Natural Resources and Sustainable Development (Nov 2019)
EVALUATION OF SOIL WATER MANAGEMENT PROPERTIES BASED ON LIDAR DATA AND SOIL ANALYSES, AT FARM LEVEL
Abstract
Rapid weather fluctuations with an increasing demand for resource use impacts crop production sustainability leading to severe use of land and water resources. Laboratory analysis and technological improvements, such as remote sensing, generate new information and knowledge, to ease the visibility of effects by agricultural practices, bringing new opportunities to better use resources and improve farming sustainability and water management practices. Irrigation use and assessment are important to assure the sustainability; planning and modelling based on soil-plant economy relationship by the use of technological innovation, as Lidar imagery, enhancing the precision to large scale knowledge gained a plot-farm level. Agronomics, agriculture engineers, management technologies aim to reduce non-productive water use in agriculture. Finding the correlation between soil water retention and physical parameters contributes to irrigation management plant, therefore, reducing water use, cutting costs for agri-food production and reducing environmental impact. Soil sampling is performed in two depth and analysis of soil physical and water retention parameters with the correlation of LiDAR survey proving in-depth on-field information. Silt-loamy texture makes a good texture, water retention capacity. A decrease of silt content in the upper layer (6.4 %), an increase of sand and clay (7 % and 28 %) respectively. Conventional soil cultivation made an impact on the soil upper layer. Soil water retention did not show the major fluctuation of two layers regarding pF values. LiDAR results shown the area is not susceptible to erosion, 68 % is in the 1st slope category and 28 % in the 2nd. LiDAR, clear understanding and visualisation of site laboratory data for different. The field is well drained, vegetation period and cultivation could require scheduled, separated irrigation on land based on DEM and runoff lines helping to improve irrigation planning and water use efficiency. Demonstration the benefits of using high accuracy remote sensing LiDAR data, preventing water logging, misuse, and improve irrigation management and shows good examples to use in large scale to ease comprehensive understating of data.
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