Estimating water infiltration rate in oxisols under pasture and agriculture management in the Brazilian Savanna with support of a Drone-RGB onboard sensor

Abstract

Methods for evaluating physical water data are being increasingly supported by modern and practical tools that have become indispensable for field surveys. Among these tools, unmanned aerial vehicles (UAV) equipped with optical, multispectral, and thermal sensors allow carrying out interventions, monitoring, and strategic data collection with significant cost and time reductions. In this research we used a fixed wing UAV (Swinglet CAM, Sensefly) with RGB camera for creating a precise Digital Terrain Model (DTM) aiming to support an assessment of soil water infiltration in areas under pasture and agricultural management, using the Kostiakov model with concentric rings. Thus, we produced a centimetric-resolution DTM for identifying geomorphological features intrinsically linked to the soil water dynamics and and the accurate insertion of the concentric rings in the slopes. Water velocity and infiltration rates were estimated from descriptive statistics of the data obtained with the Kostiakov model. In this way, the application of the potential equation (Kostiakov) made it possible to mathematically construct the determinants of accumulated infiltration and instantaneous velocity, which can then be replicated and updated at various times, changing only the input data that were logarithmized. The results showed a higher infiltration (54%) in the pasture area, while the unmanned aerial vehicle was considered as an essential tool for obtaining a detailed synoptic representation of the natural and anthropic landscape.