Impacts of Agricultural Expansion on Surface Runoff: A Case Study of a River Basin in the Brazilian Legal Amazon

This work presents an analysis of the Land Use and Land Cover (LULC) changes of a region in the Brazilian Legal Amazon, and an evaluation of their impacts on the surface runoff regime. This case study took place at the Suiá-Miçu River basin, located in the northeast region of Mato Grosso State. LULC maps were produced for the years 1973, 1984 and 2005 using remote sensing data. After analyzing the agricultural expansion in the study area, the Automated Geospatial Watershed Assessment Tool (AGWA) was applied in performing the surface runoff modeling for each of the analyzed years using the SCS curve number method. The results showed that by 1984, 13% of the natural vegetation had been replaced by pasture in this drainage basin. These changes were responsible for a 5.7% increase in the annual average surface runoff volume when compared with the baseline values of 1973. In 2005, the agricultural areas increased to around 40% of the drainage basin, being 28% occupied by pasture and 12% by crop fields. In this last scenario, the annual average surface runoff was 37% higher than in 1973

Methodology for the use of DSSAT models for precision agriculture decision support

A prototype decision support system (DSS) called Apollo was developed to assist researchers in using the Decision Support System for Agrotechnology Transfer (DSSAT) crop growth models to analyze precision farming datasets. Because the DSSAT models are written to simulate crop growth and development within a homogenous unit of land, the Apollo DSS has specialized functions to manage running the DSSAT models to simulate and analyze spatially variable land and management. The DSS has modules that allow the user to build model input files for spatial simulations across predefined management zones, calibrate the models to simulate historic spatial yield variability, validate the models for seasons not used for calibration, and estimate the crop response and environmental impacts of nitrogen, plant population, cultivar, and irrigation prescriptions. This paper details the functionality of Apollo, and presents the results of an example application

Multidimensional Tool for the Visualization of Spatiotemporal Variance in Soil Moisture

With water a precious resource, it is important to understand factors affecting soil moisture. Current research focuses on understanding this relationship; unfortunately these methods are specialized in their applications or overwhelm the user with information making correlations difficult to comprehend. Often, numerical results provide understanding of prominent correlations but miss subtle relationships, hindering subsequent decisions. This project aims to develop a decision making tool combining numerical analysis with visualization techniques to provide the user with the information to analyze soil moisture’s spatial and temporal variability. Current work has shown that self-organizing maps are effective for displaying comprehendible relationships to the user