『Abstract
　To calculate critical acid loads or to predict element concentrations in the soil solution, information on weathering rates is essential. Several studies have taken place in the Netherlands to obtain weathering rates for non-calcareous sandy soils. Recently information on weathering rates in less vulnerable loess and clay soils have become available. However, up to now no system is available to estimate weathering rates on a regional scale by relating them to regionally available soil properties. To obtain weathering rates of loess and clay soils on a regional scale for the Netherlands, the applicability of a statistical regression model and the process based PROFILE model have been evaluated. Both models were calibrated on a set of laboratory experiments. To evaluate their predictive power, both methods were validated on a number of sites for which field weathering rates were available. Predictions with the statistical model, for the individual base cations, were generally within a factor 2 of the calculated historical weathering rates, except for Ca, which was overestimated, by a factor 3 to 4. PROFILE strongly overestimated all weathering rates using both standard parameters and in particular after calibration on the laboratory rates. However, PROFILE predicted weathering rates of the loess soils quite good after calibration on historical weathering rates, indicating that the downscaling procedure used in PROFILE to translate laboratory to field weathering rates is inadequate for the considered soils. The statistical model was applied to predict weathering rates, for the Netherlands on a 1×1 km grid scale. Weathering rates at the present pH values in forested loess and clay soils ranged from 135 to 6000 molc ha^-1 a^-1 in loess soils and from 100 to 1750 molc ha^-1 a^-1 in clay soils.

Keywords: clay deposits; (clay) minerals; critical loads; forest soils; loess deposits; modeling; pedotransfer functions; soil acidification; weathering rates』

1. Introduction
2. Methods
　2.1. General approach
　2.2. Calibration and validation datasets
　　2.2.1. Laboratory weathering rates used for model calibration
　　2.2.2. Field weathering rates used for model validation
　2.3. Derivation of the statistical model from laboratory data
　　2.3.1. Derivation
　2.4. Application and calibration of PROFILE on laboratory data
　　2.4.1. Application
　　2.4.2. Calibration
　2.5. Field weathering rates and model validation
　2.6. Regional application of the selected model
3. Results and discussion
　3.1. Application and calibration of PROFILE on the laboratory experiments
　3.2. Validation of the models on historical weathering rates
　　3.2.1. The statistical model
　　3.2.2. Profile
　3.3. Regional application
　　3.3.1. Selection of the best model for regional application
　　3.3.2. Predicted weathering rates
4. Conclusions
Acknowledgements
References