Search

Many research and scientific organizations emphasize the importance of science for society in their strategic plans. This is certainly true for land use studies being discussed in this chapter as new environmental policies are introduced at European and national level. Such policies reflect concerns of society so that a structural link between science and policymaking would appear to be logical and desirable. Rather than following traditional top‐down and disciplinary research approaches, emphasis is increasingly being placed on interactive, interdisciplinary work in Communities of Practice (CoPs) in which scientists work together with various stakeholders and policymakers in a joint learning mode. But this requires new research approaches including long‐term engagement during the entire policy cycle asking for a new attitude of scientists. Few experiences have been reported so far. Three Dutch case studies are therefore discussed to illustrate the functioning of CoPs by focusing on up‐ and downscaling (called multiscaling hereafter), a key element of land use research. Five types of multiscaling were used in the three case studies. Three were technical: (1) use of model‐ or design‐based (geo)statistical techniques, (2) extrapolation of data obtained from experimental plots to larger areas, and (3) use of quasi‐3D process models to upscale grid data in a Geographic Information System (GIS) to regions. Two were policy oriented: (1) nutrient balances for farms to allow upscaling from fields to farm and (2) a research framework for regions, based on the DPSIR approach, which sequentially covers aspects mentioned in environmental laws as being important for sustainable development. Quite diverse and unrelated questions about land use issues by different members of the CoP cannot be a fruitful basis for research programs. Scientists have therefore an important role to play within a CoP in orchestrating a demand analysis that puts questions into context and defines existing knowledge as well as knowledge gaps. Defining research on the basis of a demand analysis in a CoP creates innovative ideas, creates commitment of participants, and allows definition of needed research that is functional. This includes cutting edge research publishable in literature and requires for land use studies updating of valuable existing soil survey information to a level that can be used in modern modeling techniques including functional characterization of soil series, development of pedotransfer functions, and definition of phenoforms. Particular attention is needed for introducing modern monitoring techniques for soil and water because the high cost of traditional methods implies that little monitoring is done now with detrimental effects for the calibration and validation of simulation models that increasingly secure a live of their own. The scientific community needs to take a fresh look at its paradigms. Next to the establishment of CoPs, we therefore advocate development of Communities of Scientific Practice (CSP) within the research community that define different functions for members of the scientific community in terms of (1) communication within CoPs by shaping the demand analysis and to the outside world and (2) defining research needs and its execution, using knowledge chains including basic research.

Dutch regulations for ammonia emission require farmers to inject slurry into the soil (shallow) or to apply it in narrow bands at the surface. For one commercial dairy farm in the Netherlands it was hypothesized that its alternative farming strategy, including low-protein feeding and surface spreading, could be an equally effective tool for ammonia emission abatement. The overall objective of the research was to investigate how management at this farm is related to nitrogen (N) losses to the environment, including groundwater and surface water. Gaseous emission of ammonia and greenhouse gasses from the naturally ventilated stables were 8.1 and 3.1 kg yr(-1) AU(-1) on average using the internal tracer (SF(6))-ratio method. Measurements on volatilization of ammonia from slurry application to the field using an integrated horizontal flux method and the micrometeorological mass balance method yielded relatively low values of ammonia emissions per ha (3.5-10.9 kg NH(3)-N ha(-1)). The mean nitrate concentration in the upper ground water was 6.7 mg L(-1) for 2004 and 3.0 mg L(-1) for 2005, and the half-year summer means of N in surface water were 2.3 mg N L(-1) and 3.4 mg N L(-1) for 2004 and 2005, respectively. Using a nutrient budget model for this farm, partly based on these findings, it was found that the calculated ammonia loss per ton milk (range 5.3-7.5 kg N Mg(-1)) is comparable with the estimated ammonia loss of a conventional farm that applies animal slurry using prescribed technologies.

Soil hydraulic functions can be obtained with methods that range from complex and costly to simple and cheap. Decisions as to which is the most appropriate method for a specific application have to be based on a comparison of generated hydraulic functions. This comparison should preferably be based on a statistical comparison of practical applications calculated with the different hydraulic functions rather than on a statistical comparison of the functions themselves. In this study four different methods were used to generate hydraulic functions: (A) direct on-site measurement, (B) measurement in soil horizons in the area, (C) use of a national data set, and (D) use of Van Genuchten parameters correlated with soil texture and organic matter content. The four methods were compared by their effect on two practical aspects of soil behaviour: (1) evapotranspiration deficit and (2) flux through a plane at 30 cm below soil surface. These two aspects are highly relevant for agricultural and environmental use. However, direct measurement is not feasible. A validated simulation model was used for the calculations and results obtained with method A were taken as a reference. Calculations were performed for three soil profiles for a period of seven years. Deficits and fluxes, calculated with the four methods to generate hydraulic functions, were not significantly different using the data of the seven-year period. However, methods were significantly different when rainfall deficits were used as a covariable. This is true with the exception of downward fluxes in the period October until March which are most important for leaching of pollutants. The user has to decide whether differences between methods are sufficiently large to justify repeated, expensive on-site measurements (method A) or whether an investment will be made to make standard series of curves to be used everywhere (methods C and D).

Precision agriculture aims at adjusting and fine-tuning land and crop management to the needs of plants within heterogeneous fields. Production aspects have to be balanced against environmental threshold values and modern information technology has made it possible to devise operational field systems. A reactive approach is described, using yield maps and sensors. A proactive approach uses simulation modelling of plant growth and solute fluxes to predict optimal timing of management practices. Precision agriculture, combining both approaches, is seen as making a major contribution towards the development of sustainable agricultural production systems.

The EU Commission has proposed a way forward towards a Thematic Strategy for Soil Protection based on the distinction of seven soil functions and eight threats. A Technical Working Group on Research defined some 200 general priority research areas in the context of the dynamic DPSIR approach considering drivers, pressures, states, impacts and responses. Though quite valuable as a source document, this may be too generic and academic to be a starting point for new, effective soil research in different regions of the EU. A six-step storyline procedure is therefore proposed aimed at deriving effective operational procedures for a water management unit in a given region, using available soil expertise and defining new research only where needed. The procedure, that was illustrated for a Dutch case study, consists of defining: (i) water management units (wmu's) in a landscape context; (ii) land-use, area hydrology and soil functions (iii) soil threats and relevant soil qualities; (iv) drivers of land-use change and their future impact; (v) improvement of relevant soil qualities; (vi) possibilities to institutionalize soil quality improvement as part of the EU soil protection strategy. A focus on regional wmu's is likely to result in a strong commitment of local stakeholders and governmental officials, allowing a more specific DPSIR approach. But this will only work if local officials also receive legal powers to develop and enforce codified `good practices¿, to be developed in the context of communities of practice. Innovative research topics can be derived from a combined analysis of experiences within different communities of practice in different wmu's and should not be left to researchers to define.

Soil science is a vital scientific discipline producing cutting-edge research in its various sub-disciplines. Its role in studying major environmental issues, often defined as food security, water and energy availability, climate change and biodiversity loss, is, however, less obvious to stakeholders, policy makers and the public at large. It deserves better. Reframing the soil story by taking a pro-active interdisciplinary approach in demonstrating the role of soils when studying these issues is advocated in the context of the ten Sustainable Development Goals. Soil change matters not only in a negative way when referring to erosion and degradation but also, and particularly, to soil improvement. But only successfully completed programs in practice will be convincing and that's why an active role of soil researchers and soil scientists, acting as knowledge brokers, is advocated in transdisciplinary programs. This includes more emphasis on preparation and implementation than is allowed in current programs. A case study is presented and a narrative is used to link the five major environmental issues in a logical sequence, showing their interdependence. Current soil research and education programs should reflect demands made by inter- and transdisciplinary approaches and need a new, fresh approach.

This paper presents a vision that advocates hydropedology as an advantageous integration of pedology and hydrology for studying the intimate relationships between soil, landscape, and hydrology. Landscape water flux is suggested as a unifying precept for hydropedology, through which pedologic and hydrologic expertise can be better integrated. Landscape water flux here encompasses the source, storage, flux, pathway, residence time, availability, and spatiotemporal distribution of water in the root and deep vadose zones within the landscape. After illustrating multiple knowledge gaps that can be addressed by the synergistic integration of pedology and hydrology, we suggest five scientific hypotheses that are critical to advancing hydropedology and enhancing the prediction of landscape water flux. We then present interlinked strategies for achieving the stated vision. It is our hope that by working together, hydrologists and pedologists, along with scientists in related disciplines, can better guide data acquisition, knowledge integration, and model-based prediction so as to advance the hydrologic sciences in the next decade and beyond.

Publisher Summary Science and technology in situ has changed its course along with social and economic developments. Although it has not always been beneficial to human beings, civilization has got the required mileage to drive information, culture, resources, and wealth throughout the world from one era to another. The awareness of soil goes right back to the start of our civilization. The ‘‘true’’ soil has been the favorite domain of the soil scientist, using ever more sophisticated methods to measure soil characteristics and to characterize dynamic soil processes. This has greatly expanded the knowledge about soils and been a major contribution to society at large as this knowledge was applied in many products and services. Effects of land use are difficult to predict in the same quantitative and unique manner in which, for example, a Cation Exchange Capacity (CEC) can be predicted because conditions are so diverse. There is no single magic answer to any given land‐use question because many stakeholders are involved with widely varying interests. The soil scientist should try to define the ‘‘true’’ soil as well as possible but should be modest and know his limits. Soil scientists have a major handicap: soils occur underground and are invisible except when excavated. Plants and animals are highly visible, at least partly explaining the viability of policies enforcing biodiversity. There are efforts now to define soil‐charters and the EU is working on soil policies.

Hydropedology is an intertwined branch of soil science and hydrology that encompasses multiscale basic and applied research of interactive pedological and hydrological processes and their properties in the unsaturated zone. The synergistic integration of classical pedology with soil physics, hydrology, and other related bio- and geosciences into hydropedology suggests a renewed perspective and a more integrated approach to studying landscape–soil–water dynamics across scales. Pedality, layering of soil horizons, and soil–landscape relationships are three essential characteristics of soils as occurring on the landscape. Fundamental issues of hydropedology include (1) soil structure and layering as indicators of flow and transport characteristics in field soils; (2) soil morphology as signatures of soil hydrology; (3) water movement over the landscape; and (4) hydrology as a factor of soil formation and a driving force of dynamic soil system. Hydrology affects and is affected by all of the five natural soil-forming factors and the four general soil-forming processes. Hence, hydropedology offers potential opportunities for quantifying soil-forming processes. Future needs in advancing hydropedology are encapsulated in the philosophy of “bridging disciplines, scales, data, and education.” These include (1) systems approaches to understanding and communicating landscape–soil–water dynamics; (2) addressing variability using patterns at various scales; (3) enhancing pedotransfer functions and developing soil inference systems and hydropedoinformatics; and (4) education of the next generation of soil scientists and hydrologists. Hydropedology calls for adequate attention to soil morphology (including soil structure) in the field and soil patterns over the landscape to guide optimal soil physical and hydrological measurements, field monitoring and experimental designs, and understanding and modeling of flow and transport in the critical zone. Identification and prediction of patterns (spatial-temporal organizations) across multiple scales are coming to the forefront in soil science and hydrology, which offer rich and comprehensive insights regarding variability and the underlying processes. We suggest various hydropedological approaches to address diverse knowledge gaps. Given its links to a wide array of environmental, ecological, geological, agricultural, and natural resource issues of societal importance, hydropedology is emerging as a promising field that could contribute significantly to the study of the pedosphere, the hydrological cycle, the earth's critical zone, and the earth system.

The Netherlands has attempted to follow EU guidelines in developing national policies to reduce pollution of groundwater by nitrates originating from (over) fertilized agricultural land. The EU has not been satisfied with these policies and this is resulting in legal conflicts. National policies have focused on nitrogen budgeting and on fertilization rates, over-simplifying the crucial role of soils during the leaching of nitrates to groundwater. As an alternative, a dynamic approach using simulation modeling is introduced as is illustrated for a study area in the Netherlands. A number of considerations for future policy directions are suggested, including requirements for research: (i) promotion of research aimed at improving and maintaining nutrient use efficiency at farm level; (ii) promotion of joint learning experiences between farmers and researchers, where farmers' organizations could act as "research consortia"; (iii) emphasis on site and time specific management (precision agriculture) in policy development, and provision of site-specific advice via modem information and communication technologies; (iv) clearer guidelines for groundwater monitoring procedures, including additional monitoring at greater depths and consideration of groundwater quality from an appropriate regional perspective; (v) groundwater monitoring should take place at locations selected according to specific hydro-geological characteristics, rather than being executed at random and (vi) clear goals that are defined within existing and future policies at EU and international level, should allow for regional differentiation in indicators; these being the outcome of negotiations between farmers or their representatives, policy makers and researchers. (C) 2003 Elsevier Ltd. All rights reserved.

Differences in land use history among taxonomically identical soils often result in different hydraulic properties, derived from either laboratory measurements or pedotransfer functions (PTFs). Additionally, flow mechanisms in sandy soils may also change through differences in water repellency associated with land use history. The soil water regimes for three sandy soils of the same taxonomic unit and under pasture but with differences in land use history were simulated. The land use histories were old grassland (site A), recently reseeded grassland (site B) and previous maize-cultivated land (site C). Degrees of water repellency, as indicated by the Water Drop Penetration Time (WDPT) test, were found to be highest for the topsoil of sites A and B. Initial simulations, using continuous pedotransfer functions to derive the Mualem-Van Genuchten parameters, corresponded poorly with field measurements (TDR). Additional laboratory measurements did not result in a better correspondence. Taking account of preferential flow in sites A and B, using the mobile/immobile concept, improved modelling performance significantly. Model simulations for a limited time period showed that water storage in the top 50 cm was on average 59 mm higher for site C compared with site A, and 23 mm higher for site B compared with site A. Downward fluxes at 50-cm depth were especially larger for site A compared with sites B and C. (C) 2002 Elsevier Science B.V All rights reserved.

This paper aims to contribute to an analysis of the historical developments in soil science, confined to the broad relations between soil science and developments in society in the Dutch or Western European context. It summarizes the major developments during the past 50 years and provides some notes on the future of soil science.

In the 1970s and 1980s much progress has been made in studying agricultural production systems by using simulation modelling of agronomic processes. The International Benchwork Sites Network for Agrotechnology Transfer (IBSNAT) group in the USA and the group around Professor Kees De Wit in Wageningen were active in this new area of research which created an important ‘niche’ within the agricultural sciences because of its integrative, interdisciplinary character and its focus on quantitative, process-based approaches. A first joint scientific meeting of the two groups was held in Bangkok in 1991 (SAAD1 conference: Systems Analysis for Agricultural Development). At the SAAD2 conference at IRRI in 1995, in which also other groups took part, notably the Agricultural Production Systems Research Unit (APSRU) group from Australia, the International Consortium for Agricultural Systems Applications (ICASA) was established as a forum for researchers engaged in the study of agricultural systems at different spatial scales ranging from fields, farms to regions and beyond. The ICASA is an informal network with a focus on three major activities: (1) sharing experiences and joint development of compatible software allowing more widespread use of models having been developed by various member groups; (2) organization of joint courses on different aspects of dynamic modelling of agricultural production systems. There is an increasing interest in such courses, also in developing countries, and local researchers increasingly take an active part in them; and (3) joint research on projects dealing with dynamic characterization of agronomic production systems at different spatial scales. ICASA researchers take part in eco-regional methodology development, through projects that are funded by the Dutch and Swiss governments, with ISNAR acting as the administrative agency. ICASA intends to be an effective platform on which researchers, stakeholders and policy makers can interact.

Simulation modelling is an important tool in evaluating the economical and environmental effects of different farm management practices. Availability and quality of input data are crucial factors that determine the accuracy of modelling results. With respect to soil water regimes, much depends on the accuracy of soil hydraulic properties. These are conventionally derived through expensive laboratory measurements. Pedotransfer functions have been developed to increase cost effectiveness: hydraulic properties are estimated using basic soil properties that can be measured with relative ease. This study compares four methods to derive hydraulic properties by analysing their effect on simulated soil moisture contents. Applied methods include: (A) laboratory measurements, (B) class pedotransfer functions, (C) continuous pedotransfer functions and (D) continuous pedotransfer functions combined with simple laboratory measurements. Modelling performance was evaluated by comparing simulated and measured soil moisture contents for three sites and two depths. Modelling uncertainty was evaluated through Monte Carlo simulations. The combination of continuous pedotransfer functions and simple laboratory measurements (method D) clearly produced best results. Modelling performance was highest overall and results were consistent for individual profiles and depths. Modelling uncertainty was lowest, far lower than the uncertainty resulting from the measured data set (method A). Based on these results, a general procedure was defined to combine continuous pedotransfer functions with simple soil physical measurements.

Many soil scientists feel that their expertise is not being used sufficiently when politicians, interdisciplinary research teams, and various other stakeholders address modern environmental and land-use issues. However, taking a proactive rather than a reactive approach and developing and presenting their expertise in a more productive manner would be a more effective response. This requires innovative approaches. To cope better with conditions in our modern network society, soil scientists must learn to listen to and to communicate with their stakeholders, but, more importantly, they must also learn to present their expertise in a flexible manner and, from the beginning, become thoroughly engaged in settings of joint learning and negotiation.

The complexity of agricultural systems and the need to fulfil multiple objectives in sustainable agro-ecosystems call for interdisciplinary analyzes and input from a wide variety of disciplines in order to better understand the complete agronomic production system. Systems approaches have been developed to support these interdisciplinary studies; their development and use have increased strongly in the past decades. Agronomic systems have pronounced spatial and temporal dimensions. Spatial aspects can be distinguished at crop, field, farm, regional and higher levels while processes at each spatial level have characteristic temporal components. Systems analysis in agronomic systems implies the use of various types of knowledge, such as expert knowledge including stakeholder expertise and knowledge derived from scientific measurements and model-simulations. The latter two can be derived from different types of studies: simple, rapid and cheap procedures, which are often relatively unreliable, at one end of the scale and complex, cumbersome and expensive data-intensive procedures at the other end. Selection of proper procedures for specific issues, both in terms of measurements and in applying simulation models, needs attention. Each problem requires its own research approach. Based on the output requirements and data availability, the proper systems approach has to be selected. Examples of these different procedures are given in this paper. Considering the type of problems to be studied in agronomic systems, different procedures can be followed to address the issues raised at a specific scale. These procedures start with a proper analysis of the system followed by studies that are projectory, exploratory, predictive, or are focused on decision support. Examples will be provided. Increasingly, systems approaches include stakeholders to fine-tune problem definition, the research itself, and the implementation of results. Stakeholders are farmers and citizens on farm and community levels and policy makers and planners at higher levels of aggregation. A comprehensive interdisciplinary analysis of agricultural production systems is seen as a necessary condition for the development of innovative, sustainable systems for the future. Systems for improving crop production systems are presented in this paper as well as applications of systems approaches at the farm and regional levels with emphasis on selecting the right approach.

Environmental and market constraints are increasingly restraining the banana sector in Costa Rica. This chapter reports on the development of a decision support system to enhance a more environment- friendly and economically viable production of banana. The system has been developed in close cooperation with a banana producer and the National Banana Corporation (CORBANA; CORporacion BAnanera NAcional). The system is based on the principles of precision agriculture, a practice that is being promoted as an alternative form of land management resulting in an economically feasible and environmentally friendly type of agriculture. In precision agriculture spatial and temporal variation in cropping conditions govern farm management. The objective is to obtain maximum quantities of high quality produce without exceeding threshold values of certain environmental indicators. Although precision agriculture is often based on advanced equipment, information technology and deterministic simulation models, in tropical environments and for perennial crops advanced equipment and simulation models are not always available. The decision support system that has been developed is therefore based on information technology in combination with the knowledge of the owner and manager of the farm. Yield maps are being created and linked to other available information for the plantation, including detailed soil maps. Next, areas are identified that have a relatively low production compared to their potential. On the basis of additional analysis, crop management for those sites is modified.

This chapter provides an overview of the various methodologies for land use analysis presented in this book. It starts with a discussion of objectives, structure, terminology, levels of analysis, and aggregation issues. The methodologies are classified in five groups, (i) projective, (ii) explorative, (iii) predictive, (iv) generative and (v) design-oriented. Whereas the first three involve land use analysis on (sub-)regional to national scales, the fourth quantifies actual and alternative land use systems, and the fifth provides completely new farm or field management designs. The terminology used in all methodologies closely follows the one originally suggested by the FAO. The land use methodologies cover a series of spatial scales — or levels of analysis — and aggregation issues, involving the land use system, farm, sub-region, region and nation. For all methodologies, the implementation domain is explicitly specified, as well as their mutual complementarity and role in agricultural policy support. Together, the methodologies form a coherent toolbox to support policy design by analyzing (i) current land use, (ii) likely changes in future land use and their drivers, (iii) technical options for future land use, and (iv) policies intended to induce land use changes in the (near) future. Sustainability issues addressed are related to the goals of “maintaining the resource base”, “protecting the environment” and “optimizing non-renewable resource use efficiency”. Whereas the first two concepts are mainly biophysical in nature, the latter focuses more on economics. Specific biophysical sustainability indicators relating to the first two concepts were derived from relevant sustainability issues in the Atlantic Zone of Costa Rica, and implemented in the generative, explorative and predictive methodologies. Finally, reflections are offered on the importance of user involvement in both the development and the application of land use analysis methodologies for successful policy support.

This paper focuses on possibilities for using a simple scoring technique to make estimates of millet yield. Estimates are intended to be used for defining application rates of manure in the context of low-tech precision agriculture. Yields from 1995 and 1996 at three locations were related to scoring, soil data and elevation. Kriging was used to interpolate point data to areas. Several procedures for pattern comparison were applied. Because scoring data were available at a much higher density than yield data a sensitivity analysis was made to compare scoring and yield. Correlations between scoring and yield ranged from 0.42 to 0.91. During a separate experiment the optimal time for scoring turned out to be approximately 3 months after seeding for the local varieties of 120 days, but 2 months is convenient for farmers to locally apply chemical fertilizer. R2 values ranging from 0.15 to 0.60 were observed for soil data and yield, subject to local conditions and changes in weather. We conclude that scoring is a cheap and reliable procedure to identify field patterns which can form the basis for precision agriculture.

A long history of increases in population pressure in Java has caused agricultural land use to expand and intensify. More recent land use changes caused the conversion of prime agricultural land into residential and industrial area. Results of a dynamic, regional-scale, land use change model are presented, defining the spatial distribution of these land use changes. The model is based on multi-scale modelling of the relations between land use and socio-economic and biophysical determinants. Historical validation showed that the model can adequately simulate the pattern of land use change. Future patterns of land use change between 1994 and 2010 are simulated assuming further urbanization. The results suggest that most intensive land use changes will occur in Java's lowland areas.

Within-field spatial variability of pearl millet (Pennisetum glaucum) was studied at three different sites on Alfisols in Niger. Grain yields in fields on a North-South gradient were 8-383, 2-1343, 7-815 kg/ha, with a coefficient of variation of 61, 55, and 53%, respectively. Variability was explained by soil chemical factors for only 5 to 28%. A simple method of scoring millet growth for individual hills a few weeks before harvest was tested by measuring yield variability in a field as an alternative for expensive soil chemical analyses. The median score value explained 25, 67, and 8% of the variability for the same gradient, respectively. As a verification step, map pattern comparisons of millet grain and straw yields with median score values gave low taxonomic distances (0.01-1.7), indicating significant similarities in variability. The hill scoring method is an appropriate tool to identify millet grain and straw yield variability.

Macroporosity influences the dynamics of water and dissolved solutes in the soil. Size, shape and continuity of macropores is affected by soil management. In this study, dye staining technique, followed by digital image processing, are used to quantify macroporosity under field conditions in a short time at low cost. We compared 17 macroporosity parameters, in 55 staining patterns from three fields with different soil management types at five depths, within one soil type. Factor analysis indicates that five factors explain 95% of the variation. The first factor equals the ‘pore extent’, and was similar for the three fields, but showed significantly lower values with increasing depths. The second factor is the ‘individual pore size’, and the third factor the ‘shape’ of the pores. Both were influenced by soil management. Factors four and five were equal to the range and the nugget of the indicator variogram, respectively. We concluded that the most appropriate parameters to quantify staining patterns in an explanatory analysis are the number of pores, the average area per pore and the pore-shape, whereas the best parameter to quantify staining patterns with only one characteristic is the fractal dimension D s .

During the 1994 International Congress of soil science in Mexico, a special session was devoted to the future of soil science. This session resulted in a statement on proposed activities to: “Seize opportunities for soil science and its applications in the 21st century” [2]. Some key elements of this statement refer to broadening of soil science constituents beyond traditional agricultural patterns and expansion of the focus of soil science to include ecosystem management, sustainability of the biosphere, environmental protection and the urban environment. A more holistic interdisciplinary approach to soil systems was proposed and it was advocated that a definition of soil quality be established, because soil quality is identified as a key indicator of environmental health. To obtain a state-of-the-art picture of interdisciplinary research in the context of soil quality and to inspire future research activities, three working groups of the ISSS have organized a workshop with integrated case studies on soil and water quality, with special emphasis on scale aspects. The title of the workshop was, therefore: “Soil and water quality at different scales”. In this paper some relevant definitions will be presented and the general scope of the problem being considered will be discussed. Also, major conclusions and recommendations of the workshop will be presented.

A study was designed to compare the performance of six spatial interpolation methods to estimate soil properties at unvisited points. These methods were global mean, moving average, nearest neighbour, inverse squared distance, Laplacian smoothing splines and ordinary point kriging. These methods were also applied in combination with a choropleth map (soil map) by stratifying the area. The soil properties estimated were thickness of A1 horizon, maximum areic mass of phosphate adsorbed by soil, mean highest water table and mean lowest water table. The performance of the methods was measured by estimating the spatial means of the squared and absolute error (quality criteria not conditional on the sample of test points) by a stratified simple random sample of test points. The mean squared error was very large in proportion to the spatial variation over the total area for all methods and properties. Differences between methods were small. In general, no statistically significant stratification or weighting effects were found. The effect of weighting plus stratification was usually not significant either. Overall, weighting with inverse squared distance was as satisfactory as weighting by ordinary point kriging. However, the latter was superior near data points. Also, when combined with soil map stratification, kriging was more reliable in the sense that it estimated all properties well. Estimates obtained using the means of six soil map units were better, although not significantly, than those obtained from unstratified kriging and as good as kriging within three map units.

Soil surveys have now been completed in many countries and qualitative interpretations in terms of soil suitability for different forms of land use, which are part of most soil survey reports, are being used widely. These interpretations are, however, essentially based on expert judgement and they are inadequate to answer many modern questions about ecological and environmental aspects of alternative forms of land use. Simulation modeling of solute transport and plant growth has become an operational tool in land use studies and soil survey databases can be an important source of basic soil and landscape information to be used in modeling. Still, many data are not in a form that can be used directly and an effort has to be made to transform soil survey data into a usable format, by developing pedotransfer functions. In discussing soil survey data, a distinction can be made between point- and area data. Case studies for leaching of nitrates (NO 3 - ) and growth of potato (Solanum tuberosum L.) in a loamy and clayey soil, illustrate use of different types of class-pedotransfer functions for functional soil horizons. Monte Carlo techniques are used to illustrate the effect of variability of hydraulic basic data on results obtained. Soil surveys define soil data and interpretations for areas of land by considering representative soil profiles for delineated areas on the map. Internal variation is expressed only in qualitative terms. Geostatistical techniques can be used to interpolate point data to areas of land, allowing quantitative expressions including error statements. The effects of upscaling of point data to cells of different sizes on leaching of NO 3 - and growth of potato are illustrated for data derived from a Dutch field. All illustrations demonstrate the crucial role of Geographic Information Systems (GIS) in storing and manipulating basic soil and landscape data.

The data crisis in scenario studies embodies topics such as (i) the relevance of existing data for current and forthcoming models; (ii) deciding on the use ofexisting soil data or sampling new data ; (iii) the sensivity of models to several sources of uncertainty in model inputs and consequences for data sampling; (iv) pragmatic approaches to the data crisis; and (v) the presentation of uncertain model results. In all these topics, the magnitude of the data crisis with respect to any parameter is a function of the spatial and temporal variability of this parameter, and of the sensivity the simulation model shows to this variability. The five topics are addressed using case studies and literature rev iews for illustrative purposes. Conclusions drawn with respect to the above topics, are : (i) soil data have merely an identification function when used with conceptual models, but have an estimation function too with implemented models; (ii) existing soil data may not be representing soil bodies unbiasedly, in which case probability sampling in combination with simulation modelling is a proposed method to select representative data based on soil behaviour; (iii) an uncertainty analysis of a model is a useful method to obtain sampling priorities; (iv) Pragmatic solutions to the data cris is exist in the field of exogenous model inputs, model initialisation and obtaining values for process parameters; (v) the presentation of results of scenario studies in terms of probabilities enables the incorporation of the effects of several sources of uncertainty and hence is a powerful method to be further developed.

Geographical Information Systems can be used for processing spatial data to assess the risks of environmental contamination. Their use depends upon the amount and quality of available data, the models for interpolation and calculation of health risk, data processing procedures and interactivity. In this study, it is shown that interactive use of GIS is important for obtaining physically relevant results. Three forms of interactivity are distinguished: interactivity by means of user interfacing, interactivity requiring additional information outside GIS and interactivity when changing the use of GIS. Three stages in which interaction with GIS are crucial can be distinguished: application of geostatistics, choice of appropriate models, and decision making. This study focuses on three cases in The Netherlands dealing with soil contamination and soil stress analysis and with implications for risk assessment in which interactivity within GIS is analysed. Emphasis is given to contour volumes of pollute...

Reducing water losses through bypass flow is important in rice-growing areas (rainfed and irrigated) where water losses during land preparation for rice are high owing to soil cracking on the surface and a relatively permeable subsoil. Bypass flow processes were studied in a cracked, previously puddled rice soil. Vertical continuity of soil cracks (10-10 mm in width) was determined in the field using a morphological staining technique. Cracks reached a depth of 0.65 m. An infiltration experiment showed that water was mainly absorbed in the subsoil between 0.2 and 0.5 m epth. In a laboratory experiment, simulated rainfall was applied to large undisturbed soil columns taken from the field. High bypassing ratios (greater than 0.9) were obtained for low (10 mm h−1) and high (30 mm h−1) rain intensities. Shallow surface tillage (0–50 mm) in the field reduced bypass flow, and laboratory experiments showed 45–60% water savings as a result of making the cracks discontinuous. For rainfed rice areas, introduction of this tillage practice may lead to earlier transplanting and therefore reduced risk of late drought. In some areas this may broaden the scope for a second crop. In irrigated rice systems, water savings during land preparation may allow an increase in the command area of an irrigation system.

Growing demand for soil-specific fertilizer management is currently met with about 100 variable-rate fertilizer applicators. One company alone in 1992 contracted 28,000 ha for variable-rate application. Data from several states indicate variable-rate programs cost $10 to $17/ha more than conventional single-rate-per-field programs. Savings from decreased fertilizer use, or returns from higher yields, usually met or exceeded costs even without accounting for environmental benefits. GIS/GPS technology, environmental legislation, and precise field navigation possibilities encourage further development of soil-specific farming practices. Future developments require low cost site-specific data, real-time simulations of soil water and decision support systems and more quantitative studies on economical and environmental benefits.

A land evaluation at farm level was made for a toposequence of three New York soils, using the FAO framework and the LEACHN simulation model. The land utilization type (LUT) was continuous corn, using three varieties with different growing periods. Ten experts identified the same land qualities but three different types of land characteristics, as derived from soil survey data, field observations and simulation modelling. Differences could be explained by the backgrounds of the experts. A land evaluation procedure according to framework criteria using decision trees rather than matching tables was more accessible and transparent. Simulation of the soil-water regime provided quantitative data for all land qualities considered, and this procedure was preferred to qualitative estimates based on poorly defined procedures. When some land qualities cannot be characterized by simulation, however, a mix of qualitative and quantitative decision tree branches may be considered. The standard scheme of land evaluation, which is scale independent, provides irrelevant results at farm level because farmers’ questions are different from those of regional planners who are well served by the traditional land evaluation procedure. For the farmer, development of decision support systems should be focused on optimal management decisions.

Systems approaches for agricultural development can be realized at different levels of detail which are associated with different data needs. For soils five levels were defined, ranging from farmer’s knowledge and expert systems to use of complex simulation models. Any problem to be studied should be analyzed thoroughly beforehand and the most appropriate level of study should be established for each discipline. Field monitoring of soil physical conditions, which is crucial for model calibration and validation, becomes increasingly important at higher levels of detail. Monitoring should be increased, paying due attention to soil profile characteristics during installation of equipment. Measurements of physical parameters needed for simulation should preferably be made in situ, using methods that are relatively simple, accurate and low-cost, such as the crust-test infiltrometer. Pedotransfer functions, which relate available soil data to parameters needed for simulation, are a potentially important source of basic soil data and should be further developed. One type of pedotransfer function uses pedogenic soil horizons from soil surveys as ‘carriers’ of data. This approach is illustrated for both a small scale and a large scale soil survey carried out in the Philippines. Field work is needed to better characterize ‘non-ideal’ soil behaviour due to soil heterogeneity, which is quite common and is as yet not covered by existing models which assume soils to be homogeneous. Soil input is not only relevant for obtaining point data but also to assist in obtaining results that are representative for areas of land. Geostatistics can make contributions towards developing efficient sampling schemes which base the number of observations on spatial heterogeneity and not on the scale of the map to be made. Geostatistics was used successfully to interpolate point data to areas of land, including estimates of accuracies, as is illustrated for a case study at the International Rice Research Institute.

The effects of different soil management systems on soil structure and associated physical properties in a Dutch clay loam soil were evaluated using a combination of simulation modelling, field investigations and laboratory experiments. The investigations were focused on field recognition of identical soils only differing in structure type caused by soil management systems. Two soil structure types were recognised: a type developed in permanent grassland and a type in young arable land, which had been used for intensive vegetable growing since 1979. The types were characterised by examining the micro- and macro-morphology and soil hydraulic properties, such as soil structure, rooting patterns, pore shape and size distribution, bypass flow and water retention and unsaturated hydraulic conductivity characteristics. Field recognition of structure types and subsequent morphological and physical characterisation was used as an alternative to the application of a machine-soil submodel. Significantly different properties of both soil structure types were functionally interpreted by using a simulation model for the soil-plant subsystem. Morphological and hydraulic analyses were essential for the definition of proper boundary conditions and input parameters. The land qualities water deficits, workability and soil aeration were calculated for a potato crop under Dutch climatological conditions. Expressions for temporal variability were obtained by using a 30 year record of weather data. The soil structure of permanent grassland proved to be more favourable than that of young arable land. This resulted in a 10% decrease in the average annual water deficit, 40% more workable days in the planting phase and 5–10% more days with a well-aerated soil. The impact of these differences on the potato tuber yield interpreted in terms of the effect of soil structure degradation, was estimated to be at least 5% in 20 out of 100 years under Dutch climatic conditions. The differences calculated also equalled the maximum possible effect of soil structure regeneration.

A mixed qualitative/quantitative physical land evaluation methodology is proposed. This mixed approach comprises both qualitative and quantitative methods. The screening of land for serious constraints associated with a defined land utilization type is carried out by qualitative methods based on computer-captured expert knowledge. Subsequently, the more comprehensive quantitative evaluation methods, using computer models to simulate soil-water flow and crop growth, can then be focused on remaining, potentially suited land. The mixed qualitative/quantitative evaluation approach is exemplified with potato-growing in the Netherlands. Decision trees, illustrating how expert knowledge was used to infer potentially suited land from land qualities, are shown. This way, about 65% of Dutch land was found to be potentially suited. This amount turns out to depend on the used soil map. Complex simulation models were used for a quantitative analysis of two potentially suited areas with contrasting soils, namely Calcaric Fluvisols and Humic Podzols. Probability distributions of the land qualities workability and crop water deficit and of the physical suitability expressed as potato tuber yield were determined. The mixed evaluation predominantly uses geographically referenced input data. Therefore, a linkage with geographical information systems (GIS) is a prerequisite for efficient use. After storage in a GIS, some recent projects showed that the mixed approach saved 50%–70% time compared with application of the quantitative evaluation method to all units.

Fifty-six infiltration rate (IR) measurements were made in puddled clay soil in a 0.05 ha experimental rice field consisting of 16 subplots, following a standard stratified sampling scheme. Log-transformed IR measurements were approximately normally distributed. Analysis of stationarity revealed the absence of a trend, whereas estimating the coefficients of the covariance function revealed a pure nugget effect, indicating spatial independence. A sequential t -test was used to determine the number of measurements that is sufficient to characterize the average rate of infiltration in the experimental plot under study. Results showed that 8 measurements yielded mean estimates that were not significantly different with 95% confidence from results obtained using all 56 measurements. Application of the test thus resulted in an 85% saving of measurement effort as compared with the original sampling scheme. The question of the design of the measurement scheme, i.e., which of the 8 measurements to select is addressed by means of selecting all possible combinations of the 8 observations among the 16 subplot centres, and calculating the mean squared error (MSE) and the mean variance of the prediction error (MVP) in a test set consisting of the 40 other measurements. The risk of taking an inappropriate configuration is relatively small as compared to the actual mean value to obtained.

A technique is presented to measure in-situ infiltration rate and pressure head gradients within a puddled rice soil. Measurements at 33 sites within a small 0.1 ha plot indicated unsaturated flow conditions in the non-puddled subsoil. The least permeable layer within the profile, as determined by the greatest gradient in pressure head, was found to be at the interface of puddled topsoil (0–15 cm) and non-puddled subsoil. Average thickness of this layer was about 5 cm. Hydraulic resistance of the least permeable layer at all measurement sites was lognormally distributed with an average value of 209 days, and 95% confidence limits at 156 and 262 days. Corresponding average hydraulic conductivity was 0.36 mm day −1 with 95% confidence limits at 0.27 and 0.45 mm day −1 . Measured pressure heads in the subsoil showed good agreement with values predicted from comparison of measured hydraulic resistance in the puddled surface soil and non-puddled subsoil. Puddling reduced infiltration rate by a factor of 500.

Simulation models for calculating moisture deficits for areas of land require interpolation procedures to arrive from point observations to area-covering statements. We use both (1) calculate first, interpolate later (CI) procedures, which interpolate calculated model results for test locations, and (2) procedures which interpolate basic soil data toward test locations, followed by model calculations, interpolate first, calculate later (IC) procedures. In this study several CI and IC procedures which simulate moisture deficits are compared by means of a test set of 100 observations, yielding the mean standard error (MSE). CI procedures consistently produced lower MSE values than IC procedures. Parameters of the pseudocovariance function (PCF), which models the spatial structure of bivariate increments in universal cokriging, were estimated by means of the restricted maximum likelihood procedure. Compared to universal kriging, universal cokriging yielded comparable MSE values, but a lower mean variance of the prediction error. Best results in this study were obtained by pointwise simulation model calculations, followed by statistical interpolations.