New metrics for characterizing and comparing soil moisture dynamics across depths and locations

Authors: Meles, Menberu; RAULERSON, SCOTT - University Of Georgia; RAU, BENJAMIN - Us Forest Service (FS); RAHMAN, MASHREKUR - US Department Of Agriculture (USDA); JACKSON, C. RHETT - University Of Georgia

Submitted to: Frontiers in Water
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/27/2026
Publication Date: 6/11/2026
Citation: Meles, M.B., Raulerson, S., Rau, B., Rahman, M., Jackson, C. 2026. New metrics for characterizing and comparing soil moisture dynamics across depths and locations. Frontiers in Water. 8. Article 1840091. https://doi.org/10.3389/frwa.2026.1840091.
DOI: https://doi.org/10.3389/frwa.2026.1840091

Interpretive Summary: Understanding and predicting soil moisture dynamics is an active area of research as it is a crucial driver of hydrological and agroecological processes. Assessing soil moisture changes across large landscapes demands multiple disciplines and the application of landscape classification methods. This is due to the fact that soil moisture variability is contingent upon factors such as morphology, soil, climate, and land cover conditions on soil moisture variability. However, landscape indices pertaining to soil moisture changes rely mainly on topography, and some soil properties. Unfortunately, these indices have limited predictive capability due to the coarse data and oversimplifying assumptions. To address these limitations, we developed and extracted three time series signatures from soil moisture data at five locations across the US. These signatures are the rate of soil moisture loss rates (slope of the soil moisture recession curves), the number of slope reversal in the time series, and the rapidity of short-term changes in the time series that shows the integrated impacts of the complex interactions between biotic and abiotic factors controlling soil moisture dynamics. These signatures effectively capture the integrated effects of the complex interactions between biotic and abiotic factors that influence soil moisture dynamics that can be used to develop a more comprehensive index. The findings of this research contribute valuable hydro-morphologic insights into soil moisture dynamics and have potential applications in fields such as hydrology, agriculture, and forest and rangeland management.

Technical Abstract: Soil moisture is one of the critical drivers of hydrological and agroecological processes. Efforts to characterize landscapes and predict soil moisture are the focus of scientists and practitioners. Both groups require the use of multidisciplinary approaches and the application of landscape classification methods to characterize moisture conditions across landscapes. Landscape indices related to soil moisture often rely on available spatial data like topographic position, a few soil physical properties, or combinations thereof. These indices have limited predictive capability stemming from the coarseness of available data and oversimplified assumptions. In this research, we develop three interrelated soil moisture time series signatures: the rate of soil moisture loss (slope of the soil moisture recession curves); the slope reversal frequency of the soil moisture time series; and the flashiness index, and we applied these to in-situ data from five t experimental watersheds in the US. These new time series signatures integrate the complex interactions of various biotic and abiotic factors that control the dynamics of soil moisture. Soil moisture control factors include morphologic parameters, soils, climate, land cover, and proximity parameters. In this work, we will show the workflow for computing new soil moisture time series signatures that integrate the effects of the various control factors that can be applied to understand the role and extent of the control factors on soil moisture dynamics.