Differences in throughfall and net precipitation between soybean and transitional tropical forest in the southern Amazon, Brazil

The expansion of soybean cultivation into the Amazon in Brazil has potential hydrological effects at local to regional scales. To determine the impacts of soybean agriculture on hydrology, a comparison of net precipitation (throughfall, stemflow) in undisturbed tropical forest and soybean fields on the southern edge of the Amazon Basin in the state of Mato Grosso is needed. This study measured throughfall with troughs and stemflow with collar collectors during two rainy seasons. The results showed that in forest 91.6% of rainfall was collected as throughfall and 0.3% as stemflow, while in soybean fields with two-month old plants, 46.2% of rainfall was collected as throughfall and 9.0% as stemflow. Hence, interception of precipitation in soybean fields was far greater than in intact forests. Differences in throughfall, stemflow and net precipitation were found to be mainly associated with differences in plant structure and stem density in transitional forest and soybean cropland. Because rainfall interception in soybean fields is higher than previously believed and because both the area of cropland and the frequency of crop cycles (double cropping) are increasing rapidly, interception needs to be reconsidered in regional water balance models when consequences of land cover changes are analyzed in the Amazon soybean frontier region. Based on the continued expansion of soybean fields across the landscape and the finding that net precipitation is lower in soy agriculture, a reduction in water availability in the long term can be assumed.

► Interception of soybean is higher than forest interception.
► Differences in interception are due to plant structure and stem density.
► Stemflow in soybean contributes a high proportion to net precipitation.
► Stemflow in forest depends on bark roughness and the inclination of branches.
► Multi-cropping in Mato Grosso reduces water availability in the long term.