No abstract

Assessing the impact/adaptation of human activities on/to climate change is a key issue, especially in the tropics that concentrate major anthropogenic dynamics such as deforestation and nearly two-thirds of the planetary rainfall. However, this task is often made tough because human activities such as agricultural dynamics are usually analysed at local or regional scale whereas climate related studies are led at large to global scales due to a lack of reliable data, especially in the tropics. In this article we argue that the increased spatial resolution of remote sensing-based rainfall estimates enables assessing the spatiotemporal variability of rainfall regimes at regional and local scales, thus allowing fine analysis of the interactions with human activities. We processed Tropical Rainfall Measuring Mission (TRMM) 3B42 daily rainfall estimates over the state of Mato Grosso (southern Brazilian Amazon) for the 1998-2012 study period in order to compute rainfall metrics such as annual rainfall and duration, onset and end dates of the rainy season based on the Anomalous Accumulation methodology (at a 0.25◦ spatial resolution). We then crossed these metrics with agricultural maps (produced at a 250m spatial resolution) and proved that the adoption of intensive agricultural practices such as double cropping systems is partly the result of a strategy to adapt practices to local climatic conditions. Finally, we discuss how such results raise important issues regarding the sustainability of the agricultural development model in the Southern Amazon