Moisture pulse-reserve in the soil-plant continuum observed across biomes

Feldman, Andrew F.; Gianotti, Daniel J. Short; Konings, Alexandra G.; McColl, Kaighin A.; Akbar, Ruzbeh; Salvucci, Guido D.; Entekhabi, Dara

doi:10.1038/s41477-018-0304-9

Cited by 96 publications

(92 citation statements)

References 61 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…While the time it takes to reach θ* may be quicker in coarse soils during drying (Aminzadeh & Or, ), moisture extraction via ET can occur at lower θ due to less matric suction than in finer soils. This is consistent with findings of lower θ thresholds on plant water uptake for coarser soils (Feldman et al, ). θ* and mean annual precipitation are weakly, positively correlated ( ρ = 0.26; p < 0.01) with the sign of dependence consistent with previous studies (Akbar et al, ; Schwingshackl et al, ).…”

Section: Resultssupporting

confidence: 92%

Satellite‐Based Assessment of Land Surface Energy Partitioning–Soil Moisture Relationships and Effects of Confounding Variables

Feldman

Gianotti

Trigo

et al. 2019

Water Resources Research

Self Cite

View full text Add to dashboard Cite

Land surface energetic partitioning between latent, sensible, and ground heat fluxes determines climate and influences the terrestrial segment of land-atmosphere coupling. Soil moisture, among other variables, has a direct influence on this partitioning. Dry surfaces characterize a water-limited regime where evapotranspiration and soil moisture are coupled. This coupling is subdued for wet surfaces, or an energy-limited regime. This framework is commonly evaluated using the evaporative fraction--soil moisture relationship. However, this relationship is explicitly or implicitly prescribed in land surface models. These impositions, in turn, confound model-based evaluations of energetic partitioning--soil moisture relationships. In this study, we use satellite-based observations of surface temperature diurnal amplitude (directly related to available energy partitioning) and soil moisture, free of model impositions, to estimate characteristics of surface energetic partitioning--soil moisture relationships during 10--20-day surface drying periods across Africa. We specifically estimate the spatial patterns of water-limited energy flux sensitivity to soil moisture (m) and the soil moisture threshold separating water and energy-limited regimes (θ*). We also assess how time evolution of other factors (e.g., solar radiation, vapor pressure deficit, surface albedo, and wind speed) can confound the energetic partitioning--soil moisture relationship. We find higher m in drier regions and interestingly similar spatial θ* distributions across biomes. Vapor pressure deficit and insolation increases during drying tend to increase m. Only vapor pressure deficit increases in the Sahelian grasslands systematically decrease θ*. Ultimately, soil and atmospheric moisture availability together play the largest role in land surface energy partitioning with minimal consistent influences of time evolution of other forcings.Plain Language Summary Whether available, incoming solar energy is used for evaporating surface water, or surface heating largely depends on water availability across the landscape. Under dry conditions (water limitation), increasing soil moisture increases evaporation and surface cooling. In this regime, droughts and heatwaves can be initiated and sustained because drying is positively reinforced. Under wetter conditions (energy limitation), increasing soil moisture does not generally influence evaporation. Climate models rely on these soil moisture-evaporation relationships to describe associations between water and energy cycles and predict future climate. However, due to difficulty observing evaporation at large scales, these relationships assume different forms across climate models which contribute to divergences and uncertainty in making climate projections. We use satellite observations of soil moisture and daily temperature range (quantifying surface heating; inversely related to evaporation) to evaluate these relationships free of model impositions across Africa. Following rain events during surface drying, da...

show abstract

Section: Resultssupporting

confidence: 92%

Satellite‐Based Assessment of Land Surface Energy Partitioning–Soil Moisture Relationships and Effects of Confounding Variables

Feldman

Gianotti

Trigo

et al. 2019

Water Resources Research

Self Cite

View full text Add to dashboard Cite

show abstract

“…Our study further indicates that satellite microwave vegetation optical depth observations show notable responses to surface and atmospheric variability not only at seasonal, but also at sub-weekly timescales (Feldman et al, 2018;).…”

Section: Discussionsupporting

confidence: 70%

“…VAR assumes linear interactions between variables and time constant . While nonlinearities between variables and time changing interactions may exist (for example, between wet and dry seasons, which can influence soil moisture effects), primary effects are reduced by considering interactions only in drydowns and water-limited regimes where nonlinearities due to transitioning between dry and wet moisture states are not present (Feldman et al, 2019(Feldman et al, , 2018.…”

Section: Vector Autoregressionmentioning

confidence: 99%

Land‐Atmosphere Drivers of Landscape‐Scale Plant Water Content Loss

Feldman

Gianotti

Trigo

et al. 2020

Geophysical Research Letters

Self Cite

View full text Add to dashboard Cite

Plant water content observations using microwave remote sensing measurements allow monitoring of landscape-scale plant water stress. During soil drying following rainfall events, we use a Granger causality framework to quantify the degree to which environmental factors drive satellite-based plant water content loss across Africa's diverse biomes. After soil drying into the water-limited regime, satellite observations show that plants dry while solar radiation, vapor pressure deficit, and diurnal temperature amplitude increase. We find that soil drying primarily drives plant water content loss across African drylands, though with regional effects of diurnal temperature amplitude increases (found to indicate vapor pressure deficit increases here). We also detect interactions between these factors that reinforce plant drying during periods of soil moisture loss. Our results provide observational evidence across Africa that individual and interactive components of surface drying and heating can all drive plant water stress, especially during intermittent post-storm drying periods.

show abstract

“…This could be a reason why the canonical wilting point value of −1.5 MPa, which is based on plant vigor, when whole‐plant transpiration ceases, is more negative than our inferred Ψ 0 values, based only on the surface soil water balance. Prior satellite estimates of thresholds at which vegetation water content decreases correspond to more negative soil water potentials than those found in this study (Feldman et al, ). Models that represent water uptake from different soil layers typically use same thresholds for each depth (Baker et al, ; Clark et al, ; Oleson et al, ).…”

Section: Resultssupporting

confidence: 43%

Plant Water Uptake Thresholds Inferred From Satellite Soil Moisture

Bassiouni

Good

Still

et al. 2020

Geophysical Research Letters

View full text Add to dashboard Cite

Empirical functions are widely used in hydrological, agricultural, and Earth system models to parameterize plant water uptake. We infer soil water potentials at which uptake is downregulated from its well-watered rate and at which uptake ceases, in biomes with <60% woody vegetation at 36-km grid resolution. We estimate thresholds through Bayesian inference using a stochastic soil water balance framework to construct theoretical soil moisture probability distributions consistent with empirical distributions derived from satellite soil moisture observations. The global median Nash-Sutcliffe efficiency between empirical soil moisture distributions and theoretical distributions using reference constants, inferred median parameters per biome, and spatially variable inferred parameters are 0.38, 0.59, and 0.8, respectively. Spatially variable thresholds capture location-specific vegetation and climate characteristics and can be connected to biome-level water uptake strategies. Results demonstrate that satellite soil moisture probability distributions encode information, valuable to understanding biome-level ecohydrological adaptation and resistance to climate variability.Plain Language Summary Vegetation regulates a large fraction of the terrestrial water and carbon cycles as it adapts and responds to changing environmental conditions such as soil moisture availability, yet our ability to characterize diversity in vegetation soil water-use behavior at large scales is limited. In this study, we analyze satellite observations to estimate thresholds that are commonly used to approximate when vegetation extracts water from the soil. We show that the newly found values are more consistent with global patterns of soil moisture compared to constants found in the literature. Spatially variable plant water uptake thresholds reflect land cover and climate characteristics and can be connected to water-use strategies in biomes not dominated by trees.

show abstract

Moisture pulse-reserve in the soil-plant continuum observed across biomes

Cited by 96 publications

References 61 publications

Satellite‐Based Assessment of Land Surface Energy Partitioning–Soil Moisture Relationships and Effects of Confounding Variables

Satellite‐Based Assessment of Land Surface Energy Partitioning–Soil Moisture Relationships and Effects of Confounding Variables

Land‐Atmosphere Drivers of Landscape‐Scale Plant Water Content Loss

Plant Water Uptake Thresholds Inferred From Satellite Soil Moisture

Contact Info

Product

Resources

About