Rothamsted Landscape Model

The Rothamsted Landscape Model is a suite of interacting process-based modules that simulate soil processes, (including soil organic matter, soil nutrient and water dynamics), livestock production and crop growth and yield, including interactions with arable weeds. The model is spatially explicit with adjacent pieces of land (fields or watercourses) linked to simulate spatial movement of nutrients, water (and in the future pests).

The model components are based on well-established models such as RothC and LINTUL (as described in Coleman et al., 2017) but also include many new routines, for example (i) the production and emissions from dairy, based on work done by Misselbrook et al.) on the Defra funded project ‘Improvements to the UK Greenhouse Gas Inventory’ (ii) erosion, and (iii) a novel trait-based weed model (Metcalfe et al., 2019).

Notable capabilities include the ability to run UK based scenarios to simulate:

(i) Arable crop yields, emissions, and nutrient run-offs

(ii) Milk production from UK dairy sector and associated environmental impacts

(iii) The response of various weed species to crop management

(iv) Assess trade-offs between multiple objectives (for example production, soil-erosion and emissions)

The model has been coupled with a management optimisation system, that can be used to explore means to improve environmental outcomes from farming while maintaining or increasing production. The model is currently being used in a number of projects by Rothamsted and our collaborators.

OUR TEAM

PAPERS:

Sharp, R., Bellamy, A. S., Clear, A., Finnigan, S. M., Furness, E., Meador, E., Metcalfe, H., Mills, S., Coleman, K., Whitmore, A. P. and Milne, A. E. 2024. Implications and impacts of aligning regional agriculture with a healthy diet. Journal of Cleaner Production. 449, p. 141375. https://doi.org/10.1016/j.jclepro.2024.141375

Romero-Ruiz, A., O'Leary, D., Daly, E., Tuohy, P., Milne, A. E., Coleman, K. and Whitmore, A. P. 2024. An agrogeophysical modelling framework for the detection of soil compaction spatial variability due to grazing using field-scale electromagnetic induction data. Soil Use and Management. 40 (2), p. e13039. https://doi.org/10.1111/sum.13039

Metcalfe, H., Storkey, J., Hull, R. I., Bullock, J. M., Whitmore, A. P., Sharp, R. and Milne, A. E. 2023. Trade-offs constrain the success of glyphosate-free farming. Scientific Reports. 14, p. 8001. https://doi.org/10.1038/s41598-024-58183-8

Hassall, K. L., Coleman, K., Dixit, P., Granger, S. J., Zhang, Y., Sharp, R., Wu, L., Whitmore, A. P., Richter, G. M., Collins, A. L. and Milne, A. E. 2022. Exploring the effects of land management change on productivity, carbon and nutrient balance: Application of an Ensemble Modelling Approach to the upper River Taw observatory, UK. Science of the Total Environment. 824, p. 153824. https://doi.org/10.1016/j.scitotenv.2022.153824

Coleman, K., Whitmore, A. P., Hassall, K. L., Shield, I., Semenov, M. A., Dobermann, A., Bourhis, Y., Eskandary, A., and Milne, A. E. 2021. The potential for soybean to diversify the production of plant-based protein in the UK. Sci. Total Environ. 767:144903. https://doi.org/10.1016/j.scitotenv.2020.144903

Metcalfe, H., Milne., A.E., Delledale, F., Storkey, J. 2020. Using Functional Traits to Model Annual Plant Community Dynamics, Ecology, 101(11), e03167. https://doi.org/10.1002/ecy.3167

Milne, A.E., Coleman, K., Todman, L.C., Whitmore, A.P. 2020. Model-based optimisation of agricultural profitability and nutrient management: a practical approach for dealing with issues of scale. Environmental Monitoring and Assessment, 192:730. https://doi.org10.1007/s10661-020-08699-z

Todman LC, Coleman K, Milne AE, Gil JDB, Reidsma P, Schwoob M-H, et al. Multi-objective optimization as a tool to identify possibilities for future agricultural landscapes. Science of The Total Environment 2019; 687: 535-545, https://doi.org/10.1016/j.scitotenv.2019.06.070

Muhammed SE, Coleman K, Wu LH, Bell VA, Davies JAC, Quinton JN, et al. Impact of two centuries of intensive agriculture on soil carbon, nitrogen and phosphorus cycling in the UK. Science of the Total Environment 2018; 634: 1486-1504, https://doi.org/10.1016/j.scitotenv.2018.03.378

Coleman, K., Muhammed, S. E., Milne, A. E., Todman, L. C., Dailey, A. G., Glendining, M. J., and Whitmore, A. P. 2017. The landscape model: A model for exploring trade-offs between agricultural production and the environment. Sci. Total Environ. 609:1483-1499 https://doi.org/10.1016/j.scitotenv.2017.07.193