The 2015-16 El Nino had a record-breaking impact on the Amazon rainforest, with the region experiencing extremes of heat and drought. We study the impact of the 2015 drought on the water dynamics in a central Amazonian tropical rainforest using field observations of soil moisture, sap flow, and net radiation among other micrometeorological variables collected at the BR-Ma2 tower (Manaus - ZF2 K34 tower) site. We use these data to look for quantitative and mechanistic relationships between soil moisture, plant transpiration, and precipitation over tropical rainforest. We further study the physiological drivers that control plant transpiration during the drought and in a normal year. Here we present quantifications of precipitation, soil water usage, and plant transpiration during and after the 2015 drought, and characterizations of the impacts of the 2015 drought on ecosystem water processes such as plant transpiration and soil water usage.

A novel non-gradient model is formulated for estimating gas fluxes using single-level time-series data of near-surface gas concentration over land surfaces. When the vertical turbulent transport process in the atmospheric surface layer is described by a one-dimensional diffusion equation, a gas flux is expressed as a weighted integral of the time-history of single-level gas concentration. The eddy-diffusivity may be parameterized as a function of sensible heat flux based on the Monin-Obukhov similarity theory without explicit dependence on wind speed and surface roughness. Sensible heat flux may be estimated from net radiation and surface temperature using the maximum entropy production model. Case studies at six sites with diverse vegetation covers, geographic and climatic conditions at sub-daily scale demonstrate the model’s ability to simulate diurnal variations of water vapor and CO2 fluxes using fewer inputs than other models. Good performance of the model at seasonal scale suggests that the proposed model is a promising tool for the assessment of annual water and carbon budgets over vegetated land surfaces.