Soil Water and Agronomic Productivity (Advances in Soil Science)

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References and Recommended Reading

Obviously, only computer simulations can be used when exploring future conditions — another important reason to use dynamic simulation modeling in the context of characterizing soil quality and soil health. The approach in this paper extends earlier studies on soil quality for some major soil types in the world that did not consider aspects of soil health nor effects of climate change Bouma, ; Bouma et al.

The soil—water—atmosphere—plant model Kroes et al. SWAP is an integrated physically based simulation model of water, solute and heat transport in the saturated—unsaturated zone in relation to crop growth. In this study only the water flow module was used; it assumes unidimensional vertical flow processes and calculates the soil water flow through the Richards equation.

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The unit gradient was set as the condition at the bottom boundary. The upper boundary conditions of SWAP in agricultural crops are generally described by the potential evapotranspiration ET p , irrigation and daily precipitation. The water uptake and actual transpiration were modeled according to Feddes et al. The model was calibrated and validated by measured soil water content data at different depths for Italian conditions Bonfante et al. Simulations were run considering a soil without assumed degradation phenomena the reference and for three variants with a compacted plow layer, surface runoff and erosion, as discussed above.

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Runoff from the soil surface was simulated removing ponded water resulting form intensive rainfall events. Variants were theoretical but based on local knowledge of the Sele Plain. Compaction is relevant considering the highly specialized and intensive horticulture land use of the Sele Plain which typically involves repetitive soil tillage at similar depth.

The main agricultural production consists of irrigated crops maize, vegetables and fruit orchards , greenhouse-grown vegetables and mozzarella cheese from water buffalo herds. The area can be divided into four different landform classes foothills, alluvial fans, fluvial terraces and dunes with heterogeneous parent materials in which 20 different soil series were distinguished within Inceptisol, Alfisol, Mollisol, Entisol and Vertisol soil orders Regione Campania, , according to Soil Taxonomy Soil Survey Staff, Six soil series were selected in the area to test application of the soil quality and soil health concepts.

Decision trees were developed to test whether the selection process of the soil series was based on stable criteria, allowing extrapolation of results from measured to unmeasured locations when considering effects of climate change. While extrapolation in space of soil series data has been a common procedure in soil survey e. A basic principle of many taxonomic soil classification systems is a focus on stable soil characteristics when selecting diagnostic criteria for soil types.

Also, emphasis on morphological features allows, in principle, a soil classification without requiring elaborate laboratory analyses e. A given soil classification should, in order to obtain permanent names, not change following traditional management measures, such as plowing. This does, however, not apply to all soils and therefore a different name will have to be assigned. This way, soil classification results in an assessment of the semi permanent physical constitution of a given soil in terms of its horizons and textures.

That is why soil quality is defined for each soil type as a characteristic range of Yw values, representing different effects of soil management that have not changed the soil classification. The validations performed showed that these model data agree closely with different regional high-resolution observational datasets, in terms of both average temperature and precipitation in Bucchignani et al.

In particular, the Representative Concentration Pathway 8. The simulations covered the period from to ; more specifically, the CMIP5 historical experiment based on historical greenhouse gas concentrations was used for the period — reference climate scenario — RC , while for the period —, a simulation was performed using the IPCC scenario mentioned. The reliability of this equation in the study area was performed by Fagnano et al. The Yp potential yield is the maize production for the Destra Sele area assuming optimal irrigation and fertilization and no pests and diseases.

Yp is only calculated for the reference climate. The differences in temperature between RC and the period — showed an average increase in minimum and maximum temperatures of about 6. The projected increase in temperatures produces an increase in the expected ET 0. Considering current climate conditions, the Longobarda and Cifariello soils with loamy textures have the highest values, while the sandy soil Lazzaretto is lower.

The effects of climate change are most pronounced and quite clear for the two periods after This follows from the important reduction of projected rainfall during the cropping season Fig.

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Only a Yp value is presented for current conditions because estimates for future climates involve too many unknown factors. The projected effects of soil compaction are shown in Fig. The effects of compaction are very strong in all soils, demonstrating that restricting the rooting depth has major effects on biomass production.

Clearly, any effort to increase the effective rooting patterns of crops should be a key element when considering attempts to combat effects of climate change. Data indicate that reactions are soil specific. Other terms are explained in Fig. Runoff occurs when rainfall intensity is higher than the assumed infiltrative capacity of the soil. Results presented in Fig.

Effect of Surface Residues on Soil Water Storage

This implies that surface crusting or compaction of surface soil, leading to lower infiltration rates and more surface runoff, does not seem to have played a major role here in the assumed scenarios. Real field measurements may well produce different results. Even though projected future climate scenarios predict rains with higher intensities that were reflected in the climate scenarios being run, the effects of lower precipitation, as shown in Fig.

Soil quality for a given soil is thus represented by a characteristic range of values. Soil health is indicated by the particular location of an actual Ya within this range. Yw values are lower in all soils as compared with reference climate conditions, but loamy and clayey subsoils still can still provide moisture to plant roots, leading to relatively low reductions of Yw e.

But Van Ittersum et al.

Agronomy and water management

This provides important signals for the future. As discussed, the presented ranges are soil specific and are based on hypothetical conditions associated with different forms of land degradation. Field research may well result in different ranges also possibly considering different soil degradation factors beyond compaction, surface runoff and erosion. Nevertheless, principles involved are identical.

Ranges presented in Fig. Actual values Ya will fit somewhere in this range and will thus indicate how far they are removed from the maximum and minimum value, thereby presenting a quantitative measure for soil physical health. This cannot only be important for communication purposes but it also allows a judgment of the effects of different forms of degradation in different soils as well as potential for improvement. Of course, different indicator crops will have to be defined for different areas in the world.

Linking soil quality and health to specific and well-defined soil types is essential because soil types, such as the soil series presented in this paper, uniquely reflect soil-forming processes in a landscape context. They provide much more information than just a collection of soil characteristics, such as texture, organic matter content and bulk density.

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They are well known to stakeholders and policymakers in many countries. A good example is the USA where state soils have been defined.

Associated Data

Defining semipermanent soil quality for specific soil types, in terms of a characteristic range of Yw values reflecting effects of different forms of land management, represents a quantification of the more traditional soil survey interpretations or land evaluations where soil performance was judged by qualitative, empirical criteria. In this exploratory study, hypothetical effects of three forms of soil degradation were tested. In reality, soil researchers should go to the field and assemble data for a given soil series as shown on soil maps, establishing a characteristic range of properties, following the example of Pulleman et al.

This way, a characteristic series of phenoforms can be established. Physical soil quality for a given soil type, which is the genoform has a characteristic range of Yw values, as shown in Fig. One could argue that this range acts as a thermometer for a particular type of soil allowing the determination of the physical health of a given soil by the placement of Ya. But calculating Yw has implications beyond defining physical soil quality and health.

As discussed, Yw not only reflects the effects of soil moisture regimes but also assumes that chemical conditions for crop growth are optimal and that pests and diseases do not occur. Defining Yw can thus function as a starting point of a general soil quality and soil health discussion. If Ya is lower than Yw the reasons must be found. Is it lack of water, nutrients, or occurrence of pests and diseases? Irrigation may be difficult to realize but fertility can be restored rather easily and many methods, biological or chemical, are available to combat pests and diseases.

This way, the Yw analysis can be a logical starting point for follow-up discussions defining appropriate forms of future soil management. This paper has focused on physical aspects but the proposed procedure has the potential to extend the discussion to chemical and biological aspects, to be further explored in future. Rather than consider the physical, chemical and biological aspects separately, each with their own indicators as proposed by Moebius-Clune et al. This is more relevant because the definition of reproducible biological soil health parameters is still an object of study Wade et al.

Recent tests of current soil health protocols have not resulted in the adequate expression of soil conditions in North Carolina Roper et al. Lack of widely accepted, operational criteria to express soil quality and soil health is a barrier for effective external communication of the importance of soil science. Using well-defined soil types as carriers of information on soil quality and soil health can improve communication to stakeholders and the policy arena.

A universal system defining soil quality and soil health is needed based on reproducible scientific principles that can be applied all over the world, avoiding a multitude of different local systems.

Soil Water and Agronomic Productivity (Advances in Soil Science) Soil Water and Agronomic Productivity (Advances in Soil Science)
Soil Water and Agronomic Productivity (Advances in Soil Science) Soil Water and Agronomic Productivity (Advances in Soil Science)
Soil Water and Agronomic Productivity (Advances in Soil Science) Soil Water and Agronomic Productivity (Advances in Soil Science)
Soil Water and Agronomic Productivity (Advances in Soil Science) Soil Water and Agronomic Productivity (Advances in Soil Science)
Soil Water and Agronomic Productivity (Advances in Soil Science) Soil Water and Agronomic Productivity (Advances in Soil Science)
Soil Water and Agronomic Productivity (Advances in Soil Science) Soil Water and Agronomic Productivity (Advances in Soil Science)

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