Soil Texture Often Exerts a Stronger Influence Than Precipitation on Mesoscale Soil Moisture Patterns

Abstract

Soil moisture patterns are commonly thought to be dominated by land surface characteristics, such as soil texture, at small scales and by atmospheric processes, such as precipitation, at larger scales. However, a growing body of evidence challenges this conceptual model. We investigated the structural similarity and spatial correlations between mesoscale (∼1–100 km) soil moisture patterns and land surface and atmospheric factors along a 150 km transect using 4 km multisensor precipitation data and a cosmic‐ray neutron rover, with a 400 m diameter footprint. The rover was used to measure soil moisture along the transect 18 times over 13 months. Spatial structures of soil moisture, soil texture (sand content), and antecedent precipitation index (API) were characterized using autocorrelation functions and fitted with exponential models. Relative importance of land surface characteristics and atmospheric processes were compared using correlation coefficients (r) between soil moisture and sand content or API. The correlation lengths of soil moisture, sand content, and API ranged from 12–32 km, 13–20 km, and 14–45 km, respectively. Soil moisture was more strongly correlated with sand content (r = −0.536 to −0.704) than with API for all but one date. Thus, land surface characteristics exhibit coherent spatial patterns at scales up to 20 km, and those patterns often exert a stronger influence than do precipitation patterns on mesoscale spatial patterns of soil moisture.

Exploring Scale‐Specific Controls on Soil Water Content across a 500‐Kilometer Transect Using Multivariate Empirical Mode Decomposition

“…Many researchers have reported that soil moisture is commonly thought to be controlled by land surface characteristics, such as topography, vegetation, and deduced root structure, and landform at small scales, and by atmospheric factors, such as precipitation and evaporation patterns, at larger scales (Seyfried, 1998; Entin et al, 2000; Brocca et al, 2010; Cho and Choi 2014). Using empirical orthogonal functions (Champa and Mohanty, 2010; Wang et al, 2017a) and cosmic‐ray neutron rover methods (Dong and Ochsner, 2018), some evidence suggests that soil texture is a large‐scale factor for soil moisture variation. In the current study, we applied the MEMD method first across a regional scale and investigated the relative roles of meteorological forcings and local factors in controlling soil moisture patterns.…”

A Comprehensive Distributed Hydrological Modeling Intercomparison to Support Process Representation and Data Collection Strategies

“…Thus, high‐spatial‐resolution soil moisture observations as provided by remote sensing products are valuable information to integrate in the models even if only the surface soil is detected (Barrett et al, ; Paloscia et al, ). The use of roving cosmic ray neutron sensing could be another promising tool for inferring soil moisture status and their integration into hydrological models, also because the signal integrates over most of the root zone (Chrisman & Zreda, ; Dong & Ochsner, ; Schrön et al, ).…”

Mesoscale Soil Moisture Patterns Revealed Using a Sparse In Situ Network and Regression Kriging

“…In a parallel study, we discovered a strong negative correlation between mesoscale patterns in sand content and soil moisture (Dong & Ochsner, ); therefore, sand content (%) is used in the regression kriging approach as a proxy for the various soil properties that control soil water retention. For every Mesonet site and each grid point, sand content at 5, 25, and 60 cm was estimated using the 10‐m resolution Gridded Soil Survey Geographic (gSSURGO) Database (Soil Survey Staff, ).…”