Abstract
Abstract. There is an increased demand for quantitative high-resolution soil maps that enable within-field management. Commonly available soil maps are generally not suited for this purpose, but digital soil mapping and geophysical methods in particular allow soil information to be obtained with an unprecedented level of detail. However, it is often difficult to quantify the added value of such high-resolution soil information for agricultural management and agro-ecosystem modelling. In this study, a detailed geophysics-based soil map was compared to two commonly available general-purpose soil maps. In particular, the three maps were used as input for crop growth models to simulate leaf area index (LAI) of five crops for an area of ∼ 1 km2. The simulated development of LAI for the five crops was evaluated using LAI obtained from multispectral satellite images. Overall, it was found that the geophysics-based soil map provided better LAI predictions than the two general-purpose soil maps in terms of correlation coefficient R2, model efficiency (ME), and root mean square error (RMSE). Improved performance was most apparent in the case of prolonged periods of drought and was strongly related to the combination of soil characteristics and crop type.
Highlights
Detailed soil information on areas within a single field that require different treatment, so-called management zones, is key in agricultural management (King et al, 2005; Stafford et al, 1996; Sylvester-Bradley et al, 1999)
In the geophysics-based soil map, this subdivision is based on the measured apparent electrical conductivity (ECa) data (Brogi et al, 2019), whereas the delineation in the commonly available soil maps was mainly based on coarse soil augering and topography since this limit approximately coincides with the top of the slope that divides these two sub-areas
Agro-ecosystem simulations were performed on a 1 km × 1 km agricultural area by using information from three different soil maps: (i) a high-resolution geophysicsbased soil map, (ii) a 1 : 5000 regional soil map, and (iii) a soil taxation map
Summary
Detailed soil information on areas within a single field that require different treatment, so-called management zones, is key in agricultural management (King et al, 2005; Stafford et al, 1996; Sylvester-Bradley et al, 1999). Management zones are generally characterized by soils with relatively uniform characteristics (i.e. a soil unit) These soil units can potentially be obtained from a variety of commonly available thematic maps that provide spatially distributed soil information (e.g. geological, soil, and yield potential maps). These products are often insufficiently detailed (Franzen et al, 2002; Nawar et al, 2017; Robert, 1993) since they are discretized in relatively large polygons and provide qualitative information that might differ from the inputs that are useful for farmers (Krüger et al, 2013; Söderström et al, 2016). Maps with higher sampling resolution such as the German soil taxation maps that were surveyed on a 50 m grid (four points per hectare) often do not provide improved results
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