Integrated EMI-GPR surveys can support precision agriculture by monitoring and evaluating the effects of land uses and agricultural management

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Soil physical properties, thus soil hydrology, varies across the landscape and is altered following land use changes and different agricultural practices. Precision agriculture has become the key to increase the productivity and maintaining the sustainability of agriculture. Ground penetrating radar (GPR) and electromagnetic induction (EMI) methods can be used to assess the spatiotemporal variability of soil properties that will directly or indirectly effect on soil hydrology. For achieving this, soil's apparent electrical conductivity (ECa) and radar wave velocity (RWv) will be used through integrated EMI?GPR. However, estimating soil properties using traditional methods is expensive, labor-intensive, and time-consuming and provides point information only, which hinder any rapid response management activities. A potential way to acquire information at field-scale is by noninvasive mapping of easily recordable and reproducible physical variables such as ECa using the EMI and RWv using the GPR that correlate with relevant soil properties. The application of the integrated EMI-GPR methods for estimating the spatiotemporal variability soil properties are unique in boreal ecosystems and will aid in the development of new scientific knowledge for sustainable management of land and water resources. In this research, combined multi-coil and multi-frequency EMI sensors integrated with GPR using different frequencies will be correlated with fundamental soil properties. The proposed research will address key research gaps regarding the understanding of the effects of different land uses and agronomic practices for supporting precision agriculture. Development of protocols and guidelines for conducting ECa surveys using combined EMI sensors integrated with GPR will help to monitor the spatial variability of soil properties across different landscapes rapidly. Thus, correct soil, water and nutrient management decisions can be decided in supporting precision agriculture. Objectives of the research are to: (a) allocate ECa data to stable soil relatively stable soil properties and generate regression models using measured data; (b) obtain variable soil parameters to reveal hydrological processes such as water holding capacity, water repellency and infiltration capacity by means of time-lapse EMI; (c) evaluate the accuracy of two different EMI sensors and their exploration depths for predicting near-surface soil properties by integrating with GPR measurements and ground truth data; and (d) assess the effects of different land use and agronomic practices on soil properties based on the results from a-c. The integrated EMI-GPR-soil sample information will build the baseline for different management scenarios and concepts. The long-term goal is to generate high-resolution maps of key physical and hydraulic properties in order to assess the effects of different land uses and agronomic practices on soil hydrology, and thus on precision agriculture.