Gabriele Manoli

The influence of water table depth and the free atmospheric state on convective rainfall predisposition

A mechanistic model for the soil-plant system is coupled to a conventional slab representation of the atmospheric boundary layer (ABL) to explore the role of groundwater table (WT) variations and free atmospheric (FA) states on convective rainfall predisposition (CRP) at a Loblolly pine plantation site situated in the lower coastal plain of North Carolina. Predisposition is quantified using the crossing between modeled lifting condensation level (LCL) and convectively grown ABL depth. The LCL-ABL depth crossing is necessary for air saturation but not sufficient for cloud formation and subsequent convective rainfall occurrence. However, such crossing forms the main template for which all subsequent dynamical processes regulating the formation (or suppression) of convective rainfall operate on. If the feedback between surface fluxes and FA conditions is neglected, a reduction in latent heat flux associated with reduced WT levels is shown to enhance the ABL-LCL crossing probability. When the soil-plant system is fully coupled with ABL dynamics thereby allowing feedback with ABL temperature and humidity, FA states remain the leading control on CRP. However, vegetation water stress plays a role in controlling ABL-LCL crossing when the humidity supply by the FA is within an intermediate range of values. When FA humidity supply is low, cloud formation is suppressed independent of surface latent heat flux. Similarly, when FA moisture supply is high, cloud formation can occur independent of surface latent heat flux. In an intermediate regime of FA moisture supply, the surface latent heat flux controlled by soil water availability can supplement (or suppress) the necessary water vapor leading to reduced LCL and subsequent ABL-LCL crossing. It is shown that this intermediate state corresponds to FA values around the mode in observed humidity lapse rates γw (between −2.5 × 10−6 and −1.5 × 10−6 kg kg−1m−1), suggesting that vegetation water uptake may be controlling CRP at the study site.

An iterative particle filter approach for coupled hydro-geophysical inversion of a controlled infiltration experiment

The modeling of unsaturated groundwater flow is affected by a high degree of uncertainty related to both measurement and model errors. Geophysical methods such as Electrical Resistivity Tomography (ERT) can provide useful indirect information on the hydrological processes occurring in the vadose zone. In this paper, we propose and test an iterated particle filter method to solve the coupled hydrogeophysical inverse problem. We focus on an infiltration test monitored by time-lapse ERT and modeled using Richards equation. The goal is to identify hydrological model parameters from ERT electrical potential measurements. Traditional uncoupled inversion relies on the solution of two sequential inverse problems, the first one applied to the ERT measurements, the second one to Richards equation. This approach does not ensure an accurate quantitative description of the physical state, typically violating mass balance. To avoid one of these two inversions and incorporate in the process more physical simulation constraints, we cast the problem within the framework of a SIR (Sequential Importance Resampling) data assimilation approach that uses a Richards equation solver to model the hydrological dynamics and a forward ERT simulator combined with Archies law to serve as measurement model. ERT observations are then used to update the state of the system as well as to estimate the model parameters and their posterior distribution. The limitations of the traditional sequential Bayesian approach are investigated and an innovative iterative approach is proposed to estimate the model parameters with high accuracy. The numerical properties of the developed algorithm are verified on both homogeneous and heterogeneous synthetic test cases based on a real-world field experiment.

The effect of plant water storage on water fluxes within the coupled soil–plant system

In addition to buffering plants from water stress during severe droughts, plant water storage (PWS) alters many features of the spatio-temporal dynamics of water movement in the soil-plant system. How PWS impacts water dynamics and drought resilience is explored using a multi-layer porous media model. The model numerically resolves soil-plant hydrodynamics by coupling them to leaf-level gas exchange and soil-root interfacial layers. Novel features of the model are the considerations of a coordinated relationship between stomatal aperture variation and whole-system hydraulics and of the effects of PWS and nocturnal transpiration (Fe,night) on hydraulic redistribution (HR) in the soil. The model results suggest that daytime PWS usage and Fe,night generate a residual water potential gradient (Δψp,night) along the plant vascular system overnight. This Δψp,night represents a non-negligible competing sink strength that diminishes the significance of HR. Considering the co-occurrence of PWS usage and HR during a single extended dry-down, a wide range of plant attributes and environmental/soil conditions selected to enhance or suppress plant drought resilience is discussed. When compared with HR, model calculations suggest that increased root water influx into plant conducting-tissues overnight maintains a more favorable water status at the leaf, thereby delaying the onset of drought stress.

Matching ecohydrological processes and scales of banded vegetation patterns in semiarid catchments

While the claim that water-carbon interactions result in spatially coherent vegetation patterning is rarely disputed in many arid and semi-arid regions, the significance of the detailed water pathways and other high frequency variability remain an open question. How the short temporal scale meteorological fluctuations form the long term spatial variability of available soil water in complex terrains due to the various hydrological, land surface and vegetation dynamic feedbacks, frames the scope of the work here. Knowledge of the detailed mechanistic feedbacks between soil, plants and the atmosphere will lead to advances in our understanding of plant water availability in arid and semi-arid ecosystems and will provide insights for future model development concerning vegetation pattern formation. In this study, quantitative estimates of water fluxes and vegetation productivity are provided for a semi-arid ecosystem with established vegetation bands on hillslopes using numerical simulations. A state-of-the-science process based ecohydrological model is used, which resolves hydrological and plant physiological processes at the relevant space and time scales, for relatively small periods (e.g. decades) of mature ecosystems (i.e. spatially static vegetation distribution). To unfold the mechanisms that shape the spatial distribution of soil moisture, plant productivity and the relevant surface/subsurface and atmospheric water fluxes, idealized hillslope numerical experiments are constructed, where the effects of soil-type, slope steepness and overland flow accumulation area are quantified. Those mechanisms are also simulated in the presence of complex topography features on landscapes. The main results are: (a) Short temporal scale meteorological variability and accurate representation of the scales at which each ecohydrological process operates are crucial for the estimation of the spatial variability of soil water availability to the plant root zone; (b) Water fluxes such as evapotranspiration, infiltration, runoff-runon and subsurface soil water movement have a dynamic short temporal scale behavior that determines the long term spatial organization of plant soil water availability in ecosystems with established vegetation patterns; (c) Hypotheses concerning the hydrological responses that can lead to vegetation pattern formation have to accommodate realistic and physically based representations of the fast dynamics of key ecohydrological fluxes.

Delay-induced rebounds in CO2 emissions and critical time-scales to meet global warming targets: DELAY-INDUCED REBOUNDS AND CRITICAL TIMESCALES FOR GLOBAL WARMING TARGETS

While climate science debates are focused on the attainment of peak anthropogenic CO2 emissions and policy tools to reduce peak temperatures, the human-energy-climate system can hold “rebound” surprises beyond this peak. Following the second industrial revolution, global per capita CO2 emissions (cc) experienced a punctuated growth of about 100% every 60 years, mainly attributable to technological development and its global spread. A model of the human-energy-climate system capable of reproducing past punctuated dynamics shows that rebounds in global CO2 emissions emerge due to delays intrinsic to the diffusion of innovations. Such intrinsic delays in the adoption and spread of low-carbon emitting technologies, together with projected population growth, upset the warming target set by the Paris Agreement. To avoid rebounds and their negative climate effects, model calculations show that the diffusion of climate-friendly technologies must occur with lags one-order of magnitude shorter (i.e., ∼6 years) than the characteristic timescale of past punctuated growth in cc. Radically new strategies to globally implement the technological advances at unprecedented rates are needed if the current emission goals are to be achieved.