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Elizabeth Cultra

Publications and source records attributed to Elizabeth Cultra.

2 recordsLinked to original sources

Ecohydrological Controls on Moist Convection and Long-Term Rainfall Feedback

To elucidate how land surface state and soil moisture dynamics regulate moist convection, and how convective rainfall subsequently reshapes surface and root-zone hydrology, we develop a stochastic dynamical model that couples soil moisture, vegetation hydraulics, atmospheric boundary layer evolution, and convective available potential energy (CAPE). We show that CAPE depends not only on the free-tropospheric environment but also on soil moisture, through its control of surface fluxes, boundary-layer growth, and the timing of the intersection between the atmospheric boundary layer and the lifting condensation level (LCL). Soil texture and plant properties strongly modulate convective potential during dry-down. Loamy sand favors convection at relatively high soil moisture and maintains the largest CAPE at the time of LCL-ABL crossing across drying conditions. In contrast, sandy soils exhibit high CAPE when wet but lose convective potential rapidly as they dry. As matric potential becomes more negative, convection is increasingly suppressed in finer, loamy clay textures. Plant functional type further shapes dry-down dynamics: water-use-maximizing strategies can enhance dry persistence via stomatal closure during drying, whereas more conservative strategies can sustain convection for longer periods. On longer timescales, stochastic rainfall forcing with CAPE-dependent precipitation intensity produces persistent wet and dry soil moisture regimes, with switching times that depend on soil hydraulic properties, plant physiological traits, and atmospheric conditions.

physics.ao-ph

Stochastic ecohydrological perspective on semi-distributed rainfall-runoff dynamics

Quantifying watershed process variability consistently with climate change and ecohydrological dynamics remains a central challenge in hydrology. Stochastic ecohydrology characterizes hydrologic variability through probability distributions that link climate, hydrology, and ecology. However, these approaches are often limited to small spatial scales (e.g., point or plot level) or focus on specific fluxes (e.g., streamflow), without accounting for the entire water balance at the basin scale. While semi-distributed models account for spatial heterogeneity and upscaled hydrologic fluxes, they lack the analytical simplicity of stochastic ecohydrology or the SCS-CN method and, perhaps more importantly, do not integrate the effects of past random variability in hydroclimatic conditions. This hinders an efficient characterization of hydrological statistics at the watershed scale. To overcome these limitations, we merge stochastic ecohydrology, the spatial upscaling of semi-distributed modeling, and the SCS-CN rainfall-runoff partitioning. The resulting unified model analytically characterizes watershed ecohydrological and hydrological statistics using probability density functions (PDFs) that are functions of climate and watershed attributes -- something unattainable with the Monte Carlo methods of traditional stochastic hydrology. Calibrated across 81 watersheds in Florida and southern Louisiana, the model PDFs precisely capture the long-term average water balance and runoff variance, as well as the runoff quantiles with a median normalized Nash-Sutcliffe (NNSE) efficiency of 0.95. These results also advance the SCS-CN method by providing an analytical PDF for the Curve Number (CN), explicitly linked to climate variables, baseflow, and the long-term water balance partitioning described by the Budyko curve.

physics.geo-ph