Se utilizó el modelo regionalizado de lluvia Regionalisierte Niederschlage (Regnie) para interpolar la lluvia y temperatura media del aire de las regiones Andina, Caribe y Pacífica de Colombia. Este modelo integró los datos de la pendiente y exposición del terreno obtenidos del modelo digital de elevación, así como los promedios climatológicos de 1440 series de precipitación y 258 series de temperatura registradas en igual número de estaciones meteorológicas de superficie para cada variable. Se establecieron los modelos de regresión lineal múltiple de la precipitación media anual y temperatura media anual del aire, además se utilizaron herramientas de geoprocesamiento para la generación de las superficies interpoladas. Los estadísticos de prueba de las superficies Regnie fueron similares a los obtenidos con interpolaciones con los métodos Spline e IDW para precipitación (coeficiente de determinación 0.81 y error medio de 55.6 mm) y mejores para la temperatura media (coeficiente de determinación 0.99 y error medio de 0.02°C).

This study represents the first nationwide survey regarding the distribution of Cd content in cacao-growing soils in Colombia. The soil Cd distribution was analyzed using a cold/hotspots model. Moreover, both descriptive and predictive analytical tools were used to assess the key factors regulating the Cd concentration, considering Cd content and eight soil variables in the cacao systems. A critical discussion was performed in four main cacao-growing districts. Our results suggest that the performance of a model using all the variables will always be superior to the one using Zn alone. The analyzed variables featured an appropriate predictive performance, nonetheless, that performance has to be improved to develop a prediction method that might be used nationwide. Results from the fitted graphical models showed that the largest associations (as measured by the partial correlation coefficients) were those between Cd and Zn. Ca had the second-largest partial correlation with Cd and its predictive performance ranked second. Interestingly, it was found that there was a high variability in the factors correlated with Cd in cacao growing soils at a national level. Therefore, this study constitutes a baseline for the forthcoming studies in the country and should be reinforced with an analysis of cadmium content in cacao beans.

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Abstract. Spatial soil databases can help model complex phenomena in which soils are decisive, for example, evaluating agricultural potential or estimating carbon storage capacity. The Soil Information System for Latin America and the Caribbean, SISLAC, is a regional initiative promoted by the FAO's South American Soil Partnership to contribute to the sustainable management of soil. SISLAC includes data coming from 49,084 soil profiles distributed unevenly across the continent, making it the region's largest soil database. However, some problems hinder its usages, such as the quality of the data and its high dimensionality. The objective of this research is twofold. First, to evaluate the quality of SISLAC and its data values and generate a new, improved version that meets the minimum quality requirements to be used by different interests or practical applications. Second, to demonstrate the potential of improved soil profile databases to generate more accurate information on soil properties, by conducting a case study to estimate the spatial variability of the percentage of soil organic carbon using 192 profiles in a 1473 km2 region located in the department of Valle del Cauca, Colombia. The findings show that 15 percent of the existing soil profiles had an inaccurate description of the diagnostic horizons. Further correction of an 4.5 additional percent of existing inconsistencies improved overall data quality. The improved database consists of 41,691 profiles and is available for public use at https://doi.org/10.5281/zenodo.6540710 (Díaz-Guadarrama, S. & Guevara, M., 2022). The updated profiles were segmented using algorithms for quantitative pedology to estimate the spatial variability. We generated segments one centimeter thick along with each soil profile data, then the values of these segments were adjusted using a spline-type function to enhance vertical continuity and reliability. Vertical variability was estimated up to 150 cm in-depth, while ordinary kriging predicts horizontal variability at three depth intervals, 0 to 5, 5 to 15, and 15 to 30 cm, at 250 m-spatial resolution, following the standards of the GlobalSoilMap project. Finally, the leave-one-out cross-validation provides information for evaluating the kriging model performance, obtaining values for the RMSE index between 1.77 % and 1.79 % and the R2 index greater than 0.5. The results show the usability of SISLAC database to generate spatial information on soil properties and suggest further efforts to collect a more significant amount of data to guide sustainable soil management.

The agricultural sector in Colombia and especially, small-scale agriculture subsector in the Colombian Caribbean has been very vulnerable to the negative impacts of climate variability in part due to the poor existence and lack of access to agro-climatic information. The objective was to build a methodology for agroclimatic zoning for crops growing in Colombian dry Caribbean. To achieve this goal, a case study of tomato crop growing in the municipality of Repelon (Atlantico, Colombia) was selected. The methodology was based in the combination of crop-specific soil suitability assessment and the monthly prob ability of a humidity condition occurrence in the soil for tomato production under water deficit. Probability was constructed through water balances generated from the Palmer drought severity index, calculated for each month of crop production cycle during the 1980 to 2011 series. The resulting maps show defined areas called Productive Niches with lower limitations per soil and low probabilities of soil water deficit in the growth of tomato crop in the municipality. The methodology can be used to delineate areas suitable for planting tomato or other crops in climate variability events in the dry Caribbean region of Colombia.

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Current available soil information allows building baselines to improve research, such as sustainable resource management; however, its use requires analysis of accuracy and precision that describes specific variables on local and global scales. Therefore, this study evaluated differences in the spatial distribution of water retention capacity (WRC) of the soil at a depth of 0.3 m, calculated from local general soil surveys and the global gridded soil information system (SoilGrids), using detailed or semi-detailed soil surveys as a reference, in two regions of Colombia (A and B). The qualitative and statistical analyses evaluated differences in WRC surfaces generated by the information sources. Neither information sources described WRC accurately, achieving correlations between-0.15 and 0.49 and average absolute errors between 9.65 and 19.52 mm for zones A and B, respectively. However, studies on the local scale remain within the ranges observed in the most detailed local studies. The use of products on the global scale is subject to regional analyses; nevertheless, they can be included as a covariate in digital soil mapping studies on more detailed scales.