Soil moisture assessed by digital mapping techniques and its field validation

Abstract

Digital techniques and tools can assist not only in the prediction of soil properties, such as soil moisture, but also in planning the use and management of areas for agriculture and, or, environmental purposes. In this sense, this work aimed to study wetness indexes methods, defining the spatial resolution and selecting the estimation method that best correlates with water content data measured in the field, evaluating even moisture at different soil depths and seasons. This study was developed in a landscape with strongly undulated relief and covered with Nitosols at the summit and upper middle third, and Argisols at the low middle third, ranging in altitude from 845 to 890 m, located in the southern state of Minas Gerais, Brazil. It were performed analyses of Pearson linear correlation between soil moisture determined in the field, at depths of 10, 20, 30, 40, 60 and 100 cm and the water storage in 0-100 cm depth, and the topographic and SAGA wetness indexes, TWI and SWI, respectively, obtained from digital elevation models at different spatial resolutions. In most studied conditions, the TWI with resolution of 10 m provided better results, particularly for the dry season. In this study, only the depth of 100 cm resulted in a significant and positive correlation, suggesting that the moisture levels are suitable for water dynamic studies in the subsurface, assisting in studies of hydrological dynamics and planning the soil use and management, especially for perennial plants with deeper root systems.Index terms: Terrain attributes, soil water content determination, relief, water dynamics. RESUMOTécnicas e ferramentas digitais podem auxiliar na predição de propriedades do solo, a exemplo da umidade do solo, auxiliando no planejamento do uso e manejo de áreas com fins agrícolas e/ou ambientais. Nesse sentido, objetivou-se estudar índices de umidade, definir a resolução espacial e selecionar o método de estimativa que melhor se correlaciona com dados de teor de água medidos em campo, avaliando-se, ainda, a umidade em diferentes profundidades do solo e épocas do ano. Este estudo foi desenvolvido em uma paisagem com relevo forte ondulado e recoberta por Nitossolo no topo e no terço médio superior, e Argissolo no terço médio inferior, em altitude variando de 845 a 890 m, no sul do Estado de Minas Gerais, Brasil. Foram realizadas análises de correlação linear de Pearson entre a umidade do solo determinada em campo, nas profundidades de 10, 20, 30, 40, 60 e 100 cm além do armazenamento de água na camada 0-100 cm, e os índices de umidade TWI (índice topográfico de umidade) e SWI (índice de umidade SAGA) obtidos a partir de modelos digitais de elevação em diferentes resoluções espaciais. Na maioria das situações estudadas, o índice TWI com resolução de 10 m condicionou melhores resultados, particularmente no período seco do ano. Neste estudo, apenas para a profundidade de 100 cm houve correlação positiva e significativa, sugerindo que os índices de umidade são indicados para estudos de dinâmica da água em subsupe...

Soil Moisture Analysis by Means of Multispectral Images According to Land Use and Spatial Resolution on Andosols in the Colombian Andes

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Approaches for evaluation of relief morphometric characteristics influence on spatial distribution of moisture in the soils of steppe part of Crimea

“…Quite a lot of scientific papers have been devoted to the study of soil moisture reserves amount, especially in connection with the influence of hydrological conditions of land use territory, preceding crops, crop cultivation technologies on the structure and hydrophysical properties of the soil [1][2][3][4][5]. To assess the effect of micro-relief scientists use both topographic surveys [6][7][8] and DEM (Digital Elevation Model) together with the calculated soil moisture indexes [9] and the balance method using hydrological models [10,11] in their research. Data on the amount of soil moisture reserves are the key information for efficient agricultural production in dry conditions of the Crimean Peninsula.…”

DTM Generation Through Uav Survey With a Fisheye Camera on a Vineyard

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