1. General Model Information

Name: PARCH: Predicting Arable Resource Capture in Hostile environments

Acronym: PARCH


Main medium: air+terrestrial
Main subject: biogeochemistry, hydrology, agriculture
Organization level: ecosystem
Type of model: ordinary differential equations
Main application:
Keywords: crop growth, sorghum, water balance, semi-arid tropics, water stress, light interception, nutrient uptake, growth limitations, stress response, stress index, mineral fertiliser, organic manure, nitrogen, phosphorus

Contact:

Dr. N.M.J. Crout
University of Nottingham
Institute of Environmental Sciences
Nottingham NG7 2RD
UK


Phone: 0115 951 6253
Fax:
email: neil.crout@nottingham.ac.uk
Homepage: http://www.nottingham.ac.uk/ies/staff/index.htm

Author(s):

T. Hess(2), W. Stephens(2), N.M.J. Crout(1), S.D. Young(1) and R.G. Bradley(1)

(1):
Physiology and Environmental Science
University of Nottingham,
Sutton Bonington,
LE12 5RD, UK

(2):
School of Agriculture Food and Environment,
Cranfield University,
Silsoe,
MK45 4DT, UK

Abstract:

PARCH is a model developed for simulating the growth of sorghum in harsh environments. Its development was suported over a number of years by the UKs Overseas Development Administration (as was, now renamed DfID) through programmes managed by the Natural Resources Institute (NRI).

The PARCH model consists of 4 main sub-models:

The model uses a daily time step for the simulation of crop growth. On each day, the resources of light, water and nutrients are `intercepted' or `extracted' and converted into assimilated dry matter. Depending upon the availability of these resources and the crop's ability to sequester them, its growth is considered as either light, water, or nutrient `limited'. An index of crop stress is calculated in terms of the ratio of light to water or nutrient limited growth. This stress index is then used to control a number of the crop's stress responses, such as leaf rolling or increased partitioning to roots. Partitioning of resources between crop organs is calculated by empirically derived fractions which are adjusted according to growth stage and level of stress. Resources partitioned to the leaf canopy and root system add to leaf area and root length thereby feeding back into subsequent calculations for light interception and water and nutrient uptake.

Although the model is general it has been developed for applications in the dry tropics and, to emphasise this, the model has the acronym PARCH (Predicting Arable Resource Capture in Hostile environments). Therefore considerable attention has been paid to the crop's water supply. A multi-layer water balance simulation is a key component of the model. This simulates vertical redistribution of soil water, infiltration, drainage and soil evaporation.

Within PARCH the influence of soil nitrogen supply on crop growth can be simulated. Nitrate is distributed vertically between the soil profile layers from where it is available for both leaching and crop uptake. The mineralisation and immobilisation of nitrogen by soil organic matter is modelled using approaches derived from the CERES models (Jones & Kiniry 1986). These account for the influence of soil moisture, temperature, and C:N ratio. Crop uptake is controlled by nitrogen availability within the soil, crop root distribution and crop nitrogen content. The crops response to nitrogen deficiency is simulated using a nitrogen stress index similar in principle to the water stress index. The model allows for the addition of nitrogen, either in the form of mineral fertiliser, or as an organic manure. In the case of manures it is necessary to define the characteristics of the manure.
Limitation by phosphate is also included although this is considered in less detail.

The model has been calibrated for four cultivars, CSH-6, CSH-8, M-35-1, and DK55 using data from 17 experiments selected from a larger dataset of 68 yield and 59 total biomass observations. The calibrated model has been tested against the remaining 51 yield and 42 biomass observations. Overall there is good agreement between the model and observation with the model accounting for >80% of the observed variation in crop yield and biomass with a residual standard deviation of 0.53 tha-1 for yield and 1.66 tha-1 for biomass The model shows no significant bias in prediction although there is a tendancy to underpredict yield. The model undoubtedly requires further testing of the model, in particular for situations of low yield.

A version of the model for rainwater harvesting has been developed at Newcastle University by Damion Young and co-workers: PARCHED-THIRST

A combination of the HYBRID tree/forest model with PARCH, named HyPAR (v.2.7), was developed by D. Mobbs et al. at the Institute of Terrestrial Ecology, UK, to model a simple, theoretical agroforestry system.

Sources of abstract:
Environmental Modelling at Nottingham University
Manual/User Guide/ Tutorial Download Page


II. Technical Information

II.1 Executables:

Operating System(s):

II.2 Source-code:

Programming Language(s): FORTRAN 77

II.3 Manuals:



II.4 Data:



III. Mathematical Information


III.1 Mathematics


III.2 Quantities


III.2.1 Input

III.2.2 Output


IV. References

Crout, N.M.J.; Young, S.D. and Bradley, R.G. 1997. PARCH - Technical Manual. Natural Resources Institute, Chatham, UK.
Hess, T. M.; Stephens, W.; Crout, N. M. J.; Young; S. D. and Bradley; R. G. 1997. PARCH - User Guide. Natural Resources Institute, Chatham, UK.
Stephens, W.; Hess, T. M.; Crout, N. M. J.; Young, S. D. and Bradley, R. G. 1997 PARCH - User Tutorial. Natural Resources Institute, Chatham, UK.
Mobbs, D.C.; Cannell, M.G.R.; Crout, N.M.J.; Lawson, G.J.; Friend, A.D.; Arah, J. 1998. Complementarity of light and water use in tropical agroforests I. Theoretical model outline, performance and sensitivity. Forest Ecology and Management.1998, 102: 2-3, 259-274; 40 ref..
Mobbs, D.C.; Crout, N.M.J.; Lawson, G.J.; Cannell, M.G.R.; Sinclair, F.L. (ed.); Lawson, G.J. 1997. Structure and applications of the HyPAR model. Special issue on agroforestry modelling: selected papers from a workshop held in Edinburgh, 28-30 May 1997. Agroforestry-Forum. 1997, 8: 2, 10-14; 6 ref..
Bradley, R. G., Crout, N. M. J. and Azam-Ali, S. N., 1996. PARCH: A model for the growth and yield of sorghum: 2. Validation of yield and biomass predictions. Submitted to J. Agric. Sci.
Fry, G.J.; Lungu, C. 1994. Assessing the benefits of interventions to improve soil moisture conditions using the PARCH Crop Environment Model. In: Land degradation: a challenge to agricultural production. Proceedings 5th Annual Scientific Conference, SADC-land and water management research programme, Harare, Zimbabwe, 10-14 October, 1994. 1996, 119-125; 8 ref..
Mahoo, H.; Gowing, J.W.; Hatibu, N.; Kayombo, B.; Ussiri, D.A.N.; Wyseure, G.C.L.; Young, M.D.B. 1995. A rainfall-runoff model for rain water harvesting design in Tanzania: comparison and validation of an empirical and a physical model. (THIRST, PARCHED THIRST) SACCAR-Newsletter.1995, No. 32, 1-9; 7 ref..
Lawson, G.J.; Crout, N.M.J.; Levy, P.E.; Mobbs, D.C.; Wallace, J.S.; Cannell, M.G.R.; Bradley, R.G.; Sinclair, F. 1995. The tree-crop interface: representation by coupling of forest and crop process-models. Agroforestry: science, policy and practice.Selected papers from the agroforestry sessions of the IUFRO 20th World Congress, Tampere, Finland, 6-12 August, 1995. Agroforestry-Systems. 1995, 30: 1-2, 199-221; 29 ref..
Daamen, C.C. & Simmonds, L.P. 1995. Soil Water, Energy And Transpiration (SWEAT). A numerical model of water and energy fluxes in soil profiles and sparse canopies . Department of Soil Science, University of Reading, UK.
Azam-Ali, S. N.; Crout, N.M.J.; Bradley, R.G. 1994. Some Perspectives in Modelling Resource Capture by Crops. Proceedings of 52nd Easter School in Agricultural Science, Sutton Bonington, UK.
Hammer, G.L. & Muchow, R.C.1994. Assessing climatic risk to sorghum production in water-limited subtropical environments. I. Development and testing of a simulation model. Field Crops Research 23: 221-237.
Maas, S.J. 1993a. Agroclimatology and Modelling. Parameterized Model of Gramineous Crop Growth: I. Leaf Area and Dry Mass Simulation. Agron. J, 85: 348-353.
Evett, S.R. & Lascano R.J. 1993. ENWATBAL.BAS: A Mechanistic Evapotranspiration Model Written in Compiled Basic. Agron. J., 85: 763-772.
Berge, H.F.M. ten.; Jansen, D.M.; Rappoldt, K. and Stol, W. 1992. The soil water balance module SAWAH: description and users guide. Simulation Reports CABO-TT, no.22. DLO-Centre for Agrobi. Research & Dept of Theor. Prod. Ecology, Wageningen Agriicultural Uni, 78p.
Laar, H.H. Van; Goudriaan, J. & Keulen, H. Van (Eds.) 1992. Simulation of crop growth for potential and water-limited production situations (as applied to spring wheat). Simulation Report CABO-TT no.23. Centre for Agrobi. Research (CABO) & Dept of Theor. Prod. Ecology. Wageningen Uni.
Keating, B.A. & Wafula,B. M. 1992. Modelling the fully Expanded Area of Maize Leaves. Field Crops Research , 29: 163-176.
Carberry, P.S. & Abrecht, D.G. 1991. Tailoring crop models to the Semiarid Tropics. In Climatic risk in crop production: Models and management for the Semiarid Tropics and Subtropics. (Eds. R C Muchow & J A Bellamy). C.A.B. International, Wallingford, Oxon, UK. pp. 157-182.
Jarvis, N.J.; Bergström, L. & Dik, P.E. 1991a. Modelling Water and Solute Transport in Macroporous Soil. I. Model Description and Sensitivity Analysis. Journal of Soil Science, 42: 59-70.
Jarvis, N.J.; Bergström, L. & Dik, P.E. 1991b. Modelling Water and Solute Transport in Macroporous Soil. II. Chloride Breakthrough under Non-Steady Flow. Journal of Soil Science, 42: 71-81.
Muchow, R.C. & Bellamy, J.A. (eds.) 1991. Climatic risk in crop production: Models and management for the Semiarid Tropics and Subtropics. C.A.B. International, Wallingford, Oxon, UK
Hammer, G.L. & Muchow, R.C. 1991. Quantifying climatic risk to sorghum in Australia's semiarid tropics and subtropics: model development and simulation. In Climatic risk in crop production: Models and management for the Semiarid Tropics and Subtropics. (Eds. R C Muchow & J A Bellamy). C.A.B. International, Wallingford, Oxon, UK. pp. 329-358.
Grant, R.F. 1991. The distribution of water and nitrogen in the soil-crop system: a simulation study with validation from a winter wheat field trial. Fertilizer Research, 27: 199-213.
Hansen, S.; Jensen, N.E.; Nielsen, N.E. & Svendsen, H. 1991. Simulation of nitrogen dynamics and biomass production in winter wheat using the Danish simulation model DAISY. Fertilizer Research, 27: 245-259.
Penning de Vries, F.W.T. & Spitters, C.J.T. 1991. The potential for improvement in crop yield simulation. In Climatic risk in crop production: Models and management for the Semiarid Tropics and Subtropics. (Eds. R C Muchow & J A Bellamy). C.A.B. International, Wallingford, Oxon, UK. pp. 123-140.
Ritchie, J.T. 1991. Specifications of the ideal model for predicting crop yields. In Climatic risk in crop production: Models and management for the Semiarid Tropics and Subtropics. (Eds. R C Muchow & J A Bellamy). C.A.B. International, Wallingford, Oxon, UK. pp. 97-122.
Birch, C.J.; Carberry, P.S.; Muchow, R.C.; McCown, R.L. & Hargreaves, J.N.G. 1990. Development and Evaluation of a Sorghum Model Based on CERES-Maize in a Semi-Arid Tropical Environment. Field Crops Research, 24: 87-104. Elsevier Science Publishers BV, Amsterdam.
Muchow, R.C. & Carberry, P.S. 1990. Phenology and Leaf-Area Development in a Tropical Grain Sorghum. Field Crops Research , 23: 221-237. Elsevier Science Publishers BV, Amsterdam
Erenstein, O. 1990. Simulation of water-limited yields of sorghum, millet and cowpea for the 5th region of Mali in the framework of quantitative land evaluation. Department of Theoretical Production Ecology, Ag. Uni. Wageningen.
Montheit, J.L.; Huda, A.K.S. & Midya, D. 1989. RESCAP: A resource capture model for sorghum and pearl millet. In Modelling the growth and development of sorghum and pearl millet. (Eds. Virmani, S.M., Tandon, H.L.S. & Alagarswamy, G.). ICRISAT Research Bulletin 12, Patancheru, India. pp. 30-34.
Montheit, J.L. 1994. Principles of Resource Capture by Crop Stands. Proceedings of 52nd Easter School in Agricultural Science, Sutton Bonington, UK. (Ed. J L Monteith, R K Scott & M H Unsworth). Nottingham University Press. pp. 1-16.
Rosenthal, W.D.; Vanderlip, R.L.; Jackson, B.S. & Arkin, G.F. 1989. SORKHAM: A Grain Sorghum Crop Growth Model. Texas Agricultural Experiment Station Computer Software Documentation Series MP 1669, College Station.
Muchow, R.C. & Davis, R. 1988. Effect of Nitrogen Supply on the Comparative Productivity of Maize and Sorghum in a Semi-Arid Tropical Environment. II. Radiation Interception and Biomass Accumulation. Field Crops Research , 18: 17-30. Elsevier Science Publishers BV, Amsterdam.
Gregson, K.; Hector, D.J. & McGowan, M. 1987. A one-parameter model for the soil water characteristic. University of Nottingham, Sutton Bonington Campus, Leicester, LE12 5RD. Journal of Soil Science, 38: 483-486.
Muchow, R.C. & Coates, D.B. 1986. An Analysis of the Environmental Limitation to Yield of Irrigated Grain Sorghum During the Dry Season in Tropical Australia Using a Radiation Interception Model. Aust. J. Agric. Res., 37: 135-148.
Jones, C.A. & Kiniry, J.R. 1986. CERES-Maize: A simulation model of maize growth and development. Texas A&M University press, College Station, Texas, 194 pp.
Jones, C.A.; Cole, C.V.; Sharpley, A.N. & Williams, J.R. 1984. A simplified soil and plant phosphorus model: I. Documentation. Soil. Science Soc. Am. J., 48:800-805
Jones, C.A.; Cole, C.V.; Sharpley, A.N. & Williams, J.R. 1984. A simplified soil and plant phosphorus model: III. Testing. Soil. Science Soc. Am. J., 48:810-813
Williams, J.R., Jones, C.A. & Dyke, P.T. 1984. A modeling approach to determining the relationship between erosion and soil productivity. Trans ASAE 27:129-144.


V. Further information in the World-Wide-Web


VI. Additional remarks


Last review of this document by: J. Bierwirth Thu Mar 15 2001

Status of the document:
last modified by Tobias Gabele Wed Aug 21 21:44:47 CEST 2002

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