was observed for soil depth. The mean K sat decreased exponentially with depth, from 6.51 ´ 10 6 m s −1 for upper horizons to 2.37 ´ 10 −7 m s −1 for bottom horizons. Recognizing the significantly decreasing trend of K sat with soil depth and the lack of consistent trends between soils and slope positions for small catchments, K sat values were extrapolated from the small catchments occurring in Dillon Creek to another large watershed (Hall Creek) based on soil similarity and distribution. The Nash-Sutcliffe model overall efficiency of 0.52 indicated a good performance in simulating streamflows without model calibration. Combining K sat measurement methods in small catchments with an understanding of soil landscapes and soil distribution relationships allowed successful upscaling of localized soil hydraulic properties for streamflow predictions to larger watersheds.

Toprak hidropedolojik özelliklerinin gypsic ustorthent ve typic ustifluent’de faktör analizi ile değerlendirilmesi

“…The results are consistent with those reported in many studies, showing positive relations between macropores and Ks (Jarvis 2007;Dexter and Richard, 2009;Van Tol et al 2012). However, soil macropores and voids can increase Ks, which are not completely related to unsaturated hydraulic conductivity K(h) (Libohova et al, 2018). Structural macropores and/or root macropores have important contributions to Ks variability (Perret et al 1999;Watson and Luxmoore, 1986;White 1985).…”

Coupled inversion of hydraulic and self‐potential data from transient outflow experiments to estimate soil petrophysical properties

“…The spatial variability of hydraulic properties in the subsurface could significantly affect the partitioning of precipitation in the critical zone (Takagi & Lin, 2011), an open system extending from the top of the canopy to the base of active groundwater (Giardino & Houser, 2015), thus influencing the amount, routing, and residence time of groundwater (Brooks et al., 2015). Many experimental methods have been proven effective in characterizing the hydraulic properties of earth materials in the critical zone, including field sampling and then testing in the laboratory (Wieting et al., 2017), field hydraulic tests (Libohova et al., 2018; Zhang et al., 2020), and geophysical tests (Holbrook et al., 2014). As an important portion of the critical zone, the vadose zone plays a paramount role in affecting the water chemistry and dynamics in the critical zone (Jin et al., 2011).…”

Identifying Covariates to Assess the Spatial Variability of Saturated Soil Hydraulic Conductivity Using Robust Cokriging at the Watershed Scale

“…Techniques that capture soil spatial and temporal variability have recently evolved to focus the attention of soil scientists on soil attributes related to hydrological models (Qiao et al 2018;She et al 2017). According to Libohova et al (2018), the success of predictions when modeling hydrological processes depends on the accurate representation of the spatial and temporal variability of soil hydrological attributes and the main external factors, such as climate, land use and management, and soil water dynamics.…”