H. R. da Rocha

Seasonal drought stress in the Amazon: Reconciling models and observations

[1] The Amazon Basin is crucial to global circulatory and carbon patterns due to the large areal extent and large flux magnitude. Biogeophysical models have had difficulty reproducing the annual cycle of net ecosystem exchange (NEE) of carbon in some regions of the Amazon, generally simulating uptake during the wet season and efflux during seasonal drought. In reality, the opposite occurs. Observational and modeling studies have identified several mechanisms that explain the observed annual cycle, including: (1) deep soil columns that can store large water amount, (2) the ability of deep roots to access moisture at depth when near-surface soil dries during annual drought, (3) movement of water in the soil via hydraulic redistribution, allowing for more efficient uptake of water during the wet season, and moistening of near-surface soil during the annual drought, and (4) photosynthetic response to elevated light levels as cloudiness decreases during the dry season. We incorporate these mechanisms into the third version of the Simple Biosphere model (SiB3) both singly and collectively, and confront the results with observations. For the forest to maintain function through seasonal drought, there must be sufficient water storage in the soil to sustain transpiration through the dry season in addition to the ability of the roots to access the stored water. We find that individually, none of these mechanisms by themselves produces a simulation of the annual cycle of NEE that matches the observed. When these mechanisms are combined into the model, NEE follows the general trend of the observations, showing efflux during the wet season and uptake during seasonal drought.

Seasonal soil water storage changes beneath central Amazonian rainforest and pasture

Evaporation and infiltration were compared for tropical rainforest and pasture, near to Manaus, Brazil from October 1990 to February 1992 using measurements of soil water storage over a depth of 2 m. The soil is a clayey oxisol of low water available capacity. In both of the dry seasons studied, the maximum change in soil water storage in the forest was 154 mm and in the pasture it was 131 and 112 mm. Similar behaviour of the soil water reservoir below forest and pasture in the wet season implied that differences in evaporation and drainage were small. In the dry season, soil water storage behaviour in the upper metre of the soil was similar but there were marked differences in the second metre. The pasture took up little water from below 1.5 m but the forest appeared to utilise all of the available water in the 2 m profile in both seasons. The water balance of the 2 m profile showed that the pasture evaporation rate was equal to that of the forest until storage had decreased 80 mm from the maximum. There was then a decline in pasture evaporation rate to 1.2 mm day−1 as the storage decreased by a further 50 mm. In contrast, the forest uptake rate remained above 3.5 mm day−1 until storage had decreased 140 mm from the maximum (within 15 mm of the extraction limit), before declining abruptly to less than 1.5 mm day−1. There was strong evidence that the forest was able to abstract water from depths greater than 3.6 m. Spatial variability of soil water storage was significantly greater beneath the pasture than beneath the forest, particularly following rainfall events in the dry season. This was largely the result of redistribution of rainfall as local surface runoff. There was no evidence of redistribution or runoff in the forest.

Atmosphere and hydrological controls of the evapotranspiration over a floodplain forest in the Bananal Island region, Amazonia

influenced the energy exchange. Soil moisture, which was substantially depleted during the dry season, and adaptative vegetation mechanisms such as leaf senescence contributed to limit the dry season ET. Strong drainage within permeable sandy soils helped to explain the soil moisture depletion. These results suggest that the Bananal flooding area shows a different pattern in relation to the upland Amazon forests, being more similar to the savanna strictu senso areas in central Brazil. For example, seasonal ET variation was not in phase with Rn; the wet season ETwas higher than the dry season ET; and the system stored only a tiny memory of the flooding period, being sensitive to extended drought periods.

A biophysical model of Sugarcane growth

Scientists predict that global agricultural lands will expand over the next few decades due to increasing demands for food production and an exponential increase in crop‐based biofuel production. These changes in land use will greatly impact biogeochemical and biogeophysical cycles across the globe. It is therefore important to develop models that can accurately simulate the interactions between the atmosphere and important crops. In this study, we develop and validate a new process‐based sugarcane model (included as a module within the Agro‐IBIS dynamic agro‐ecosystem model) which can be applied at multiple spatial scales. At site level, the model systematically under/overestimated the daily sensible/latent heat flux (by −10.5% and 14.8%, H and λE, respectively) when compared against the micrometeorological observations from southeast Brazil. The model underestimated ET (relative bias between −10.1% and –12.5%) when compared against an agro‐meteorological field experiment from northeast Australia. At the regional level, the model accurately simulated average yield for the four largest mesoregions (clusters of municipalities) in the state of São Paulo, Brazil, over a period of 16 years, with a yield relative bias of −0.68% to 1.08%. Finally, the simulated annual average sugarcane yield over 31 years for the state of Louisiana (US) had a low relative bias (−2.67%), but exhibited a lower interannual variability than the observed yields.