Carbo-pro: A simulation model to manage soil organic matter through compost applications

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matter through compost applications

Clément Peltre, Jérémie Doublet, R. Biquillon, A. Pereira, Claire Lhoutellier, M. Agenis-Nevers, Sabine Houot

To cite this version:

Clément Peltre, Jérémie Doublet, R. Biquillon, A. Pereira, Claire Lhoutellier, et al.. Carbo-pro:

A simulation model to manage soil organic matter through compost applications. The 8th ORBIT conference Global assessment for organic resources and waste management, Jun 2012, Rennes, France.

�hal-01757719�

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CARBO-PRO: A SIMULATION MODEL TO MANAGE SOIL ORGANIC MATTER THROUGH COMPOST APPLICATIONS C.Peltre, J.Doublet, R. Biquillon, A. Pereira, C. Lhoutellier, M. Agenis-Nevers, S. Houot

CARBO-PRO: A SIMULATION MODEL TO MANAGE SOIL ORGANIC MATTER THROUGH COMPOST APPLICATIONS

C. Peltre

¹

, J. Doublet

²

, R. Biquillon

²

, A. Pereira

²

, C. Lhoutellier

²

, M. Agenis-Nevers

²

, S. Houot

¹

(1). INRA EGC Soil, 78850 Thiverval Grignon, France, (2) VEOLIA Environnement R&I, 78 Limay, France.

CONTACT: Dr. Sabine Houot, INRA EGC Soil, 78850 Thiverval-Grignon, France, Tel:

+33130815401, [email protected] EXECUTIVE SUMMARY

The decline in soil organic C (SOC) content leads to reduced fertility and biological activity and reversely to greater susceptibility of soil to erosion. The loss of SOC has been identified as a major threat towards the soil resource. In addition, soils account for one of the largest terrestrial C reservoirs and small but consistent increases in SOC stocks could mitigate climate change effects by storing atmospheric CO2-C in soil organic matter. Annual application of exogenous organic matter (EOM) to cultivated land may lead to long continued accumulation of SOC. In Europe, recycling of organic biodegradable wastes through composting or anaerobic digestion is encouraged and is expected to increase in the future. The produced composts and digestates applied on cultivated soils differ in their potential contribution to SOC, depending on their origin and degree of transformation before being added to soil. Since C stocks change slowly, repeated applications are needed to observe an increase in SOC.

Multi-compartment models of C turnover in soil accurately simulate SOC dynamics in the long-term under different climatic conditions and soil types. RothC is one of the most widely used model that simulates SOC dynamic based on relatively few parameters and input data. In RothC, total organic C in EOM is distributed into pools of labile (DPM), resistant (RPM) and humified (HUM) organic matter according to partition coefficients (fDPM, fRPM and fHUM, respectively). Equations based on the standardized Indicator of residual organic carbon IROC have been developed to calculate the partition coefficients for any kind of EOM and then simulate the evolution of SOC after repeated applications of EOMs.

The objective of this study was to develop a web based simulation model allowing the estimation of the effect of repeated or single EOM land application on SOC storage and various associated soil properties.

The CARBO-PRO tool is based on the RothC model associated with databases of soil, EOM and climate characteristics.

CARBO-PRO makes it possible to simulate the evolution of SOC for any chosen strategy of EOM application under all French soil and climate conditions. Many soil properties are related to SOC contents, including soil aggregate stability, soil water retention, and nutrient availability. In the CARBO PRO tool, available pedotransfer functions relating aggregate stability, cation exchange capacity and water retention to SOC content have been associated to the RothC model. Thus together with SOC increase, the evolution of related soil properties is simulated for the tested scenario of EOM applications.

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1.1 Background

Soil organic carbon (SOC) constitutes one of the largest C reservoirs on earth. The amount held in the first meter of soil is approximately 1500 Gt C, that is about twice the amount of C contained in the atmosphere as CO2 (about 750 Gt C) and three times the amount of C contained in vegetation (about 500 Gt C) (IPCC, 2001). Between 1850 and 2000, the soil C pool has lost about 78 ± 12 Gt C due to land use change. In comparison, 270 Gt C were emitted to the atmosphere as CO2 due to fossil fuel combustion (Lal, 2009). In addition to land use change, Bellamy et al (2005) showed that arable land in United Kingdom and Wales tended to loose SOC between 1978 and 2003, which may be attributed to a decrease of C inputs in cultivated soils due to intensive management (Ciais et al., 2010).

Soil organic carbon (SOC) is involved in most of the functions and ecosystem services provided by the soil (Van-Camp et al., 2004). It is a key determinant for the chemical, biological and physical fertility of soil and determines its ability to ensure sustained food production (FAO, 2005). The SOC provides nutrients for plants, increases the ability of soil to retain nutrients, increases soil porosity and water holding capacity, leading to improved soil tillage and workability (Van-Camp et al., 2004).

The soil aggregate stability and thus the resistance of soil to erosion (Le Bissonnais et al., 2002) is also highly related with SOC content. For these reasons, the loss of SOC has been identified as a major threat to the quality of the soil resource in a proposal for a directive for soil protection (European Commission, 2006).

Land application of organic amendments derived from waste materials from urban, industrial or agricultural activities (referred to as exogenous organic matter: EOM) constitutes an important practice which can be used to increase or maintain SOC contents (Arrouays et al., 2002) and to improve soil properties related to SOC levels. In Europe, recycling of organic biodegradable wastes is expected to increase in the forthcoming years while decreasing waste landfilling and incineration without energy recovery (European Commission, 2010). Land application after some biological treatment (e.g. composting or anaerobic digestion with digestates production) is likely to be one of the most environmentally friendly waste management options (European Commission, 2010). However, detailed environmental assessments to allow a proper comparison with other waste management options are still lacking. Therefore it is also impossible to identify the best biological treatment in term of environmental performance. In this context, the production of quantitative applied tools allowing the effects of EOM land application to the soil quality to be estimated is urgently needed to identify the most suited waste management options.

1.2 Research objectives

The objective of this study was to develop a web based simulation model allowing estimation of the effect of repeated EOM land application on SOC storage and various associated soil properties. The developed model is based on the RothC SOC dynamics model, published pedotransfer functions and database for climatic, soil and EOM characteristics data.

2 METHODOLOGY

CARBO-PRO allows estimating of the potential C storage in soils after land application of EOM and changes in certain soil properties arising from: aggregates stability, cation exchange capacity and water-holding capacity. The C simulation model is based on the RothC carbon dynamics model (Coleman and Jenkinson, 1999; Jenkinson and Rayner, 1977) allowing to simulate the potential C storage in soil after EOM application. The simulated C storage output is then used to estimate changes in the different soil properties using pedotransfer functions (Fig. 1).

Figure 1 General scheme of CARBO-PRO

2.1 Potential carbon storage in soil after PRO applications

The RothC model describes the dynamics of soil C using three organic C pools: HUM (humified organic C, mean residence time in soil of 50 years), BIO (microbial biomass, mean residence time of 1.5 years) and IOM (inert organic C which does not degrade during the duration of simulation). When an EOM is applied to the soil, its organic C is partitioned into a pool of labile C: DPM (mean residence time in soil of 1.2 months), a more resistant C pool: RPM (mean residence time of 3.3 years), and possibly into the humified pool (Fig. 1). The necessary inputs for the model include weather and soil texture data as well

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as an indicator of EOM stability. The application includes databases providing inputs for the RothC model which are detailed bellow.

2.1.1 Weather data

The application includes monthly weather data for metropolitan France regions for the parameters: average air temperature, cumulative rainfall and potential evapotranspiration (PET) by the Penman method (Penman, 1948). The data are average values over a ten years period (2001-2010) from all weather stations within the regions. The number of weather stations ranged between 1 and 6, with a mean of 2.6. The user can also type in manually his weather data.

2.1.2 Soil texture data

Choices of soil textural classes are proposed to define the proportions of clay, silt and sand making up soil (% Sand = 100- Clay - Silt). A range of 17 soil textural classes is proposed, based on the GEPPA soil texture classification (Richer-de-Forges et al., 2008).

2.1.3 Bulk density of soil

The bulk density of soil is used to calculate soil C stocks from soil C contents and conversely, in order to apply pedotransfer functions to estimate changes in various soil properties based on C contents.

Bulk density is estimated from the clay and silt content and initial soil organic carbon using the pedotransfer function of Martin et al. (2009) implemented in the R software (R development core team, 2011). This pedotransfer function was developed from the French soil quality data network (RMQS) throughout France territory and is therefore especially well- suited to this area.

2.1.4 Organic matter quality of EOM

The C contained in the EOM is partitioned in the entry pools of the RothC model according to partition coefficients, namely fDPM, fRPM and fHUM for the proportion of C in the DPM, RPM and HUM pools respectively (Fig. 1). These partition coefficients are determined from empirical functions based on the indicator of residual organic C (IROC, Lashermes et al., 2009) which is derived from standardized laboratory characterizations of EOM (AFNOR, 2009; Lashermes et al., 2009) by the following equations (Peltre et al., 2012):

fDPM = -1.254 IROC + 115.922 fRPM = 0.979 IROC - 8.928

fHUM = 100 - fDPM - fRPM

Where IROC = 44.5 + 0.5 SOL - 0.2 CEL + 0.7 LIC - 2.3 C3d with SOL, CEL and LIC the soluble, cellulose and lignin+cutin like fractions, respectively, of the Van Soest biochemical fractionation (AFNOR , 2009a) and C3d the proportion of EOM-C mineralized after 3 days of incubation with soil under controlled conditions at 28°C (AFNOR, 2009b). The IROC values for different types of EOM are issued from a database developed in a previous study gathering biochemical characteristics of more than 400 EOMs (Lashermes et al., 2009). Alternatively, the IROC can be estimated from the biological stability index (BSI) which is an older indicator of EOM stability that is still used in France (AFNOR, 2005b; Linères and Djakovitch, 1993). When typing a BSI value, the IROC value is automatically computed according to an empirical equation developed using all EOM present in the database (R² = 0.43):

IROC = 0.6418*BSI + 36.009

2.2 Additional nitrogen mineralization

Nitrogen in EOM is present in large part in organic form, bounded to organic matter more or less stabilized against biodegradation. Therefore, only a small fraction of N provided by the EOM is immediately available for plant uptake, whereas the remaining organic part is progressively mineralized during organic matter decomposition. The amount of additional mineral nitrogen (ΔN min) released in relation with the increased soil organic matter (ΔC) is calculated by multiplying the amount of total soil nitrogen derived from EOM () by the annual coefficient of mineralization of soil organic matter (K2, second term in equation below) (Henin and Dupuis, 1945; Rémy and Marin-Laflèche, 1976) according to the equation (Comifer, 2011):

The total amount of soil nitrogen is derived from the C storage simulation output (ΔC), assuming a constant C:N ratio of 9 and using the ‘Fsyst’ factor accounting for the organic amendments application rate and level of biological stability of the EOM (Table 1). The assumption is made that crop residues are returned to the soil to half of the total amount.

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applications Never 5-10 years 3-4 years 1-2 years

Type of product Type A Type B Type A Type B Type A Type B

Fsyst factor 0.90 1.00 0.95 1.05 1.00 1.10 1.02

Type A : product with slow decomposition rate (IROC >65%) ; Type B : product with fast decomposition rate (IROC <65%)

2.3 Change in soil properties following EOM application

Increasing levels of SOC after EOM application results in many changes of soil properties such as aggregate stability, cation exchange capacity (CEC), water holding capacity etc. CARBO-PRO includes a module estimating these properties based on published pedotransfer functions.

2.3.1 Soil aggregates stability

The soil aggregates stability can be characterized by the method of Le Bissonnais (AFNOR, 2005a; Le Bissonnais, 1996) that combines slow wetting, fast wetting and mechanical breakdown tests on soil aggregates of size 3-5 mm. The size distribution of aggregates is measured after each test and the mean weighted diameter of aggregates (MWD) is calculated. The higher the MWD, the higher the soil aggregate stability is. In CARBO-PRO, the pedotransfer function of Darboux et al. (2009) is used to estimate the MWD after a fast wetting test by the method of Le Bissonnais reproducing the effect of a high intensity rainfall according to the equation:

MWD (t) = 0.34 orgC (t) + 0.008 Clay + 0.17

Where orgC and Clay are the organic carbon and clay content of soil (in %). This equation has been built from a database of 480 samples mainly from surface horizons of cultivated soils in France (Darboux et al., 2009).

2.3.2 Cation exchange capacity (CEC)

The soil cation exchange capacity is estimated in CARBO-PRO from the pedotransfer function of Manrique et al. (1991):

CEC(t) = 3.67 orgC(t) + 0.196 Clay + 3.238

With the CEC expressed in milliequivalents / 100 g soil (meq 100 g^-1), the organic C content and clay content expressed as %.

This function has been developed from over 5000 soil samples from the United States. We used it assuming that the diversity of soils used for its calculation includes the diversity of soils of metropolitan France.

2.3.3 Water holding capacity

The available water capacity or available water content (AWC in mm) is the water that can be stored in soil available for plant uptakes. It is the difference between the moisture at field capacity (θ33 in mm) and at permanent wilting point (θ1500 in mm).

The soil water retention properties are related to both its texture and its organic carbon content (Hudson, 1994, Rawls et al., 2003). The estimate of available water capacity in the topsoil horizon proposed in CARBO-PRO is based on pedotransfer functions of Rawls et al. (2003) developed from 12000 soil samples from the United States national database of soil characterization. These functions predict the water content at field capacity and at permanent wilting point (at -33 and -1500 kPa, and noted θ33 θ1500, respectively). This relation provides lower confidence for fine-textured soils having clay contents >

50% for which results should be interpreted cautiously.

2 RESULTS AND DISCUSSION 3.1 General interface

The general interface is made up with three sub-windows: two windows for data inputs (soil and EOM data) and a main window with three tables of results for soil carbon storage, soil properties and scenario comparison (Fig. 2). The top bar contains a project management menu to create and save projects containing up to 5 scenarios, buttons to switch the displayed scenario and add scenarios to the comparison tool. Additional functions make it possible to change the language

(French/English), to display information about the application and details on calculation, to e-mail the administrator or to logout.

3.2 Data input

The input data are defined using two windows: a climate and soil data window and an EOM data window (Fig. 2, left side).

Climatic data are defined by choosing a French region in a dropdown list. Soil textural class is defined in a second dropdown list. After setting the initial soil C content, the bulk density of soil is computed using the pedotransfer function previously described. Soil parameters also include calcium carbonate content and depth of the ploughed layer. In the EOM data window, a

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dropdown menu contains a range of 25 predefined types of EOM. Each type of EOM is associated with an IROC indicator value (median values ± third and first quartiles) and organic matter content. All default parameters can also be modified manually.

Other fields allow defining of the applied dose of EOM, the dry matter content, the application frequency and the month where the EOM is applied. The example in Fig. 1 presents the application of a sewage sludge compost in the Brittany region of France on a silt clay soil at the rate of 10 tons of compost applied every second year in September.

3.2 Evolution of soil carbon storage

The window presenting the potential soil C storage displays the result of the simulations drawing soil C accumulation over a period of 100 years (Fig. 2, right side). Several key values and indicators are displayed over a period which can be defined by the user (20 years in the example presented in Fig. 2: total C applied, amount of C stored, portion of applied C stored in soil and yearly rate of storage. The amount of additional N mineralized during the year for which the results are displayed (20^th in the example in Fig. 2) is also presented. All results are calculated based on the median value of the IROC indicator associated with the type of EOM previously selected. Results corresponding to the first and third quartile of the IROC value are also displayed as upper and lower curves in the figures and values between parentheses in the boxes. Detailed results can be displayed, comprising evolution of the soil C accumulation in each pool of the RothC model. The graphics can be exported as a pdf file and the numeric values of the simulations can be exported as an Excel file.

In the example presented, the application of 10 T of composted sewage sludge every second year results in the accumulation of 5.7 T of soil C per ha after 20 years, which corresponds to 41.0% of the total amount of C applied (13.8 T C ha^-1). The 20^th year after the first application, 10.7 kg ha^-1 of additional N would be mineralized.

Figure 2 General interface of the Carbo-PRO application. Data input windows (left side) and result window (right side)

3.3 Evolution of soil properties

The window on soil properties displays results of the evolution of soil properties deriving from the soil C accumulation. Three graphics are displayed for aggregate stability, cation exchange capacity, and changes in available water content after EOM application, along with boxes displaying numerical values for a period defined by the user (after 20 years of application in the

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results, soil properties results are provided with lower and upper values corresponding to lower and upper values of the IROC

indicator.

For the example presented, repeated applications of composted sewage sludge would lead to a 6.1% increase in aggregate stability (mean weight diameter of aggregates after a fast re-wetting of soil), 3.0% increase of cation exchange capacity and 0.3% of available water content.

3.4 Scenario comparison tool

The scenario comparison tool makes it possible to easily compare the results of different simulated scenarios. This screen contains bar charts with numeric value displayed at the top of the bars (Fig. 4). Each bar corresponds to a scenario previously defined. Up to five scenarios can be compared simultaneously. The comparison tool includes charts for stored C, aggregate stability, cation exchange capacity and available water content. All results are expressed as percentage of evolution compared to the initial state at the start of the simulations.

Figure 3 Soil properties result window

Figure 4 Window of scenarios comparison tool.

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4 CONCLUSION

The simulation tool developed during this study allows an easy assessment of the amount of C that can be potentially stored in soil after the application of widely different types of organic amendments and the potential associated effects on aggregate stability, cation exchange capacity and water retention. The CARBO-PRO tool comprises databases for most of the parameters necessary to conduct the simulations so that very few data are required from the user. These databases comprise data for a broad range of EOM and pedoclimatic conditions. Besides it can also be used for other types of EOM or pedoclimatic conditions not contained in the proposed databases simply by replacing the proposed input values. The interface has been designed to be intuitive and self-explanatory and also includes a scenario comparison tool allowing an easy and interactive comparison of the combined effects of different types of EOM and pedoclimatic situations. Overall the CARBO-PRO tool is likely to be useful whenever researchers, professionals of waste recycling or farmers want to assess the potential effect of EOM land application on soil carbon storage and subsequent change in soil properties.

LIST OF REFERENCES

AFNOR, (2005a): Norme NF X31-515. Mesure de la stabilité d'agrégats de sols pour l'évaluation de la sensibilité à la battance et à l'érosion hydrique. AFNOR, Paris.

AFNOR, (2005b) : Norme XP U 44-162. Fractionnement biochimique et estimation de la stabilité biologique - Méthode de caractérisation de la matière organique par solubilisations successives. AFNOR, Paris.

AFNOR, (2009) : Norme XP U 44-162. Caractérisation de la matière organique par fractionnement biochimique et estimation de sa stabilité biologique. AFNOR, Paris.

Arrouays, D., Balesdent, J., Germon, J.C., Jayet, P.A., Soussana, J.F., Stengel, P. (2002) : Stocker du carbone dans les sols agricoles de France ?, Expertise Scientifique Collective. INRA, p. 332.

Bellamy, P.H., Loveland, P.J., Bradley, R.I., Lark, R.M., Kirk, G.J.D. (2005) : Carbon losses from all soils across England and Wales 1978-2003. Nature (London) 437, 245-248.

Ciais, P., Wattenbach, M., Vuichard, N., Smith, P., Piao, S.L., Don, A., Luyssaert, S., Janssens, I.A., Bondeau, A., Dechow, R., Leip, A., Smith, P.C., Beer, C., van der Werf, G.R., Gervois, S., Van Oost, K., Tomelleri, E., Freibauer, A., Schulze, E.D. (2010): The European carbon balance. Part 2: croplands. Global Change Biology 16, 1409-1428.

Coleman, K., Jenkinson, D.S., (1999): A model for the turnover of carbon in soil, Model description and windows users guide.

IACR – Rothamsted Harpenden Herts AL5 2JQ, p. 47.

Comifer, (2011) : Calcul de la fertilisation azotée des cultures annuelles et prairies. Comifer, Paris, 92 pp.

European Commission, (2006): Proposal for a directive of the european parliament and of the council establishing a framework for the protection of soil. http://ec.europa.eu/environment/soil/pdf/com_2006_0232_en.pdf.

European Commission, (2010): Communication from the Commission to the Council and the European Parliement on future steps in bio-waste management in the European Union.

http://ec.europa.eu/environment/waste/compost/pdf/com_biowaste.pdf.

FAO, (2005): The importance of soil organic matter, key to drought-resistant soil and sustained food and production. FAO Soils Bulletins 80. ftp://ftp.fao.org/agl/agll/docs/sb80e.pdf.

Henin, S., Dupuis, M. (1945) : Essai de bilan de la de la matière organique du sol. Annales Agronomiques 15, 17-29.

IPCC, (2001): The scientific basis contribution of working group I to the third assessment report of the Intergovernmental Panel on Climate Change (IPCC), Summary for policymakers. Houghton, J.T. et al. Geneva, Swizerland, p. 98.

Jenkinson, D.S., Rayner, J.H. (1977) : The turnover of soil organic matter in some of the Rothamsted classical experiments.

Soil Science 123, 298-305.

Lal, R. (2009): Challenges and opportunities in soil organic matter research. European Journal of Soil Science 60, 158-169.

Lashermes, G., Nicolardot, B., Parnaudeau, V., Thuriès, L., Chaussod, R., Guillotin, M.L., Linères, M., Mary, B., Metzger, L., Morvan, T., Tricaud, A., Villette, C., Houot, S., 2009. Indicator of potential residual carbon in soils after exogenous organic matter application. European Journal of Soil Science 60, 297-310.

Le Bissonnais, Y. (1996). Aggregate stability and assessment of soil crustability and erodibility: I. Theory and methodology.

European Journal of Soil Science 47, 425-437.

Le Bissonnais, Y., Montier, C., Jamagne, M., Daroussin, J., King, D. (2002) : Mapping erosion risk for cultivated soil in France. Catena 46, 207-220.

Linères, M., Djakovitch, J.L. (1993): Caractérisation de la stabilité biologique des apports organiques par l'analyse biochimique. In: Decroux, J., Ignazi, J.C. (Eds.), Quatrième journées de terres et cinquième forum de la fertilisation raisonnée. GEMAS-COMIFER, Paris.

Martin, M.P., Seen, D.l., Boulonne, L., Jolivet, C., Nair, K.M., Bourgeon, G., Arrouays, D. (2009) : Optimizing pedotransfer functions for estimating soil bulk density using boosted regression trees. Soil Science Society of America Journal 73, 485-493.

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Penman, H.L. (1948): Natural evaporation from open water, bare soil and grass. Proceedings of the Royal Society of London.

Series A, Mathematical and Physical Sciences 193, 120-145.

Rémy, J.C., Marin-Laflèche, A. (1976) : L’entretien organique des terres. Coût d’une politique de l’humus. Entreprises Agricoles Nov. 1976, 63-67.

Richer-de-Forges, A., Feller, C., Jamagne, M., Arrouays, D. (2008) : Perdu dans le triangle des textures. Etude et Gestion des Sols 15, 97-111.

Van-Camp, L., Bujarrabal, B., Gentile, A.-R., Jones, R.J.A., Montanarella, L., Olazabal, C., Selvaradjou, S.-K. (2004): Reports of the technical working groups established under the thematic strategy for soil protection. Volume III. Organic matter and biodiversity. http://eusoils.jrc.ec.europa.eu/esdb_archive/Policies/STSWeb/Vol3.pdf. EUR 21319 EN/3, Office for Official Publications of the European Communities, Luxembourg, p. 195.