Core Ideas Clay content, soil organic matter, slope, NDVI, and topographic wetness index delineate management zones. Hard and fuzzy clustering analysis resulted in divisions of two and three areas. Wavelet analysis revealed variability in temporal soil water dynamics between zones. Due to spatial variability of soil genesis, topography, and resulting soil properties in farmers' fields, soil and crop processes vary in space and time. Therefore, optimum rates and timing of resource applications, such as nutrients and irrigation water, may vary as well. It remains a challenge to quantify the spatial variability of a field and to identify effective ways to manage fields in a site‐specific manner. The objective of this study was to delineate management zones within a farmer's field based on relatively easily obtainable information that is statistically integrated. Moreover, soil water temporal dynamics should be evaluated regarding their spatial differences in different zones. The set of direct and indirect observations included clay and silt content, apparent electrical conductivity, soil chemical properties (pH; organic matter; and total N, P, K, Ca, Mg, and Zn), satellite‐based normalized difference vegetation index (NDVI), and lidar‐based topographic variables in a western Kentucky field. Several key variables and their capability to describe spatial crop yield variability were identified by using principal component analysis: soil clay content, slope, soil organic matter content, topographic wetness index, and NDVI. Two types of cluster analysis were applied to delineate management zones. The cluster analyses revealed that two to three zones was the optimal number of classes based on different criteria. Delineated zones were evaluated and revealed significant differences in corn (Zea mays L.) yield and temporally different soil moisture dynamics. The results demonstrate the ability of the proposed procedure to delineate a farmer's field into zones based on spatially varying soil and crop properties that should be considered for irrigation management.

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Over 51,000 ha of low yield tobacco were harvested in the year 2000/2001 in Cuba. Since the Union of Tobacco Enterprises plans to increase this area to 72,000 ha of tobacco in 2005, where most of these new areas will be irrigated with surface irrigation, then the introduction of new irrigation technologies is an important premise to achieve high yield productions. Because of this, some field evaluations of furrow irrigation with continuous and intermittent flow applications were carried out on a plot belonging to the «Cítricos Ciego de Avila» enterprise, in the Ceballos municipality of the Ciego de Avila province, Cuba. The objective of these field evaluations was to compare the hydraulic behavior of different water management strategies of furrow irrigation for the cultivation of black tobacco in a Ferralsol soil, using a surface irrigation simulation model. The intermittent application of water considerably reduced the infiltration capacity of the soil. Likewise, the influence of soil water content and furrow wetted perimeter on infiltration parameters was corroborated. The surge flow furrow irrigation with variable time cycles increased the application efficiency by more than six fold, and the water volume was reduced by more than 80% compared to continuous irrigation. The largest rises in distribution uniformity and reductions in percolation losses were obtained with a furrow length of 200 m and a discharge of 1 L s -1 , respectively. Key words: infiltration, water management, performance indices. ResumenComparación entre el riego por pulsos y el riego por surcos convencional para el cultivo del tabaco negro tapado en un suelo Ferralsol En la campaña 2000/2001 se cosecharon en Cuba alrededor de 51.000 ha de tabaco con un rendimiento medio relativamente bajo. Si se considera que para el año 2005 la Unión de Empresas del Tabaco prevé crecer hasta 72.600 ha, en donde la mayor parte de esta superficie será regada con métodos superficiales, entonces la introducción de nuevas tecnologías de riego por superficie es una premisa necesaria para lograr los incrementos previstos en los volúmenes de producción del tabaco. Teniendo en cuenta lo anterior, se realizaron evaluaciones de campo de riego por surcos con flujo continuo e intermitente en áreas de la empresa «Cítricos de Ciego de Avila», ubicada en el municipio Ceballos de la provincia de Ciego de Ávila, Cuba. El objetivo de las evaluaciones fue comparar el comportamiento hidráulico de diferentes estrategias de manejo del riego por surcos para el cultivo del tabaco negro tapado en un suelo Ferralsol. Se ejecutaron experimentos numéricos con un modelo matemático de simulación a fin de determinar las estrategias óptimas de manejo del riego por pulsos y comparar sus índices de idoneidad con los del riego por surcos convencional. La aplicación intermitente del agua en el riego por surcos redujo considerablemente la capacidad de infiltración del suelo. Asimismo, se constató la influencia que ejerce el contenido de agua en el suelo y el perímetro mojado del surco...

Core Ideas Surface clay content was derived through a combination of clay measurements and a proximal sensor. Apparent electrical conductivity (ECa) supported reliable clay content estimation. Predictions of clay coregionalized with ECa performed well, even for one soil sample per two hectares. Understanding the spatial variability of soil texture within field soils is important due to its influence on a large number of soil and plant related processes and for site‐specific application of inputs that are crucial to crop production. It remains a problem to obtain a reliable clay content map based on a limited number of sampling locations. The objective of this study was to identify spatial variability of soil clay content and the behavior of the estimation result for different spatial resolutions of measured clay content (0–20 cm depth) in combination with a coregionalization approach using apparent electrical conductivity (ECa). In a silty loam soil, soil clay content was measured at 96 points in a 50‐m by 50‐m grid within an agricultural field. ECa was measured using a contact sensor Veris 3150. Data were analyzed with ordinary kriging and cokriging while using ECa at a shallow depth. We analyzed different sampling scenarios based on clay subsamples of 48, 24, and 12 data points distributed over the 27‐ha field. In all scenarios investigated here, the RMSE stayed in the range of 3 to 4% by using different validations, with cokriging performing constantly better than ordinary kriging. Clay content maps estimated with cokriging maintained a satisfactory precision when the sampling density was reduced to one sample per two hectares, a result that leads to the conclusion that electrical conductivity in combination with spatial coregionalization demonstrated to be a promising tool to estimate the spatial variation of clay content even at a low clay sampling density.

Agricultural soils serve as crucial storage sites for soil organic carbon (SOC). Their appropriate management is pivotal for mitigating climate change. Continuous monitoring is imperative to evaluate spatial and temporal changes in SOC within agricultural fields. In-field datasets of Vis-NIR soil spectra were collected on a long-term experimental site using an on-the-go spectrophotometer. Data processing for continuous SOC prediction involves a two-step modeling approach. In Step 1, a partial least square (PLSR) regression model is trained to establish a relationship between the SOC content and spectral information, including spectral preprocessing. In Step 2, the predicted SOC content obtained from the PLSR models is interpolated using ordinary kriging. Among the tested spectral preprocessing techniques and semivariogram models, Savitzky–Golay and the Gap-Segment derivative preprocessing along with a Gaussian semivariogram model, yielded the best performance resulting in a root mean square error of 1.24 and 1.26 g kg−1. A striping effect due to the transect-based data collection was addressed by testing the effectiveness of extending the spatial separation distance, employing data aggregation, and defining the distribution based on treatment plots using block kriging. Overall, the results highlight the high potential of on-the-go spectral Vis-NIR data for field-scale spatial-temporal monitoring of SOC.