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Water modelling approaches and opportunities to simulate spatial water variations at crop field level

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  • Tenreiro, Tomás R.
  • García-Vila, Margarita
  • Gómez, José A.
  • Jimenez-Berni, José A.
  • Fereres, Elías

Abstract

Considerable spatial variability in soil hydraulic properties exists within a field, even in those considered homogeneous. Spatial variability of water as a major driver of crop heterogeneity gains particular relevance within the context of precision agriculture, but modelling has devoted insufficient efforts to scale up from point to field the associated ‘cause-effect’ relations of water spatial variations. Seven crop simulation models (WOFOST, DSSAT, APSIM, DAISY, STICS, AquaCrop and MONICA) and five hydrologic models (HYDRUS-1D, HYDRUS-2D, SWAP, MIKE-SHE and SWIM) were selected and their water modelling approaches were systematically reviewed for comparison. Crop models rely mainly on ‘discrete’ and empirical approaches for modelling soil water movement while hydrologic models emphasize more ‘continuous’ and mechanistic ones. Combining both types of models may not be the best way forward as none of the models consider all of the processes which are relevant for the simulation of spatial variations. Hydrologic models pay more attention to spatially variable water processes than crop simulation models, although their focus is on scales higher than the field which is the relevant scale for assessing the influence of such variations on crop behaviour. Opportunities for progress in the spatial simulation of water processes at field level will probably come from two different directions. One implying a stronger synergism between both model families by using continuous-type approaches to simulate some mechanisms in existing crop models, and the other through the integration of lateral flows in the simulation of discrete water movement approaches.

Suggested Citation

  • Tenreiro, Tomás R. & García-Vila, Margarita & Gómez, José A. & Jimenez-Berni, José A. & Fereres, Elías, 2020. "Water modelling approaches and opportunities to simulate spatial water variations at crop field level," Agricultural Water Management, Elsevier, vol. 240(C).
    • Handle: RePEc:eee:agiwat:v:240:y:2020:i:c:s0378377419321821
    DOI: 10.1016/j.agwat.2020.106254
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    1. Nendel, C. & Berg, M. & Kersebaum, K.C. & Mirschel, W. & Specka, X. & Wegehenkel, M. & Wenkel, K.O. & Wieland, R., 2011. "The MONICA model: Testing predictability for crop growth, soil moisture and nitrogen dynamics," Ecological Modelling, Elsevier, vol. 222(9), pages 1614-1625.
    2. Zwart, Sander J. & Bastiaanssen, Wim G.M., 2007. "SEBAL for detecting spatial variation of water productivity and scope for improvement in eight irrigated wheat systems," Agricultural Water Management, Elsevier, vol. 89(3), pages 287-296, May.
    3. Han, Congying & Zhang, Baozhong & Chen, He & Wei, Zheng & Liu, Yu, 2019. "Spatially distributed crop model based on remote sensing," Agricultural Water Management, Elsevier, vol. 218(C), pages 165-173.
    4. Zhou, Hong & Zhao, Wen zhi, 2019. "Modeling soil water balance and irrigation strategies in a flood-irrigated wheat-maize rotation system. A case in dry climate, China," Agricultural Water Management, Elsevier, vol. 221(C), pages 286-302.
    5. Hansen, J. W. & Jones, J. W., 2000. "Scaling-up crop models for climate variability applications," Agricultural Systems, Elsevier, vol. 65(1), pages 43-72, July.
    6. Mateos, Luciano & Lopez-Cortijo, Ignacio & Sagardoy, Juan A., 2002. "SIMIS: the FAO decision support system for irrigation scheme management," Agricultural Water Management, Elsevier, vol. 56(3), pages 193-206, August.
    7. Šimůnek, Jiří & Hopmans, Jan W., 2009. "Modeling compensated root water and nutrient uptake," Ecological Modelling, Elsevier, vol. 220(4), pages 505-521.
    8. Er-Raki, S. & Chehbouni, A. & Guemouria, N. & Duchemin, B. & Ezzahar, J. & Hadria, R., 2007. "Combining FAO-56 model and ground-based remote sensing to estimate water consumptions of wheat crops in a semi-arid region," Agricultural Water Management, Elsevier, vol. 87(1), pages 41-54, January.
    9. Passioura, J. B., 1983. "Roots and drought resistance," Agricultural Water Management, Elsevier, vol. 7(1-3), pages 265-280, September.
    10. Basso, B. & Ritchie, J. T. & Pierce, F. J. & Braga, R. P. & Jones, J. W., 2001. "Spatial validation of crop models for precision agriculture," Agricultural Systems, Elsevier, vol. 68(2), pages 97-112, May.
    11. Bouman, B. A. M. & van Keulen, H. & van Laar, H. H. & Rabbinge, R., 1996. "The `School of de Wit' crop growth simulation models: A pedigree and historical overview," Agricultural Systems, Elsevier, vol. 52(2-3), pages 171-198.
    Full references (including those not matched with items on IDEAS)

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