Methoden vergelijken

	Kationenuitwisselingscapaciteit	Digitale Bodemkartering	Bodemvochtcurve
Vakgebied	Agronomie	Agronomie	Agronomie
Familie	Process / pipeline	Process / pipeline	Process / pipeline
Jaar van ontstaan	1920-1982	Late 1990s – early 2000s (formalised ~2003)	1956-1980
Grondlegger	Georg Wiegner, Heinrich Rotter, Melvin E. Sumner	Multiple contributors; foundational framework by Alex McBratney and colleagues	Willard Robert Gardner, Rollin H. Brooks, Arthur T. Corey
Type	Analytical soil characterization method	Spatial prediction and mapping pipeline	Empirical soil water retention model
Oorspronkelijke bron	Thomas, G. W. (1982). Exchangeable cations. In A. L. Page, R. H. Miller, & D. R. Keeney (Eds.), Methods of soil analysis. Part 2: Chemical and microbiological properties (2nd ed., pp. 159-165). American Society of Agronomy.	McBratney, A. B., Mendonca Santos, M. L., & Minasny, B. (2003). On digital soil mapping. Geoderma, 117(1–2), 3–52.	Gardner, W. R. (1956). Representation of soil aggregate-size distribution by a logarithmic-normal distribution. Soil Science Society of America Journal, 20(2), 151-153.
Aliassen	CEC, Soil nutrient retention, Base saturation	DSM, predictive soil mapping, quantitative soil-landscape modelling, geostatistical soil mapping	Water Retention Curve, pF Curve, Characteristic Curve, SWRC
Verwant	3	1	3
Samenvatting	Cation exchange capacity (CEC) is a fundamental soil property that measures the soil's ability to hold and release positively charged nutrient ions (cations: K⁺, Ca²⁺, Mg²⁺, Na⁺, H⁺, Al³⁺) in forms available to plant roots. CEC reflects the amount and type of clay minerals and organic matter in the soil—compounds with negatively charged surface sites that attract and temporarily bind cations. High CEC soils retain nutrients longer and require less frequent fertilization; low CEC soils lose nutrients rapidly through leaching.	Digital Soil Mapping (DSM) is a quantitative, data-driven pipeline that predicts the spatial distribution of soil properties and classes across a landscape by statistically linking field observations to environmental covariates — terrain attributes, remote sensing imagery, climate surfaces, and geology layers. The approach replaces or augments traditional expert-drawn soil surveys with reproducible, spatially explicit models, and is applied in agronomy, land management, food security, and environmental assessment.	The soil moisture curve (or soil water retention curve, SWRC) describes the relationship between soil water content and soil matric potential (water tension). It characterizes how tightly water is bound in pores of different sizes: large pores drain at low tensions (wet soils), while smaller pores retain water at high tensions (dry soils). Quantifying this relationship is essential for water balance modeling, unsaturated flow prediction, and assessing plant-available water.