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International audience; Recent findings suggest that soil organic carbon mineralization and stabilization depend to a substantial degree on the soil geochemistry and the degree of weathering. We hypothesized that this dependence can be translated to decay rate modifiers in a model context, and used data from the Merced chronosequence (CA, U.S.A., 100 yr-3 Myr), representing a weathering sequence, to test, on a 1000-year time scale for model spin-up, a simple soil organic carbon (SOC) model based on the RothC26.3 model concepts. Model performance was tested for four levels of information: (1) known decay rates for each model SOC pool at individual chronosequence locations, obtained by calibrating the model to measured SOC-fractions and measured site-specific C-inputs; (2) average decay rates for each SOC-pool, corrected per location with rate modifiers based on geochemical proxies and measured site-specific C-inputs; (3) uncorrected average decay rates per SOC-pool and measured site-specific C-inputs; (4) uncorrected average decay rates per SOC-pool and averaged C-inputs. A lumped root mean square error (RMSE) statistic was calculated for each information level. We found that using local measurements of fresh C-input led to a decrease in RMSE of near 15% relative to information level (4). Applying geochemical rate modifiers led to a further reduction of 20%. Thus, we conclude that there is a benefit of including geo-chemical rate modifiers in this SOC-model. We repeated this analysis for a five-pool and a four-pool SOC model that either included or excluded an inert organic matter pool. In terms of the lumped RMSE both models performed similarly, but by comparing measured and simulated percentage Modern Carbon (pMC) for bulk SOC we concluded that measured pMC was best approximated using a four-pool SOC model (without an Inert Organic Matter pool). Furthermore, it is likely that a five-pool model including a very slowly decaying pool would further improve model performance.

Modeling soil evolution is an important step towards understanding the complexity of the soil system and its interaction with the other systems. The major challenge confronted by pedologists until now is the ability to develop models capable of describing the complete complexity of the soil system. This paper presents the state of art overview of such a soil evolution model, SoilGen, its applications and limitations. In addition, the paper gives an overview of how the SoilGen model may be linked to landscape evolution models to model soilscape development. SoilGen is a mechanistic pedogenetic model in which soil forming processes such as clay migration, decalcification, carbon cycling, bioturbation, physical and chemical weathering coupled with water flow are simulated at multi-millennium time scale. The model has been calibrated and undergone extensive field testing, giving reasonable results at both pedon and landscape scales. However discrepancies between observed and simulated soil properties such as base saturation (BS), cation exchange capacity (CEC) and pH have been reported. These have been attributed partly to simplification of soil forming processes particularly in the weathering and chemical systems. There is therefore a need to extend the description of chemical and weathering systems in the SoilGen model. These extensions will not only improve model performance but will also enlarge its application range in simulating the genesis of typical features of more than half of the WRB-Reference Soil Groups. We also note here that although landscape evolution models have been successfully applied to model soil production and distribution, simplified and/or incomplete description of soil forming processes remain major limitations. We therefore add to the voices in scientific literature calling for integration of pedon and landscape scale models. In addition there is critical need for high quality chronosequence, climosequence, and toposequence profile datasets to enhance calibration and validation of soil evolution models.

We evaluated the suitability and performance of boosted regression trees (BRT) as a potential technique for soil mapping using a limited point dataset in an arid region of Iran. The model was applied using two approaches: logistic-BRT as an indirect approach and multiclass-BRT as a direct approach to produce soil class maps. In indirect prediction, the occurrence of relevant diagnostic horizons was first mapped and various maps were then combined for a pixel-wise classification by combining the presence or absence of diagnostic horizons. To allow combination of the indicator maps for classification into great groups, a decision tree was defined for linking the occurrence of diagnostic horizons to a soil great group. In direct prediction, the dependent variable was the great group itself and; therefore, the probability distribution of the soil great groups was directly predicted. Auxiliary data used in this study to represent predictive soil forming factors were terrain attributes and Landsat data as quantitative variables and a geomorphology map as categorical variable. To assess the added value of the geomorphology map, the most laborious auxiliary variable to obtain, the BRT-performance of 2 data situations was compared: (i) using only the DEM and remote sensing covariates and (ii) additionally using the geomorphology map. Results showed that the geomorphology map contributed importantly to the prediction accuracy. When it was removed from the predictors, the prediction accuracy strongly decreased. The maximum reduction in predictive performance of both indirect and direct models occurred in the absence of geomorphology map, particularly for soil classes whose presence has direct relationship with geomorphic surfaces. Generally, poor predictions seemed to be mainly due to low sample size, high variability of ancillary predictors and the inability of the geomorphology map to differentiate the strata in detail. In most predictions, the purity was better for the direct model. The indirect method predicted a high probability of salic horizon in playa landform, gypsic horizon in gypsiferous hills and calcic horizon in alluvial fans. The indirect method could provide an insight into the causes of errors in prediction at the level of diagnostic horizons, which could help in selecting better covariates.

Long-term impacts of climate evolution and agricultural management on soil properties and thus soil functioning must be assessed by modelling studies. We focus on modelling of the clay depth distribution as a result of natural soil formation and agricultural management by using the soil genesis model SoilGen2 with loess-derived Luvisols in northern France. An essential first step is the calibration of the processes concerning clay leaching (lessivage) in this model, for which we propose a reproducible method consisting of a screening for a realistic parameter range, a sensitivity analysis and finally a model calibration. To be able to separate the effects of natural soil evolution and more recent agricultural activities, we calibrated the model firstly on natural soils still under forest. Four parameters were the most sensitive and in need of calibration, representing the volume fraction of the soil in contact with macropores, a filter coefficient and physical weathering producing clay-sized particles. These parameters were successfully calibrated, but independent validations at Belgian and Norwegian sites with Albeluvisols and Stagnosols developed in loess and marine clay did not always show an improvement on earlier calibrations. This can be related to several factors, most importantly the dominance of processes other than lessivage in Albeluvisols and uncertain reconstructions of the climate. After calibration, a functional sensitivity analysis was carried out to assess the effect of agricultural management on lessivage. Clear effects on clay loss in the topsoil were found for the length of the crop-cover period and the ploughing depth and to a lesser extent for the intensity of soil mixing and the interception evaporation of the crops. As it is not feasible to reconstruct these factors for the entire period of agriculture in this region (several millennia), further analysis should take the form of scenario studies, but this should be preceded by use of field leaching experiments to calibrate SoilGen2 over short time-scales.

The future of science will be transdisciplinary. The meaning of a transdisciplinary linguistics is explained. Transdisciplinarity is not identical to interdisciplinarity. It strives at connective knowledge. Ecolinguistics proper will serve as a pace maker towards that aim because it changes the understanding of the linguistic problems by the connective thinking in ecological systems (demonstrated by the theory of language, grammar and pragmatics). The task to fulfill is hampered by the bureaucratic inertia of university structures; some examples are given. The chapter ends with a critique of normal ‘ecolinguistics light’ for following the common scientific routine of disregarding linguistic diversity.

There is a growing demand for digital soil maps for environmental planning, modeling and management. If mapped soil classes are taken from a hierarchical taxonomic system, a question arises: which taxonomic level is most appropriate to be depicted on the map with a given sample size, available environmental covariates and the strength of predictive relations between covariates and the soil classes? Pedodiversity, the study and measurement of soil diversity, can be considered as a framework to analyze spatial patterns depicted on soil maps. This paper discusses the selection of the taxonomic level for soil mapping in an arid region in southeast Iran on the basis of (1) the purity of a digital soil class map derived from an artificial neural network (ANN) prediction method using environmental covariates and (2) pedodiversity indices of these soil maps. The prediction of soil classes and the calculation of diversity indices were carried out for taxonomic categories of order, suborder, great group, and subgroup. Using the feed forward back-propagation algorithm, three-layer ANNs with input, hidden and output layers were trained for soil class prediction at each category level. In most predictions, the combined use of terrain attributes and geomorphic surfaces provided the best results. When the taxonomic level changed from order to subgroup, the purity decreased, whereas the values of the diversity indices increased. The highest purity and lowest diversity are observed at the order level, indicating a good quality map in terms of its purity, but reflecting only little soil diversity, thus with a low usage potential. On the other hand, soil maps at the level of subgroup illustrate high diversity and low purity, so that the predicted map units are highly uncertain. This map is also inappropriate for users. We introduced an index combining the diversity and purity which indicated that the best taxonomic level for soil mapping in the study area is the great group, with both high diversity and purity.

[1] Spatial patterns of soil often do not reflect those of topographic controls. We attempted to identify possible causes of this by comparing observed and simulated soil horizon depths. Observed depths of E, Bt, BC, C1, and C2 horizons in loess-derived soils in Belgium showed a weak to absent relation to terrain attributes in a sloping area. We applied the soil genesis model SoilGen2.16 onto 108 1 × 1 m2 locations in a 1329 ha area to find possible causes. Two scenarios were simulated. Model 1 simulated soil development under undisturbed conditions, taking slope, aspect, and loess thickness as the only sources of variations. Model 2 additionally included a stochastic submodel to generate tree-uprooting events based on the exposure of trees to the wind. Outputs of both models were converted to depths of transitions between horizons, using an algorithm calibrated to horizon depths observed in the field. Model 1 showed strong correlations between terrain attributes and depths for all horizons, although surprisingly, regression kriging was not able to model all variations. Model 2 showed a weak to absent correlation for the upper horizons but still a strong correlation for the deeper horizons BC, C1, and C2. For the upper horizons the spatial variation strongly resembled that of the measurements. This is a strong indication that bioturbation in the course of soil formation due to treefalls influences spatial patterns of horizon depths.

This paper presents new geo-archaeological perspectives on the Late Glacial and Early Holocene human occupation around a large palaeolake, the Moervaart palaeolake (∼25 km 2 ). Intensive fieldwork, using invasive and non-invasive survey techniques, combined with modelling of the palaeotopography and palaeogroundwater and multi-proxy palaeoecological analyses have resulted in a detailed reconstruction of the landscape during the Final Palaeolithic and Early Mesolithic occupation of the area. A major shift in the occupation from the Federmesser Culture to the Early Mesolithic was contemporaneous with a sudden and drastic change in the palaeohydrology of the area between ca. 13,300 and 13,000 cal BP (end of Allerod), which coincided with a short but abrupt cooling event known as the Intra Allerod Cold Period (IACP) GI 1b. It is assumed that this event triggered the sudden drying up of the Moervaart palaeolake and surrounding ponds, which until then had provided Federmesser hunter-gatherers with extensive and fertile grounds for hunting, gathering and drinking water. The population decline which followed this hydrological event was reinforced by the prevailing cold and harsh conditions of the Younger Dryas and probably lasted until the Pre-boreal. Hunter-gatherers returned to the area in the Boreal, now settling along the proximal floodplain regions of a meandering channel which was connected with the southern Scheldt River.

Reconstruction of past topography is an essential step towards the understanding of past landscapes in terms of biophysical patterns and processes and man–landscape interactions by archaeologists, geomorphologists, geologists and soil scientists. Landscape reconstructions can be based on process knowledge, on data, or on a combination of both. In this case study we focus on a data-based approach, where knowledge on the geological history is used to interpret and exploit legacy data. As part of a landscape reconstruction of a large area of 584 km2 a map of the elevation near 10 000 BC was produced. Starting from a present-day grid digital elevation model (GDEM) that was filtered for human influences, we identified the thickness of accumulated sediments over the Holocene, mapped these and corrected the GDEM. To map the thickness of Holocene sediments we used 72 (OSL and 14C) dated sediment samples, 731 recent profile descriptions and 3288 legacy profile descriptions. Protocols were formulated based on literature and local correlative studies to convert the legacy profile descriptions into estimates of the thickness of Holocene sediments, with an estimate of the precision. The method of Kriging with uncertain data was applied to obtain a map. Validation at 200 independent test locations with certain data showed a mean error of –6 cm and a standard deviation or error of 16 cm, which was in accordance with the estimated precision of 16 cm. The resulting map indicated zones with marked change that could be studied in more detail. Future reconstructions could employ both process knowledge and data by combining landscape genesis models with legacy data to map model errors and thus increase the quality of the reconstruction. Copyright © 2013 John Wiley & Sons, Ltd.

Archaeological distribution patterns are often biased by cultural and environmental processes. These processes influence the preservation of archaeological phenomena in the landscape. Their impact starts when the site and structures are left or abandoned or objects are deposited or disposed of. However, in archaeological landscape research, these processes are seldom incorporated. Therefore, the potential impact of both environmental and cultural processes on the preservation of archaeological phenomena needs to be understood and their influence on the observed archaeological site distribution patterns needs to be measured. Furthermore the history, intensity and methodology of the archaeological research in the region influence the known archaeological distribution pattern and therefore an understanding of the archaeological practice in the region is necessary in the study of the past landscapes of that region. This paper presents a case study on the distribution pattern of Bronze Age barrows in the highly urbanised landscape of north-western Belgium. By integrating natural, cultural and archaeological processes in archaeological landscape research, the completeness and reliability of the archaeological dataset can be estimated. Efforts to estimate completeness and reliability of any dataset should be an integral part of every archaeological landscape research project, especially as biases or hiatuses in datasets can lead to serious misinterpretations or circular reasoning. Furthermore, knowledge of the biography of landscapes is not only important in the study and understanding of past archaeological landscapes, but also in the preservation of these landscapes and our ability to incorporate hidden past landscapes into the actual sustainable management of its cultural–historical heritage.

Topographic position index (TPI) is an algorithm increasingly used to measure topographic slope positions and to automate landform classifications. We applied TPI to a geoarchaeological research project in northwestern Belgium but its use led to erroneous landform classifications in this heterogeneous landscape. We asked whether deviation from mean elevation (DEV) was a better method for landform classification than TPI. We found that it enabled more accurate geomorphological assessment when using northwestern Belgium as a case study.

The first results of modeling soil development in marine sediments in S Norway using the model SoilGen are compared to measured properties of two soil chronosequences, on the western and eastern side of Oslofjord, respectively. The aim of this work is to test how well soil development under well-defined environmental conditions can be modeled. Such testing reveals to what degree soil-forming processes are understood, allowing formulation of adequate calculations reflecting these processes. The model predicts particle size distribution reasonably well, although clay depletion in the upper parts of the soils as a result of clay migration is overestimated. The model tends to underestimate contents of organic carbon and CEC in the A horizons: below, modeled CEC matches well with measured CEC. Base saturation is overestimated in the upper 40 cm and underestimated below. Apparently, leaching of bases proceeds less rapidly in reality than is predicted by the model, due to strong soil structure of the B horizons, causing preferential flow and base leaching around the aggregates, whereas bases inside the aggregates are only slightly affected by leaching. Difficulties and possibilities for improvements are identified, some related to model input data and some to the model itself. Input data could be improved by determining the amounts of organic carbon in organic surface horizons and by quantifying effects of bioturbation. A big challenge is the implementation of soil structure formation in the model. Quantitative data on the development of soil structure with time that can be included in a model are required. Amounts, distribution and connectivity of macro pores need to be defined for each stage of soil development, and zones of low and high base leaching need to be distinguished in the model for each time step. The long-term aim of this work is to model soil development with different sets of soil-forming factors, e.g. different climatic conditions in order to reliably predict soil development under different climate scenarios and related sets of soil-forming factors. The results of the first model runs and the identified possible improvements suggest that this aim is generally achievable.

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Summary The main objectives of this study were to compare binary logistic regression as an indirect approach and multinomial logistic regression as a direct approach to produce soil class maps in the Zarand region of southeast Iran. With indirect prediction, the occurrence of relevant diagnostic horizons was first mapped, and subsequently, various maps were combined for a pixel-wise classification by combining the presence or absence of diagnostic horizons. In direct prediction, the dependent variable was the great group itself, so the probability distribution of the great soil groups was directly predicted. Among the predictors, the geomorphology map was identified as an important tool for digital soil mapping approaches as it helped to increase the accuracy. The results of prediction showed larger mean probability values for each great soil group in the areas actually covered by the great soil groups compared with other areas, indicating the reliability of the prediction. In most predictions, the global purity was slightly better than the actual purity for the models; however, both models provided poor predictions for Haplocambids and Calcigypsids. The results showed that soils with better prediction were those much influenced by topographical and geomorphological characteristics and soils with very poor accuracy of prediction were only slightly influenced by topographical and geomorphological characteristics. An advantage of the indirect method is that it gives insight into the causes of errors in prediction at the scale of diagnostic horizons, which helps in the selection of better covariates.

The unique selling point of pedometricians still is close to their cradle: ability to map. Irrespective of the many scientific achievements one can ask if offering mapping ability, allbeit in various contexts, is all a pedometrician can do to bring forward soil science's broader agenda. This paper identifies, within some of the hotter issues on the soil science agenda, activities that need the input of pedometricians. Digital soil mapping (DSM) has reached maturity although some issues like the optimal use of legacy data still need attention. The necessary shift from DSM to digital soil function mapping implies an increased need for process knowledge in mapping, but also an increased focus of pedometricians on the strengthening of process models. Most quality issues related to DSM have a counterpart in process modelling, and some of these issues need elaboration to construct well-calibrated and complete models, e.g. by making motivated choices between the inclusion of processes or model reduction. Reaching out to stakeholders is also an issue of increasing interest, as these are confronted with uncertain concurrent models to evaluate future scenarios. Questions are raised such as: Does the need for a state-of-the-art (SOTA) approach imply a choice for one model and how should this be made, or is SOTA implementable as some weighted average of screened concurrent models. Can observations and model results be combined in decision making and what techniques are needed. The above issues are illustrated with existing examples and new material from soil science and beyond. As DSM and process modelling share common ground, mutual benefits can be expected at the interface of both research fields such as (i) increased usage of process knowledge in DSM and (ii) probabilistic approaches to less well understood soil processes. Stakeholders will profit from the development of decision frameworks to choose applicable DSM-techniques and the increased application of ensembles of DSM-methods and models to narrow prediction error bandwidths. Additionally, they will profit from the development of decision support systems filled with outcomes of scenario studies of multiple, uncertain, and concurrent models as these provide an interesting alternative to the application of one selected model.

Based on radiocarbon and optically stimulated luminescence (OSL) results obtained in the last 5 yr, this paper discusses the absolute chronology of the formation of one of the largest sand dunes within NW Belgium, the Great Ridge of Maldegem-Stekene. Multiproxy analysis of 6 sedimentary sequences points to a complex formation history covering the entire Late Glacial. Dry phases, characterized by eolian deflation and sedimentation, alternated with wet phases in which numerous mostly shallow dune slacks were filled with freshwater. The latter reached their highest water level during the first half of the Allerød, attracting both animals (e.g. European elk) and humans (Federmesser hunter-gatherers). Near the end of the Allerød, all dune slacks finally disappeared as they were filled in with windblown sand ("coversand"), likely forcing prehistoric hunter-gatherers to leave the area.

Four types of soil data, each with a characteristic reliability, are proposed for point observations and areas of land. Distinctions are based on procedures by which data are obtained: (i) measurement; (ii) estimation by experts; (iii) calculation by pedotransfer-functions, and (iv) same, by simulation models. Data are either static, requiring a single measurement, or dynamic, requiring measurements over a period of time. Three case studies illustrate: (i) interpolation of a static point measurement with multiple indicator kriging allowing an expression of risk of exceeding critical values; (ii) interpolation based on a time series of nitrate fluxes, calculated with a deterministic simulation model. Reliability was difficult to define because input data consisted of measured and estimated parameters with unknown reliability, and (iii) expression of data reliability in an uncertainty analysis by using rotated random scan and Monte Carlo techniques in the context of simulating water fluxes in a clay soil. Results reflect data reliability and use of this procedure is therefore recommended.

The predictive quality of the current drainage class map of Flanders was evaluated using data from two monitoring networks: one with good spatial coverage but poor temporal coverage and another with better temporal but poor spatial coverage. We combine both networks to obtain 1678 point predictions for mean highest water (MHW) and mean lowest water (MLW) tables by applying time series modelling and total least squares regression. The resulting MHW and MLW point data set was used to evaluate the currency of the existing map and to identify regional differences. The quality of the current map is moderate, and large differences occur between regions. Especially the Campine region shows large and systematic differences, whereas the southeastern hills and chalk–loam region is relatively accurate. If more weight is given to errors in the wetter drainage classes, about 50% of the area of Flanders would benefit from remapping. Copyright © 2011 John Wiley & Sons, Ltd.

Field methods to map and reconstruct the morphology of buried river systems are highly dependent on spatial interpolation. Conventional methods, such as standard borehole survey, allow a detailed vertical reconstruction of the shallow subsurface but leave lateral connections between sample locations open to interpretation. Geophysical survey techniques have recently introduced more detail. Mobile electromagnetic induction (EMI) survey combines high density sampling with full lateral coverage but fails to produce detailed information about vertical facies changes. Recently, multicoil EMI survey added vertical discrimination potential to this lateral continuity. In this study, we present an integrated approach for reconstructing the morphology of a known palaeochannel segment by modelling the depth to the sandy substrate. In addition, a calibration method based on a limited number of auger data is proposed. In a first phase, the modelling procedure was evaluated along two transects on a test site, showing palaeochannel depths ranging from 1 to > 4 m beneath the surface. In a second phase, the morphology of the entire site was reconstructed. These three resulting depth models were then compared with auger observations and electrical resistivity tomography (ERT) data. The high correlation coefficients (> 0.9) between observed and modelled depths showed that even in complex pedological environments, palaeochannel morphology could be predicted precisely using multicoil EMI data. Therefore, we concluded that a multicoil EMI survey proves to be an efficient and reliable solution for mapping and reconstructing the morphology of the shallow subsurface.

The SoilGen1 model was developed to simulate soil development in calcareous loess at Holocene (15,000 BP–present) temporal extent. We used the LEACHC model as a core and added process formulations to describe the effect of vegetation and soil macrofauna on various soil properties. A limited calibration was done on the calcite solubility constant by comparing decarbonization rates in various leaching climates with values predicted by the metamodel of Egli and Fitze [Egli, M. and Fitze, P. 2001. Quantitative aspects of carbonate leaching of soils with differing ages and climates. Catena 46:35–62.]. Soil profiles of C and pH after 15,000 years compared well with measurements in a Belgian loess profile that was never under agriculture, taking the composition of the C-horizon as uniform parent material. Scenarios with and without agriculture, with varying degrees of bioturbation and for documented Holocene climatic and vegetation evolutions in Belgium and Hungary were simulated and compared. Results show a clear effect of bioturbation on soil development, especially in the continental climate evolution of Hungary. Indicators for the possible occurrence of clay migration and disturbance of lateglacial morphology were calculated and these also show the importance of bioturbation.

Silicate mineral dissolution rates depend on the interaction of a number of factors categorized either as intrinsic (e.g. mineral surface area, mineral composition) or extrinsic (e.g. climate, hydrology, biological factors, physical weathering). Estimating the integrated effect of these factors on the silicate mineral dissolution rates therefore necessitates the use of fully mechanistic soil evolution models. This study applies a mechanistic soil evolution model (SoilGen) to explore the sensitivity of silicate mineral dissolution rates to the integrated effect of other soil-forming processes and factors. The SoilGen soil evolution model is a 1-D model developed to simulate the time-depth evolution of soil properties as a function of various soil-forming processes (e.g. water, heat and solute transport, chemical and physical weathering, clay migration, nutrient cycling, and bioturbation) driven by soil-forming factors (i.e., climate, organisms, relief, parent material). Results from this study show that although soil solution chemistry (pH) plays a dominant role in determining the silicate mineral dissolution rates, all processes that directly or indirectly influence the soil solution composition play an equally important role in driving silicate mineral dissolution rates. Model results demonstrated a decrease of silicate mineral dissolution rates with time, an obvious effect of texture and an indirect but substantial effect of physical weathering on silicate mineral dissolution rates. Results further indicated that clay migration and plant nutrient recycling processes influence the pH and thus the silicate mineral dissolution rates. Our silicate mineral dissolution rates results fall between field and laboratory rates but were rather high and more close to the laboratory rates possibly due to the assumption of far from equilibrium reaction used in our dissolution rate mechanism. There is therefore a need to include secondary mineral precipitation mechanism in our formulation. In addition, there is a need for a more detailed study that is specific to field sites with detailed measurements of silicate mineral dissolution rates, climate, hydrology, and mineralogy to enable the calibration and validation of the model. Nevertheless, this study is another important step to demonstrate the critical need to couple different soil-forming processes with chemical weathering in order to explain differences observed between laboratory and field measured silicate mineral dissolution rates.

The new standard 'ISO 17636-2:2013: Non-destructive testing of welds - Radiographic testing - Part 2: X- and gamma-ray techniques with digital detectors', defines the practice for radiographic inspection of welded pipes for manufacturing and in-service inspection. It is applied in Europe for inspections of pipe welds in nuclear power plants as well as in chemical plants and allows a faster inspection with digital detector arrays (DDA) than with film. Nevertheless, it does not allow the evaluation of the depth and shape of volumetric and planar indications. In 2001 a planar tomography scanner, TomoCAR, was introduced for mechanized radiographic testing (RT) inspection and non-destructive measurement of cross sections. The project TomoWELD is based on a new concept of the scan geometry, an enhanced GPU based reconstruction, and the application of a new generation of photon counting DDAs based on CdTe crystal CMOS hybrids. The new detector permits the selection of energy thresholds to obtain an optimum energy range and reduction of the influence of scattered radiation. The concept and first measurements are presented. Flaw depth and shape of volumetric and planar irregularities can be determined.

Agricultural activities in the Netherlands cause high nitrogen and phosphorous fluxes from soil to ground- and surface water. A model chain (STONE) has been developed to study and predict the magnitude of the resulting ground- and surface water pollution under different environmental conditions. STONE has three main components, namely: 1) the fertiliser distribution model CLEAN; 2) the atmospheric transport and deposition model OPS; and 3) the soil and soil-water quality model ANIMO. The goal of this study was to assess the accuracy of the STONE model output by comparing model predictions with independent observations, while accounting for spatial variation and differences in spatial support. The specific STONE output considered was mineral phosphorous concentration in the top soil. Predictions from STONE are made at the block support and, specifically, for 500 × 500 m grid cells, whereas the observations are on a point support. Therefore, aggregation of the point observations or disaggregation of the STONE model predictions is needed in order to test the accuracy of the STONE model. This study used the aggregation route. Specifically, ordinary and regression block kriging were used to aggregate the point observations to the block support. Overall, there was a good correspondence between the kriged observations and the STONE predictions, with no evidence of bias in the model predictions. However, there were meaningful differences locally, which was partly attributed to the smoothing of the kriging interpolator. Closer inspection revealed that not all of the differences could be attributed to measurement errors in the phosphorous observations and interpolation errors in the kriged phosphorous maps. Thus, it was demonstrated that the STONE output suffers from input and/or model errors. However, quantification of these errors was restricted by the fairly large interpolation uncertainty of the kriged phosphorous observations. Nevertheless, the spatial pattern of error in the STONE predictions could be partly attributed to combinations of landuse and soil type.

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Groundwater table (GWT) class maps have been mapped for the whole of The Netherlands at a scale of 1:50,000, and provide useful information for a variety of purposes. Due to strong human impact on the Dutch landscape, water tables have changed and the maps now need updating. Six updating methods have been defined, varying in data requirements and in the smallest spatial unit that can be updated. The performance and cost of each of the methods were measured in a 9228-ha test area. The costs were also extrapolated to larger areas of 46,994 and 75,684 ha using measures of sampling error as criteria. The major cost factor is largely determined by the sample size, which is method dependent. A method that updates GWT maps by evaluating an objective function in locations obtained through stratified random sampling showed the best performance in the test area and a reasonable cost development at larger areas. Validation in the 75,684 ha area supported this conclusion. A kriging-based method performed well, but was expensive. In the near future, elevation data will be available at the national scale. Using these data as ancillary information will decrease cost and increase the accuracy of GWT map updates. This will allow for drawing new map polygons instead of re-labeling existing ones.

Understanding palaeotopographical variability forms the basis for understanding prehistoric societies. Alluvial and lacustrine environments, in particular, are key areas with both a high archaeological and palaeoecological potential. However, the often deep stratification of these sites, the high water table and the complex sedimentological variations can hamper a detailed reconstruction of the spatial relationship between prehistoric settlement and their environment. Combining different remote and proximal sensing techniques and coring data, can offer detailed insight into such landscapes. More specifically, the integration of mobile geophysical methods allows the collection of unprecedented continuous information on large-scale palaeolandscape variability. In this study we present a combined approach in order to map and model prehistoric landscapes and river systems in and around a Late Glacial palaeolake in north-western Belgium. Based on filtered and unfiltered digital elevation models, a survey area of 60 ha was selected, in which detailed mobile multi-receiver electromagnetic induction survey was conducted. The results allowed for the delineation of palaeochannels in the area and enabled modelling the depth of these features in the survey area, providing insight into their flow characteristics. 14C sampling enabled the dating of the evolving river system to the transition between the Late Glacial and the Early Holocene. Through additional coring, this river system could be traced further through the palaeolake area. Based on these results a detailed reconstruction was made of the palaeotopography that harboured the Final Palaeolithic and Early Mesolithic occupation of the study site.

Uncertainties in major input variables in water and solute models were quantified and their effects on simulated functional aspects of soil behaviour were studied using basic soil properties from an important soil map unit in the Netherlands. Two sources of uncertainty were studied: spatial variability of basic soil properties, and the use of pedotransfer functions to predict soil hydraulic functions. Depending on the type of process studied, variability of basic soil properties explained between 40 and 99.9% of the total variance. Uncertainty of pedotransfer functions is of importance mainly when physical soil behaviour (e.g. workable days and aeration status) is studied.

Class pedotransfer functions were used to generate average hydraulic characteristics for distinct soil texture classes. Continuous pedotransfer functions were used to generate soil hydraulic characteristics from the actually measured median of the sand particle size, bulk density and percentages clay, silt and organic matter. Both approaches were used to predict the soil physical input data to calculate five different functional aspects of soil behaviour. The functional aspects were: number of workable days, number of days with adequate soil aeration, elapsed time until 10% breakthrough of chloride, amount of cadmium leached after one year and amount of Isoproturon leached after one year. Simulations of water and solute transport were made for 88 profiles which form a statistically representative set of profiles for cover sands in the northeastern part of the Netherlands. The calculated number of workable days did not depend on the type of pedotransfer used. However, the differences between the class and continuous pedotransfer function approach were significant for the other four functional aspects of soil behaviour. For adsorbing cadmium and adsorbing and degradable Isoproturon, differences between the two approaches were statistically significant because they were systematic. However, these differences were so small that they were irrelevant in practice. When to prefer which approach was ambiguous and depended on the functional aspect under consideration. When differences were not significant or irrelevant in practice, the cheaper and easier to use class pedotransfer function approach is preferred over the continuous pedotransfer function approach.

A comité de lecture, avec review; International audience; In this chapter, we discuss hydrology as an input in modeling pedogenesis by comparing the advantages and limitations of different modeling approaches. Water is the main driving force of pedogenesis, as it is responsible for the transfer of solutes and particles and for most of the geochemical and biological reactions occurring in soils. It is thus indirectly responsible for soil texture and structure evolution that influences water transfer and residence time in soils. Two example models that combine geochemistry, hydrology, and plant growth modules are presented: SoilGen and WITCH. These two models simulate the evolution of some soil characteristics on the pedologic time scale reasonably well. However, in their present states of development, these models are not able to simulate any type of soil evolution; therefore, further improvements are needed to implement soil processes and the feedbacks among them. Parametrization and validation, on pedologic time scale, also remain a challenge.

Estimation of land use during the Holocene is crucial to understand impacts of human activity on climate change in preindustrial period. Until now it is still a key issue to reconstruct amount and spatial distribution of prehistoric land use due to lack of data. Most reconstructions are simply extrapolations of population, cleared land amount per person and land suitability for agriculture. In this study, a new quantitative prehistoric land use model (PLUM) is developed based on semi-quantitative predictive models of archeological sites. The PLUM is driven by environmental and social parameters of archeological sites, which are objective evidences of prehistoric human activity, and produces realistic patterns of land use. After successful validation of the model with modern observed data, the PLUM was applied to reconstruct land use from 8 to 4 ka B.P. in Yiluo valley, one of the most important agriculture origin centers in northern China. Results reveal that about 2–9% of land area in the valley was used by human activity from 8 to 4 ka B.P., expanding from gentle slopes along the river to hinterlands in middle and lower parts of the valley. The land cover was affected by increasing agricultural land use during the middle Holocene.

To evaluate the effect of various levels of fertilizer applications, six fertilizing scenarios were analyzed by computer simulations using a process-based simulation model. By using simulation results of one of the fertilizer scenarios as a covariable in disjunctive cokriging (DCK), the number of simulations in the remaining scenarios could be reduced to 20% of the original number, while the prediction quality in fifty test points still satisfied two criteria based on the sample variance. When the conditional probability of exceeding a threshold value is to be mapped, an expanded data set is of limited use because some variance is lost in the expansion process.

SUMMARYField scale variability in the grain yield of barley in 1989 was investigated in 62 field plots in a Dutch polder area, and compared to soil- and simulation-type characteristics. Total grain mass varied between 3409 and 6019 kg/ha, and grain moisture content between 131 and 14·7%. Soil profile descriptions and soil characteristics were used as basic input data for simulations. Soil water flow was simulated at 119 locations with the LEACHM model, for the purpose of quantifying spatial variability in transpiration deficits in the growing season. Both soil- and simulation-type characteristics were translated from point values to spatial averages for the harvested fields, using kriging. Kriged characteristics were correlated with yields, and used to construct transfer functions. Simulated transpiration deficits during sensitive crop development phases showed negative correlations with grain yield. Transfer functions explained at maximum 68·2% of the variance in the yields.

Thinly stratified sedimentary deposits in a heterogeneous field were investigated to obtain basic physical data for the simulation of water flow. A procedure is described which translates a thinly stratified soil profile into a number of functional layers using functional hydrological properties. A functional layer is defined as a combination of one or more soil horizons and should (i) be recognizable during a soil survey using an auger and (ii) show significantly different functional hydrological properties when compared with another functional layer. This procedure gave three easily recognizable functional layers. Sets of hydrological characteristics of these three functional layers were obtained by physical measurements of the soil and by estimation, using textural data for classification into a standard Dutch series. The performance of several combinations of these sets was tested by comparing simulated and measured soil matric potentials for seven plots during one year. The best simulation results were obtained if measured soil hydraulic characteristics were used for relatively homogeneous functional layers and if the soil hydraulic characteristics were estimated at each location for the most heterogeneous layer.

Soil structure variability was inventoried on a field scale, and translated to basic input data for a solute transport and crop production simulation model. After validation of the model, it was used to simulate the spatially varying effect of slurry application and N-fertilizing scenarios by multiple point-simulations. Feasibility of scenarios was determined by comparing nitrate leaching concentrations with current and pursued threshold levels. Disjunctive kriging was used to estimate and map the probability that these threshold levels were exceeded. Emphasis was given to the effect of soil-specific slurry application rates and N-fertilizer levels on leaching probabilities and crop yields. Soil-specific N-treatments increased field yields, because crop response to N, both in slurry and in fertilizer, was soil dependent. The leaching response to N-treatment was also soil dependent.

Introduction - Robert L. Canfield Part I, Repressions and their Consequences 1. Authoritarianism and Its Consequences in ex-Soviet Central Asia - Anatoly Khazanov 2. Localism and Identity among the Uyghur of Xinjiang - Ildiko Beller-Hann Part II, Ethnic Perceptions and Reactions 3. Central Asian Attitudes towards Afghanistan Perceptions of the Afghan War in Uzbekistan - Peter Finke 4. Alignment Politics and Factionalism among the Uzbeks of North-Eastern Afghanistan - Gabriele Rasuly-Paleczek 5. Rebuilding Afghanistan - Thomas Barfield 6. Pukhtun Identity in Swat, Northern Pakistan - Charles Lindholm Part III, Devices of Mutual Support 7. Towards a Transnational Community: Migration and Remittances among the Hazaras - Alessandro Monsutti 8. An Interregional History of Pashtun Migration, c. 1775-2000 - Robert Nichols Part IV, Mechanisms of Authority and Influence 9. Political Games in Post-Soviet Uzbekistan: Factions, Protection and New Resistances - Boris PetriAa 10. Female Mullahs, Healers and Leaders of Central Asian Islam: Gendering the Old and New Religious Roles in Post-Communist Societies - Habiba Fathi 11. Efficacy and Hierarchy: Practices in Afghanistan as an Example - Robert L. Canfield

Betrachtet man die Entwicklung der europaischen Wohlfahrtsstaaten, dann lassen sich Konturen eines neuen Leitbilds ihrer „Modernisierung“ erkennen. In Europa hat sich unter sozialdemokratischer Federfuhrung eine „Politik des Dritten Weges“ (Giddens 1997) zur Reform des Wohlfahrtsstaates herausgebildet, in deren Rahmen zwecks Effizienzsteigerung auf der Makro-, der Meso- und der Mikroebene in Staat und Gesellschaft Markt- und Wettbewerbselemente eingebaut werden. Der „Um- bzw. Ruckbau“ des Sozialstaats findet unter der Losung statt, dass in Zeiten der Globalisierung bzw. Europaisierung der Sozialstaat zwar auch weiterhin zur Sicherung des gesellschaftlichen Zusammenhalts notig ist, seine Leistungstiefe und damit auch die Art und Weise sowie der Umfang seiner Finanzierung aber neu organisiert werden mussen, um im weltweiten Wettbewerb mit anderen Wirtschaftsstandorten bestehen zu konnen.