The Budyko curve is an empirical relation among evapotranspiration, potential evapotranspiration and precipitation observed across a variety of landscapes and biomes around the world. Using data from more than three hundred catchments and a simple water balance model, the Budyko curve is inverted to explore the ecohydrological controls of the soil water balance. Comparing the results across catchments reveals that aboveground transpiration efficiency and belowground rooting structure have adapted to the dryness index and the phase lag between peak seasonal radiation and precipitation. The vertical and/or lateral extent of the rooting zone exhibits a maximum in semi‐arid catchments or when peak radiation and precipitation are out of phase. This demonstrates plant strategies in Mediterranean climates in order to cope with water stress: the deeper rooting structure buffers the phase difference between precipitation and radiation. Results from this study can be used to constrain land‐surface parameterizations in ungauged basins or general circulation models.

Root biomass, root production and lifespan, and root-mycorrhizal interactions govern soil carbon fluxes and resource uptake and are critical components of terrestrial models. However, limitations in data and confusions over terminology, together with a strong dependence on a small set of conceptual frameworks, have limited the exploration of root function in terrestrial models. We review the key root processes of interest to both field ecologists and modelers including root classification, production, turnover, biomass, resource uptake, and depth distribution to ask (1) what are contemporary approaches for modeling roots in terrestrial models? and (2) can these approaches be improved via recent advancements in field research methods? We isolate several emerging themes that are ready for collaboration among field scientists and modelers: (1) alternatives to size-class based root classifications based on function and the inclusion of fungal symbioses, (2) dynamic root allocation and phenology as a function of root environment, rather than leaf demand alone, (3) improved understanding of the treatment of root turnover in models, including the role of root tissue chemistry on root lifespan, (4) better estimates of root stocks across sites and species to parameterize or validate models, and (5) dynamic interplay among rooting depth, resource availability and resource uptake. Greater attention to model parameterization and structural representation of roots will lead to greater appreciation for belowground processes in terrestrial models and improve estimates of ecosystem resilience to global change drivers.

Abstract. This paper presents the development of a rainfalltriggered landslide module within an existing physically based spatially distributed ecohydrologic model. The model, tRIBS-VEGGIE (Triangulated Irregular Networks-based Real-time Integrated Basin Simulator and Vegetation Generator for Interactive Evolution), is capable of a sophisticated description of many hydrological processes; in particular, the soil moisture dynamics are resolved at a temporal and spatial resolution required to examine the triggering mechanisms of rainfall-induced landslides. The validity of the tRIBS-VEGGIE model to a tropical environment is shown with an evaluation of its performance against direct observations made within the study area of Luquillo Forest.The newly developed landslide module builds upon the previous version of the tRIBS landslide component. This new module utilizes a numerical solution to the Richards' equation (present in tRIBS-VEGGIE but not in tRIBS), which better represents the time evolution of soil moisture transport through the soil column. Moreover, the new landslide module utilizes an extended formulation of the factor of safety (FS) to correctly quantify the role of matric suction in slope stability and to account for unsaturated conditions in the evaluation of FS.The new modeling framework couples the capabilities of the detailed hydrologic model to describe soil moisture dynamics with the infinite slope model, creating a powerful tool for the assessment of rainfall-triggered landslide risk.

[1] A simple method for estimating thermal inertia using daily amplitude of surface soil heat flux and temperature is proposed. Based on an analytical solution of the diffusion equation where the soil temperature is idealized as a sinusoidal function, the thermal inertia is expressed as a proportional coefficient in a linear equation relating the amplitudes of surface soil (ground) heat flux and temperature. Tests of the proposed method demonstrate that this simple method is potentially useful in the Earth and extra-terrestrial remote sensing.